diff --git a/.nojekyll b/.nojekyll new file mode 100644 index 0000000..e69de29 diff --git a/api/cassini_iss.html b/api/cassini_iss.html new file mode 100644 index 0000000..493ca8d --- /dev/null +++ b/api/cassini_iss.html @@ -0,0 +1,824 @@ + + + + + + + + + + +planetarypy - Cassini ISS + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Cassini ISS

+
+ +
+
+ Data getters for Cassini ISS image data +
+
+ + +
+ + + + +
+ + +
+ + +
+
storage_root
+
+
Path('/Users/maye/planetarypy_data/missions/cassini/iss')
+
+
+
+

source

+
+

DataRetriever

+
+
 DataRetriever (pid)
+
+

Initialize self. See help(type(self)) for accurate signature.

+ + + + + + + + + + + + + +
Details
pidPDS product_id, e.g. N1454725799
+
+
pid = "N1454725799"
+
+
+
dm = DataRetriever(pid)
+
+
+
dm.raw_fname
+
+
'N1454725799_1.IMG'
+
+
+
+
dm.raw_data_url
+
+
URL('https://opus.pds-rings.seti.org/holdings/volumes/COISS_2xxx/COISS_2001/data/1454725799_1455008789/N1454725799_1.IMG')
+
+
+
+
dm.raw_label_url
+
+
URL('https://opus.pds-rings.seti.org/holdings/volumes/COISS_2xxx/COISS_2001/data/1454725799_1455008789/N1454725799_1.LBL')
+
+
+
+
dm.raw_prefix_fmt_url
+
+
URL('https://opus.pds-rings.seti.org/holdings/volumes/COISS_2xxx/COISS_2001/label/prefix2.fmt')
+
+
+
+
dm.raw_tlmtab_url
+
+
URL('https://opus.pds-rings.seti.org/holdings/volumes/COISS_2xxx/COISS_2001/label/tlmtab.fmt')
+
+
+
+
dm.calib_data_url
+
+
URL('https://opus.pds-rings.seti.org/holdings/calibrated/COISS_2xxx/COISS_2001/data/1454725799_1455008789/N1454725799_1_CALIB.IMG')
+
+
+
+

source

+
+
+

ISS

+
+
 ISS (pid)
+
+

Initialize self. See help(type(self)) for accurate signature.

+
+
id = "N1874681996"
+id = "N1454725799"
+# id = "N1878581142"
+
+
+
list(storage_root.rglob(f"{id}*"))
+
+
[Path('/Users/maye/planetarypy_data/missions/cassini/iss/N1454725799'),
+ Path('/Users/maye/planetarypy_data/missions/cassini/iss/N1454725799/N1454725799_1_CALIB.IMG')]
+
+
+
+
iss = ISS(pid)
+
+
Found 1 obsids.
+
+
+
+
iss.local_folder
+
+
Path('/Users/maye/planetarypy_data/missions/cassini/iss/N1454725799')
+
+
+
+
iss.raw_data_url
+
+
URL('https://opus.pds-rings.seti.org/holdings/volumes/COISS_2xxx/COISS_2001/data/1454725799_1455008789/N1454725799_1.IMG')
+
+
+
+
iss.raw_tlmtab_url
+
+
URL('https://opus.pds-rings.seti.org/holdings/volumes/COISS_2xxx/COISS_2001/label/tlmtab.fmt')
+
+
+
+
iss.download_calib()
+
+
File exists. Use `overwrite` to force re-download.
+
+
+
+
config.storage_root
+
+
Path('/Users/maye/planetarypy_data')
+
+
+
+
iss.dict.keys()
+
+
dict_keys(['coiss_raw', 'coiss_calib', 'coiss_thumb', 'coiss_medium', 'coiss_full', 'coiss_documentation', 'rms_index', 'inventory', 'planet_geometry', 'moon_geometry', 'ring_geometry', 'browse_thumb', 'browse_small', 'browse_medium', 'browse_full'])
+
+
+
+
iss.local_calib_path
+
+
Path('/Users/maye/planetarypy_data/missions/cassini/iss/N1454725799/N1454725799_1_CALIB.IMG')
+
+
+
+
iss.calib_data_url
+
+
URL('https://opus.pds-rings.seti.org/holdings/calibrated/COISS_2xxx/COISS_2001/data/1454725799_1455008789/N1454725799_1_CALIB.IMG')
+
+
+
+
dm.calib_data_url
+
+
URL('https://opus.pds-rings.seti.org/holdings/calibrated/COISS_2xxx/COISS_2001/data/1454725799_1455008789/N1454725799_1_CALIB.IMG')
+
+
+
+
iss.raw_data_url
+
+
URL('https://opus.pds-rings.seti.org/holdings/volumes/COISS_2xxx/COISS_2001/data/1454725799_1455008789/N1454725799_1.IMG')
+
+
+
+
iss.volume
+
+
'COISS_2001'
+
+
+
+
iss.local_folder
+
+
Path('/Users/maye/planetarypy_data/missions/cassini/iss/N1454725799')
+
+
+
+
def get_raw_data_path(product_id):
+    iss = ISS(product_id)
+    return iss.local_data_path
+
+
+
id
+
+
'N1454725799'
+
+
+
+
list(storage_root.glob(f"**/{id}"))
+
+
[Path('/Users/maye/planetarypy_data/missions/cassini/iss/N1454725799')]
+
+
+
+
storage_root
+
+
Path('/Users/maye/planetarypy_data/missions/cassini/iss')
+
+
+
+
!ls {storage_root}
+
+
N1454725799/ N1874681996/ indexes/
+
+
+
+
get_raw_data_path(id)
+
+
Found 1 obsids.
+
+
+
Path('/Users/maye/planetarypy_data/missions/cassini/iss/N1454725799/N1454725799_1.IMG')
+
+
+
+
iss.dict
+
+
{'coiss_raw': ['https://opus.pds-rings.seti.org/holdings/volumes/COISS_2xxx/COISS_2001/data/1454725799_1455008789/N1454725799_1.IMG',
+  'https://opus.pds-rings.seti.org/holdings/volumes/COISS_2xxx/COISS_2001/data/1454725799_1455008789/N1454725799_1.LBL',
+  'https://opus.pds-rings.seti.org/holdings/volumes/COISS_2xxx/COISS_2001/label/prefix2.fmt',
+  'https://opus.pds-rings.seti.org/holdings/volumes/COISS_2xxx/COISS_2001/label/tlmtab.fmt'],
+ 'coiss_calib': ['https://opus.pds-rings.seti.org/holdings/calibrated/COISS_2xxx/COISS_2001/data/1454725799_1455008789/N1454725799_1_CALIB.IMG',
+  'https://opus.pds-rings.seti.org/holdings/calibrated/COISS_2xxx/COISS_2001/data/1454725799_1455008789/N1454725799_1_CALIB.LBL'],
+ 'coiss_thumb': ['https://opus.pds-rings.seti.org/holdings/volumes/COISS_2xxx/COISS_2001/extras/thumbnail/1454725799_1455008789/N1454725799_1.IMG.jpeg_small'],
+ 'coiss_medium': ['https://opus.pds-rings.seti.org/holdings/volumes/COISS_2xxx/COISS_2001/extras/browse/1454725799_1455008789/N1454725799_1.IMG.jpeg'],
+ 'coiss_full': ['https://opus.pds-rings.seti.org/holdings/volumes/COISS_2xxx/COISS_2001/extras/full/1454725799_1455008789/N1454725799_1.IMG.png'],
+ 'coiss_documentation': ['https://opus.pds-rings.seti.org/holdings/documents/COISS_0xxx/VICAR-File-Format.pdf',
+  'https://opus.pds-rings.seti.org/holdings/documents/COISS_0xxx/ISS-Users-Guide.pdf',
+  'https://opus.pds-rings.seti.org/holdings/documents/COISS_0xxx/ISS-Users-Guide.docx',
+  'https://opus.pds-rings.seti.org/holdings/documents/COISS_0xxx/Data-Product-SIS.txt',
+  'https://opus.pds-rings.seti.org/holdings/documents/COISS_0xxx/Data-Product-SIS.pdf',
+  'https://opus.pds-rings.seti.org/holdings/documents/COISS_0xxx/Cassini-ISS-Final-Report.pdf',
+  'https://opus.pds-rings.seti.org/holdings/documents/COISS_0xxx/Calibration-Theoretical-Basis.pdf',
+  'https://opus.pds-rings.seti.org/holdings/documents/COISS_0xxx/Calibration-Plan.pdf',
+  'https://opus.pds-rings.seti.org/holdings/documents/COISS_0xxx/CISSCAL-Users-Guide.pdf',
+  'https://opus.pds-rings.seti.org/holdings/documents/COISS_0xxx/Archive-SIS.txt',
+  'https://opus.pds-rings.seti.org/holdings/documents/COISS_0xxx/Archive-SIS.pdf'],
+ 'rms_index': ['https://opus.pds-rings.seti.org/holdings/metadata/COISS_2xxx/COISS_2001/COISS_2001_index.tab',
+  'https://opus.pds-rings.seti.org/holdings/metadata/COISS_2xxx/COISS_2001/COISS_2001_index.lbl'],
+ 'inventory': ['https://opus.pds-rings.seti.org/holdings/metadata/COISS_2xxx/COISS_2001/COISS_2001_inventory.csv',
+  'https://opus.pds-rings.seti.org/holdings/metadata/COISS_2xxx/COISS_2001/COISS_2001_inventory.lbl'],
+ 'planet_geometry': ['https://opus.pds-rings.seti.org/holdings/metadata/COISS_2xxx/COISS_2001/COISS_2001_saturn_summary.tab',
+  'https://opus.pds-rings.seti.org/holdings/metadata/COISS_2xxx/COISS_2001/COISS_2001_saturn_summary.lbl'],
+ 'moon_geometry': ['https://opus.pds-rings.seti.org/holdings/metadata/COISS_2xxx/COISS_2001/COISS_2001_moon_summary.tab',
+  'https://opus.pds-rings.seti.org/holdings/metadata/COISS_2xxx/COISS_2001/COISS_2001_moon_summary.lbl'],
+ 'ring_geometry': ['https://opus.pds-rings.seti.org/holdings/metadata/COISS_2xxx/COISS_2001/COISS_2001_ring_summary.tab',
+  'https://opus.pds-rings.seti.org/holdings/metadata/COISS_2xxx/COISS_2001/COISS_2001_ring_summary.lbl'],
+ 'browse_thumb': ['https://opus.pds-rings.seti.org/holdings/previews/COISS_2xxx/COISS_2001/data/1454725799_1455008789/N1454725799_1_thumb.jpg'],
+ 'browse_small': ['https://opus.pds-rings.seti.org/holdings/previews/COISS_2xxx/COISS_2001/data/1454725799_1455008789/N1454725799_1_small.jpg'],
+ 'browse_medium': ['https://opus.pds-rings.seti.org/holdings/previews/COISS_2xxx/COISS_2001/data/1454725799_1455008789/N1454725799_1_med.jpg'],
+ 'browse_full': ['https://opus.pds-rings.seti.org/holdings/previews/COISS_2xxx/COISS_2001/data/1454725799_1455008789/N1454725799_1_full.png']}
+
+
+ + +
+ +
+ +
+ + + + \ No newline at end of file diff --git a/api/cassini_uvis.html b/api/cassini_uvis.html new file mode 100644 index 0000000..578bf78 --- /dev/null +++ b/api/cassini_uvis.html @@ -0,0 +1,1019 @@ + + + + + + + + + + +planetarypy - UVIS + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

UVIS

+
+ +
+
+ Data management for Cassini UVIS. +
+
+ + +
+ + + + +
+ + +
+ + +
+
get_index("cassini.uvis", "index")
+
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
FILE_NAMEOBSERVATION_TYPESTART_TIMESTOP_TIMETARGET_NAMEDATA_SET_IDSPACECRAFT_CLOCK_START_COUNTSPACECRAFT_CLOCK_STOP_COUNTINTEGRATION_DURATIONCOMPRESSION_TYPE...SUB_SOLAR_LONGITUDESUB_SPACECRAFT_LATITUDESUB_SPACECRAFT_LONGITUDEPHASE_ANGLEEMISSION_ANGLESOLAR_INCIDENCE_ANGLECENTRAL_BODY_DISTANCEDWELL_TIMEH_LEVELD_LEVEL
0/COUVIS_0001/DATA/D1999_007/EUV1999_007_17_05.LBLUSTARE1999-01-07 17:05:01.9491999-01-07 17:08:37.949<NA>CO-J-UVIS-2-SPEC-V1.21/1294420183.000UNK4.0NONE...-999.0-999.0-999.0-999.0-999.0-999-999.0-999<NA><NA>
1/COUVIS_0001/DATA/D1999_007/EUV1999_007_17_08.LBLUSTARE1999-01-07 17:08:51.9471999-01-07 17:12:27.947<NA>CO-J-UVIS-2-SPEC-V1.21/1294420413.000UNK4.0NONE...-999.0-999.0-999.0-999.0-999.0-999-999.0-999<NA><NA>
2/COUVIS_0001/DATA/D1999_007/FUV1999_007_16_57.LBLUSTARE1999-01-07 16:57:21.9521999-01-07 17:00:57.952<NA>CO-J-UVIS-2-SPEC-V1.21/1294419723.000UNK4.0NONE...-999.0-999.0-999.0-999.0-999.0-999-999.0-999<NA><NA>
3/COUVIS_0001/DATA/D1999_007/FUV1999_007_17_01.LBLUSTARE1999-01-07 17:01:11.9501999-01-07 17:04:47.950<NA>CO-J-UVIS-2-SPEC-V1.21/1294419953.000UNK4.0NONE...-999.0-999.0-999.0-999.0-999.0-999-999.0-999<NA><NA>
4/COUVIS_0001/DATA/D1999_007/HDAC1999_007_16_31...UHDAC1999-01-07 16:31:07.9621999-01-07 16:31:11.962<NA>CO-J-UVIS-2-SSB-V1.21/1294418149.000UNK-999.0NONE...-999.0-999.0-999.0-999.0-999.0-999-999.01(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0)(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0)
..................................................................
203240/COUVIS_0060/DATA/D2017_258/FUV2017_258_04_31.LBL<NA>2017-09-15 04:31:53.0052017-09-15 09:04:56.755SOLAR WINDCO-S-UVIS-2-CUBE-V1.41/1884145299.160UNK8191.875SQRT_9...-999.0-999.0-999.0-999.0-999.0-999-999.0-999<NA><NA>
203241/COUVIS_0060/DATA/D2017_258/FUV2017_258_07_00.LBL<NA>2017-09-15 07:00:27.6972017-09-15 07:13:40.447SOLAR WINDCO-S-UVIS-2-SPEC-V1.41/1884154214.096UNK2.625SQRT_9...-999.0-999.0-999.0-999.0-999.0-999-999.0-999<NA><NA>
203242/COUVIS_0060/DATA/D2017_258/FUV2017_258_07_15.LBL<NA>2017-09-15 07:15:04.4422017-09-15 10:31:51.692SOLAR WINDCO-S-UVIS-2-SPEC-V1.41/1884155091.032UNK2.625SQRT_9...-999.0-999.0-999.0-999.0-999.0-999-999.0-999<NA><NA>
203243/COUVIS_0060/DATA/D2017_258/HDAC2017_258_02_14...<NA>2017-09-15 02:14:02.4332017-09-15 02:14:06.433SOLAR WINDCO-S-UVIS-2-SSB-V1.41/1884137029.000UNK-999.0NONE...-999.0-999.0-999.0-999.0-999.0-999-999.01(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0)(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0)
203244/COUVIS_0060/DATA/D2017_258/HDAC2017_258_02_15...<NA>2017-09-15 02:15:25.0582017-09-15 02:17:33.058SOLAR WINDCO-S-UVIS-2-SSB-V1.41/1884137111.160UNK-999.0NONE...-999.0-999.0-999.0-999.0-999.0-999-999.032(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0)(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0)
+ +

203245 rows × 28 columns

+
+
+
+
+

source

+
+

DataManager

+
+
 DataManager (pid:str, skip_download:bool=False)
+
+

Initialize self. See help(type(self)) for accurate signature.

+ ++++++ + + + + + + + + + + + + + + + + + + + + + + +
TypeDefaultDetails
pidstrProduct ID. If longer than PDS_ID, will be cut in attribute pds_id
skip_downloadboolFalseskip trying to download
+
+
pid = "EUV2002_198_03_26_54_UVIS_C33ST_SPICARAST002_PRIME"
+
+
+
dm = DataManager(pid)
+
+
+
dm.raw_label_url
+
+
URL('https://opus.pds-rings.seti.org/holdings/volumes/COUVIS_0xxx/COUVIS_0004/DATA/D2002_198/EUV2002_198_03_26.LBL')
+
+
+
+
assert dm.pid == pid
+
+

PDS data is only stored under the first 17 characters of any UVIS-internal product id.

+
+
assert dm.pds_id == pid[:17]
+
+

The originally used product ID pid will be stored under original_pid.txt in the data folder:

+
+
dm.original_pid_file
+
+
Path('/home/ayek72/mnt/slowdata/planetarypy/missions/cassini/uvis/EUV2002_198_03_26/original_pid.txt')
+
+
+

The OPUS result file will be stored as a TOML file:

+
+
dm.results_file
+
+
Path('/home/ayek72/mnt/slowdata/planetarypy/missions/cassini/uvis/EUV2002_198_03_26/urls.toml')
+
+
+
+
dm.download(overwrite=False)
+
+
Local files exists. Use `overwrite=True` to download fresh.
+
+
+
+
dm.raw_data_path
+
+
Path('/home/ayek72/mnt/slowdata/planetarypy/missions/cassini/uvis/EUV2002_198_03_26/EUV2002_198_03_26.DAT')
+
+
+
+
dm.calib_corr_path
+
+
Path('/home/ayek72/mnt/slowdata/planetarypy/missions/cassini/uvis/EUV2002_198_03_26/EUV2002_198_03_26_CAL_3.DAT')
+
+
+
+

source

+
+
+

get_label_path

+
+
 get_label_path (pid)
+
+
+

source

+
+
+

get_data_path

+
+
 get_data_path (pid, skip_download=False)
+
+
+
get_data_path(pid)
+
+
Path('/home/ayek72/mnt/slowdata/planetarypy/missions/cassini/uvis/EUV2002_198_03_26/EUV2002_198_03_26.DAT')
+
+
+
+
get_label_path(pid)
+
+
Path('/home/ayek72/mnt/slowdata/planetarypy/missions/cassini/uvis/EUV2002_198_03_26/EUV2002_198_03_26.LBL')
+
+
+
+

source

+
+
+

get_user_guide

+
+
 get_user_guide ()
+
+
+
get_user_guide()
+
+
Path('/home/ayek72/mnt/slowdata/planetarypy/missions/cassini/uvis/uvis_user_guide.pdf')
+
+
+ + +
+ +
+ +
+ + + + \ No newline at end of file diff --git a/api/config.html b/api/config.html new file mode 100644 index 0000000..c04d0ae --- /dev/null +++ b/api/config.html @@ -0,0 +1,845 @@ + + + + + + + + + + +planetarypy - Config + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Config

+
+ +
+
+ This module manages configuration of the planetarypy package. +
+
+ + +
+ + + + +
+ + +
+ + +
+

source

+
+

reset_non_urls

+
+
 reset_non_urls (source:dict, reset:str='')
+
+

Reset all non-URL values in the config file.

+

This is useful for copying the private config file with new data items back into the source tree for a clean commit.

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
TypeDefaultDetails
sourcedictsource dictionary
resetstrvalue to reset non URLs to
Returnsdict
+
+

source

+
+
+

Config

+
+
 Config (config_path:str=None)
+
+

Manage config stuff.

+

The key, value pairs found in the config file become attributes of the class instance after initialization. At minimum, there should be the storage_root attribute for storing data for this package.

+ + + + + + + + + + + + + + + + + +
TypeDefaultDetails
config_pathstrNonestr or pathlib.Path
+
+
+

The Config() object

+

The config module instantiates a config object from the Config class. Its attributes can be used to access several aspects relevant to the configuration of planetarypy. Using an object approach enables easy growth and nesting over time.

+
+
config = Config(config_path="test_config.toml")
+
+
+
assert config.storage_root == Path.home() / "planetarypy_data"
+
+
+

source

+
+

Config.get_value

+
+
 Config.get_value (key:str)
+
+

Get sub-dictionary by nested key.

+ +++++ + + + + + + + + + + + + + + + + + + + +
TypeDetails
keystrA nested key in dotted format, e.g. cassini.uvis.indexes
ReturnsstrReturning empty string if not existing, because Path(’’) is False which is handy (e.g. in ctx mod.)
+
+
config.list_indexes("mro.hirise")
+
+
['dtm', 'edr', 'rdr']
+
+
+
+
index = "missions.cassini.iss.indexes.moon_summary"
+
+
+
config.get_value(index)['url']
+
+
'https://pds-rings.seti.org/holdings/metadata/COISS_2xxx/COISS_2999/COISS_2999_moon_summary.lbl'
+
+
+
+

source

+
+
+

Config.set_value

+
+
 Config.set_value (nested_key:str, value:Union[float,str], save:bool=True)
+
+

Set value in sub-dic using dotted key.

+ ++++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
TypeDefaultDetails
nested_keystrA nested key in dotted format, e.g. cassini.uvis.ring_summary
valueUnionValue for the given key to be stored
saveboolTrueSwitch to control writing out to disk
+
+

source

+
+
+

Config.save

+
+
 Config.save ()
+
+

Write the TOML doc to file.

+
+
config.get_value(index)['url']
+
+
'https://pds-rings.seti.org/holdings/metadata/COISS_2xxx/COISS_2999/COISS_2999_moon_summary.lbl'
+
+
+
+
config.get_value("mro.ctx.datalevels")['edr']['url']
+
+
'https://pds-imaging.jpl.nasa.gov/data/mro/mars_reconnaissance_orbiter/ctx'
+
+
+
+

source

+
+
+

Config.ask_storage_root

+
+
 Config.ask_storage_root ()
+
+

Use input() to ask user for the storage_root path.

+

The path will be stored in the TOML-dict and saved into existing config file at Class.path, either default or as given during init. storage_root attribute is set as well.

+
+
config.missions
+
+
['cassini', 'mro', 'lro', 'go']
+
+
+
+
assert config.path.name == '.planetarypy_config.toml'
+
+
+
config.list_instruments("cassini")
+
+
['iss', 'uvis']
+
+
+
+
config.list_indexes("cassini.iss")
+
+
['index', 'inventory', 'moon_summary', 'ring_summary', 'saturn_summary']
+
+
+
+

source

+
+
+

Config.get_datalevels

+
+
 Config.get_datalevels (mission_instrument)
+
+

Return configured data levels available for an instrument.

+

This currently simply points to the indexes, assuming that everything that has an index is also its own datalevel. In case it ever is not, we can add more here.

+ + + + + + + + + + + + + +
Details
mission_instrumentmission.instrument code, e.g. mro.hirise
+
+
config.get_datalevels("mro.hirise")
+
+
['dtm', 'edr', 'rdr']
+
+
+
+
from nbdev import nbdev_export
+
+nbdev_export()
+
+ + +
+
+ +
+ +
+ + + + \ No newline at end of file diff --git a/api/ctx.html b/api/ctx.html new file mode 100644 index 0000000..79bdb3f --- /dev/null +++ b/api/ctx.html @@ -0,0 +1,3067 @@ + + + + + + + + + + +planetarypy - CTX + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

CTX

+
+ +
+
+ Utils for working with MRO CTX data +
+
+ + +
+ + + + +
+ + +
+ + +
+
import pandas as pd
+
+pd.set_option("display.max_columns", 1000)
+
+
+

source

+
+

get_edr_index

+
+
 get_edr_index (refresh=False)
+
+
+
get_edr_index(False)
+
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
VOLUME_IDFILE_SPECIFICATION_NAMEORIGINAL_PRODUCT_IDPRODUCT_IDIMAGE_TIMEINSTRUMENT_IDINSTRUMENT_MODE_IDLINE_SAMPLESLINESSPATIAL_SUMMINGSCALED_PIXEL_WIDTHPIXEL_ASPECT_RATIOEMISSION_ANGLEINCIDENCE_ANGLEPHASE_ANGLECENTER_LONGITUDECENTER_LATITUDEUPPER_LEFT_LONGITUDEUPPER_LEFT_LATITUDEUPPER_RIGHT_LONGITUDEUPPER_RIGHT_LATITUDELOWER_LEFT_LONGITUDELOWER_LEFT_LATITUDELOWER_RIGHT_LONGITUDELOWER_RIGHT_LATITUDEMISSION_PHASE_NAMETARGET_NAMESPACECRAFT_CLOCK_START_COUNTFOCAL_PLANE_TEMPERATURELINE_EXPOSURE_DURATIONOFFSET_MODE_IDSAMPLE_FIRST_PIXELSCALED_IMAGE_WIDTHSCALED_IMAGE_HEIGHTSPACECRAFT_ALTITUDETARGET_CENTER_DISTANCESLANT_DISTANCEUSAGE_NOTENORTH_AZIMUTHSUB_SOLAR_AZIMUTHSUB_SOLAR_LONGITUDESUB_SOLAR_LATITUDESUB_SPACECRAFT_LONGITUDESUB_SPACECRAFT_LATITUDESOLAR_DISTANCESOLAR_LONGITUDELOCAL_TIMEIMAGE_SKEW_ANGLERATIONALE_DESCDATA_QUALITY_DESCORBIT_NUMBERshort_pidmonth_col
0MROX_0001DATA/CRU_000001_9999_XN_99N999W.IMG4A_04_0001000400CRU_000001_9999_XN_99N999W2005-08-30 15:40:21.549CTXNIFL5056102410.00.0999.9999.9999.9999.9999.9999.9999.9999.9999.9999.9999.9999.9999.9CRUISESPACE0809883639:076283.310.0194/53/5300.00.00.00.00.0N0.00.00.00.00.00.00.0278.8910.160.0Instrument checkout image of spaceOK-4242CRU_000001_9999CRU
1MROX_0001DATA/CRU_000002_9999_XN_99N999W.IMG4A_04_0001000500CRU_000002_9999_XN_99N999W2005-09-08 15:59:45.313CTXNIFL50561536010.00.0999.9999.9999.9999.9999.9999.9999.9999.9999.9999.9999.9999.9999.9CRUISEMOON0810662403:012296.05.71196/243/23800.00.00.00.00.0N0.00.00.00.00.00.00.0284.484.60.0Calibration image of the MoonOK-4126CRU_000002_9999CRU
2MROX_0001DATA/CRU_000003_9999_XN_99N999W.IMG4A_04_0001000600CRU_000003_9999_XN_99N999W2005-09-08 16:03:37.927CTXNIFL5056204810.00.0999.9999.9999.9999.9999.9999.9999.9999.9999.9999.9999.9999.9999.9CRUISESTAR0810662635:169296.622.9196/243/23800.00.00.00.00.0N0.00.00.00.00.00.00.0284.484.660.0Calibration image of Omega Centauri (globular ...OK-4126CRU_000003_9999CRU
3MROX_0001DATA/CRU_000004_9999_XN_99N999W.IMG4A_04_0001000700CRU_000004_9999_XN_99N999W2005-09-08 16:08:23.841CTXNIFL5056204810.00.0999.9999.9999.9999.9999.9999.9999.9999.9999.9999.9999.9999.9999.9CRUISESTAR0810662921:147296.822.9196/243/23800.00.00.00.00.0N0.00.00.00.00.00.00.0284.484.740.0Calibration image of Omega Centauri (globular ...OK-4126CRU_000004_9999CRU
4MROX_0001DATA/CRU_000005_9999_XN_99N999W.IMG4A_04_0001000800CRU_000005_9999_XN_99N999W2005-09-08 16:11:18.649CTXNIFL50562150410.00.0999.9999.9999.9999.9999.9999.9999.9999.9999.9999.9999.9999.9999.9CRUISEMOON0810663096:098297.15.71196/243/23800.00.00.00.00.0N0.00.00.00.00.00.00.0284.484.790.0Calibration image of the MoonOK-4126CRU_000005_9999CRU
..................................................................................................................................................................
142363MROX_4656DATA/U17_077781_1107_XI_69S045W.IMG4A_04_118B04B300U17_077781_1107_XI_69S045W2023-03-01 00:01:37.834CTXITL5056716815.061.194.9689.486.1745.21-69.4245.64-69.8244.42-69.7445.97-69.144.79-69.02ESPMARS1362096156:230294.01.877197/202/197025.3643.16252.63631.28253.48N279.93230.3796.4912.7446.17-69.47243271024.830.815.4290.1Southern autumn frost streak area in Viking 2 ...OK77781U17_077781_1107U17
142364MROX_4656DATA/U17_077781_1560_XN_24S055W.IMG4A_04_118A04B400U17_077781_1560_XN_24S055W2023-03-01 00:15:17.076CTXNIFL50563072015.131.190.0956.8456.7855.44-24.0855.48-25.6755.0-25.6255.88-22.5555.41-22.5ESPMARS1362096976:036293.91.877197/202/197025.68186.57256.543649.44256.54N276.89222.2899.912.7455.44-24.08243270437.830.8114.9690.2Ride-along with HiRISEOK77781U17_077781_1560U17
142365MROX_4656DATA/U17_077781_1683_XN_11S057W.IMG4A_04_118A04B500U17_077781_1683_XN_11S057W2023-03-01 00:19:04.486CTXNIFL50563174415.221.160.0949.8249.7657.0-11.7157.03-13.3556.58-13.2957.42-10.1256.98-10.06ESPMARS1362097203:141293.81.877197/202/197026.13192.71260.843656.22260.84N277.01214.98100.8312.7457.0-11.7243270441.730.8114.9190.2Terrain north of Coprates ChasmaOK77781U17_077781_1683U17
142366MROX_4656DATA/U17_077781_2027_XI_22N061W.IMG4A_04_118B04B600U17_077781_2027_XI_22N061W2023-03-01 00:29:24.818CTXITL50565222415.651.063.541.5638.0660.9622.860.8820.1560.3820.2161.5625.461.0425.45ESPMARS1362097823:226293.81.877197/202/197028.27312.92281.463674.69281.94N276.85180.29103.4212.7461.2522.78243271031.730.8114.8289.8Kasei Valles regionOK77781U17_077781_2027U17
142367MROX_4656DATA/U17_077781_2440_XN_64N067W.IMG4A_04_118A04B700U17_077781_2440_XN_64N067W2023-03-01 00:43:08.662CTXNIFL5056716816.220.945.4158.153.8867.7464.0768.2363.6867.0563.7568.4464.3867.2364.45ESPMARS1362098647:186293.81.877197/202/197031.1541.8309.793689.87311.07N277.1143.31106.5912.7468.7664.02243272920.630.8214.5989.9Ride-along with HiRISEOK77781U17_077781_2440U17
+ +

142368 rows × 53 columns

+
+
+
+
+

source

+
+
+

CTXEDR

+
+
 CTXEDR (pid:str, root:str='', with_volume=None, with_pid_folder=None,
+         refresh_index=False)
+
+

Manage access to EDR data

+ ++++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
TypeDefaultDetails
pidstrCTX product id (pid)
rootstralternative root folder for EDR data
with_volumeNoneTypeNonedoes the storage path include the volume folder
with_pid_folderNoneTypeNonecontrol if stuff is stored inside PID folders
refresh_indexboolFalse
+

PRODUCT_IDs can be provided in the shortened form (still unique), which are the first 15 characters of the full PRODUCT_ID:

+
+
pid = "F10_039666_1383"
+pid = "B01_009958_1524_XI_27S347W"
+
+
+
edr = CTXEDR(pid)
+
+
+

source

+
+
+

CTXEDR.pid

+
+
 CTXEDR.pid ()
+
+

Return product_id

+
+
edr.pid
+
+
'B01_009958_1524_XI_27S347W'
+
+
+
+
edr.short_pid
+
+
'B01_009958_1524'
+
+
+

These are the storage configuration settings:

+
+
edr.root
+
+
Path('/home/maye/big_drive/planetary_data/missions/mro/ctx/edr')
+
+
+
+
edr.with_pid_folder
+
+
True
+
+
+
+
edr.with_volume
+
+
True
+
+
+
+

source

+
+
+

CTXEDR.source_folder

+
+
 CTXEDR.source_folder ()
+
+

Calculate the source folder based on storage options with_pid_folder and with_volume.

+
+
edr.source_folder
+
+
Path('/home/maye/big_drive/planetary_data/missions/mro/ctx/edr/mrox_0684/B01_009958_1524_XI_27S347W')
+
+
+
+

source

+
+
+

CTXEDR.source_path

+
+
 CTXEDR.source_path ()
+
+

Combine source_folder with pid into full path.

+
+
edr.source_path
+
+
Path('/home/maye/big_drive/planetary_data/missions/mro/ctx/edr/mrox_0684/B01_009958_1524_XI_27S347W/B01_009958_1524_XI_27S347W.IMG')
+
+
+
+
edr.source_path.exists()
+
+
False
+
+
+
+

source

+
+
+

CTXEDR.meta

+
+
 CTXEDR.meta ()
+
+

get the metadata from the index table

+
+
edr.meta
+
+
volume_id                                                    MROX_0684
+file_specification_name            DATA/B01_009958_1524_XI_27S347W.IMG
+original_product_id                                   4A_04_103100F800
+product_id                                  B01_009958_1524_XI_27S347W
+image_time                                  2008-09-10 10:15:05.533000
+instrument_id                                                      CTX
+instrument_mode_id                                                 ITL
+line_samples                                                      5056
+lines                                                            18432
+spatial_summing                                                      1
+scaled_pixel_width                                                5.13
+pixel_aspect_ratio                                                1.18
+emission_angle                                                    1.08
+incidence_angle                                                  71.46
+phase_angle                                                      70.61
+center_longitude                                                347.59
+center_latitude                                                 -27.64
+upper_left_longitude                                            347.71
+upper_left_latitude                                              -28.6
+upper_right_longitude                                           347.22
+upper_right_latitude                                            -28.55
+lower_left_longitude                                            347.96
+lower_left_latitude                                             -26.73
+lower_right_longitude                                           347.47
+lower_right_latitude                                            -26.68
+mission_phase_name                                                 PSP
+target_name                                                       MARS
+spacecraft_clock_start_count                            0905508925:217
+focal_plane_temperature                                          292.8
+line_exposure_duration                                           1.877
+offset_mode_id                                             196/190/181
+sample_first_pixel                                                   0
+scaled_image_width                                               25.69
+scaled_image_height                                             111.85
+spacecraft_altitude                                             256.72
+target_center_distance                                         3648.65
+slant_distance                                                  256.76
+usage_note                                                           N
+north_azimuth                                                   276.86
+sub_solar_azimuth                                                223.2
+sub_solar_longitude                                              42.32
+sub_solar_latitude                                               20.59
+sub_spacecraft_longitude                                        347.68
+sub_spacecraft_latitude                                         -27.64
+solar_distance                                             239051686.0
+solar_longitude                                                 125.14
+local_time                                                       15.66
+image_skew_angle                                                  90.2
+rationale_desc                  Valley trace in northern Noachis Terra
+data_quality_desc                                                   OK
+orbit_number                                                      9958
+short_pid                                              B01_009958_1524
+month_col                                                          B01
+Name: 16153, dtype: object
+
+
+
+

source

+
+
+

CTXEDR.url

+
+
 CTXEDR.url ()
+
+

Calculate URL from input dataframe row.

+
+

source

+
+
+

CTXEDR.download

+
+
 CTXEDR.download (overwrite=False)
+
+

Download and store correctly the EDR data, if not locally available.

+ + + + + + + + + + + + + + + + + +
TypeDefaultDetails
overwriteboolFalseuse overwrite to download in all cases.
+
+
edr.download()
+
+ +
+
+
+
edr.source_path
+
+
Path('/home/maye/big_drive/planetary_data/missions/mro/ctx/edr/mrox_0684/B01_009958_1524_XI_27S347W.IMG')
+
+
+
+

source

+
+
+

CTXEDR.__str__

+
+
 CTXEDR.__str__ ()
+
+

Show some info about yourself when returned in a REPL (like ipython/jupyter).

+
+
Path(config.get_value("mro.ctx.preproc_root"))
+
+
Path('/remote/trove/geo/planet/Mars/CTX/special/cal_noflat')
+
+
+
+

source

+
+
+

CTX

+
+
 CTX (id_:str, source_dir:str='', proc_root:str='', with_volume=None,
+      with_pid_folder=None, use_preproc=False)
+
+

Class to manage dealing with CTX data.

+

HAS a CTXEDR attribute as defined above. Attributes from CTXEDR are availalbe via getattr()

+ ++++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
TypeDefaultDetails
id_strCTX product id
source_dirstrwhere the raw EDR data is stored, if not coming from plpy
proc_rootstrwhere to store processed, if not plpy
with_volumeNoneTypeNonestore with extra volume subfolder?
with_pid_folderNoneTypeNonestore with extra product_id subfolder?
use_preprocboolFalseuse preproc for cal_da
+
+
pid = "N05_064260_1638_XI_16S351W"
+
+
+
ctx = CTX(pid)
+
+
+
ctx.save_as_tif()
+
+
File exists. Use `refresh=True` to force recreation.
+
+
+
+
str(ctx.map_path)
+
+
'/home/ayek72/mnt/slowdata/planetarypy/missions/mro/ctx/edr/mrox_3629/N05_064260_1638_XI_16S351W/N05_064260_1638_XI_16S351W.lev2.cub'
+
+
+
+
ctx.proc_folder / ctx.map_name.with_suffix(".tif")
+
+
Path('/home/ayek72/mnt/slowdata/planetarypy/missions/mro/ctx/edr/mrox_3629/N05_064260_1638_XI_16S351W/N05_064260_1638_XI_16S351W.lev2.tif')
+
+
+
+
ctx.cal_da
+
+ +
+ + + + + + + + + + + + + + +
<xarray.DataArray 'N05_064260_1638 calibrated' (y: 15360, x: 5000)>
+[76800000 values with dtype=float32]
+Coordinates:
+  * x        (x) float64 0.5 1.5 2.5 3.5 ... 4.996e+03 4.998e+03 4.998e+03 5e+03
+  * y        (y) float64 0.5 1.5 2.5 3.5 ... 1.536e+04 1.536e+04 1.536e+04
+Attributes:
+    BANDWIDTH:        0.15
+    BANDWIDTH_UNIT:   micrometers
+    WAVELENGTH:       0.65
+    WAVELENGTH_UNIT:  micrometers
+    scale_factor:     1.0
+    add_offset:       0.0
+    long_name:        BroadBand
+
+
+
+
ctx.preproc_cal_path
+
+
Path('/remote/trove/geo/planet/Mars/CTX/special/cal_noflat/mrox_3629/N05_064260_1638_XI_16S351W.ctxcal.cub')
+
+
+

Based on storage options with_pid_folder and with_volume, we calculate the proc_folder for self-processed data:

+
+

source

+
+
+

CTX.proc_folder

+
+
 CTX.proc_folder ()
+
+

the folder for foreign processed data, like pre-processed calibrated data, e.g.

+
+
ctx.proc_folder
+
+
Path('/home/ayek72/mnt/slowdata/planetarypy/missions/mro/ctx/edr/mrox_3629/N05_064260_1638_XI_16S351W')
+
+
+

These can be changed at object creation:

+
+
CTX(pid, with_volume=True, with_pid_folder=True).source_folder
+
+
Path('/remote/trove/geo/planet/Mars/CTX/pds/mrox_3629')
+
+
+
+

source

+
+
+

CTX.cal_path

+
+
 CTX.cal_path ()
+
+

Path to calibrated cube file. Also destriped files get this name.

+
+
ctx.cal_path
+
+
Path('/home/ayek72/mnt/slowdata/planetarypy/missions/mro/ctx/edr/mrox_3629/N05_064260_1638_XI_16S351W/N05_064260_1638_XI_16S351W.cal.cub')
+
+
+
+

source

+
+
+

CTX.calib_pipeline

+
+
 CTX.calib_pipeline (overwrite=False)
+
+

Execute the whole ISIS pipeline for CTX EDR data.

+
+
ctx.proc_folder
+
+
Path('/home/ayek72/mnt/slowdata/planetarypy/missions/mro/ctx/edr/mrox_3629/N05_064260_1638_XI_16S351W')
+
+
+
+
ctx.isis_import()
+
+
+
ctx.spice_init(web="yes")
+
+
+
ctx.calibrate()
+
+
+
ctx.destripe()
+
+
+
# not executing always, as it takes lot of time
+# ctx.map_project()
+
+
+
ctx.map_path
+
+
+
ctx.calib_pipeline()
+
+
+

source

+
+
+

CTX.plot_edr

+
+
 CTX.plot_edr ()
+
+

Plot EDR xarray using hvplot.

+
+
ctx.plot_edr()
+
+ +
+
+
+
+
+ +
+
+
+
+
+ +
+
+Note +
+
+
+

Note the different shape of EDR data and calibrated data. A few SAMPLES are being used for calibration.

+
+
+
+
ctx.edr_shape
+
+
(15360, 5056)
+
+
+
+
ctx.cal_shape
+
+
(15360, 5000)
+
+
+
+
ctx.plot_calibrated()
+
+ +
+
+
+
+
+ +
+
+
+

source

+
+
+

CTXCollection

+
+
 CTXCollection (product_ids, full_width=False, filter_error=False,
+                edrindex=None)
+
+

Class with several helpful methods to work with a set of CTX images.

+

We identify the images via a list of product_ids. Several methods manipulate this list based on the requested constraint.

+

The CTXCollection class offers a few class methods for a wider range of finding CTX product_ids from the index file:

+
+

source

+
+
+

CTXCollection.by_volume

+
+
 CTXCollection.by_volume (vol_id, **kwargs)
+
+

Create a CTXCollection from the PDS volume number.

+
+
CTXCollection.by_volume(4114).n_items
+
+
30
+
+
+
+
CTXCollection.by_volume(4114, full_width=True).n_items
+
+
19
+
+
+
+
CTXCollection.by_volume(4114, full_width=True, filter_error=True).n_items
+
+
14
+
+
+
+
CTXCollection.by_volume(4114, full_width=False, filter_error=True).n_items
+
+
23
+
+
+
+

source

+
+
+

CTXCollection.by_month

+
+
 CTXCollection.by_month (month_letters, nth_volume=None, **kwargs)
+
+

Create a CTXCollection based on the first 3 letters of the product_id (a.k.a. “month”)

+
+
CTXCollection.by_month("J18", filter_error=True, full_width=True).n_items
+
+
287
+
+
+
+

source

+
+
+

CTXCollection.volume_from_pid

+
+
 CTXCollection.volume_from_pid (pid, **kwargs)
+
+

Get a CTXCollection of the volume for a given image (product_id).

+

We define an example list of product_ids:

+
+
ids = get_edr_index().sample(3, random_state=41).PRODUCT_ID
+ids
+
+
41779    G16_024548_2195_XI_39N161W
+33475    G02_018931_1907_XI_10N166W
+45075    G20_026104_2617_XN_81N181W
+Name: PRODUCT_ID, dtype: string
+
+
+
+
CTXCollection.volume_from_pid(ids.values[0]).n_items  # getting the whole volume here
+
+
56
+
+
+
+
coll = CTXCollection(ids)
+
+
+
coll.edr_exist_check()
+
+
[('G02_018931_1907_XI_10N166W', True),
+ ('G16_024548_2195_XI_39N161W', True),
+ ('G20_026104_2617_XN_81N181W', True)]
+
+
+
+
coll.get_urls()
+
+
[URL('https://pds-imaging.jpl.nasa.gov/data/mro/mars_reconnaissance_orbiter/ctx/mrox_1200/data/G02_018931_1907_XI_10N166W.IMG'),
+ URL('https://pds-imaging.jpl.nasa.gov/data/mro/mars_reconnaissance_orbiter/ctx/mrox_1422/data/G16_024548_2195_XI_39N161W.IMG'),
+ URL('https://pds-imaging.jpl.nasa.gov/data/mro/mars_reconnaissance_orbiter/ctx/mrox_1532/data/G20_026104_2617_XN_81N181W.IMG')]
+
+
+

The next command launches a parallel download:

+
+
coll.download_collection(overwrite=False)
+
+
Downloading collection...
+File exists. Use `overwrite=True` to download fresh.
+File exists. Use `overwrite=True` to download fresh.
+File exists. Use `overwrite=True` to download fresh.
+
+
+ +
+
+

This is performing the ISIS import and calibration in parallel:

+
+
coll.calibrate_collection()
+
+
+
coll.calib_exist_check()
+
+
[('G02_018931_1907_XI_10N166W', False),
+ ('G16_024548_2195_XI_39N161W', False),
+ ('G20_026104_2617_XN_81N181W', False)]
+
+
+
+
coll = CTXCollection.by_volume(4114)
+
+
+
coll.product_ids
+
+
<StringArray>
+['N20_069979_1676_XI_12S177W', 'N20_069980_1676_XI_12S205W',
+ 'N20_069981_1919_XI_11N234W', 'N20_069982_1380_XI_42S255W',
+ 'N20_069982_1820_XI_02N261W', 'N20_069982_2287_XN_48N269W',
+ 'N20_069983_1442_XI_35S283W', 'N20_069984_1686_XI_11S313W',
+ 'N20_069984_2097_XI_29N319W', 'N20_069985_2064_XI_26N345W',
+ 'N20_069986_2025_XI_22N012W', 'N20_069987_2243_XN_44N042W',
+ 'N20_069991_1451_XI_34S142W', 'N20_069991_1940_XI_14N149W',
+ 'N20_069992_1761_XI_03S173W', 'N20_069993_1724_XI_07S200W',
+ 'N20_069994_1753_XI_04S227W', 'N20_069995_1633_XI_16S254W',
+ 'N20_069995_2028_XI_22N258W', 'N20_069996_2085_XN_28N285W',
+ 'N20_069997_1479_XI_32S306W', 'N20_069999_1558_XI_24S003W',
+ 'N20_070004_1931_XI_13N144W', 'N20_070006_1430_XI_37S191W',
+ 'N20_070007_1793_XI_00S223W', 'N20_070009_2018_XN_21N282W',
+ 'N20_070010_1466_XI_33S301W', 'N20_070011_1507_XI_29S328W',
+ 'N20_070011_2252_XI_45N338W', 'N20_070012_1824_XN_02N001W']
+Length: 30, dtype: string
+
+
+
+

source

+
+
+

CTXCollection.get_corrupted

+
+
 CTXCollection.get_corrupted ()
+
+

Return the product_ids where the PDS index file has an ‘ERROR’ flag for the DATA_QUALITY_DESC field.

+
+
coll.get_corrupted()
+
+
['N20_069991_1451_XI_34S142W',
+ 'N20_069992_1761_XI_03S173W',
+ 'N20_069993_1724_XI_07S200W',
+ 'N20_069994_1753_XI_04S227W',
+ 'N20_069997_1479_XI_32S306W',
+ 'N20_070010_1466_XI_33S301W',
+ 'N20_070012_1824_XN_02N001W']
+
+
+
+

source

+
+
+

CTXCollection.n_items

+
+
 CTXCollection.n_items ()
+
+

Return length of product_ids list.

+
+
coll.n_items
+
+
30
+
+
+
+

source

+
+
+

CTXCollection.sample

+
+
 CTXCollection.sample (n)
+
+

Return random sample of product_ids, size n.

+
+
coll.sample(4)
+
+
['N20_070006_1430_XI_37S191W',
+ 'N20_069999_1558_XI_24S003W',
+ 'N20_069986_2025_XI_22N012W',
+ 'N20_069983_1442_XI_35S283W']
+
+
+
+

source

+
+
+

CTXCollection.meta

+
+
 CTXCollection.meta ()
+
+

Return the index file filtered for the given product_ids.

+
+
coll.meta.head()
+
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
VOLUME_IDFILE_SPECIFICATION_NAMEORIGINAL_PRODUCT_IDPRODUCT_IDIMAGE_TIMEINSTRUMENT_IDINSTRUMENT_MODE_IDLINE_SAMPLESLINESSPATIAL_SUMMINGSCALED_PIXEL_WIDTHPIXEL_ASPECT_RATIOEMISSION_ANGLEINCIDENCE_ANGLEPHASE_ANGLECENTER_LONGITUDECENTER_LATITUDEUPPER_LEFT_LONGITUDEUPPER_LEFT_LATITUDEUPPER_RIGHT_LONGITUDEUPPER_RIGHT_LATITUDELOWER_LEFT_LONGITUDELOWER_LEFT_LATITUDELOWER_RIGHT_LONGITUDELOWER_RIGHT_LATITUDEMISSION_PHASE_NAMETARGET_NAMESPACECRAFT_CLOCK_START_COUNTFOCAL_PLANE_TEMPERATURELINE_EXPOSURE_DURATIONOFFSET_MODE_IDSAMPLE_FIRST_PIXELSCALED_IMAGE_WIDTHSCALED_IMAGE_HEIGHTSPACECRAFT_ALTITUDETARGET_CENTER_DISTANCESLANT_DISTANCEUSAGE_NOTENORTH_AZIMUTHSUB_SOLAR_AZIMUTHSUB_SOLAR_LONGITUDESUB_SOLAR_LATITUDESUB_SPACECRAFT_LONGITUDESUB_SPACECRAFT_LATITUDESOLAR_DISTANCESOLAR_LONGITUDELOCAL_TIMEIMAGE_SKEW_ANGLERATIONALE_DESCDATA_QUALITY_DESCORBIT_NUMBERshort_pidmonth_col
127546MROX_4114DATA/N20_069979_1676_XI_12S177W.IMG4A_04_1165000100N20_069979_1676_XI_12S177W2021-07-01 02:22:53.651CTXITL50564300815.31.145.365.1861.08177.4-12.53177.37-14.74176.91-14.69177.89-10.37177.43-10.32ESPMARS1309573428:228291.31.877196/188/183026.53260.74262.713657.97263.76N276.79219.82233.323.12177.78-12.56249116269.665.9715.7290.2Northern Terra SirenumOK69979N20_069979_1676N20
127547MROX_4114DATA/N20_069980_1676_XI_12S205W.IMG4A_04_1165000200N20_069980_1676_XI_12S205W2021-07-01 04:15:32.600CTXITL50561843215.261.152.4864.9963.03204.93-12.5205.04-13.46204.59-13.41205.26-11.59204.81-11.53ESPMARS1309580187:215290.91.877196/188/183026.34111.73262.543657.8262.77N276.75219.87260.6223.13205.11-12.51249117636.266.015.7190.1Valleys in Terra CimmeriaOK69980N20_069980_1676N20
127548MROX_4114DATA/N20_069981_1919_XI_11N234W.IMG4A_04_1165000300N20_069981_1919_XI_11N234W2021-07-01 06:14:46.674CTXITL50565222415.621.078.1353.4346.2234.6411.91234.589.25234.19.3235.214.52234.7114.57ESPMARS1309587341:234291.11.877196/188/183028.12314.36275.313670.67277.89N276.65206.74289.7623.14235.2711.85249118514.066.0415.6690.0Nepenthes Planum regionOK69981N20_069981_1919N20
127549MROX_4114DATA/N20_069982_1380_XI_42S255W.IMG4A_04_1165000400N20_069982_1380_XI_42S255W2021-07-01 07:50:56.614CTXITL25287168210.251.194.8783.9880.5255.35-42.07255.52-42.83254.94-42.77255.75-41.37255.18-41.32ESPMARS1309593111:219291.21.884196/188/183025.6587.09254.993642.26255.85N276.84225.48313.0223.14255.8-42.1249121323.666.0715.8490.1Apron in the Hellas Montes regionOK69982N20_069982_1380N20
127550MROX_4114DATA/N20_069982_1820_XI_02N261W.IMG4A_04_1165000500N20_069982_1820_XI_02N261W2021-07-01 08:03:55.615CTXITL50565222415.421.115.1157.4753.17261.022.02260.94-0.66260.49-0.6261.574.63261.114.69ESPMARS1309593890:219291.01.877196/188/183027.13315.79268.723664.89269.71N276.84213.19316.3323.14261.41.98249120029.266.0715.6790.1Tyrrhena TerraOK69982N20_069982_1820N20
+ +
+
+
+
+

source

+
+
+

CTXCollection.image_times

+
+
 CTXCollection.image_times ()
+
+

Return the image observation times.

+
+
coll.image_times
+
+
127546   2021-07-01 02:22:53.651
+127547   2021-07-01 04:15:32.600
+127548   2021-07-01 06:14:46.674
+127549   2021-07-01 07:50:56.614
+127550   2021-07-01 08:03:55.615
+127551   2021-07-01 08:19:18.963
+127552   2021-07-01 09:44:54.631
+127553   2021-07-01 11:44:29.607
+127554   2021-07-01 11:57:15.646
+127555   2021-07-01 13:48:19.595
+127556   2021-07-01 15:39:04.638
+127557   2021-07-01 17:38:53.212
+127558   2021-07-02 00:42:16.641
+127559   2021-07-02 00:57:36.688
+127560   2021-07-02 02:44:15.621
+127561   2021-07-02 04:35:30.668
+127562   2021-07-02 06:28:38.621
+127563   2021-07-02 08:16:50.660
+127564   2021-07-02 08:29:27.601
+127565   2021-07-02 10:23:41.558
+127566   2021-07-02 11:56:54.648
+127567   2021-07-02 15:43:37.659
+127568   2021-07-03 01:16:03.651
+127569   2021-07-03 04:45:28.607
+127570   2021-07-03 06:48:35.596
+127571   2021-07-03 10:40:22.119
+127572   2021-07-03 12:14:51.615
+127573   2021-07-03 14:08:48.673
+127574   2021-07-03 14:31:39.582
+127575   2021-07-03 16:10:56.454
+Name: IMAGE_TIME, dtype: datetime64[ns]
+
+
+

Also cool: pandas can do time-average:

+
+
coll.image_times.mean()
+
+
Timestamp('2021-07-02 05:45:11.936933376')
+
+
+
+

source

+
+
+

CTXCollection.get_ctx_n

+
+
 CTXCollection.get_ctx_n (n)
+
+

Get CTX object for n-th product_id

+
+
coll.get_ctx_n(2)
+
+
PRODUCT_ID: N20_069981_1919_XI_11N234W
+URL: https://pds-imaging.jpl.nasa.gov/data/mro/mars_reconnaissance_orbiter/ctx/mrox_4114/data/N20_069981_1919_XI_11N234W.IMG
+source_path: /remote/trove/geo/planet/Mars/CTX/pds/mrox_4114/N20_069981_1919_XI_11N234W.IMG
+Shape: (52224, 5056)
+
+
+
+

source

+
+
+

CTXCollection.get_pid_n

+
+
 CTXCollection.get_pid_n (n)
+
+

Get pid for n-th entry in product_ids.

+
+
coll.get_pid_n(2)
+
+
'N20_069981_1919_XI_11N234W'
+
+
+
+
coll = CTXCollection.by_month("N21")
+
+
+
len(coll.product_ids)
+
+
342
+
+
+
+
coll
+
+
# of product IDs: 342
+Volumes contained in list of product_ids:
+<StringArray>
+['MROX_4126', 'MROX_4127', 'MROX_4128', 'MROX_4129', 'MROX_4130', 'MROX_4131',
+ 'MROX_4132', 'MROX_4133']
+Length: 8, dtype: string
+
+
+
+
+

Command line interfaces

+
+

source

+
+

ctx_calib

+
+
 ctx_calib (pid:str, source:str='', proc_root:str='',
+            overwrite:bool=False)
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
TypeDefaultDetails
pidstrCTX product_id
sourcestrpath to where EDRs are stored if not from plpy
proc_rootstrpath to where processed data is to be stored
overwriteboolFalseoverwrite processed data
+
+
ctx_calib(pid, overwrite=True)
+
+
+
from nbdev import nbdev_export
+
+nbdev_export()
+
+ + +
+
+ +
+ + +
+ + + + \ No newline at end of file diff --git a/api/diviner.html b/api/diviner.html new file mode 100644 index 0000000..8439204 --- /dev/null +++ b/api/diviner.html @@ -0,0 +1,670 @@ + + + + + + + + + + +planetarypy - Diviner + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Diviner

+
+ +
+
+ Tools to work with Diviner PDS data +
+
+ + +
+ + + + +
+ + +
+ + +
+

source

+
+

DataManager

+
+
 DataManager (tstr)
+
+

Initialize self. See help(type(self)) for accurate signature.

+
+
dm = DataManager("2010010110")
+
+
+
dm.local_path
+
+
+

source

+
+
+

read_l1a_data

+
+
 read_l1a_data (fname, nrows=None)
+
+
+

source

+
+
+

L1AHeader

+
+
 L1AHeader ()
+
+

Initialize self. See help(type(self)) for accurate signature.

+
+

source

+
+
+

parse_header_line

+
+
 parse_header_line (line)
+
+

Parse header lines.

+
+
+
+

s = ’ a b c ’ parse_header_line(s) [‘a’, ‘b’, ‘c’] s = ’ a, b , c ’ parse_header_line(s) [‘a’, ‘b’, ‘c’]

+
+
+
+
+
dm = DataManager("2010010110")
+
+
+
dm.download()
+
+
+
dm.volume
+
+
+
dm.url
+
+
+
df = pd.read_csv(
+    dm.local_path,
+    comment="#",
+    # names=L1AHeader.columns,
+    na_values="-9999",
+    skipinitialspace=True,
+)
+df.head()
+
+
+
pd.set_option("display.max_columns", 200)
+
+
+
df.index
+
+
+
dm.local_path
+
+
+

source

+
+
+

get_data_path

+
+
 get_data_path (tstr)
+
+
+
get_data_path("2017010110")
+
+ + +
+ +
+ +
+ + + + \ No newline at end of file diff --git a/api/exceptions.html b/api/exceptions.html new file mode 100644 index 0000000..7c20b02 --- /dev/null +++ b/api/exceptions.html @@ -0,0 +1,622 @@ + + + + + + + + + + +planetarypy - Package exceptions + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Package exceptions

+
+ +
+
+ Specialized exceptions that provide better feed-back +
+
+ + +
+ + + + +
+ + +
+ + +
+

source

+
+

MissingParameterError

+
+
 MissingParameterError (txt)
+
+

Base class for exceptions in this module.

+
+

source

+
+
+

SpiceError

+
+
 SpiceError (function)
+
+

Base class for exceptions in this module.

+
+

source

+
+
+

ObserverNotSetError

+

Base class for exceptions in this module.

+
+

source

+
+
+

SPointNotSetError

+

Base class for exceptions in this module.

+
+

source

+
+
+

SpicerError

+

Base class for exceptions in this module.

+
+

source

+
+
+

GeoTransformNotSetError

+
+
 GeoTransformNotSetError (where, what)
+
+

Exception raised for errors in the input of transformations.

+

Attributes: where – where is something missing what – what is missing

+
+

source

+
+
+

ProjectionNotSetError

+
+
 ProjectionNotSetError (where, what)
+
+

Exception raised for errors in the input of transformations.

+

Attributes: where – where is something missing what – what is missing

+
+

source

+
+
+

SomethingNotSetError

+
+
 SomethingNotSetError (where, what)
+
+

Exception raised for errors in the input of transformations.

+

Attributes: where – where is something missing what – what is missing

+
+

source

+
+
+

Error

+

Base class for exceptions in this module.

+ + +
+ +
+ +
+ + + + \ No newline at end of file diff --git a/api/geotools.html b/api/geotools.html new file mode 100644 index 0000000..31d8385 --- /dev/null +++ b/api/geotools.html @@ -0,0 +1,914 @@ + + + + + + + + + + +planetarypy - Geotools + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Geotools

+
+ +
+
+ Utilities to work with geo-referenced (image) data. (GDAL required) +
+
+ + +
+ + + + +
+ + +
+ + +
+

Abbreviations

+
    +
  • ul = Upper Left
    • +
  • lr = LowerRight
    • +
+
+

source

+
+

pixel_to_meter

+
+
 pixel_to_meter (sample, line, geotransform, shift=False)
+
+

provide point in map projection coordinates.

+ ++++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
TypeDefaultDetails
sample
line
geotransform
shiftboolFalse
Returnstuple (x,y) coordinates in the projection of the dataset
+
+

source

+
+
+

shift_to_center

+
+
 shift_to_center (x, y, geotransform)
+
+
+

source

+
+
+

debug_srs

+
+
 debug_srs (projection)
+
+

Correct wrong scale_factor in PolarStereographic data.

+

Some PolarStereographic data have a 0 as a scale_factor in the projection (mostly MOLA), which is being corrected here. TODO: Check for being PolarStereographic before doing this!

+
+

source

+
+
+

get_sun_angles

+
+
 get_sun_angles (spicer, img)
+
+

Calculate solar azimuth and incidence.

+

By requiring a spicer object for this function, it becomes independent from the solar system object where the calculations are made.

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
TypeDetails
spicerspicer.Spicerneeds to be setup for time, but spoint is set from img.center in here.
imggeotools.ImgDataThe image data of which the center point serves as the start point.
Returnstuple(float, float)Solar azimuth, incidence [degrees]
+
+

source

+
+
+

calculate_image_north_azimuth

+
+
 calculate_image_north_azimuth (img, zero='right')
+
+
+

source

+
+
+

get_north_shifted_point

+
+
 get_north_shifted_point (img, offset=0.001)
+
+

Increasing the latitude is a sure way of getting north.

+
+

source

+
+
+

calculate_image_azimuth

+
+
 calculate_image_azimuth (origPoint, newPoint, zero='right')
+
+

Calculate azimuth angle between 2 image points.

+

Beware that this function calculates trigonometric angles. If the points are from an image that has (0, 0) in the upper left, this means that the angles increase clockwise. That is why, for example, for an HiRISE image, the return of this function matches the angle rotation definition for HiRISE data.

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
TypeDefaultDetails
origPoint
newPoint
zerostrright
Returnsazimuth: Azimuth angle
+
/home/runner/micromamba/envs/my-env/lib/python3.11/site-packages/fastcore/docscrape.py:225: UserWarning: Unknown section Requires
+  else: warn(msg)
+
+

source

+
+
+

Point

+
+
 Point (sample=None, line=None, x=None, y=None, lon=None, lat=None,
+        geotrans=None, proj=None)
+
+

Point class to manage pixel and map points and their transformations.

+
+

source

+
+
+

Window

+
+
 Window (ulPoint=None, lrPoint=None, centerPoint=None, width=None)
+
+

class to manage a window made of corner Points (objects of Point())

+

when using width, only quadratic windows supported currently >>> p1 = Point(0, 1) >>> p2 = Point(10,20)

+
+

source

+
+
+

ImgData

+
+
 ImgData (fname=None)
+
+

docstring for ImgData

+
+
# todo: Fix missing MOLA class
+#| export
+# class CTX(ImgData):
+#     """docstring for CTX"""
+
+#     def __init__(self, fname):
+#         ImgData.__init__(self, fname)
+
+#     def add_mola_contours(self):
+#         self.window_coords_to_lonlat()
+#         mola = MOLA()
+#         mola.window = self.window.copy()
+#         mola.window_coords_to_pixel()
+#         mola.read_window(mola.window)
+#         mola.data = mola.data - mola.data.mean()
+#         fig = plt.figure(figsize=(10, 10))
+#         ax = fig.add_subplot(111)
+#         plt.gray()
+#         ax.imshow(self.data, extent=self.window.get_extent(self.dataset))
+#         CS = ax.contour(
+#             mola.data,
+#             8,
+#             cmap=cm.jet,
+#             extent=self.window.get_extent(self.dataset),
+#             origin="image",
+#         )
+#         plt.clabel(CS, fontsize=13, inline=1)
+#         ax.set_xlabel("Polar stereographic X [km]")
+#         ax.set_ylabel("Polar stereographic Y [km]")
+#         ax.set_title("CTX: " + os.path.basename(self.fname))
+#         self.ax = ax
+#         plt.show()
+
+
+
# def combine_ctx_and_mola(ctxFilename, ctxSample, ctxLine, ctxWidth):
+#     """combine CTX and MOLA data.
+#
+#     MOLA and CTX data will be combined with these tools.
+#     User shall provide line,sample center coordinate of CTX file ROI to
+#     define distance in meters from southpole.
+#     """
+#
+#     ctx = CTX(ctxFilename)
+#     mola = MOLA()
+#     ctxULsample, ctxULline, ctxLRsample, ctxLRline = \
+#         get_corners_from_center(ctxSample, ctxLine, ctxWidth)
+#     ulX,ulY = get_coords_from_pixels(ctxDS, ctxULsample, ctxULline)
+#     lrX,lrY = get_coords_from_pixels(ctxDS, ctxLRsample, ctxLRline)
+#
+#     molaULsample,molaULline = get_pixels_from_coords(molaDS,ulX,ulY)
+#     molaLRsample,molaLRline = get_pixels_from_coords(molaDS,lrX,lrY)
+#     print(ctxULsample, ctxULline, ctxLRsample, ctxLRline)
+#     print(molaULsample, molaULline,molaLRsample, molaLRline)
+#     print(ulX,ulY,lrX,lrY)
+#     ctxData = ctxDS.ReadAsArray(ctxULsample,ctxULline,ctxWidth,ctxWidth)
+#     molaData = molaDS.ReadAsArray(int(molaULsample)+1,int(molaULline),
+#                                   int(molaLRsample - molaULsample),
+#                                   int(molaLRline - molaULline))
+#
+#     molaData = molaData - molaData.mean()
+#
+#     # x = np.arange(ulX,lrX)
+#     # y = np.arange(lrY,ulY)
+#     # X, Y = np.meshgrid(x,y)
+#     # plotting
+#     fig = plt.figure(figsize=(10,10))
+#     ax = fig.add_subplot(111)
+#     plt.gray()
+#     ax.imshow(ctxData, extent=(min(ulX,lrX),max(ulX,lrX),min(ulY,lrY),
+#                                      max(ulY,lrY)))
+#     CS = ax.contour(molaData, 20, cmap = cm.jet,
+#                      extent=(min(ulX,lrX),
+#                              max(ulX,lrX),
+#                              min(ulY,lrY),
+#                              max(ulY,lrY)),
+#                      origin='image' )
+#     plt.clabel(CS,fontsize=9, inline=1)
+#     plt.show()
+
+# def main(argv=None):
+#     """docstring for main"""
+#     from mayavi import mlab
+
+#     if argv is None:
+#         argv = sys.argv
+
+#     x1 = x2 = y1 = y2 = 0
+#     fname = ""
+#     try:
+#         fname = argv[1]
+#         x1, x2, y1, y2 = [int(i) for i in argv[2:]]
+#     except:
+#         print("Usage: {0} fname x1 x2 y1 y2".format(argv[0]))
+
+#     print(x1, x2, y1, y2)
+#     ds = gdal.Open(fname)
+#     band = ds.GetRasterBand(1)
+#     STORED_VALUE = band.ReadAsArray(x1, y1, x2 - x1, y2 - y1)
+#     ds = 0
+
+#     # PDS label infos:
+#     SCALING_FACTOR = 0.25
+#     OFFSET = -8000
+#     topo = (STORED_VALUE * SCALING_FACTOR) + OFFSET
+#     mlab.surf(topo, warp_scale=1 / 115.0, vmin=1700)
+#     mlab.colorbar(orientation="vertical", title="Height [m]", label_fmt="%4.0f")
+#     mlab.show()
+
+ + +
+
+ +
+ +
+ + + + \ No newline at end of file diff --git a/api/hirise.html b/api/hirise.html new file mode 100644 index 0000000..641da99 --- /dev/null +++ b/api/hirise.html @@ -0,0 +1,1695 @@ + + + + + + + + + + +planetarypy - HiRISE + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

HiRISE

+
+ +
+
+ Data management for HiRISE data. +
+
+ + +
+ + + + +
+ + +
+ + +
+

source

+
+

OBSID

+
+
 OBSID (obsid:str)
+
+

Manage HiRISE observation ids.

+

For example PSP_003092_0985. phase is set to PSP for orbits < 11000, no setting required.

+ + + + + + + + + + + + + + + +
TypeDetails
obsidstre.g. PSP_003092_0985
+
+
obsid = OBSID("PSP_003092_0985")
+obsid
+
+
PSP_003092_0985
+
+
+
+
assert obsid.orbit == "003092"
+
+
+
assert obsid.targetcode == "0985"
+
+
+
assert obsid.phase == "PSP"
+
+
+
assert obsid.upper_orbit_folder == "ORB_003000_003099"
+
+
+
assert obsid.storage_path_stem == "PSP/ORB_003000_003099/PSP_003092_0985"
+
+
+

source

+
+
+

ProductPathfinder

+
+
 ProductPathfinder (initstr:str, check_url:bool=True)
+
+

Determine paths and URLs for HiRISE RDR products (also EXTRAS.)

+

We use the PDS definition of PRODUCT_ID here, e.g. PSP_003092_0985_RED.

+

Attributes jp2_path and label_path get you the official RDR mosaic product, with kind steering if you get the COLOR or the RED product. All other properties go to the RDR/EXTRAS folder. The “PDS” part of the path is handled in the OBSID class.

+ ++++++ + + + + + + + + + + + + + + + + + + + + + + +
TypeDefaultDetails
initstrstrPRODUCT_ID string, e.g. PSP_003092_0985_RED
check_urlboolTruefor performance, the user might not want the url check
+
+
pid = "ESP_039983_1390_RED"
+
+
+
ppf = ProductPathfinder(pid)
+
+
+
ppf.storage_stem
+
+
'ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED'
+
+
+
+
ppf.local_label_path.exists()
+
+
False
+
+
+
+
ppf.edr_storage_stem
+
+
Path('EDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED')
+
+
+
+
ppf.download_label()
+
+ +
+
+
Path('/home/ayek72/mnt/slowdata/planetarypy/missions/mro/hirise/ESP_039983_1390/ESP_039983_1390_RED.LBL')
+
+
+
+
ppf.go_to_homepage()
+
+
4;1HPS connection to uahirise.org[22;24H                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             Getting https://uahirise.org/ESP_039983_1390
+
+
+
+
ppf.homepage
+
+
'https://uahirise.org/ESP_039983_1390'
+
+
+
+
assert isinstance(ppf.obsid, OBSID)
+
+
+
assert ppf.kind == "RED"
+
+
+
assert ppf.label_fname == "ESP_039983_1390_RED.LBL"
+
+
+
assert ppf.label_path == Path('RDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED.LBL')
+
+
+
+

Paths and URLS

+

Each xxx_path attribute is also available as xxx_url, and accessing the _url parameter immediately checks for its existence on the server.

+
+
# little helper to show attributes inside ProductPathfinder object...
+def _isprop(v):
+    return isinstance(v, property)
+
+
+def _get_properties(classname, substring):
+    names = [name for (name, value) in inspect.getmembers(classname, _isprop) if name.endswith(substring)]
+    return names
+
+
+
# Here I'm checking that all _url versions work, each access checks for existence:
+for prop in _get_properties(ProductPathfinder, "_path"):
+    if prop.startswith("local_label"):
+        continue
+    print(prop)
+    print(getattr(ppf, prop))
+    urlattr = prop.replace("_path", "_url")
+    print(urlattr)
+    url = getattr(ppf, urlattr)
+    print(url)
+
+
abrowse_path
+EXTRAS/RDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED.abrowse.jpg
+abrowse_url
+https://hirise-pds.lpl.arizona.edu/PDS/EXTRAS/RDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED.abrowse.jpg
+browse_path
+EXTRAS/RDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED.browse.jpg
+browse_url
+https://hirise-pds.lpl.arizona.edu/PDS/EXTRAS/RDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED.browse.jpg
+jp2_path
+RDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED.JP2
+jp2_url
+https://hirise-pds.lpl.arizona.edu/PDS/RDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED.JP2
+label_path
+RDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED.LBL
+label_url
+https://hirise-pds.lpl.arizona.edu/PDS/RDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED.LBL
+nomap_browse_path
+EXTRAS/RDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED.NOMAP.browse.jpg
+nomap_browse_url
+https://hirise-pds.lpl.arizona.edu/PDS/EXTRAS/RDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED.NOMAP.browse.jpg
+nomap_jp2_path
+EXTRAS/RDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED.NOMAP.JP2
+nomap_jp2_url
+https://hirise-pds.lpl.arizona.edu/PDS/EXTRAS/RDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED.NOMAP.JP2
+nomap_thumbnail_path
+EXTRAS/RDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED.NOMAP.thumb.jpg
+nomap_thumbnail_url
+https://hirise-pds.lpl.arizona.edu/PDS/EXTRAS/RDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED.NOMAP.thumb.jpg
+quicklook_path
+EXTRAS/RDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED.QLOOK.JP2
+quicklook_url
+https://hirise-pds.lpl.arizona.edu/PDS/EXTRAS/RDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED.QLOOK.JP2
+thumbnail_path
+EXTRAS/RDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED.thumb.jpg
+thumbnail_url
+https://hirise-pds.lpl.arizona.edu/PDS/EXTRAS/RDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED.thumb.jpg
+
+
+
+
ppf.storage_stem
+
+
'ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED'
+
+
+
+
ppf.nomap_browse_url
+
+
URL('https://hirise-pds.lpl.arizona.edu/PDS/EXTRAS/RDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED.NOMAP.browse.jpg')
+
+
+
+
ppf.abrowse_url
+
+
URL('https://hirise-pds.lpl.arizona.edu/PDS/EXTRAS/RDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED.abrowse.jpg')
+
+
+
+
ppf.nomap_jp2_path
+
+
'EXTRAS/RDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED.NOMAP.JP2'
+
+
+
+

source

+
+
+

COLOR_PRODUCT

+
+
 COLOR_PRODUCT (obsid)
+
+

Initialize self. See help(type(self)) for accurate signature.

+
+

source

+
+
+

RGB_NOMAP

+
+
 RGB_NOMAP (obsid)
+
+

Initialize self. See help(type(self)) for accurate signature.

+
+
obsid = "ESP_039983_1390"
+
+
+
rgb = RGB_NOMAP(obsid)
+
+
+
rgb.obsid
+
+
'ESP_039983_1390'
+
+
+
+
rgb.product_id
+
+
'ESP_039983_1390_RGB'
+
+
+
+
rgb.meta.head()
+
+
volume_id                                                         MROHR_0001
+file_name_specification    RDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_...
+instrument_host_id                                                       MRO
+instrument_id                                                         HIRISE
+observation_id                                               ESP_039983_1390
+Name: 75508, dtype: object
+
+
+
+
rgb.local_path
+
+
Path('/home/ayek72/mnt/slowdata/planetarypy/missions/mro/hirise/ESP_039983_1390/ESP_039983_1390_RGB.NOMAP.JP2')
+
+
+
+
rgb.url
+
+
URL('https://hirise-pds.lpl.arizona.edu/PDS/EXTRAS/RDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RGB.NOMAP.JP2')
+
+
+
+
rgb.download(overwrite=False)
+
+
File exists. Use `overwrite=True` to download fresh.
+
+
+
+
rgb.read()
+
+ +
+ + + + + + + + + + + + + + +
<xarray.DataArray (band: 3, y: 20000, x: 2024)>
+dask.array<open_rasterio-3e88685e58afe3daaabd13b6ff29c609<this-array>, shape=(3, 20000, 2024), dtype=uint16, chunksize=(1, 2024, 2024), chunktype=numpy.ndarray>
+Coordinates:
+  * band         (band) int64 1 2 3
+  * x            (x) float64 0.5 1.5 2.5 3.5 ... 2.022e+03 2.022e+03 2.024e+03
+  * y            (y) float64 0.5 1.5 2.5 3.5 4.5 ... 2e+04 2e+04 2e+04 2e+04
+    spatial_ref  int64 0
+Attributes:
+    scale_factor:  1.0
+    add_offset:    0.0
+
+
+
+
rgb.show(xslice=slice(1000, 2000), yslice=slice(16000, 18000))
+
+ +
+
+ +
+
+ +
+
+
+ +
+
+
+

source

+
+
+

RGB_NOMAPCollection

+
+
 RGB_NOMAPCollection (obsids)
+
+

Class to deal with a set of RGB_NOMAP products.

+
/home/runner/micromamba/envs/my-env/lib/python3.11/site-packages/fastcore/docscrape.py:225: UserWarning: Unknown section Example
+  else: warn(msg)
+
+

source

+
+
+

SOURCE_PRODUCT

+
+
 SOURCE_PRODUCT (spid, saveroot=None, check_url=True)
+
+

Manage SOURCE_PRODUCT id.

+
+
obsid = 'ESP_027021_1525_RED'
+
+
+
for i in range(10):
+    for ch in [0, 1]:
+        spid = f"{obsid}{i}_{ch}"
+        try:
+            SOURCE_PRODUCT(spid).download()
+        except ConnectionError:
+            pass
+
+
File exists. Use `overwrite=True` to download fresh.
+File exists. Use `overwrite=True` to download fresh.
+File exists. Use `overwrite=True` to download fresh.
+File exists. Use `overwrite=True` to download fresh.
+File exists. Use `overwrite=True` to download fresh.
+File exists. Use `overwrite=True` to download fresh.
+File exists. Use `overwrite=True` to download fresh.
+File exists. Use `overwrite=True` to download fresh.
+File exists. Use `overwrite=True` to download fresh.
+File exists. Use `overwrite=True` to download fresh.
+File exists. Use `overwrite=True` to download fresh.
+File exists. Use `overwrite=True` to download fresh.
+File exists. Use `overwrite=True` to download fresh.
+File exists. Use `overwrite=True` to download fresh.
+File exists. Use `overwrite=True` to download fresh.
+File exists. Use `overwrite=True` to download fresh.
+File exists. Use `overwrite=True` to download fresh.
+File exists. Use `overwrite=True` to download fresh.
+
+
+
/tmp/ipykernel_1172729/2293453911.py:88: UserWarning: https://hirise-pds.lpl.arizona.edu/PDS/EDR/ESP/ORB_027000_027099/ESP_027021_1525/ESP_027021_1525_RED9_0.IMG does not exist on the server.
+  warnings.warn(f"{u} does not exist on the server.")
+/tmp/ipykernel_1172729/2293453911.py:88: UserWarning: https://hirise-pds.lpl.arizona.edu/PDS/EDR/ESP/ORB_027000_027099/ESP_027021_1525/ESP_027021_1525_RED9_1.IMG does not exist on the server.
+  warnings.warn(f"{u} does not exist on the server.")
+
+
+
+
sp = SOURCE_PRODUCT("ESP_027021_1525_RED0_0")
+
+
+
sp.local_path
+
+
Path('/home/ayek72/mnt/slowdata/planetarypy/missions/mro/hirise/ESP_027021_1525/ESP_027021_1525_RED0_0.IMG')
+
+
+
+
sp.download()
+
+
File exists. Use `overwrite=True` to download fresh.
+
+
+
+
sp.stitched_cube_path
+
+
Path('/home/ayek72/mnt/slowdata/planetarypy/missions/mro/hirise/ESP_027021_1525/ESP_027021_1525_RED0.cub')
+
+
+
+
sp.url
+
+
URL('https://hirise-pds.lpl.arizona.edu/PDS/EDR/ESP/ORB_027000_027099/ESP_027021_1525/ESP_027021_1525_RED0_0.IMG')
+
+
+
+
sp.remote_path
+
+
Path('EDR/ESP/ORB_027000_027099/ESP_027021_1525/ESP_027021_1525_RED0_0.IMG')
+
+
+
+
sp.local_path
+
+
Path('/home/ayek72/mnt/slowdata/planetarypy/missions/mro/hirise/ESP_027021_1525/ESP_027021_1525_RED0_0.IMG')
+
+
+
+
sp.channel
+
+
'0'
+
+
+
+
sp.ccd
+
+
'RED0'
+
+
+
+
sp.color
+
+
'RED'
+
+
+
+
sp.ccdno
+
+
'0'
+
+
+
+
sp.spid
+
+
'ESP_027021_1525_RED0_0'
+
+
+
+
sp
+
+
SOURCE_PRODUCT: ESP_027021_1525_RED0_0
+
+
+
+
sp.fname
+
+
'ESP_027021_1525_RED0_0.IMG'
+
+
+
+
sp.local_cube
+
+
Path('/home/ayek72/mnt/slowdata/planetarypy/missions/mro/hirise/ESP_027021_1525/ESP_027021_1525_RED0_0.cub')
+
+
+
+
sp.stitched_cube_name
+
+
'ESP_027021_1525_RED0.cub'
+
+
+
+
sp.stitched_cube_path.exists()
+
+
True
+
+
+
+

source

+
+
+

RED_PRODUCT

+
+
 RED_PRODUCT (obsid, ccdno, channel, **kwargs)
+
+

This exists to support creating a RED_PRODUCT_ID from parts of a SOURCE_PRODUCT id.

+
+
RED_PRODUCT("ESP_027021_1525", 4, 0).channel
+
+
'0'
+
+
+
+
rpid = RED_PRODUCT("ESP_039983_1390", "4", "0")
+rpid.spid
+
+
'ESP_039983_1390_RED4_0'
+
+
+
+
rpid.fname
+
+
'ESP_039983_1390_RED4_0.IMG'
+
+
+
+
rpid.url
+
+
URL('https://hirise-pds.lpl.arizona.edu/PDS/EDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED4_0.IMG')
+
+
+
+
rpid.download()
+
+
File exists. Use `overwrite=True` to download fresh.
+
+
+
+

source

+
+
+

BG_PRODUCT

+
+
 BG_PRODUCT (obsid, ccdno, channel)
+
+

Manage SOURCE_PRODUCT id.

+
+

source

+
+
+

IR_PRODUCT

+
+
 IR_PRODUCT (obsid, ccdno, channel)
+
+

Manage SOURCE_PRODUCT id.

+
+

source

+
+
+

RedMosaic

+
+
 RedMosaic (obsid)
+
+

Initialize self. See help(type(self)) for accurate signature.

+
+
obsid = "ESP_027021_1525"
+
+
+
red = RedMosaic(obsid)
+
+
+
!ls {red.local_path.parent}
+
+
B01_009958_1524_XI_27S347W.cal.cub   ESP_027021_1525_RED4_1.IMG
+B01_009958_1524_XI_27S347W.lev2.cub  ESP_027021_1525_RED4.cub
+cube2.lis                            ESP_027021_1525_RED4.map.cub
+cube.lis                             ESP_027021_1525_RED4.norm.cub
+ESP_027021_1525_RED0_0.cal.cub       ESP_027021_1525_RED5_0.cal.cub
+ESP_027021_1525_RED0_0.cub           ESP_027021_1525_RED5_0.cub
+ESP_027021_1525_RED0_0.hical.log     ESP_027021_1525_RED5_0.hical.log
+ESP_027021_1525_RED0_0.IMG           ESP_027021_1525_RED5_0.IMG
+ESP_027021_1525_RED0_1.cal.cub       ESP_027021_1525_RED5_1.cal.cub
+ESP_027021_1525_RED0_1.cub           ESP_027021_1525_RED5_1.cub
+ESP_027021_1525_RED0_1.hical.log     ESP_027021_1525_RED5_1.hical.log
+ESP_027021_1525_RED0_1.IMG           ESP_027021_1525_RED5_1.IMG
+ESP_027021_1525_RED0.cub             ESP_027021_1525_RED5.cub
+ESP_027021_1525_RED0.map.cub         ESP_027021_1525_RED5.map.cub
+ESP_027021_1525_RED0.norm.cub        ESP_027021_1525_RED5.map.cub.aux.xml
+ESP_027021_1525_RED1_0.cal.cub       ESP_027021_1525_RED5.norm.cub
+ESP_027021_1525_RED1_0.cub           ESP_027021_1525_RED6_0.cal.cub
+ESP_027021_1525_RED1_0.hical.log     ESP_027021_1525_RED6_0.cub
+ESP_027021_1525_RED1_0.IMG           ESP_027021_1525_RED6_0.hical.log
+ESP_027021_1525_RED1_1.cal.cub       ESP_027021_1525_RED6_0.IMG
+ESP_027021_1525_RED1_1.cub           ESP_027021_1525_RED6_1.cal.cub
+ESP_027021_1525_RED1_1.hical.log     ESP_027021_1525_RED6_1.cub
+ESP_027021_1525_RED1_1.IMG           ESP_027021_1525_RED6_1.hical.log
+ESP_027021_1525_RED1.cub             ESP_027021_1525_RED6_1.IMG
+ESP_027021_1525_RED1.map.cub         ESP_027021_1525_RED6.cub
+ESP_027021_1525_RED1.norm.cub        ESP_027021_1525_RED6.map.cub
+ESP_027021_1525_RED2_0.cal.cub       ESP_027021_1525_RED6.norm.cub
+ESP_027021_1525_RED2_0.cub           ESP_027021_1525_RED7_0.cal.cub
+ESP_027021_1525_RED2_0.hical.log     ESP_027021_1525_RED7_0.cub
+ESP_027021_1525_RED2_0.IMG           ESP_027021_1525_RED7_0.hical.log
+ESP_027021_1525_RED2_1.cal.cub       ESP_027021_1525_RED7_0.IMG
+ESP_027021_1525_RED2_1.cub           ESP_027021_1525_RED7_1.cal.cub
+ESP_027021_1525_RED2_1.hical.log     ESP_027021_1525_RED7_1.cub
+ESP_027021_1525_RED2_1.IMG           ESP_027021_1525_RED7_1.hical.log
+ESP_027021_1525_RED2.cub             ESP_027021_1525_RED7_1.IMG
+ESP_027021_1525_RED2.map.cub         ESP_027021_1525_RED7.cub
+ESP_027021_1525_RED2.norm.cub        ESP_027021_1525_RED7.map.cub
+ESP_027021_1525_RED3_0.cal.cub       ESP_027021_1525_RED7.norm.cub
+ESP_027021_1525_RED3_0.cub           ESP_027021_1525_RED8_0.cal.cub
+ESP_027021_1525_RED3_0.hical.log     ESP_027021_1525_RED8_0.cub
+ESP_027021_1525_RED3_0.IMG           ESP_027021_1525_RED8_0.hical.log
+ESP_027021_1525_RED3_1.cal.cub       ESP_027021_1525_RED8_0.IMG
+ESP_027021_1525_RED3_1.cub           ESP_027021_1525_RED8_1.cal.cub
+ESP_027021_1525_RED3_1.hical.log     ESP_027021_1525_RED8_1.cub
+ESP_027021_1525_RED3_1.IMG           ESP_027021_1525_RED8_1.hical.log
+ESP_027021_1525_RED3.cub             ESP_027021_1525_RED8_1.IMG
+ESP_027021_1525_RED3.map.cub         ESP_027021_1525_RED8.cub
+ESP_027021_1525_RED3.norm.cub        ESP_027021_1525_RED8.map.cub
+ESP_027021_1525_RED4_0.cal.cub       ESP_027021_1525_RED8.norm.cub
+ESP_027021_1525_RED4_0.cub           ESP_027021_1525_RED.LBL
+ESP_027021_1525_RED4_0.hical.log     normalized.lis
+ESP_027021_1525_RED4_0.IMG           point.txt
+ESP_027021_1525_RED4_1.cal.cub       print.prt
+ESP_027021_1525_RED4_1.cub           set_overlaps.txt
+ESP_027021_1525_RED4_1.hical.log
+
+
+ + +
+ +
+ + +
+ + + + \ No newline at end of file diff --git a/api/pds.apps.html b/api/pds.apps.html new file mode 100644 index 0000000..3dcab84 --- /dev/null +++ b/api/pds.apps.html @@ -0,0 +1,1669 @@ + + + + + + + + + + +planetarypy - Apps + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Apps

+
+ +
+
+ User interface apps/functions to make using the PDS tools easy. +
+
+ + +
+ + + + +
+ + +
+ + +
+

source

+
+

find_indexes

+
+
 find_indexes (instrument:str)
+
+

Find existing indexes for an instrument.

+ + + + + + + + + + + + + + + + + + + + +
TypeDetails
instrumentstrDotted mission.instrument key, e.g. cassini.iss
ReturnslistList of configured index names
+
+
find_indexes("cassini.iss")
+
+
['index', 'inventory', 'moon_summary', 'ring_summary', 'saturn_summary']
+
+
+
+
find_indexes("mro.ctx")
+
+
['edr']
+
+
+
+

source

+
+
+

get_index

+
+
 get_index (instr:str, index_name:str='', refresh:bool=True,
+            force:bool=False)
+
+

Example: get_index(“cassini.iss”, “index”)

+ ++++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
TypeDefaultDetails
instrstrDotted instrument index, e.g. cassini.iss
index_namestrIndex name, for exmample ‘moon_summary. Optional’
refreshboolTrueswitch to refresh an index (i.e. download if update available).
Set to False for faster return time to avoid web scraping
forceboolFalseswitch off for faster return time.
ReturnsDataFrameThe PDS index convert to pandas DataFrame
+
+
instr = "cassini.iss"
+index_name = "moon_summary"
+
+
+
index = get_index(instr, index_name, refresh=False)
+
+
+
index
+
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
VOLUME_IDFILE_SPECIFICATION_NAMEOPUS_IDTARGET_NAMEMINIMUM_PLANETOCENTRIC_LATITUDEMAXIMUM_PLANETOCENTRIC_LATITUDEMINIMUM_PLANETOGRAPHIC_LATITUDEMAXIMUM_PLANETOGRAPHIC_LATITUDEMINIMUM_IAU_LONGITUDEMAXIMUM_IAU_LONGITUDE...MAXIMUM_EMISSION_ANGLESUB_SOLAR_PLANETOCENTRIC_LATITUDESUB_SOLAR_PLANETOGRAPHIC_LATITUDESUB_OBSERVER_PLANETOCENTRIC_LATITUDESUB_OBSERVER_PLANETOGRAPHIC_LATITUDESUB_SOLAR_IAU_LONGITUDESUB_OBSERVER_IAU_LONGITUDECENTER_RESOLUTIONCENTER_DISTANCECENTER_PHASE_ANGLE
0COISS_2001data/1454725799_1455008789/N1454725799_1.LBLco-iss-n1454725799RHEA-999.0-999.0-999.0-999.0-999.0-999.0...-999.0-25.206-25.442-16.566-16.558183.907252.947423.635670701354.36664.429
1COISS_2001data/1454725799_1455008789/N1454725799_1.LBLco-iss-n1454725799HELENE-999.0-999.0-999.0-999.0-999.0-999.0...-999.0-25.532-50.716-16.532-36.57148.17217.149424.3690270823757.00264.345
2COISS_2001data/1454725799_1455008789/N1454725799_1.LBLco-iss-n1454725799TELESTO-999.0-999.0-999.0-999.0-999.0-999.0...-999.0-26.061-51.51-15.639-21.616189.199257.807424.2874670810144.51964.28
3COISS_2001data/1454725799_1455008789/N1454726579_1.LBLco-iss-n1454726579TITAN-36.111-36.111-36.111-36.1110.0360.0...54.704-25.325-25.325-16.28-16.28340.09247.855428.8967371579395.06663.37
4COISS_2001data/1454725799_1455008789/N1454727359_1.LBLco-iss-n1454727359HYPERION-999.0-999.0-999.0-999.0-999.0-999.0...-999.011.77725.90744.10457.544173.985237.769418.9454569918606.58663.093
..................................................................
385714COISS_2116data/1884017637_1884113741/N1884017911_1.LBLco-iss-n1884017911TITAN-14.35272.101-14.35272.101229.956329.975...89.06926.64426.64423.59923.59932.084299.3894.64069774493.281.887
385715COISS_2116data/1884017637_1884113741/N1884018021_1.LBLco-iss-n1884018021TITAN-14.59771.882-14.59771.882230.932330.255...88.91326.64426.64423.59423.59432.107299.4154.64263774816.73181.888
385716COISS_2116data/1884017637_1884113741/N1884018579_1.LBLco-iss-n1884018579TITAN-14.43572.643-14.43572.643228.942330.644...88.86926.64426.64423.5723.5732.217299.5369.30328776321.46681.889
385717COISS_2116data/1884017637_1884113741/N1884091792_1.LBLco-iss-n1884091792DAPHNIS-999.0-999.0-999.0-999.0-999.0-999.0...-999.026.68439.96625.32138.64294.939124.6414.56619762060.157127.157
385718COISS_2116data/1884017637_1884113741/N1884109343_1.LBLco-iss-n1884109343PANDORA40.38463.74956.97376.9520.0360.0...62.43526.68649.38633.09553.259335.495142.0163.45805577120.582118.858
+ +

385719 rows × 35 columns

+
+
+
+

Indexes can be given as 2 parameters (“cassini.iss”, “ring_summary”) or one (“cassini.iss.ring_summary”):

+
+
index = get_index("cassini.iss", "ring_summary", refresh=False)
+index.head()
+
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
VOLUME_IDFILE_SPECIFICATION_NAMEOPUS_IDMINIMUM_RIGHT_ASCENSIONMAXIMUM_RIGHT_ASCENSIONMINIMUM_DECLINATIONMAXIMUM_DECLINATIONMINIMUM_RING_RADIUSMAXIMUM_RING_RADIUSFINEST_RING_INTERCEPT_RESOLUTION...RING_CENTER_DISTANCESUB_SOLAR_RING_LONGITUDESUB_OBSERVER_RING_LONGITUDERING_CENTER_PHASE_ANGLERING_CENTER_INCIDENCE_ANGLERING_CENTER_NORTH_BASED_INCIDENCE_ANGLERING_CENTER_EMISSION_ANGLERING_CENTER_NORTH_BASED_EMISSION_ANGLESOLAR_RING_OPENING_ANGLEOBSERVER_RING_OPENING_ANGLE
0COISS_2001data/1454725799_1455008789/N1454725799_1.LBLco-iss-n145472579935.52839835.9055559.71963710.091212205899.3351098621.586419.0137...70874998.947284.523215.95164.0764.589115.41173.676106.324-25.411-16.324
1COISS_2001data/1454725799_1455008789/N1454726579_1.LBLco-iss-n145472657936.66289837.0390389.5901149.960833721136.1551745689.307421.97145...70870851.371284.524215.95164.0764.589115.41173.676106.324-25.411-16.324
2COISS_2001data/1454725799_1455008789/N1454727359_1.LBLco-iss-n145472735936.92806637.3043349.87959310.250111042341.4382186830.92414.79041...70866703.094284.524215.95164.07164.589115.41173.676106.324-25.411-16.324
3COISS_2001data/1454725799_1455008789/N1454728139_1.LBLco-iss-n145472813928.1004228.4796186.2247096.601574-999.0-999.0-999.0...70862557.207284.524215.95164.07164.589115.41173.676106.324-25.411-16.324
4COISS_2001data/1454725799_1455008789/N1454728919_1.LBLco-iss-n145472891937.98141838.35779110.61194710.9816973865717.5893905151.343405.91234...70858406.794284.525215.95164.07164.589115.41173.676106.324-25.411-16.324
+ +

5 rows × 59 columns

+
+
+
+
+
index = get_index("cassini.iss.ring_summary", refresh=False)
+index.head()
+
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
VOLUME_IDFILE_SPECIFICATION_NAMEOPUS_IDMINIMUM_RIGHT_ASCENSIONMAXIMUM_RIGHT_ASCENSIONMINIMUM_DECLINATIONMAXIMUM_DECLINATIONMINIMUM_RING_RADIUSMAXIMUM_RING_RADIUSFINEST_RING_INTERCEPT_RESOLUTION...RING_CENTER_DISTANCESUB_SOLAR_RING_LONGITUDESUB_OBSERVER_RING_LONGITUDERING_CENTER_PHASE_ANGLERING_CENTER_INCIDENCE_ANGLERING_CENTER_NORTH_BASED_INCIDENCE_ANGLERING_CENTER_EMISSION_ANGLERING_CENTER_NORTH_BASED_EMISSION_ANGLESOLAR_RING_OPENING_ANGLEOBSERVER_RING_OPENING_ANGLE
0COISS_2001data/1454725799_1455008789/N1454725799_1.LBLco-iss-n145472579935.52839835.9055559.71963710.091212205899.3351098621.586419.0137...70874998.947284.523215.95164.0764.589115.41173.676106.324-25.411-16.324
1COISS_2001data/1454725799_1455008789/N1454726579_1.LBLco-iss-n145472657936.66289837.0390389.5901149.960833721136.1551745689.307421.97145...70870851.371284.524215.95164.0764.589115.41173.676106.324-25.411-16.324
2COISS_2001data/1454725799_1455008789/N1454727359_1.LBLco-iss-n145472735936.92806637.3043349.87959310.250111042341.4382186830.92414.79041...70866703.094284.524215.95164.07164.589115.41173.676106.324-25.411-16.324
3COISS_2001data/1454725799_1455008789/N1454728139_1.LBLco-iss-n145472813928.1004228.4796186.2247096.601574-999.0-999.0-999.0...70862557.207284.524215.95164.07164.589115.41173.676106.324-25.411-16.324
4COISS_2001data/1454725799_1455008789/N1454728919_1.LBLco-iss-n145472891937.98141838.35779110.61194710.9816973865717.5893905151.343405.91234...70858406.794284.525215.95164.07164.589115.41173.676106.324-25.411-16.324
+ +

5 rows × 59 columns

+
+
+
+
+
get_index("mro.ctx.edr", refresh=False)
+
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
VOLUME_IDFILE_SPECIFICATION_NAMEORIGINAL_PRODUCT_IDPRODUCT_IDIMAGE_TIMEINSTRUMENT_IDINSTRUMENT_MODE_IDLINE_SAMPLESLINESSPATIAL_SUMMING...SUB_SOLAR_LATITUDESUB_SPACECRAFT_LONGITUDESUB_SPACECRAFT_LATITUDESOLAR_DISTANCESOLAR_LONGITUDELOCAL_TIMEIMAGE_SKEW_ANGLERATIONALE_DESCDATA_QUALITY_DESCORBIT_NUMBER
0MROX_0001DATA/CRU_000001_9999_XN_99N999W.IMG4A_04_0001000400CRU_000001_9999_XN_99N999W2005-08-30 15:40:21.549CTXNIFL505610241...0.00.00.00.0278.8910.160.0Instrument checkout image of spaceOK-4242
1MROX_0001DATA/CRU_000002_9999_XN_99N999W.IMG4A_04_0001000500CRU_000002_9999_XN_99N999W2005-09-08 15:59:45.313CTXNIFL5056153601...0.00.00.00.0284.484.60.0Calibration image of the MoonOK-4126
2MROX_0001DATA/CRU_000003_9999_XN_99N999W.IMG4A_04_0001000600CRU_000003_9999_XN_99N999W2005-09-08 16:03:37.927CTXNIFL505620481...0.00.00.00.0284.484.660.0Calibration image of Omega Centauri (globular ...OK-4126
3MROX_0001DATA/CRU_000004_9999_XN_99N999W.IMG4A_04_0001000700CRU_000004_9999_XN_99N999W2005-09-08 16:08:23.841CTXNIFL505620481...0.00.00.00.0284.484.740.0Calibration image of Omega Centauri (globular ...OK-4126
4MROX_0001DATA/CRU_000005_9999_XN_99N999W.IMG4A_04_0001000800CRU_000005_9999_XN_99N999W2005-09-08 16:11:18.649CTXNIFL5056215041...0.00.00.00.0284.484.790.0Calibration image of the MoonOK-4126
..................................................................
138410MROX_4461DATA/U14_076622_1804_XN_00N105W.IMG4A_04_118404B100U14_076622_1804_XN_00N105W2022-11-30 17:29:26.742CTXNIFL5056337921...-5.6105.050.45228081883.9346.914.3989.7Terrain northwest of Noctis LabyrinthusOK76622
138411MROX_4461DATA/U14_076622_2009_XI_20N108W.IMG4A_04_118504B200U14_076622_2009_XI_20N108W2022-11-30 17:36:13.062CTXITL505671681...-5.6107.6120.98228082990.5346.914.390.1Candidate impact site formed at most between M...OK76622
138412MROX_4461DATA/U14_076623_1977_XN_17N133W.IMG4A_04_118404B300U14_076623_1977_XN_17N133W2022-11-30 19:26:53.410CTXNIFL5056358401...-5.59134.4517.69228097986.1346.9414.3790.1Ride-along with HiRISEOK76623
138413MROX_4461DATA/U14_076625_1182_XN_61S177W.IMG4A_04_118404B800U14_076625_1182_XN_61S177W2022-11-30 22:46:27.741CTXNIFL5056522241...-5.56177.43-61.87228126022.3347.0114.7190.4Southern highlandsOK76625
138414MROX_4461DATA/U14_076625_1714_XN_08S185W.IMG4A_04_118404B900U14_076625_1714_XN_08S185W2022-11-30 23:02:50.690CTXNIFL5056522241...-5.55185.83-8.75228127015.7347.0214.4590.5Ride-along with HiRISEOK76625
+ +

138415 rows × 51 columns

+
+
+
+
+

source

+
+
+

find_instruments

+
+
 find_instruments (mission:str)
+
+

Find existing instruments for a mission.

+ + + + + + + + + + + + + + + + + + + + +
TypeDetails
missionstrMission string, e.g. “cassini”
ReturnslistList of configured instrument names
+
+
find_instruments("cassini")
+
+
['iss', 'uvis']
+
+
+
+
find_instruments("mro")
+
+
['hirise', 'ctx']
+
+
+
+
from nbdev import nbdev_export
+nbdev_export()
+
+ + +
+ +
+ +
+ + + + \ No newline at end of file diff --git a/api/pds.crism_index.html b/api/pds.crism_index.html new file mode 100644 index 0000000..f43a6d2 --- /dev/null +++ b/api/pds.crism_index.html @@ -0,0 +1,927 @@ + + + + + + + + + + +planetarypy - CRISM PDS Index + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

CRISM PDS Index

+
+ +
+
+ Tools to work with the CRISM PDS index files +
+
+ + +
+ + + + +
+ + +
+ + +
+
url = URL("https://pds-geosciences.wustl.edu/mro/mro-m-crism-5-rdr-mptargeted-v1/mrocr_4001/index/mtrdr0705_index.lbl")
+
+
+

source

+
+

MTRDRIndex

+
+
 MTRDRIndex (url)
+
+

Index manager class.

+

This class manages one index, identified by a dotted key, e.g. cassini.iss.ring_summary

+
+
index = MTRDRIndex(url=url)
+
+
+
index.download()
+
+ +
+
+ +
+
+
Downloaded /home/ayek72/mnt/slowdata/planetarypy/missions/mro/crism/indexes/mtrdr/mtrdr0705_index.lbl and /home/ayek72/mnt/slowdata/planetarypy/missions/mro/crism/indexes/mtrdr/mtrdr0705_index.tab
+Done.
+
+
+
+
index.convert_to_parquet()
+
+
Done.
+
+
+
+
index.parquet
+
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
VOLUME_IDPRODUCT_IDPRODUCT_TYPEFILE_SPECIFICATION_NAMEPARTICIPATING_INSTRUMENTSPRODUCT_CREATION_TIMESTART_TIMESTOP_TIMESPACECRAFT_CLOCK_START_COUNTSPACECRAFT_CLOCK_STOP_COUNT...WESTERNMOST_LONGITUDEEASTERNMOST_LONGITUDELOWER_RIGHT_LATITUDELOWER_RIGHT_LONGITUDELOWER_LEFT_LATITUDELOWER_LEFT_LONGITUDEUPPER_RIGHT_LATITUDEUPPER_RIGHT_LONGITUDEUPPER_LEFT_LATITUDEUPPER_LEFT_LONGITUDE
0MROCR_4001FRT00005F0C_07_IF163J_MTR3MPTARGETED_RDRMTRDR/2007/2007_148/FRT00005F0C/FRT00005F0C_07...<NA>2015-06-12 09:00:202007-05-28 17:30:38.6052007-05-28 17:32:22.3392/0864840658.002252/0864840761.48344...52.853.267-99.999-999.999-99.999-999.999-99.999-999.999-99.999-999.999
1MROCR_4001FRT00005F0C_07_WV163J_MTR3MPTARGETED_RDRMTRDR/2007/2007_148/FRT00005F0C/FRT00005F0C_07...<NA>2015-06-12 09:00:202007-05-28 17:30:38.6052007-05-28 17:32:22.3392/0864840658.002252/0864840761.48344...-999.999-999.999-99.999-999.999-99.999-999.999-99.999-999.999-99.999-999.999
2MROCR_4001FRT00005F0C_07_IN163J_MTR3MPTARGETED_RDRMTRDR/2007/2007_148/FRT00005F0C/FRT00005F0C_07...<NA>2015-06-12 09:04:092007-05-28 17:30:38.6052007-05-28 17:32:22.3392/0864840658.002252/0864840761.48344...52.853.267-99.999-999.999-99.999-999.999-99.999-999.999-99.999-999.999
3MROCR_4001FRT00005F0C_07_DE163L_MTR1MAP_PROJECTED_DDRMTRDR/2007/2007_148/FRT00005F0C/FRT00005F0C_07...<NA>2015-06-12 09:04:032007-05-28 17:30:38.6052007-05-28 17:32:22.3392/864840658:2252/864840761:48344...52.853.267-62.7153.27-62.7652.84-62.5953.23-62.652.8
4MROCR_4001FRT00005F0C_07_SU163J_MTR3MPTARGETED_RDRMTRDR/2007/2007_148/FRT00005F0C/FRT00005F0C_07...<NA>2015-06-12 09:00:292007-05-28 17:30:38.6052007-05-28 17:32:22.3392/0864840658.002252/0864840761.48344...52.853.267-99.999-999.999-99.999-999.999-99.999-999.999-99.999-999.999
..................................................................
553MROCR_4001FRT00005DAC_07_IF165J_MTR3MPTARGETED_RDRMTRDR/2007/2007_144/FRT00005DAC/FRT00005DAC_07...<NA>2015-06-12 07:20:092007-05-24 07:16:57.9262007-05-24 07:18:57.6602/0864458237.210462/0864458357.03629...156.527156.771-99.999-999.999-99.999-999.999-99.999-999.999-99.999-999.999
554MROCR_4001FRT00005DAC_07_DE165L_MTR1MAP_PROJECTED_DDRMTRDR/2007/2007_144/FRT00005DAC/FRT00005DAC_07...<NA>2015-06-12 07:22:512007-05-24 07:16:57.9262007-05-24 07:18:57.6602/864458237:210462/864458357:3629...156.527156.7719.67156.779.66156.549.88156.759.84156.53
555MROCR_4001FRT00005DAC_07_WV165J_MTR3MPTARGETED_RDRMTRDR/2007/2007_144/FRT00005DAC/FRT00005DAC_07...<NA>2015-06-12 07:20:092007-05-24 07:16:57.9262007-05-24 07:18:57.6602/0864458237.210462/0864458357.03629...-999.999-999.999-99.999-999.999-99.999-999.999-99.999-999.999-99.999-999.999
556MROCR_4001FRT00005DAC_07_IN165J_MTR3MPTARGETED_RDRMTRDR/2007/2007_144/FRT00005DAC/FRT00005DAC_07...<NA>2015-06-12 07:22:562007-05-24 07:16:57.9262007-05-24 07:18:57.6602/0864458237.210462/0864458357.03629...156.527156.771-99.999-999.999-99.999-999.999-99.999-999.999-99.999-999.999
557MROCR_4001FRT00005DAC_07_SU165J_MTR3MPTARGETED_RDRMTRDR/2007/2007_144/FRT00005DAC/FRT00005DAC_07...<NA>2015-06-12 07:20:172007-05-24 07:16:57.9262007-05-24 07:18:57.6602/0864458237.210462/0864458357.03629...156.527156.771-99.999-999.999-99.999-999.999-99.999-999.999-99.999-999.999
+ +

558 rows × 57 columns

+
+
+
+ + +
+ +
+ + +
+ + + + \ No newline at end of file diff --git a/api/pds.ctx_index.html b/api/pds.ctx_index.html new file mode 100644 index 0000000..fe1f60e --- /dev/null +++ b/api/pds.ctx_index.html @@ -0,0 +1,686 @@ + + + + + + + + + + +planetarypy - CTX Index + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

CTX Index

+
+ +
+
+ Scraping the latest CTX index file from the latest added volume. +
+
+ + +
+ + + + +
+ + +
+ + +
+

source

+
+

CTXIndex

+
+
 CTXIndex ()
+
+

Initialize self. See help(type(self)) for accurate signature.

+
+
ctx = CTXIndex()
+
+
+
ctx.volumes_table
+
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameLast modified
2mrox_0001/05-Jun-2007 10:15
3mrox_0001_md5.txt10-Dec-2019 04:32
4mrox_0002/05-Jun-2007 10:15
5mrox_0002_md5.txt09-Dec-2019 19:14
6mrox_0003/05-Jun-2007 10:15
.........
9515mrox_4757_md5.txt15-Nov-2023 23:23
9516mrox_4758/15-Nov-2023 23:08
9517mrox_4758_md5.txt15-Nov-2023 23:23
9518mrox_4759/15-Nov-2023 23:10
9519mrox_4759_md5.txt15-Nov-2023 23:23
+ +

9518 rows × 2 columns

+
+
+
+
+
ctx.latest_release_folder
+
+
'mrox_4759/'
+
+
+
+
ctx.latest_release_number
+
+
'4759'
+
+
+
+
ctx.latest_index_label_url
+
+
URL('https://planetarydata.jpl.nasa.gov/img/data/mro/mars_reconnaissance_orbiter/ctx/mrox_4759/index/cumindex.lbl')
+
+
+ + +
+ +
+ +
+ + + + \ No newline at end of file diff --git a/api/pds.indexes.html b/api/pds.indexes.html new file mode 100644 index 0000000..feecef8 --- /dev/null +++ b/api/pds.indexes.html @@ -0,0 +1,784 @@ + + + + + + + + + + +planetarypy - PDS Indexes + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

PDS Indexes

+
+ +
+
+ Support tools to work with PDS index files. +
+
+ + +
+ + + + +
+ + +
+ + +
+

source

+
+

Index

+
+
 Index (key:str, url:str=None, check_update:bool=True)
+
+

Index manager class.

+

This class manages one index, identified by a dotted key, e.g. cassini.iss.ring_summary

+ ++++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
TypeDefaultDetails
keystrNested (dotted) key, e.g. cassini.iss.ring_summary
urlstrNoneURL to index. If not given, will be read from config object.
check_updateboolTrueswitch if dynamic URLS will be derived upon start
+
+

source

+
+
+

Index.parse_key

+
+
 Index.parse_key (key:str)
+
+

Take care of different ways how the key could be structured.

+

This involves adding the sub-key indexes for the config file structure, which is something the user of this class should not need to know.

+ + + + + + + + + + + + + + + +
TypeDetails
keystrdotted key
+
+

source

+
+
+

Index.download

+
+
 Index.download ()
+
+

Wrapping URLs for downloading PDS indices and their label files.

+
+

source

+
+
+

Index.update_available

+
+
 Index.update_available ()
+
+

Property indicating if the index needs to be downloaded.

+
+
key = "missions.cassini.iss.indexes.moon_summary"
+key = "missions.lro.lroc.edr"
+
+
+
index = Index(key, check_update=True)
+index
+
+
Key: missions.lro.lroc.indexes.edr
+URL: http://pds.lroc.asu.edu/data/LRO-L-LROC-2-EDR-V1.0/LROLRC_0048C/INDEX/CUMINDEX.LBL
+Timestamp: 2023-10-10 15:30:56.195462
+
+
+
+
index.key
+
+
'missions.lro.lroc.indexes.edr'
+
+
+
+
index.label_filename
+
+
Path('CUMINDEX.LBL')
+
+
+
+
index.url
+
+
'http://pds.lroc.asu.edu/data/LRO-L-LROC-2-EDR-V1.0/LROLRC_0048C/INDEX/CUMINDEX.LBL'
+
+
+
+
index.local_dir
+
+
Path('/home/ayek72/mnt/slowdata/planetarypy/missions/lro/lroc/indexes/edr')
+
+
+
+
if index.check_update and index.update_available:
+    index.download()
+
+

The key can be provided * with or without the leading ‘missions’ * with or without the internal indexes level of the config file

+
+
Index("cassini.iss.moon_summary")
+
+
Key: missions.cassini.iss.indexes.moon_summary
+URL: https://pds-rings.seti.org/holdings/metadata/COISS_2xxx/COISS_2999/COISS_2999_moon_summary.lbl
+Timestamp: 2019-06-08 16:28:22
+
+
+
+
Index("cassini.iss.indexes.moon_summary")
+
+
Key: missions.cassini.iss.indexes.moon_summary
+URL: https://pds-rings.seti.org/holdings/metadata/COISS_2xxx/COISS_2999/COISS_2999_moon_summary.lbl
+Timestamp: 2019-06-08 16:28:22
+
+
+
+
index.isotimestamp
+
+
'2023-10-10T15:30:56.195462'
+
+
+
+
index.mission_key
+
+
'lro'
+
+
+
+
index.local_dir
+
+
Path('/home/ayek72/mnt/slowdata/planetarypy/missions/lro/lroc/indexes/edr')
+
+
+
+
index.key_tokens[:2]
+
+
['missions', 'lro']
+
+
+
+
index.instrument_key
+
+
'lro.lroc'
+
+
+
+
config.get_value(index.instrument_key)
+
+
{'indexes': {'edr': {'url': 'http://pds.lroc.asu.edu/data/LRO-L-LROC-2-EDR-V1.0/LROLRC_0048C/INDEX/CUMINDEX.LBL', 'timestamp': '2023-10-10T15:30:56.195462'}}}
+
+
+
+
index = Index('mro.ctx.edr', check_update=False)
+
+
+
index.url
+
+
''
+
+
+
+
index.label_filename
+
+
Path('/home/ayek72/mnt/slowdata/planetarypy/missions/mro/ctx/indexes/edr/cumindex.lbl')
+
+
+
+
list(index.local_dir.glob("*.[lL][bB][lL]"))
+
+
[Path('/home/ayek72/mnt/slowdata/planetarypy/missions/mro/ctx/indexes/edr/cumindex.lbl')]
+
+
+ + +
+ +
+ +
+ + + + \ No newline at end of file diff --git a/api/pds.lroc_index.html b/api/pds.lroc_index.html new file mode 100644 index 0000000..f1a22a5 --- /dev/null +++ b/api/pds.lroc_index.html @@ -0,0 +1,613 @@ + + + + + + + + + + +planetarypy - LROC Index + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

LROC Index

+
+ +
+
+ LROC Index is not at a fixed URL, so need to determine dynamically. +
+
+ + +
+ + + + +
+ + +
+ + +
+

EDR vs RDR etc.

+

I cannot distinguish between different data levels for dynamic index URLs yet, as is required for LROC, so for now I only implement the EDR index, pretending it’s the only one!

+
+

source

+
+

LROCIndex

+
+
 LROCIndex ()
+
+

Initialize self. See help(type(self)) for accurate signature.

+
+
lroc = LROCIndex()
+
+
+
lroc.latest_release_folder
+
+
'LROLRC_0056A/'
+
+
+
+
lroc.latest_release_number
+
+
'0056A'
+
+
+
+
lroc.latest_index_label_url
+
+
URL('https://pds.lroc.asu.edu/data/LRO-L-LROC-2-EDR-V1.0/LROLRC_0056A/INDEX/CUMINDEX.LBL')
+
+
+ + +
+
+ +
+ +
+ + + + \ No newline at end of file diff --git a/api/pds.opusapi.html b/api/pds.opusapi.html new file mode 100644 index 0000000..759131e --- /dev/null +++ b/api/pds.opusapi.html @@ -0,0 +1,611 @@ + + + + + + + + + + +planetarypy - OPUSAPI class + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

OPUSAPI class

+
+ +
+
+ A simple wrapper to get data from the Rings-Moons Systems PDS node +
+
+ + +
+ + + + +
+ + +
+ + +
+

source

+
+

OPUS

+
+
 OPUS (silent=False)
+
+

Manage OPUS API requests.

+
+

source

+
+
+

OPUSObsID

+
+
 OPUSObsID (obsid_data)
+
+

Manage observation IDs from OPUS responses.

+
+

source

+
+
+

OPUSImageURL

+
+
 OPUSImageURL (jsonlist)
+
+

Manage URLS from the OPUS response.

+
+
opus = OPUS()
+
+
+
opus.query_image_id("FUV2003_363_00_22")
+
+ + +
+ +
+ +
+ + + + \ No newline at end of file diff --git a/api/pds.utils.html b/api/pds.utils.html new file mode 100644 index 0000000..05dbf38 --- /dev/null +++ b/api/pds.utils.html @@ -0,0 +1,746 @@ + + + + + + + + + + +planetarypy - PDS Utils + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

PDS Utils

+
+ +
+
+ Utilities used by the pds sub-package. +
+
+ + +
+ + + + +
+ + +
+ + +
+

source

+
+

IndexLabel

+
+
 IndexLabel (labelpath:Union[str,pathlib.Path])
+
+

Support working with label files of PDS Index tables.

+ +++++ + + + + + + + + + + + + + + +
TypeDetails
labelpathUnionPath to the labelfile for a PDS Indexfile.
The actual table should reside in the same folder to be automatically parsed
when calling the read_index_data method.
+
+

source

+
+
+

index_to_df

+
+
 index_to_df (indexpath:Union[str,pathlib.Path],
+              label:__main__.IndexLabel, convert_times=True)
+
+

The main reader function for PDS Indexfiles.

+

In conjunction with an IndexLabel object that figures out the column widths, this reader should work for all PDS TAB files.

+ ++++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
TypeDefaultDetails
indexpathUnionPath to the index TAB file
labelIndexLabelLabel object that has both the column names and the columns widths as attributes
‘colnames’ and ‘colspecs’
convert_timesboolTrueSwitch to control if to convert columns with “TIME” in name (unless COUNT is as well in name) to datetime
+
+

source

+
+
+

PVLColumn

+
+
 PVLColumn (pvlobj)
+
+

Manages just one of the columns in a table that is described via PVL.

+
+

source

+
+
+

decode_line

+
+
 decode_line (linedata:str, labelpath:Union[str,pathlib.Path])
+
+

Decode one line of tabbed data with the appropriate label file.

+ +++++ + + + + + + + + + + + + + + + + + + + +
TypeDetails
linedatastrOne line of a .tab data file
labelpathUnionPath to the appropriate label that describes the data.
+
+

source

+
+
+

find_mixed_type_cols

+
+
 find_mixed_type_cols (df:pandas.core.frame.DataFrame, fix:bool=True)
+
+

For a given dataframe, find the columns that are of mixed type.

+

Tool to help with the performance warning when trying to save a pandas DataFrame as a HDF. When a column changes datatype somewhere, pickling occurs, slowing down the reading process of the HDF file.

+ ++++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
TypeDefaultDetails
dfDataFrameDataframe to be searched for mixed data-types
fixboolTrueSwitch to control if NaN values in these problem columns should be replaced by the string ‘UNKNOWN’
ReturnslistList of column names that have data type changes within themselves.
+
+

source

+
+
+

fix_hirise_edrcumindex

+
+
 fix_hirise_edrcumindex (infname:Union[str,pathlib.Path],
+                         outfname:Union[str,pathlib.Path])
+
+

Fix HiRISE EDRCUMINDEX.

+

The HiRISE EDRCUMINDEX has some broken lines where the SCAN_EXPOSURE_DURATION is of format F10.4 instead of the defined F9.4. This function simply replaces those incidences with one less decimal fraction, so 20000.0000 becomes 20000.000.

+ + + + + + + + + + + + + + + + + + + + +
TypeDetails
infnameUnionPath to broken EDRCUMINDEX.TAB
outfnameUnionPath where to store the fixed TAB file
+ + +
+ +
+ +
+ + + + \ No newline at end of file diff --git a/api/spice.kernels.html b/api/spice.kernels.html new file mode 100644 index 0000000..b848128 --- /dev/null +++ b/api/spice.kernels.html @@ -0,0 +1,1984 @@ + + + + + + + + + + +planetarypy - SPICE Kernels + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

SPICE Kernels

+
+ +
+
+ Tools to manage SPICE kernels +
+
+ + +
+ + + + +
+ + +
+ + +
+

Intro

+

Feature list for this module:

+
    +
  • Receive the list of supported datasets for automatic retrieval of archived SPICE kernels +
      +
    • The supported datasets are tabled here at NAIF: https://naif.jpl.nasa.gov/naif/data_archived.html
      • +
    • +
  • Receive the list of required SPICE kernels for a given mission and time range
    • +
  • Automatic download of kernels for a given mission and time range either into a given location or the planetarypy local archive.
    • +
+

As always in planetarypy the general design philosophy is to first develop a management class to give the user full control over all the details, and then add easy-to-use function for the end-user that do the most frequently used things in one go. (See section “User Functions”)

+
+
+

Identifying and downloading kernel sets

+

One repeating task for SPICE calculations is the identification and retrieval of all SPICE kernels for a mission for a given time interval.

+

The folks at NAIF offer a “Subset” feature at their servers. Here we set up a table of the currently supported datasets:

+
+
datasets
+
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
pathMission NamePDS3 or PDS4Data Size (GB)Start TimeStop Time
shorthand
bcbc/bc_spiceBepiColombo41.12018-10-202023-01-01
cassinico-s_j_e_v-spice-6-v1.0/cosp_1000Cassini Orbiter362.51997-10-152017-09-15
clementineclem1-l-spice-6-v1.0/clsp_1000Clementine30.81994-01-261994-05-07
dartdart/dart_spiceDART49.12021-11-092050-01-01
dawndawn-m_a-spice-6-v1.0/dawnsp_1000DAWN386.42007-09-272018-10-31
didi-c-spice-6-v1.0/disp_1000Deep Impact30.72005-01-122005-08-09
ds1ds1-a_c-spice-6-v1.0/ds1sp_1000Deep Space 130.91998-10-242001-12-18
epoxidif-c_e_x-spice-6-v1.0/epxsp_1000EPOXI31.02005-08-232011-03-01
em16em16/em16_spiceExoMars TGO 201649.42016-03-142023-01-01
grailgrail-l-spice-6-v1.0/grlsp_1000GRAIL34.32011-09-102012-12-17
hayabusahay-a-spice-6-v1.0/haysp_1000Hayabusa30.32005-09-112005-11-19
insightinsight/insight_spiceInSight40.92018-05-052022-12-15
junojno-j_e_ss-spice-6-v1.0/jnosp_1000JUNO346.92011-08-052022-08-17
ladeeladee/ladee_spiceLADEE40.62013-09-072050-01-01
lrolro-l-spice-6-v1.0/lrosp_1000Lunar Reconnaissance Orbiter3595.72009-06-182023-03-15
mavenmaven/maven_spiceMAVEN454.42013-11-182023-04-01
opportunitymer1-m-spice-6-v1.0/mer1sp_1000MER 1 (Opportunity)34.12003-07-072018-06-10
spiritmer2-m-spice-6-v1.0/mer2sp_1000MER 2 (Spirit)32.62003-06-102010-05-03
messengermess-e_v_h-spice-6-v1.0/messsp_1000MESSENGER344.82004-08-032015-04-30
mars2020mars2020/mars2020_spiceMars 202040.62020-07-302022-12-28
mexmex-e_m-spice-6-v2.0/mexsp_2000Mars Express38.52003-06-022022-11-30
mgsmgs-m-spice-6-v1.0/mgsp_1000Mars Global Surveyor315.41996-11-062006-11-02
odyody-m-spice-6-v1.0/odsp_1000Mars Odyssey333.22001-04-072022-10-01
mromro-m-spice-6-v1.0/mrosp_1000Mars Reconnaissance Orbiter3314.92005-08-122023-04-01
mslmsl-m-spice-6-v1.0/mslsp_1000Mars Science Laboratory30.62011-11-262022-11-06
nearnear-a-spice-6-v1.0/nearsp_1000NEAR32.41996-05-302001-02-28
nhnh-j_p_ss-spice-6-v1.0/nhsp_1000New Horizons31.62006-01-192019-12-30
orexorex/orex_spiceOSIRIS-REx4418.42016-09-082021-02-22
rosettaro_rl-e_m_a_c-spice-6-v1.0/rossp_1000Rosetta35.92004-03-022017-01-01
stardustsdu-c-spice-6-v1.0/sdsp_1000Stardust31.91999-02-072011-05-01
venus_climate_orbitervco/vco_spiceVenus Climate Orbiter41.72010-05-212022-01-01
vexvex-e_v-spice-6-v2.0/vexsp_2000Venus Express35.02005-11-092015-02-06
vovo1_vo2-m-spice-6-v1.0/vosp_1000Viking Orbiter30.11976-06-161980-07-30
+ +
+
+
+

To receive this dataframe:

+
from planetarypy.spice.kernels import datasets
+

Some validation helpers:

+
+

source

+
+

is_stop_valid

+
+
 is_stop_valid (mission:str, stop:astropy.time.core.Time)
+
+ + + + + + + + + + + + + + + + + + + + +
TypeDetails
missionstrmission shorthand label of datasets dataframe
stopTimestop time in astropy.Time format
+
+

source

+
+
+

is_start_valid

+
+
 is_start_valid (mission:str, start:astropy.time.core.Time)
+
+ + + + + + + + + + + + + + + + + + + + +
TypeDetails
missionstrmission shorthand label of datasets dataframe
startTimestart time in astropy.Time format
+
+
assert is_start_valid("cassini", Time("1998-01-01")) is True
+assert is_start_valid("cassini", Time("1997-01-01")) is False
+assert is_stop_valid("cassini", "2017-01-01") is True
+assert is_stop_valid("cassini", "2018-01-01") is False
+
+

Now we build a management class for wrapping the Perl script available at below’s URL for accessing subsets of these datasets.

+

First, the basic URLs we will use:

+

The Perl script subsetds.pl (the name at the end of the BASE_URL) requires as input:

+
    +
  • the dataset name
    • +
  • start and stop of the time interval
    • +
  • a constant named “Subset” to identify the action for this Perl script
    • +
+

We can assemble these parameters into a payload dictionary for the requests.get call and we manage different potential actions on the zipfile with a Subsetter class, that only requires the mission identifier, start and stop as parameters.

+
/home/runner/micromamba/envs/my-env/lib/python3.11/site-packages/fastcore/docscrape.py:225: UserWarning: Unknown section Attributes
+  else: warn(msg)
+
+

source

+
+
+

Subsetter

+
+
 Subsetter (mission:str, start:str, stop=None, save_location=None)
+
+

Class to manage retrieving subset SPICE kernel lists

+ ++++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
TypeDefaultDetails
missionstrmission shorthand in datasets dataframe
startstrstart time in either ISO or yyyy-jjj format
stopNoneTypeNonestop time in either ISO or yyyy-jjj format
save_locationNoneTypeNoneoverwrite default storing in planetarpy archive
+
+

source

+
+
+

download_one_url

+
+
 download_one_url (url, local_path, overwrite:bool=False)
+
+
+
subset = Subsetter("cassini", "2014-270")
+
+
+
subset.kernel_names
+
+
['ck/14001_15001pa_gapfill_v14.bc',
+ 'ck/14212_14279py_as_flown.bc',
+ 'ck/14268_14273ra.bc',
+ 'ck/cas_cda_20150318.bc',
+ 'ck/cas_lemms_05109_20001_v2.bc',
+ 'fk/cas_dyn_v03.tf',
+ 'fk/cas_mimi_v202.tf',
+ 'fk/cas_rocks_v18.tf',
+ 'fk/cas_v41.tf',
+ 'ik/cas_caps_v03.ti',
+ 'ik/cas_cda_v01.ti',
+ 'ik/cas_cirs_v09.ti',
+ 'ik/cas_inms_v02.ti',
+ 'ik/cas_iss_v10.ti',
+ 'ik/cas_mag_v01.ti',
+ 'ik/cas_mimi_v11.ti',
+ 'ik/cas_radar_v11.ti',
+ 'ik/cas_rpws_v01.ti',
+ 'ik/cas_rss_v03.ti',
+ 'ik/cas_sru_v02.ti',
+ 'ik/cas_uvis_v06.ti',
+ 'ik/cas_vims_v06.ti',
+ 'lsk/naif0012.tls',
+ 'pck/pck00010.tpc',
+ 'sclk/cas00172.tsc',
+ 'spk/140809BP_IRRE_00256_25017.bsp',
+ 'spk/150122R_SCPSE_14251_14283.bsp',
+ 'spk/180927AP_RE_90165_18018.bsp']
+
+
+
+
# this should fail:
+def _failing():
+    Subsetter("cassini", "2019-01-01")
+
+
+test_fail(_failing, contains="start/stop")
+
+
+
subset = Subsetter("cassini", "2011-02-13", "2011-02-14")
+
+
+
subset.urls_file
+
+
'urls_cosp_1000_110213_110214.txt'
+
+
+
+
subset.metakernel_file
+
+
'cas_2011_v17_110213_110214.tm'
+
+
+
+

source

+
+
+

Subsetter.kernel_names

+
+
 Subsetter.kernel_names ()
+
+

Return list of names of kernels for the given time range.

+
+
subset.kernel_names
+
+
['ck/11001_12001pa_gapfill_v14.bc',
+ 'ck/11017_11066py_as_flown.bc',
+ 'ck/11044_11049ra.bc',
+ 'ck/cas_cda_20120517.bc',
+ 'ck/cas_lemms_05109_20001_v2.bc',
+ 'fk/cas_dyn_v03.tf',
+ 'fk/cas_mimi_v202.tf',
+ 'fk/cas_rocks_v18.tf',
+ 'fk/cas_v41.tf',
+ 'ik/cas_caps_v03.ti',
+ 'ik/cas_cda_v01.ti',
+ 'ik/cas_cirs_v09.ti',
+ 'ik/cas_inms_v02.ti',
+ 'ik/cas_iss_v10.ti',
+ 'ik/cas_mag_v01.ti',
+ 'ik/cas_mimi_v11.ti',
+ 'ik/cas_radar_v11.ti',
+ 'ik/cas_rpws_v01.ti',
+ 'ik/cas_rss_v03.ti',
+ 'ik/cas_sru_v02.ti',
+ 'ik/cas_uvis_v06.ti',
+ 'ik/cas_vims_v06.ti',
+ 'lsk/naif0012.tls',
+ 'pck/pck00010.tpc',
+ 'sclk/cas00172.tsc',
+ 'spk/110504R_SCPSE_11041_11093.bsp',
+ 'spk/140809BP_IRRE_00256_25017.bsp',
+ 'spk/180927AP_RE_90165_18018.bsp']
+
+
+
+
subset.kernel_urls
+
+
['https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/ck/11001_12001pa_gapfill_v14.bc',
+ 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/ck/11017_11066py_as_flown.bc',
+ 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/ck/11044_11049ra.bc',
+ 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/ck/cas_cda_20120517.bc',
+ 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/ck/cas_lemms_05109_20001_v2.bc',
+ 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/fk/cas_dyn_v03.tf',
+ 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/fk/cas_mimi_v202.tf',
+ 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/fk/cas_rocks_v18.tf',
+ 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/fk/cas_v41.tf',
+ 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/ik/cas_caps_v03.ti',
+ 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/ik/cas_cda_v01.ti',
+ 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/ik/cas_cirs_v09.ti',
+ 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/ik/cas_inms_v02.ti',
+ 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/ik/cas_iss_v10.ti',
+ 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/ik/cas_mag_v01.ti',
+ 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/ik/cas_mimi_v11.ti',
+ 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/ik/cas_radar_v11.ti',
+ 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/ik/cas_rpws_v01.ti',
+ 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/ik/cas_rss_v03.ti',
+ 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/ik/cas_sru_v02.ti',
+ 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/ik/cas_uvis_v06.ti',
+ 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/ik/cas_vims_v06.ti',
+ 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/lsk/naif0012.tls',
+ 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/pck/pck00010.tpc',
+ 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/sclk/cas00172.tsc',
+ 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/spk/110504R_SCPSE_11041_11093.bsp',
+ 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/spk/140809BP_IRRE_00256_25017.bsp',
+ 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/spk/180927AP_RE_90165_18018.bsp']
+
+
+
+

source

+
+
+

Subsetter.get_local_path

+
+
 Subsetter.get_local_path (url)
+
+

Calculate local storage path from Kernel URL, using save_location if given.

+

If self.save_location is None, the planetarypy archive is being used.

+ +++++ + + + + + + + + + + + + + + + + + + + +
TypeDetails
urlkernel url to determine local storage path
ReturnsPathfull local path where kernel in URL will be stored
+
+
subset.get_local_path(subset.kernel_urls[0])
+
+
Path('/home/ayek72/mnt/slowdata/planetarypy/spice_kernels/cassini/ck/11001_12001pa_gapfill_v14.bc')
+
+
+
+
subset.save_location = Path(".")
+
+
+
subset.get_local_path(subset.kernel_urls[0])
+
+
Path('ck/11001_12001pa_gapfill_v14.bc')
+
+
+
+

source

+
+
+

Subsetter.download_kernels

+
+
 Subsetter.download_kernels (overwrite:bool=False,
+                             non_blocking:bool=False, quiet:bool=False)
+
+ ++++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
TypeDefaultDetails
overwriteboolFalseswitch to control if kernels should be downloaded over existing ones
non_blockingboolFalse
quietboolFalse
+
+
# reset save_location to prevent additional download
+subset.save_location = None
+
+
+
subset.download_kernels()
+
+ +
+
+
ck 11001_12001pa_gapfill_v14.bc locally available.
+ck 11017_11066py_as_flown.bc locally available.
+ck 11044_11049ra.bc locally available.
+ck cas_cda_20120517.bc locally available.
+ck cas_lemms_05109_20001_v2.bc locally available.
+fk cas_dyn_v03.tf locally available.
+fk cas_mimi_v202.tf locally available.
+fk cas_rocks_v18.tf locally available.
+fk cas_v41.tf locally available.
+ik cas_caps_v03.ti locally available.
+ik cas_cda_v01.ti locally available.
+ik cas_cirs_v09.ti locally available.
+ik cas_inms_v02.ti locally available.
+ik cas_iss_v10.ti locally available.
+ik cas_mag_v01.ti locally available.
+ik cas_mimi_v11.ti locally available.
+ik cas_radar_v11.ti locally available.
+ik cas_rpws_v01.ti locally available.
+ik cas_rss_v03.ti locally available.
+ik cas_sru_v02.ti locally available.
+ik cas_uvis_v06.ti locally available.
+ik cas_vims_v06.ti locally available.
+lsk naif0012.tls locally available.
+pck pck00010.tpc locally available.
+sclk cas00172.tsc locally available.
+spk 110504R_SCPSE_11041_11093.bsp locally available.
+spk 140809BP_IRRE_00256_25017.bsp locally available.
+spk 180927AP_RE_90165_18018.bsp locally available.
+
+
+
+
subset.download_kernels(non_blocking=True)
+
+ +
+
+
ck 11001_12001pa_gapfill_v14.bc locally available.
+ck 11017_11066py_as_flown.bc locally available.
+ck 11044_11049ra.bc locally available.
+ck cas_cda_20120517.bc locally available.
+ck cas_lemms_05109_20001_v2.bc locally available.
+fk cas_dyn_v03.tf locally available.
+fk cas_mimi_v202.tf locally available.
+fk cas_rocks_v18.tf locally available.
+fk cas_v41.tf locally available.
+ik cas_caps_v03.ti locally available.
+ik cas_cda_v01.ti locally available.
+ik cas_cirs_v09.ti locally available.
+ik cas_inms_v02.ti locally available.
+ik cas_iss_v10.ti locally available.
+ik cas_mag_v01.ti locally available.
+ik cas_mimi_v11.ti locally available.
+ik cas_radar_v11.ti locally available.
+ik cas_rpws_v01.ti locally available.
+ik cas_rss_v03.ti locally available.
+ik cas_sru_v02.ti locally available.
+ik cas_uvis_v06.ti locally available.
+ik cas_vims_v06.ti locally available.
+lsk naif0012.tls locally available.
+pck pck00010.tpc locally available.
+sclk cas00172.tsc locally available.
+spk 110504R_SCPSE_11041_11093.bsp locally available.
+spk 140809BP_IRRE_00256_25017.bsp locally available.
+spk 180927AP_RE_90165_18018.bsp locally available.
+
+
+
[]
+
+
+
+

source

+
+
+

Subsetter.get_metakernel

+
+
 Subsetter.get_metakernel ()
+
+

Get metakernel file from NAIF and adapt path to match local storage.

+

Use save_location if given, otherwise planetarypy archive.

+
+
mkpath = subset.get_metakernel()
+mkpath
+
+
Path('/home/ayek72/mnt/slowdata/planetarypy/spice_kernels/cassini/cas_2011_v17_110213_110214.tm')
+
+
+
+
!cat {mkpath}
+
+
KPL/MK
+
+   This meta-kernel lists a subset of kernels from the meta-kernel
+   cas_2011_v17.tm provided in the CO-S/J/E/V-SPICE-6-V1.0 SPICE PDS3 archive,
+   covering the whole or a part of the customer requested time period
+   from 2011-02-13T00:00:00.000 to 2011-02-14T00:00:00.000.
+
+   The documentation describing these kernels can be found in the
+   complete CO-S/J/E/V-SPICE-6-V1.0 SPICE PDS3 archive available at this URL
+
+   https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000
+
+   To use this meta-kernel users may need to modify the value of the
+   PATH_VALUES keyword to point to the actual location of the archive's
+   ``data'' directory on their system. Replacing ``/'' with ``\''
+   and converting line terminators to the format native to the user's
+   system may also be required if this meta-kernel is to be used on a
+   non-UNIX workstation.
+
+   This meta-kernel was created by the NAIF node's SPICE PDS archive
+   subsetting service version 2.1 on Mon Jun 19 08:13:34 PDT 2023.
+
+ 
+   \begindata
+ 
+      PATH_VALUES     = (
+                         '/home/ayek72/mnt/slowdata/planetarypy/spice_kernels/cassini'
+                        )
+ 
+      PATH_SYMBOLS    = (
+                         'KERNELS'
+                        )
+ 
+      KERNELS_TO_LOAD = (
+                         '$KERNELS/lsk/naif0012.tls'
+                         '$KERNELS/pck/pck00010.tpc'
+                         '$KERNELS/fk/cas_rocks_v18.tf'
+                         '$KERNELS/fk/cas_mimi_v202.tf'
+                         '$KERNELS/fk/cas_dyn_v03.tf'
+                         '$KERNELS/fk/cas_v41.tf'
+                         '$KERNELS/ik/cas_caps_v03.ti'
+                         '$KERNELS/ik/cas_cda_v01.ti'
+                         '$KERNELS/ik/cas_cirs_v09.ti'
+                         '$KERNELS/ik/cas_inms_v02.ti'
+                         '$KERNELS/ik/cas_iss_v10.ti'
+                         '$KERNELS/ik/cas_mag_v01.ti'
+                         '$KERNELS/ik/cas_mimi_v11.ti'
+                         '$KERNELS/ik/cas_radar_v11.ti'
+                         '$KERNELS/ik/cas_rpws_v01.ti'
+                         '$KERNELS/ik/cas_rss_v03.ti'
+                         '$KERNELS/ik/cas_sru_v02.ti'
+                         '$KERNELS/ik/cas_uvis_v06.ti'
+                         '$KERNELS/ik/cas_vims_v06.ti'
+                         '$KERNELS/sclk/cas00172.tsc'
+                         '$KERNELS/spk/180927AP_RE_90165_18018.bsp'
+                         '$KERNELS/spk/140809BP_IRRE_00256_25017.bsp'
+                         '$KERNELS/spk/110504R_SCPSE_11041_11093.bsp'
+                         '$KERNELS/ck/11001_12001pa_gapfill_v14.bc'
+                         '$KERNELS/ck/11017_11066py_as_flown.bc'
+                         '$KERNELS/ck/11044_11049ra.bc'
+                         '$KERNELS/ck/cas_cda_20120517.bc'
+                         '$KERNELS/ck/cas_lemms_05109_20001_v2.bc'
+                        )
+ 
+   \begintext
+ 
+
+
+
+

Loading the metakernel works! :

+
+
spice.furnsh(str(mkpath))
+
+

Or, with given save_location:

+
+
subset.save_location = Path(".")
+mkpath = subset.get_metakernel()
+mkpath
+
+
Path('cas_2011_v17_110213_110214.tm')
+
+
+

The metakernel is correctly adapted, however for these tests, I didn’t download the kernels again

+
+
!cat {mkpath}
+
+
KPL/MK
+
+   This meta-kernel lists a subset of kernels from the meta-kernel
+   cas_2011_v17.tm provided in the CO-S/J/E/V-SPICE-6-V1.0 SPICE PDS3 archive,
+   covering the whole or a part of the customer requested time period
+   from 2011-02-13T00:00:00.000 to 2011-02-14T00:00:00.000.
+
+   The documentation describing these kernels can be found in the
+   complete CO-S/J/E/V-SPICE-6-V1.0 SPICE PDS3 archive available at this URL
+
+   https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000
+
+   To use this meta-kernel users may need to modify the value of the
+   PATH_VALUES keyword to point to the actual location of the archive's
+   ``data'' directory on their system. Replacing ``/'' with ``\''
+   and converting line terminators to the format native to the user's
+   system may also be required if this meta-kernel is to be used on a
+   non-UNIX workstation.
+
+   This meta-kernel was created by the NAIF node's SPICE PDS archive
+   subsetting service version 2.1 on Mon Jun 19 08:13:34 PDT 2023.
+
+ 
+   \begindata
+ 
+      PATH_VALUES     = (
+                         '.'
+                        )
+ 
+      PATH_SYMBOLS    = (
+                         'KERNELS'
+                        )
+ 
+      KERNELS_TO_LOAD = (
+                         '$KERNELS/lsk/naif0012.tls'
+                         '$KERNELS/pck/pck00010.tpc'
+                         '$KERNELS/fk/cas_rocks_v18.tf'
+                         '$KERNELS/fk/cas_mimi_v202.tf'
+                         '$KERNELS/fk/cas_dyn_v03.tf'
+                         '$KERNELS/fk/cas_v41.tf'
+                         '$KERNELS/ik/cas_caps_v03.ti'
+                         '$KERNELS/ik/cas_cda_v01.ti'
+                         '$KERNELS/ik/cas_cirs_v09.ti'
+                         '$KERNELS/ik/cas_inms_v02.ti'
+                         '$KERNELS/ik/cas_iss_v10.ti'
+                         '$KERNELS/ik/cas_mag_v01.ti'
+                         '$KERNELS/ik/cas_mimi_v11.ti'
+                         '$KERNELS/ik/cas_radar_v11.ti'
+                         '$KERNELS/ik/cas_rpws_v01.ti'
+                         '$KERNELS/ik/cas_rss_v03.ti'
+                         '$KERNELS/ik/cas_sru_v02.ti'
+                         '$KERNELS/ik/cas_uvis_v06.ti'
+                         '$KERNELS/ik/cas_vims_v06.ti'
+                         '$KERNELS/sclk/cas00172.tsc'
+                         '$KERNELS/spk/180927AP_RE_90165_18018.bsp'
+                         '$KERNELS/spk/140809BP_IRRE_00256_25017.bsp'
+                         '$KERNELS/spk/110504R_SCPSE_11041_11093.bsp'
+                         '$KERNELS/ck/11001_12001pa_gapfill_v14.bc'
+                         '$KERNELS/ck/11017_11066py_as_flown.bc'
+                         '$KERNELS/ck/11044_11049ra.bc'
+                         '$KERNELS/ck/cas_cda_20120517.bc'
+                         '$KERNELS/ck/cas_lemms_05109_20001_v2.bc'
+                        )
+ 
+   \begintext
+ 
+
+
+
+
+
+
+

User functions

+
+

source

+
+

get_metakernel_and_files

+
+
 get_metakernel_and_files (mission:str, start:str, stop:str,
+                           save_location:str=None, quiet:bool=False)
+
+

For a given mission and start/stop times, download the kernels and get metakernel path

+ ++++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
TypeDefaultDetails
missionstrmission shorthand from datasets dataframe
startstrstart time as iso-string, or yyyy-jjj
stopstrstop time as iso-string or yyyy-jjj
save_locationstrNoneoverride storage into planetarypy archive
quietboolFalsesuppress kernel-wise feedback
ReturnsPathpathlib.Path to metakernel file with corrected data path.
+
+
mkpath = get_metakernel_and_files("cassini", "2011-02-13", "2011-02-14")
+mkpath
+
+
/Users/maye/mambaforge/envs/py39/lib/python3.9/site-packages/distributed/node.py:182: UserWarning: Port 8787 is already in use.
+Perhaps you already have a cluster running?
+Hosting the HTTP server on port 57624 instead
+  warnings.warn(
+
+
+ +
+
+
ck 11001_12001pa_gapfill_v14.bc locally available.
+ck 11017_11066py_as_flown.bc locally available.
+ck 11044_11049ra.bc locally available.
+ck cas_cda_20120517.bc locally available.
+ck cas_lemms_05109_20001_v2.bc locally available.
+fk cas_dyn_v03.tf locally available.
+fk cas_mimi_v202.tf locally available.
+fk cas_rocks_v18.tf locally available.
+fk cas_v41.tf locally available.
+ik cas_caps_v03.ti locally available.
+ik cas_cda_v01.ti locally available.
+ik cas_cirs_v09.ti locally available.
+ik cas_inms_v02.ti locally available.
+ik cas_iss_v10.ti locally available.
+ik cas_mag_v01.ti locally available.
+ik cas_mimi_v11.ti locally available.
+ik cas_radar_v11.ti locally available.
+ik cas_rpws_v01.ti locally available.
+ik cas_rss_v03.ti locally available.
+ik cas_sru_v02.ti locally available.
+ik cas_uvis_v06.ti locally available.
+ik cas_vims_v06.ti locally available.
+lsk naif0012.tls locally available.
+pck pck00010.tpc locally available.
+sclk cas00172.tsc locally available.
+spk 110504R_SCPSE_11041_11093.bsp locally available.
+spk 140809BP_IRRE_00256_25017.bsp locally available.
+spk 180927AP_RE_90165_18018.bsp locally available.
+
+
+
Path('/Users/maye/planetarypy_data/spice_kernels/cassini/cas_2011_v17_110213_110214.tm')
+
+
+
+

source

+
+
+

list_kernels_for_day

+
+
 list_kernels_for_day (mission:str, start:str, stop:str='')
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
TypeDefaultDetails
missionstrmission shorthand from datasets dataframe
startstrstart time as iso-string, or yyyy-jjj
stopstrstop time as iso-string or yyyy-jjj
Returnslistlist of kernel names
+
+
list_kernels_for_day("mro", "2015-02-13")
+
+
['ck/mro_crm_psp_150201_150228.bc',
+ 'ck/mro_hga_psp_150210_150216_v2.bc',
+ 'ck/mro_mcs_psp_150201_150228.bc',
+ 'ck/mro_sa_psp_150210_150216_v2.bc',
+ 'ck/mro_sc_psp_150210_150216_v2.bc',
+ 'fk/mro_v16.tf',
+ 'ik/mro_crism_v10.ti',
+ 'ik/mro_ctx_v11.ti',
+ 'ik/mro_hirise_v12.ti',
+ 'ik/mro_marci_v10.ti',
+ 'ik/mro_mcs_v10.ti',
+ 'ik/mro_onc_v10.ti',
+ 'lsk/naif0012.tls',
+ 'pck/pck00008.tpc',
+ 'sclk/mro_sclkscet_00095_65536.tsc',
+ 'spk/de421.bsp',
+ 'spk/mar097.bsp',
+ 'spk/mro_psp34.bsp',
+ 'spk/mro_psp34_ssd_mro95a.bsp',
+ 'spk/mro_struct_v10.bsp']
+
+
+
+
# this always takes much longer than other requests!
+list_kernels_for_day("maven", "2017-01-01")
+
+
['ck/mvn_app_rel_161226_170101_v01.bc',
+ 'ck/mvn_app_rel_170102_170108_v01.bc',
+ 'ck/mvn_iuvs_rem_170101_170331_v03.bc',
+ 'ck/mvn_sc_rel_161226_170101_v01.bc',
+ 'ck/mvn_sc_rel_170102_170108_v02.bc',
+ 'ck/mvn_swea_nom_131118_300101_v02.bc',
+ 'fk/maven_v09.tf',
+ 'ik/maven_ant_v10.ti',
+ 'ik/maven_euv_v10.ti',
+ 'ik/maven_iuvs_v11.ti',
+ 'ik/maven_ngims_v10.ti',
+ 'ik/maven_sep_v12.ti',
+ 'ik/maven_static_v11.ti',
+ 'ik/maven_swea_v11.ti',
+ 'ik/maven_swia_v10.ti',
+ 'lsk/naif0012.tls',
+ 'pck/pck00010.tpc',
+ 'sclk/mvn_sclkscet_00072.tsc',
+ 'spk/de430s.bsp',
+ 'spk/mar097s.bsp',
+ 'spk/maven_orb_rec_170101_170401_v1.bsp',
+ 'spk/maven_struct_v01.bsp']
+
+
+
+
# this always takes much longer than other requests!
+list_kernels_for_day("orex", "2018-11-30")
+
+
['ck/orx_sa_rel_181126_181202_v01.bc',
+ 'ck/orx_sc_rel_181126_181202_v01.bc',
+ 'ck/orx_struct_mapcam_v01.bc',
+ 'ck/orx_struct_polycam_v01.bc',
+ 'fk/orx_shape_v03.tf',
+ 'fk/orx_v14.tf',
+ 'ik/orx_lidar_v00.ti',
+ 'ik/orx_navcam_v02.ti',
+ 'ik/orx_ocams_v07.ti',
+ 'ik/orx_ola_v01.ti',
+ 'ik/orx_otes_v00.ti',
+ 'ik/orx_ovirs_v00.ti',
+ 'ik/orx_rexis_v01.ti',
+ 'ik/orx_stowcam_v00.ti',
+ 'ik/orx_struct_v00.ti',
+ 'lsk/naif0012.tls',
+ 'pck/bennu_v17.tpc',
+ 'pck/pck00010.tpc',
+ 'sclk/orx_sclkscet_00074.tsc',
+ 'spk/bennu_refdrmc_v1.bsp',
+ 'spk/de424.bsp',
+ 'spk/orx_180301_181201_180921_od044_v1.bsp',
+ 'spk/orx_180801_190302_181218_od077_v1.bsp',
+ 'spk/orx_181203_190302_190104_od085_v1.bsp',
+ 'spk/orx_struct_v04.bsp']
+
+
+
+
def _test_mission_kernels_available(mission):
+    print("Doing", mission)
+    start = datasets.at[mission, "Start Time"]
+    end = datasets.at[mission, "Stop Time"]
+    half = Time(start) + (Time(end) - Time(start)) / 2
+    print("Half time:", half)
+    try:
+        found = list_kernels_for_day(mission, half)
+    except IndexError:
+        print("Problem with", mission)
+    else:
+        print(f"Found {len(found)} kernels for {mission}")
+
+for mission in datasets.index:
+    _test_mission_kernels_available(mission)
+
+
Doing bc
+Half time: 2020-11-25 00:00:00.000
+Found 41 kernels for bc
+Doing cassini
+Half time: 2007-09-30 12:00:01.000
+Found 32 kernels for cassini
+Doing clementine
+Half time: 1994-03-17 12:00:00.000
+Found 19 kernels for clementine
+Doing dart
+Half time: 2035-12-06 00:00:00.000
+Found 14 kernels for dart
+Doing dawn
+Half time: 2013-04-14 00:00:00.000
+Found 21 kernels for dawn
+Doing di
+Half time: 2005-04-26 12:00:00.000
+Found 16 kernels for di
+Doing ds1
+Half time: 2000-05-21 11:59:59.500
+Found 11 kernels for ds1
+Doing epoxi
+Half time: 2008-05-27 00:00:00.000
+Found 12 kernels for epoxi
+Doing em16
+Half time: 2019-08-07 23:59:59.500
+Found 27 kernels for em16
+Doing grail
+Half time: 2012-04-29 00:00:00.500
+Found 20 kernels for grail
+Doing hayabusa
+Half time: 2005-10-15 12:00:00.000
+Found 15 kernels for hayabusa
+Doing insight
+Half time: 2020-08-24 12:00:00.000
+Found 21 kernels for insight
+Doing juno
+Half time: 2017-02-08 23:59:58.500
+Found 25 kernels for juno
+Doing ladee
+Half time: 2031-11-04 11:59:59.000
+Found 12 kernels for ladee
+Doing lro
+Half time: 2016-04-30 23:59:59.500
+Found 24 kernels for lro
+Doing maven
+Half time: 2018-07-25 11:59:59.000
+Found 20 kernels for maven
+Doing opportunity
+Half time: 2010-12-23 00:00:00.500
+Found 23 kernels for opportunity
+Doing spirit
+Half time: 2006-11-20 12:00:00.000
+Found 24 kernels for spirit
+Doing messenger
+Half time: 2009-12-15 23:59:59.500
+Found 18 kernels for messenger
+Doing mars2020
+Half time: 2021-10-13 12:00:00.000
+Found 17 kernels for mars2020
+Doing mex
+Half time: 2013-03-01 11:59:59.500
+Found 39 kernels for mex
+Doing mgs
+Half time: 2001-11-03 23:59:59.500
+Found 20 kernels for mgs
+Doing ody
+Half time: 2012-01-03 12:00:00.500
+Found 14 kernels for ody
+Doing mro
+Half time: 2014-06-06 11:59:59.500
+Found 20 kernels for mro
+Doing msl
+Half time: 2017-05-16 23:59:58.500
+Found 50 kernels for msl
+Doing near
+Half time: 1998-10-14 12:00:00.000
+Found 15 kernels for near
+Doing nh
+Half time: 2013-01-08 12:00:00.000
+Found 28 kernels for nh
+Doing orex
+Half time: 2018-11-30 23:59:59.500
+
+
+
  warnings.warn('ERFA function "{}" yielded {}'.format(func_name, wmsg),
+  warnings.warn('ERFA function "{}" yielded {}'.format(func_name, wmsg),
+  warnings.warn('ERFA function "{}" yielded {}'.format(func_name, wmsg),
+  warnings.warn('ERFA function "{}" yielded {}'.format(func_name, wmsg),
+
+
+
OSError: SPICE Server request returned status code: {r.status_code}
+
+
+
+

NOTE: Any ErfaWarnings above are caused by the LADEE mission using a kernel up to 2050, and the astropy.Time module warns about potential precicision issues regarding unknown leapseconds that will be put in in the future.

+
+
+
+

Generic kernel management

+

There are a few generic kernels that are required for basic illumination calculations as supported by this package.

+
+

source

+
+
+

download_generic_kernels

+
+
 download_generic_kernels (overwrite=False)
+
+

Download all kernels as required by generic_kernel_list.

+
+
download_generic_kernels()
+
+
+

source

+
+
+

load_generic_kernels

+
+
 load_generic_kernels ()
+
+

Load all kernels in generic_kernels list.

+

Loads pure planetary bodies meta-kernel without spacecraft data.

+

Downloads any missing generic kernels.

+
+
spice.kclear()
+
+
+
load_generic_kernels()
+
+
+

source

+
+
+

show_loaded_kernels

+
+
 show_loaded_kernels ()
+
+

Print overview of loaded kernels.

+
+
show_loaded_kernels()
+
+
+
from nbdev import nbdev_export
+
+nbdev_export()
+
+ + +
+
+ +
+ + +
+ + + + \ No newline at end of file diff --git a/api/utils.html b/api/utils.html new file mode 100644 index 0000000..3298a6d --- /dev/null +++ b/api/utils.html @@ -0,0 +1,1171 @@ + + + + + + + + + + +planetarypy - Utils + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Utils

+
+ +
+
+ General utilities. Should probably split up into utils.time and utils.download +
+
+ + +
+ + + + +
+ + +
+ + +
+

Time format strings

+

First, we define the different format strings these utils convert from and to.

+

An identifier with xxx_dt_format_xxx in its name signifies a full datetime format as compared to dates only.

+
+

NASA date to datetime and ISO

+

What we call NASA data, is the often used YYYY-JJJ based format in the Planetary Data System identifying dates via the running number of the day in the year, e.g. “2010-240”.

+
+

source

+
+
+

nasa_time_to_datetime

+
+
 nasa_time_to_datetime (inputstr)
+
+

User function to convert all kinds of NASA PDS datestrings with day_of_year into datetimes.

+ +++++ + + + + + + + + + + + + + + + + + + + +
TypeDetails
inputstrinputstr of format YYYY-jjj, YYYY-jjjTHH:MM:SS or YYYY-jjjTHH:MM:SS.ffffff
Returnsdatetime
+

Example dates and times to test:

+
+
nasa_date = "2010-110"
+iso_date = "2010-4-20"
+nasa_datetime = "2010-110T10:12:14"
+nasa_datetime_with_ms = nasa_datetime + ".123000"
+iso_datetime = "2010-04-20T10:12:14"
+iso_datetime_with_ms = iso_datetime + ".123000"
+nasa_times = [nasa_date, nasa_datetime, nasa_datetime_with_ms]
+iso_times = [iso_date, iso_datetime, iso_datetime_with_ms]
+
+
+
assert nasa_time_to_datetime(nasa_date) == dt.datetime(2010, 4, 20, 0, 0)
+
+
+
assert nasa_time_to_datetime(nasa_datetime) == dt.datetime(2010, 4, 20, 10, 12, 14)
+
+
+
assert nasa_time_to_datetime(nasa_datetime_with_ms) == dt.datetime(2010, 4, 20, 10, 12, 14, 123000)
+
+
+

source

+
+
+

nasa_time_to_iso

+
+
 nasa_time_to_iso (inputstr:str, with_hours:bool=False)
+
+

Convert the day-number based NASA datetime format to ISO

+ ++++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
TypeDefaultDetails
inputstrstr
with_hoursboolFalseSwitch if return is wanted with hours (i.e. isoformat)
ReturnsstrDatestring in ISO-format.
+

Conversions to ISO format, but not providing hours if they are not in input:

+
+
for t in nasa_times:
+    print("Input:", t)
+    print(nasa_time_to_iso(t))
+
+
Input: 2010-110
+2010-04-20
+Input: 2010-110T10:12:14
+2010-04-20T10:12:14
+Input: 2010-110T10:12:14.123000
+2010-04-20T10:12:14.123000
+
+
+

If hours are wanted in the isostring, use with_hours=True:

+
+
for t in nasa_times:
+    print("Input:", t)
+    print(nasa_time_to_iso(t, with_hours=True))
+
+
Input: 2010-110
+2010-04-20T00:00:00
+Input: 2010-110T10:12:14
+2010-04-20T10:12:14
+Input: 2010-110T10:12:14.123000
+2010-04-20T10:12:14.123000
+
+
+
+
assert nasa_time_to_iso(nasa_date, with_hours=True) == "2010-04-20T00:00:00"
+assert nasa_time_to_iso(nasa_date) == "2010-04-20"
+
+
+
+

ISO date to “NASA-format”

+

Again, with NASA-format, we mean the ofen used (in PDS and mission files) YYYY-JJJ format, e.g. “2010-240”.

+
+

source

+
+
+

iso_to_nasa_time

+
+
 iso_to_nasa_time (inputstr:str)
+
+

Convert iso date to day-number based NASA date.

+ + + + + + + + + + + + + + + + + + + + +
TypeDetails
inputstrstrDate string of the form Y-m-d
ReturnsstrDatestring in NASA standard yyyy-jjj
+
+

source

+
+
+

iso_to_nasa_datetime

+
+
 iso_to_nasa_datetime (dtimestr:str)
+
+

Convert iso datetime to day-number based NASA datetime.

+ + + + + + + + + + + + + + + +
TypeDetails
dtimestrstrDatetime string of the form yyyy-mm-ddTHH-MM-SS
+
+
for t in iso_times:
+    print("Input:", t)
+    print(iso_to_nasa_time(t))
+
+
Input: 2010-4-20
+2010-110
+Input: 2010-04-20T10:12:14
+2010-110T10:12:14
+Input: 2010-04-20T10:12:14.123000
+2010-110T10:12:14.123000
+
+
+
+
assert iso_to_nasa_time(iso_date) == nasa_date
+
+
+
assert nasa_time_to_iso(nasa_datetime) == iso_datetime
+assert nasa_time_to_iso(nasa_datetime_with_ms) == iso_datetime_with_ms
+
+
+
assert iso_to_nasa_time(iso_datetime) == nasa_datetime
+assert iso_to_nasa_time(iso_datetime_with_ms) == nasa_datetime_with_ms
+
+
+

source

+
+
+

replace_all_nasa_times

+
+
 replace_all_nasa_times (df:pandas.core.frame.DataFrame)
+
+

Find all NASA times in dataframe and replace with ISO.

+

Changes will be implemented on incoming dataframe!

+

This will be done for all columns with the word TIME in the column name.

+ + + + + + + + + + + + + + + +
TypeDetails
dfDataFrameDataFrame with NASA time columns
+
+
+
+

Network utils

+
+

source

+
+

have_internet

+
+
 have_internet ()
+
+

Fastest way to check for active internet connection.

+

From https://stackoverflow.com/a/29854274/680232

+
+

source

+
+
+

url_retrieve

+
+
 url_retrieve (url:str, outfile:str, chunk_size:int=4096, user:str=None,
+               passwd:str=None)
+
+

Improved urlretrieve with progressbar, timeout and chunker.

+

This downloader has built-in progress bar using tqdm and using the requests package it improves standard urllib behavior by adding time-out capability.

+

I tested different chunk_sizes and most of the time 128 was actually fastest, YMMV.

+

Inspired by https://stackoverflow.com/a/61575758/680232

+ ++++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
TypeDefaultDetails
urlstrThe URL to download
outfilestrThe path where to store the downloaded file.
chunk_sizeint4096def chunk size for the request.iter_content call
userstrNoneif provided, create HTTPBasicAuth object
passwdstrNoneif provided, create HTTPBasicAuth object
+
+

source

+
+
+

check_url_exists

+
+
 check_url_exists (url)
+
+
+

source

+
+
+

get_remote_timestamp

+
+
 get_remote_timestamp (url:str)
+
+

Get the timestamp of a remote file.

+

Useful for checking if there’s an updated file available.

+ + + + + + + + + + + + + + + + + + + + +
TypeDetails
urlstrURL to check timestamp for
Returnsdatetime
+
+

source

+
+
+

parse_http_date

+
+
 parse_http_date (text:str)
+
+

Parse date string retrieved via urllib.request.

+ +++++ + + + + + + + + + + + + + + + + + + + +
TypeDetails
textstrdatestring from urllib.request
Returnsdatetimedt.datetime object from given datetime string
+
+
have_internet()
+
+
True
+
+
+
+
+
+

Image processing helpers

+
+

source

+
+

file_variations

+
+
 file_variations (filename:Union[str,pathlib.Path], extensions:list)
+
+

Create a variation of file names.

+

Generate a list of variations on a filename by replacing the extension with the provided list.

+

Adapted from T. Olsens `file_variations of the pysis module for using pathlib.

+ + + + + + + + + + + + + + + + + + + + + + + + + +
TypeDetails
filenameUnionThe original filename to use as a base.
extensionslist
Returnslistlist of Paths
+
+

source

+
+
+

get_gdal_center_coords

+
+
 get_gdal_center_coords (imgpath:Union[str,pathlib.Path])
+
+

Get center rows/cols pixel coordinate for GDAL-readable dataset.

+

Check CLI gdalinfo --formats to see all formats that GDAL can open.

+ + + + + + + + + + + + + + + + + + + + +
TypeDetails
imgpathUnionPath to raster image that is readable by GDLA
ReturnsTuplecenter row/col coordinates.
+
+

source

+
+
+

height_from_shadow

+
+
 height_from_shadow (shadow_in_pixels:float, sun_elev:float)
+
+

Calculate height of an object from its shadow length.

+

Note, that your image might have been binned. You need to correct shadow_in_pixels for that.

+ + + + + + + + + + + + + + + + + + + + + + + + + +
TypeDetails
shadow_in_pixelsfloatMeasured length of shadow in pixels
sun_elevfloatAnge of sun over horizon in degrees
ReturnsfloatHeight [meter]
+
+
fname = "abc.txt"
+
+
+
extensions = ".cub .cal.cub .map.cal.cub".split()
+
+
+
file_variations(fname, extensions)
+
+
[Path('abc.cub'), Path('abc.cal.cub'), Path('abc.map.cal.cub')]
+
+
+
+
assert len(extensions) == len(file_variations(fname, extensions))
+
+
+
+
+

ISIS helpers

+
+

source

+
+

catch_isis_error

+
+
 catch_isis_error (func)
+
+

can be used as decorator for any ISIS function

+
+
+
+

Notebook tools

+
+

source

+
+

fix_nb_metadata_folder

+
+
 fix_nb_metadata_folder (folder)
+
+
+

source

+
+
+

fix_nb_metadata

+
+
 fix_nb_metadata (fpath)
+
+
+
from nbdev import nbdev_export
+
+nbdev_export()
+
+ + +
+
+ +
+ +
+ + + + \ No newline at end of file diff --git a/index.html b/index.html new file mode 100644 index 0000000..9afc041 --- /dev/null +++ b/index.html @@ -0,0 +1,1114 @@ + + + + + + + + + +planetarypy - PlanetaryPy + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

PlanetaryPy

+
+ + + +
+ + + + +
+ + +
+ + +
+

PlanetaryPy

+
+

Beta release: This will become (part of) the core package of the PlanetaryPy organisation.

+
+

Potential logo:image.png

+
+

Install

+
pip install planetarypy
+

This will pull in these other dependencies and their dependencies:

+

tomlkit pandas pvl numpy python-dateutil tqdm lxml yarl hirise-tools kalasiris

+
+
+

Suggested standard abbreviations:

+
    +
  • Inside these docs the package will be called PLPY for brevity.
    • +
  • A standard Python import could be: plp or plpy +
      +
    • because the last p in plp can be pronounced out, we consider these equivalent for human conversation and pronounce these “plippy”.
      • +
    • +
+
+
+

General scope

+

First and foremost this package should provide support in working with planetary science data.

+

With working we mean:

+
    +
  • locating
    • +
  • retrieving
    • +
  • reading
    • +
  • further processing
    • +
+

of data.

+
+

Locating

+

This library manages, via its PDS tools, multiple PDS3 index files per instrument that can be used for identifying data of interest. These index files are automatically downloaded and converted to the very performant (and cloud-ready) parquet file format. > Parquet is able to store advanced datatypes like nan-capable integer and full datetime objects, as opposed to HDF5.

+
+
+

Retrieving

+

The interface to getting data is via a path-retrieving function based on a PDS product-id. If that product-id is available locally, the path will be returned. If it is not, it will previously be downloaded, stored in a systematic fashion organized by mission and instrument, and then the local path will be returned.

+
+
+

Reading

+

For now, the library only returns the path to the object and the user needs to sort out the reading process. A recently funded NASA project Planetary Data Reader will be integrated here, so that basic reading into memory can be provided.

+

As such, we anticipate two classes of reading support: 1. basic reading into numpy and/or xarray 1. added reader functionality like basic plots and basic geospatial processing, as supported by interested parties

+

There will exist larger other packages that focus on working with a given instrument’s data, in which case that package could become an affiliated package with the planetarypy GitHub organization, if so desired.

+
+
+

Further processing

+

In the future, additional frequently used procedures will be added to this library, e.g. * frequently used GDAL/rasterio procedures * frequently used SPICE operations * like surface illumination on a given body

+
+
+
+

PDS tools

+

Look at the Apps docs to see what pds.apps exist for easily getting PDS indexes. The find_index app is specifically useful when you don’t know what index files exist.

+

So far, the following indexes are supported (but not necessarily all tested within PLPY):

+
    +
  • Cassini +
      +
    • ISS (all)
      • +
    • UVIS (all)
      • +
    • +
  • MRO +
      +
    • CTX EDR
      • +
    • HiRISE +
        +
      • EDR, RDR, DTM +
          +
        • EDR index has a bug (as delivered by the team, reported), where I need to activate an existing fix for it.
          • +
        • +
      • +
    • +
  • LRO +
      +
    • Diviner (DLRE) +
        +
      • EDR, RDR
        • +
      • +
    • LOLA +
        +
      • EDR, RDR
        • +
      • +
    • +
+
+

More indexes

+

More indexes of other instruments can be easily added by following the existing structure of what has been copied into your config at ~/.planetarypy_config.toml.

+

Please consider submitting a pull request for adding further PDS index files into the config file at its source: https://github.com/michaelaye/nbplanetary/blob/master/planetarypy/data/planetarypy_config.toml

+
+
+
+

Utils

+

Find something in Utils for working with NASA timestamps and a well working URL download function url_retrieve, among other stuff.

+
+
+

Experiment/Instrument Specific

+

So far, planetarypy supports CTX EDR and HiRISE RGB.NOMAP data. Look at the CTX and HiRISE pages for descriptions of classes for working with these data.

+
+
+

Bug reports

+

Please submit bug reports at https://github.com/michaelaye/nbplanetary/issues

+
+
+

How to use

+
+

Indexes

+

See PDS apps for more details.

+
+
from planetarypy.pds.apps import get_index
+
+
+
ctrindex = get_index("mro.ctx", "edr", refresh=False)
+ctrindex.sample(5, random_state=42)  # setting random_state to always get same files for docs
+
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
VOLUME_IDFILE_SPECIFICATION_NAMEORIGINAL_PRODUCT_IDPRODUCT_IDIMAGE_TIMEINSTRUMENT_IDINSTRUMENT_MODE_IDLINE_SAMPLESLINESSPATIAL_SUMMING...SUB_SOLAR_LATITUDESUB_SPACECRAFT_LONGITUDESUB_SPACECRAFT_LATITUDESOLAR_DISTANCESOLAR_LONGITUDELOCAL_TIMEIMAGE_SKEW_ANGLERATIONALE_DESCDATA_QUALITY_DESCORBIT_NUMBER
86101MROX_2757DATA/J07_047671_1256_XN_54S338W.IMG4A_04_10F0036A00J07_047671_1256_XN_54S338W2016-09-27 00:24:54.682CTXNIFL252881921...-19.41338.09-54.43207762612.4230.5815.4890.1Crater in Noachis TerraOK47671
54420MROX_1819DATA/D10_031170_1808_XN_00N221W.IMG4A_04_109C017D00D10_031170_1808_XN_00N221W2013-03-21 06:58:09.892CTXNIFL505671681...-24.39221.520.88209925149.5286.1514.4990.1Ride-along with HiRISEOK31170
71053MROX_2331DATA/F10_039530_1470_XI_33S203W.IMG4A_04_10C9000F00F10_039530_1470_XI_33S203W2015-01-01 16:20:01.840CTXITL5056522241...-25.3203.96-33.12207070298.2263.9315.290.4Terrain in Terra CimmeriaOK39530
51385MROX_1742DATA/D04_028919_2026_XN_22N327W.IMG4A_04_109002A800D04_028919_2026_XN_22N327W2012-09-26 21:17:00.483CTXNIFL505661441...0.67327.0622.78219814412.3178.4415.5390.1Ride-along with HiRISEOK28919
51923MROX_1757DATA/D05_029283_1524_XN_27S180W.IMG4A_04_1092020B00D05_029283_1524_XN_27S180W2012-10-25 05:44:21.786CTXNIFL505692161...-6.28178.36-27.56214830233.7194.7215.5790.1Ride-along with HiRISEOK29283
+ +

5 rows × 51 columns

+
+
+
+
+
hirise_rdr = get_index("mro.hirise", "rdr")
+hirise_rdr.sample(5, random_state=42)
+
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
VOLUME_IDFILE_NAME_SPECIFICATIONINSTRUMENT_HOST_IDINSTRUMENT_IDOBSERVATION_IDPRODUCT_IDPRODUCT_VERSION_IDTARGET_NAMEORBIT_NUMBERMISSION_PHASE_NAME...LINE_PROJECTION_OFFSETSAMPLE_PROJECTION_OFFSETCORNER1_LATITUDECORNER1_LONGITUDECORNER2_LATITUDECORNER2_LONGITUDECORNER3_LATITUDECORNER3_LONGITUDECORNER4_LATITUDECORNER4_LONGITUDE
144822MROHR_0001RDR/ESP/ORB_074100_074199/ESP_074107_1410/ESP_...MROHIRISEESP_074107_1410ESP_074107_1410_COLOR1MARS74107Extended Science Phase...-4568562.52009279.5-38.7446159.311-38.7465159.287-38.614159.269-38.6121159.293
22518MROHR_0001RDR/ESP/ORB_014000_014099/ESP_014080_1040/ESP_...MROHIRISEESP_014080_1040ESP_014080_1040_RED1MARS14080Extended Science Phase...-3193960.0-845180.0-76.0185165.215-76.0315164.858-75.6958164.658-75.6831165.005
86634MROHR_0001RDR/ESP/ORB_046300_046399/ESP_046395_1730/ESP_...MROHIRISEESP_046395_1730ESP_046395_1730_COLOR1MARS46395Extended Science Phase...-1584330.0-26573400.0-6.9957292.569-6.9979292.551-6.6838292.51-6.6815292.529
138163MROHR_0001RDR/ESP/ORB_069100_069199/ESP_069178_2345/ESP_...MROHIRISEESP_069178_2345ESP_069178_2345_RED1MARS69178Extended Science Phase...12762196.015708938.053.859876.759153.847476.60254.001376.567254.013776.7249
125490MROHR_0001RDR/ESP/ORB_063500_063599/ESP_063504_1995/ESP_...MROHIRISEESP_063504_1995ESP_063504_1995_COLOR1MARS63504Extended Science Phase...4638178.512794202.019.4523124.14919.45124.12819.5686124.11319.5709124.133
+ +

5 rows × 54 columns

+
+
+
+
+
+
+

Instrument tools

+
+

CTX

+
+
from planetarypy.ctx import CTX
+
+
+
pid = ctrindex.sample(random_state=42).squeeze().PRODUCT_ID
+pid
+
+
'J07_047671_1256_XN_54S338W'
+
+
+
+
ctx = CTX(pid)
+ctx
+
+
PRODUCT_ID: J07_047671_1256_XN_54S338W
+URL: https://pds-imaging.jpl.nasa.gov/data/mro/mars_reconnaissance_orbiter/ctx/mrox_2757/data/J07_047671_1256_XN_54S338W.IMG
+source_path: /remote/trove/geo/planet/Mars/CTX/pds/mrox_2757/J07_047671_1256_XN_54S338W.IMG
+Shape: (8192, 2528)
+
+
+
+
ctx.source_path
+
+
Path('/remote/trove/geo/planet/Mars/CTX/pds/mrox_2757/J07_047671_1256_XN_54S338W.IMG')
+
+
+
+
ctx.download()
+
+
File exists. Use `overwrite=True` to download fresh.
+
+
+
+
+
+

Acknowledgements

+

The creation of this library was in part supported by:

+
    +
  • NASA Cassini UVIS mission
    • +
  • NASA SSW grant NNX15AH36G
    • +
  • NASA PDART grant 80NSSC20K0875
    • +
  • NASA SSW grant 80NSSC20K0748
    • +
  • German Space Agency (DLR Bonn), grant 50 OO 2204, on behalf of the German Federal Ministry for Economic Affairs and Climate Action.
    • +
  • This research has made use of the USGS Integrated Software for Imagers and Spectrometers (ISIS)(Laura et al. 2022).
    • +
+ + + +
+
+ +

References

+
+Laura, Jason, Alex Acosta, Travis Addair, Lauren Adoram-Kershner, James Alexander, Oleg Alexandrov, Stacey Alley, et al. 2022. “Integrated Software for Imagers and Spectrometers.” Zenodo. https://doi.org/10.5281/zenodo.7443567. +
+
+ +
+ + + + \ No newline at end of file diff --git a/robots.txt b/robots.txt new file mode 100644 index 0000000..1378433 --- /dev/null +++ b/robots.txt @@ -0,0 +1 @@ +Sitemap: https://michaelaye.github.io/planetarypy/sitemap.xml diff --git a/search.json b/search.json new file mode 100644 index 0000000..c921b14 --- /dev/null +++ b/search.json @@ -0,0 +1,429 @@ +[ + { + "objectID": "index.html", + "href": "index.html", + "title": "PlanetaryPy", + "section": "", + "text": "Beta release: This will become (part of) the core package of the PlanetaryPy organisation.\n\nPotential logo:\n\n\npip install planetarypy\nThis will pull in these other dependencies and their dependencies:\ntomlkit pandas pvl numpy python-dateutil tqdm lxml yarl hirise-tools kalasiris\n\n\n\n\nInside these docs the package will be called PLPY for brevity.\nA standard Python import could be: plp or plpy\n\nbecause the last p in plp can be pronounced out, we consider these equivalent for human conversation and pronounce these “plippy”.\n\n\n\n\n\nFirst and foremost this package should provide support in working with planetary science data.\nWith working we mean:\n\nlocating\nretrieving\nreading\nfurther processing\n\nof data.\n\n\nThis library manages, via its PDS tools, multiple PDS3 index files per instrument that can be used for identifying data of interest. These index files are automatically downloaded and converted to the very performant (and cloud-ready) parquet file format. > Parquet is able to store advanced datatypes like nan-capable integer and full datetime objects, as opposed to HDF5.\n\n\n\nThe interface to getting data is via a path-retrieving function based on a PDS product-id. If that product-id is available locally, the path will be returned. If it is not, it will previously be downloaded, stored in a systematic fashion organized by mission and instrument, and then the local path will be returned.\n\n\n\nFor now, the library only returns the path to the object and the user needs to sort out the reading process. A recently funded NASA project Planetary Data Reader will be integrated here, so that basic reading into memory can be provided.\nAs such, we anticipate two classes of reading support: 1. basic reading into numpy and/or xarray 1. added reader functionality like basic plots and basic geospatial processing, as supported by interested parties\nThere will exist larger other packages that focus on working with a given instrument’s data, in which case that package could become an affiliated package with the planetarypy GitHub organization, if so desired.\n\n\n\nIn the future, additional frequently used procedures will be added to this library, e.g. * frequently used GDAL/rasterio procedures * frequently used SPICE operations * like surface illumination on a given body\n\n\n\n\nLook at the Apps docs to see what pds.apps exist for easily getting PDS indexes. The find_index app is specifically useful when you don’t know what index files exist.\nSo far, the following indexes are supported (but not necessarily all tested within PLPY):\n\nCassini\n\nISS (all)\nUVIS (all)\n\nMRO\n\nCTX EDR\nHiRISE\n\nEDR, RDR, DTM\n\nEDR index has a bug (as delivered by the team, reported), where I need to activate an existing fix for it.\n\n\n\nLRO\n\nDiviner (DLRE)\n\nEDR, RDR\n\nLOLA\n\nEDR, RDR\n\n\n\n\n\nMore indexes of other instruments can be easily added by following the existing structure of what has been copied into your config at ~/.planetarypy_config.toml.\nPlease consider submitting a pull request for adding further PDS index files into the config file at its source: https://github.com/michaelaye/nbplanetary/blob/master/planetarypy/data/planetarypy_config.toml\n\n\n\n\nFind something in Utils for working with NASA timestamps and a well working URL download function url_retrieve, among other stuff.\n\n\n\nSo far, planetarypy supports CTX EDR and HiRISE RGB.NOMAP data. Look at the CTX and HiRISE pages for descriptions of classes for working with these data.\n\n\n\nPlease submit bug reports at https://github.com/michaelaye/nbplanetary/issues\n\n\n\n\n\nSee PDS apps for more details.\n\nfrom planetarypy.pds.apps import get_index\n\n\nctrindex = get_index(\"mro.ctx\", \"edr\", refresh=False)\nctrindex.sample(5, random_state=42) # setting random_state to always get same files for docs\n\n\n\n\n\n\n\n\nVOLUME_ID\nFILE_SPECIFICATION_NAME\nORIGINAL_PRODUCT_ID\nPRODUCT_ID\nIMAGE_TIME\nINSTRUMENT_ID\nINSTRUMENT_MODE_ID\nLINE_SAMPLES\nLINES\nSPATIAL_SUMMING\n...\nSUB_SOLAR_LATITUDE\nSUB_SPACECRAFT_LONGITUDE\nSUB_SPACECRAFT_LATITUDE\nSOLAR_DISTANCE\nSOLAR_LONGITUDE\nLOCAL_TIME\nIMAGE_SKEW_ANGLE\nRATIONALE_DESC\nDATA_QUALITY_DESC\nORBIT_NUMBER\n\n\n\n\n86101\nMROX_2757\nDATA/J07_047671_1256_XN_54S338W.IMG\n4A_04_10F0036A00\nJ07_047671_1256_XN_54S338W\n2016-09-27 00:24:54.682\nCTX\nNIFL\n2528\n8192\n1\n...\n-19.41\n338.09\n-54.43\n207762612.4\n230.58\n15.48\n90.1\nCrater in Noachis Terra\nOK\n47671\n\n\n54420\nMROX_1819\nDATA/D10_031170_1808_XN_00N221W.IMG\n4A_04_109C017D00\nD10_031170_1808_XN_00N221W\n2013-03-21 06:58:09.892\nCTX\nNIFL\n5056\n7168\n1\n...\n-24.39\n221.52\n0.88\n209925149.5\n286.15\n14.49\n90.1\nRide-along with HiRISE\nOK\n31170\n\n\n71053\nMROX_2331\nDATA/F10_039530_1470_XI_33S203W.IMG\n4A_04_10C9000F00\nF10_039530_1470_XI_33S203W\n2015-01-01 16:20:01.840\nCTX\nITL\n5056\n52224\n1\n...\n-25.3\n203.96\n-33.12\n207070298.2\n263.93\n15.2\n90.4\nTerrain in Terra Cimmeria\nOK\n39530\n\n\n51385\nMROX_1742\nDATA/D04_028919_2026_XN_22N327W.IMG\n4A_04_109002A800\nD04_028919_2026_XN_22N327W\n2012-09-26 21:17:00.483\nCTX\nNIFL\n5056\n6144\n1\n...\n0.67\n327.06\n22.78\n219814412.3\n178.44\n15.53\n90.1\nRide-along with HiRISE\nOK\n28919\n\n\n51923\nMROX_1757\nDATA/D05_029283_1524_XN_27S180W.IMG\n4A_04_1092020B00\nD05_029283_1524_XN_27S180W\n2012-10-25 05:44:21.786\nCTX\nNIFL\n5056\n9216\n1\n...\n-6.28\n178.36\n-27.56\n214830233.7\n194.72\n15.57\n90.1\nRide-along with HiRISE\nOK\n29283\n\n\n\n\n5 rows × 51 columns\n\n\n\n\nhirise_rdr = get_index(\"mro.hirise\", \"rdr\")\nhirise_rdr.sample(5, random_state=42)\n\n\n\n\n\n\n\n\nVOLUME_ID\nFILE_NAME_SPECIFICATION\nINSTRUMENT_HOST_ID\nINSTRUMENT_ID\nOBSERVATION_ID\nPRODUCT_ID\nPRODUCT_VERSION_ID\nTARGET_NAME\nORBIT_NUMBER\nMISSION_PHASE_NAME\n...\nLINE_PROJECTION_OFFSET\nSAMPLE_PROJECTION_OFFSET\nCORNER1_LATITUDE\nCORNER1_LONGITUDE\nCORNER2_LATITUDE\nCORNER2_LONGITUDE\nCORNER3_LATITUDE\nCORNER3_LONGITUDE\nCORNER4_LATITUDE\nCORNER4_LONGITUDE\n\n\n\n\n144822\nMROHR_0001\nRDR/ESP/ORB_074100_074199/ESP_074107_1410/ESP_...\nMRO\nHIRISE\nESP_074107_1410\nESP_074107_1410_COLOR\n1\nMARS\n74107\nExtended Science Phase\n...\n-4568562.5\n2009279.5\n-38.7446\n159.311\n-38.7465\n159.287\n-38.614\n159.269\n-38.6121\n159.293\n\n\n22518\nMROHR_0001\nRDR/ESP/ORB_014000_014099/ESP_014080_1040/ESP_...\nMRO\nHIRISE\nESP_014080_1040\nESP_014080_1040_RED\n1\nMARS\n14080\nExtended Science Phase\n...\n-3193960.0\n-845180.0\n-76.0185\n165.215\n-76.0315\n164.858\n-75.6958\n164.658\n-75.6831\n165.005\n\n\n86634\nMROHR_0001\nRDR/ESP/ORB_046300_046399/ESP_046395_1730/ESP_...\nMRO\nHIRISE\nESP_046395_1730\nESP_046395_1730_COLOR\n1\nMARS\n46395\nExtended Science Phase\n...\n-1584330.0\n-26573400.0\n-6.9957\n292.569\n-6.9979\n292.551\n-6.6838\n292.51\n-6.6815\n292.529\n\n\n138163\nMROHR_0001\nRDR/ESP/ORB_069100_069199/ESP_069178_2345/ESP_...\nMRO\nHIRISE\nESP_069178_2345\nESP_069178_2345_RED\n1\nMARS\n69178\nExtended Science Phase\n...\n12762196.0\n15708938.0\n53.8598\n76.7591\n53.8474\n76.602\n54.0013\n76.5672\n54.0137\n76.7249\n\n\n125490\nMROHR_0001\nRDR/ESP/ORB_063500_063599/ESP_063504_1995/ESP_...\nMRO\nHIRISE\nESP_063504_1995\nESP_063504_1995_COLOR\n1\nMARS\n63504\nExtended Science Phase\n...\n4638178.5\n12794202.0\n19.4523\n124.149\n19.45\n124.128\n19.5686\n124.113\n19.5709\n124.133\n\n\n\n\n5 rows × 54 columns\n\n\n\n\n\n\n\n\n\n\nfrom planetarypy.ctx import CTX\n\n\npid = ctrindex.sample(random_state=42).squeeze().PRODUCT_ID\npid\n\n'J07_047671_1256_XN_54S338W'\n\n\n\nctx = CTX(pid)\nctx\n\nPRODUCT_ID: J07_047671_1256_XN_54S338W\nURL: https://pds-imaging.jpl.nasa.gov/data/mro/mars_reconnaissance_orbiter/ctx/mrox_2757/data/J07_047671_1256_XN_54S338W.IMG\nsource_path: /remote/trove/geo/planet/Mars/CTX/pds/mrox_2757/J07_047671_1256_XN_54S338W.IMG\nShape: (8192, 2528)\n\n\n\nctx.source_path\n\nPath('/remote/trove/geo/planet/Mars/CTX/pds/mrox_2757/J07_047671_1256_XN_54S338W.IMG')\n\n\n\nctx.download()\n\nFile exists. Use `overwrite=True` to download fresh.\n\n\n\n\n\n\nThe creation of this library was in part supported by:\n\nNASA Cassini UVIS mission\nNASA SSW grant NNX15AH36G\nNASA PDART grant 80NSSC20K0875\nNASA SSW grant 80NSSC20K0748\nGerman Space Agency (DLR Bonn), grant 50 OO 2204, on behalf of the German Federal Ministry for Economic Affairs and Climate Action.\nThis research has made use of the USGS Integrated Software for Imagers and Spectrometers (ISIS)(Laura et al. 2022)." + }, + { + "objectID": "index.html#install", + "href": "index.html#install", + "title": "PlanetaryPy", + "section": "", + "text": "pip install planetarypy\nThis will pull in these other dependencies and their dependencies:\ntomlkit pandas pvl numpy python-dateutil tqdm lxml yarl hirise-tools kalasiris" + }, + { + "objectID": "index.html#suggested-standard-abbreviations", + "href": "index.html#suggested-standard-abbreviations", + "title": "PlanetaryPy", + "section": "", + "text": "Inside these docs the package will be called PLPY for brevity.\nA standard Python import could be: plp or plpy\n\nbecause the last p in plp can be pronounced out, we consider these equivalent for human conversation and pronounce these “plippy”." + }, + { + "objectID": "index.html#general-scope", + "href": "index.html#general-scope", + "title": "PlanetaryPy", + "section": "", + "text": "First and foremost this package should provide support in working with planetary science data.\nWith working we mean:\n\nlocating\nretrieving\nreading\nfurther processing\n\nof data.\n\n\nThis library manages, via its PDS tools, multiple PDS3 index files per instrument that can be used for identifying data of interest. These index files are automatically downloaded and converted to the very performant (and cloud-ready) parquet file format. > Parquet is able to store advanced datatypes like nan-capable integer and full datetime objects, as opposed to HDF5.\n\n\n\nThe interface to getting data is via a path-retrieving function based on a PDS product-id. If that product-id is available locally, the path will be returned. If it is not, it will previously be downloaded, stored in a systematic fashion organized by mission and instrument, and then the local path will be returned.\n\n\n\nFor now, the library only returns the path to the object and the user needs to sort out the reading process. A recently funded NASA project Planetary Data Reader will be integrated here, so that basic reading into memory can be provided.\nAs such, we anticipate two classes of reading support: 1. basic reading into numpy and/or xarray 1. added reader functionality like basic plots and basic geospatial processing, as supported by interested parties\nThere will exist larger other packages that focus on working with a given instrument’s data, in which case that package could become an affiliated package with the planetarypy GitHub organization, if so desired.\n\n\n\nIn the future, additional frequently used procedures will be added to this library, e.g. * frequently used GDAL/rasterio procedures * frequently used SPICE operations * like surface illumination on a given body" + }, + { + "objectID": "index.html#pds-tools", + "href": "index.html#pds-tools", + "title": "PlanetaryPy", + "section": "", + "text": "Look at the Apps docs to see what pds.apps exist for easily getting PDS indexes. The find_index app is specifically useful when you don’t know what index files exist.\nSo far, the following indexes are supported (but not necessarily all tested within PLPY):\n\nCassini\n\nISS (all)\nUVIS (all)\n\nMRO\n\nCTX EDR\nHiRISE\n\nEDR, RDR, DTM\n\nEDR index has a bug (as delivered by the team, reported), where I need to activate an existing fix for it.\n\n\n\nLRO\n\nDiviner (DLRE)\n\nEDR, RDR\n\nLOLA\n\nEDR, RDR\n\n\n\n\n\nMore indexes of other instruments can be easily added by following the existing structure of what has been copied into your config at ~/.planetarypy_config.toml.\nPlease consider submitting a pull request for adding further PDS index files into the config file at its source: https://github.com/michaelaye/nbplanetary/blob/master/planetarypy/data/planetarypy_config.toml" + }, + { + "objectID": "index.html#utils", + "href": "index.html#utils", + "title": "PlanetaryPy", + "section": "", + "text": "Find something in Utils for working with NASA timestamps and a well working URL download function url_retrieve, among other stuff." + }, + { + "objectID": "index.html#experimentinstrument-specific", + "href": "index.html#experimentinstrument-specific", + "title": "PlanetaryPy", + "section": "", + "text": "So far, planetarypy supports CTX EDR and HiRISE RGB.NOMAP data. Look at the CTX and HiRISE pages for descriptions of classes for working with these data." + }, + { + "objectID": "index.html#bug-reports", + "href": "index.html#bug-reports", + "title": "PlanetaryPy", + "section": "", + "text": "Please submit bug reports at https://github.com/michaelaye/nbplanetary/issues" + }, + { + "objectID": "index.html#how-to-use", + "href": "index.html#how-to-use", + "title": "PlanetaryPy", + "section": "", + "text": "See PDS apps for more details.\n\nfrom planetarypy.pds.apps import get_index\n\n\nctrindex = get_index(\"mro.ctx\", \"edr\", refresh=False)\nctrindex.sample(5, random_state=42) # setting random_state to always get same files for docs\n\n\n\n\n\n\n\n\nVOLUME_ID\nFILE_SPECIFICATION_NAME\nORIGINAL_PRODUCT_ID\nPRODUCT_ID\nIMAGE_TIME\nINSTRUMENT_ID\nINSTRUMENT_MODE_ID\nLINE_SAMPLES\nLINES\nSPATIAL_SUMMING\n...\nSUB_SOLAR_LATITUDE\nSUB_SPACECRAFT_LONGITUDE\nSUB_SPACECRAFT_LATITUDE\nSOLAR_DISTANCE\nSOLAR_LONGITUDE\nLOCAL_TIME\nIMAGE_SKEW_ANGLE\nRATIONALE_DESC\nDATA_QUALITY_DESC\nORBIT_NUMBER\n\n\n\n\n86101\nMROX_2757\nDATA/J07_047671_1256_XN_54S338W.IMG\n4A_04_10F0036A00\nJ07_047671_1256_XN_54S338W\n2016-09-27 00:24:54.682\nCTX\nNIFL\n2528\n8192\n1\n...\n-19.41\n338.09\n-54.43\n207762612.4\n230.58\n15.48\n90.1\nCrater in Noachis Terra\nOK\n47671\n\n\n54420\nMROX_1819\nDATA/D10_031170_1808_XN_00N221W.IMG\n4A_04_109C017D00\nD10_031170_1808_XN_00N221W\n2013-03-21 06:58:09.892\nCTX\nNIFL\n5056\n7168\n1\n...\n-24.39\n221.52\n0.88\n209925149.5\n286.15\n14.49\n90.1\nRide-along with HiRISE\nOK\n31170\n\n\n71053\nMROX_2331\nDATA/F10_039530_1470_XI_33S203W.IMG\n4A_04_10C9000F00\nF10_039530_1470_XI_33S203W\n2015-01-01 16:20:01.840\nCTX\nITL\n5056\n52224\n1\n...\n-25.3\n203.96\n-33.12\n207070298.2\n263.93\n15.2\n90.4\nTerrain in Terra Cimmeria\nOK\n39530\n\n\n51385\nMROX_1742\nDATA/D04_028919_2026_XN_22N327W.IMG\n4A_04_109002A800\nD04_028919_2026_XN_22N327W\n2012-09-26 21:17:00.483\nCTX\nNIFL\n5056\n6144\n1\n...\n0.67\n327.06\n22.78\n219814412.3\n178.44\n15.53\n90.1\nRide-along with HiRISE\nOK\n28919\n\n\n51923\nMROX_1757\nDATA/D05_029283_1524_XN_27S180W.IMG\n4A_04_1092020B00\nD05_029283_1524_XN_27S180W\n2012-10-25 05:44:21.786\nCTX\nNIFL\n5056\n9216\n1\n...\n-6.28\n178.36\n-27.56\n214830233.7\n194.72\n15.57\n90.1\nRide-along with HiRISE\nOK\n29283\n\n\n\n\n5 rows × 51 columns\n\n\n\n\nhirise_rdr = get_index(\"mro.hirise\", \"rdr\")\nhirise_rdr.sample(5, random_state=42)\n\n\n\n\n\n\n\n\nVOLUME_ID\nFILE_NAME_SPECIFICATION\nINSTRUMENT_HOST_ID\nINSTRUMENT_ID\nOBSERVATION_ID\nPRODUCT_ID\nPRODUCT_VERSION_ID\nTARGET_NAME\nORBIT_NUMBER\nMISSION_PHASE_NAME\n...\nLINE_PROJECTION_OFFSET\nSAMPLE_PROJECTION_OFFSET\nCORNER1_LATITUDE\nCORNER1_LONGITUDE\nCORNER2_LATITUDE\nCORNER2_LONGITUDE\nCORNER3_LATITUDE\nCORNER3_LONGITUDE\nCORNER4_LATITUDE\nCORNER4_LONGITUDE\n\n\n\n\n144822\nMROHR_0001\nRDR/ESP/ORB_074100_074199/ESP_074107_1410/ESP_...\nMRO\nHIRISE\nESP_074107_1410\nESP_074107_1410_COLOR\n1\nMARS\n74107\nExtended Science Phase\n...\n-4568562.5\n2009279.5\n-38.7446\n159.311\n-38.7465\n159.287\n-38.614\n159.269\n-38.6121\n159.293\n\n\n22518\nMROHR_0001\nRDR/ESP/ORB_014000_014099/ESP_014080_1040/ESP_...\nMRO\nHIRISE\nESP_014080_1040\nESP_014080_1040_RED\n1\nMARS\n14080\nExtended Science Phase\n...\n-3193960.0\n-845180.0\n-76.0185\n165.215\n-76.0315\n164.858\n-75.6958\n164.658\n-75.6831\n165.005\n\n\n86634\nMROHR_0001\nRDR/ESP/ORB_046300_046399/ESP_046395_1730/ESP_...\nMRO\nHIRISE\nESP_046395_1730\nESP_046395_1730_COLOR\n1\nMARS\n46395\nExtended Science Phase\n...\n-1584330.0\n-26573400.0\n-6.9957\n292.569\n-6.9979\n292.551\n-6.6838\n292.51\n-6.6815\n292.529\n\n\n138163\nMROHR_0001\nRDR/ESP/ORB_069100_069199/ESP_069178_2345/ESP_...\nMRO\nHIRISE\nESP_069178_2345\nESP_069178_2345_RED\n1\nMARS\n69178\nExtended Science Phase\n...\n12762196.0\n15708938.0\n53.8598\n76.7591\n53.8474\n76.602\n54.0013\n76.5672\n54.0137\n76.7249\n\n\n125490\nMROHR_0001\nRDR/ESP/ORB_063500_063599/ESP_063504_1995/ESP_...\nMRO\nHIRISE\nESP_063504_1995\nESP_063504_1995_COLOR\n1\nMARS\n63504\nExtended Science Phase\n...\n4638178.5\n12794202.0\n19.4523\n124.149\n19.45\n124.128\n19.5686\n124.113\n19.5709\n124.133\n\n\n\n\n5 rows × 54 columns" + }, + { + "objectID": "index.html#instrument-tools", + "href": "index.html#instrument-tools", + "title": "PlanetaryPy", + "section": "", + "text": "from planetarypy.ctx import CTX\n\n\npid = ctrindex.sample(random_state=42).squeeze().PRODUCT_ID\npid\n\n'J07_047671_1256_XN_54S338W'\n\n\n\nctx = CTX(pid)\nctx\n\nPRODUCT_ID: J07_047671_1256_XN_54S338W\nURL: https://pds-imaging.jpl.nasa.gov/data/mro/mars_reconnaissance_orbiter/ctx/mrox_2757/data/J07_047671_1256_XN_54S338W.IMG\nsource_path: /remote/trove/geo/planet/Mars/CTX/pds/mrox_2757/J07_047671_1256_XN_54S338W.IMG\nShape: (8192, 2528)\n\n\n\nctx.source_path\n\nPath('/remote/trove/geo/planet/Mars/CTX/pds/mrox_2757/J07_047671_1256_XN_54S338W.IMG')\n\n\n\nctx.download()\n\nFile exists. Use `overwrite=True` to download fresh." + }, + { + "objectID": "index.html#acknowledgements", + "href": "index.html#acknowledgements", + "title": "PlanetaryPy", + "section": "", + "text": "The creation of this library was in part supported by:\n\nNASA Cassini UVIS mission\nNASA SSW grant NNX15AH36G\nNASA PDART grant 80NSSC20K0875\nNASA SSW grant 80NSSC20K0748\nGerman Space Agency (DLR Bonn), grant 50 OO 2204, on behalf of the German Federal Ministry for Economic Affairs and Climate Action.\nThis research has made use of the USGS Integrated Software for Imagers and Spectrometers (ISIS)(Laura et al. 2022)." + }, + { + "objectID": "tutorials/tutorial.html", + "href": "tutorials/tutorial.html", + "title": "Tutorial", + "section": "", + "text": "from planetarypy.pds.apps import find_indexes, get_index, find_instruments\n\n\nfind_instruments?\n\n\nSignature: find_instruments(mission: str) -> list\nDocstring: Find existing instruments for a mission.\nFile: ~/Dropbox/src/nbplanetary/planetarypy/pds/apps.py\nType: function\n\n\n\n\nfind_instruments(\"mro\")\n\n['hirise', 'ctx']\n\n\nNow, seeing that the CTX instrument is supported, one could ask what index files (= catalogs) are available, using the dotted code for mission.instrument:\n\nfind_indexes(\"mro.ctx\")\n\n['edr']\n\n\nWe only have one index file for EDR data. Let’s get it, using the now 3-segments dot-code (it returns a pandas Dataframe):\n\nindex = get_index('mro.ctx.edr', refresh=False)\nindex.head()\n\n\n\n\n\n\n\n\nVOLUME_ID\nFILE_SPECIFICATION_NAME\nORIGINAL_PRODUCT_ID\nPRODUCT_ID\nIMAGE_TIME\nINSTRUMENT_ID\nINSTRUMENT_MODE_ID\nLINE_SAMPLES\nLINES\nSPATIAL_SUMMING\n...\nSUB_SOLAR_LATITUDE\nSUB_SPACECRAFT_LONGITUDE\nSUB_SPACECRAFT_LATITUDE\nSOLAR_DISTANCE\nSOLAR_LONGITUDE\nLOCAL_TIME\nIMAGE_SKEW_ANGLE\nRATIONALE_DESC\nDATA_QUALITY_DESC\nORBIT_NUMBER\n\n\n\n\n0\nMROX_0001\nDATA/CRU_000001_9999_XN_99N999W.IMG\n4A_04_0001000400\nCRU_000001_9999_XN_99N999W\n2005-08-30 15:40:21.549\nCTX\nNIFL\n5056\n1024\n1\n...\n0.0\n0.0\n0.0\n0.0\n278.89\n10.16\n0.0\nInstrument checkout image of space\nOK\n-4242\n\n\n1\nMROX_0001\nDATA/CRU_000002_9999_XN_99N999W.IMG\n4A_04_0001000500\nCRU_000002_9999_XN_99N999W\n2005-09-08 15:59:45.313\nCTX\nNIFL\n5056\n15360\n1\n...\n0.0\n0.0\n0.0\n0.0\n284.48\n4.6\n0.0\nCalibration image of the Moon\nOK\n-4126\n\n\n2\nMROX_0001\nDATA/CRU_000003_9999_XN_99N999W.IMG\n4A_04_0001000600\nCRU_000003_9999_XN_99N999W\n2005-09-08 16:03:37.927\nCTX\nNIFL\n5056\n2048\n1\n...\n0.0\n0.0\n0.0\n0.0\n284.48\n4.66\n0.0\nCalibration image of Omega Centauri (globular ...\nOK\n-4126\n\n\n3\nMROX_0001\nDATA/CRU_000004_9999_XN_99N999W.IMG\n4A_04_0001000700\nCRU_000004_9999_XN_99N999W\n2005-09-08 16:08:23.841\nCTX\nNIFL\n5056\n2048\n1\n...\n0.0\n0.0\n0.0\n0.0\n284.48\n4.74\n0.0\nCalibration image of Omega Centauri (globular ...\nOK\n-4126\n\n\n4\nMROX_0001\nDATA/CRU_000005_9999_XN_99N999W.IMG\n4A_04_0001000800\nCRU_000005_9999_XN_99N999W\n2005-09-08 16:11:18.649\nCTX\nNIFL\n5056\n21504\n1\n...\n0.0\n0.0\n0.0\n0.0\n284.48\n4.79\n0.0\nCalibration image of the Moon\nOK\n-4126\n\n\n\n\n5 rows × 51 columns\n\n\n\nYou might have ssen, that planetarypy realized that the existing index on my disk was outdated and proceeded to get an updated one.\nThe warning is about badly formatted data on the PDS for which planetarypy had to force path names to the correct letter case. This is not something we can influence, but we reported the issue at the PDS, and here, we just let the user know, that we fudged around that issue.\nNote that the catalog ascii times have been converted to proper datetime objects, using the utility functions in planetarypy.utils. This means that you can use these times to create proper plots over time in case you are interested in catalog statistics.\n\nindex.IMAGE_TIME\n\n0 2005-08-30 15:40:21.549\n1 2005-09-08 15:59:45.313\n2 2005-09-08 16:03:37.927\n3 2005-09-08 16:08:23.841\n4 2005-09-08 16:11:18.649\n ... \n142363 2023-03-01 00:01:37.834\n142364 2023-03-01 00:15:17.076\n142365 2023-03-01 00:19:04.486\n142366 2023-03-01 00:29:24.818\n142367 2023-03-01 00:43:08.662\nName: IMAGE_TIME, Length: 142368, dtype: datetime64[ns]\n\n\nUsing standard pandas operations, we can now filte the data down, and identify a data product we are interested in:\n\nindex.columns\n\nIndex(['VOLUME_ID', 'FILE_SPECIFICATION_NAME', 'ORIGINAL_PRODUCT_ID',\n 'PRODUCT_ID', 'IMAGE_TIME', 'INSTRUMENT_ID', 'INSTRUMENT_MODE_ID',\n 'LINE_SAMPLES', 'LINES', 'SPATIAL_SUMMING', 'SCALED_PIXEL_WIDTH',\n 'PIXEL_ASPECT_RATIO', 'EMISSION_ANGLE', 'INCIDENCE_ANGLE',\n 'PHASE_ANGLE', 'CENTER_LONGITUDE', 'CENTER_LATITUDE',\n 'UPPER_LEFT_LONGITUDE', 'UPPER_LEFT_LATITUDE', 'UPPER_RIGHT_LONGITUDE',\n 'UPPER_RIGHT_LATITUDE', 'LOWER_LEFT_LONGITUDE', 'LOWER_LEFT_LATITUDE',\n 'LOWER_RIGHT_LONGITUDE', 'LOWER_RIGHT_LATITUDE', 'MISSION_PHASE_NAME',\n 'TARGET_NAME', 'SPACECRAFT_CLOCK_START_COUNT',\n 'FOCAL_PLANE_TEMPERATURE', 'LINE_EXPOSURE_DURATION', 'OFFSET_MODE_ID',\n 'SAMPLE_FIRST_PIXEL', 'SCALED_IMAGE_WIDTH', 'SCALED_IMAGE_HEIGHT',\n 'SPACECRAFT_ALTITUDE', 'TARGET_CENTER_DISTANCE', 'SLANT_DISTANCE',\n 'USAGE_NOTE', 'NORTH_AZIMUTH', 'SUB_SOLAR_AZIMUTH',\n 'SUB_SOLAR_LONGITUDE', 'SUB_SOLAR_LATITUDE', 'SUB_SPACECRAFT_LONGITUDE',\n 'SUB_SPACECRAFT_LATITUDE', 'SOLAR_DISTANCE', 'SOLAR_LONGITUDE',\n 'LOCAL_TIME', 'IMAGE_SKEW_ANGLE', 'RATIONALE_DESC', 'DATA_QUALITY_DESC',\n 'ORBIT_NUMBER'],\n dtype='object')\n\n\n\nindex.EMISSION_ANGLE.describe()\n\ncount 142368.0\nmean 4.396005\nstd 18.999974\nmin 0.0\n25% 0.1\n50% 1.56\n75% 5.94\nmax 999.9\nName: EMISSION_ANGLE, dtype: Float64\n\n\n\nindex.LOCAL_TIME.describe()\n\ncount 142368.0\nmean 15.055919\nstd 1.427996\nmin 0.0\n25% 14.65\n50% 15.12\n75% 15.53\nmax 23.99\nName: LOCAL_TIME, dtype: Float64\n\n\n\nangle_filter = index.EMISSION_ANGLE < 1.0\n\nLet’s also calculate a mean latitude and longitude instead of the image corners, for rough location filtering. As a habit, we recommend to assign lower case letters to column names that we add on top of the PDS ones:\n\nindex = index.assign(\n lat_mean=(\n index.UPPER_LEFT_LATITUDE\n + index.UPPER_RIGHT_LATITUDE\n + index.LOWER_LEFT_LATITUDE\n + index.LOWER_RIGHT_LATITUDE) /\n 4)\n\n\nindex = index.assign(\n lon_mean=(\n index.UPPER_LEFT_LONGITUDE\n + index.UPPER_RIGHT_LONGITUDE\n + index.LOWER_LEFT_LONGITUDE\n + index.LOWER_RIGHT_LONGITUDE) /\n 4)\n\n\nindex.info()\n\n<class 'pandas.core.frame.DataFrame'>\nRangeIndex: 142368 entries, 0 to 142367\nData columns (total 53 columns):\n # Column Non-Null Count Dtype \n--- ------ -------------- ----- \n 0 VOLUME_ID 142368 non-null string \n 1 FILE_SPECIFICATION_NAME 142368 non-null string \n 2 ORIGINAL_PRODUCT_ID 142368 non-null string \n 3 PRODUCT_ID 142368 non-null string \n 4 IMAGE_TIME 142368 non-null datetime64[ns]\n 5 INSTRUMENT_ID 142368 non-null string \n 6 INSTRUMENT_MODE_ID 142368 non-null string \n 7 LINE_SAMPLES 142368 non-null Int64 \n 8 LINES 142368 non-null Int64 \n 9 SPATIAL_SUMMING 142368 non-null Int64 \n 10 SCALED_PIXEL_WIDTH 142368 non-null Float64 \n 11 PIXEL_ASPECT_RATIO 142368 non-null Float64 \n 12 EMISSION_ANGLE 142368 non-null Float64 \n 13 INCIDENCE_ANGLE 142368 non-null Float64 \n 14 PHASE_ANGLE 142368 non-null Float64 \n 15 CENTER_LONGITUDE 142368 non-null Float64 \n 16 CENTER_LATITUDE 142368 non-null Float64 \n 17 UPPER_LEFT_LONGITUDE 142368 non-null Float64 \n 18 UPPER_LEFT_LATITUDE 142368 non-null Float64 \n 19 UPPER_RIGHT_LONGITUDE 142368 non-null Float64 \n 20 UPPER_RIGHT_LATITUDE 142368 non-null Float64 \n 21 LOWER_LEFT_LONGITUDE 142368 non-null Float64 \n 22 LOWER_LEFT_LATITUDE 142368 non-null Float64 \n 23 LOWER_RIGHT_LONGITUDE 142368 non-null Float64 \n 24 LOWER_RIGHT_LATITUDE 142368 non-null Float64 \n 25 MISSION_PHASE_NAME 142368 non-null string \n 26 TARGET_NAME 142368 non-null string \n 27 SPACECRAFT_CLOCK_START_COUNT 142368 non-null string \n 28 FOCAL_PLANE_TEMPERATURE 142368 non-null Float64 \n 29 LINE_EXPOSURE_DURATION 142368 non-null Float64 \n 30 OFFSET_MODE_ID 142368 non-null string \n 31 SAMPLE_FIRST_PIXEL 142368 non-null Int64 \n 32 SCALED_IMAGE_WIDTH 142368 non-null Float64 \n 33 SCALED_IMAGE_HEIGHT 142368 non-null Float64 \n 34 SPACECRAFT_ALTITUDE 142368 non-null Float64 \n 35 TARGET_CENTER_DISTANCE 142368 non-null Float64 \n 36 SLANT_DISTANCE 142368 non-null Float64 \n 37 USAGE_NOTE 142368 non-null string \n 38 NORTH_AZIMUTH 142368 non-null Float64 \n 39 SUB_SOLAR_AZIMUTH 142368 non-null Float64 \n 40 SUB_SOLAR_LONGITUDE 142368 non-null Float64 \n 41 SUB_SOLAR_LATITUDE 142368 non-null Float64 \n 42 SUB_SPACECRAFT_LONGITUDE 142368 non-null Float64 \n 43 SUB_SPACECRAFT_LATITUDE 142368 non-null Float64 \n 44 SOLAR_DISTANCE 142368 non-null Float64 \n 45 SOLAR_LONGITUDE 142368 non-null Float64 \n 46 LOCAL_TIME 142368 non-null Float64 \n 47 IMAGE_SKEW_ANGLE 142368 non-null Float64 \n 48 RATIONALE_DESC 142368 non-null string \n 49 DATA_QUALITY_DESC 142368 non-null string \n 50 ORBIT_NUMBER 142368 non-null Int64 \n 51 lat_mean 142368 non-null Float64 \n 52 lon_mean 142368 non-null Float64 \ndtypes: Float64(34), Int64(5), datetime64[ns](1), string(13)\nmemory usage: 62.9 MB\n\n\n\nlat_filter = index.lat_mean.between(-80,-60)\nlon_filter = index.lon_mean.between(0, 10)\n\n\nindex[angle_filter & lat_filter & lon_filter]\n\n\n\n\n\n\n\n\nVOLUME_ID\nFILE_SPECIFICATION_NAME\nORIGINAL_PRODUCT_ID\nPRODUCT_ID\nIMAGE_TIME\nINSTRUMENT_ID\nINSTRUMENT_MODE_ID\nLINE_SAMPLES\nLINES\nSPATIAL_SUMMING\n...\nSUB_SPACECRAFT_LATITUDE\nSOLAR_DISTANCE\nSOLAR_LONGITUDE\nLOCAL_TIME\nIMAGE_SKEW_ANGLE\nRATIONALE_DESC\nDATA_QUALITY_DESC\nORBIT_NUMBER\nlat_mean\nlon_mean\n\n\n\n\n1267\nMROX_0035\nDATA/P03_002074_1155_XN_64S004W.IMG\n4A_04_1008005C00\nP03_002074_1155_XN_64S004W\n2007-01-05 01:02:50.418\nCTX\nNIFL\n5056\n12288\n1\n...\n-64.59\n225779573.9\n161.53\n16.02\n90.1\nDunes in Wegener Crater in MOC R15-01815\nOK\n2074\n-64.59\n4.61\n\n\n4551\nMROX_0165\nDATA/P09_004738_1020_XN_78S008W.IMG\n4A_04_1014016300\nP09_004738_1020_XN_78S008W\n2007-07-31 14:55:12.379\nCTX\nNIFL\n5056\n52224\n1\n...\n-77.97\n210058626.6\n286.93\n15.36\n90.4\nSouth polar landforms\nOK\n4738\n-77.965\n5.9325\n\n\n4677\nMROX_0173\nDATA/P10_004883_1020_XN_78S005W.IMG\n4A_04_1016007800\nP10_004883_1020_XN_78S005W\n2007-08-11 22:05:40.494\nCTX\nNIFL\n5056\n52224\n1\n...\n-78.09\n211455781.6\n293.82\n15.27\n90.4\nSouth polar seasonal cap edge\nOK\n4883\n-78.08\n4.57\n\n\n5184\nMROX_0197\nDATA/P11_005252_1199_XI_60S008W.IMG\n4A_04_101900A800\nP11_005252_1199_XI_60S008W\n2007-09-09 16:17:03.275\nCTX\nITL\n5056\n14336\n1\n...\n-60.18\n215826377.3\n310.92\n14.58\n90.1\nSouth mid- to high-latitude crater\nOK\n5252\n-60.1875\n8.6425\n\n\n5395\nMROX_0209\nDATA/P11_005384_1066_XN_73S007W.IMG\n4A_04_1018017C00\nP11_005384_1066_XN_73S007W\n2007-09-19 23:03:52.412\nCTX\nNIFL\n5056\n35840\n1\n...\n-73.48\n217613174.8\n316.85\n14.82\n90.3\nSisyphi Cavi\nOK\n5384\n-73.48\n7.05\n\n\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n\n\n133106\nMROX_4264\nDATA/U09_074575_1037_XN_76S005W.IMG\n4A_04_117A02AC00\nU09_074575_1037_XN_76S005W\n2022-06-24 05:06:01.401\nCTX\nNIFL\n5056\n52224\n1\n...\n-76.26\n206646214.2\n252.89\n15.96\n90.4\nSisyphi Cavi region\nOK\n74575\n-76.2575\n4.98\n\n\n133926\nMROX_4298\nDATA/U10_074878_1161_XN_63S005W.IMG\n4A_04_117C022300\nU10_074878_1161_XN_63S005W\n2022-07-17 19:55:57.184\nCTX\nNIFL\n2528\n24576\n1\n...\n-63.93\n207381603.7\n267.84\n15.35\n90.2\nSouthern highlands\nOK\n74878\n-63.94\n5.53\n\n\n134438\nMROX_4315\nDATA/U10_075023_1075_XN_72S001W.IMG\n4A_04_117C042B00\nU10_075023_1075_XN_72S001W\n2022-07-29 03:04:41.315\nCTX\nNIFL\n5056\n7168\n1\n...\n-72.61\n208145471.6\n274.94\n15.41\n90.1\nRide-along with HiRISE\nOK\n75023\n-72.6275\n1.005\n\n\n135612\nMROX_4352\nDATA/U12_075498_1055_XN_74S006W.IMG\n4A_04_1180007200\nU12_075498_1055_XN_74S006W\n2022-09-04 03:17:19.126\nCTX\nNIFL\n5056\n7168\n1\n...\n-74.52\n212296356.7\n297.69\n15.13\n90.1\nRide-along with HiRISE\nOK\n75498\n-74.535\n6.62\n\n\n136976\nMROX_4402\nDATA/U13_076012_1155_XN_64S004W.IMG\n4A_04_118201BB00\nU13_076012_1155_XN_64S004W\n2022-10-14 04:35:24.111\nCTX\nNIFL\n5056\n7168\n1\n...\n-64.62\n218924928.8\n321.08\n14.71\n90.1\nRide-along with HiRISE\nOK\n76012\n-64.6275\n3.995\n\n\n\n\n119 rows × 53 columns\n\n\n\nCopying a PRODUCT_ID, we can now automatically download it via the CTX utilities:\n\npid = \"P03_002074_1155_XN_64S004W\"\n\n\nfrom planetarypy import ctx\n\nAbove could issue a warning that is about not finding an ISIS installation, which is required for SOME of this library’s features. Make sure your current environment has the environment variable ISISROOT and ISISDATA defined, so that planetarypy can find the ISIS tools, in case you want to use functions related to them.\nNow let’s use the CTX class to access data:\n\ndata = ctx.CTX(pid)\n\n\ndata.download()\n\nFile exists. Use `overwrite=True` to download fresh.\n\n\nThe data was downloaded to a mission- and instrument-based storage folder that was defined the first time you imported planetarypy. You can verify it’s location by looking at the config object:\n\nfrom planetarypy.config import config\n\n\nconfig.storage_root\n\nPath('/home/ayek72/mnt/slowdata/planetarypy')\n\n\nWe can now read the data into a multi-dimensional xarray, which supports elaborate indexing via its coordinates.\n\ndata.edr_da\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n<xarray.DataArray 'P03_002074_1155 EDR' (y: 12288, x: 5056)>\n[62128128 values with dtype=uint8]\nCoordinates:\n * x (x) float64 0.5 1.5 2.5 3.5 ... 5.054e+03 5.054e+03 5.056e+03\n * y (y) float64 0.5 1.5 2.5 3.5 ... 1.229e+04 1.229e+04 1.229e+04\nAttributes: (12/19)\n BANDWIDTH: \n CENTER_FILTER_WAVELENGTH: \n DATA_SET_ID: \"MRO-M-CTX-2-EDR-L0-V1.0\"\n FILTER_NAME: \n INSTRUMENT_ID: CTX\n INSTRUMENT_NAME: \"CONTEXT CAMERA\"\n ... ...\n START_TIME: 2007-01-05T01:02:50.418\n STOP_TIME: 2007-01-05T01:03:13.479\n TARGET_NAME: MARS\n _FillValue: 0\n scale_factor: 1.0\n add_offset: 0.0xarray.DataArray'P03_002074_1155 EDR'y: 12288x: 5056...[62128128 values with dtype=uint8]Coordinates: (2)x(x)float640.5 1.5 2.5 ... 5.054e+03 5.056e+03array([5.0000e-01, 1.5000e+00, 2.5000e+00, ..., 5.0535e+03, 5.0545e+03,\n 5.0555e+03])y(y)float640.5 1.5 2.5 ... 1.229e+04 1.229e+04array([5.00000e-01, 1.50000e+00, 2.50000e+00, ..., 1.22855e+04, 1.22865e+04,\n 1.22875e+04])Indexes: (2)xPandasIndexPandasIndex(Float64Index([ 0.5, 1.5, 2.5, 3.5, 4.5, 5.5, 6.5, 7.5,\n 8.5, 9.5,\n ...\n 5046.5, 5047.5, 5048.5, 5049.5, 5050.5, 5051.5, 5052.5, 5053.5,\n 5054.5, 5055.5],\n dtype='float64', name='x', length=5056))yPandasIndexPandasIndex(Float64Index([ 0.5, 1.5, 2.5, 3.5, 4.5, 5.5, 6.5,\n 7.5, 8.5, 9.5,\n ...\n 12278.5, 12279.5, 12280.5, 12281.5, 12282.5, 12283.5, 12284.5,\n 12285.5, 12286.5, 12287.5],\n dtype='float64', name='y', length=12288))Attributes: (19)BANDWIDTH :CENTER_FILTER_WAVELENGTH :DATA_SET_ID :\"MRO-M-CTX-2-EDR-L0-V1.0\"FILTER_NAME :INSTRUMENT_ID :CTXINSTRUMENT_NAME :\"CONTEXT CAMERA\"MISSION_NAME :NOTE :PRODUCER_INSTITUTION_NAME :PRODUCT_CREATION_TIME :2007-08-08T23:29:12PRODUCT_ID :\"P03_002074_1155_XN_64S004W\"PRODUCT_TYPE :SPACECRAFT_NAME :MARS_RECONNAISSANCE_ORBITERSTART_TIME :2007-01-05T01:02:50.418STOP_TIME :2007-01-05T01:03:13.479TARGET_NAME :MARS_FillValue :0scale_factor :1.0add_offset :0.0\n\n\nBut one also get the image data simply as a numpy array:\n\ndata.edr_da.values\n\narray([[ 9, 9, 10, ..., 8, 10, 8],\n [ 9, 8, 10, ..., 9, 10, 9],\n [ 9, 8, 10, ..., 8, 11, 10],\n ...,\n [11, 10, 11, ..., 10, 10, 10],\n [10, 9, 10, ..., 9, 10, 10],\n [11, 10, 10, ..., 11, 11, 10]], dtype=uint8)\n\n\nOr plot the image using holoviews and datashader, so that even large images won’t bog down your browser:\n\ndata.plot_edr()\n\n\n\n\n\n\n \n\n\n\n\nNote, that the above data is the uncalibrated EDR, so the dynamics of the image seem a little rough. If you have configured the ISIS properly, so that the current Python environment is aware of it (using ISISROOT and ISISDATA env variables), you can calibrate this data yourself now:" + }, + { + "objectID": "tutorials/pdw_2023.html", + "href": "tutorials/pdw_2023.html", + "title": "On the way to a core PlanetaryPy Package", + "section": "", + "text": "PlanetaryPy organization is community effort to\n\ndevelop a core Python package for planetary science\nhelp other planetary science Python programmers to disseminate their work\n\nThis talk is about the core package status only." + }, + { + "objectID": "tutorials/pdw_2023.html#what-is-this", + "href": "tutorials/pdw_2023.html#what-is-this", + "title": "On the way to a core PlanetaryPy Package", + "section": "", + "text": "PlanetaryPy organization is community effort to\n\ndevelop a core Python package for planetary science\nhelp other planetary science Python programmers to disseminate their work\n\nThis talk is about the core package status only." + }, + { + "objectID": "tutorials/pdw_2023.html#core-package-work-plan", + "href": "tutorials/pdw_2023.html#core-package-work-plan", + "title": "On the way to a core PlanetaryPy Package", + "section": "Core package work plan", + "text": "Core package work plan\n\nI am since long working on a core package draft.\nNothing is especially clever, the structured unification is the clue!\nShall be submitted (done?) to the community members for review.\nAfter successful review open for public pull requests and hackathons." + }, + { + "objectID": "tutorials/pdw_2023.html#core-package-focal-points", + "href": "tutorials/pdw_2023.html#core-package-focal-points", + "title": "On the way to a core PlanetaryPy Package", + "section": "Core package focal points", + "text": "Core package focal points\n\nEasier access, download, and local management of\n\nPDS data\nSPICE kernels\n\nRemoving need to learn various web interfaces for different data\nWorking easier with collections of PDS data\nEasy basic SPICE calculations with human readable I/F\nSome web and time related utilities" + }, + { + "objectID": "tutorials/pdw_2023.html#pds-indexes-1", + "href": "tutorials/pdw_2023.html#pds-indexes-1", + "title": "On the way to a core PlanetaryPy Package", + "section": "PDS Indexes", + "text": "PDS Indexes\n\n\n\nPDS Indexes contain useful meta-data for PDS datasets\nplanetarypy provides access to these via a config file\n\npull requests to config file will add more findable indices!\n\nconfig file tells planetarypy where to find index\n\n\n\nplanetarypy downloads index file and\nstored as parquet file, ready for pandas based analysis.\ntells user when new index is available" + }, + { + "objectID": "tutorials/pdw_2023.html#example-use", + "href": "tutorials/pdw_2023.html#example-use", + "title": "On the way to a core PlanetaryPy Package", + "section": "Example use", + "text": "Example use\n\nfrom planetarypy.pds.apps import get_index\n\ndf = get_index(\"cassini.iss\", \"index\")\nprint(df.info())\ndf.head(3)[\"FILE_NAME IMAGE_MID_TIME IMAGE_OBSERVATION_TYPE\".split()]\n\n<class 'pandas.core.frame.DataFrame'>\nRangeIndex: 407299 entries, 0 to 407298\nColumns: 140 entries, FILE_NAME to STANDARD_DATA_PRODUCT_ID\ndtypes: Float64(70), Int64(20), datetime64[ns](7), string(43)\nmemory usage: 470.0 MB\nNone\n\n\n\n\n\n\n\n\n\nFILE_NAME\nIMAGE_MID_TIME\nIMAGE_OBSERVATION_TYPE\n\n\n\n\n0\nN1454725799_1.IMG\n2004-02-06 02:07:06.458\nOPNAV\n\n\n1\nN1454726579_1.IMG\n2004-02-06 02:20:06.362\nOPNAV\n\n\n2\nN1454727359_1.IMG\n2004-02-06 02:33:06.397\nOPNAV" + }, + { + "objectID": "tutorials/pdw_2023.html#instrument-data-1", + "href": "tutorials/pdw_2023.html#instrument-data-1", + "title": "On the way to a core PlanetaryPy Package", + "section": "Instrument data", + "text": "Instrument data\n\nMeant to serve as basic data access, read, and access classes\n\nto be boosted in the future by the GOAT PDS reader pdr by Million, Inc.\n\nconfig file controls what data levels are accessible\n\nand how they are stored locally\n\ncurrently CTX, HiRISE, UVIS, CISS are supported (Diviner in the works)" + }, + { + "objectID": "tutorials/pdw_2023.html#example-use-hirise", + "href": "tutorials/pdw_2023.html#example-use-hirise", + "title": "On the way to a core PlanetaryPy Package", + "section": "Example use HiRISE", + "text": "Example use HiRISE\n\nfrom planetarypy.hirise import ProductPathfinder as PPF\n\nppf = PPF(\"PSP_003092_0985_RED\")\n\nprint(ppf.jp2_path)\nprint(ppf.homepage)\nprint(ppf.abrowse_path)\nprint(ppf.nomap_thumbnail_path)\n\n\n\n\n\n\n\n\n\n\n\nRDR/PSP/ORB_003000_003099/PSP_003092_0985/PSP_003092_0985_RED.JP2\nhttps://uahirise.org/PSP_003092_0985\nEXTRAS/RDR/PSP/ORB_003000_003099/PSP_003092_0985/PSP_003092_0985_RED.abrowse.jpg\nEXTRAS/RDR/PSP/ORB_003000_003099/PSP_003092_0985/PSP_003092_0985_RED.NOMAP.thumb.jpg" + }, + { + "objectID": "tutorials/pdw_2023.html#example-use-ctxcollection", + "href": "tutorials/pdw_2023.html#example-use-ctxcollection", + "title": "On the way to a core PlanetaryPy Package", + "section": "Example use CTXCollection", + "text": "Example use CTXCollection\n\nfrom planetarypy.ctx import CTXCollection\n\ncoll = CTXCollection.by_month(\"F01\")\nprint(coll.n_items)\nprint(len(coll.get_corrupted()))\n\n1321\n35" + }, + { + "objectID": "tutorials/pdw_2023.html#archived-spice-kernel-sets", + "href": "tutorials/pdw_2023.html#archived-spice-kernel-sets", + "title": "On the way to a core PlanetaryPy Package", + "section": "Archived SPICE kernel sets", + "text": "Archived SPICE kernel sets\n\n\n\nNAIF offers archived mission kernel sets for 33 missions:\nKernels can be subset by time window using Subset link.\nplanetarypy offers programmatic wrapper around subset feature.\n\n\n\nZip file unpacked.\nKernel files stored locally and logically.\nMeta-kernel edited appropriately and immediately loadable." + }, + { + "objectID": "tutorials/pdw_2023.html#example-use-1", + "href": "tutorials/pdw_2023.html#example-use-1", + "title": "On the way to a core PlanetaryPy Package", + "section": "Example use", + "text": "Example use\n\nfrom planetarypy.spice import kernels\n\nkernels.datasets.drop(\"path\", axis=1).head()\n\n\n\n\n\n\n\n\nMission Name\nPDS3 or PDS4\nData Size (GB)\nStart Time\nStop Time\n\n\nshorthand\n\n\n\n\n\n\n\n\n\nbc\nBepiColombo\n4\n2.3\n2018-10-20\n2023-06-21\n\n\ncassini\nCassini Orbiter\n3\n62.5\n1997-10-15\n2017-09-15\n\n\nclementine\nClementine\n3\n0.8\n1994-01-26\n1994-05-07\n\n\ndart\nDART\n4\n10.0\n2021-11-09\n2050-01-01\n\n\ndawn\nDAWN\n3\n86.4\n2007-09-27\n2018-10-31\n\n\n\n\n\n\n\n\nTwo main user functions:\n\nget_metakernel_and_files\n\nwill check if the kernel files are already locally available\nif not, download kernels\nreturns the path to the edited meta-kernel\n\nlist_kernels_for_day\n\nwill only list kernel filenames valid for the given day" + }, + { + "objectID": "tutorials/pdw_2023.html#generic-kernels", + "href": "tutorials/pdw_2023.html#generic-kernels", + "title": "On the way to a core PlanetaryPy Package", + "section": "Generic kernels", + "text": "Generic kernels\n\nManages a minimal set for basic illumination calculations\nCurrently slightly biased for Mars but many other bodies work\nKernels are automatically downloaded and loaded when needed." + }, + { + "objectID": "tutorials/pdw_2023.html#example-use-2", + "href": "tutorials/pdw_2023.html#example-use-2", + "title": "On the way to a core PlanetaryPy Package", + "section": "Example use", + "text": "Example use\n\nfrom planetarypy.spice.spicer import MoonSpicer\n\nmoon = MoonSpicer(\"2022-02-22\")\nprint(f\"Sol. const: {moon.solar_constant:.1f}\")\nmoon.set_spoint_by(lat=0, lon=0)\nmoon.aspect = 180\nmoon.tilt = 30\nprint(f\"Irradiance on tilted surface element: {moon.F_tilt:.1f}\")\n\nSol. const: 1388.4 W / m2\nIrradiance on tilted surface element: 412.5 W / m2" + }, + { + "objectID": "api/pds.utils.html", + "href": "api/pds.utils.html", + "title": "PDS Utils", + "section": "", + "text": "source\n\nIndexLabel\n\n IndexLabel (labelpath:Union[str,pathlib.Path])\n\nSupport working with label files of PDS Index tables.\n\n\n\n\n\n\n\n\n\nType\nDetails\n\n\n\n\nlabelpath\nUnion\nPath to the labelfile for a PDS Indexfile.The actual table should reside in the same folder to be automatically parsedwhen calling the read_index_data method.\n\n\n\n\nsource\n\n\nindex_to_df\n\n index_to_df (indexpath:Union[str,pathlib.Path],\n label:__main__.IndexLabel, convert_times=True)\n\nThe main reader function for PDS Indexfiles.\nIn conjunction with an IndexLabel object that figures out the column widths, this reader should work for all PDS TAB files.\n\n\n\n\n\n\n\n\n\n\nType\nDefault\nDetails\n\n\n\n\nindexpath\nUnion\n\nPath to the index TAB file\n\n\nlabel\nIndexLabel\n\nLabel object that has both the column names and the columns widths as attributes‘colnames’ and ‘colspecs’\n\n\nconvert_times\nbool\nTrue\nSwitch to control if to convert columns with “TIME” in name (unless COUNT is as well in name) to datetime\n\n\n\n\nsource\n\n\nPVLColumn\n\n PVLColumn (pvlobj)\n\nManages just one of the columns in a table that is described via PVL.\n\nsource\n\n\ndecode_line\n\n decode_line (linedata:str, labelpath:Union[str,pathlib.Path])\n\nDecode one line of tabbed data with the appropriate label file.\n\n\n\n\n\n\n\n\n\nType\nDetails\n\n\n\n\nlinedata\nstr\nOne line of a .tab data file\n\n\nlabelpath\nUnion\nPath to the appropriate label that describes the data.\n\n\n\n\nsource\n\n\nfind_mixed_type_cols\n\n find_mixed_type_cols (df:pandas.core.frame.DataFrame, fix:bool=True)\n\nFor a given dataframe, find the columns that are of mixed type.\nTool to help with the performance warning when trying to save a pandas DataFrame as a HDF. When a column changes datatype somewhere, pickling occurs, slowing down the reading process of the HDF file.\n\n\n\n\n\n\n\n\n\n\nType\nDefault\nDetails\n\n\n\n\ndf\nDataFrame\n\nDataframe to be searched for mixed data-types\n\n\nfix\nbool\nTrue\nSwitch to control if NaN values in these problem columns should be replaced by the string ‘UNKNOWN’\n\n\nReturns\nlist\n\nList of column names that have data type changes within themselves.\n\n\n\n\nsource\n\n\nfix_hirise_edrcumindex\n\n fix_hirise_edrcumindex (infname:Union[str,pathlib.Path],\n outfname:Union[str,pathlib.Path])\n\nFix HiRISE EDRCUMINDEX.\nThe HiRISE EDRCUMINDEX has some broken lines where the SCAN_EXPOSURE_DURATION is of format F10.4 instead of the defined F9.4. This function simply replaces those incidences with one less decimal fraction, so 20000.0000 becomes 20000.000.\n\n\n\n\nType\nDetails\n\n\n\n\ninfname\nUnion\nPath to broken EDRCUMINDEX.TAB\n\n\noutfname\nUnion\nPath where to store the fixed TAB file" + }, + { + "objectID": "api/cassini_iss.html", + "href": "api/cassini_iss.html", + "title": "Cassini ISS", + "section": "", + "text": "storage_root\n\nPath('/Users/maye/planetarypy_data/missions/cassini/iss')\n\n\n\nsource\n\nDataRetriever\n\n DataRetriever (pid)\n\nInitialize self. See help(type(self)) for accurate signature.\n\n\n\n\nDetails\n\n\n\n\npid\nPDS product_id, e.g. N1454725799\n\n\n\n\npid = \"N1454725799\"\n\n\ndm = DataRetriever(pid)\n\n\ndm.raw_fname\n\n'N1454725799_1.IMG'\n\n\n\ndm.raw_data_url\n\nURL('https://opus.pds-rings.seti.org/holdings/volumes/COISS_2xxx/COISS_2001/data/1454725799_1455008789/N1454725799_1.IMG')\n\n\n\ndm.raw_label_url\n\nURL('https://opus.pds-rings.seti.org/holdings/volumes/COISS_2xxx/COISS_2001/data/1454725799_1455008789/N1454725799_1.LBL')\n\n\n\ndm.raw_prefix_fmt_url\n\nURL('https://opus.pds-rings.seti.org/holdings/volumes/COISS_2xxx/COISS_2001/label/prefix2.fmt')\n\n\n\ndm.raw_tlmtab_url\n\nURL('https://opus.pds-rings.seti.org/holdings/volumes/COISS_2xxx/COISS_2001/label/tlmtab.fmt')\n\n\n\ndm.calib_data_url\n\nURL('https://opus.pds-rings.seti.org/holdings/calibrated/COISS_2xxx/COISS_2001/data/1454725799_1455008789/N1454725799_1_CALIB.IMG')\n\n\n\nsource\n\n\nISS\n\n ISS (pid)\n\nInitialize self. See help(type(self)) for accurate signature.\n\nid = \"N1874681996\"\nid = \"N1454725799\"\n# id = \"N1878581142\"\n\n\nlist(storage_root.rglob(f\"{id}*\"))\n\n[Path('/Users/maye/planetarypy_data/missions/cassini/iss/N1454725799'),\n Path('/Users/maye/planetarypy_data/missions/cassini/iss/N1454725799/N1454725799_1_CALIB.IMG')]\n\n\n\niss = ISS(pid)\n\nFound 1 obsids.\n\n\n\niss.local_folder\n\nPath('/Users/maye/planetarypy_data/missions/cassini/iss/N1454725799')\n\n\n\niss.raw_data_url\n\nURL('https://opus.pds-rings.seti.org/holdings/volumes/COISS_2xxx/COISS_2001/data/1454725799_1455008789/N1454725799_1.IMG')\n\n\n\niss.raw_tlmtab_url\n\nURL('https://opus.pds-rings.seti.org/holdings/volumes/COISS_2xxx/COISS_2001/label/tlmtab.fmt')\n\n\n\niss.download_calib()\n\nFile exists. Use `overwrite` to force re-download.\n\n\n\nconfig.storage_root\n\nPath('/Users/maye/planetarypy_data')\n\n\n\niss.dict.keys()\n\ndict_keys(['coiss_raw', 'coiss_calib', 'coiss_thumb', 'coiss_medium', 'coiss_full', 'coiss_documentation', 'rms_index', 'inventory', 'planet_geometry', 'moon_geometry', 'ring_geometry', 'browse_thumb', 'browse_small', 'browse_medium', 'browse_full'])\n\n\n\niss.local_calib_path\n\nPath('/Users/maye/planetarypy_data/missions/cassini/iss/N1454725799/N1454725799_1_CALIB.IMG')\n\n\n\niss.calib_data_url\n\nURL('https://opus.pds-rings.seti.org/holdings/calibrated/COISS_2xxx/COISS_2001/data/1454725799_1455008789/N1454725799_1_CALIB.IMG')\n\n\n\ndm.calib_data_url\n\nURL('https://opus.pds-rings.seti.org/holdings/calibrated/COISS_2xxx/COISS_2001/data/1454725799_1455008789/N1454725799_1_CALIB.IMG')\n\n\n\niss.raw_data_url\n\nURL('https://opus.pds-rings.seti.org/holdings/volumes/COISS_2xxx/COISS_2001/data/1454725799_1455008789/N1454725799_1.IMG')\n\n\n\niss.volume\n\n'COISS_2001'\n\n\n\niss.local_folder\n\nPath('/Users/maye/planetarypy_data/missions/cassini/iss/N1454725799')\n\n\n\ndef get_raw_data_path(product_id):\n iss = ISS(product_id)\n return iss.local_data_path\n\n\nid\n\n'N1454725799'\n\n\n\nlist(storage_root.glob(f\"**/{id}\"))\n\n[Path('/Users/maye/planetarypy_data/missions/cassini/iss/N1454725799')]\n\n\n\nstorage_root\n\nPath('/Users/maye/planetarypy_data/missions/cassini/iss')\n\n\n\n!ls {storage_root}\n\nN1454725799/ N1874681996/ indexes/\n\n\n\nget_raw_data_path(id)\n\nFound 1 obsids.\n\n\nPath('/Users/maye/planetarypy_data/missions/cassini/iss/N1454725799/N1454725799_1.IMG')\n\n\n\niss.dict\n\n{'coiss_raw': ['https://opus.pds-rings.seti.org/holdings/volumes/COISS_2xxx/COISS_2001/data/1454725799_1455008789/N1454725799_1.IMG',\n 'https://opus.pds-rings.seti.org/holdings/volumes/COISS_2xxx/COISS_2001/data/1454725799_1455008789/N1454725799_1.LBL',\n 'https://opus.pds-rings.seti.org/holdings/volumes/COISS_2xxx/COISS_2001/label/prefix2.fmt',\n 'https://opus.pds-rings.seti.org/holdings/volumes/COISS_2xxx/COISS_2001/label/tlmtab.fmt'],\n 'coiss_calib': ['https://opus.pds-rings.seti.org/holdings/calibrated/COISS_2xxx/COISS_2001/data/1454725799_1455008789/N1454725799_1_CALIB.IMG',\n 'https://opus.pds-rings.seti.org/holdings/calibrated/COISS_2xxx/COISS_2001/data/1454725799_1455008789/N1454725799_1_CALIB.LBL'],\n 'coiss_thumb': ['https://opus.pds-rings.seti.org/holdings/volumes/COISS_2xxx/COISS_2001/extras/thumbnail/1454725799_1455008789/N1454725799_1.IMG.jpeg_small'],\n 'coiss_medium': ['https://opus.pds-rings.seti.org/holdings/volumes/COISS_2xxx/COISS_2001/extras/browse/1454725799_1455008789/N1454725799_1.IMG.jpeg'],\n 'coiss_full': ['https://opus.pds-rings.seti.org/holdings/volumes/COISS_2xxx/COISS_2001/extras/full/1454725799_1455008789/N1454725799_1.IMG.png'],\n 'coiss_documentation': ['https://opus.pds-rings.seti.org/holdings/documents/COISS_0xxx/VICAR-File-Format.pdf',\n 'https://opus.pds-rings.seti.org/holdings/documents/COISS_0xxx/ISS-Users-Guide.pdf',\n 'https://opus.pds-rings.seti.org/holdings/documents/COISS_0xxx/ISS-Users-Guide.docx',\n 'https://opus.pds-rings.seti.org/holdings/documents/COISS_0xxx/Data-Product-SIS.txt',\n 'https://opus.pds-rings.seti.org/holdings/documents/COISS_0xxx/Data-Product-SIS.pdf',\n 'https://opus.pds-rings.seti.org/holdings/documents/COISS_0xxx/Cassini-ISS-Final-Report.pdf',\n 'https://opus.pds-rings.seti.org/holdings/documents/COISS_0xxx/Calibration-Theoretical-Basis.pdf',\n 'https://opus.pds-rings.seti.org/holdings/documents/COISS_0xxx/Calibration-Plan.pdf',\n 'https://opus.pds-rings.seti.org/holdings/documents/COISS_0xxx/CISSCAL-Users-Guide.pdf',\n 'https://opus.pds-rings.seti.org/holdings/documents/COISS_0xxx/Archive-SIS.txt',\n 'https://opus.pds-rings.seti.org/holdings/documents/COISS_0xxx/Archive-SIS.pdf'],\n 'rms_index': ['https://opus.pds-rings.seti.org/holdings/metadata/COISS_2xxx/COISS_2001/COISS_2001_index.tab',\n 'https://opus.pds-rings.seti.org/holdings/metadata/COISS_2xxx/COISS_2001/COISS_2001_index.lbl'],\n 'inventory': ['https://opus.pds-rings.seti.org/holdings/metadata/COISS_2xxx/COISS_2001/COISS_2001_inventory.csv',\n 'https://opus.pds-rings.seti.org/holdings/metadata/COISS_2xxx/COISS_2001/COISS_2001_inventory.lbl'],\n 'planet_geometry': ['https://opus.pds-rings.seti.org/holdings/metadata/COISS_2xxx/COISS_2001/COISS_2001_saturn_summary.tab',\n 'https://opus.pds-rings.seti.org/holdings/metadata/COISS_2xxx/COISS_2001/COISS_2001_saturn_summary.lbl'],\n 'moon_geometry': ['https://opus.pds-rings.seti.org/holdings/metadata/COISS_2xxx/COISS_2001/COISS_2001_moon_summary.tab',\n 'https://opus.pds-rings.seti.org/holdings/metadata/COISS_2xxx/COISS_2001/COISS_2001_moon_summary.lbl'],\n 'ring_geometry': ['https://opus.pds-rings.seti.org/holdings/metadata/COISS_2xxx/COISS_2001/COISS_2001_ring_summary.tab',\n 'https://opus.pds-rings.seti.org/holdings/metadata/COISS_2xxx/COISS_2001/COISS_2001_ring_summary.lbl'],\n 'browse_thumb': ['https://opus.pds-rings.seti.org/holdings/previews/COISS_2xxx/COISS_2001/data/1454725799_1455008789/N1454725799_1_thumb.jpg'],\n 'browse_small': ['https://opus.pds-rings.seti.org/holdings/previews/COISS_2xxx/COISS_2001/data/1454725799_1455008789/N1454725799_1_small.jpg'],\n 'browse_medium': ['https://opus.pds-rings.seti.org/holdings/previews/COISS_2xxx/COISS_2001/data/1454725799_1455008789/N1454725799_1_med.jpg'],\n 'browse_full': ['https://opus.pds-rings.seti.org/holdings/previews/COISS_2xxx/COISS_2001/data/1454725799_1455008789/N1454725799_1_full.png']}" + }, + { + "objectID": "api/pds.indexes.html", + "href": "api/pds.indexes.html", + "title": "PDS Indexes", + "section": "", + "text": "source\n\nIndex\n\n Index (key:str, url:str=None, check_update:bool=True)\n\nIndex manager class.\nThis class manages one index, identified by a dotted key, e.g. cassini.iss.ring_summary\n\n\n\n\n\n\n\n\n\n\nType\nDefault\nDetails\n\n\n\n\nkey\nstr\n\nNested (dotted) key, e.g. cassini.iss.ring_summary\n\n\nurl\nstr\nNone\nURL to index. If not given, will be read from config object.\n\n\ncheck_update\nbool\nTrue\nswitch if dynamic URLS will be derived upon start\n\n\n\n\nsource\n\n\nIndex.parse_key\n\n Index.parse_key (key:str)\n\nTake care of different ways how the key could be structured.\nThis involves adding the sub-key indexes for the config file structure, which is something the user of this class should not need to know.\n\n\n\n\nType\nDetails\n\n\n\n\nkey\nstr\ndotted key\n\n\n\n\nsource\n\n\nIndex.download\n\n Index.download ()\n\nWrapping URLs for downloading PDS indices and their label files.\n\nsource\n\n\nIndex.update_available\n\n Index.update_available ()\n\nProperty indicating if the index needs to be downloaded.\n\nkey = \"missions.cassini.iss.indexes.moon_summary\"\nkey = \"missions.lro.lroc.edr\"\n\n\nindex = Index(key, check_update=True)\nindex\n\nKey: missions.lro.lroc.indexes.edr\nURL: http://pds.lroc.asu.edu/data/LRO-L-LROC-2-EDR-V1.0/LROLRC_0048C/INDEX/CUMINDEX.LBL\nTimestamp: 2023-10-10 15:30:56.195462\n\n\n\nindex.key\n\n'missions.lro.lroc.indexes.edr'\n\n\n\nindex.label_filename\n\nPath('CUMINDEX.LBL')\n\n\n\nindex.url\n\n'http://pds.lroc.asu.edu/data/LRO-L-LROC-2-EDR-V1.0/LROLRC_0048C/INDEX/CUMINDEX.LBL'\n\n\n\nindex.local_dir\n\nPath('/home/ayek72/mnt/slowdata/planetarypy/missions/lro/lroc/indexes/edr')\n\n\n\nif index.check_update and index.update_available:\n index.download()\n\nThe key can be provided * with or without the leading ‘missions’ * with or without the internal indexes level of the config file\n\nIndex(\"cassini.iss.moon_summary\")\n\nKey: missions.cassini.iss.indexes.moon_summary\nURL: https://pds-rings.seti.org/holdings/metadata/COISS_2xxx/COISS_2999/COISS_2999_moon_summary.lbl\nTimestamp: 2019-06-08 16:28:22\n\n\n\nIndex(\"cassini.iss.indexes.moon_summary\")\n\nKey: missions.cassini.iss.indexes.moon_summary\nURL: https://pds-rings.seti.org/holdings/metadata/COISS_2xxx/COISS_2999/COISS_2999_moon_summary.lbl\nTimestamp: 2019-06-08 16:28:22\n\n\n\nindex.isotimestamp\n\n'2023-10-10T15:30:56.195462'\n\n\n\nindex.mission_key\n\n'lro'\n\n\n\nindex.local_dir\n\nPath('/home/ayek72/mnt/slowdata/planetarypy/missions/lro/lroc/indexes/edr')\n\n\n\nindex.key_tokens[:2]\n\n['missions', 'lro']\n\n\n\nindex.instrument_key\n\n'lro.lroc'\n\n\n\nconfig.get_value(index.instrument_key)\n\n{'indexes': {'edr': {'url': 'http://pds.lroc.asu.edu/data/LRO-L-LROC-2-EDR-V1.0/LROLRC_0048C/INDEX/CUMINDEX.LBL', 'timestamp': '2023-10-10T15:30:56.195462'}}}\n\n\n\nindex = Index('mro.ctx.edr', check_update=False)\n\n\nindex.url\n\n''\n\n\n\nindex.label_filename\n\nPath('/home/ayek72/mnt/slowdata/planetarypy/missions/mro/ctx/indexes/edr/cumindex.lbl')\n\n\n\nlist(index.local_dir.glob(\"*.[lL][bB][lL]\"))\n\n[Path('/home/ayek72/mnt/slowdata/planetarypy/missions/mro/ctx/indexes/edr/cumindex.lbl')]" + }, + { + "objectID": "api/diviner.html", + "href": "api/diviner.html", + "title": "Diviner", + "section": "", + "text": "source\n\nDataManager\n\n DataManager (tstr)\n\nInitialize self. See help(type(self)) for accurate signature.\n\ndm = DataManager(\"2010010110\")\n\n\ndm.local_path\n\n\nsource\n\n\nread_l1a_data\n\n read_l1a_data (fname, nrows=None)\n\n\nsource\n\n\nL1AHeader\n\n L1AHeader ()\n\nInitialize self. See help(type(self)) for accurate signature.\n\nsource\n\n\nparse_header_line\n\n parse_header_line (line)\n\nParse header lines.\n\n\n\ns = ’ a b c ’ parse_header_line(s) [‘a’, ‘b’, ‘c’] s = ’ a, b , c ’ parse_header_line(s) [‘a’, ‘b’, ‘c’]\n\n\n\n\ndm = DataManager(\"2010010110\")\n\n\ndm.download()\n\n\ndm.volume\n\n\ndm.url\n\n\ndf = pd.read_csv(\n dm.local_path,\n comment=\"#\",\n # names=L1AHeader.columns,\n na_values=\"-9999\",\n skipinitialspace=True,\n)\ndf.head()\n\n\npd.set_option(\"display.max_columns\", 200)\n\n\ndf.index\n\n\ndm.local_path\n\n\nsource\n\n\nget_data_path\n\n get_data_path (tstr)\n\n\nget_data_path(\"2017010110\")" + }, + { + "objectID": "api/cassini_uvis.html", + "href": "api/cassini_uvis.html", + "title": "UVIS", + "section": "", + "text": "get_index(\"cassini.uvis\", \"index\")\n\n\n\n\n\n\n\n\nFILE_NAME\nOBSERVATION_TYPE\nSTART_TIME\nSTOP_TIME\nTARGET_NAME\nDATA_SET_ID\nSPACECRAFT_CLOCK_START_COUNT\nSPACECRAFT_CLOCK_STOP_COUNT\nINTEGRATION_DURATION\nCOMPRESSION_TYPE\n...\nSUB_SOLAR_LONGITUDE\nSUB_SPACECRAFT_LATITUDE\nSUB_SPACECRAFT_LONGITUDE\nPHASE_ANGLE\nEMISSION_ANGLE\nSOLAR_INCIDENCE_ANGLE\nCENTRAL_BODY_DISTANCE\nDWELL_TIME\nH_LEVEL\nD_LEVEL\n\n\n\n\n0\n/COUVIS_0001/DATA/D1999_007/EUV1999_007_17_05.LBL\nUSTARE\n1999-01-07 17:05:01.949\n1999-01-07 17:08:37.949\n<NA>\nCO-J-UVIS-2-SPEC-V1.2\n1/1294420183.000\nUNK\n4.0\nNONE\n...\n-999.0\n-999.0\n-999.0\n-999.0\n-999.0\n-999\n-999.0\n-999\n<NA>\n<NA>\n\n\n1\n/COUVIS_0001/DATA/D1999_007/EUV1999_007_17_08.LBL\nUSTARE\n1999-01-07 17:08:51.947\n1999-01-07 17:12:27.947\n<NA>\nCO-J-UVIS-2-SPEC-V1.2\n1/1294420413.000\nUNK\n4.0\nNONE\n...\n-999.0\n-999.0\n-999.0\n-999.0\n-999.0\n-999\n-999.0\n-999\n<NA>\n<NA>\n\n\n2\n/COUVIS_0001/DATA/D1999_007/FUV1999_007_16_57.LBL\nUSTARE\n1999-01-07 16:57:21.952\n1999-01-07 17:00:57.952\n<NA>\nCO-J-UVIS-2-SPEC-V1.2\n1/1294419723.000\nUNK\n4.0\nNONE\n...\n-999.0\n-999.0\n-999.0\n-999.0\n-999.0\n-999\n-999.0\n-999\n<NA>\n<NA>\n\n\n3\n/COUVIS_0001/DATA/D1999_007/FUV1999_007_17_01.LBL\nUSTARE\n1999-01-07 17:01:11.950\n1999-01-07 17:04:47.950\n<NA>\nCO-J-UVIS-2-SPEC-V1.2\n1/1294419953.000\nUNK\n4.0\nNONE\n...\n-999.0\n-999.0\n-999.0\n-999.0\n-999.0\n-999\n-999.0\n-999\n<NA>\n<NA>\n\n\n4\n/COUVIS_0001/DATA/D1999_007/HDAC1999_007_16_31...\nUHDAC\n1999-01-07 16:31:07.962\n1999-01-07 16:31:11.962\n<NA>\nCO-J-UVIS-2-SSB-V1.2\n1/1294418149.000\nUNK\n-999.0\nNONE\n...\n-999.0\n-999.0\n-999.0\n-999.0\n-999.0\n-999\n-999.0\n1\n(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0)\n(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0)\n\n\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n\n\n203240\n/COUVIS_0060/DATA/D2017_258/FUV2017_258_04_31.LBL\n<NA>\n2017-09-15 04:31:53.005\n2017-09-15 09:04:56.755\nSOLAR WIND\nCO-S-UVIS-2-CUBE-V1.4\n1/1884145299.160\nUNK\n8191.875\nSQRT_9\n...\n-999.0\n-999.0\n-999.0\n-999.0\n-999.0\n-999\n-999.0\n-999\n<NA>\n<NA>\n\n\n203241\n/COUVIS_0060/DATA/D2017_258/FUV2017_258_07_00.LBL\n<NA>\n2017-09-15 07:00:27.697\n2017-09-15 07:13:40.447\nSOLAR WIND\nCO-S-UVIS-2-SPEC-V1.4\n1/1884154214.096\nUNK\n2.625\nSQRT_9\n...\n-999.0\n-999.0\n-999.0\n-999.0\n-999.0\n-999\n-999.0\n-999\n<NA>\n<NA>\n\n\n203242\n/COUVIS_0060/DATA/D2017_258/FUV2017_258_07_15.LBL\n<NA>\n2017-09-15 07:15:04.442\n2017-09-15 10:31:51.692\nSOLAR WIND\nCO-S-UVIS-2-SPEC-V1.4\n1/1884155091.032\nUNK\n2.625\nSQRT_9\n...\n-999.0\n-999.0\n-999.0\n-999.0\n-999.0\n-999\n-999.0\n-999\n<NA>\n<NA>\n\n\n203243\n/COUVIS_0060/DATA/D2017_258/HDAC2017_258_02_14...\n<NA>\n2017-09-15 02:14:02.433\n2017-09-15 02:14:06.433\nSOLAR WIND\nCO-S-UVIS-2-SSB-V1.4\n1/1884137029.000\nUNK\n-999.0\nNONE\n...\n-999.0\n-999.0\n-999.0\n-999.0\n-999.0\n-999\n-999.0\n1\n(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0)\n(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0)\n\n\n203244\n/COUVIS_0060/DATA/D2017_258/HDAC2017_258_02_15...\n<NA>\n2017-09-15 02:15:25.058\n2017-09-15 02:17:33.058\nSOLAR WIND\nCO-S-UVIS-2-SSB-V1.4\n1/1884137111.160\nUNK\n-999.0\nNONE\n...\n-999.0\n-999.0\n-999.0\n-999.0\n-999.0\n-999\n-999.0\n32\n(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0)\n(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0)\n\n\n\n\n203245 rows × 28 columns\n\n\n\n\nsource\n\nDataManager\n\n DataManager (pid:str, skip_download:bool=False)\n\nInitialize self. See help(type(self)) for accurate signature.\n\n\n\n\n\n\n\n\n\n\nType\nDefault\nDetails\n\n\n\n\npid\nstr\n\nProduct ID. If longer than PDS_ID, will be cut in attribute pds_id\n\n\nskip_download\nbool\nFalse\nskip trying to download\n\n\n\n\npid = \"EUV2002_198_03_26_54_UVIS_C33ST_SPICARAST002_PRIME\"\n\n\ndm = DataManager(pid)\n\n\ndm.raw_label_url\n\nURL('https://opus.pds-rings.seti.org/holdings/volumes/COUVIS_0xxx/COUVIS_0004/DATA/D2002_198/EUV2002_198_03_26.LBL')\n\n\n\nassert dm.pid == pid\n\nPDS data is only stored under the first 17 characters of any UVIS-internal product id.\n\nassert dm.pds_id == pid[:17]\n\nThe originally used product ID pid will be stored under original_pid.txt in the data folder:\n\ndm.original_pid_file\n\nPath('/home/ayek72/mnt/slowdata/planetarypy/missions/cassini/uvis/EUV2002_198_03_26/original_pid.txt')\n\n\nThe OPUS result file will be stored as a TOML file:\n\ndm.results_file\n\nPath('/home/ayek72/mnt/slowdata/planetarypy/missions/cassini/uvis/EUV2002_198_03_26/urls.toml')\n\n\n\ndm.download(overwrite=False)\n\nLocal files exists. Use `overwrite=True` to download fresh.\n\n\n\ndm.raw_data_path\n\nPath('/home/ayek72/mnt/slowdata/planetarypy/missions/cassini/uvis/EUV2002_198_03_26/EUV2002_198_03_26.DAT')\n\n\n\ndm.calib_corr_path\n\nPath('/home/ayek72/mnt/slowdata/planetarypy/missions/cassini/uvis/EUV2002_198_03_26/EUV2002_198_03_26_CAL_3.DAT')\n\n\n\nsource\n\n\nget_label_path\n\n get_label_path (pid)\n\n\nsource\n\n\nget_data_path\n\n get_data_path (pid, skip_download=False)\n\n\nget_data_path(pid)\n\nPath('/home/ayek72/mnt/slowdata/planetarypy/missions/cassini/uvis/EUV2002_198_03_26/EUV2002_198_03_26.DAT')\n\n\n\nget_label_path(pid)\n\nPath('/home/ayek72/mnt/slowdata/planetarypy/missions/cassini/uvis/EUV2002_198_03_26/EUV2002_198_03_26.LBL')\n\n\n\nsource\n\n\nget_user_guide\n\n get_user_guide ()\n\n\nget_user_guide()\n\nPath('/home/ayek72/mnt/slowdata/planetarypy/missions/cassini/uvis/uvis_user_guide.pdf')" + }, + { + "objectID": "api/pds.opusapi.html", + "href": "api/pds.opusapi.html", + "title": "OPUSAPI class", + "section": "", + "text": "source\n\nOPUS\n\n OPUS (silent=False)\n\nManage OPUS API requests.\n\nsource\n\n\nOPUSObsID\n\n OPUSObsID (obsid_data)\n\nManage observation IDs from OPUS responses.\n\nsource\n\n\nOPUSImageURL\n\n OPUSImageURL (jsonlist)\n\nManage URLS from the OPUS response.\n\nopus = OPUS()\n\n\nopus.query_image_id(\"FUV2003_363_00_22\")" + }, + { + "objectID": "api/pds.ctx_index.html", + "href": "api/pds.ctx_index.html", + "title": "CTX Index", + "section": "", + "text": "source\n\nCTXIndex\n\n CTXIndex ()\n\nInitialize self. See help(type(self)) for accurate signature.\n\nctx = CTXIndex()\n\n\nctx.volumes_table\n\n\n\n\n\n\n\n\nName\nLast modified\n\n\n\n\n2\nmrox_0001/\n05-Jun-2007 10:15\n\n\n3\nmrox_0001_md5.txt\n10-Dec-2019 04:32\n\n\n4\nmrox_0002/\n05-Jun-2007 10:15\n\n\n5\nmrox_0002_md5.txt\n09-Dec-2019 19:14\n\n\n6\nmrox_0003/\n05-Jun-2007 10:15\n\n\n...\n...\n...\n\n\n9515\nmrox_4757_md5.txt\n15-Nov-2023 23:23\n\n\n9516\nmrox_4758/\n15-Nov-2023 23:08\n\n\n9517\nmrox_4758_md5.txt\n15-Nov-2023 23:23\n\n\n9518\nmrox_4759/\n15-Nov-2023 23:10\n\n\n9519\nmrox_4759_md5.txt\n15-Nov-2023 23:23\n\n\n\n\n9518 rows × 2 columns\n\n\n\n\nctx.latest_release_folder\n\n'mrox_4759/'\n\n\n\nctx.latest_release_number\n\n'4759'\n\n\n\nctx.latest_index_label_url\n\nURL('https://planetarydata.jpl.nasa.gov/img/data/mro/mars_reconnaissance_orbiter/ctx/mrox_4759/index/cumindex.lbl')" + }, + { + "objectID": "api/config.html", + "href": "api/config.html", + "title": "Config", + "section": "", + "text": "source" + }, + { + "objectID": "api/config.html#the-config-object", + "href": "api/config.html#the-config-object", + "title": "Config", + "section": "The Config() object", + "text": "The Config() object\nThe config module instantiates a config object from the Config class. Its attributes can be used to access several aspects relevant to the configuration of planetarypy. Using an object approach enables easy growth and nesting over time.\n\nconfig = Config(config_path=\"test_config.toml\")\n\n\nassert config.storage_root == Path.home() / \"planetarypy_data\"\n\n\nsource\n\nConfig.get_value\n\n Config.get_value (key:str)\n\nGet sub-dictionary by nested key.\n\n\n\n\n\n\n\n\n\nType\nDetails\n\n\n\n\nkey\nstr\nA nested key in dotted format, e.g. cassini.uvis.indexes\n\n\nReturns\nstr\nReturning empty string if not existing, because Path(’’) is False which is handy (e.g. in ctx mod.)\n\n\n\n\nconfig.list_indexes(\"mro.hirise\")\n\n['dtm', 'edr', 'rdr']\n\n\n\nindex = \"missions.cassini.iss.indexes.moon_summary\"\n\n\nconfig.get_value(index)['url']\n\n'https://pds-rings.seti.org/holdings/metadata/COISS_2xxx/COISS_2999/COISS_2999_moon_summary.lbl'\n\n\n\nsource\n\n\nConfig.set_value\n\n Config.set_value (nested_key:str, value:Union[float,str], save:bool=True)\n\nSet value in sub-dic using dotted key.\n\n\n\n\n\n\n\n\n\n\nType\nDefault\nDetails\n\n\n\n\nnested_key\nstr\n\nA nested key in dotted format, e.g. cassini.uvis.ring_summary\n\n\nvalue\nUnion\n\nValue for the given key to be stored\n\n\nsave\nbool\nTrue\nSwitch to control writing out to disk\n\n\n\n\nsource\n\n\nConfig.save\n\n Config.save ()\n\nWrite the TOML doc to file.\n\nconfig.get_value(index)['url']\n\n'https://pds-rings.seti.org/holdings/metadata/COISS_2xxx/COISS_2999/COISS_2999_moon_summary.lbl'\n\n\n\nconfig.get_value(\"mro.ctx.datalevels\")['edr']['url']\n\n'https://pds-imaging.jpl.nasa.gov/data/mro/mars_reconnaissance_orbiter/ctx'\n\n\n\nsource\n\n\nConfig.ask_storage_root\n\n Config.ask_storage_root ()\n\nUse input() to ask user for the storage_root path.\nThe path will be stored in the TOML-dict and saved into existing config file at Class.path, either default or as given during init. storage_root attribute is set as well.\n\nconfig.missions\n\n['cassini', 'mro', 'lro', 'go']\n\n\n\nassert config.path.name == '.planetarypy_config.toml'\n\n\nconfig.list_instruments(\"cassini\")\n\n['iss', 'uvis']\n\n\n\nconfig.list_indexes(\"cassini.iss\")\n\n['index', 'inventory', 'moon_summary', 'ring_summary', 'saturn_summary']\n\n\n\nsource\n\n\nConfig.get_datalevels\n\n Config.get_datalevels (mission_instrument)\n\nReturn configured data levels available for an instrument.\nThis currently simply points to the indexes, assuming that everything that has an index is also its own datalevel. In case it ever is not, we can add more here.\n\n\n\n\nDetails\n\n\n\n\nmission_instrument\nmission.instrument code, e.g. mro.hirise\n\n\n\n\nconfig.get_datalevels(\"mro.hirise\")\n\n['dtm', 'edr', 'rdr']\n\n\n\nfrom nbdev import nbdev_export\n\nnbdev_export()" + }, + { + "objectID": "api/pds.lroc_index.html", + "href": "api/pds.lroc_index.html", + "title": "LROC Index", + "section": "", + "text": "EDR vs RDR etc.\nI cannot distinguish between different data levels for dynamic index URLs yet, as is required for LROC, so for now I only implement the EDR index, pretending it’s the only one!\n\nsource\n\nLROCIndex\n\n LROCIndex ()\n\nInitialize self. See help(type(self)) for accurate signature.\n\nlroc = LROCIndex()\n\n\nlroc.latest_release_folder\n\n'LROLRC_0056A/'\n\n\n\nlroc.latest_release_number\n\n'0056A'\n\n\n\nlroc.latest_index_label_url\n\nURL('https://pds.lroc.asu.edu/data/LRO-L-LROC-2-EDR-V1.0/LROLRC_0056A/INDEX/CUMINDEX.LBL')" + }, + { + "objectID": "api/geotools.html", + "href": "api/geotools.html", + "title": "Geotools", + "section": "", + "text": "ul = Upper Left\nlr = LowerRight\n\n\nsource\n\n\n\n pixel_to_meter (sample, line, geotransform, shift=False)\n\nprovide point in map projection coordinates.\n\n\n\n\n\n\n\n\n\n\nType\nDefault\nDetails\n\n\n\n\nsample\n\n\n\n\n\nline\n\n\n\n\n\ngeotransform\n\n\n\n\n\nshift\nbool\nFalse\n\n\n\nReturns\ntuple (x,y) coordinates in the projection of the dataset\n\n\n\n\n\n\nsource\n\n\n\n\n shift_to_center (x, y, geotransform)\n\n\nsource\n\n\n\n\n debug_srs (projection)\n\nCorrect wrong scale_factor in PolarStereographic data.\nSome PolarStereographic data have a 0 as a scale_factor in the projection (mostly MOLA), which is being corrected here. TODO: Check for being PolarStereographic before doing this!\n\nsource\n\n\n\n\n get_sun_angles (spicer, img)\n\nCalculate solar azimuth and incidence.\nBy requiring a spicer object for this function, it becomes independent from the solar system object where the calculations are made.\n\n\n\n\n\n\n\n\n\nType\nDetails\n\n\n\n\nspicer\nspicer.Spicer\nneeds to be setup for time, but spoint is set from img.center in here.\n\n\nimg\ngeotools.ImgData\nThe image data of which the center point serves as the start point.\n\n\nReturns\ntuple(float, float)\nSolar azimuth, incidence [degrees]\n\n\n\n\nsource\n\n\n\n\n calculate_image_north_azimuth (img, zero='right')\n\n\nsource\n\n\n\n\n get_north_shifted_point (img, offset=0.001)\n\nIncreasing the latitude is a sure way of getting north.\n\nsource\n\n\n\n\n calculate_image_azimuth (origPoint, newPoint, zero='right')\n\nCalculate azimuth angle between 2 image points.\nBeware that this function calculates trigonometric angles. If the points are from an image that has (0, 0) in the upper left, this means that the angles increase clockwise. That is why, for example, for an HiRISE image, the return of this function matches the angle rotation definition for HiRISE data.\n\n\n\n\nType\nDefault\nDetails\n\n\n\n\norigPoint\n\n\n\n\n\nnewPoint\n\n\n\n\n\nzero\nstr\nright\n\n\n\nReturns\nazimuth: \n\nAzimuth angle\n\n\n\n/home/runner/micromamba/envs/my-env/lib/python3.11/site-packages/fastcore/docscrape.py:225: UserWarning: Unknown section Requires\n else: warn(msg)\n\nsource\n\n\n\n\n Point (sample=None, line=None, x=None, y=None, lon=None, lat=None,\n geotrans=None, proj=None)\n\nPoint class to manage pixel and map points and their transformations.\n\nsource\n\n\n\n\n Window (ulPoint=None, lrPoint=None, centerPoint=None, width=None)\n\nclass to manage a window made of corner Points (objects of Point())\nwhen using width, only quadratic windows supported currently >>> p1 = Point(0, 1) >>> p2 = Point(10,20)\n\nsource\n\n\n\n\n ImgData (fname=None)\n\ndocstring for ImgData\n\n# todo: Fix missing MOLA class\n#| export\n# class CTX(ImgData):\n# \"\"\"docstring for CTX\"\"\"\n\n# def __init__(self, fname):\n# ImgData.__init__(self, fname)\n\n# def add_mola_contours(self):\n# self.window_coords_to_lonlat()\n# mola = MOLA()\n# mola.window = self.window.copy()\n# mola.window_coords_to_pixel()\n# mola.read_window(mola.window)\n# mola.data = mola.data - mola.data.mean()\n# fig = plt.figure(figsize=(10, 10))\n# ax = fig.add_subplot(111)\n# plt.gray()\n# ax.imshow(self.data, extent=self.window.get_extent(self.dataset))\n# CS = ax.contour(\n# mola.data,\n# 8,\n# cmap=cm.jet,\n# extent=self.window.get_extent(self.dataset),\n# origin=\"image\",\n# )\n# plt.clabel(CS, fontsize=13, inline=1)\n# ax.set_xlabel(\"Polar stereographic X [km]\")\n# ax.set_ylabel(\"Polar stereographic Y [km]\")\n# ax.set_title(\"CTX: \" + os.path.basename(self.fname))\n# self.ax = ax\n# plt.show()\n\n\n# def combine_ctx_and_mola(ctxFilename, ctxSample, ctxLine, ctxWidth):\n# \"\"\"combine CTX and MOLA data.\n#\n# MOLA and CTX data will be combined with these tools.\n# User shall provide line,sample center coordinate of CTX file ROI to\n# define distance in meters from southpole.\n# \"\"\"\n#\n# ctx = CTX(ctxFilename)\n# mola = MOLA()\n# ctxULsample, ctxULline, ctxLRsample, ctxLRline = \\\n# get_corners_from_center(ctxSample, ctxLine, ctxWidth)\n# ulX,ulY = get_coords_from_pixels(ctxDS, ctxULsample, ctxULline)\n# lrX,lrY = get_coords_from_pixels(ctxDS, ctxLRsample, ctxLRline)\n#\n# molaULsample,molaULline = get_pixels_from_coords(molaDS,ulX,ulY)\n# molaLRsample,molaLRline = get_pixels_from_coords(molaDS,lrX,lrY)\n# print(ctxULsample, ctxULline, ctxLRsample, ctxLRline)\n# print(molaULsample, molaULline,molaLRsample, molaLRline)\n# print(ulX,ulY,lrX,lrY)\n# ctxData = ctxDS.ReadAsArray(ctxULsample,ctxULline,ctxWidth,ctxWidth)\n# molaData = molaDS.ReadAsArray(int(molaULsample)+1,int(molaULline),\n# int(molaLRsample - molaULsample),\n# int(molaLRline - molaULline))\n#\n# molaData = molaData - molaData.mean()\n#\n# # x = np.arange(ulX,lrX)\n# # y = np.arange(lrY,ulY)\n# # X, Y = np.meshgrid(x,y)\n# # plotting\n# fig = plt.figure(figsize=(10,10))\n# ax = fig.add_subplot(111)\n# plt.gray()\n# ax.imshow(ctxData, extent=(min(ulX,lrX),max(ulX,lrX),min(ulY,lrY),\n# max(ulY,lrY)))\n# CS = ax.contour(molaData, 20, cmap = cm.jet,\n# extent=(min(ulX,lrX),\n# max(ulX,lrX),\n# min(ulY,lrY),\n# max(ulY,lrY)),\n# origin='image' )\n# plt.clabel(CS,fontsize=9, inline=1)\n# plt.show()\n\n# def main(argv=None):\n# \"\"\"docstring for main\"\"\"\n# from mayavi import mlab\n\n# if argv is None:\n# argv = sys.argv\n\n# x1 = x2 = y1 = y2 = 0\n# fname = \"\"\n# try:\n# fname = argv[1]\n# x1, x2, y1, y2 = [int(i) for i in argv[2:]]\n# except:\n# print(\"Usage: {0} fname x1 x2 y1 y2\".format(argv[0]))\n\n# print(x1, x2, y1, y2)\n# ds = gdal.Open(fname)\n# band = ds.GetRasterBand(1)\n# STORED_VALUE = band.ReadAsArray(x1, y1, x2 - x1, y2 - y1)\n# ds = 0\n\n# # PDS label infos:\n# SCALING_FACTOR = 0.25\n# OFFSET = -8000\n# topo = (STORED_VALUE * SCALING_FACTOR) + OFFSET\n# mlab.surf(topo, warp_scale=1 / 115.0, vmin=1700)\n# mlab.colorbar(orientation=\"vertical\", title=\"Height [m]\", label_fmt=\"%4.0f\")\n# mlab.show()" + }, + { + "objectID": "api/geotools.html#abbreviations", + "href": "api/geotools.html#abbreviations", + "title": "Geotools", + "section": "", + "text": "ul = Upper Left\nlr = LowerRight\n\n\nsource\n\n\n\n pixel_to_meter (sample, line, geotransform, shift=False)\n\nprovide point in map projection coordinates.\n\n\n\n\n\n\n\n\n\n\nType\nDefault\nDetails\n\n\n\n\nsample\n\n\n\n\n\nline\n\n\n\n\n\ngeotransform\n\n\n\n\n\nshift\nbool\nFalse\n\n\n\nReturns\ntuple (x,y) coordinates in the projection of the dataset\n\n\n\n\n\n\nsource\n\n\n\n\n shift_to_center (x, y, geotransform)\n\n\nsource\n\n\n\n\n debug_srs (projection)\n\nCorrect wrong scale_factor in PolarStereographic data.\nSome PolarStereographic data have a 0 as a scale_factor in the projection (mostly MOLA), which is being corrected here. TODO: Check for being PolarStereographic before doing this!\n\nsource\n\n\n\n\n get_sun_angles (spicer, img)\n\nCalculate solar azimuth and incidence.\nBy requiring a spicer object for this function, it becomes independent from the solar system object where the calculations are made.\n\n\n\n\n\n\n\n\n\nType\nDetails\n\n\n\n\nspicer\nspicer.Spicer\nneeds to be setup for time, but spoint is set from img.center in here.\n\n\nimg\ngeotools.ImgData\nThe image data of which the center point serves as the start point.\n\n\nReturns\ntuple(float, float)\nSolar azimuth, incidence [degrees]\n\n\n\n\nsource\n\n\n\n\n calculate_image_north_azimuth (img, zero='right')\n\n\nsource\n\n\n\n\n get_north_shifted_point (img, offset=0.001)\n\nIncreasing the latitude is a sure way of getting north.\n\nsource\n\n\n\n\n calculate_image_azimuth (origPoint, newPoint, zero='right')\n\nCalculate azimuth angle between 2 image points.\nBeware that this function calculates trigonometric angles. If the points are from an image that has (0, 0) in the upper left, this means that the angles increase clockwise. That is why, for example, for an HiRISE image, the return of this function matches the angle rotation definition for HiRISE data.\n\n\n\n\nType\nDefault\nDetails\n\n\n\n\norigPoint\n\n\n\n\n\nnewPoint\n\n\n\n\n\nzero\nstr\nright\n\n\n\nReturns\nazimuth: \n\nAzimuth angle\n\n\n\n/home/runner/micromamba/envs/my-env/lib/python3.11/site-packages/fastcore/docscrape.py:225: UserWarning: Unknown section Requires\n else: warn(msg)\n\nsource\n\n\n\n\n Point (sample=None, line=None, x=None, y=None, lon=None, lat=None,\n geotrans=None, proj=None)\n\nPoint class to manage pixel and map points and their transformations.\n\nsource\n\n\n\n\n Window (ulPoint=None, lrPoint=None, centerPoint=None, width=None)\n\nclass to manage a window made of corner Points (objects of Point())\nwhen using width, only quadratic windows supported currently >>> p1 = Point(0, 1) >>> p2 = Point(10,20)\n\nsource\n\n\n\n\n ImgData (fname=None)\n\ndocstring for ImgData\n\n# todo: Fix missing MOLA class\n#| export\n# class CTX(ImgData):\n# \"\"\"docstring for CTX\"\"\"\n\n# def __init__(self, fname):\n# ImgData.__init__(self, fname)\n\n# def add_mola_contours(self):\n# self.window_coords_to_lonlat()\n# mola = MOLA()\n# mola.window = self.window.copy()\n# mola.window_coords_to_pixel()\n# mola.read_window(mola.window)\n# mola.data = mola.data - mola.data.mean()\n# fig = plt.figure(figsize=(10, 10))\n# ax = fig.add_subplot(111)\n# plt.gray()\n# ax.imshow(self.data, extent=self.window.get_extent(self.dataset))\n# CS = ax.contour(\n# mola.data,\n# 8,\n# cmap=cm.jet,\n# extent=self.window.get_extent(self.dataset),\n# origin=\"image\",\n# )\n# plt.clabel(CS, fontsize=13, inline=1)\n# ax.set_xlabel(\"Polar stereographic X [km]\")\n# ax.set_ylabel(\"Polar stereographic Y [km]\")\n# ax.set_title(\"CTX: \" + os.path.basename(self.fname))\n# self.ax = ax\n# plt.show()\n\n\n# def combine_ctx_and_mola(ctxFilename, ctxSample, ctxLine, ctxWidth):\n# \"\"\"combine CTX and MOLA data.\n#\n# MOLA and CTX data will be combined with these tools.\n# User shall provide line,sample center coordinate of CTX file ROI to\n# define distance in meters from southpole.\n# \"\"\"\n#\n# ctx = CTX(ctxFilename)\n# mola = MOLA()\n# ctxULsample, ctxULline, ctxLRsample, ctxLRline = \\\n# get_corners_from_center(ctxSample, ctxLine, ctxWidth)\n# ulX,ulY = get_coords_from_pixels(ctxDS, ctxULsample, ctxULline)\n# lrX,lrY = get_coords_from_pixels(ctxDS, ctxLRsample, ctxLRline)\n#\n# molaULsample,molaULline = get_pixels_from_coords(molaDS,ulX,ulY)\n# molaLRsample,molaLRline = get_pixels_from_coords(molaDS,lrX,lrY)\n# print(ctxULsample, ctxULline, ctxLRsample, ctxLRline)\n# print(molaULsample, molaULline,molaLRsample, molaLRline)\n# print(ulX,ulY,lrX,lrY)\n# ctxData = ctxDS.ReadAsArray(ctxULsample,ctxULline,ctxWidth,ctxWidth)\n# molaData = molaDS.ReadAsArray(int(molaULsample)+1,int(molaULline),\n# int(molaLRsample - molaULsample),\n# int(molaLRline - molaULline))\n#\n# molaData = molaData - molaData.mean()\n#\n# # x = np.arange(ulX,lrX)\n# # y = np.arange(lrY,ulY)\n# # X, Y = np.meshgrid(x,y)\n# # plotting\n# fig = plt.figure(figsize=(10,10))\n# ax = fig.add_subplot(111)\n# plt.gray()\n# ax.imshow(ctxData, extent=(min(ulX,lrX),max(ulX,lrX),min(ulY,lrY),\n# max(ulY,lrY)))\n# CS = ax.contour(molaData, 20, cmap = cm.jet,\n# extent=(min(ulX,lrX),\n# max(ulX,lrX),\n# min(ulY,lrY),\n# max(ulY,lrY)),\n# origin='image' )\n# plt.clabel(CS,fontsize=9, inline=1)\n# plt.show()\n\n# def main(argv=None):\n# \"\"\"docstring for main\"\"\"\n# from mayavi import mlab\n\n# if argv is None:\n# argv = sys.argv\n\n# x1 = x2 = y1 = y2 = 0\n# fname = \"\"\n# try:\n# fname = argv[1]\n# x1, x2, y1, y2 = [int(i) for i in argv[2:]]\n# except:\n# print(\"Usage: {0} fname x1 x2 y1 y2\".format(argv[0]))\n\n# print(x1, x2, y1, y2)\n# ds = gdal.Open(fname)\n# band = ds.GetRasterBand(1)\n# STORED_VALUE = band.ReadAsArray(x1, y1, x2 - x1, y2 - y1)\n# ds = 0\n\n# # PDS label infos:\n# SCALING_FACTOR = 0.25\n# OFFSET = -8000\n# topo = (STORED_VALUE * SCALING_FACTOR) + OFFSET\n# mlab.surf(topo, warp_scale=1 / 115.0, vmin=1700)\n# mlab.colorbar(orientation=\"vertical\", title=\"Height [m]\", label_fmt=\"%4.0f\")\n# mlab.show()" + }, + { + "objectID": "api/utils.html", + "href": "api/utils.html", + "title": "Utils", + "section": "", + "text": "First, we define the different format strings these utils convert from and to.\nAn identifier with xxx_dt_format_xxx in its name signifies a full datetime format as compared to dates only.\n\n\nWhat we call NASA data, is the often used YYYY-JJJ based format in the Planetary Data System identifying dates via the running number of the day in the year, e.g. “2010-240”.\n\nsource\n\n\n\n\n nasa_time_to_datetime (inputstr)\n\nUser function to convert all kinds of NASA PDS datestrings with day_of_year into datetimes.\n\n\n\n\n\n\n\n\n\nType\nDetails\n\n\n\n\ninputstr\n\ninputstr of format YYYY-jjj, YYYY-jjjTHH:MM:SS or YYYY-jjjTHH:MM:SS.ffffff\n\n\nReturns\ndatetime\n\n\n\n\nExample dates and times to test:\n\nnasa_date = \"2010-110\"\niso_date = \"2010-4-20\"\nnasa_datetime = \"2010-110T10:12:14\"\nnasa_datetime_with_ms = nasa_datetime + \".123000\"\niso_datetime = \"2010-04-20T10:12:14\"\niso_datetime_with_ms = iso_datetime + \".123000\"\nnasa_times = [nasa_date, nasa_datetime, nasa_datetime_with_ms]\niso_times = [iso_date, iso_datetime, iso_datetime_with_ms]\n\n\nassert nasa_time_to_datetime(nasa_date) == dt.datetime(2010, 4, 20, 0, 0)\n\n\nassert nasa_time_to_datetime(nasa_datetime) == dt.datetime(2010, 4, 20, 10, 12, 14)\n\n\nassert nasa_time_to_datetime(nasa_datetime_with_ms) == dt.datetime(2010, 4, 20, 10, 12, 14, 123000)\n\n\nsource\n\n\n\n\n nasa_time_to_iso (inputstr:str, with_hours:bool=False)\n\nConvert the day-number based NASA datetime format to ISO\n\n\n\n\n\n\n\n\n\n\nType\nDefault\nDetails\n\n\n\n\ninputstr\nstr\n\n\n\n\nwith_hours\nbool\nFalse\nSwitch if return is wanted with hours (i.e. isoformat)\n\n\nReturns\nstr\n\nDatestring in ISO-format.\n\n\n\nConversions to ISO format, but not providing hours if they are not in input:\n\nfor t in nasa_times:\n print(\"Input:\", t)\n print(nasa_time_to_iso(t))\n\nInput: 2010-110\n2010-04-20\nInput: 2010-110T10:12:14\n2010-04-20T10:12:14\nInput: 2010-110T10:12:14.123000\n2010-04-20T10:12:14.123000\n\n\nIf hours are wanted in the isostring, use with_hours=True:\n\nfor t in nasa_times:\n print(\"Input:\", t)\n print(nasa_time_to_iso(t, with_hours=True))\n\nInput: 2010-110\n2010-04-20T00:00:00\nInput: 2010-110T10:12:14\n2010-04-20T10:12:14\nInput: 2010-110T10:12:14.123000\n2010-04-20T10:12:14.123000\n\n\n\nassert nasa_time_to_iso(nasa_date, with_hours=True) == \"2010-04-20T00:00:00\"\nassert nasa_time_to_iso(nasa_date) == \"2010-04-20\"\n\n\n\n\nAgain, with NASA-format, we mean the ofen used (in PDS and mission files) YYYY-JJJ format, e.g. “2010-240”.\n\nsource\n\n\n\n\n iso_to_nasa_time (inputstr:str)\n\nConvert iso date to day-number based NASA date.\n\n\n\n\nType\nDetails\n\n\n\n\ninputstr\nstr\nDate string of the form Y-m-d\n\n\nReturns\nstr\nDatestring in NASA standard yyyy-jjj\n\n\n\n\nsource\n\n\n\n\n iso_to_nasa_datetime (dtimestr:str)\n\nConvert iso datetime to day-number based NASA datetime.\n\n\n\n\nType\nDetails\n\n\n\n\ndtimestr\nstr\nDatetime string of the form yyyy-mm-ddTHH-MM-SS\n\n\n\n\nfor t in iso_times:\n print(\"Input:\", t)\n print(iso_to_nasa_time(t))\n\nInput: 2010-4-20\n2010-110\nInput: 2010-04-20T10:12:14\n2010-110T10:12:14\nInput: 2010-04-20T10:12:14.123000\n2010-110T10:12:14.123000\n\n\n\nassert iso_to_nasa_time(iso_date) == nasa_date\n\n\nassert nasa_time_to_iso(nasa_datetime) == iso_datetime\nassert nasa_time_to_iso(nasa_datetime_with_ms) == iso_datetime_with_ms\n\n\nassert iso_to_nasa_time(iso_datetime) == nasa_datetime\nassert iso_to_nasa_time(iso_datetime_with_ms) == nasa_datetime_with_ms\n\n\nsource\n\n\n\n\n replace_all_nasa_times (df:pandas.core.frame.DataFrame)\n\nFind all NASA times in dataframe and replace with ISO.\nChanges will be implemented on incoming dataframe!\nThis will be done for all columns with the word TIME in the column name.\n\n\n\n\nType\nDetails\n\n\n\n\ndf\nDataFrame\nDataFrame with NASA time columns" + }, + { + "objectID": "api/utils.html#time-format-strings", + "href": "api/utils.html#time-format-strings", + "title": "Utils", + "section": "", + "text": "First, we define the different format strings these utils convert from and to.\nAn identifier with xxx_dt_format_xxx in its name signifies a full datetime format as compared to dates only.\n\n\nWhat we call NASA data, is the often used YYYY-JJJ based format in the Planetary Data System identifying dates via the running number of the day in the year, e.g. “2010-240”.\n\nsource\n\n\n\n\n nasa_time_to_datetime (inputstr)\n\nUser function to convert all kinds of NASA PDS datestrings with day_of_year into datetimes.\n\n\n\n\n\n\n\n\n\nType\nDetails\n\n\n\n\ninputstr\n\ninputstr of format YYYY-jjj, YYYY-jjjTHH:MM:SS or YYYY-jjjTHH:MM:SS.ffffff\n\n\nReturns\ndatetime\n\n\n\n\nExample dates and times to test:\n\nnasa_date = \"2010-110\"\niso_date = \"2010-4-20\"\nnasa_datetime = \"2010-110T10:12:14\"\nnasa_datetime_with_ms = nasa_datetime + \".123000\"\niso_datetime = \"2010-04-20T10:12:14\"\niso_datetime_with_ms = iso_datetime + \".123000\"\nnasa_times = [nasa_date, nasa_datetime, nasa_datetime_with_ms]\niso_times = [iso_date, iso_datetime, iso_datetime_with_ms]\n\n\nassert nasa_time_to_datetime(nasa_date) == dt.datetime(2010, 4, 20, 0, 0)\n\n\nassert nasa_time_to_datetime(nasa_datetime) == dt.datetime(2010, 4, 20, 10, 12, 14)\n\n\nassert nasa_time_to_datetime(nasa_datetime_with_ms) == dt.datetime(2010, 4, 20, 10, 12, 14, 123000)\n\n\nsource\n\n\n\n\n nasa_time_to_iso (inputstr:str, with_hours:bool=False)\n\nConvert the day-number based NASA datetime format to ISO\n\n\n\n\n\n\n\n\n\n\nType\nDefault\nDetails\n\n\n\n\ninputstr\nstr\n\n\n\n\nwith_hours\nbool\nFalse\nSwitch if return is wanted with hours (i.e. isoformat)\n\n\nReturns\nstr\n\nDatestring in ISO-format.\n\n\n\nConversions to ISO format, but not providing hours if they are not in input:\n\nfor t in nasa_times:\n print(\"Input:\", t)\n print(nasa_time_to_iso(t))\n\nInput: 2010-110\n2010-04-20\nInput: 2010-110T10:12:14\n2010-04-20T10:12:14\nInput: 2010-110T10:12:14.123000\n2010-04-20T10:12:14.123000\n\n\nIf hours are wanted in the isostring, use with_hours=True:\n\nfor t in nasa_times:\n print(\"Input:\", t)\n print(nasa_time_to_iso(t, with_hours=True))\n\nInput: 2010-110\n2010-04-20T00:00:00\nInput: 2010-110T10:12:14\n2010-04-20T10:12:14\nInput: 2010-110T10:12:14.123000\n2010-04-20T10:12:14.123000\n\n\n\nassert nasa_time_to_iso(nasa_date, with_hours=True) == \"2010-04-20T00:00:00\"\nassert nasa_time_to_iso(nasa_date) == \"2010-04-20\"\n\n\n\n\nAgain, with NASA-format, we mean the ofen used (in PDS and mission files) YYYY-JJJ format, e.g. “2010-240”.\n\nsource\n\n\n\n\n iso_to_nasa_time (inputstr:str)\n\nConvert iso date to day-number based NASA date.\n\n\n\n\nType\nDetails\n\n\n\n\ninputstr\nstr\nDate string of the form Y-m-d\n\n\nReturns\nstr\nDatestring in NASA standard yyyy-jjj\n\n\n\n\nsource\n\n\n\n\n iso_to_nasa_datetime (dtimestr:str)\n\nConvert iso datetime to day-number based NASA datetime.\n\n\n\n\nType\nDetails\n\n\n\n\ndtimestr\nstr\nDatetime string of the form yyyy-mm-ddTHH-MM-SS\n\n\n\n\nfor t in iso_times:\n print(\"Input:\", t)\n print(iso_to_nasa_time(t))\n\nInput: 2010-4-20\n2010-110\nInput: 2010-04-20T10:12:14\n2010-110T10:12:14\nInput: 2010-04-20T10:12:14.123000\n2010-110T10:12:14.123000\n\n\n\nassert iso_to_nasa_time(iso_date) == nasa_date\n\n\nassert nasa_time_to_iso(nasa_datetime) == iso_datetime\nassert nasa_time_to_iso(nasa_datetime_with_ms) == iso_datetime_with_ms\n\n\nassert iso_to_nasa_time(iso_datetime) == nasa_datetime\nassert iso_to_nasa_time(iso_datetime_with_ms) == nasa_datetime_with_ms\n\n\nsource\n\n\n\n\n replace_all_nasa_times (df:pandas.core.frame.DataFrame)\n\nFind all NASA times in dataframe and replace with ISO.\nChanges will be implemented on incoming dataframe!\nThis will be done for all columns with the word TIME in the column name.\n\n\n\n\nType\nDetails\n\n\n\n\ndf\nDataFrame\nDataFrame with NASA time columns" + }, + { + "objectID": "api/utils.html#network-utils", + "href": "api/utils.html#network-utils", + "title": "Utils", + "section": "Network utils", + "text": "Network utils\n\nsource\n\nhave_internet\n\n have_internet ()\n\nFastest way to check for active internet connection.\nFrom https://stackoverflow.com/a/29854274/680232\n\nsource\n\n\nurl_retrieve\n\n url_retrieve (url:str, outfile:str, chunk_size:int=4096, user:str=None,\n passwd:str=None)\n\nImproved urlretrieve with progressbar, timeout and chunker.\nThis downloader has built-in progress bar using tqdm and using the requests package it improves standard urllib behavior by adding time-out capability.\nI tested different chunk_sizes and most of the time 128 was actually fastest, YMMV.\nInspired by https://stackoverflow.com/a/61575758/680232\n\n\n\n\n\n\n\n\n\n\nType\nDefault\nDetails\n\n\n\n\nurl\nstr\n\nThe URL to download\n\n\noutfile\nstr\n\nThe path where to store the downloaded file.\n\n\nchunk_size\nint\n4096\ndef chunk size for the request.iter_content call\n\n\nuser\nstr\nNone\nif provided, create HTTPBasicAuth object\n\n\npasswd\nstr\nNone\nif provided, create HTTPBasicAuth object\n\n\n\n\nsource\n\n\ncheck_url_exists\n\n check_url_exists (url)\n\n\nsource\n\n\nget_remote_timestamp\n\n get_remote_timestamp (url:str)\n\nGet the timestamp of a remote file.\nUseful for checking if there’s an updated file available.\n\n\n\n\nType\nDetails\n\n\n\n\nurl\nstr\nURL to check timestamp for\n\n\nReturns\ndatetime\n\n\n\n\n\nsource\n\n\nparse_http_date\n\n parse_http_date (text:str)\n\nParse date string retrieved via urllib.request.\n\n\n\n\n\n\n\n\n\nType\nDetails\n\n\n\n\ntext\nstr\ndatestring from urllib.request\n\n\nReturns\ndatetime\ndt.datetime object from given datetime string\n\n\n\n\nhave_internet()\n\nTrue" + }, + { + "objectID": "api/utils.html#image-processing-helpers", + "href": "api/utils.html#image-processing-helpers", + "title": "Utils", + "section": "Image processing helpers", + "text": "Image processing helpers\n\nsource\n\nfile_variations\n\n file_variations (filename:Union[str,pathlib.Path], extensions:list)\n\nCreate a variation of file names.\nGenerate a list of variations on a filename by replacing the extension with the provided list.\nAdapted from T. Olsens `file_variations of the pysis module for using pathlib.\n\n\n\n\nType\nDetails\n\n\n\n\nfilename\nUnion\nThe original filename to use as a base.\n\n\nextensions\nlist\n\n\n\nReturns\nlist\nlist of Paths\n\n\n\n\nsource\n\n\nget_gdal_center_coords\n\n get_gdal_center_coords (imgpath:Union[str,pathlib.Path])\n\nGet center rows/cols pixel coordinate for GDAL-readable dataset.\nCheck CLI gdalinfo --formats to see all formats that GDAL can open.\n\n\n\n\nType\nDetails\n\n\n\n\nimgpath\nUnion\nPath to raster image that is readable by GDLA\n\n\nReturns\nTuple\ncenter row/col coordinates.\n\n\n\n\nsource\n\n\nheight_from_shadow\n\n height_from_shadow (shadow_in_pixels:float, sun_elev:float)\n\nCalculate height of an object from its shadow length.\nNote, that your image might have been binned. You need to correct shadow_in_pixels for that.\n\n\n\n\nType\nDetails\n\n\n\n\nshadow_in_pixels\nfloat\nMeasured length of shadow in pixels\n\n\nsun_elev\nfloat\nAnge of sun over horizon in degrees\n\n\nReturns\nfloat\nHeight [meter]\n\n\n\n\nfname = \"abc.txt\"\n\n\nextensions = \".cub .cal.cub .map.cal.cub\".split()\n\n\nfile_variations(fname, extensions)\n\n[Path('abc.cub'), Path('abc.cal.cub'), Path('abc.map.cal.cub')]\n\n\n\nassert len(extensions) == len(file_variations(fname, extensions))" + }, + { + "objectID": "api/utils.html#isis-helpers", + "href": "api/utils.html#isis-helpers", + "title": "Utils", + "section": "ISIS helpers", + "text": "ISIS helpers\n\nsource\n\ncatch_isis_error\n\n catch_isis_error (func)\n\ncan be used as decorator for any ISIS function" + }, + { + "objectID": "api/utils.html#notebook-tools", + "href": "api/utils.html#notebook-tools", + "title": "Utils", + "section": "Notebook tools", + "text": "Notebook tools\n\nsource\n\nfix_nb_metadata_folder\n\n fix_nb_metadata_folder (folder)\n\n\nsource\n\n\nfix_nb_metadata\n\n fix_nb_metadata (fpath)\n\n\nfrom nbdev import nbdev_export\n\nnbdev_export()" + }, + { + "objectID": "api/exceptions.html", + "href": "api/exceptions.html", + "title": "Package exceptions", + "section": "", + "text": "source\n\nMissingParameterError\n\n MissingParameterError (txt)\n\nBase class for exceptions in this module.\n\nsource\n\n\nSpiceError\n\n SpiceError (function)\n\nBase class for exceptions in this module.\n\nsource\n\n\nObserverNotSetError\nBase class for exceptions in this module.\n\nsource\n\n\nSPointNotSetError\nBase class for exceptions in this module.\n\nsource\n\n\nSpicerError\nBase class for exceptions in this module.\n\nsource\n\n\nGeoTransformNotSetError\n\n GeoTransformNotSetError (where, what)\n\nException raised for errors in the input of transformations.\nAttributes: where – where is something missing what – what is missing\n\nsource\n\n\nProjectionNotSetError\n\n ProjectionNotSetError (where, what)\n\nException raised for errors in the input of transformations.\nAttributes: where – where is something missing what – what is missing\n\nsource\n\n\nSomethingNotSetError\n\n SomethingNotSetError (where, what)\n\nException raised for errors in the input of transformations.\nAttributes: where – where is something missing what – what is missing\n\nsource\n\n\nError\nBase class for exceptions in this module." + }, + { + "objectID": "api/hirise.html", + "href": "api/hirise.html", + "title": "HiRISE", + "section": "", + "text": "source\n\nOBSID\n\n OBSID (obsid:str)\n\nManage HiRISE observation ids.\nFor example PSP_003092_0985. phase is set to PSP for orbits < 11000, no setting required.\n\n\n\n\nType\nDetails\n\n\n\n\nobsid\nstr\ne.g. PSP_003092_0985\n\n\n\n\nobsid = OBSID(\"PSP_003092_0985\")\nobsid\n\nPSP_003092_0985\n\n\n\nassert obsid.orbit == \"003092\"\n\n\nassert obsid.targetcode == \"0985\"\n\n\nassert obsid.phase == \"PSP\"\n\n\nassert obsid.upper_orbit_folder == \"ORB_003000_003099\"\n\n\nassert obsid.storage_path_stem == \"PSP/ORB_003000_003099/PSP_003092_0985\"\n\n\nsource\n\n\nProductPathfinder\n\n ProductPathfinder (initstr:str, check_url:bool=True)\n\nDetermine paths and URLs for HiRISE RDR products (also EXTRAS.)\nWe use the PDS definition of PRODUCT_ID here, e.g. PSP_003092_0985_RED.\nAttributes jp2_path and label_path get you the official RDR mosaic product, with kind steering if you get the COLOR or the RED product. All other properties go to the RDR/EXTRAS folder. The “PDS” part of the path is handled in the OBSID class.\n\n\n\n\n\n\n\n\n\n\nType\nDefault\nDetails\n\n\n\n\ninitstr\nstr\n\nPRODUCT_ID string, e.g. PSP_003092_0985_RED\n\n\ncheck_url\nbool\nTrue\nfor performance, the user might not want the url check\n\n\n\n\npid = \"ESP_039983_1390_RED\"\n\n\nppf = ProductPathfinder(pid)\n\n\nppf.storage_stem\n\n'ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED'\n\n\n\nppf.local_label_path.exists()\n\nFalse\n\n\n\nppf.edr_storage_stem\n\nPath('EDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED')\n\n\n\nppf.download_label()\n\n\n\n\nPath('/home/ayek72/mnt/slowdata/planetarypy/missions/mro/hirise/ESP_039983_1390/ESP_039983_1390_RED.LBL')\n\n\n\nppf.go_to_homepage()\n\n4;1HPS connection to uahirise.org[22;24H Getting https://uahirise.org/ESP_039983_1390 \n\n\n\nppf.homepage\n\n'https://uahirise.org/ESP_039983_1390'\n\n\n\nassert isinstance(ppf.obsid, OBSID)\n\n\nassert ppf.kind == \"RED\"\n\n\nassert ppf.label_fname == \"ESP_039983_1390_RED.LBL\"\n\n\nassert ppf.label_path == Path('RDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED.LBL')\n\n\n\nPaths and URLS\nEach xxx_path attribute is also available as xxx_url, and accessing the _url parameter immediately checks for its existence on the server.\n\n# little helper to show attributes inside ProductPathfinder object...\ndef _isprop(v):\n return isinstance(v, property)\n\n\ndef _get_properties(classname, substring):\n names = [name for (name, value) in inspect.getmembers(classname, _isprop) if name.endswith(substring)]\n return names\n\n\n# Here I'm checking that all _url versions work, each access checks for existence:\nfor prop in _get_properties(ProductPathfinder, \"_path\"):\n if prop.startswith(\"local_label\"):\n continue\n print(prop)\n print(getattr(ppf, prop))\n urlattr = prop.replace(\"_path\", \"_url\")\n print(urlattr)\n url = getattr(ppf, urlattr)\n print(url)\n\nabrowse_path\nEXTRAS/RDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED.abrowse.jpg\nabrowse_url\nhttps://hirise-pds.lpl.arizona.edu/PDS/EXTRAS/RDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED.abrowse.jpg\nbrowse_path\nEXTRAS/RDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED.browse.jpg\nbrowse_url\nhttps://hirise-pds.lpl.arizona.edu/PDS/EXTRAS/RDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED.browse.jpg\njp2_path\nRDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED.JP2\njp2_url\nhttps://hirise-pds.lpl.arizona.edu/PDS/RDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED.JP2\nlabel_path\nRDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED.LBL\nlabel_url\nhttps://hirise-pds.lpl.arizona.edu/PDS/RDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED.LBL\nnomap_browse_path\nEXTRAS/RDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED.NOMAP.browse.jpg\nnomap_browse_url\nhttps://hirise-pds.lpl.arizona.edu/PDS/EXTRAS/RDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED.NOMAP.browse.jpg\nnomap_jp2_path\nEXTRAS/RDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED.NOMAP.JP2\nnomap_jp2_url\nhttps://hirise-pds.lpl.arizona.edu/PDS/EXTRAS/RDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED.NOMAP.JP2\nnomap_thumbnail_path\nEXTRAS/RDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED.NOMAP.thumb.jpg\nnomap_thumbnail_url\nhttps://hirise-pds.lpl.arizona.edu/PDS/EXTRAS/RDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED.NOMAP.thumb.jpg\nquicklook_path\nEXTRAS/RDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED.QLOOK.JP2\nquicklook_url\nhttps://hirise-pds.lpl.arizona.edu/PDS/EXTRAS/RDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED.QLOOK.JP2\nthumbnail_path\nEXTRAS/RDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED.thumb.jpg\nthumbnail_url\nhttps://hirise-pds.lpl.arizona.edu/PDS/EXTRAS/RDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED.thumb.jpg\n\n\n\nppf.storage_stem\n\n'ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED'\n\n\n\nppf.nomap_browse_url\n\nURL('https://hirise-pds.lpl.arizona.edu/PDS/EXTRAS/RDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED.NOMAP.browse.jpg')\n\n\n\nppf.abrowse_url\n\nURL('https://hirise-pds.lpl.arizona.edu/PDS/EXTRAS/RDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED.abrowse.jpg')\n\n\n\nppf.nomap_jp2_path\n\n'EXTRAS/RDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED.NOMAP.JP2'\n\n\n\nsource\n\n\nCOLOR_PRODUCT\n\n COLOR_PRODUCT (obsid)\n\nInitialize self. See help(type(self)) for accurate signature.\n\nsource\n\n\nRGB_NOMAP\n\n RGB_NOMAP (obsid)\n\nInitialize self. See help(type(self)) for accurate signature.\n\nobsid = \"ESP_039983_1390\"\n\n\nrgb = RGB_NOMAP(obsid)\n\n\nrgb.obsid\n\n'ESP_039983_1390'\n\n\n\nrgb.product_id\n\n'ESP_039983_1390_RGB'\n\n\n\nrgb.meta.head()\n\nvolume_id MROHR_0001\nfile_name_specification RDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_...\ninstrument_host_id MRO\ninstrument_id HIRISE\nobservation_id ESP_039983_1390\nName: 75508, dtype: object\n\n\n\nrgb.local_path\n\nPath('/home/ayek72/mnt/slowdata/planetarypy/missions/mro/hirise/ESP_039983_1390/ESP_039983_1390_RGB.NOMAP.JP2')\n\n\n\nrgb.url\n\nURL('https://hirise-pds.lpl.arizona.edu/PDS/EXTRAS/RDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RGB.NOMAP.JP2')\n\n\n\nrgb.download(overwrite=False)\n\nFile exists. Use `overwrite=True` to download fresh.\n\n\n\nrgb.read()\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n<xarray.DataArray (band: 3, y: 20000, x: 2024)>\ndask.array<open_rasterio-3e88685e58afe3daaabd13b6ff29c609<this-array>, shape=(3, 20000, 2024), dtype=uint16, chunksize=(1, 2024, 2024), chunktype=numpy.ndarray>\nCoordinates:\n * band (band) int64 1 2 3\n * x (x) float64 0.5 1.5 2.5 3.5 ... 2.022e+03 2.022e+03 2.024e+03\n * y (y) float64 0.5 1.5 2.5 3.5 4.5 ... 2e+04 2e+04 2e+04 2e+04\n spatial_ref int64 0\nAttributes:\n scale_factor: 1.0\n add_offset: 0.0xarray.DataArrayband: 3y: 20000x: 2024dask.array<chunksize=(1, 2024, 2024), meta=np.ndarray>\n\n\n\n\n\n\n\n\n\n\n\nArray\nChunk\n\n\n\n\nBytes\n231.63 MiB\n7.81 MiB\n\n\nShape\n(3, 20000, 2024)\n(1, 2024, 2024)\n\n\nDask graph\n30 chunks in 2 graph layers\n\n\nData type\nuint16 numpy.ndarray\n\n\n\n\n\n\n\nCoordinates: (4)band(band)int641 2 3array([1, 2, 3])x(x)float640.5 1.5 2.5 ... 2.022e+03 2.024e+03array([5.0000e-01, 1.5000e+00, 2.5000e+00, ..., 2.0215e+03, 2.0225e+03,\n 2.0235e+03])y(y)float640.5 1.5 2.5 ... 2e+04 2e+04 2e+04array([5.00000e-01, 1.50000e+00, 2.50000e+00, ..., 1.99975e+04, 1.99985e+04,\n 1.99995e+04])spatial_ref()int640GeoTransform :0.0 1.0 0.0 0.0 0.0 1.0array(0)Indexes: (3)bandPandasIndexPandasIndex(Int64Index([1, 2, 3], dtype='int64', name='band'))xPandasIndexPandasIndex(Float64Index([ 0.5, 1.5, 2.5, 3.5, 4.5, 5.5, 6.5, 7.5,\n 8.5, 9.5,\n ...\n 2014.5, 2015.5, 2016.5, 2017.5, 2018.5, 2019.5, 2020.5, 2021.5,\n 2022.5, 2023.5],\n dtype='float64', name='x', length=2024))yPandasIndexPandasIndex(Float64Index([ 0.5, 1.5, 2.5, 3.5, 4.5, 5.5, 6.5,\n 7.5, 8.5, 9.5,\n ...\n 19990.5, 19991.5, 19992.5, 19993.5, 19994.5, 19995.5, 19996.5,\n 19997.5, 19998.5, 19999.5],\n dtype='float64', name='y', length=20000))Attributes: (2)scale_factor :1.0add_offset :0.0\n\n\n\nrgb.show(xslice=slice(1000, 2000), yslice=slice(16000, 18000))\n\n\n\n\n\n\n\n\n\n \n\n\n\n\n\nsource\n\n\nRGB_NOMAPCollection\n\n RGB_NOMAPCollection (obsids)\n\nClass to deal with a set of RGB_NOMAP products.\n/home/runner/micromamba/envs/my-env/lib/python3.11/site-packages/fastcore/docscrape.py:225: UserWarning: Unknown section Example\n else: warn(msg)\n\nsource\n\n\nSOURCE_PRODUCT\n\n SOURCE_PRODUCT (spid, saveroot=None, check_url=True)\n\nManage SOURCE_PRODUCT id.\n\nobsid = 'ESP_027021_1525_RED'\n\n\nfor i in range(10):\n for ch in [0, 1]:\n spid = f\"{obsid}{i}_{ch}\"\n try:\n SOURCE_PRODUCT(spid).download()\n except ConnectionError:\n pass\n\nFile exists. Use `overwrite=True` to download fresh.\nFile exists. Use `overwrite=True` to download fresh.\nFile exists. Use `overwrite=True` to download fresh.\nFile exists. Use `overwrite=True` to download fresh.\nFile exists. Use `overwrite=True` to download fresh.\nFile exists. Use `overwrite=True` to download fresh.\nFile exists. Use `overwrite=True` to download fresh.\nFile exists. Use `overwrite=True` to download fresh.\nFile exists. Use `overwrite=True` to download fresh.\nFile exists. Use `overwrite=True` to download fresh.\nFile exists. Use `overwrite=True` to download fresh.\nFile exists. Use `overwrite=True` to download fresh.\nFile exists. Use `overwrite=True` to download fresh.\nFile exists. Use `overwrite=True` to download fresh.\nFile exists. Use `overwrite=True` to download fresh.\nFile exists. Use `overwrite=True` to download fresh.\nFile exists. Use `overwrite=True` to download fresh.\nFile exists. Use `overwrite=True` to download fresh.\n\n\n/tmp/ipykernel_1172729/2293453911.py:88: UserWarning: https://hirise-pds.lpl.arizona.edu/PDS/EDR/ESP/ORB_027000_027099/ESP_027021_1525/ESP_027021_1525_RED9_0.IMG does not exist on the server.\n warnings.warn(f\"{u} does not exist on the server.\")\n/tmp/ipykernel_1172729/2293453911.py:88: UserWarning: https://hirise-pds.lpl.arizona.edu/PDS/EDR/ESP/ORB_027000_027099/ESP_027021_1525/ESP_027021_1525_RED9_1.IMG does not exist on the server.\n warnings.warn(f\"{u} does not exist on the server.\")\n\n\n\nsp = SOURCE_PRODUCT(\"ESP_027021_1525_RED0_0\")\n\n\nsp.local_path\n\nPath('/home/ayek72/mnt/slowdata/planetarypy/missions/mro/hirise/ESP_027021_1525/ESP_027021_1525_RED0_0.IMG')\n\n\n\nsp.download()\n\nFile exists. Use `overwrite=True` to download fresh.\n\n\n\nsp.stitched_cube_path\n\nPath('/home/ayek72/mnt/slowdata/planetarypy/missions/mro/hirise/ESP_027021_1525/ESP_027021_1525_RED0.cub')\n\n\n\nsp.url\n\nURL('https://hirise-pds.lpl.arizona.edu/PDS/EDR/ESP/ORB_027000_027099/ESP_027021_1525/ESP_027021_1525_RED0_0.IMG')\n\n\n\nsp.remote_path\n\nPath('EDR/ESP/ORB_027000_027099/ESP_027021_1525/ESP_027021_1525_RED0_0.IMG')\n\n\n\nsp.local_path\n\nPath('/home/ayek72/mnt/slowdata/planetarypy/missions/mro/hirise/ESP_027021_1525/ESP_027021_1525_RED0_0.IMG')\n\n\n\nsp.channel\n\n'0'\n\n\n\nsp.ccd\n\n'RED0'\n\n\n\nsp.color\n\n'RED'\n\n\n\nsp.ccdno\n\n'0'\n\n\n\nsp.spid\n\n'ESP_027021_1525_RED0_0'\n\n\n\nsp\n\nSOURCE_PRODUCT: ESP_027021_1525_RED0_0\n\n\n\nsp.fname\n\n'ESP_027021_1525_RED0_0.IMG'\n\n\n\nsp.local_cube\n\nPath('/home/ayek72/mnt/slowdata/planetarypy/missions/mro/hirise/ESP_027021_1525/ESP_027021_1525_RED0_0.cub')\n\n\n\nsp.stitched_cube_name\n\n'ESP_027021_1525_RED0.cub'\n\n\n\nsp.stitched_cube_path.exists()\n\nTrue\n\n\n\nsource\n\n\nRED_PRODUCT\n\n RED_PRODUCT (obsid, ccdno, channel, **kwargs)\n\nThis exists to support creating a RED_PRODUCT_ID from parts of a SOURCE_PRODUCT id.\n\nRED_PRODUCT(\"ESP_027021_1525\", 4, 0).channel\n\n'0'\n\n\n\nrpid = RED_PRODUCT(\"ESP_039983_1390\", \"4\", \"0\")\nrpid.spid\n\n'ESP_039983_1390_RED4_0'\n\n\n\nrpid.fname\n\n'ESP_039983_1390_RED4_0.IMG'\n\n\n\nrpid.url\n\nURL('https://hirise-pds.lpl.arizona.edu/PDS/EDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RED4_0.IMG')\n\n\n\nrpid.download()\n\nFile exists. Use `overwrite=True` to download fresh.\n\n\n\nsource\n\n\nBG_PRODUCT\n\n BG_PRODUCT (obsid, ccdno, channel)\n\nManage SOURCE_PRODUCT id.\n\nsource\n\n\nIR_PRODUCT\n\n IR_PRODUCT (obsid, ccdno, channel)\n\nManage SOURCE_PRODUCT id.\n\nsource\n\n\nRedMosaic\n\n RedMosaic (obsid)\n\nInitialize self. See help(type(self)) for accurate signature.\n\nobsid = \"ESP_027021_1525\"\n\n\nred = RedMosaic(obsid)\n\n\n!ls {red.local_path.parent}\n\nB01_009958_1524_XI_27S347W.cal.cub ESP_027021_1525_RED4_1.IMG\nB01_009958_1524_XI_27S347W.lev2.cub ESP_027021_1525_RED4.cub\ncube2.lis ESP_027021_1525_RED4.map.cub\ncube.lis ESP_027021_1525_RED4.norm.cub\nESP_027021_1525_RED0_0.cal.cub ESP_027021_1525_RED5_0.cal.cub\nESP_027021_1525_RED0_0.cub ESP_027021_1525_RED5_0.cub\nESP_027021_1525_RED0_0.hical.log ESP_027021_1525_RED5_0.hical.log\nESP_027021_1525_RED0_0.IMG ESP_027021_1525_RED5_0.IMG\nESP_027021_1525_RED0_1.cal.cub ESP_027021_1525_RED5_1.cal.cub\nESP_027021_1525_RED0_1.cub ESP_027021_1525_RED5_1.cub\nESP_027021_1525_RED0_1.hical.log ESP_027021_1525_RED5_1.hical.log\nESP_027021_1525_RED0_1.IMG ESP_027021_1525_RED5_1.IMG\nESP_027021_1525_RED0.cub ESP_027021_1525_RED5.cub\nESP_027021_1525_RED0.map.cub ESP_027021_1525_RED5.map.cub\nESP_027021_1525_RED0.norm.cub ESP_027021_1525_RED5.map.cub.aux.xml\nESP_027021_1525_RED1_0.cal.cub ESP_027021_1525_RED5.norm.cub\nESP_027021_1525_RED1_0.cub ESP_027021_1525_RED6_0.cal.cub\nESP_027021_1525_RED1_0.hical.log ESP_027021_1525_RED6_0.cub\nESP_027021_1525_RED1_0.IMG ESP_027021_1525_RED6_0.hical.log\nESP_027021_1525_RED1_1.cal.cub ESP_027021_1525_RED6_0.IMG\nESP_027021_1525_RED1_1.cub ESP_027021_1525_RED6_1.cal.cub\nESP_027021_1525_RED1_1.hical.log ESP_027021_1525_RED6_1.cub\nESP_027021_1525_RED1_1.IMG ESP_027021_1525_RED6_1.hical.log\nESP_027021_1525_RED1.cub ESP_027021_1525_RED6_1.IMG\nESP_027021_1525_RED1.map.cub ESP_027021_1525_RED6.cub\nESP_027021_1525_RED1.norm.cub ESP_027021_1525_RED6.map.cub\nESP_027021_1525_RED2_0.cal.cub ESP_027021_1525_RED6.norm.cub\nESP_027021_1525_RED2_0.cub ESP_027021_1525_RED7_0.cal.cub\nESP_027021_1525_RED2_0.hical.log ESP_027021_1525_RED7_0.cub\nESP_027021_1525_RED2_0.IMG ESP_027021_1525_RED7_0.hical.log\nESP_027021_1525_RED2_1.cal.cub ESP_027021_1525_RED7_0.IMG\nESP_027021_1525_RED2_1.cub ESP_027021_1525_RED7_1.cal.cub\nESP_027021_1525_RED2_1.hical.log ESP_027021_1525_RED7_1.cub\nESP_027021_1525_RED2_1.IMG ESP_027021_1525_RED7_1.hical.log\nESP_027021_1525_RED2.cub ESP_027021_1525_RED7_1.IMG\nESP_027021_1525_RED2.map.cub ESP_027021_1525_RED7.cub\nESP_027021_1525_RED2.norm.cub ESP_027021_1525_RED7.map.cub\nESP_027021_1525_RED3_0.cal.cub ESP_027021_1525_RED7.norm.cub\nESP_027021_1525_RED3_0.cub ESP_027021_1525_RED8_0.cal.cub\nESP_027021_1525_RED3_0.hical.log ESP_027021_1525_RED8_0.cub\nESP_027021_1525_RED3_0.IMG ESP_027021_1525_RED8_0.hical.log\nESP_027021_1525_RED3_1.cal.cub ESP_027021_1525_RED8_0.IMG\nESP_027021_1525_RED3_1.cub ESP_027021_1525_RED8_1.cal.cub\nESP_027021_1525_RED3_1.hical.log ESP_027021_1525_RED8_1.cub\nESP_027021_1525_RED3_1.IMG ESP_027021_1525_RED8_1.hical.log\nESP_027021_1525_RED3.cub ESP_027021_1525_RED8_1.IMG\nESP_027021_1525_RED3.map.cub ESP_027021_1525_RED8.cub\nESP_027021_1525_RED3.norm.cub ESP_027021_1525_RED8.map.cub\nESP_027021_1525_RED4_0.cal.cub ESP_027021_1525_RED8.norm.cub\nESP_027021_1525_RED4_0.cub ESP_027021_1525_RED.LBL\nESP_027021_1525_RED4_0.hical.log normalized.lis\nESP_027021_1525_RED4_0.IMG point.txt\nESP_027021_1525_RED4_1.cal.cub print.prt\nESP_027021_1525_RED4_1.cub set_overlaps.txt\nESP_027021_1525_RED4_1.hical.log" + }, + { + "objectID": "api/pds.apps.html", + "href": "api/pds.apps.html", + "title": "Apps", + "section": "", + "text": "source\n\nfind_indexes\n\n find_indexes (instrument:str)\n\nFind existing indexes for an instrument.\n\n\n\n\nType\nDetails\n\n\n\n\ninstrument\nstr\nDotted mission.instrument key, e.g. cassini.iss\n\n\nReturns\nlist\nList of configured index names\n\n\n\n\nfind_indexes(\"cassini.iss\")\n\n['index', 'inventory', 'moon_summary', 'ring_summary', 'saturn_summary']\n\n\n\nfind_indexes(\"mro.ctx\")\n\n['edr']\n\n\n\nsource\n\n\nget_index\n\n get_index (instr:str, index_name:str='', refresh:bool=True,\n force:bool=False)\n\nExample: get_index(“cassini.iss”, “index”)\n\n\n\n\n\n\n\n\n\n\nType\nDefault\nDetails\n\n\n\n\ninstr\nstr\n\nDotted instrument index, e.g. cassini.iss\n\n\nindex_name\nstr\n\nIndex name, for exmample ‘moon_summary. Optional’\n\n\nrefresh\nbool\nTrue\nswitch to refresh an index (i.e. download if update available).Set to False for faster return time to avoid web scraping\n\n\nforce\nbool\nFalse\nswitch off for faster return time.\n\n\nReturns\nDataFrame\n\nThe PDS index convert to pandas DataFrame\n\n\n\n\ninstr = \"cassini.iss\"\nindex_name = \"moon_summary\"\n\n\nindex = get_index(instr, index_name, refresh=False)\n\n\nindex\n\n\n\n\n\n\n\n\nVOLUME_ID\nFILE_SPECIFICATION_NAME\nOPUS_ID\nTARGET_NAME\nMINIMUM_PLANETOCENTRIC_LATITUDE\nMAXIMUM_PLANETOCENTRIC_LATITUDE\nMINIMUM_PLANETOGRAPHIC_LATITUDE\nMAXIMUM_PLANETOGRAPHIC_LATITUDE\nMINIMUM_IAU_LONGITUDE\nMAXIMUM_IAU_LONGITUDE\n...\nMAXIMUM_EMISSION_ANGLE\nSUB_SOLAR_PLANETOCENTRIC_LATITUDE\nSUB_SOLAR_PLANETOGRAPHIC_LATITUDE\nSUB_OBSERVER_PLANETOCENTRIC_LATITUDE\nSUB_OBSERVER_PLANETOGRAPHIC_LATITUDE\nSUB_SOLAR_IAU_LONGITUDE\nSUB_OBSERVER_IAU_LONGITUDE\nCENTER_RESOLUTION\nCENTER_DISTANCE\nCENTER_PHASE_ANGLE\n\n\n\n\n0\nCOISS_2001\ndata/1454725799_1455008789/N1454725799_1.LBL\nco-iss-n1454725799\nRHEA\n-999.0\n-999.0\n-999.0\n-999.0\n-999.0\n-999.0\n...\n-999.0\n-25.206\n-25.442\n-16.566\n-16.558\n183.907\n252.947\n423.6356\n70701354.366\n64.429\n\n\n1\nCOISS_2001\ndata/1454725799_1455008789/N1454725799_1.LBL\nco-iss-n1454725799\nHELENE\n-999.0\n-999.0\n-999.0\n-999.0\n-999.0\n-999.0\n...\n-999.0\n-25.532\n-50.716\n-16.532\n-36.57\n148.17\n217.149\n424.36902\n70823757.002\n64.345\n\n\n2\nCOISS_2001\ndata/1454725799_1455008789/N1454725799_1.LBL\nco-iss-n1454725799\nTELESTO\n-999.0\n-999.0\n-999.0\n-999.0\n-999.0\n-999.0\n...\n-999.0\n-26.061\n-51.51\n-15.639\n-21.616\n189.199\n257.807\n424.28746\n70810144.519\n64.28\n\n\n3\nCOISS_2001\ndata/1454725799_1455008789/N1454726579_1.LBL\nco-iss-n1454726579\nTITAN\n-36.111\n-36.111\n-36.111\n-36.111\n0.0\n360.0\n...\n54.704\n-25.325\n-25.325\n-16.28\n-16.28\n340.092\n47.855\n428.89673\n71579395.066\n63.37\n\n\n4\nCOISS_2001\ndata/1454725799_1455008789/N1454727359_1.LBL\nco-iss-n1454727359\nHYPERION\n-999.0\n-999.0\n-999.0\n-999.0\n-999.0\n-999.0\n...\n-999.0\n11.777\n25.907\n44.104\n57.544\n173.985\n237.769\n418.94545\n69918606.586\n63.093\n\n\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n\n\n385714\nCOISS_2116\ndata/1884017637_1884113741/N1884017911_1.LBL\nco-iss-n1884017911\nTITAN\n-14.352\n72.101\n-14.352\n72.101\n229.956\n329.975\n...\n89.069\n26.644\n26.644\n23.599\n23.599\n32.084\n299.389\n4.64069\n774493.2\n81.887\n\n\n385715\nCOISS_2116\ndata/1884017637_1884113741/N1884018021_1.LBL\nco-iss-n1884018021\nTITAN\n-14.597\n71.882\n-14.597\n71.882\n230.932\n330.255\n...\n88.913\n26.644\n26.644\n23.594\n23.594\n32.107\n299.415\n4.64263\n774816.731\n81.888\n\n\n385716\nCOISS_2116\ndata/1884017637_1884113741/N1884018579_1.LBL\nco-iss-n1884018579\nTITAN\n-14.435\n72.643\n-14.435\n72.643\n228.942\n330.644\n...\n88.869\n26.644\n26.644\n23.57\n23.57\n32.217\n299.536\n9.30328\n776321.466\n81.889\n\n\n385717\nCOISS_2116\ndata/1884017637_1884113741/N1884091792_1.LBL\nco-iss-n1884091792\nDAPHNIS\n-999.0\n-999.0\n-999.0\n-999.0\n-999.0\n-999.0\n...\n-999.0\n26.684\n39.966\n25.321\n38.64\n294.939\n124.641\n4.56619\n762060.157\n127.157\n\n\n385718\nCOISS_2116\ndata/1884017637_1884113741/N1884109343_1.LBL\nco-iss-n1884109343\nPANDORA\n40.384\n63.749\n56.973\n76.952\n0.0\n360.0\n...\n62.435\n26.686\n49.386\n33.095\n53.259\n335.495\n142.016\n3.45805\n577120.582\n118.858\n\n\n\n\n385719 rows × 35 columns\n\n\n\nIndexes can be given as 2 parameters (“cassini.iss”, “ring_summary”) or one (“cassini.iss.ring_summary”):\n\nindex = get_index(\"cassini.iss\", \"ring_summary\", refresh=False)\nindex.head()\n\n\n\n\n\n\n\n\nVOLUME_ID\nFILE_SPECIFICATION_NAME\nOPUS_ID\nMINIMUM_RIGHT_ASCENSION\nMAXIMUM_RIGHT_ASCENSION\nMINIMUM_DECLINATION\nMAXIMUM_DECLINATION\nMINIMUM_RING_RADIUS\nMAXIMUM_RING_RADIUS\nFINEST_RING_INTERCEPT_RESOLUTION\n...\nRING_CENTER_DISTANCE\nSUB_SOLAR_RING_LONGITUDE\nSUB_OBSERVER_RING_LONGITUDE\nRING_CENTER_PHASE_ANGLE\nRING_CENTER_INCIDENCE_ANGLE\nRING_CENTER_NORTH_BASED_INCIDENCE_ANGLE\nRING_CENTER_EMISSION_ANGLE\nRING_CENTER_NORTH_BASED_EMISSION_ANGLE\nSOLAR_RING_OPENING_ANGLE\nOBSERVER_RING_OPENING_ANGLE\n\n\n\n\n0\nCOISS_2001\ndata/1454725799_1455008789/N1454725799_1.LBL\nco-iss-n1454725799\n35.528398\n35.905555\n9.719637\n10.091212\n205899.335\n1098621.586\n419.0137\n...\n70874998.947\n284.523\n215.951\n64.07\n64.589\n115.411\n73.676\n106.324\n-25.411\n-16.324\n\n\n1\nCOISS_2001\ndata/1454725799_1455008789/N1454726579_1.LBL\nco-iss-n1454726579\n36.662898\n37.039038\n9.590114\n9.960833\n721136.155\n1745689.307\n421.97145\n...\n70870851.371\n284.524\n215.951\n64.07\n64.589\n115.411\n73.676\n106.324\n-25.411\n-16.324\n\n\n2\nCOISS_2001\ndata/1454725799_1455008789/N1454727359_1.LBL\nco-iss-n1454727359\n36.928066\n37.304334\n9.879593\n10.25011\n1042341.438\n2186830.92\n414.79041\n...\n70866703.094\n284.524\n215.951\n64.071\n64.589\n115.411\n73.676\n106.324\n-25.411\n-16.324\n\n\n3\nCOISS_2001\ndata/1454725799_1455008789/N1454728139_1.LBL\nco-iss-n1454728139\n28.10042\n28.479618\n6.224709\n6.601574\n-999.0\n-999.0\n-999.0\n...\n70862557.207\n284.524\n215.951\n64.071\n64.589\n115.411\n73.676\n106.324\n-25.411\n-16.324\n\n\n4\nCOISS_2001\ndata/1454725799_1455008789/N1454728919_1.LBL\nco-iss-n1454728919\n37.981418\n38.357791\n10.611947\n10.981697\n3865717.589\n3905151.343\n405.91234\n...\n70858406.794\n284.525\n215.951\n64.071\n64.589\n115.411\n73.676\n106.324\n-25.411\n-16.324\n\n\n\n\n5 rows × 59 columns\n\n\n\n\nindex = get_index(\"cassini.iss.ring_summary\", refresh=False)\nindex.head()\n\n\n\n\n\n\n\n\nVOLUME_ID\nFILE_SPECIFICATION_NAME\nOPUS_ID\nMINIMUM_RIGHT_ASCENSION\nMAXIMUM_RIGHT_ASCENSION\nMINIMUM_DECLINATION\nMAXIMUM_DECLINATION\nMINIMUM_RING_RADIUS\nMAXIMUM_RING_RADIUS\nFINEST_RING_INTERCEPT_RESOLUTION\n...\nRING_CENTER_DISTANCE\nSUB_SOLAR_RING_LONGITUDE\nSUB_OBSERVER_RING_LONGITUDE\nRING_CENTER_PHASE_ANGLE\nRING_CENTER_INCIDENCE_ANGLE\nRING_CENTER_NORTH_BASED_INCIDENCE_ANGLE\nRING_CENTER_EMISSION_ANGLE\nRING_CENTER_NORTH_BASED_EMISSION_ANGLE\nSOLAR_RING_OPENING_ANGLE\nOBSERVER_RING_OPENING_ANGLE\n\n\n\n\n0\nCOISS_2001\ndata/1454725799_1455008789/N1454725799_1.LBL\nco-iss-n1454725799\n35.528398\n35.905555\n9.719637\n10.091212\n205899.335\n1098621.586\n419.0137\n...\n70874998.947\n284.523\n215.951\n64.07\n64.589\n115.411\n73.676\n106.324\n-25.411\n-16.324\n\n\n1\nCOISS_2001\ndata/1454725799_1455008789/N1454726579_1.LBL\nco-iss-n1454726579\n36.662898\n37.039038\n9.590114\n9.960833\n721136.155\n1745689.307\n421.97145\n...\n70870851.371\n284.524\n215.951\n64.07\n64.589\n115.411\n73.676\n106.324\n-25.411\n-16.324\n\n\n2\nCOISS_2001\ndata/1454725799_1455008789/N1454727359_1.LBL\nco-iss-n1454727359\n36.928066\n37.304334\n9.879593\n10.25011\n1042341.438\n2186830.92\n414.79041\n...\n70866703.094\n284.524\n215.951\n64.071\n64.589\n115.411\n73.676\n106.324\n-25.411\n-16.324\n\n\n3\nCOISS_2001\ndata/1454725799_1455008789/N1454728139_1.LBL\nco-iss-n1454728139\n28.10042\n28.479618\n6.224709\n6.601574\n-999.0\n-999.0\n-999.0\n...\n70862557.207\n284.524\n215.951\n64.071\n64.589\n115.411\n73.676\n106.324\n-25.411\n-16.324\n\n\n4\nCOISS_2001\ndata/1454725799_1455008789/N1454728919_1.LBL\nco-iss-n1454728919\n37.981418\n38.357791\n10.611947\n10.981697\n3865717.589\n3905151.343\n405.91234\n...\n70858406.794\n284.525\n215.951\n64.071\n64.589\n115.411\n73.676\n106.324\n-25.411\n-16.324\n\n\n\n\n5 rows × 59 columns\n\n\n\n\nget_index(\"mro.ctx.edr\", refresh=False)\n\n\n\n\n\n\n\n\nVOLUME_ID\nFILE_SPECIFICATION_NAME\nORIGINAL_PRODUCT_ID\nPRODUCT_ID\nIMAGE_TIME\nINSTRUMENT_ID\nINSTRUMENT_MODE_ID\nLINE_SAMPLES\nLINES\nSPATIAL_SUMMING\n...\nSUB_SOLAR_LATITUDE\nSUB_SPACECRAFT_LONGITUDE\nSUB_SPACECRAFT_LATITUDE\nSOLAR_DISTANCE\nSOLAR_LONGITUDE\nLOCAL_TIME\nIMAGE_SKEW_ANGLE\nRATIONALE_DESC\nDATA_QUALITY_DESC\nORBIT_NUMBER\n\n\n\n\n0\nMROX_0001\nDATA/CRU_000001_9999_XN_99N999W.IMG\n4A_04_0001000400\nCRU_000001_9999_XN_99N999W\n2005-08-30 15:40:21.549\nCTX\nNIFL\n5056\n1024\n1\n...\n0.0\n0.0\n0.0\n0.0\n278.89\n10.16\n0.0\nInstrument checkout image of space\nOK\n-4242\n\n\n1\nMROX_0001\nDATA/CRU_000002_9999_XN_99N999W.IMG\n4A_04_0001000500\nCRU_000002_9999_XN_99N999W\n2005-09-08 15:59:45.313\nCTX\nNIFL\n5056\n15360\n1\n...\n0.0\n0.0\n0.0\n0.0\n284.48\n4.6\n0.0\nCalibration image of the Moon\nOK\n-4126\n\n\n2\nMROX_0001\nDATA/CRU_000003_9999_XN_99N999W.IMG\n4A_04_0001000600\nCRU_000003_9999_XN_99N999W\n2005-09-08 16:03:37.927\nCTX\nNIFL\n5056\n2048\n1\n...\n0.0\n0.0\n0.0\n0.0\n284.48\n4.66\n0.0\nCalibration image of Omega Centauri (globular ...\nOK\n-4126\n\n\n3\nMROX_0001\nDATA/CRU_000004_9999_XN_99N999W.IMG\n4A_04_0001000700\nCRU_000004_9999_XN_99N999W\n2005-09-08 16:08:23.841\nCTX\nNIFL\n5056\n2048\n1\n...\n0.0\n0.0\n0.0\n0.0\n284.48\n4.74\n0.0\nCalibration image of Omega Centauri (globular ...\nOK\n-4126\n\n\n4\nMROX_0001\nDATA/CRU_000005_9999_XN_99N999W.IMG\n4A_04_0001000800\nCRU_000005_9999_XN_99N999W\n2005-09-08 16:11:18.649\nCTX\nNIFL\n5056\n21504\n1\n...\n0.0\n0.0\n0.0\n0.0\n284.48\n4.79\n0.0\nCalibration image of the Moon\nOK\n-4126\n\n\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n\n\n138410\nMROX_4461\nDATA/U14_076622_1804_XN_00N105W.IMG\n4A_04_118404B100\nU14_076622_1804_XN_00N105W\n2022-11-30 17:29:26.742\nCTX\nNIFL\n5056\n33792\n1\n...\n-5.6\n105.05\n0.45\n228081883.9\n346.9\n14.39\n89.7\nTerrain northwest of Noctis Labyrinthus\nOK\n76622\n\n\n138411\nMROX_4461\nDATA/U14_076622_2009_XI_20N108W.IMG\n4A_04_118504B200\nU14_076622_2009_XI_20N108W\n2022-11-30 17:36:13.062\nCTX\nITL\n5056\n7168\n1\n...\n-5.6\n107.61\n20.98\n228082990.5\n346.9\n14.3\n90.1\nCandidate impact site formed at most between M...\nOK\n76622\n\n\n138412\nMROX_4461\nDATA/U14_076623_1977_XN_17N133W.IMG\n4A_04_118404B300\nU14_076623_1977_XN_17N133W\n2022-11-30 19:26:53.410\nCTX\nNIFL\n5056\n35840\n1\n...\n-5.59\n134.45\n17.69\n228097986.1\n346.94\n14.37\n90.1\nRide-along with HiRISE\nOK\n76623\n\n\n138413\nMROX_4461\nDATA/U14_076625_1182_XN_61S177W.IMG\n4A_04_118404B800\nU14_076625_1182_XN_61S177W\n2022-11-30 22:46:27.741\nCTX\nNIFL\n5056\n52224\n1\n...\n-5.56\n177.43\n-61.87\n228126022.3\n347.01\n14.71\n90.4\nSouthern highlands\nOK\n76625\n\n\n138414\nMROX_4461\nDATA/U14_076625_1714_XN_08S185W.IMG\n4A_04_118404B900\nU14_076625_1714_XN_08S185W\n2022-11-30 23:02:50.690\nCTX\nNIFL\n5056\n52224\n1\n...\n-5.55\n185.83\n-8.75\n228127015.7\n347.02\n14.45\n90.5\nRide-along with HiRISE\nOK\n76625\n\n\n\n\n138415 rows × 51 columns\n\n\n\n\nsource\n\n\nfind_instruments\n\n find_instruments (mission:str)\n\nFind existing instruments for a mission.\n\n\n\n\nType\nDetails\n\n\n\n\nmission\nstr\nMission string, e.g. “cassini”\n\n\nReturns\nlist\nList of configured instrument names\n\n\n\n\nfind_instruments(\"cassini\")\n\n['iss', 'uvis']\n\n\n\nfind_instruments(\"mro\")\n\n['hirise', 'ctx']\n\n\n\nfrom nbdev import nbdev_export\nnbdev_export()" + }, + { + "objectID": "api/ctx.html", + "href": "api/ctx.html", + "title": "CTX", + "section": "", + "text": "import pandas as pd\n\npd.set_option(\"display.max_columns\", 1000)\nsource" + }, + { + "objectID": "api/ctx.html#command-line-interfaces", + "href": "api/ctx.html#command-line-interfaces", + "title": "CTX", + "section": "Command line interfaces", + "text": "Command line interfaces\n\nsource\n\nctx_calib\n\n ctx_calib (pid:str, source:str='', proc_root:str='',\n overwrite:bool=False)\n\n\n\n\n\nType\nDefault\nDetails\n\n\n\n\npid\nstr\n\nCTX product_id\n\n\nsource\nstr\n\npath to where EDRs are stored if not from plpy\n\n\nproc_root\nstr\n\npath to where processed data is to be stored\n\n\noverwrite\nbool\nFalse\noverwrite processed data\n\n\n\n\nctx_calib(pid, overwrite=True)\n\n\nfrom nbdev import nbdev_export\n\nnbdev_export()" + }, + { + "objectID": "api/pds.crism_index.html", + "href": "api/pds.crism_index.html", + "title": "CRISM PDS Index", + "section": "", + "text": "url = URL(\"https://pds-geosciences.wustl.edu/mro/mro-m-crism-5-rdr-mptargeted-v1/mrocr_4001/index/mtrdr0705_index.lbl\")\n\n\nsource\n\nMTRDRIndex\n\n MTRDRIndex (url)\n\nIndex manager class.\nThis class manages one index, identified by a dotted key, e.g. cassini.iss.ring_summary\n\nindex = MTRDRIndex(url=url)\n\n\nindex.download()\n\n\n\n\n\n\n\nDownloaded /home/ayek72/mnt/slowdata/planetarypy/missions/mro/crism/indexes/mtrdr/mtrdr0705_index.lbl and /home/ayek72/mnt/slowdata/planetarypy/missions/mro/crism/indexes/mtrdr/mtrdr0705_index.tab\nDone.\n\n\n\nindex.convert_to_parquet()\n\nDone.\n\n\n\nindex.parquet\n\n\n\n\n\n\n\n\nVOLUME_ID\nPRODUCT_ID\nPRODUCT_TYPE\nFILE_SPECIFICATION_NAME\nPARTICIPATING_INSTRUMENTS\nPRODUCT_CREATION_TIME\nSTART_TIME\nSTOP_TIME\nSPACECRAFT_CLOCK_START_COUNT\nSPACECRAFT_CLOCK_STOP_COUNT\n...\nWESTERNMOST_LONGITUDE\nEASTERNMOST_LONGITUDE\nLOWER_RIGHT_LATITUDE\nLOWER_RIGHT_LONGITUDE\nLOWER_LEFT_LATITUDE\nLOWER_LEFT_LONGITUDE\nUPPER_RIGHT_LATITUDE\nUPPER_RIGHT_LONGITUDE\nUPPER_LEFT_LATITUDE\nUPPER_LEFT_LONGITUDE\n\n\n\n\n0\nMROCR_4001\nFRT00005F0C_07_IF163J_MTR3\nMPTARGETED_RDR\nMTRDR/2007/2007_148/FRT00005F0C/FRT00005F0C_07...\n<NA>\n2015-06-12 09:00:20\n2007-05-28 17:30:38.605\n2007-05-28 17:32:22.339\n2/0864840658.00225\n2/0864840761.48344\n...\n52.8\n53.267\n-99.999\n-999.999\n-99.999\n-999.999\n-99.999\n-999.999\n-99.999\n-999.999\n\n\n1\nMROCR_4001\nFRT00005F0C_07_WV163J_MTR3\nMPTARGETED_RDR\nMTRDR/2007/2007_148/FRT00005F0C/FRT00005F0C_07...\n<NA>\n2015-06-12 09:00:20\n2007-05-28 17:30:38.605\n2007-05-28 17:32:22.339\n2/0864840658.00225\n2/0864840761.48344\n...\n-999.999\n-999.999\n-99.999\n-999.999\n-99.999\n-999.999\n-99.999\n-999.999\n-99.999\n-999.999\n\n\n2\nMROCR_4001\nFRT00005F0C_07_IN163J_MTR3\nMPTARGETED_RDR\nMTRDR/2007/2007_148/FRT00005F0C/FRT00005F0C_07...\n<NA>\n2015-06-12 09:04:09\n2007-05-28 17:30:38.605\n2007-05-28 17:32:22.339\n2/0864840658.00225\n2/0864840761.48344\n...\n52.8\n53.267\n-99.999\n-999.999\n-99.999\n-999.999\n-99.999\n-999.999\n-99.999\n-999.999\n\n\n3\nMROCR_4001\nFRT00005F0C_07_DE163L_MTR1\nMAP_PROJECTED_DDR\nMTRDR/2007/2007_148/FRT00005F0C/FRT00005F0C_07...\n<NA>\n2015-06-12 09:04:03\n2007-05-28 17:30:38.605\n2007-05-28 17:32:22.339\n2/864840658:225\n2/864840761:48344\n...\n52.8\n53.267\n-62.71\n53.27\n-62.76\n52.84\n-62.59\n53.23\n-62.6\n52.8\n\n\n4\nMROCR_4001\nFRT00005F0C_07_SU163J_MTR3\nMPTARGETED_RDR\nMTRDR/2007/2007_148/FRT00005F0C/FRT00005F0C_07...\n<NA>\n2015-06-12 09:00:29\n2007-05-28 17:30:38.605\n2007-05-28 17:32:22.339\n2/0864840658.00225\n2/0864840761.48344\n...\n52.8\n53.267\n-99.999\n-999.999\n-99.999\n-999.999\n-99.999\n-999.999\n-99.999\n-999.999\n\n\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n\n\n553\nMROCR_4001\nFRT00005DAC_07_IF165J_MTR3\nMPTARGETED_RDR\nMTRDR/2007/2007_144/FRT00005DAC/FRT00005DAC_07...\n<NA>\n2015-06-12 07:20:09\n2007-05-24 07:16:57.926\n2007-05-24 07:18:57.660\n2/0864458237.21046\n2/0864458357.03629\n...\n156.527\n156.771\n-99.999\n-999.999\n-99.999\n-999.999\n-99.999\n-999.999\n-99.999\n-999.999\n\n\n554\nMROCR_4001\nFRT00005DAC_07_DE165L_MTR1\nMAP_PROJECTED_DDR\nMTRDR/2007/2007_144/FRT00005DAC/FRT00005DAC_07...\n<NA>\n2015-06-12 07:22:51\n2007-05-24 07:16:57.926\n2007-05-24 07:18:57.660\n2/864458237:21046\n2/864458357:3629\n...\n156.527\n156.771\n9.67\n156.77\n9.66\n156.54\n9.88\n156.75\n9.84\n156.53\n\n\n555\nMROCR_4001\nFRT00005DAC_07_WV165J_MTR3\nMPTARGETED_RDR\nMTRDR/2007/2007_144/FRT00005DAC/FRT00005DAC_07...\n<NA>\n2015-06-12 07:20:09\n2007-05-24 07:16:57.926\n2007-05-24 07:18:57.660\n2/0864458237.21046\n2/0864458357.03629\n...\n-999.999\n-999.999\n-99.999\n-999.999\n-99.999\n-999.999\n-99.999\n-999.999\n-99.999\n-999.999\n\n\n556\nMROCR_4001\nFRT00005DAC_07_IN165J_MTR3\nMPTARGETED_RDR\nMTRDR/2007/2007_144/FRT00005DAC/FRT00005DAC_07...\n<NA>\n2015-06-12 07:22:56\n2007-05-24 07:16:57.926\n2007-05-24 07:18:57.660\n2/0864458237.21046\n2/0864458357.03629\n...\n156.527\n156.771\n-99.999\n-999.999\n-99.999\n-999.999\n-99.999\n-999.999\n-99.999\n-999.999\n\n\n557\nMROCR_4001\nFRT00005DAC_07_SU165J_MTR3\nMPTARGETED_RDR\nMTRDR/2007/2007_144/FRT00005DAC/FRT00005DAC_07...\n<NA>\n2015-06-12 07:20:17\n2007-05-24 07:16:57.926\n2007-05-24 07:18:57.660\n2/0864458237.21046\n2/0864458357.03629\n...\n156.527\n156.771\n-99.999\n-999.999\n-99.999\n-999.999\n-99.999\n-999.999\n-99.999\n-999.999\n\n\n\n\n558 rows × 57 columns" + }, + { + "objectID": "api/spice.kernels.html", + "href": "api/spice.kernels.html", + "title": "SPICE Kernels", + "section": "", + "text": "Feature list for this module:\n\nReceive the list of supported datasets for automatic retrieval of archived SPICE kernels\n\nThe supported datasets are tabled here at NAIF: https://naif.jpl.nasa.gov/naif/data_archived.html\n\nReceive the list of required SPICE kernels for a given mission and time range\nAutomatic download of kernels for a given mission and time range either into a given location or the planetarypy local archive.\n\nAs always in planetarypy the general design philosophy is to first develop a management class to give the user full control over all the details, and then add easy-to-use function for the end-user that do the most frequently used things in one go. (See section “User Functions”)" + }, + { + "objectID": "api/spice.kernels.html#intro", + "href": "api/spice.kernels.html#intro", + "title": "SPICE Kernels", + "section": "", + "text": "Feature list for this module:\n\nReceive the list of supported datasets for automatic retrieval of archived SPICE kernels\n\nThe supported datasets are tabled here at NAIF: https://naif.jpl.nasa.gov/naif/data_archived.html\n\nReceive the list of required SPICE kernels for a given mission and time range\nAutomatic download of kernels for a given mission and time range either into a given location or the planetarypy local archive.\n\nAs always in planetarypy the general design philosophy is to first develop a management class to give the user full control over all the details, and then add easy-to-use function for the end-user that do the most frequently used things in one go. (See section “User Functions”)" + }, + { + "objectID": "api/spice.kernels.html#identifying-and-downloading-kernel-sets", + "href": "api/spice.kernels.html#identifying-and-downloading-kernel-sets", + "title": "SPICE Kernels", + "section": "Identifying and downloading kernel sets", + "text": "Identifying and downloading kernel sets\nOne repeating task for SPICE calculations is the identification and retrieval of all SPICE kernels for a mission for a given time interval.\nThe folks at NAIF offer a “Subset” feature at their servers. Here we set up a table of the currently supported datasets:\n\ndatasets\n\n\n\n\n\n\n\n\npath\nMission Name\nPDS3 or PDS4\nData Size (GB)\nStart Time\nStop Time\n\n\nshorthand\n\n\n\n\n\n\n\n\n\n\nbc\nbc/bc_spice\nBepiColombo\n4\n1.1\n2018-10-20\n2023-01-01\n\n\ncassini\nco-s_j_e_v-spice-6-v1.0/cosp_1000\nCassini Orbiter\n3\n62.5\n1997-10-15\n2017-09-15\n\n\nclementine\nclem1-l-spice-6-v1.0/clsp_1000\nClementine\n3\n0.8\n1994-01-26\n1994-05-07\n\n\ndart\ndart/dart_spice\nDART\n4\n9.1\n2021-11-09\n2050-01-01\n\n\ndawn\ndawn-m_a-spice-6-v1.0/dawnsp_1000\nDAWN\n3\n86.4\n2007-09-27\n2018-10-31\n\n\ndi\ndi-c-spice-6-v1.0/disp_1000\nDeep Impact\n3\n0.7\n2005-01-12\n2005-08-09\n\n\nds1\nds1-a_c-spice-6-v1.0/ds1sp_1000\nDeep Space 1\n3\n0.9\n1998-10-24\n2001-12-18\n\n\nepoxi\ndif-c_e_x-spice-6-v1.0/epxsp_1000\nEPOXI\n3\n1.0\n2005-08-23\n2011-03-01\n\n\nem16\nem16/em16_spice\nExoMars TGO 2016\n4\n9.4\n2016-03-14\n2023-01-01\n\n\ngrail\ngrail-l-spice-6-v1.0/grlsp_1000\nGRAIL\n3\n4.3\n2011-09-10\n2012-12-17\n\n\nhayabusa\nhay-a-spice-6-v1.0/haysp_1000\nHayabusa\n3\n0.3\n2005-09-11\n2005-11-19\n\n\ninsight\ninsight/insight_spice\nInSight\n4\n0.9\n2018-05-05\n2022-12-15\n\n\njuno\njno-j_e_ss-spice-6-v1.0/jnosp_1000\nJUNO\n3\n46.9\n2011-08-05\n2022-08-17\n\n\nladee\nladee/ladee_spice\nLADEE\n4\n0.6\n2013-09-07\n2050-01-01\n\n\nlro\nlro-l-spice-6-v1.0/lrosp_1000\nLunar Reconnaissance Orbiter\n3\n595.7\n2009-06-18\n2023-03-15\n\n\nmaven\nmaven/maven_spice\nMAVEN\n4\n54.4\n2013-11-18\n2023-04-01\n\n\nopportunity\nmer1-m-spice-6-v1.0/mer1sp_1000\nMER 1 (Opportunity)\n3\n4.1\n2003-07-07\n2018-06-10\n\n\nspirit\nmer2-m-spice-6-v1.0/mer2sp_1000\nMER 2 (Spirit)\n3\n2.6\n2003-06-10\n2010-05-03\n\n\nmessenger\nmess-e_v_h-spice-6-v1.0/messsp_1000\nMESSENGER\n3\n44.8\n2004-08-03\n2015-04-30\n\n\nmars2020\nmars2020/mars2020_spice\nMars 2020\n4\n0.6\n2020-07-30\n2022-12-28\n\n\nmex\nmex-e_m-spice-6-v2.0/mexsp_2000\nMars Express\n3\n8.5\n2003-06-02\n2022-11-30\n\n\nmgs\nmgs-m-spice-6-v1.0/mgsp_1000\nMars Global Surveyor\n3\n15.4\n1996-11-06\n2006-11-02\n\n\nody\nody-m-spice-6-v1.0/odsp_1000\nMars Odyssey\n3\n33.2\n2001-04-07\n2022-10-01\n\n\nmro\nmro-m-spice-6-v1.0/mrosp_1000\nMars Reconnaissance Orbiter\n3\n314.9\n2005-08-12\n2023-04-01\n\n\nmsl\nmsl-m-spice-6-v1.0/mslsp_1000\nMars Science Laboratory\n3\n0.6\n2011-11-26\n2022-11-06\n\n\nnear\nnear-a-spice-6-v1.0/nearsp_1000\nNEAR\n3\n2.4\n1996-05-30\n2001-02-28\n\n\nnh\nnh-j_p_ss-spice-6-v1.0/nhsp_1000\nNew Horizons\n3\n1.6\n2006-01-19\n2019-12-30\n\n\norex\norex/orex_spice\nOSIRIS-REx\n4\n418.4\n2016-09-08\n2021-02-22\n\n\nrosetta\nro_rl-e_m_a_c-spice-6-v1.0/rossp_1000\nRosetta\n3\n5.9\n2004-03-02\n2017-01-01\n\n\nstardust\nsdu-c-spice-6-v1.0/sdsp_1000\nStardust\n3\n1.9\n1999-02-07\n2011-05-01\n\n\nvenus_climate_orbiter\nvco/vco_spice\nVenus Climate Orbiter\n4\n1.7\n2010-05-21\n2022-01-01\n\n\nvex\nvex-e_v-spice-6-v2.0/vexsp_2000\nVenus Express\n3\n5.0\n2005-11-09\n2015-02-06\n\n\nvo\nvo1_vo2-m-spice-6-v1.0/vosp_1000\nViking Orbiter\n3\n0.1\n1976-06-16\n1980-07-30\n\n\n\n\n\n\n\nTo receive this dataframe:\nfrom planetarypy.spice.kernels import datasets\nSome validation helpers:\n\nsource\n\nis_stop_valid\n\n is_stop_valid (mission:str, stop:astropy.time.core.Time)\n\n\n\n\n\nType\nDetails\n\n\n\n\nmission\nstr\nmission shorthand label of datasets dataframe\n\n\nstop\nTime\nstop time in astropy.Time format\n\n\n\n\nsource\n\n\nis_start_valid\n\n is_start_valid (mission:str, start:astropy.time.core.Time)\n\n\n\n\n\nType\nDetails\n\n\n\n\nmission\nstr\nmission shorthand label of datasets dataframe\n\n\nstart\nTime\nstart time in astropy.Time format\n\n\n\n\nassert is_start_valid(\"cassini\", Time(\"1998-01-01\")) is True\nassert is_start_valid(\"cassini\", Time(\"1997-01-01\")) is False\nassert is_stop_valid(\"cassini\", \"2017-01-01\") is True\nassert is_stop_valid(\"cassini\", \"2018-01-01\") is False\n\nNow we build a management class for wrapping the Perl script available at below’s URL for accessing subsets of these datasets.\nFirst, the basic URLs we will use:\nThe Perl script subsetds.pl (the name at the end of the BASE_URL) requires as input:\n\nthe dataset name\nstart and stop of the time interval\na constant named “Subset” to identify the action for this Perl script\n\nWe can assemble these parameters into a payload dictionary for the requests.get call and we manage different potential actions on the zipfile with a Subsetter class, that only requires the mission identifier, start and stop as parameters.\n/home/runner/micromamba/envs/my-env/lib/python3.11/site-packages/fastcore/docscrape.py:225: UserWarning: Unknown section Attributes\n else: warn(msg)\n\nsource\n\n\nSubsetter\n\n Subsetter (mission:str, start:str, stop=None, save_location=None)\n\nClass to manage retrieving subset SPICE kernel lists\n\n\n\n\n\n\n\n\n\n\nType\nDefault\nDetails\n\n\n\n\nmission\nstr\n\nmission shorthand in datasets dataframe\n\n\nstart\nstr\n\nstart time in either ISO or yyyy-jjj format\n\n\nstop\nNoneType\nNone\nstop time in either ISO or yyyy-jjj format\n\n\nsave_location\nNoneType\nNone\noverwrite default storing in planetarpy archive\n\n\n\n\nsource\n\n\ndownload_one_url\n\n download_one_url (url, local_path, overwrite:bool=False)\n\n\nsubset = Subsetter(\"cassini\", \"2014-270\")\n\n\nsubset.kernel_names\n\n['ck/14001_15001pa_gapfill_v14.bc',\n 'ck/14212_14279py_as_flown.bc',\n 'ck/14268_14273ra.bc',\n 'ck/cas_cda_20150318.bc',\n 'ck/cas_lemms_05109_20001_v2.bc',\n 'fk/cas_dyn_v03.tf',\n 'fk/cas_mimi_v202.tf',\n 'fk/cas_rocks_v18.tf',\n 'fk/cas_v41.tf',\n 'ik/cas_caps_v03.ti',\n 'ik/cas_cda_v01.ti',\n 'ik/cas_cirs_v09.ti',\n 'ik/cas_inms_v02.ti',\n 'ik/cas_iss_v10.ti',\n 'ik/cas_mag_v01.ti',\n 'ik/cas_mimi_v11.ti',\n 'ik/cas_radar_v11.ti',\n 'ik/cas_rpws_v01.ti',\n 'ik/cas_rss_v03.ti',\n 'ik/cas_sru_v02.ti',\n 'ik/cas_uvis_v06.ti',\n 'ik/cas_vims_v06.ti',\n 'lsk/naif0012.tls',\n 'pck/pck00010.tpc',\n 'sclk/cas00172.tsc',\n 'spk/140809BP_IRRE_00256_25017.bsp',\n 'spk/150122R_SCPSE_14251_14283.bsp',\n 'spk/180927AP_RE_90165_18018.bsp']\n\n\n\n# this should fail:\ndef _failing():\n Subsetter(\"cassini\", \"2019-01-01\")\n\n\ntest_fail(_failing, contains=\"start/stop\")\n\n\nsubset = Subsetter(\"cassini\", \"2011-02-13\", \"2011-02-14\")\n\n\nsubset.urls_file\n\n'urls_cosp_1000_110213_110214.txt'\n\n\n\nsubset.metakernel_file\n\n'cas_2011_v17_110213_110214.tm'\n\n\n\nsource\n\n\nSubsetter.kernel_names\n\n Subsetter.kernel_names ()\n\nReturn list of names of kernels for the given time range.\n\nsubset.kernel_names\n\n['ck/11001_12001pa_gapfill_v14.bc',\n 'ck/11017_11066py_as_flown.bc',\n 'ck/11044_11049ra.bc',\n 'ck/cas_cda_20120517.bc',\n 'ck/cas_lemms_05109_20001_v2.bc',\n 'fk/cas_dyn_v03.tf',\n 'fk/cas_mimi_v202.tf',\n 'fk/cas_rocks_v18.tf',\n 'fk/cas_v41.tf',\n 'ik/cas_caps_v03.ti',\n 'ik/cas_cda_v01.ti',\n 'ik/cas_cirs_v09.ti',\n 'ik/cas_inms_v02.ti',\n 'ik/cas_iss_v10.ti',\n 'ik/cas_mag_v01.ti',\n 'ik/cas_mimi_v11.ti',\n 'ik/cas_radar_v11.ti',\n 'ik/cas_rpws_v01.ti',\n 'ik/cas_rss_v03.ti',\n 'ik/cas_sru_v02.ti',\n 'ik/cas_uvis_v06.ti',\n 'ik/cas_vims_v06.ti',\n 'lsk/naif0012.tls',\n 'pck/pck00010.tpc',\n 'sclk/cas00172.tsc',\n 'spk/110504R_SCPSE_11041_11093.bsp',\n 'spk/140809BP_IRRE_00256_25017.bsp',\n 'spk/180927AP_RE_90165_18018.bsp']\n\n\n\nsubset.kernel_urls\n\n['https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/ck/11001_12001pa_gapfill_v14.bc',\n 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/ck/11017_11066py_as_flown.bc',\n 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/ck/11044_11049ra.bc',\n 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/ck/cas_cda_20120517.bc',\n 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/ck/cas_lemms_05109_20001_v2.bc',\n 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/fk/cas_dyn_v03.tf',\n 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/fk/cas_mimi_v202.tf',\n 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/fk/cas_rocks_v18.tf',\n 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/fk/cas_v41.tf',\n 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/ik/cas_caps_v03.ti',\n 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/ik/cas_cda_v01.ti',\n 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/ik/cas_cirs_v09.ti',\n 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/ik/cas_inms_v02.ti',\n 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/ik/cas_iss_v10.ti',\n 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/ik/cas_mag_v01.ti',\n 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/ik/cas_mimi_v11.ti',\n 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/ik/cas_radar_v11.ti',\n 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/ik/cas_rpws_v01.ti',\n 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/ik/cas_rss_v03.ti',\n 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/ik/cas_sru_v02.ti',\n 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/ik/cas_uvis_v06.ti',\n 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/ik/cas_vims_v06.ti',\n 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/lsk/naif0012.tls',\n 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/pck/pck00010.tpc',\n 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/sclk/cas00172.tsc',\n 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/spk/110504R_SCPSE_11041_11093.bsp',\n 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/spk/140809BP_IRRE_00256_25017.bsp',\n 'https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/spk/180927AP_RE_90165_18018.bsp']\n\n\n\nsource\n\n\nSubsetter.get_local_path\n\n Subsetter.get_local_path (url)\n\nCalculate local storage path from Kernel URL, using save_location if given.\nIf self.save_location is None, the planetarypy archive is being used.\n\n\n\n\n\n\n\n\n\nType\nDetails\n\n\n\n\nurl\n\nkernel url to determine local storage path\n\n\nReturns\nPath\nfull local path where kernel in URL will be stored\n\n\n\n\nsubset.get_local_path(subset.kernel_urls[0])\n\nPath('/home/ayek72/mnt/slowdata/planetarypy/spice_kernels/cassini/ck/11001_12001pa_gapfill_v14.bc')\n\n\n\nsubset.save_location = Path(\".\")\n\n\nsubset.get_local_path(subset.kernel_urls[0])\n\nPath('ck/11001_12001pa_gapfill_v14.bc')\n\n\n\nsource\n\n\nSubsetter.download_kernels\n\n Subsetter.download_kernels (overwrite:bool=False,\n non_blocking:bool=False, quiet:bool=False)\n\n\n\n\n\n\n\n\n\n\n\nType\nDefault\nDetails\n\n\n\n\noverwrite\nbool\nFalse\nswitch to control if kernels should be downloaded over existing ones\n\n\nnon_blocking\nbool\nFalse\n\n\n\nquiet\nbool\nFalse\n\n\n\n\n\n# reset save_location to prevent additional download\nsubset.save_location = None\n\n\nsubset.download_kernels()\n\n\n\n\nck 11001_12001pa_gapfill_v14.bc locally available.\nck 11017_11066py_as_flown.bc locally available.\nck 11044_11049ra.bc locally available.\nck cas_cda_20120517.bc locally available.\nck cas_lemms_05109_20001_v2.bc locally available.\nfk cas_dyn_v03.tf locally available.\nfk cas_mimi_v202.tf locally available.\nfk cas_rocks_v18.tf locally available.\nfk cas_v41.tf locally available.\nik cas_caps_v03.ti locally available.\nik cas_cda_v01.ti locally available.\nik cas_cirs_v09.ti locally available.\nik cas_inms_v02.ti locally available.\nik cas_iss_v10.ti locally available.\nik cas_mag_v01.ti locally available.\nik cas_mimi_v11.ti locally available.\nik cas_radar_v11.ti locally available.\nik cas_rpws_v01.ti locally available.\nik cas_rss_v03.ti locally available.\nik cas_sru_v02.ti locally available.\nik cas_uvis_v06.ti locally available.\nik cas_vims_v06.ti locally available.\nlsk naif0012.tls locally available.\npck pck00010.tpc locally available.\nsclk cas00172.tsc locally available.\nspk 110504R_SCPSE_11041_11093.bsp locally available.\nspk 140809BP_IRRE_00256_25017.bsp locally available.\nspk 180927AP_RE_90165_18018.bsp locally available.\n\n\n\nsubset.download_kernels(non_blocking=True)\n\n\n\n\nck 11001_12001pa_gapfill_v14.bc locally available.\nck 11017_11066py_as_flown.bc locally available.\nck 11044_11049ra.bc locally available.\nck cas_cda_20120517.bc locally available.\nck cas_lemms_05109_20001_v2.bc locally available.\nfk cas_dyn_v03.tf locally available.\nfk cas_mimi_v202.tf locally available.\nfk cas_rocks_v18.tf locally available.\nfk cas_v41.tf locally available.\nik cas_caps_v03.ti locally available.\nik cas_cda_v01.ti locally available.\nik cas_cirs_v09.ti locally available.\nik cas_inms_v02.ti locally available.\nik cas_iss_v10.ti locally available.\nik cas_mag_v01.ti locally available.\nik cas_mimi_v11.ti locally available.\nik cas_radar_v11.ti locally available.\nik cas_rpws_v01.ti locally available.\nik cas_rss_v03.ti locally available.\nik cas_sru_v02.ti locally available.\nik cas_uvis_v06.ti locally available.\nik cas_vims_v06.ti locally available.\nlsk naif0012.tls locally available.\npck pck00010.tpc locally available.\nsclk cas00172.tsc locally available.\nspk 110504R_SCPSE_11041_11093.bsp locally available.\nspk 140809BP_IRRE_00256_25017.bsp locally available.\nspk 180927AP_RE_90165_18018.bsp locally available.\n\n\n[]\n\n\n\nsource\n\n\nSubsetter.get_metakernel\n\n Subsetter.get_metakernel ()\n\nGet metakernel file from NAIF and adapt path to match local storage.\nUse save_location if given, otherwise planetarypy archive.\n\nmkpath = subset.get_metakernel()\nmkpath\n\nPath('/home/ayek72/mnt/slowdata/planetarypy/spice_kernels/cassini/cas_2011_v17_110213_110214.tm')\n\n\n\n!cat {mkpath}\n\nKPL/MK\n\n This meta-kernel lists a subset of kernels from the meta-kernel\n cas_2011_v17.tm provided in the CO-S/J/E/V-SPICE-6-V1.0 SPICE PDS3 archive,\n covering the whole or a part of the customer requested time period\n from 2011-02-13T00:00:00.000 to 2011-02-14T00:00:00.000.\n\n The documentation describing these kernels can be found in the\n complete CO-S/J/E/V-SPICE-6-V1.0 SPICE PDS3 archive available at this URL\n\n https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000\n\n To use this meta-kernel users may need to modify the value of the\n PATH_VALUES keyword to point to the actual location of the archive's\n ``data'' directory on their system. Replacing ``/'' with ``\\''\n and converting line terminators to the format native to the user's\n system may also be required if this meta-kernel is to be used on a\n non-UNIX workstation.\n\n This meta-kernel was created by the NAIF node's SPICE PDS archive\n subsetting service version 2.1 on Mon Jun 19 08:13:34 PDT 2023.\n\n \n \\begindata\n \n PATH_VALUES = (\n '/home/ayek72/mnt/slowdata/planetarypy/spice_kernels/cassini'\n )\n \n PATH_SYMBOLS = (\n 'KERNELS'\n )\n \n KERNELS_TO_LOAD = (\n '$KERNELS/lsk/naif0012.tls'\n '$KERNELS/pck/pck00010.tpc'\n '$KERNELS/fk/cas_rocks_v18.tf'\n '$KERNELS/fk/cas_mimi_v202.tf'\n '$KERNELS/fk/cas_dyn_v03.tf'\n '$KERNELS/fk/cas_v41.tf'\n '$KERNELS/ik/cas_caps_v03.ti'\n '$KERNELS/ik/cas_cda_v01.ti'\n '$KERNELS/ik/cas_cirs_v09.ti'\n '$KERNELS/ik/cas_inms_v02.ti'\n '$KERNELS/ik/cas_iss_v10.ti'\n '$KERNELS/ik/cas_mag_v01.ti'\n '$KERNELS/ik/cas_mimi_v11.ti'\n '$KERNELS/ik/cas_radar_v11.ti'\n '$KERNELS/ik/cas_rpws_v01.ti'\n '$KERNELS/ik/cas_rss_v03.ti'\n '$KERNELS/ik/cas_sru_v02.ti'\n '$KERNELS/ik/cas_uvis_v06.ti'\n '$KERNELS/ik/cas_vims_v06.ti'\n '$KERNELS/sclk/cas00172.tsc'\n '$KERNELS/spk/180927AP_RE_90165_18018.bsp'\n '$KERNELS/spk/140809BP_IRRE_00256_25017.bsp'\n '$KERNELS/spk/110504R_SCPSE_11041_11093.bsp'\n '$KERNELS/ck/11001_12001pa_gapfill_v14.bc'\n '$KERNELS/ck/11017_11066py_as_flown.bc'\n '$KERNELS/ck/11044_11049ra.bc'\n '$KERNELS/ck/cas_cda_20120517.bc'\n '$KERNELS/ck/cas_lemms_05109_20001_v2.bc'\n )\n \n \\begintext\n \n\n\n\nLoading the metakernel works! :\n\nspice.furnsh(str(mkpath))\n\nOr, with given save_location:\n\nsubset.save_location = Path(\".\")\nmkpath = subset.get_metakernel()\nmkpath\n\nPath('cas_2011_v17_110213_110214.tm')\n\n\nThe metakernel is correctly adapted, however for these tests, I didn’t download the kernels again\n\n!cat {mkpath}\n\nKPL/MK\n\n This meta-kernel lists a subset of kernels from the meta-kernel\n cas_2011_v17.tm provided in the CO-S/J/E/V-SPICE-6-V1.0 SPICE PDS3 archive,\n covering the whole or a part of the customer requested time period\n from 2011-02-13T00:00:00.000 to 2011-02-14T00:00:00.000.\n\n The documentation describing these kernels can be found in the\n complete CO-S/J/E/V-SPICE-6-V1.0 SPICE PDS3 archive available at this URL\n\n https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000\n\n To use this meta-kernel users may need to modify the value of the\n PATH_VALUES keyword to point to the actual location of the archive's\n ``data'' directory on their system. Replacing ``/'' with ``\\''\n and converting line terminators to the format native to the user's\n system may also be required if this meta-kernel is to be used on a\n non-UNIX workstation.\n\n This meta-kernel was created by the NAIF node's SPICE PDS archive\n subsetting service version 2.1 on Mon Jun 19 08:13:34 PDT 2023.\n\n \n \\begindata\n \n PATH_VALUES = (\n '.'\n )\n \n PATH_SYMBOLS = (\n 'KERNELS'\n )\n \n KERNELS_TO_LOAD = (\n '$KERNELS/lsk/naif0012.tls'\n '$KERNELS/pck/pck00010.tpc'\n '$KERNELS/fk/cas_rocks_v18.tf'\n '$KERNELS/fk/cas_mimi_v202.tf'\n '$KERNELS/fk/cas_dyn_v03.tf'\n '$KERNELS/fk/cas_v41.tf'\n '$KERNELS/ik/cas_caps_v03.ti'\n '$KERNELS/ik/cas_cda_v01.ti'\n '$KERNELS/ik/cas_cirs_v09.ti'\n '$KERNELS/ik/cas_inms_v02.ti'\n '$KERNELS/ik/cas_iss_v10.ti'\n '$KERNELS/ik/cas_mag_v01.ti'\n '$KERNELS/ik/cas_mimi_v11.ti'\n '$KERNELS/ik/cas_radar_v11.ti'\n '$KERNELS/ik/cas_rpws_v01.ti'\n '$KERNELS/ik/cas_rss_v03.ti'\n '$KERNELS/ik/cas_sru_v02.ti'\n '$KERNELS/ik/cas_uvis_v06.ti'\n '$KERNELS/ik/cas_vims_v06.ti'\n '$KERNELS/sclk/cas00172.tsc'\n '$KERNELS/spk/180927AP_RE_90165_18018.bsp'\n '$KERNELS/spk/140809BP_IRRE_00256_25017.bsp'\n '$KERNELS/spk/110504R_SCPSE_11041_11093.bsp'\n '$KERNELS/ck/11001_12001pa_gapfill_v14.bc'\n '$KERNELS/ck/11017_11066py_as_flown.bc'\n '$KERNELS/ck/11044_11049ra.bc'\n '$KERNELS/ck/cas_cda_20120517.bc'\n '$KERNELS/ck/cas_lemms_05109_20001_v2.bc'\n )\n \n \\begintext" + }, + { + "objectID": "api/spice.kernels.html#user-functions", + "href": "api/spice.kernels.html#user-functions", + "title": "SPICE Kernels", + "section": "User functions", + "text": "User functions\n\nsource\n\nget_metakernel_and_files\n\n get_metakernel_and_files (mission:str, start:str, stop:str,\n save_location:str=None, quiet:bool=False)\n\nFor a given mission and start/stop times, download the kernels and get metakernel path\n\n\n\n\n\n\n\n\n\n\nType\nDefault\nDetails\n\n\n\n\nmission\nstr\n\nmission shorthand from datasets dataframe\n\n\nstart\nstr\n\nstart time as iso-string, or yyyy-jjj\n\n\nstop\nstr\n\nstop time as iso-string or yyyy-jjj\n\n\nsave_location\nstr\nNone\noverride storage into planetarypy archive\n\n\nquiet\nbool\nFalse\nsuppress kernel-wise feedback\n\n\nReturns\nPath\n\npathlib.Path to metakernel file with corrected data path.\n\n\n\n\nmkpath = get_metakernel_and_files(\"cassini\", \"2011-02-13\", \"2011-02-14\")\nmkpath\n\n/Users/maye/mambaforge/envs/py39/lib/python3.9/site-packages/distributed/node.py:182: UserWarning: Port 8787 is already in use.\nPerhaps you already have a cluster running?\nHosting the HTTP server on port 57624 instead\n warnings.warn(\n\n\n\n\n\nck 11001_12001pa_gapfill_v14.bc locally available.\nck 11017_11066py_as_flown.bc locally available.\nck 11044_11049ra.bc locally available.\nck cas_cda_20120517.bc locally available.\nck cas_lemms_05109_20001_v2.bc locally available.\nfk cas_dyn_v03.tf locally available.\nfk cas_mimi_v202.tf locally available.\nfk cas_rocks_v18.tf locally available.\nfk cas_v41.tf locally available.\nik cas_caps_v03.ti locally available.\nik cas_cda_v01.ti locally available.\nik cas_cirs_v09.ti locally available.\nik cas_inms_v02.ti locally available.\nik cas_iss_v10.ti locally available.\nik cas_mag_v01.ti locally available.\nik cas_mimi_v11.ti locally available.\nik cas_radar_v11.ti locally available.\nik cas_rpws_v01.ti locally available.\nik cas_rss_v03.ti locally available.\nik cas_sru_v02.ti locally available.\nik cas_uvis_v06.ti locally available.\nik cas_vims_v06.ti locally available.\nlsk naif0012.tls locally available.\npck pck00010.tpc locally available.\nsclk cas00172.tsc locally available.\nspk 110504R_SCPSE_11041_11093.bsp locally available.\nspk 140809BP_IRRE_00256_25017.bsp locally available.\nspk 180927AP_RE_90165_18018.bsp locally available.\n\n\nPath('/Users/maye/planetarypy_data/spice_kernels/cassini/cas_2011_v17_110213_110214.tm')\n\n\n\nsource\n\n\nlist_kernels_for_day\n\n list_kernels_for_day (mission:str, start:str, stop:str='')\n\n\n\n\n\nType\nDefault\nDetails\n\n\n\n\nmission\nstr\n\nmission shorthand from datasets dataframe\n\n\nstart\nstr\n\nstart time as iso-string, or yyyy-jjj\n\n\nstop\nstr\n\nstop time as iso-string or yyyy-jjj\n\n\nReturns\nlist\n\nlist of kernel names\n\n\n\n\nlist_kernels_for_day(\"mro\", \"2015-02-13\")\n\n['ck/mro_crm_psp_150201_150228.bc',\n 'ck/mro_hga_psp_150210_150216_v2.bc',\n 'ck/mro_mcs_psp_150201_150228.bc',\n 'ck/mro_sa_psp_150210_150216_v2.bc',\n 'ck/mro_sc_psp_150210_150216_v2.bc',\n 'fk/mro_v16.tf',\n 'ik/mro_crism_v10.ti',\n 'ik/mro_ctx_v11.ti',\n 'ik/mro_hirise_v12.ti',\n 'ik/mro_marci_v10.ti',\n 'ik/mro_mcs_v10.ti',\n 'ik/mro_onc_v10.ti',\n 'lsk/naif0012.tls',\n 'pck/pck00008.tpc',\n 'sclk/mro_sclkscet_00095_65536.tsc',\n 'spk/de421.bsp',\n 'spk/mar097.bsp',\n 'spk/mro_psp34.bsp',\n 'spk/mro_psp34_ssd_mro95a.bsp',\n 'spk/mro_struct_v10.bsp']\n\n\n\n# this always takes much longer than other requests!\nlist_kernels_for_day(\"maven\", \"2017-01-01\")\n\n['ck/mvn_app_rel_161226_170101_v01.bc',\n 'ck/mvn_app_rel_170102_170108_v01.bc',\n 'ck/mvn_iuvs_rem_170101_170331_v03.bc',\n 'ck/mvn_sc_rel_161226_170101_v01.bc',\n 'ck/mvn_sc_rel_170102_170108_v02.bc',\n 'ck/mvn_swea_nom_131118_300101_v02.bc',\n 'fk/maven_v09.tf',\n 'ik/maven_ant_v10.ti',\n 'ik/maven_euv_v10.ti',\n 'ik/maven_iuvs_v11.ti',\n 'ik/maven_ngims_v10.ti',\n 'ik/maven_sep_v12.ti',\n 'ik/maven_static_v11.ti',\n 'ik/maven_swea_v11.ti',\n 'ik/maven_swia_v10.ti',\n 'lsk/naif0012.tls',\n 'pck/pck00010.tpc',\n 'sclk/mvn_sclkscet_00072.tsc',\n 'spk/de430s.bsp',\n 'spk/mar097s.bsp',\n 'spk/maven_orb_rec_170101_170401_v1.bsp',\n 'spk/maven_struct_v01.bsp']\n\n\n\n# this always takes much longer than other requests!\nlist_kernels_for_day(\"orex\", \"2018-11-30\")\n\n['ck/orx_sa_rel_181126_181202_v01.bc',\n 'ck/orx_sc_rel_181126_181202_v01.bc',\n 'ck/orx_struct_mapcam_v01.bc',\n 'ck/orx_struct_polycam_v01.bc',\n 'fk/orx_shape_v03.tf',\n 'fk/orx_v14.tf',\n 'ik/orx_lidar_v00.ti',\n 'ik/orx_navcam_v02.ti',\n 'ik/orx_ocams_v07.ti',\n 'ik/orx_ola_v01.ti',\n 'ik/orx_otes_v00.ti',\n 'ik/orx_ovirs_v00.ti',\n 'ik/orx_rexis_v01.ti',\n 'ik/orx_stowcam_v00.ti',\n 'ik/orx_struct_v00.ti',\n 'lsk/naif0012.tls',\n 'pck/bennu_v17.tpc',\n 'pck/pck00010.tpc',\n 'sclk/orx_sclkscet_00074.tsc',\n 'spk/bennu_refdrmc_v1.bsp',\n 'spk/de424.bsp',\n 'spk/orx_180301_181201_180921_od044_v1.bsp',\n 'spk/orx_180801_190302_181218_od077_v1.bsp',\n 'spk/orx_181203_190302_190104_od085_v1.bsp',\n 'spk/orx_struct_v04.bsp']\n\n\n\ndef _test_mission_kernels_available(mission):\n print(\"Doing\", mission)\n start = datasets.at[mission, \"Start Time\"]\n end = datasets.at[mission, \"Stop Time\"]\n half = Time(start) + (Time(end) - Time(start)) / 2\n print(\"Half time:\", half)\n try:\n found = list_kernels_for_day(mission, half)\n except IndexError:\n print(\"Problem with\", mission)\n else:\n print(f\"Found {len(found)} kernels for {mission}\")\n\nfor mission in datasets.index:\n _test_mission_kernels_available(mission)\n\nDoing bc\nHalf time: 2020-11-25 00:00:00.000\nFound 41 kernels for bc\nDoing cassini\nHalf time: 2007-09-30 12:00:01.000\nFound 32 kernels for cassini\nDoing clementine\nHalf time: 1994-03-17 12:00:00.000\nFound 19 kernels for clementine\nDoing dart\nHalf time: 2035-12-06 00:00:00.000\nFound 14 kernels for dart\nDoing dawn\nHalf time: 2013-04-14 00:00:00.000\nFound 21 kernels for dawn\nDoing di\nHalf time: 2005-04-26 12:00:00.000\nFound 16 kernels for di\nDoing ds1\nHalf time: 2000-05-21 11:59:59.500\nFound 11 kernels for ds1\nDoing epoxi\nHalf time: 2008-05-27 00:00:00.000\nFound 12 kernels for epoxi\nDoing em16\nHalf time: 2019-08-07 23:59:59.500\nFound 27 kernels for em16\nDoing grail\nHalf time: 2012-04-29 00:00:00.500\nFound 20 kernels for grail\nDoing hayabusa\nHalf time: 2005-10-15 12:00:00.000\nFound 15 kernels for hayabusa\nDoing insight\nHalf time: 2020-08-24 12:00:00.000\nFound 21 kernels for insight\nDoing juno\nHalf time: 2017-02-08 23:59:58.500\nFound 25 kernels for juno\nDoing ladee\nHalf time: 2031-11-04 11:59:59.000\nFound 12 kernels for ladee\nDoing lro\nHalf time: 2016-04-30 23:59:59.500\nFound 24 kernels for lro\nDoing maven\nHalf time: 2018-07-25 11:59:59.000\nFound 20 kernels for maven\nDoing opportunity\nHalf time: 2010-12-23 00:00:00.500\nFound 23 kernels for opportunity\nDoing spirit\nHalf time: 2006-11-20 12:00:00.000\nFound 24 kernels for spirit\nDoing messenger\nHalf time: 2009-12-15 23:59:59.500\nFound 18 kernels for messenger\nDoing mars2020\nHalf time: 2021-10-13 12:00:00.000\nFound 17 kernels for mars2020\nDoing mex\nHalf time: 2013-03-01 11:59:59.500\nFound 39 kernels for mex\nDoing mgs\nHalf time: 2001-11-03 23:59:59.500\nFound 20 kernels for mgs\nDoing ody\nHalf time: 2012-01-03 12:00:00.500\nFound 14 kernels for ody\nDoing mro\nHalf time: 2014-06-06 11:59:59.500\nFound 20 kernels for mro\nDoing msl\nHalf time: 2017-05-16 23:59:58.500\nFound 50 kernels for msl\nDoing near\nHalf time: 1998-10-14 12:00:00.000\nFound 15 kernels for near\nDoing nh\nHalf time: 2013-01-08 12:00:00.000\nFound 28 kernels for nh\nDoing orex\nHalf time: 2018-11-30 23:59:59.500\n\n\n warnings.warn('ERFA function \"{}\" yielded {}'.format(func_name, wmsg),\n warnings.warn('ERFA function \"{}\" yielded {}'.format(func_name, wmsg),\n warnings.warn('ERFA function \"{}\" yielded {}'.format(func_name, wmsg),\n warnings.warn('ERFA function \"{}\" yielded {}'.format(func_name, wmsg),\n\n\nOSError: SPICE Server request returned status code: {r.status_code}\n\n\n\nNOTE: Any ErfaWarnings above are caused by the LADEE mission using a kernel up to 2050, and the astropy.Time module warns about potential precicision issues regarding unknown leapseconds that will be put in in the future.\n\n\n\nGeneric kernel management\nThere are a few generic kernels that are required for basic illumination calculations as supported by this package.\n\nsource\n\n\ndownload_generic_kernels\n\n download_generic_kernels (overwrite=False)\n\nDownload all kernels as required by generic_kernel_list.\n\ndownload_generic_kernels()\n\n\nsource\n\n\nload_generic_kernels\n\n load_generic_kernels ()\n\nLoad all kernels in generic_kernels list.\nLoads pure planetary bodies meta-kernel without spacecraft data.\nDownloads any missing generic kernels.\n\nspice.kclear()\n\n\nload_generic_kernels()\n\n\nsource\n\n\nshow_loaded_kernels\n\n show_loaded_kernels ()\n\nPrint overview of loaded kernels.\n\nshow_loaded_kernels()\n\n\nfrom nbdev import nbdev_export\n\nnbdev_export()" + }, + { + "objectID": "tutorials/pdw2023_demo.html", + "href": "tutorials/pdw2023_demo.html", + "title": "Demo of PlanetaryPy", + "section": "", + "text": "import planetarypy as plpy\nplpy.__version__\n\n'0.30.0'\nfrom planetarypy.pds.apps import get_index, find_indexes\n!head -n 50 $HOME/.planetarypy_config.toml\n\nstorage_root = \"/home/ayek72/mnt/slowdata/planetarypy\"\n\n[missions.cassini.iss.indexes.index]\n# 'index' is the ID of the originally delivered index\n# inventory, moon_summary, ring_summary, and saturn_summary are other indexes produced\n# by the Rings-Moons Systems PDS node\nurl = \"https://pds-rings.seti.org/holdings/metadata/COISS_2xxx/COISS_2999/COISS_2999_index.lbl\"\ntimestamp = \"2021-02-21T15:55:27\"\n\n[missions.cassini.iss.indexes.inventory]\nurl = \"https://pds-rings.seti.org/holdings/metadata/COISS_2xxx/COISS_2999/COISS_2999_inventory.lbl\"\n\n[missions.cassini.iss.indexes.moon_summary]\nurl = \"https://pds-rings.seti.org/holdings/metadata/COISS_2xxx/COISS_2999/COISS_2999_moon_summary.lbl\"\ntimestamp = \"2019-06-08T16:28:22\"\n\n[missions.cassini.iss.indexes.ring_summary]\nurl = \"https://pds-rings.seti.org/holdings/metadata/COISS_2xxx/COISS_2999/COISS_2999_ring_summary.lbl\"\ntimestamp = \"2022-08-08T11:54:51.140376\"\n\n[missions.cassini.iss.indexes.saturn_summary]\nurl = \"https://pds-rings.seti.org/holdings/metadata/COISS_2xxx/COISS_2999/COISS_2999_saturn_summary.lbl\"\ntimestamp = \"2022-12-21T18:10:29.248055\"\n\n\n[missions.cassini.uvis.indexes.index]\nurl = \"https://pds-rings.seti.org/holdings/metadata/COUVIS_0xxx/COUVIS_0999/COUVIS_0999_index.lbl\"\ntimestamp = \"2022-09-01T14:14:10.014705\"\n\n[missions.cassini.uvis.indexes.moon_summary]\nurl = \"https://pds-rings.seti.org/holdings/metadata/COUVIS_0xxx/COUVIS_0999/COUVIS_0999_moon_summary.lbl\"\n\n[missions.cassini.uvis.indexes.ring_summary]\nurl = \"https://pds-rings.seti.org/holdings/metadata/COUVIS_0xxx/COUVIS_0999/COUVIS_0999_ring_summary.lbl\"\ntimestamp = \"2022-08-08T11:53:16.071844\"\n\n[missions.cassini.uvis.indexes.saturn_summary]\nurl = \"https://pds-rings.seti.org/holdings/metadata/COUVIS_0xxx/COUVIS_0999/COUVIS_0999_saturn_summary.lbl\"\n\n[missions.cassini.uvis.indexes.supplemental_index]\nurl = \"https://pds-rings.seti.org/holdings/metadata/COUVIS_0xxx/COUVIS_0999/COUVIS_0999_supplemental_index.lbl\"\n\n[missions.cassini.uvis.indexes.versions]\nurl = \"https://pds-rings.seti.org/holdings/metadata/COUVIS_0xxx/COUVIS_0999/COUVIS_0999_versions.lbl\"\n\n\n\n[missions.mro.hirise.indexes.dtm]\nurl = \"https://hirise-pds.lpl.arizona.edu/PDS/INDEX/DTMCUMINDEX.LBL\"\nfind_indexes(\"cassini.iss\")\n\n['index', 'inventory', 'moon_summary', 'ring_summary', 'saturn_summary']\nfind_indexes(\"cassini.uvis\")\n\n['index',\n 'moon_summary',\n 'ring_summary',\n 'saturn_summary',\n 'supplemental_index',\n 'versions']\ndf = get_index(\"cassini.iss.index\")\ndf.head()\n\n\n\n\n\n\n\n\nFILE_NAME\nFILE_SPECIFICATION_NAME\nVOLUME_ID\nANTIBLOOMING_STATE_FLAG\nBIAS_STRIP_MEAN\nCALIBRATION_LAMP_STATE_FLAG\nCOMMAND_FILE_NAME\nCOMMAND_SEQUENCE_NUMBER\nDARK_STRIP_MEAN\nDATA_CONVERSION_TYPE\n...\nTWIST_ANGLE\nTARGET_LIST\nUPPER_LEFT_LATITUDE\nUPPER_LEFT_LONGITUDE\nUPPER_RIGHT_LATITUDE\nUPPER_RIGHT_LONGITUDE\nDATA_SET_NAME\nINSTRUMENT_HOST_ID\nPRODUCT_TYPE\nSTANDARD_DATA_PRODUCT_ID\n\n\n\n\n0\nN1454725799_1.IMG\ndata/1454725799_1455008789/N1454725799_1.IMG\nCOISS_2001\nOFF\n14.869863\n<NA>\nOPNAV_848_3.ioi\n8\n0.0\n12BIT\n...\n89.513591\nS2_2004,HELENE,TELESTO,RHEA\n-100000000000000005366162204393472.0\n-100000000000000005366162204393472.0\n-100000000000000005366162204393472.0\n-100000000000000005366162204393472.0\nCASSINI ORBITER SATURN ISSNA/ISSWA 2 EDR VERSI...\nCO\nEDR\nISS_EDR\n\n\n1\nN1454726579_1.IMG\ndata/1454725799_1455008789/N1454726579_1.IMG\nCOISS_2001\nOFF\n14.860078\n<NA>\nOPNAV_864_3.ioi\n8\n0.0\n12BIT\n...\n89.647635\nTITAN\n-100000000000000005366162204393472.0\n-100000000000000005366162204393472.0\n-100000000000000005366162204393472.0\n-100000000000000005366162204393472.0\nCASSINI ORBITER SATURN ISSNA/ISSWA 2 EDR VERSI...\nCO\nEDR\nISS_EDR\n\n\n2\nN1454727359_1.IMG\ndata/1454725799_1455008789/N1454727359_1.IMG\nCOISS_2001\nOFF\n14.87867\n<NA>\nOPNAV_880_3.ioi\n8\n0.0\n12BIT\n...\n89.679084\nHYPERION\n-100000000000000005366162204393472.0\n-100000000000000005366162204393472.0\n-100000000000000005366162204393472.0\n-100000000000000005366162204393472.0\nCASSINI ORBITER SATURN ISSNA/ISSWA 2 EDR VERSI...\nCO\nEDR\nISS_EDR\n\n\n3\nN1454728139_1.IMG\ndata/1454725799_1455008789/N1454728139_1.IMG\nCOISS_2001\nOFF\n14.842465\n<NA>\nOPNAV_912_3.ioi\n8\n0.0\n12BIT\n...\n88.677516\nPHOEBE\n-100000000000000005366162204393472.0\n-100000000000000005366162204393472.0\n-100000000000000005366162204393472.0\n-100000000000000005366162204393472.0\nCASSINI ORBITER SATURN ISSNA/ISSWA 2 EDR VERSI...\nCO\nEDR\nISS_EDR\n\n\n4\nN1454728919_1.IMG\ndata/1454725799_1455008789/N1454728919_1.IMG\nCOISS_2001\nOFF\n14.86497\n<NA>\nOPNAV_896_3.ioi\n8\n0.0\n12BIT\n...\n89.79891\nIAPETUS\n-100000000000000005366162204393472.0\n-100000000000000005366162204393472.0\n-100000000000000005366162204393472.0\n-100000000000000005366162204393472.0\nCASSINI ORBITER SATURN ISSNA/ISSWA 2 EDR VERSI...\nCO\nEDR\nISS_EDR\n\n\n\n\n5 rows × 140 columns\ndf.columns\n\nIndex(['FILE_NAME', 'FILE_SPECIFICATION_NAME', 'VOLUME_ID',\n 'ANTIBLOOMING_STATE_FLAG', 'BIAS_STRIP_MEAN',\n 'CALIBRATION_LAMP_STATE_FLAG', 'COMMAND_FILE_NAME',\n 'COMMAND_SEQUENCE_NUMBER', 'DARK_STRIP_MEAN', 'DATA_CONVERSION_TYPE',\n ...\n 'TWIST_ANGLE', 'TARGET_LIST', 'UPPER_LEFT_LATITUDE',\n 'UPPER_LEFT_LONGITUDE', 'UPPER_RIGHT_LATITUDE', 'UPPER_RIGHT_LONGITUDE',\n 'DATA_SET_NAME', 'INSTRUMENT_HOST_ID', 'PRODUCT_TYPE',\n 'STANDARD_DATA_PRODUCT_ID'],\n dtype='object', length=140)\ndf.set_index(\"IMAGE_MID_TIME\").loc['20170914 00':'20170914 15']\n\n\n\n\n\n\n\n\nFILE_NAME\nFILE_SPECIFICATION_NAME\nVOLUME_ID\nANTIBLOOMING_STATE_FLAG\nBIAS_STRIP_MEAN\nCALIBRATION_LAMP_STATE_FLAG\nCOMMAND_FILE_NAME\nCOMMAND_SEQUENCE_NUMBER\nDARK_STRIP_MEAN\nDATA_CONVERSION_TYPE\n...\nTWIST_ANGLE\nTARGET_LIST\nUPPER_LEFT_LATITUDE\nUPPER_LEFT_LONGITUDE\nUPPER_RIGHT_LATITUDE\nUPPER_RIGHT_LONGITUDE\nDATA_SET_NAME\nINSTRUMENT_HOST_ID\nPRODUCT_TYPE\nSTANDARD_DATA_PRODUCT_ID\n\n\nIMAGE_MID_TIME\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n2017-09-14 13:26:59.927\nN1884091007_1.IMG\ndata/1884017637_1884113741/N1884091007_1.IMG\nCOISS_2116\nOFF\n21.611872\n<NA>\ntrigger_25245_3.ioi\n25245\n1.218444\n12BIT\n...\n4.868274\n<NA>\n-100000000000000005366162204393472.0\n-100000000000000005366162204393472.0\n-100000000000000005366162204393472.0\n-100000000000000005366162204393472.0\nCASSINI ORBITER SATURN ISSNA/ISSWA 2 EDR VERSI...\nCO\nEDR\nISS_EDR\n\n\n2017-09-14 13:31:18.910\nN1884091266_1.IMG\ndata/1884017637_1884113741/N1884091266_1.IMG\nCOISS_2116\nOFF\n21.594259\n<NA>\ntrigger_25245_3.ioi\n25245\n1.222236\n12BIT\n...\n4.812541\n<NA>\n-100000000000000005366162204393472.0\n-100000000000000005366162204393472.0\n-100000000000000005366162204393472.0\n-100000000000000005366162204393472.0\nCASSINI ORBITER SATURN ISSNA/ISSWA 2 EDR VERSI...\nCO\nEDR\nISS_EDR\n\n\n2017-09-14 13:35:41.908\nN1884091529_1.IMG\ndata/1884017637_1884113741/N1884091529_1.IMG\nCOISS_2116\nOFF\n21.87019\n<NA>\ntrigger_25245_3.ioi\n25245\n1.229574\n12BIT\n...\n4.77302\nDAPHNIS\n-100000000000000005366162204393472.0\n-100000000000000005366162204393472.0\n-100000000000000005366162204393472.0\n-100000000000000005366162204393472.0\nCASSINI ORBITER SATURN ISSNA/ISSWA 2 EDR VERSI...\nCO\nEDR\nISS_EDR\n\n\n2017-09-14 13:40:04.906\nN1884091792_1.IMG\ndata/1884017637_1884113741/N1884091792_1.IMG\nCOISS_2116\nOFF\n21.843445\n<NA>\ntrigger_25245_3.ioi\n25245\n1.254036\n12BIT\n...\n4.748047\n<NA>\n-100000000000000005366162204393472.0\n-100000000000000005366162204393472.0\n-100000000000000005366162204393472.0\n-100000000000000005366162204393472.0\nCASSINI ORBITER SATURN ISSNA/ISSWA 2 EDR VERSI...\nCO\nEDR\nISS_EDR\n\n\n2017-09-14 13:44:27.905\nN1884092055_1.IMG\ndata/1884017637_1884113741/N1884092055_1.IMG\nCOISS_2116\nOFF\n21.885845\n<NA>\ntrigger_25245_3.ioi\n25245\n1.263209\n12BIT\n...\n4.736484\n<NA>\n-100000000000000005366162204393472.0\n-100000000000000005366162204393472.0\n-100000000000000005366162204393472.0\n-100000000000000005366162204393472.0\nCASSINI ORBITER SATURN ISSNA/ISSWA 2 EDR VERSI...\nCO\nEDR\nISS_EDR\n\n\n2017-09-14 13:48:50.903\nN1884092318_1.IMG\ndata/1884017637_1884113741/N1884092318_1.IMG\nCOISS_2116\nOFF\n21.558872\n<NA>\ntrigger_25245_3.ioi\n25245\n1.260029\n12BIT\n...\n4.737905\n<NA>\n-100000000000000005366162204393472.0\n-100000000000000005366162204393472.0\n-100000000000000005366162204393472.0\n-100000000000000005366162204393472.0\nCASSINI ORBITER SATURN ISSNA/ISSWA 2 EDR VERSI...\nCO\nEDR\nISS_EDR\n\n\n2017-09-14 13:53:13.901\nN1884092581_1.IMG\ndata/1884017637_1884113741/N1884092581_1.IMG\nCOISS_2116\nOFF\n21.606491\n<NA>\ntrigger_25245_3.ioi\n25245\n1.248288\n12BIT\n...\n4.750201\n<NA>\n-100000000000000005366162204393472.0\n-100000000000000005366162204393472.0\n-100000000000000005366162204393472.0\n-100000000000000005366162204393472.0\nCASSINI ORBITER SATURN ISSNA/ISSWA 2 EDR VERSI...\nCO\nEDR\nISS_EDR\n\n\n\n\n7 rows × 139 columns" + }, + { + "objectID": "tutorials/pdw2023_demo.html#archived-kernels", + "href": "tutorials/pdw2023_demo.html#archived-kernels", + "title": "Demo of PlanetaryPy", + "section": "Archived kernels", + "text": "Archived kernels\n\nfrom planetarypy.spice import kernels\n\n\nkernels.datasets\n\n\n\n\n\n\n\n\npath\nMission Name\nPDS3 or PDS4\nData Size (GB)\nStart Time\nStop Time\n\n\nshorthand\n\n\n\n\n\n\n\n\n\n\nbc\nbc/bc_spice\nBepiColombo\n4\n2.3\n2018-10-20\n2023-06-21\n\n\ncassini\nco-s_j_e_v-spice-6-v1.0/cosp_1000\nCassini Orbiter\n3\n62.5\n1997-10-15\n2017-09-15\n\n\nclementine\nclem1-l-spice-6-v1.0/clsp_1000\nClementine\n3\n0.8\n1994-01-26\n1994-05-07\n\n\ndart\ndart/dart_spice\nDART\n4\n10.0\n2021-11-09\n2050-01-01\n\n\ndawn\ndawn-m_a-spice-6-v1.0/dawnsp_1000\nDAWN\n3\n86.4\n2007-09-27\n2018-10-31\n\n\ndi\ndi-c-spice-6-v1.0/disp_1000\nDeep Impact\n3\n0.7\n2005-01-12\n2005-08-09\n\n\nds1\nds1-a_c-spice-6-v1.0/ds1sp_1000\nDeep Space 1\n3\n0.9\n1998-10-24\n2001-12-18\n\n\nepoxi\ndif-c_e_x-spice-6-v1.0/epxsp_1000\nEPOXI\n3\n1.0\n2005-08-23\n2011-03-01\n\n\nem16\nem16/em16_spice\nExoMars TGO 2016\n4\n10.4\n2016-03-14\n2023-10-01\n\n\ngrail\ngrail-l-spice-6-v1.0/grlsp_1000\nGRAIL\n3\n4.3\n2011-09-10\n2012-12-17\n\n\nhayabusa\nhay-a-spice-6-v1.0/haysp_1000\nHayabusa\n3\n0.3\n2005-09-11\n2005-11-19\n\n\ninsight\ninsight/insight_spice\nInSight\n4\n0.9\n2018-05-05\n2022-12-15\n\n\njuno\njno-j_e_ss-spice-6-v1.0/jnosp_1000\nJUNO\n3\n48.2\n2011-08-05\n2023-04-08\n\n\nladee\nladee/ladee_spice\nLADEE\n4\n0.6\n2013-09-07\n2050-01-01\n\n\nlro\nlro-l-spice-6-v1.0/lrosp_1000\nLunar Reconnaissance Orbiter\n3\n616.9\n2009-06-18\n2023-09-15\n\n\nmaven\nmaven/maven_spice\nMAVEN\n4\n56.6\n2013-11-18\n2023-10-01\n\n\nopportunity\nmer1-m-spice-6-v1.0/mer1sp_1000\nMER 1 (Opportunity)\n3\n4.1\n2003-07-07\n2018-06-10\n\n\nspirit\nmer2-m-spice-6-v1.0/mer2sp_1000\nMER 2 (Spirit)\n3\n2.6\n2003-06-10\n2010-05-03\n\n\nmessenger\nmess-e_v_h-spice-6-v1.0/messsp_1000\nMESSENGER\n3\n44.8\n2004-08-03\n2015-04-30\n\n\nmars2020\nmars2020/mars2020_spice\nMars 2020\n4\n0.6\n2020-07-30\n2023-08-31\n\n\nmex\nmex-e_m-spice-6-v2.0/mexsp_2000\nMars Express\n3\n10.6\n2003-06-02\n2023-08-31\n\n\nmgs\nmgs-m-spice-6-v1.0/mgsp_1000\nMars Global Surveyor\n3\n15.4\n1996-11-06\n2006-11-02\n\n\nody\nody-m-spice-6-v1.0/odsp_1000\nMars Odyssey\n3\n35.2\n2001-04-07\n2023-07-01\n\n\nmro\nmro-m-spice-6-v1.0/mrosp_1000\nMars Reconnaissance Orbiter\n3\n324.7\n2005-08-12\n2023-10-01\n\n\nmsl\nmsl-m-spice-6-v1.0/mslsp_1000\nMars Science Laboratory\n3\n0.6\n2011-11-26\n2023-07-29\n\n\nnear\nnear-a-spice-6-v1.0/nearsp_1000\nNEAR\n3\n2.4\n1996-05-30\n2001-02-28\n\n\nnh\nnh-j_p_ss-spice-6-v1.0/nhsp_1000\nNew Horizons\n3\n1.6\n2006-01-19\n2019-12-30\n\n\norex\norex/orex_spice\nOSIRIS-REx\n4\n424.7\n2016-09-08\n2023-10-02\n\n\nrosetta\nro_rl-e_m_a_c-spice-6-v1.0/rossp_1000\nRosetta\n3\n5.9\n2004-03-02\n2017-01-01\n\n\nstardust\nsdu-c-spice-6-v1.0/sdsp_1000\nStardust\n3\n1.9\n1999-02-07\n2011-05-01\n\n\nvenus_climate_orbiter\nvco/vco_spice\nVenus Climate Orbiter\n4\n1.9\n2010-05-21\n2023-01-01\n\n\nvex\nvex-e_v-spice-6-v2.0/vexsp_2000\nVenus Express\n3\n5.0\n2005-11-09\n2015-02-06\n\n\nvo\nvo1_vo2-m-spice-6-v1.0/vosp_1000\nViking Orbiter\n3\n0.1\n1976-06-16\n1980-07-30\n\n\n\n\n\n\n\n\nkernels.list_kernels_for_day('bc', '2019-01-01')\n\n['ck/bc_mmo_sc_cruise_v01.bc',\n 'ck/bc_mpo_magboom_v01.bc',\n 'ck/bc_mtm_sc_cruise_v01.bc',\n 'fk/bc_dsk_surfaces_v03.tf',\n 'fk/bc_mmo_v13.tf',\n 'fk/bc_mpo_v34.tf',\n 'fk/bc_mtm_v12.tf',\n 'fk/bc_sci_v12.tf',\n 'fk/earth_topo_201023.tf',\n 'fk/earthstns_jaxa_20230905.tf',\n 'fk/estrack_v04.tf',\n 'fk/rssd0002.tf',\n 'ik/bc_mmo_mppe_v04.ti',\n 'ik/bc_mmo_msasi_v03.ti',\n 'ik/bc_mpo_aux_v01.ti',\n 'ik/bc_mpo_bela_v09.ti',\n 'ik/bc_mpo_mertis_v08.ti',\n 'ik/bc_mpo_mgns_v02.ti',\n 'ik/bc_mpo_mixs_v06.ti',\n 'ik/bc_mpo_phebus_v06.ti',\n 'ik/bc_mpo_serena_v08.ti',\n 'ik/bc_mpo_simbio-sys_v10.ti',\n 'ik/bc_mpo_sixs_v08.ti',\n 'ik/bc_mpo_str_v02.ti',\n 'ik/bc_mtm_mcam_v05.ti',\n 'lsk/naif0012.tls',\n 'pck/earth_000101_231220_230927.bpc',\n 'pck/gm_de431.tpc',\n 'pck/pck00011_bc_v00.tpc',\n 'sclk/bc_mmo_fict_20170228.tsc',\n 'sclk/bc_mpo_fict_20181127.tsc',\n 'sclk/bc_mpo_step_20230917.tsc',\n 'spk/bc_mmo_cruise_v01.bsp',\n 'spk/bc_mmo_struct_v01.bsp',\n 'spk/bc_mpo_cog_v03.bsp',\n 'spk/bc_mpo_struct_v09.bsp',\n 'spk/bc_mtm_cruise_v01.bsp',\n 'spk/bc_mtm_struct_v06.bsp',\n 'spk/bc_sci_v02.bsp',\n 'spk/de432s.bsp',\n 'spk/earthstns_itrf93_201023.bsp',\n 'spk/earthstns_jaxa_20230905.bsp',\n 'spk/estrack_v04.bsp']\n\n\n\nmkpath = kernels.get_metakernel_and_files('msl', '2020-01-01', '2020-01-05')\n\n\n\n\nmsl_ra_toolsref_v1.bc: 0%| | 0/18432 [00:00<?, ?it/s]\nmsl_v08.tf: 0%| | 0/205622 [00:00<?, ?it/s]/325632 [00:00<?, ?it/s]\nmsl_surf_rsm_tlmenc_2579_2713_v1.bc: 0%| | 0/4276224 [00:00<?, ?it/s][A\nmsl_surf_hga_tlm_2579_2713_v1.bc: 0%| | 0/2271232 [00:00<?, ?it/s]\nmsl_ra_toolsref_v1.bc: 100%|██████████| 18.0k/18.0k [00:00<00:00, 118kB/s] it/s]\nmsl_surf_rsm_tlmenc_2579_2713_v1.bc: 0%| | 4.00k/4.08M [00:00<02:40, 26.6kB/s]\nmsl_surf_ra_tlmres_2579_2713_v1.bc: 0%| | 4.00k/1.86M [00:00<01:14, 26.0kB/s]\n\nmsl_surf_rover_tlm_2579_2713_v1.bc: 1%|▏ | 4.00k/318k [00:00<00:12, 25.1kB/s][A\nmsl_surf_rsm_tlmenc_2579_2713_v1.bc: 1%| | 36.0k/4.08M [00:00<00:31, 133kB/s] \nmsl_surf_ra_tlmres_2579_2713_v1.bc: 2%|▏ | 36.0k/1.86M [00:00<00:14, 132kB/s] \nmsl_surf_rover_tlm_2579_2713_v1.bc: 11%|█▏ | 36.0k/318k [00:00<00:02, 131kB/s] \nmsl_surf_rsm_tlmres_2579_2713_v1.bc: 1%| | 36.0k/3.56M [00:00<00:28, 131kB/s] \nmsl_surf_rsm_tlmenc_2579_2713_v1.bc: 2%|▏ | 100k/4.08M [00:00<00:16, 260kB/s] A\nmsl_surf_ra_tlmres_2579_2713_v1.bc: 5%|▌ | 100k/1.86M [00:00<00:07, 259kB/s] \nmsl_surf_rover_tlm_2579_2713_v1.bc: 31%|███▏ | 100k/318k [00:00<00:00, 258kB/s] \nmsl_surf_rsm_tlmres_2579_2713_v1.bc: 3%|▎ | 100k/3.56M [00:00<00:14, 258kB/s] \nmsl_v08.tf: 100%|██████████| 201k/201k [00:00<00:00, 398kB/s] [00:00<00:08, 257kB/s] \nmsl_surf_ra_tlmenc_2579_2713_v1.bc: 7%|▋ | 212k/3.13M [00:00<00:06, 440kB/s]]\nmsl_surf_ra_tlmres_2579_2713_v1.bc: 11%|█ | 212k/1.86M [00:00<00:03, 440kB/s]\nmsl_surf_rover_tlm_2579_2713_v1.bc: 62%|██████▏ | 196k/318k [00:00<00:00, 399kB/s]\nmsl_surf_rover_tlm_2579_2713_v1.bc: 100%|██████████| 318k/318k [00:00<00:00, 503kB/s]s]\n\nmsl_surf_rsm_tlmenc_2579_2713_v1.bc: 10%|█ | 436k/4.08M [00:00<00:04, 800kB/s]\nmsl_surf_ra_tlmres_2579_2713_v1.bc: 23%|██▎ | 436k/1.86M [00:00<00:01, 799kB/s]\nmsl_surf_rsm_tlmres_2579_2713_v1.bc: 12%|█▏ | 436k/3.56M [00:00<00:04, 798kB/s]\nmsl_hbra_20120731_c03.ti: 100%|██████████| 7.77k/7.77k [00:00<00:00, 15.7MB/s]6kB/s]\nmsl_surf_rsm_tlmenc_2579_2713_v1.bc: 21%|██ | 884k/4.08M [00:00<00:02, 1.51MB/s]\nmsl_surf_ra_tlmres_2579_2713_v1.bc: 46%|████▋ | 884k/1.86M [00:00<00:00, 1.50MB/s]\nmsl_surf_rsm_tlmres_2579_2713_v1.bc: 24%|██▍ | 884k/3.56M [00:00<00:01, 1.50MB/s]\nmsl_surf_rsm_tlmenc_2579_2713_v1.bc: 43%|████▎ | 1.74M/4.08M [00:01<00:00, 2.89MB/s]\nmsl_surf_ra_tlmres_2579_2713_v1.bc: 100%|██████████| 1.86M/1.86M [00:01<00:00, 1.74MB/s]\n\nmsl_surf_rsm_tlmres_2579_2713_v1.bc: 49%|████▉ | 1.74M/3.56M [00:01<00:00, 2.88MB/s]\nmsl_surf_hga_tlm_2579_2713_v1.bc: 100%|██████████| 2.17M/2.17M [00:01<00:00, 1.98MB/s]\nmsl_surf_ra_tlmenc_2579_2713_v1.bc: 100%|██████████| 3.13M/3.13M [00:01<00:00, 2.81MB/s]\nmsl_hflb_20120731_c03.ti: 100%|██████████| 7.77k/7.77k [00:00<00:00, 13.2MB/s]\nmsl_surf_rsm_tlmenc_2579_2713_v1.bc: 86%|████████▌ | 3.49M/4.08M [00:01<00:00, 5.62MB/s]\nmsl_surf_rsm_tlmres_2579_2713_v1.bc: 100%|██████████| 3.56M/3.56M [00:01<00:00, 2.91MB/s]\n\nmsl_aux_v00.ti: 100%|██████████| 11.3k/11.3k [00:00<00:00, 29.3MB/s]\nmsl_hfra_20120731_c03.ti: 100%|██████████| 7.77k/7.77k [00:00<00:00, 13.2MB/s]\nmsl_hblb_20120731_c03.ti: 100%|██████████| 7.76k/7.76k [00:00<00:00, 4.88MB/s]\nmsl_hbrb_20120731_c03.ti: 100%|██████████| 7.77k/7.77k [00:00<00:00, 14.4MB/s]\nmsl_hfla_20120731_c03.ti: 100%|██████████| 7.77k/7.77k [00:00<00:00, 14.0MB/s]\nmsl_mahli_20120731_c02.ti: 100%|██████████| 7.70k/7.70k [00:00<00:00, 14.0MB/s]\nmsl_chrmi_20120731_c03.ti: 100%|██████████| 7.38k/7.38k [00:00<00:00, 13.2MB/s]\nmsl_hbla_20120731_c03.ti: 100%|██████████| 7.76k/7.76k [00:00<00:00, 14.0MB/s]\nmsl_hfrb_20120731_c03.ti: 100%|██████████| 7.77k/7.77k [00:00<00:00, 13.9MB/s]\nmsl_nla_20120731_c04.ti: 100%|██████████| 7.70k/7.70k [00:00<00:00, 19.9MB/s]\nmsl_mardi_20120731_c02.ti: 100%|██████████| 7.62k/7.62k [00:00<00:00, 13.4MB/s]\nmsl_ml_20120731_c03.ti: 100%|██████████| 7.72k/7.72k [00:00<00:00, 15.9MB/s]\nmsl_mr_20120731_c03.ti: 100%|██████████| 7.72k/7.72k [00:00<00:00, 4.39MB/s]\nmsl_nra_20120731_c04.ti: 100%|██████████| 7.71k/7.71k [00:00<00:00, 14.6MB/s]\nmsl_nrb_20130530_c05.ti: 100%|██████████| 7.72k/7.72k [00:00<00:00, 13.9MB/s]\nmsl_struct_v01.ti: 100%|██████████| 10.3k/10.3k [00:00<00:00, 16.9MB/s]\nmsl_nlb_20130530_c05.ti: 100%|██████████| 7.72k/7.72k [00:00<00:00, 22.5MB/s]\nmsl_lmst_ops120808_v1.tsc: 100%|██████████| 5.80k/5.80k [00:00<00:00, 13.8MB/s]\nnaif0012.tls: 100%|██████████| 6.70k/6.70k [00:00<00:00, 9.87MB/s]\nmar085s.bsp: 0%| | 0/89539584 [00:00<?, ?it/s]0:00<?, ?it/s]\nmsl_ls_ops120808_iau2000_v1.bsp: 100%|██████████| 8.00k/8.00k [00:00<00:00, 15.9MB/s]\n\nmar085s.bsp: 0%| | 4.00k/85.4M [00:00<58:05, 25.7kB/s]<00:02, 25.6kB/s]\nmsl_76_sclkscet_refit_s8.tsc: 100%|██████████| 55.7k/55.7k [00:00<00:00, 178kB/s] \nmar085s.bsp: 0%| | 36.0k/85.4M [00:00<11:22, 131kB/s] \nmsl_surf_rover_loc_2224_2358_v1.bsp: 0%| | 0/256000 [00:00<?, ?it/s]\npck00008.tpc: 100%|██████████| 111k/111k [00:00<00:00, 236kB/s] 1kB/s] \nmar085s.bsp: 0%| | 84.0k/85.4M [00:00<07:02, 212kB/s]\nmsl_surf_rover_loc_2224_2358_v1.bsp: 2%|▏ | 4.00k/250k [00:00<00:09, 25.6kB/s]\nmsl_struct_v02.bsp: 100%|██████████| 102k/102k [00:00<00:00, 217kB/s] \nde425s.bsp: 1%| | 100k/8.84M [00:00<00:35, 259kB/s] \nmar085s.bsp: 0%| | 196k/85.4M [00:00<03:37, 411kB/s] [00:00<?, ?it/s]\nmsl_surf_rover_loc_2003_2127_v1.bsp: 0%| | 0/344064 [00:00<?, ?it/s]131kB/s] \nmar085s.bsp: 0%| | 420k/85.4M [00:00<01:54, 780kB/s]9M [00:00<01:45, 25.7kB/s]\nmsl_surf_rover_loc_2003_2127_v1.bsp: 1%| | 4.00k/336k [00:00<00:13, 25.7kB/s][A\nmsl_surf_rover_loc_0000_2003_v1.bsp: 1%|▏ | 36.0k/2.59M [00:00<00:20, 131kB/s] \nmar085s.bsp: 1%| | 852k/85.4M [00:00<01:00, 1.45MB/s]00:00<?, ?it/s]\nmsl_surf_rover_loc_2224_2358_v1.bsp: 100%|██████████| 250k/250k [00:00<00:00, 399kB/s] \nmsl_surf_rover_loc_2003_2127_v1.bsp: 11%|█ | 36.0k/336k [00:00<00:02, 131kB/s] \nmsl_surf_rover_loc_0000_2003_v1.bsp: 3%|▎ | 84.0k/2.59M [00:00<00:12, 212kB/s]\nmsl_surf_rover_loc_2003_2127_v1.bsp: 25%|██▌ | 84.0k/336k [00:00<00:01, 211kB/s]]\nmsl_surf_rover_loc_2837_2934_v1.bsp: 0%| | 0/225280 [00:00<?, ?it/s]\nmsl_surf_rover_loc_0000_2003_v1.bsp: 7%|▋ | 180k/2.59M [00:00<00:06, 371kB/s] \nmsl_surf_rover_loc_2003_2127_v1.bsp: 49%|████▉ | 164k/336k [00:00<00:00, 330kB/s] ]\nmsl_surf_rover_loc_2837_2934_v1.bsp: 2%|▏ | 4.00k/220k [00:00<00:08, 25.3kB/s]\nmsl_surf_rover_loc_2003_2127_v1.bsp: 100%|██████████| 336k/336k [00:00<00:00, 524kB/s]]\n\nde425s.bsp: 72%|███████▏ | 6.36M/8.84M [00:01<00:00, 9.82MB/s] [00:00<00:01, 131kB/s] [A\nmsl_surf_rover_loc_2837_2934_v1.bsp: 16%|█▋ | 36.0k/220k [00:00<00:01, 130kB/s] \nmsl_surf_rover_loc_0000_2003_v1.bsp: 29%|██▉ | 772k/2.59M [00:00<00:01, 1.32MB/s]\nmsl_surf_rover_loc_2579_2713_v1.bsp: 100%|██████████| 294k/294k [00:00<00:00, 468kB/s] \nde425s.bsp: 100%|██████████| 8.84M/8.84M [00:01<00:00, 6.16MB/s] [00:00<00:00, 211kB/s]\nmar085s.bsp: 14%|█▎ | 11.6M/85.4M [00:01<00:05, 15.1MB/s]0:00<?, ?it/s]\nmsl_surf_rover_loc_2837_2934_v1.bsp: 38%|███▊ | 84.0k/220k [00:00<00:00, 211kB/s]\nmsl_surf_rover_loc_2127_2224_v1.bsp: 100%|██████████| 206k/206k [00:00<00:00, 329kB/s] s]\nmsl_surf_rover_loc_0000_2003_v1.bsp: 100%|██████████| 2.59M/2.59M [00:01<00:00, 2.29MB/s]\nmsl_surf_rover_loc_2358_2482_v1.bsp: 1%|▏ | 4.00k/270k [00:00<00:10, 25.8kB/s]\nmsl_surf_rover_loc_2837_2934_v1.bsp: 100%|██████████| 220k/220k [00:00<00:00, 350kB/s] \nmsl_surf_rover_loc_2713_2837_v1.bsp: 1%| | 4.00k/333k [00:00<00:13, 25.6kB/s]\nmsl_surf_rover_loc_3192_3289_v1.bsp: 0%| | 0/313344 [00:00<?, ?it/s]\nmsl_surf_rover_loc_2358_2482_v1.bsp: 100%|██████████| 270k/270k [00:00<00:00, 431kB/s] \nmar085s.bsp: 29%|██▉ | 24.9M/85.4M [00:02<00:03, 19.0MB/s][00:00<00:02, 131kB/s] \nmsl_surf_rover_loc_2934_3068_v1.bsp: 0%| | 0/423936 [00:00<?, ?it/s]25.4kB/s]\nmsl_surf_rover_loc_3068_3192_v1.bsp: 1%| | 4.00k/355k [00:00<00:14, 25.6kB/s]\nmar085s.bsp: 31%|███ | 26.1M/85.4M [00:02<00:03, 17.0MB/s]0:00<?, ?it/s]\nmsl_surf_rover_loc_2713_2837_v1.bsp: 25%|██▌ | 84.0k/333k [00:00<00:01, 211kB/s]\nmsl_surf_rover_loc_2934_3068_v1.bsp: 1%| | 4.00k/414k [00:00<00:16, 25.7kB/s]\nmsl_surf_rover_loc_3068_3192_v1.bsp: 10%|█ | 36.0k/355k [00:00<00:02, 131kB/s] \nmar085s.bsp: 33%|███▎ | 28.5M/85.4M [00:02<00:03, 18.7MB/s][00:00<00:08, 25.7kB/s]\nmsl_surf_rover_loc_2713_2837_v1.bsp: 100%|██████████| 333k/333k [00:00<00:00, 527kB/s] ]\n\nmsl_surf_rover_loc_2934_3068_v1.bsp: 9%|▊ | 36.0k/414k [00:00<00:02, 131kB/s] [A\nmsl_surf_rover_loc_3068_3192_v1.bsp: 28%|██▊ | 100k/355k [00:00<00:01, 258kB/s] \nmar085s.bsp: 37%|███▋ | 31.8M/85.4M [00:02<00:03, 17.1MB/s][00:00<00:01, 131kB/s] \nmsl_surf_rover_loc_3547_3644_v1.bsp: 11%|█▏ | 36.0k/314k [00:00<00:02, 131kB/s] \nmsl_surf_rover_loc_3192_3289_v1.bsp: 100%|██████████| 306k/306k [00:00<00:00, 485kB/s] \nmsl_surf_rover_loc_2934_3068_v1.bsp: 20%|██ | 84.0k/414k [00:00<00:01, 211kB/s]\nmsl_surf_rover_loc_3068_3192_v1.bsp: 100%|██████████| 355k/355k [00:00<00:00, 565kB/s]\n\nmsl_surf_rover_loc_3423_3547_v1.bsp: 0%| | 0/391168 [00:00<?, ?it/s]212kB/s]\nmsl_surf_rover_loc_2934_3068_v1.bsp: 43%|████▎ | 180k/414k [00:00<00:00, 371kB/s] \nmsl_surf_rover_loc_2482_2579_v1.bsp: 100%|██████████| 208k/208k [00:00<00:00, 332kB/s] \nmsl_surf_rover_loc_3423_3547_v1.bsp: 1%| | 4.00k/382k [00:00<00:15, 25.7kB/s]\nmsl_surf_rover_loc_3547_3644_v1.bsp: 100%|██████████| 314k/314k [00:00<00:00, 501kB/s] \nmsl_surf_rover_loc_2934_3068_v1.bsp: 100%|██████████| 414k/414k [00:00<00:00, 529kB/s]\nmsl_surf_rover_loc_3423_3547_v1.bsp: 100%|██████████| 382k/382k [00:00<00:00, 606kB/s] ]\nmsl_surf_rover_loc_3289_3423_v1.bsp: 10%|█ | 36.0k/356k [00:00<00:02, 131kB/s] \nmar085s.bsp: 57%|█████▋ | 48.5M/85.4M [00:03<00:02, 16.5MB/s]0:00<?, ?it/s]\nmsl_surf_rover_loc_3289_3423_v1.bsp: 24%|██▎ | 84.0k/356k [00:00<00:01, 212kB/s]\nmsl_surf_rover_loc_3778_3902_v1.bsp: 1%| | 4.00k/354k [00:00<00:13, 25.7kB/s]\nmsl_surf_rover_loc_3289_3423_v1.bsp: 100%|██████████| 356k/356k [00:00<00:00, 566kB/s] ]\n\nmar085s.bsp: 64%|██████▎ | 54.3M/85.4M [00:04<00:01, 16.9MB/s][00:00<00:02, 131kB/s] \nmar085s.bsp: 67%|██████▋ | 56.8M/85.4M [00:04<00:01, 19.1MB/s][00:00<00:02, 131kB/s] \nmsl_surf_rover_loc_3778_3902_v1.bsp: 24%|██▎ | 84.0k/354k [00:00<00:01, 211kB/s]\nmar085s.bsp: 69%|██████▉ | 58.9M/85.4M [00:04<00:01, 20.0MB/s][00:00<00:01, 210kB/s]\nmar085s.bsp: 70%|███████ | 59.8M/85.4M [00:04<00:01, 16.5MB/s]00:00<00:00, 371kB/s] \nmsl_surf_rover_loc_3778_3902_v1.bsp: 100%|██████████| 354k/354k [00:00<00:00, 557kB/s] \nmar085s.bsp: 73%|███████▎ | 62.7M/85.4M [00:04<00:01, 19.6MB/s]\nmsl_surf_rover_loc_3644_3778_v1.bsp: 100%|██████████| 363k/363k [00:00<00:00, 462kB/s]\nmar085s.bsp: 100%|██████████| 85.4M/85.4M [00:05<00:00, 15.3MB/s]\n\n\n\nimport spiceypy as spice\n\n\nspice.furnsh(str(mkpath))\n\n\nmkpath\n\nPath('/home/ayek72/mnt/slowdata/planetarypy/spice_kernels/msl/msl_v34_200101_200105.tm')\n\n\n\n!cat {mkpath}\n\nKPL/MK\n\n This meta-kernel lists a subset of kernels from the meta-kernel\n msl_v34.tm provided in the MSL-M-SPICE-6-V1.0 SPICE PDS3 archive,\n covering the whole or a part of the customer requested time period\n from 2020-01-01T00:00:00.000 to 2020-01-05T00:00:00.000.\n\n The documentation describing these kernels can be found in the\n complete MSL-M-SPICE-6-V1.0 SPICE PDS3 archive available at this URL\n\n https://naif.jpl.nasa.gov/pub/naif/pds/data/msl-m-spice-6-v1.0/mslsp_1000\n\n To use this meta-kernel users may need to modify the value of the\n PATH_VALUES keyword to point to the actual location of the archive's\n ``data'' directory on their system. Replacing ``/'' with ``\\''\n and converting line terminators to the format native to the user's\n system may also be required if this meta-kernel is to be used on a\n non-UNIX workstation.\n\n This meta-kernel was created by the NAIF node's SPICE PDS archive\n subsetting service version 2.1 on Fri Dec 1 09:03:32 PST 2023.\n\n \n \\begindata\n \n PATH_VALUES = (\n '/home/ayek72/mnt/slowdata/planetarypy/spice_kernels/msl'\n )\n \n PATH_SYMBOLS = (\n 'KERNELS'\n )\n \n KERNELS_TO_LOAD = (\n '$KERNELS/lsk/naif0012.tls'\n '$KERNELS/pck/pck00008.tpc'\n '$KERNELS/sclk/msl_lmst_ops120808_v1.tsc'\n '$KERNELS/sclk/msl_76_sclkscet_refit_s8.tsc'\n '$KERNELS/fk/msl_v08.tf'\n '$KERNELS/ik/msl_aux_v00.ti'\n '$KERNELS/ik/msl_chrmi_20120731_c03.ti'\n '$KERNELS/ik/msl_hbla_20120731_c03.ti'\n '$KERNELS/ik/msl_hblb_20120731_c03.ti'\n '$KERNELS/ik/msl_hbra_20120731_c03.ti'\n '$KERNELS/ik/msl_hbrb_20120731_c03.ti'\n '$KERNELS/ik/msl_hfla_20120731_c03.ti'\n '$KERNELS/ik/msl_hflb_20120731_c03.ti'\n '$KERNELS/ik/msl_hfra_20120731_c03.ti'\n '$KERNELS/ik/msl_hfrb_20120731_c03.ti'\n '$KERNELS/ik/msl_mahli_20120731_c02.ti'\n '$KERNELS/ik/msl_mardi_20120731_c02.ti'\n '$KERNELS/ik/msl_ml_20120731_c03.ti'\n '$KERNELS/ik/msl_mr_20120731_c03.ti'\n '$KERNELS/ik/msl_nla_20120731_c04.ti'\n '$KERNELS/ik/msl_nlb_20130530_c05.ti'\n '$KERNELS/ik/msl_nra_20120731_c04.ti'\n '$KERNELS/ik/msl_nrb_20130530_c05.ti'\n '$KERNELS/ik/msl_struct_v01.ti'\n '$KERNELS/spk/msl_struct_v02.bsp'\n '$KERNELS/spk/de425s.bsp'\n '$KERNELS/spk/mar085s.bsp'\n '$KERNELS/spk/msl_ls_ops120808_iau2000_v1.bsp'\n '$KERNELS/spk/msl_surf_rover_loc_0000_2003_v1.bsp'\n '$KERNELS/spk/msl_surf_rover_loc_2003_2127_v1.bsp'\n '$KERNELS/spk/msl_surf_rover_loc_2127_2224_v1.bsp'\n '$KERNELS/spk/msl_surf_rover_loc_2224_2358_v1.bsp'\n '$KERNELS/spk/msl_surf_rover_loc_2358_2482_v1.bsp'\n '$KERNELS/spk/msl_surf_rover_loc_2482_2579_v1.bsp'\n '$KERNELS/spk/msl_surf_rover_loc_2579_2713_v1.bsp'\n 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"PlanetaryPy Demo", + "section": "", + "text": "from planetarypy import utils\n\n\nDo you remember that the string conversion code for “day-of-year” is %j ?\n\n\nDo we want newcomers search for that in Python docs?\n\n\ntimes = [\"2002-137\", \"2005-234T13:00:00.123\"]\n\n\nisotimes = [utils.nasa_time_to_iso(t) for t in times]\nisotimes\n\n['2002-05-17', '2005-08-22T13:00:00.123000']\n\n\n\n[utils.iso_to_nasa_time(t) for t in isotimes]\n\n['2002-137', '2005-234T13:00:00.123000']\n\n\n\n\n\n\nutils.check_url_exists(\"https://michaelaye.github.io\")\n\nTrue\n\n\n\nutils.check_url_exists?\n\n\nSignature: utils.check_url_exists(url)\nDocstring: <no docstring>\nFile: ~/Dropbox/src/nbplanetary/planetarypy/utils.py\nType: function\n\n\n\n\nutils.have_internet()\n\nTrue\n\n\n\nutils.url_retrieve(\n \"https://michaelaye.github.io/talks/2021-conda-workshop-kharkiv/conda_talk_Kharkiv_conference.pdf\",\n \"talk_slides.pdf\",\n)" + }, + { + "objectID": "tutorials/apps_demo.html#time-and-network-utils", + "href": "tutorials/apps_demo.html#time-and-network-utils", + "title": "PlanetaryPy Demo", + "section": "", + "text": "from planetarypy import utils\n\n\nDo you remember that the string conversion code for “day-of-year” is %j ?\n\n\nDo we want newcomers search for that in Python docs?\n\n\ntimes = [\"2002-137\", \"2005-234T13:00:00.123\"]\n\n\nisotimes = [utils.nasa_time_to_iso(t) for t in times]\nisotimes\n\n['2002-05-17', '2005-08-22T13:00:00.123000']\n\n\n\n[utils.iso_to_nasa_time(t) for t in isotimes]\n\n['2002-137', '2005-234T13:00:00.123000']\n\n\n\n\n\n\nutils.check_url_exists(\"https://michaelaye.github.io\")\n\nTrue\n\n\n\nutils.check_url_exists?\n\n\nSignature: utils.check_url_exists(url)\nDocstring: <no docstring>\nFile: ~/Dropbox/src/nbplanetary/planetarypy/utils.py\nType: function\n\n\n\n\nutils.have_internet()\n\nTrue\n\n\n\nutils.url_retrieve(\n \"https://michaelaye.github.io/talks/2021-conda-workshop-kharkiv/conda_talk_Kharkiv_conference.pdf\",\n \"talk_slides.pdf\",\n)" + }, + { + "objectID": "tutorials/apps_demo.html#pds-indexes", + "href": "tutorials/apps_demo.html#pds-indexes", + "title": "PlanetaryPy Demo", + "section": "PDS Indexes", + "text": "PDS Indexes\n\nfrom planetarypy.pds.apps import find_indexes, get_index, find_instruments\n\n\nfind_indexes?\n\n\nSignature: find_indexes(instrument: str) -> list\nDocstring: Find existing indexes for an instrument.\nFile: ~/Dropbox/src/nbplanetary/planetarypy/pds/apps.py\nType: function\n\n\n\n\nfind_indexes('cassini.uvis')\n\n['index',\n 'moon_summary',\n 'ring_summary',\n 'saturn_summary',\n 'supplemental_index',\n 'versions']\n\n\n\nfind_indexes('go.ssi') # Galileo orbiter SSImager\n\n['edr']\n\n\n\nget_index?\n\n\nSignature:\nget_index(\n instr: str,\n index_name: str = '',\n refresh: bool = True,\n force: bool = False,\n) -> pandas.core.frame.DataFrame\nDocstring: Example: get_index(\"cassini.iss\", \"index\")\nFile: ~/Dropbox/src/nbplanetary/planetarypy/pds/apps.py\nType: function\n\n\n\n\nget_index(\"cassini.uvis.ring_summary\")\n\n\n\n\n\n\n\n\nVOLUME_ID\nFILE_SPECIFICATION_NAME\nRING_OBSERVATION_ID\nMINIMUM_RIGHT_ASCENSION\nMAXIMUM_RIGHT_ASCENSION\nMINIMUM_DECLINATION\nMAXIMUM_DECLINATION\nMINIMUM_RING_RADIUS\nMAXIMUM_RING_RADIUS\nFINEST_RING_INTERCEPT_RESOLUTION\n...\nRING_CENTER_DISTANCE\nSUB_SOLAR_RING_LONGITUDE\nSUB_OBSERVER_RING_LONGITUDE\nRING_CENTER_PHASE_ANGLE\nRING_CENTER_INCIDENCE_ANGLE\nRING_CENTER_NORTH_BASED_INCIDENCE_ANGLE\nRING_CENTER_EMISSION_ANGLE\nRING_CENTER_NORTH_BASED_EMISSION_ANGLE\nSOLAR_RING_OPENING_ANGLE\nOBSERVER_RING_OPENING_ANGLE\n\n\n\n\n0\nCOUVIS_0006\nDATA/D2004_002/EUV2004_002_12_16.LBL\nS/CO/UVIS/2004-002T12-16/EUV\n34.154493\n37.815141\n9.679762\n9.712415\n1074925.366\n3066570.289\n87709.0\n...\n86724352.465\n283.109\n215.938\n62.786\n64.404\n115.596\n73.661\n106.339\n-25.596\n-16.34\n\n\n1\nCOUVIS_0006\nDATA/D2004_002/EUV2004_002_12_32.LBL\nS/CO/UVIS/2004-002T12-32/EUV\n34.155557\n37.817313\n9.78073\n9.81348\n521741.812\n2900680.924\n87173.0\n...\n86719417.82\n283.109\n215.938\n62.787\n64.404\n115.596\n73.661\n106.339\n-25.596\n-16.34\n\n\n2\nCOUVIS_0006\nDATA/D2004_002/EUV2004_002_12_47.LBL\nS/CO/UVIS/2004-002T12-47/EUV\n34.154107\n37.816935\n9.877249\n9.909878\n64757.681\n2839690.546\n86667.0\n...\n86714483.175\n283.11\n215.938\n62.787\n64.404\n115.596\n73.661\n106.339\n-25.596\n-16.34\n\n\n3\nCOUVIS_0006\nDATA/D2004_002/EUV2004_002_13_03.LBL\nS/CO/UVIS/2004-002T13-03/EUV\n34.155193\n37.819152\n9.978176\n10.010898\n541745.355\n2872984.474\n86145.0\n...\n86709548.529\n283.11\n215.938\n62.787\n64.404\n115.596\n73.661\n106.339\n-25.596\n-16.34\n\n\n4\nCOUVIS_0006\nDATA/D2004_002/EUV2004_002_13_18.LBL\nS/CO/UVIS/2004-002T13-18/EUV\n34.157243\n37.822332\n10.077845\n10.110536\n1068459.125\n2999016.495\n85635.0\n...\n86704613.884\n283.111\n215.938\n62.788\n64.404\n115.596\n73.661\n106.339\n-25.596\n-16.34\n\n\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n\n\n167406\nCOUVIS_0060\nDATA/D2017_258/FUV2017_258_04_31.LBL\nS/CO/UVIS/2017-258T04-31/FUV\n355.156267\n93.92438\n-69.312846\n-14.507954\n126726.883\n1083278.078\n246.61634\n...\n263974.558\n178.948\n26.856\n99.681\n63.319\n63.319\n40.359\n40.359\n26.681\n49.641\n\n\n167407\nCOUVIS_0060\nDATA/D2017_258/FUV2017_258_07_00.LBL\nS/CO/UVIS/2017-258T07-00/FUV\n82.692823\n82.747154\n-4.328498\n-4.268149\n-999.0\n-999.0\n-999.0\n...\n251887.753\n178.949\n26.661\n99.192\n63.319\n63.319\n39.696\n39.696\n26.681\n50.304\n\n\n167408\nCOUVIS_0060\nDATA/D2017_258/FUV2017_258_07_15.LBL\nS/CO/UVIS/2017-258T07-15/FUV\n54.358671\n76.196366\n-4.007282\n13.298744\n-999.0\n-999.0\n-999.0\n...\n157806.504\n178.951\n68.04\n76.009\n63.319\n63.319\n34.946\n34.946\n26.681\n55.054\n\n\n167409\nCOUVIS_0060\nDATA/D2017_258/HDAC2017_258_02_14.LBL\nS/CO/UVIS/2017-258T02-14/HDAC\n129.674881\n143.379042\n-58.332263\n-48.522644\n204871.745\n219390.536\n17773.0\n...\n447586.578\n178.942\n9.923\n115.559\n63.319\n63.319\n53.073\n53.073\n26.681\n36.927\n\n\n167410\nCOUVIS_0060\nDATA/D2017_258/HDAC2017_258_02_15.LBL\nS/CO/UVIS/2017-258T02-15/HDAC\n92.532639\n116.78171\n-67.582806\n-63.392218\n98954.702\n230819.677\n12312.0\n...\n357220.013\n178.945\n15.877\n109.156\n63.319\n63.319\n47.62\n47.62\n26.681\n42.38\n\n\n\n\n167411 rows × 59 columns\n\n\n\n\nget_index('go.ssi.edr')\n\n\n\n\n\n\n\n\nSPACECRAFT_CLOCK_START_COUNT\nMISSION_NAME\nINSTRUMENT_ID\nDATA_SET_ID\nIMAGE_ID\nOBSERVATION_ID\nPRODUCT_TYPE\nTARGET_NAME\nIMAGE_TIME\nFILTER_NAME\n...\nSUB_SPACECRAFT_LINE\nSUB_SPACECRAFT_LINE_SAMPLE\nCENTER_RING_RADIUS\nVOLUME_ID\nFILE_SPECIFICATION_NAME\nCOMPRESSION_TYPE\nENCODING_MIN_COMPRESSION_RATIO\nENCODING_MAX_COMPRESSION_RATIO\nENCODING_COMPRESSION_RATIO\nPROCESSING_HISTORY_TEXT\n\n\n\n\n0\n30611.0\nGALILEO\nSSI\nGO-V/E-SSI-2-REDR-V1.1\nUNK\nPOST_LAUNCH_CHECKOUT\nREDR\nBLACK_SKY\nNaT\nCLEAR\n...\n-999.0\n-999.0\n-999\nGO_0002\nRAW_CAL/C0003061100R.IMG\nNONE\n0.0\n0.0\n0.0\nVICAR programs run: CATLABEL,BADLABEL,COPY.\n\n\n1\n30612.0\nGALILEO\nSSI\nGO-V/E-SSI-2-REDR-V1.1\nUNK\nPOST_LAUNCH_CHECKOUT\nREDR\nBLACK_SKY\nNaT\nCLEAR\n...\n-999.0\n-999.0\n-999\nGO_0002\nRAW_CAL/C0003061200R.IMG\nNONE\n0.0\n0.0\n0.0\nVICAR programs run: CATLABEL,BADLABEL,COPY.\n\n\n2\n30613.0\nGALILEO\nSSI\nGO-V/E-SSI-2-REDR-V1.1\nUNK\nPOST_LAUNCH_CHECKOUT\nREDR\nBLACK_SKY\nNaT\nCLEAR\n...\n-999.0\n-999.0\n-999\nGO_0002\nRAW_CAL/C0003061300R.IMG\nNONE\n0.0\n0.0\n0.0\nVICAR programs run: CATLABEL,BADLABEL,COPY.\n\n\n3\n30614.0\nGALILEO\nSSI\nGO-V/E-SSI-2-REDR-V1.1\nUNK\nPOST_LAUNCH_CHECKOUT\nREDR\nBLACK_SKY\nNaT\nCLEAR\n...\n-999.0\n-999.0\n-999\nGO_0002\nRAW_CAL/C0003061400R.IMG\nNONE\n0.0\n0.0\n0.0\nVICAR programs run: CATLABEL,BADLABEL,COPY.\n\n\n4\n30619.0\nGALILEO\nSSI\nGO-V/E-SSI-2-REDR-V1.1\nUNK\nPOST_LAUNCH_CHECKOUT\nREDR\nBLACK_SKY\nNaT\nCLEAR\n...\n-999.0\n-999.0\n-999\nGO_0002\nRAW_CAL/C0003061900R.IMG\nNONE\n0.0\n0.0\n0.0\nVICAR programs run: CATLABEL,BADLABEL,COPY.\n\n\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n\n\n14904\n6006608.22\nGALILEO\nSSI\nGO-J/JSA-SSI-4-REDR-V1.0\n29N0033\n29NSFLTFLD03\nREDR\nNON_SCIENC\nNaT\nIR-7270\n...\n-999.0\n-999.0\n-999\nGO_0023\nG29/REPAIRED/C0600660822S.IMG\nINTEGER COSINE TRANSFORM\n38.918\n16.986\n76.488\nVICAR programs run:SSIMERGE,F2,FASTMOS,FASTMOS...\n\n\n14905\n6006608.23\nGALILEO\nSSI\nGO-J/JSA-SSI-4-REDR-V1.0\n29N0033\n29NSFLTFLD03\nREDR\nNON_SCIENC\nNaT\nIR-7270\n...\n-999.0\n-999.0\n-999\nGO_0023\nG29/REPAIRED/C0600660823S.IMG\nHUFFMAN\n0.0\n0.0\n0.0\nVICAR programs run:SSIMERGE,F2,FASTMOS,FASTMOS...\n\n\n14906\n6006609.68\nGALILEO\nSSI\nGO-J/JSA-SSI-4-REDR-V1.0\n29N0034\n29NSFLTFLD03\nREDR\nNON_SCIENC\nNaT\nIR-8890\n...\n-999.0\n-999.0\n-999\nGO_0023\nG29/REPAIRED/C0600660968S.IMG\nINTEGER COSINE TRANSFORM\n6.054\n4.92\n8.212\nVICAR programs run:SSIMERGE,F2,FASTMOS,FASTMOS...\n\n\n14907\n6006609.69\nGALILEO\nSSI\nGO-J/JSA-SSI-4-REDR-V1.0\n29N0034\n29NSFLTFLD03\nREDR\nNON_SCIENC\nNaT\nIR-8890\n...\n-999.0\n-999.0\n-999\nGO_0023\nG29/REPAIRED/C0600660969S.IMG\nHUFFMAN\n0.0\n0.0\n0.0\nVICAR programs run:SSIMERGE,F2,FASTMOS,FASTMOS...\n\n\n14908\n4203615.0\nGALILEO\nSSI\nGO-J/JSA-SSI-2-REDR-V1.0\n11I0003\n11ISECLIPS01\nREDR\nIO\nNaT\nCLEAR\n...\n254.092\n334.653\n-999\nGO_0023\nREDO/E11/IO/C0420361500R.IMG\nINTEGER COSINE TRANSFORM\n8.354\n6.843\n9.709\nVICAR programs run: SSIMERGE,UNMOSAIC,CATLABEL...\n\n\n\n\n14909 rows × 52 columns\n\n\n\n\nfind_indexes(\"cassini.iss\")\n\n['index', 'inventory', 'moon_summary', 'ring_summary', 'saturn_summary']\n\n\n\nget_index(\"cassini.iss.saturn_summary\")\n\n\n\n\n\n\n\n\nVOLUME_ID\nFILE_SPECIFICATION_NAME\nOPUS_ID\nTARGET_NAME\nMINIMUM_PLANETOCENTRIC_LATITUDE\nMAXIMUM_PLANETOCENTRIC_LATITUDE\nMINIMUM_PLANETOGRAPHIC_LATITUDE\nMAXIMUM_PLANETOGRAPHIC_LATITUDE\nMINIMUM_IAU_LONGITUDE\nMAXIMUM_IAU_LONGITUDE\n...\nMAXIMUM_EMISSION_ANGLE\nSUB_SOLAR_PLANETOCENTRIC_LATITUDE\nSUB_SOLAR_PLANETOGRAPHIC_LATITUDE\nSUB_OBSERVER_PLANETOCENTRIC_LATITUDE\nSUB_OBSERVER_PLANETOGRAPHIC_LATITUDE\nSUB_SOLAR_IAU_LONGITUDE\nSUB_OBSERVER_IAU_LONGITUDE\nCENTER_RESOLUTION\nCENTER_DISTANCE\nCENTER_PHASE_ANGLE\n\n\n\n\n0\nCOISS_2001\ndata/1454725799_1455008789/N1454725799_1.LBL\nco-iss-n1454725799\nSATURN\n-999.0\n-999.0\n-999.0\n-999.0\n-999.0\n-999.0\n...\n-999.0\n-25.411\n-30.279\n-16.324\n-19.796\n107.986\n176.558\n424.67606\n70874998.947\n64.07\n\n\n1\nCOISS_2001\ndata/1454725799_1455008789/N1454726579_1.LBL\nco-iss-n1454726579\nSATURN\n-999.0\n-999.0\n-999.0\n-999.0\n-999.0\n-999.0\n...\n-999.0\n-25.411\n-30.279\n-16.324\n-19.796\n115.305\n183.877\n424.65121\n70870851.371\n64.07\n\n\n2\nCOISS_2001\ndata/1454725799_1455008789/N1454727359_1.LBL\nco-iss-n1454727359\nSATURN\n-999.0\n-999.0\n-999.0\n-999.0\n-999.0\n-999.0\n...\n-999.0\n-25.411\n-30.279\n-16.324\n-19.796\n122.625\n191.197\n424.62635\n70866703.094\n64.071\n\n\n3\nCOISS_2001\ndata/1454725799_1455008789/N1454728139_1.LBL\nco-iss-n1454728139\nSATURN\n-999.0\n-999.0\n-999.0\n-999.0\n-999.0\n-999.0\n...\n-999.0\n-25.411\n-30.279\n-16.324\n-19.796\n129.94\n198.513\n424.60151\n70862557.207\n64.071\n\n\n4\nCOISS_2001\ndata/1454725799_1455008789/N1454728919_1.LBL\nco-iss-n1454728919\nSATURN\n-999.0\n-999.0\n-999.0\n-999.0\n-999.0\n-999.0\n...\n-999.0\n-25.411\n-30.279\n-16.324\n-19.796\n137.264\n205.837\n424.57664\n70858406.794\n64.071\n\n\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n\n\n405116\nCOISS_2116\ndata/1884113741_1884114531/W1884114471_1.LBL\nco-iss-w1884114471\nSATURN\n-999.0\n-999.0\n-999.0\n-999.0\n-999.0\n-999.0\n...\n51.97\n26.682\n31.701\n29.262\n34.552\n263.715\n79.081\n75.81817\n634269.821\n123.878\n\n\n405117\nCOISS_2116\ndata/1884113741_1884114531/N1884114501_1.LBL\nco-iss-n1884114501\nSATURN\n-999.0\n-999.0\n-999.0\n-999.0\n-999.0\n-999.0\n...\n30.558\n26.682\n31.701\n29.269\n34.56\n263.996\n79.357\n7.59837\n634053.296\n123.87\n\n\n405118\nCOISS_2116\ndata/1884113741_1884114531/W1884114501_1.LBL\nco-iss-w1884114501\nSATURN\n-999.0\n-999.0\n-999.0\n-999.0\n-999.0\n-999.0\n...\n52.192\n26.682\n31.701\n29.27\n34.56\n264.004\n79.364\n75.79162\n634047.739\n123.87\n\n\n405119\nCOISS_2116\ndata/1884113741_1884114531/N1884114531_1.LBL\nco-iss-n1884114531\nSATURN\n-999.0\n-999.0\n-999.0\n-999.0\n-999.0\n-999.0\n...\n30.665\n26.682\n31.701\n29.277\n34.568\n264.278\n79.633\n7.59578\n633836.731\n123.863\n\n\n405120\nCOISS_2116\ndata/1884113741_1884114531/W1884114531_2.LBL\nco-iss-w1884114531\nSATURN\n-999.0\n-999.0\n-999.0\n-999.0\n-999.0\n-999.0\n...\n52.474\n26.682\n31.701\n29.277\n34.568\n264.286\n79.641\n75.76561\n633830.161\n123.862\n\n\n\n\n405121 rows × 35 columns\n\n\n\n\nfind_indexes('mro.ctx')\n\n['edr']\n\n\n\nget_index('mro.ctx', 'edr', refresh=False)\n\n\n\n\n\n\n\n\nVOLUME_ID\nFILE_SPECIFICATION_NAME\nORIGINAL_PRODUCT_ID\nPRODUCT_ID\nIMAGE_TIME\nINSTRUMENT_ID\nINSTRUMENT_MODE_ID\nLINE_SAMPLES\nLINES\nSPATIAL_SUMMING\n...\nSUB_SOLAR_LATITUDE\nSUB_SPACECRAFT_LONGITUDE\nSUB_SPACECRAFT_LATITUDE\nSOLAR_DISTANCE\nSOLAR_LONGITUDE\nLOCAL_TIME\nIMAGE_SKEW_ANGLE\nRATIONALE_DESC\nDATA_QUALITY_DESC\nORBIT_NUMBER\n\n\n\n\n0\nMROX_0001\nDATA/CRU_000001_9999_XN_99N999W.IMG\n4A_04_0001000400\nCRU_000001_9999_XN_99N999W\n2005-08-30 15:40:21.549\nCTX\nNIFL\n5056\n1024\n1\n...\n0.0\n0.0\n0.0\n0.0\n278.89\n10.16\n0.0\nInstrument checkout image of space\nOK\n-4242\n\n\n1\nMROX_0001\nDATA/CRU_000002_9999_XN_99N999W.IMG\n4A_04_0001000500\nCRU_000002_9999_XN_99N999W\n2005-09-08 15:59:45.313\nCTX\nNIFL\n5056\n15360\n1\n...\n0.0\n0.0\n0.0\n0.0\n284.48\n4.6\n0.0\nCalibration image of the Moon\nOK\n-4126\n\n\n2\nMROX_0001\nDATA/CRU_000003_9999_XN_99N999W.IMG\n4A_04_0001000600\nCRU_000003_9999_XN_99N999W\n2005-09-08 16:03:37.927\nCTX\nNIFL\n5056\n2048\n1\n...\n0.0\n0.0\n0.0\n0.0\n284.48\n4.66\n0.0\nCalibration image of Omega Centauri (globular ...\nOK\n-4126\n\n\n3\nMROX_0001\nDATA/CRU_000004_9999_XN_99N999W.IMG\n4A_04_0001000700\nCRU_000004_9999_XN_99N999W\n2005-09-08 16:08:23.841\nCTX\nNIFL\n5056\n2048\n1\n...\n0.0\n0.0\n0.0\n0.0\n284.48\n4.74\n0.0\nCalibration image of Omega Centauri (globular ...\nOK\n-4126\n\n\n4\nMROX_0001\nDATA/CRU_000005_9999_XN_99N999W.IMG\n4A_04_0001000800\nCRU_000005_9999_XN_99N999W\n2005-09-08 16:11:18.649\nCTX\nNIFL\n5056\n21504\n1\n...\n0.0\n0.0\n0.0\n0.0\n284.48\n4.79\n0.0\nCalibration image of the Moon\nOK\n-4126\n\n\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n...\n\n\n142363\nMROX_4656\nDATA/U17_077781_1107_XI_69S045W.IMG\n4A_04_118B04B300\nU17_077781_1107_XI_69S045W\n2023-03-01 00:01:37.834\nCTX\nITL\n5056\n7168\n1\n...\n12.74\n46.17\n-69.47\n243271024.8\n30.8\n15.42\n90.1\nSouthern autumn frost streak area in Viking 2 ...\nOK\n77781\n\n\n142364\nMROX_4656\nDATA/U17_077781_1560_XN_24S055W.IMG\n4A_04_118A04B400\nU17_077781_1560_XN_24S055W\n2023-03-01 00:15:17.076\nCTX\nNIFL\n5056\n30720\n1\n...\n12.74\n55.44\n-24.08\n243270437.8\n30.81\n14.96\n90.2\nRide-along with HiRISE\nOK\n77781\n\n\n142365\nMROX_4656\nDATA/U17_077781_1683_XN_11S057W.IMG\n4A_04_118A04B500\nU17_077781_1683_XN_11S057W\n2023-03-01 00:19:04.486\nCTX\nNIFL\n5056\n31744\n1\n...\n12.74\n57.0\n-11.7\n243270441.7\n30.81\n14.91\n90.2\nTerrain north of Coprates Chasma\nOK\n77781\n\n\n142366\nMROX_4656\nDATA/U17_077781_2027_XI_22N061W.IMG\n4A_04_118B04B600\nU17_077781_2027_XI_22N061W\n2023-03-01 00:29:24.818\nCTX\nITL\n5056\n52224\n1\n...\n12.74\n61.25\n22.78\n243271031.7\n30.81\n14.82\n89.8\nKasei Valles region\nOK\n77781\n\n\n142367\nMROX_4656\nDATA/U17_077781_2440_XN_64N067W.IMG\n4A_04_118A04B700\nU17_077781_2440_XN_64N067W\n2023-03-01 00:43:08.662\nCTX\nNIFL\n5056\n7168\n1\n...\n12.74\n68.76\n64.02\n243272920.6\n30.82\n14.59\n89.9\nRide-along with HiRISE\nOK\n77781\n\n\n\n\n142368 rows × 51 columns\n\n\n\n\nfind_instruments('cassini')\n\n['iss', 'uvis']\n\n\n\nfind_instruments('mro')\n\n['hirise', 'ctx']\n\n\n\nfind_instruments('lro')\n\n['diviner', 'lola', 'lroc']" + }, + { + "objectID": "tutorials/apps_demo.html#instrument-data", + "href": "tutorials/apps_demo.html#instrument-data", + "title": "PlanetaryPy Demo", + "section": "Instrument data", + "text": "Instrument data\n\nfrom planetarypy.uvis import DataManager\n\n\nindex = get_index(\"cassini.uvis.index\")\n\n\nindex.tail()\n\n\n\n\n\n\n\n\nFILE_NAME\nOBSERVATION_TYPE\nSTART_TIME\nSTOP_TIME\nTARGET_NAME\nDATA_SET_ID\nSPACECRAFT_CLOCK_START_COUNT\nSPACECRAFT_CLOCK_STOP_COUNT\nINTEGRATION_DURATION\nCOMPRESSION_TYPE\n...\nSUB_SOLAR_LONGITUDE\nSUB_SPACECRAFT_LATITUDE\nSUB_SPACECRAFT_LONGITUDE\nPHASE_ANGLE\nEMISSION_ANGLE\nSOLAR_INCIDENCE_ANGLE\nCENTRAL_BODY_DISTANCE\nDWELL_TIME\nH_LEVEL\nD_LEVEL\n\n\n\n\n203240\n/COUVIS_0060/DATA/D2017_258/FUV2017_258_04_31.LBL\n<NA>\n2017-09-15 04:31:53.005\n2017-09-15 09:04:56.755\nSOLAR WIND\nCO-S-UVIS-2-CUBE-V1.4\n1/1884145299.160\nUNK\n8191.875\nSQRT_9\n...\n-999.0\n-999.0\n-999.0\n-999.0\n-999.0\n-999\n-999.0\n-999\n<NA>\n<NA>\n\n\n203241\n/COUVIS_0060/DATA/D2017_258/FUV2017_258_07_00.LBL\n<NA>\n2017-09-15 07:00:27.697\n2017-09-15 07:13:40.447\nSOLAR WIND\nCO-S-UVIS-2-SPEC-V1.4\n1/1884154214.096\nUNK\n2.625\nSQRT_9\n...\n-999.0\n-999.0\n-999.0\n-999.0\n-999.0\n-999\n-999.0\n-999\n<NA>\n<NA>\n\n\n203242\n/COUVIS_0060/DATA/D2017_258/FUV2017_258_07_15.LBL\n<NA>\n2017-09-15 07:15:04.442\n2017-09-15 10:31:51.692\nSOLAR WIND\nCO-S-UVIS-2-SPEC-V1.4\n1/1884155091.032\nUNK\n2.625\nSQRT_9\n...\n-999.0\n-999.0\n-999.0\n-999.0\n-999.0\n-999\n-999.0\n-999\n<NA>\n<NA>\n\n\n203243\n/COUVIS_0060/DATA/D2017_258/HDAC2017_258_02_14...\n<NA>\n2017-09-15 02:14:02.433\n2017-09-15 02:14:06.433\nSOLAR WIND\nCO-S-UVIS-2-SSB-V1.4\n1/1884137029.000\nUNK\n-999.0\nNONE\n...\n-999.0\n-999.0\n-999.0\n-999.0\n-999.0\n-999\n-999.0\n1\n(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0)\n(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0)\n\n\n203244\n/COUVIS_0060/DATA/D2017_258/HDAC2017_258_02_15...\n<NA>\n2017-09-15 02:15:25.058\n2017-09-15 02:17:33.058\nSOLAR WIND\nCO-S-UVIS-2-SSB-V1.4\n1/1884137111.160\nUNK\n-999.0\nNONE\n...\n-999.0\n-999.0\n-999.0\n-999.0\n-999.0\n-999\n-999.0\n32\n(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0)\n(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0)\n\n\n\n\n5 rows × 28 columns\n\n\n\n\ndm = DataManager(\"EUV2017_258_07_00\")\n\n\ndm.calib_label_path\n\nPath('/home/ayek72/mnt/slowdata/planetarypy/missions/cassini/uvis/EUV2017_258_07_00/EUV2017_258_07_00_CAL_3.LBL')\n\n\n\ndm.raw_data_path\n\nPath('/home/ayek72/mnt/slowdata/planetarypy/missions/cassini/uvis/EUV2017_258_07_00/EUV2017_258_07_00.DAT')\n\n\n\ndm.raw_label_path\n\nPath('/home/ayek72/mnt/slowdata/planetarypy/missions/cassini/uvis/EUV2017_258_07_00/EUV2017_258_07_00.LBL')\n\n\n\nfrom planetarypy.hirise import ProductPathfinder\n\n\n\n\n\n\n\n\n\n\n\n\nppf = ProductPathfinder(\"PSP_003092_0985_RED\")\n\n\nppf.local_label_path\n\nPath('/home/ayek72/mnt/slowdata/planetarypy/missions/mro/hirise/PSP_003092_0985/PSP_003092_0985_RED.LBL')\n\n\n\nppf.abrowse_path\n\nPath('EXTRAS/RDR/PSP/ORB_003000_003099/PSP_003092_0985/PSP_003092_0985_RED.abrowse.jpg')\n\n\n\nppf.homepage\n\n'https://uahirise.org/PSP_003092_0985'\n\n\n\nppf.nomap_jp2_url\n\nURL('https://hirise-pds.lpl.arizona.edu/PDS/EXTRAS/RDR/PSP/ORB_003000_003099/PSP_003092_0985/PSP_003092_0985_RED.NOMAP.JP2')\n\n\n\nfrom planetarypy.hirise import RGB_NOMAP\n\n\nrgb = RGB_NOMAP(\"PSP_003092_0985\")\n\n\nrgb.local_path\n\nPath('/home/ayek72/mnt/slowdata/planetarypy/missions/mro/hirise/PSP_003092_0985/PSP_003092_0985_RGB.NOMAP.JP2')" + }, + { + "objectID": "tutorials/spice_howtos.html", + "href": "tutorials/spice_howtos.html", + "title": "SPICE with planetarypy HOWTO", + "section": "", + "text": "from astropy import units as u\nfrom numpy.linalg import norm\n\nfrom planetarypy.spice.spicer import MoonSpicer, MarsSpicer\n\n\nmoon = MoonSpicer(\"2022-02-22\")\n\n\nmoon.time.isoformat()\n\n'2022-02-22T00:00:00'\n\n\n\nmoon.solar_constant\n\n\\(1388.4482 \\; \\mathrm{\\frac{W}{m^{2}}}\\)\n\n\n\nmoon.set_spoint_by(lat=0, lon=0)\n\n\nmoon.aspect = 180\nmoon.tilt = 30\n\n\nmoon.F_flat\n\n\\(497.68762 \\; \\mathrm{\\frac{W}{m^{2}}}\\)\n\n\n\nmoon.F_aspect\n\n\\(449.48514 \\; \\mathrm{\\frac{W}{m^{2}}}\\)\n\n\n\nmoon.F_tilt\n\n\\(412.53511 \\; \\mathrm{\\frac{W}{m^{2}}}\\)\n\n\n\nmoon.subsolar\n\narray([ 622.78676959, -1621.28270346, -46.23629622])\n\n\n\nmoon.local_soltime\n\n'16:35:58'\n\n\n\n# MoonSpicer returns km (as all calculations in SPICE do)\n# use astropy.units to convert to other values\nnorm(moon.body_to_object(\"EARTH\")[0]) * u.km\n\n\\(375365.92 \\; \\mathrm{km}\\)\n\n\n\n(norm(moon.body_to_object(\"MARS\")[0]) * u.km).to(u.AU)\n\n\\(2.0379563 \\; \\mathrm{AU}\\)\n\n\n\nmars = MarsSpicer()\n\n\nmars.utc\n\n'2023-06-27T18:37:50.876055'\n\n\n\nmars.l_s\n\n83.31658188802474\n\n\n\nmars.goto('inca')\n\n\nmars.spoint\n\n(220.09830399469547, -440.60853011059214, -3340.5081261541495)\n\n\n\nmars.aspect=180\nmars.tilt=30\n\n\nmars.F_flat\n\n\\(0 \\; \\mathrm{\\frac{W}{m^{2}}}\\)\n\n\n\nmars.F_aspect\n\n\\(0 \\; \\mathrm{\\frac{W}{m^{2}}}\\)\n\n\n\nmars.set_spoint_by(lat=0, lon=0)\n\n\nmars.F_flat\n\n\\(339.2043 \\; \\mathrm{\\frac{W}{m^{2}}}\\)\n\n\n\nmars.F_tilt\n\n\\(397.92501 \\; \\mathrm{\\frac{W}{m^{2}}}\\)" + }, + { + "objectID": "tutorials/spice_howtos.html#surface-calculations-on-the-moon", + "href": "tutorials/spice_howtos.html#surface-calculations-on-the-moon", + "title": "SPICE with planetarypy HOWTO", + "section": "", + "text": "from astropy import units as u\nfrom numpy.linalg import norm\n\nfrom planetarypy.spice.spicer import MoonSpicer, MarsSpicer\n\n\nmoon = MoonSpicer(\"2022-02-22\")\n\n\nmoon.time.isoformat()\n\n'2022-02-22T00:00:00'\n\n\n\nmoon.solar_constant\n\n\\(1388.4482 \\; \\mathrm{\\frac{W}{m^{2}}}\\)\n\n\n\nmoon.set_spoint_by(lat=0, lon=0)\n\n\nmoon.aspect = 180\nmoon.tilt = 30\n\n\nmoon.F_flat\n\n\\(497.68762 \\; \\mathrm{\\frac{W}{m^{2}}}\\)\n\n\n\nmoon.F_aspect\n\n\\(449.48514 \\; \\mathrm{\\frac{W}{m^{2}}}\\)\n\n\n\nmoon.F_tilt\n\n\\(412.53511 \\; \\mathrm{\\frac{W}{m^{2}}}\\)\n\n\n\nmoon.subsolar\n\narray([ 622.78676959, -1621.28270346, -46.23629622])\n\n\n\nmoon.local_soltime\n\n'16:35:58'\n\n\n\n# MoonSpicer returns km (as all calculations in SPICE do)\n# use astropy.units to convert to other values\nnorm(moon.body_to_object(\"EARTH\")[0]) * u.km\n\n\\(375365.92 \\; \\mathrm{km}\\)\n\n\n\n(norm(moon.body_to_object(\"MARS\")[0]) * u.km).to(u.AU)\n\n\\(2.0379563 \\; \\mathrm{AU}\\)\n\n\n\nmars = MarsSpicer()\n\n\nmars.utc\n\n'2023-06-27T18:37:50.876055'\n\n\n\nmars.l_s\n\n83.31658188802474\n\n\n\nmars.goto('inca')\n\n\nmars.spoint\n\n(220.09830399469547, -440.60853011059214, -3340.5081261541495)\n\n\n\nmars.aspect=180\nmars.tilt=30\n\n\nmars.F_flat\n\n\\(0 \\; \\mathrm{\\frac{W}{m^{2}}}\\)\n\n\n\nmars.F_aspect\n\n\\(0 \\; \\mathrm{\\frac{W}{m^{2}}}\\)\n\n\n\nmars.set_spoint_by(lat=0, lon=0)\n\n\nmars.F_flat\n\n\\(339.2043 \\; \\mathrm{\\frac{W}{m^{2}}}\\)\n\n\n\nmars.F_tilt\n\n\\(397.92501 \\; \\mathrm{\\frac{W}{m^{2}}}\\)" + } +] \ No newline at end of file diff --git a/site_libs/bootstrap/bootstrap-icons.css b/site_libs/bootstrap/bootstrap-icons.css new file mode 100644 index 0000000..94f1940 --- /dev/null +++ b/site_libs/bootstrap/bootstrap-icons.css @@ -0,0 +1,2018 @@ +@font-face { + font-display: block; + font-family: "bootstrap-icons"; + src: +url("./bootstrap-icons.woff?2ab2cbbe07fcebb53bdaa7313bb290f2") format("woff"); +} + +.bi::before, +[class^="bi-"]::before, 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this._config.reference&&(e=this._config.reference);const i=this._getPopperConfig(),n=i.modifiers.find((t=>"applyStyles"===t.name&&!1===t.enabled));this._popper=qe(e,this._menu,i),n&&U.setDataAttribute(this._menu,"popper","static")}_isShown(t=this._element){return t.classList.contains(Je)}_getMenuElement(){return V.next(this._element,ei)[0]}_getPlacement(){const t=this._element.parentNode;if(t.classList.contains("dropend"))return ri;if(t.classList.contains("dropstart"))return ai;const e="end"===getComputedStyle(this._menu).getPropertyValue("--bs-position").trim();return t.classList.contains("dropup")?e?ni:ii:e?oi:si}_detectNavbar(){return null!==this._element.closest(".navbar")}_getOffset(){const{offset:t}=this._config;return"string"==typeof t?t.split(",").map((t=>Number.parseInt(t,10))):"function"==typeof t?e=>t(e,this._element):t}_getPopperConfig(){const t={placement:this._getPlacement(),modifiers:[{name:"preventOverflow",options:{boundary:this._config.boundary}},{name:"offset",options:{offset:this._getOffset()}}]};return"static"===this._config.display&&(t.modifiers=[{name:"applyStyles",enabled:!1}]),{...t,..."function"==typeof this._config.popperConfig?this._config.popperConfig(t):this._config.popperConfig}}_selectMenuItem({key:t,target:e}){const i=V.find(".dropdown-menu .dropdown-item:not(.disabled):not(:disabled)",this._menu).filter(l);i.length&&v(i,e,t===Ye,!i.includes(e)).focus()}static jQueryInterface(t){return this.each((function(){const e=hi.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t])throw new TypeError(`No method named "${t}"`);e[t]()}}))}static clearMenus(t){if(t&&(2===t.button||"keyup"===t.type&&"Tab"!==t.key))return;const e=V.find(ti);for(let i=0,n=e.length;ie+t)),this._setElementAttributes(di,"paddingRight",(e=>e+t)),this._setElementAttributes(ui,"marginRight",(e=>e-t))}_disableOverFlow(){this._saveInitialAttribute(this._element,"overflow"),this._element.style.overflow="hidden"}_setElementAttributes(t,e,i){const n=this.getWidth();this._applyManipulationCallback(t,(t=>{if(t!==this._element&&window.innerWidth>t.clientWidth+n)return;this._saveInitialAttribute(t,e);const s=window.getComputedStyle(t)[e];t.style[e]=`${i(Number.parseFloat(s))}px`}))}reset(){this._resetElementAttributes(this._element,"overflow"),this._resetElementAttributes(this._element,"paddingRight"),this._resetElementAttributes(di,"paddingRight"),this._resetElementAttributes(ui,"marginRight")}_saveInitialAttribute(t,e){const i=t.style[e];i&&U.setDataAttribute(t,e,i)}_resetElementAttributes(t,e){this._applyManipulationCallback(t,(t=>{const i=U.getDataAttribute(t,e);void 0===i?t.style.removeProperty(e):(U.removeDataAttribute(t,e),t.style[e]=i)}))}_applyManipulationCallback(t,e){o(t)?e(t):V.find(t,this._element).forEach(e)}isOverflowing(){return this.getWidth()>0}}const pi={className:"modal-backdrop",isVisible:!0,isAnimated:!1,rootElement:"body",clickCallback:null},mi={className:"string",isVisible:"boolean",isAnimated:"boolean",rootElement:"(element|string)",clickCallback:"(function|null)"},gi="show",_i="mousedown.bs.backdrop";class bi{constructor(t){this._config=this._getConfig(t),this._isAppended=!1,this._element=null}show(t){this._config.isVisible?(this._append(),this._config.isAnimated&&u(this._getElement()),this._getElement().classList.add(gi),this._emulateAnimation((()=>{_(t)}))):_(t)}hide(t){this._config.isVisible?(this._getElement().classList.remove(gi),this._emulateAnimation((()=>{this.dispose(),_(t)}))):_(t)}_getElement(){if(!this._element){const t=document.createElement("div");t.className=this._config.className,this._config.isAnimated&&t.classList.add("fade"),this._element=t}return this._element}_getConfig(t){return(t={...pi,..."object"==typeof t?t:{}}).rootElement=r(t.rootElement),a("backdrop",t,mi),t}_append(){this._isAppended||(this._config.rootElement.append(this._getElement()),j.on(this._getElement(),_i,(()=>{_(this._config.clickCallback)})),this._isAppended=!0)}dispose(){this._isAppended&&(j.off(this._element,_i),this._element.remove(),this._isAppended=!1)}_emulateAnimation(t){b(t,this._getElement(),this._config.isAnimated)}}const vi={trapElement:null,autofocus:!0},yi={trapElement:"element",autofocus:"boolean"},wi=".bs.focustrap",Ei="backward";class Ai{constructor(t){this._config=this._getConfig(t),this._isActive=!1,this._lastTabNavDirection=null}activate(){const{trapElement:t,autofocus:e}=this._config;this._isActive||(e&&t.focus(),j.off(document,wi),j.on(document,"focusin.bs.focustrap",(t=>this._handleFocusin(t))),j.on(document,"keydown.tab.bs.focustrap",(t=>this._handleKeydown(t))),this._isActive=!0)}deactivate(){this._isActive&&(this._isActive=!1,j.off(document,wi))}_handleFocusin(t){const{target:e}=t,{trapElement:i}=this._config;if(e===document||e===i||i.contains(e))return;const n=V.focusableChildren(i);0===n.length?i.focus():this._lastTabNavDirection===Ei?n[n.length-1].focus():n[0].focus()}_handleKeydown(t){"Tab"===t.key&&(this._lastTabNavDirection=t.shiftKey?Ei:"forward")}_getConfig(t){return t={...vi,..."object"==typeof t?t:{}},a("focustrap",t,yi),t}}const Ti="modal",Oi="Escape",Ci={backdrop:!0,keyboard:!0,focus:!0},ki={backdrop:"(boolean|string)",keyboard:"boolean",focus:"boolean"},Li="hidden.bs.modal",xi="show.bs.modal",Di="resize.bs.modal",Si="click.dismiss.bs.modal",Ni="keydown.dismiss.bs.modal",Ii="mousedown.dismiss.bs.modal",Pi="modal-open",ji="show",Mi="modal-static";class Hi extends B{constructor(t,e){super(t),this._config=this._getConfig(e),this._dialog=V.findOne(".modal-dialog",this._element),this._backdrop=this._initializeBackDrop(),this._focustrap=this._initializeFocusTrap(),this._isShown=!1,this._ignoreBackdropClick=!1,this._isTransitioning=!1,this._scrollBar=new fi}static get Default(){return Ci}static get NAME(){return Ti}toggle(t){return this._isShown?this.hide():this.show(t)}show(t){this._isShown||this._isTransitioning||j.trigger(this._element,xi,{relatedTarget:t}).defaultPrevented||(this._isShown=!0,this._isAnimated()&&(this._isTransitioning=!0),this._scrollBar.hide(),document.body.classList.add(Pi),this._adjustDialog(),this._setEscapeEvent(),this._setResizeEvent(),j.on(this._dialog,Ii,(()=>{j.one(this._element,"mouseup.dismiss.bs.modal",(t=>{t.target===this._element&&(this._ignoreBackdropClick=!0)}))})),this._showBackdrop((()=>this._showElement(t))))}hide(){if(!this._isShown||this._isTransitioning)return;if(j.trigger(this._element,"hide.bs.modal").defaultPrevented)return;this._isShown=!1;const t=this._isAnimated();t&&(this._isTransitioning=!0),this._setEscapeEvent(),this._setResizeEvent(),this._focustrap.deactivate(),this._element.classList.remove(ji),j.off(this._element,Si),j.off(this._dialog,Ii),this._queueCallback((()=>this._hideModal()),this._element,t)}dispose(){[window,this._dialog].forEach((t=>j.off(t,".bs.modal"))),this._backdrop.dispose(),this._focustrap.deactivate(),super.dispose()}handleUpdate(){this._adjustDialog()}_initializeBackDrop(){return new bi({isVisible:Boolean(this._config.backdrop),isAnimated:this._isAnimated()})}_initializeFocusTrap(){return new Ai({trapElement:this._element})}_getConfig(t){return t={...Ci,...U.getDataAttributes(this._element),..."object"==typeof t?t:{}},a(Ti,t,ki),t}_showElement(t){const e=this._isAnimated(),i=V.findOne(".modal-body",this._dialog);this._element.parentNode&&this._element.parentNode.nodeType===Node.ELEMENT_NODE||document.body.append(this._element),this._element.style.display="block",this._element.removeAttribute("aria-hidden"),this._element.setAttribute("aria-modal",!0),this._element.setAttribute("role","dialog"),this._element.scrollTop=0,i&&(i.scrollTop=0),e&&u(this._element),this._element.classList.add(ji),this._queueCallback((()=>{this._config.focus&&this._focustrap.activate(),this._isTransitioning=!1,j.trigger(this._element,"shown.bs.modal",{relatedTarget:t})}),this._dialog,e)}_setEscapeEvent(){this._isShown?j.on(this._element,Ni,(t=>{this._config.keyboard&&t.key===Oi?(t.preventDefault(),this.hide()):this._config.keyboard||t.key!==Oi||this._triggerBackdropTransition()})):j.off(this._element,Ni)}_setResizeEvent(){this._isShown?j.on(window,Di,(()=>this._adjustDialog())):j.off(window,Di)}_hideModal(){this._element.style.display="none",this._element.setAttribute("aria-hidden",!0),this._element.removeAttribute("aria-modal"),this._element.removeAttribute("role"),this._isTransitioning=!1,this._backdrop.hide((()=>{document.body.classList.remove(Pi),this._resetAdjustments(),this._scrollBar.reset(),j.trigger(this._element,Li)}))}_showBackdrop(t){j.on(this._element,Si,(t=>{this._ignoreBackdropClick?this._ignoreBackdropClick=!1:t.target===t.currentTarget&&(!0===this._config.backdrop?this.hide():"static"===this._config.backdrop&&this._triggerBackdropTransition())})),this._backdrop.show(t)}_isAnimated(){return this._element.classList.contains("fade")}_triggerBackdropTransition(){if(j.trigger(this._element,"hidePrevented.bs.modal").defaultPrevented)return;const{classList:t,scrollHeight:e,style:i}=this._element,n=e>document.documentElement.clientHeight;!n&&"hidden"===i.overflowY||t.contains(Mi)||(n||(i.overflowY="hidden"),t.add(Mi),this._queueCallback((()=>{t.remove(Mi),n||this._queueCallback((()=>{i.overflowY=""}),this._dialog)}),this._dialog),this._element.focus())}_adjustDialog(){const t=this._element.scrollHeight>document.documentElement.clientHeight,e=this._scrollBar.getWidth(),i=e>0;(!i&&t&&!m()||i&&!t&&m())&&(this._element.style.paddingLeft=`${e}px`),(i&&!t&&!m()||!i&&t&&m())&&(this._element.style.paddingRight=`${e}px`)}_resetAdjustments(){this._element.style.paddingLeft="",this._element.style.paddingRight=""}static jQueryInterface(t,e){return this.each((function(){const i=Hi.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===i[t])throw new TypeError(`No method named "${t}"`);i[t](e)}}))}}j.on(document,"click.bs.modal.data-api",'[data-bs-toggle="modal"]',(function(t){const e=n(this);["A","AREA"].includes(this.tagName)&&t.preventDefault(),j.one(e,xi,(t=>{t.defaultPrevented||j.one(e,Li,(()=>{l(this)&&this.focus()}))}));const i=V.findOne(".modal.show");i&&Hi.getInstance(i).hide(),Hi.getOrCreateInstance(e).toggle(this)})),R(Hi),g(Hi);const Bi="offcanvas",Ri={backdrop:!0,keyboard:!0,scroll:!1},Wi={backdrop:"boolean",keyboard:"boolean",scroll:"boolean"},$i="show",zi=".offcanvas.show",qi="hidden.bs.offcanvas";class Fi extends B{constructor(t,e){super(t),this._config=this._getConfig(e),this._isShown=!1,this._backdrop=this._initializeBackDrop(),this._focustrap=this._initializeFocusTrap(),this._addEventListeners()}static get NAME(){return Bi}static get Default(){return Ri}toggle(t){return this._isShown?this.hide():this.show(t)}show(t){this._isShown||j.trigger(this._element,"show.bs.offcanvas",{relatedTarget:t}).defaultPrevented||(this._isShown=!0,this._element.style.visibility="visible",this._backdrop.show(),this._config.scroll||(new fi).hide(),this._element.removeAttribute("aria-hidden"),this._element.setAttribute("aria-modal",!0),this._element.setAttribute("role","dialog"),this._element.classList.add($i),this._queueCallback((()=>{this._config.scroll||this._focustrap.activate(),j.trigger(this._element,"shown.bs.offcanvas",{relatedTarget:t})}),this._element,!0))}hide(){this._isShown&&(j.trigger(this._element,"hide.bs.offcanvas").defaultPrevented||(this._focustrap.deactivate(),this._element.blur(),this._isShown=!1,this._element.classList.remove($i),this._backdrop.hide(),this._queueCallback((()=>{this._element.setAttribute("aria-hidden",!0),this._element.removeAttribute("aria-modal"),this._element.removeAttribute("role"),this._element.style.visibility="hidden",this._config.scroll||(new fi).reset(),j.trigger(this._element,qi)}),this._element,!0)))}dispose(){this._backdrop.dispose(),this._focustrap.deactivate(),super.dispose()}_getConfig(t){return t={...Ri,...U.getDataAttributes(this._element),..."object"==typeof t?t:{}},a(Bi,t,Wi),t}_initializeBackDrop(){return new bi({className:"offcanvas-backdrop",isVisible:this._config.backdrop,isAnimated:!0,rootElement:this._element.parentNode,clickCallback:()=>this.hide()})}_initializeFocusTrap(){return new Ai({trapElement:this._element})}_addEventListeners(){j.on(this._element,"keydown.dismiss.bs.offcanvas",(t=>{this._config.keyboard&&"Escape"===t.key&&this.hide()}))}static jQueryInterface(t){return this.each((function(){const e=Fi.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t]||t.startsWith("_")||"constructor"===t)throw new TypeError(`No method named "${t}"`);e[t](this)}}))}}j.on(document,"click.bs.offcanvas.data-api",'[data-bs-toggle="offcanvas"]',(function(t){const e=n(this);if(["A","AREA"].includes(this.tagName)&&t.preventDefault(),c(this))return;j.one(e,qi,(()=>{l(this)&&this.focus()}));const i=V.findOne(zi);i&&i!==e&&Fi.getInstance(i).hide(),Fi.getOrCreateInstance(e).toggle(this)})),j.on(window,"load.bs.offcanvas.data-api",(()=>V.find(zi).forEach((t=>Fi.getOrCreateInstance(t).show())))),R(Fi),g(Fi);const Ui=new Set(["background","cite","href","itemtype","longdesc","poster","src","xlink:href"]),Vi=/^(?:(?:https?|mailto|ftp|tel|file|sms):|[^#&/:?]*(?:[#/?]|$))/i,Ki=/^data:(?:image\/(?:bmp|gif|jpeg|jpg|png|tiff|webp)|video\/(?:mpeg|mp4|ogg|webm)|audio\/(?:mp3|oga|ogg|opus));base64,[\d+/a-z]+=*$/i,Xi=(t,e)=>{const i=t.nodeName.toLowerCase();if(e.includes(i))return!Ui.has(i)||Boolean(Vi.test(t.nodeValue)||Ki.test(t.nodeValue));const n=e.filter((t=>t instanceof RegExp));for(let t=0,e=n.length;t{Xi(t,r)||i.removeAttribute(t.nodeName)}))}return n.body.innerHTML}const Qi="tooltip",Gi=new Set(["sanitize","allowList","sanitizeFn"]),Zi={animation:"boolean",template:"string",title:"(string|element|function)",trigger:"string",delay:"(number|object)",html:"boolean",selector:"(string|boolean)",placement:"(string|function)",offset:"(array|string|function)",container:"(string|element|boolean)",fallbackPlacements:"array",boundary:"(string|element)",customClass:"(string|function)",sanitize:"boolean",sanitizeFn:"(null|function)",allowList:"object",popperConfig:"(null|object|function)"},Ji={AUTO:"auto",TOP:"top",RIGHT:m()?"left":"right",BOTTOM:"bottom",LEFT:m()?"right":"left"},tn={animation:!0,template:'',trigger:"hover focus",title:"",delay:0,html:!1,selector:!1,placement:"top",offset:[0,0],container:!1,fallbackPlacements:["top","right","bottom","left"],boundary:"clippingParents",customClass:"",sanitize:!0,sanitizeFn:null,allowList:{"*":["class","dir","id","lang","role",/^aria-[\w-]*$/i],a:["target","href","title","rel"],area:[],b:[],br:[],col:[],code:[],div:[],em:[],hr:[],h1:[],h2:[],h3:[],h4:[],h5:[],h6:[],i:[],img:["src","srcset","alt","title","width","height"],li:[],ol:[],p:[],pre:[],s:[],small:[],span:[],sub:[],sup:[],strong:[],u:[],ul:[]},popperConfig:null},en={HIDE:"hide.bs.tooltip",HIDDEN:"hidden.bs.tooltip",SHOW:"show.bs.tooltip",SHOWN:"shown.bs.tooltip",INSERTED:"inserted.bs.tooltip",CLICK:"click.bs.tooltip",FOCUSIN:"focusin.bs.tooltip",FOCUSOUT:"focusout.bs.tooltip",MOUSEENTER:"mouseenter.bs.tooltip",MOUSELEAVE:"mouseleave.bs.tooltip"},nn="fade",sn="show",on="show",rn="out",an=".tooltip-inner",ln=".modal",cn="hide.bs.modal",hn="hover",dn="focus";class un extends B{constructor(t,e){if(void 0===Fe)throw new TypeError("Bootstrap's tooltips require Popper (https://popper.js.org)");super(t),this._isEnabled=!0,this._timeout=0,this._hoverState="",this._activeTrigger={},this._popper=null,this._config=this._getConfig(e),this.tip=null,this._setListeners()}static get Default(){return tn}static get NAME(){return Qi}static get Event(){return en}static get DefaultType(){return Zi}enable(){this._isEnabled=!0}disable(){this._isEnabled=!1}toggleEnabled(){this._isEnabled=!this._isEnabled}toggle(t){if(this._isEnabled)if(t){const e=this._initializeOnDelegatedTarget(t);e._activeTrigger.click=!e._activeTrigger.click,e._isWithActiveTrigger()?e._enter(null,e):e._leave(null,e)}else{if(this.getTipElement().classList.contains(sn))return void this._leave(null,this);this._enter(null,this)}}dispose(){clearTimeout(this._timeout),j.off(this._element.closest(ln),cn,this._hideModalHandler),this.tip&&this.tip.remove(),this._disposePopper(),super.dispose()}show(){if("none"===this._element.style.display)throw new Error("Please use show on visible elements");if(!this.isWithContent()||!this._isEnabled)return;const t=j.trigger(this._element,this.constructor.Event.SHOW),e=h(this._element),i=null===e?this._element.ownerDocument.documentElement.contains(this._element):e.contains(this._element);if(t.defaultPrevented||!i)return;"tooltip"===this.constructor.NAME&&this.tip&&this.getTitle()!==this.tip.querySelector(an).innerHTML&&(this._disposePopper(),this.tip.remove(),this.tip=null);const n=this.getTipElement(),s=(t=>{do{t+=Math.floor(1e6*Math.random())}while(document.getElementById(t));return t})(this.constructor.NAME);n.setAttribute("id",s),this._element.setAttribute("aria-describedby",s),this._config.animation&&n.classList.add(nn);const o="function"==typeof this._config.placement?this._config.placement.call(this,n,this._element):this._config.placement,r=this._getAttachment(o);this._addAttachmentClass(r);const{container:a}=this._config;H.set(n,this.constructor.DATA_KEY,this),this._element.ownerDocument.documentElement.contains(this.tip)||(a.append(n),j.trigger(this._element,this.constructor.Event.INSERTED)),this._popper?this._popper.update():this._popper=qe(this._element,n,this._getPopperConfig(r)),n.classList.add(sn);const l=this._resolvePossibleFunction(this._config.customClass);l&&n.classList.add(...l.split(" ")),"ontouchstart"in document.documentElement&&[].concat(...document.body.children).forEach((t=>{j.on(t,"mouseover",d)}));const c=this.tip.classList.contains(nn);this._queueCallback((()=>{const t=this._hoverState;this._hoverState=null,j.trigger(this._element,this.constructor.Event.SHOWN),t===rn&&this._leave(null,this)}),this.tip,c)}hide(){if(!this._popper)return;const t=this.getTipElement();if(j.trigger(this._element,this.constructor.Event.HIDE).defaultPrevented)return;t.classList.remove(sn),"ontouchstart"in document.documentElement&&[].concat(...document.body.children).forEach((t=>j.off(t,"mouseover",d))),this._activeTrigger.click=!1,this._activeTrigger.focus=!1,this._activeTrigger.hover=!1;const e=this.tip.classList.contains(nn);this._queueCallback((()=>{this._isWithActiveTrigger()||(this._hoverState!==on&&t.remove(),this._cleanTipClass(),this._element.removeAttribute("aria-describedby"),j.trigger(this._element,this.constructor.Event.HIDDEN),this._disposePopper())}),this.tip,e),this._hoverState=""}update(){null!==this._popper&&this._popper.update()}isWithContent(){return Boolean(this.getTitle())}getTipElement(){if(this.tip)return this.tip;const t=document.createElement("div");t.innerHTML=this._config.template;const e=t.children[0];return this.setContent(e),e.classList.remove(nn,sn),this.tip=e,this.tip}setContent(t){this._sanitizeAndSetContent(t,this.getTitle(),an)}_sanitizeAndSetContent(t,e,i){const n=V.findOne(i,t);e||!n?this.setElementContent(n,e):n.remove()}setElementContent(t,e){if(null!==t)return o(e)?(e=r(e),void(this._config.html?e.parentNode!==t&&(t.innerHTML="",t.append(e)):t.textContent=e.textContent)):void(this._config.html?(this._config.sanitize&&(e=Yi(e,this._config.allowList,this._config.sanitizeFn)),t.innerHTML=e):t.textContent=e)}getTitle(){const t=this._element.getAttribute("data-bs-original-title")||this._config.title;return this._resolvePossibleFunction(t)}updateAttachment(t){return"right"===t?"end":"left"===t?"start":t}_initializeOnDelegatedTarget(t,e){return e||this.constructor.getOrCreateInstance(t.delegateTarget,this._getDelegateConfig())}_getOffset(){const{offset:t}=this._config;return"string"==typeof t?t.split(",").map((t=>Number.parseInt(t,10))):"function"==typeof t?e=>t(e,this._element):t}_resolvePossibleFunction(t){return"function"==typeof t?t.call(this._element):t}_getPopperConfig(t){const e={placement:t,modifiers:[{name:"flip",options:{fallbackPlacements:this._config.fallbackPlacements}},{name:"offset",options:{offset:this._getOffset()}},{name:"preventOverflow",options:{boundary:this._config.boundary}},{name:"arrow",options:{element:`.${this.constructor.NAME}-arrow`}},{name:"onChange",enabled:!0,phase:"afterWrite",fn:t=>this._handlePopperPlacementChange(t)}],onFirstUpdate:t=>{t.options.placement!==t.placement&&this._handlePopperPlacementChange(t)}};return{...e,..."function"==typeof this._config.popperConfig?this._config.popperConfig(e):this._config.popperConfig}}_addAttachmentClass(t){this.getTipElement().classList.add(`${this._getBasicClassPrefix()}-${this.updateAttachment(t)}`)}_getAttachment(t){return Ji[t.toUpperCase()]}_setListeners(){this._config.trigger.split(" ").forEach((t=>{if("click"===t)j.on(this._element,this.constructor.Event.CLICK,this._config.selector,(t=>this.toggle(t)));else if("manual"!==t){const e=t===hn?this.constructor.Event.MOUSEENTER:this.constructor.Event.FOCUSIN,i=t===hn?this.constructor.Event.MOUSELEAVE:this.constructor.Event.FOCUSOUT;j.on(this._element,e,this._config.selector,(t=>this._enter(t))),j.on(this._element,i,this._config.selector,(t=>this._leave(t)))}})),this._hideModalHandler=()=>{this._element&&this.hide()},j.on(this._element.closest(ln),cn,this._hideModalHandler),this._config.selector?this._config={...this._config,trigger:"manual",selector:""}:this._fixTitle()}_fixTitle(){const t=this._element.getAttribute("title"),e=typeof this._element.getAttribute("data-bs-original-title");(t||"string"!==e)&&(this._element.setAttribute("data-bs-original-title",t||""),!t||this._element.getAttribute("aria-label")||this._element.textContent||this._element.setAttribute("aria-label",t),this._element.setAttribute("title",""))}_enter(t,e){e=this._initializeOnDelegatedTarget(t,e),t&&(e._activeTrigger["focusin"===t.type?dn:hn]=!0),e.getTipElement().classList.contains(sn)||e._hoverState===on?e._hoverState=on:(clearTimeout(e._timeout),e._hoverState=on,e._config.delay&&e._config.delay.show?e._timeout=setTimeout((()=>{e._hoverState===on&&e.show()}),e._config.delay.show):e.show())}_leave(t,e){e=this._initializeOnDelegatedTarget(t,e),t&&(e._activeTrigger["focusout"===t.type?dn:hn]=e._element.contains(t.relatedTarget)),e._isWithActiveTrigger()||(clearTimeout(e._timeout),e._hoverState=rn,e._config.delay&&e._config.delay.hide?e._timeout=setTimeout((()=>{e._hoverState===rn&&e.hide()}),e._config.delay.hide):e.hide())}_isWithActiveTrigger(){for(const t in this._activeTrigger)if(this._activeTrigger[t])return!0;return!1}_getConfig(t){const e=U.getDataAttributes(this._element);return Object.keys(e).forEach((t=>{Gi.has(t)&&delete e[t]})),(t={...this.constructor.Default,...e,..."object"==typeof t&&t?t:{}}).container=!1===t.container?document.body:r(t.container),"number"==typeof t.delay&&(t.delay={show:t.delay,hide:t.delay}),"number"==typeof t.title&&(t.title=t.title.toString()),"number"==typeof t.content&&(t.content=t.content.toString()),a(Qi,t,this.constructor.DefaultType),t.sanitize&&(t.template=Yi(t.template,t.allowList,t.sanitizeFn)),t}_getDelegateConfig(){const t={};for(const e in this._config)this.constructor.Default[e]!==this._config[e]&&(t[e]=this._config[e]);return t}_cleanTipClass(){const t=this.getTipElement(),e=new 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b/site_libs/quarto-html/quarto-syntax-highlighting.css @@ -0,0 +1,203 @@ +/* quarto syntax highlight colors */ +:root { + --quarto-hl-ot-color: #003B4F; + --quarto-hl-at-color: #657422; + --quarto-hl-ss-color: #20794D; + --quarto-hl-an-color: #5E5E5E; + --quarto-hl-fu-color: #4758AB; + --quarto-hl-st-color: #20794D; + --quarto-hl-cf-color: #003B4F; + --quarto-hl-op-color: #5E5E5E; + --quarto-hl-er-color: #AD0000; + --quarto-hl-bn-color: #AD0000; + --quarto-hl-al-color: #AD0000; + --quarto-hl-va-color: #111111; + --quarto-hl-bu-color: inherit; + --quarto-hl-ex-color: inherit; + --quarto-hl-pp-color: #AD0000; + --quarto-hl-in-color: #5E5E5E; + --quarto-hl-vs-color: #20794D; + --quarto-hl-wa-color: #5E5E5E; + --quarto-hl-do-color: #5E5E5E; + --quarto-hl-im-color: #00769E; + --quarto-hl-ch-color: #20794D; + --quarto-hl-dt-color: #AD0000; + --quarto-hl-fl-color: #AD0000; + --quarto-hl-co-color: #5E5E5E; + --quarto-hl-cv-color: #5E5E5E; + --quarto-hl-cn-color: #8f5902; + --quarto-hl-sc-color: #5E5E5E; + --quarto-hl-dv-color: #AD0000; + --quarto-hl-kw-color: #003B4F; +} + +/* other quarto variables */ +:root { + --quarto-font-monospace: SFMono-Regular, Menlo, Monaco, Consolas, "Liberation Mono", "Courier New", monospace; +} + +pre > code.sourceCode > span { + color: #003B4F; +} + +code span { + color: #003B4F; +} + +code.sourceCode > span { + color: #003B4F; +} + +div.sourceCode, +div.sourceCode pre.sourceCode { + color: #003B4F; +} + +code span.ot { + color: #003B4F; + font-style: inherit; +} + +code span.at { + color: #657422; + font-style: inherit; +} + +code span.ss { + color: #20794D; + font-style: inherit; +} + +code span.an { + color: #5E5E5E; + font-style: inherit; +} + +code span.fu { + color: #4758AB; + font-style: inherit; +} + +code span.st { + color: #20794D; + font-style: inherit; +} + +code span.cf { + color: #003B4F; + font-style: inherit; +} + +code span.op { + color: #5E5E5E; + font-style: inherit; +} + +code span.er { + color: #AD0000; + font-style: inherit; +} + +code span.bn { + color: #AD0000; + font-style: inherit; +} + +code span.al { + color: #AD0000; + font-style: inherit; +} + +code span.va { + color: #111111; + font-style: inherit; +} + +code span.bu { + font-style: inherit; +} + +code span.ex { + font-style: inherit; +} + +code span.pp { + color: #AD0000; + font-style: inherit; +} + +code span.in { + color: #5E5E5E; + font-style: inherit; +} + +code span.vs { + color: #20794D; + font-style: inherit; +} + +code span.wa { + color: #5E5E5E; + font-style: italic; +} + +code span.do { + color: #5E5E5E; + font-style: italic; +} + +code span.im { + color: #00769E; + font-style: inherit; +} + +code span.ch { + color: #20794D; + font-style: inherit; +} + +code span.dt { + color: #AD0000; + font-style: inherit; +} + +code span.fl { + color: #AD0000; + font-style: inherit; +} + +code span.co { + color: #5E5E5E; + font-style: inherit; +} + +code span.cv { + color: #5E5E5E; + font-style: italic; +} + +code span.cn { + color: #8f5902; + font-style: inherit; +} + +code span.sc { + color: #5E5E5E; + font-style: inherit; +} + +code span.dv { + color: #AD0000; + font-style: inherit; +} + +code span.kw { + color: #003B4F; + font-style: inherit; +} + +.prevent-inlining { + content: " { + // Find any conflicting margin elements and add margins to the + // top to prevent overlap + const marginChildren = window.document.querySelectorAll( + ".column-margin.column-container > * " + ); + + let lastBottom = 0; + for (const marginChild of marginChildren) { + if (marginChild.offsetParent !== null) { + // clear the top margin so we recompute it + marginChild.style.marginTop = null; + const top = marginChild.getBoundingClientRect().top + window.scrollY; + console.log({ + childtop: marginChild.getBoundingClientRect().top, + scroll: window.scrollY, + top, + lastBottom, + }); + if (top < lastBottom) { + const margin = lastBottom - top; + marginChild.style.marginTop = `${margin}px`; + } + const styles = window.getComputedStyle(marginChild); + const marginTop = parseFloat(styles["marginTop"]); + + console.log({ + top, + height: marginChild.getBoundingClientRect().height, + marginTop, + total: top + marginChild.getBoundingClientRect().height + marginTop, + }); + lastBottom = top + marginChild.getBoundingClientRect().height + marginTop; + } + } +}; + +window.document.addEventListener("DOMContentLoaded", function (_event) { + // Recompute the position of margin elements anytime the body size changes + if (window.ResizeObserver) { + const resizeObserver = new window.ResizeObserver( + throttle(layoutMarginEls, 50) + ); + resizeObserver.observe(window.document.body); + } + + const tocEl = window.document.querySelector('nav.toc-active[role="doc-toc"]'); + const sidebarEl = window.document.getElementById("quarto-sidebar"); + const leftTocEl = window.document.getElementById("quarto-sidebar-toc-left"); + const marginSidebarEl = window.document.getElementById( + "quarto-margin-sidebar" + ); + // function to determine whether the element has a previous sibling that is active + const prevSiblingIsActiveLink = (el) => { + const sibling = el.previousElementSibling; + if (sibling && sibling.tagName === "A") { + return sibling.classList.contains("active"); + } else { + return false; + } + }; + + // fire slideEnter for bootstrap tab activations (for htmlwidget resize behavior) + function fireSlideEnter(e) { + const event = window.document.createEvent("Event"); + event.initEvent("slideenter", true, true); + window.document.dispatchEvent(event); + } + const tabs = window.document.querySelectorAll('a[data-bs-toggle="tab"]'); + tabs.forEach((tab) => { + tab.addEventListener("shown.bs.tab", fireSlideEnter); + }); + + // fire slideEnter for tabby tab activations (for htmlwidget resize behavior) + document.addEventListener("tabby", fireSlideEnter, false); + + // Track scrolling and mark TOC links as active + // get table of contents and sidebar (bail if we don't have at least one) + const tocLinks = tocEl + ? [...tocEl.querySelectorAll("a[data-scroll-target]")] + : []; + const makeActive = (link) => tocLinks[link].classList.add("active"); + const removeActive = (link) => tocLinks[link].classList.remove("active"); + const removeAllActive = () => + [...Array(tocLinks.length).keys()].forEach((link) => removeActive(link)); + + // activate the anchor for a section associated with this TOC entry + tocLinks.forEach((link) => { + link.addEventListener("click", () => { + if (link.href.indexOf("#") !== -1) { + const anchor = link.href.split("#")[1]; + const heading = window.document.querySelector( + `[data-anchor-id=${anchor}]` + ); + if (heading) { + // Add the class + heading.classList.add("reveal-anchorjs-link"); + + // function to show the anchor + const handleMouseout = () => { + heading.classList.remove("reveal-anchorjs-link"); + heading.removeEventListener("mouseout", handleMouseout); + }; + + // add a function to clear the anchor when the user mouses out of it + heading.addEventListener("mouseout", handleMouseout); + } + } + }); + }); + + const sections = tocLinks.map((link) => { + const target = link.getAttribute("data-scroll-target"); + if (target.startsWith("#")) { + return window.document.getElementById(decodeURI(`${target.slice(1)}`)); + } else { + return window.document.querySelector(decodeURI(`${target}`)); + } + }); + + const sectionMargin = 200; + let currentActive = 0; + // track whether we've initialized state the first time + let init = false; + + const updateActiveLink = () => { + // The index from bottom to top (e.g. reversed list) + let sectionIndex = -1; + if ( + window.innerHeight + window.pageYOffset >= + window.document.body.offsetHeight + ) { + sectionIndex = 0; + } else { + sectionIndex = [...sections].reverse().findIndex((section) => { + if (section) { + return window.pageYOffset >= section.offsetTop - sectionMargin; + } else { + return false; + } + }); + } + if (sectionIndex > -1) { + const current = sections.length - sectionIndex - 1; + if (current !== currentActive) { + removeAllActive(); + currentActive = current; + makeActive(current); + if (init) { + window.dispatchEvent(sectionChanged); + } + init = true; + } + } + }; + + const inHiddenRegion = (top, bottom, hiddenRegions) => { + for (const region of hiddenRegions) { + if (top <= region.bottom && bottom >= region.top) { + return true; + } + } + return false; + }; + + const categorySelector = "header.quarto-title-block .quarto-category"; + const activateCategories = (href) => { + // Find any categories + // Surround them with a link pointing back to: + // #category=Authoring + try { + const categoryEls = window.document.querySelectorAll(categorySelector); + for (const categoryEl of categoryEls) { + const categoryText = categoryEl.textContent; + if (categoryText) { + const link = `${href}#category=${encodeURIComponent(categoryText)}`; + const linkEl = window.document.createElement("a"); + linkEl.setAttribute("href", link); + for (const child of categoryEl.childNodes) { + linkEl.append(child); + } + categoryEl.appendChild(linkEl); + } + } + } catch { + // Ignore errors + } + }; + function hasTitleCategories() { + return window.document.querySelector(categorySelector) !== null; + } + + function offsetRelativeUrl(url) { + const offset = getMeta("quarto:offset"); + return offset ? offset + url : url; + } + + function offsetAbsoluteUrl(url) { + const offset = getMeta("quarto:offset"); + const baseUrl = new URL(offset, window.location); + + const projRelativeUrl = url.replace(baseUrl, ""); + if (projRelativeUrl.startsWith("/")) { + return projRelativeUrl; + } else { + return "/" + projRelativeUrl; + } + } + + // read a meta tag value + function getMeta(metaName) { + const metas = window.document.getElementsByTagName("meta"); + for (let i = 0; i < metas.length; i++) { + if (metas[i].getAttribute("name") === metaName) { + return metas[i].getAttribute("content"); + } + } + return ""; + } + + async function findAndActivateCategories() { + const currentPagePath = offsetAbsoluteUrl(window.location.href); + const response = await fetch(offsetRelativeUrl("listings.json")); + if (response.status == 200) { + return response.json().then(function (listingPaths) { + const listingHrefs = []; + for (const listingPath of listingPaths) { + const pathWithoutLeadingSlash = listingPath.listing.substring(1); + for (const item of listingPath.items) { + if ( + item === currentPagePath || + item === currentPagePath + "index.html" + ) { + // Resolve this path against the offset to be sure + // we already are using the correct path to the listing + // (this adjusts the listing urls to be rooted against + // whatever root the page is actually running against) + const relative = offsetRelativeUrl(pathWithoutLeadingSlash); + const baseUrl = window.location; + const resolvedPath = new URL(relative, baseUrl); + listingHrefs.push(resolvedPath.pathname); + break; + } + } + } + + // Look up the tree for a nearby linting and use that if we find one + const nearestListing = findNearestParentListing( + offsetAbsoluteUrl(window.location.pathname), + listingHrefs + ); + if (nearestListing) { + activateCategories(nearestListing); + } else { + // See if the referrer is a listing page for this item + const referredRelativePath = offsetAbsoluteUrl(document.referrer); + const referrerListing = listingHrefs.find((listingHref) => { + const isListingReferrer = + listingHref === referredRelativePath || + listingHref === referredRelativePath + "index.html"; + return isListingReferrer; + }); + + if (referrerListing) { + // Try to use the referrer if possible + activateCategories(referrerListing); + } else if (listingHrefs.length > 0) { + // Otherwise, just fall back to the first listing + activateCategories(listingHrefs[0]); + } + } + }); + } + } + if (hasTitleCategories()) { + findAndActivateCategories(); + } + + const findNearestParentListing = (href, listingHrefs) => { + if (!href || !listingHrefs) { + return undefined; + } + // Look up the tree for a nearby linting and use that if we find one + const relativeParts = href.substring(1).split("/"); + while (relativeParts.length > 0) { + const path = relativeParts.join("/"); + for (const listingHref of listingHrefs) { + if (listingHref.startsWith(path)) { + return listingHref; + } + } + relativeParts.pop(); + } + + return undefined; + }; + + const manageSidebarVisiblity = (el, placeholderDescriptor) => { + let isVisible = true; + let elRect; + + return (hiddenRegions) => { + if (el === null) { + return; + } + + // Find the last element of the TOC + const lastChildEl = el.lastElementChild; + + if (lastChildEl) { + // Converts the sidebar to a menu + const convertToMenu = () => { + for (const child of el.children) { + child.style.opacity = 0; + child.style.overflow = "hidden"; + } + + nexttick(() => { + const toggleContainer = window.document.createElement("div"); + toggleContainer.style.width = "100%"; + toggleContainer.classList.add("zindex-over-content"); + toggleContainer.classList.add("quarto-sidebar-toggle"); + toggleContainer.classList.add("headroom-target"); // Marks this to be managed by headeroom + toggleContainer.id = placeholderDescriptor.id; + toggleContainer.style.position = "fixed"; + + const toggleIcon = window.document.createElement("i"); + toggleIcon.classList.add("quarto-sidebar-toggle-icon"); + toggleIcon.classList.add("bi"); + toggleIcon.classList.add("bi-caret-down-fill"); + + const toggleTitle = window.document.createElement("div"); + const titleEl = window.document.body.querySelector( + placeholderDescriptor.titleSelector + ); + if (titleEl) { + toggleTitle.append( + titleEl.textContent || titleEl.innerText, + toggleIcon + ); + } + toggleTitle.classList.add("zindex-over-content"); + toggleTitle.classList.add("quarto-sidebar-toggle-title"); + toggleContainer.append(toggleTitle); + + const toggleContents = window.document.createElement("div"); + toggleContents.classList = el.classList; + toggleContents.classList.add("zindex-over-content"); + toggleContents.classList.add("quarto-sidebar-toggle-contents"); + for (const child of el.children) { + if (child.id === "toc-title") { + continue; + } + + const clone = child.cloneNode(true); + clone.style.opacity = 1; + clone.style.display = null; + toggleContents.append(clone); + } + toggleContents.style.height = "0px"; + const positionToggle = () => { + // position the element (top left of parent, same width as parent) + if (!elRect) { + elRect = el.getBoundingClientRect(); + } + toggleContainer.style.left = `${elRect.left}px`; + toggleContainer.style.top = `${elRect.top}px`; + toggleContainer.style.width = `${elRect.width}px`; + }; + positionToggle(); + + toggleContainer.append(toggleContents); + el.parentElement.prepend(toggleContainer); + + // Process clicks + let tocShowing = false; + // Allow the caller to control whether this is dismissed + // when it is clicked (e.g. sidebar navigation supports + // opening and closing the nav tree, so don't dismiss on click) + const clickEl = placeholderDescriptor.dismissOnClick + ? toggleContainer + : toggleTitle; + + const closeToggle = () => { + if (tocShowing) { + toggleContainer.classList.remove("expanded"); + toggleContents.style.height = "0px"; + tocShowing = false; + } + }; + + // Get rid of any expanded toggle if the user scrolls + window.document.addEventListener( + "scroll", + throttle(() => { + closeToggle(); + }, 50) + ); + + // Handle positioning of the toggle + window.addEventListener( + "resize", + throttle(() => { + elRect = undefined; + positionToggle(); + }, 50) + ); + + window.addEventListener("quarto-hrChanged", () => { + elRect = undefined; + }); + + // Process the click + clickEl.onclick = () => { + if (!tocShowing) { + toggleContainer.classList.add("expanded"); + toggleContents.style.height = null; + tocShowing = true; + } else { + closeToggle(); + } + }; + }); + }; + + // Converts a sidebar from a menu back to a sidebar + const convertToSidebar = () => { + for (const child of el.children) { + child.style.opacity = 1; + child.style.overflow = null; + } + + const placeholderEl = window.document.getElementById( + placeholderDescriptor.id + ); + if (placeholderEl) { + placeholderEl.remove(); + } + + el.classList.remove("rollup"); + }; + + if (isReaderMode()) { + convertToMenu(); + isVisible = false; + } else { + // Find the top and bottom o the element that is being managed + const elTop = el.offsetTop; + const elBottom = + elTop + lastChildEl.offsetTop + lastChildEl.offsetHeight; + + if (!isVisible) { + // If the element is current not visible reveal if there are + // no conflicts with overlay regions + if (!inHiddenRegion(elTop, elBottom, hiddenRegions)) { + convertToSidebar(); + isVisible = true; + } + } else { + // If the element is visible, hide it if it conflicts with overlay regions + // and insert a placeholder toggle (or if we're in reader mode) + if (inHiddenRegion(elTop, elBottom, hiddenRegions)) { + convertToMenu(); + isVisible = false; + } + } + } + } + }; + }; + + const tabEls = document.querySelectorAll('a[data-bs-toggle="tab"]'); + for (const tabEl of tabEls) { + const id = tabEl.getAttribute("data-bs-target"); + if (id) { + const columnEl = document.querySelector( + `${id} .column-margin, .tabset-margin-content` + ); + if (columnEl) + tabEl.addEventListener("shown.bs.tab", function (event) { + const el = event.srcElement; + if (el) { + const visibleCls = `${el.id}-margin-content`; + // walk up until we find a parent tabset + let panelTabsetEl = el.parentElement; + while (panelTabsetEl) { + if (panelTabsetEl.classList.contains("panel-tabset")) { + break; + } + panelTabsetEl = panelTabsetEl.parentElement; + } + + if (panelTabsetEl) { + const prevSib = panelTabsetEl.previousElementSibling; + if ( + prevSib && + prevSib.classList.contains("tabset-margin-container") + ) { + const childNodes = prevSib.querySelectorAll( + ".tabset-margin-content" + ); + for (const childEl of childNodes) { + if (childEl.classList.contains(visibleCls)) { + childEl.classList.remove("collapse"); + } else { + childEl.classList.add("collapse"); + } + } + } + } + } + + layoutMarginEls(); + }); + } + } + + // Manage the visibility of the toc and the sidebar + const marginScrollVisibility = manageSidebarVisiblity(marginSidebarEl, { + id: "quarto-toc-toggle", + titleSelector: "#toc-title", + dismissOnClick: true, + }); + const sidebarScrollVisiblity = manageSidebarVisiblity(sidebarEl, { + id: "quarto-sidebarnav-toggle", + titleSelector: ".title", + dismissOnClick: false, + }); + let tocLeftScrollVisibility; + if (leftTocEl) { + tocLeftScrollVisibility = manageSidebarVisiblity(leftTocEl, { + id: "quarto-lefttoc-toggle", + titleSelector: "#toc-title", + dismissOnClick: true, + }); + } + + // Find the first element that uses formatting in special columns + const conflictingEls = window.document.body.querySelectorAll( + '[class^="column-"], [class*=" column-"], aside, [class*="margin-caption"], [class*=" margin-caption"], [class*="margin-ref"], [class*=" margin-ref"]' + ); + + // Filter all the possibly conflicting elements into ones + // the do conflict on the left or ride side + const arrConflictingEls = Array.from(conflictingEls); + const leftSideConflictEls = arrConflictingEls.filter((el) => { + if (el.tagName === "ASIDE") { + return false; + } + return Array.from(el.classList).find((className) => { + return ( + className !== "column-body" && + className.startsWith("column-") && + !className.endsWith("right") && + !className.endsWith("container") && + className !== "column-margin" + ); + }); + }); + const rightSideConflictEls = arrConflictingEls.filter((el) => { + if (el.tagName === "ASIDE") { + return true; + } + + const hasMarginCaption = Array.from(el.classList).find((className) => { + return className == "margin-caption"; + }); + if (hasMarginCaption) { + return true; + } + + return Array.from(el.classList).find((className) => { + return ( + className !== "column-body" && + !className.endsWith("container") && + className.startsWith("column-") && + !className.endsWith("left") + ); + }); + }); + + const kOverlapPaddingSize = 10; + function toRegions(els) { + return els.map((el) => { + const boundRect = el.getBoundingClientRect(); + const top = + boundRect.top + + document.documentElement.scrollTop - + kOverlapPaddingSize; + return { + top, + bottom: top + el.scrollHeight + 2 * kOverlapPaddingSize, + }; + }); + } + + let hasObserved = false; + const visibleItemObserver = (els) => { + let visibleElements = [...els]; + const intersectionObserver = new IntersectionObserver( + (entries, _observer) => { + entries.forEach((entry) => { + if (entry.isIntersecting) { + if (visibleElements.indexOf(entry.target) === -1) { + visibleElements.push(entry.target); + } + } else { + visibleElements = visibleElements.filter((visibleEntry) => { + return visibleEntry !== entry; + }); + } + }); + + if (!hasObserved) { + hideOverlappedSidebars(); + } + hasObserved = true; + }, + {} + ); + els.forEach((el) => { + intersectionObserver.observe(el); + }); + + return { + getVisibleEntries: () => { + return visibleElements; + }, + }; + }; + + const rightElementObserver = visibleItemObserver(rightSideConflictEls); + const leftElementObserver = visibleItemObserver(leftSideConflictEls); + + const hideOverlappedSidebars = () => { + marginScrollVisibility(toRegions(rightElementObserver.getVisibleEntries())); + sidebarScrollVisiblity(toRegions(leftElementObserver.getVisibleEntries())); + if (tocLeftScrollVisibility) { + tocLeftScrollVisibility( + toRegions(leftElementObserver.getVisibleEntries()) + ); + } + }; + + window.quartoToggleReader = () => { + // Applies a slow class (or removes it) + // to update the transition speed + const slowTransition = (slow) => { + const manageTransition = (id, slow) => { + const el = document.getElementById(id); + if (el) { + if (slow) { + el.classList.add("slow"); + } else { + el.classList.remove("slow"); + } + } + }; + + manageTransition("TOC", slow); + manageTransition("quarto-sidebar", slow); + }; + const readerMode = !isReaderMode(); + setReaderModeValue(readerMode); + + // If we're entering reader mode, slow the transition + if (readerMode) { + slowTransition(readerMode); + } + highlightReaderToggle(readerMode); + hideOverlappedSidebars(); + + // If we're exiting reader mode, restore the non-slow transition + if (!readerMode) { + slowTransition(!readerMode); + } + }; + + const highlightReaderToggle = (readerMode) => { + const els = document.querySelectorAll(".quarto-reader-toggle"); + if (els) { + els.forEach((el) => { + if (readerMode) { + el.classList.add("reader"); + } else { + el.classList.remove("reader"); + } + }); + } + }; + + const setReaderModeValue = (val) => { + if (window.location.protocol !== "file:") { + window.localStorage.setItem("quarto-reader-mode", val); + } else { + localReaderMode = val; + } + }; + + const isReaderMode = () => { + if (window.location.protocol !== "file:") { + return window.localStorage.getItem("quarto-reader-mode") === "true"; + } else { + return localReaderMode; + } + }; + let localReaderMode = null; + + const tocOpenDepthStr = tocEl?.getAttribute("data-toc-expanded"); + const tocOpenDepth = tocOpenDepthStr ? Number(tocOpenDepthStr) : 1; + + // Walk the TOC and collapse/expand nodes + // Nodes are expanded if: + // - they are top level + // - they have children that are 'active' links + // - they are directly below an link that is 'active' + const walk = (el, depth) => { + // Tick depth when we enter a UL + if (el.tagName === "UL") { + depth = depth + 1; + } + + // It this is active link + let isActiveNode = false; + if (el.tagName === "A" && el.classList.contains("active")) { + isActiveNode = true; + } + + // See if there is an active child to this element + let hasActiveChild = false; + for (child of el.children) { + hasActiveChild = walk(child, depth) || hasActiveChild; + } + + // Process the collapse state if this is an UL + if (el.tagName === "UL") { + if (tocOpenDepth === -1 && depth > 1) { + el.classList.add("collapse"); + } else if ( + depth <= tocOpenDepth || + hasActiveChild || + prevSiblingIsActiveLink(el) + ) { + el.classList.remove("collapse"); + } else { + el.classList.add("collapse"); + } + + // untick depth when we leave a UL + depth = depth - 1; + } + return hasActiveChild || isActiveNode; + }; + + // walk the TOC and expand / collapse any items that should be shown + + if (tocEl) { + walk(tocEl, 0); + updateActiveLink(); + } + + // Throttle the scroll event and walk peridiocally + window.document.addEventListener( + "scroll", + throttle(() => { + if (tocEl) { + updateActiveLink(); + walk(tocEl, 0); + } + if (!isReaderMode()) { + hideOverlappedSidebars(); + } + }, 5) + ); + window.addEventListener( + "resize", + throttle(() => { + if (!isReaderMode()) { + hideOverlappedSidebars(); + } + }, 10) + ); + hideOverlappedSidebars(); + highlightReaderToggle(isReaderMode()); +}); + +// grouped tabsets +window.addEventListener("pageshow", (_event) => { + function getTabSettings() { + const data = localStorage.getItem("quarto-persistent-tabsets-data"); + if (!data) { + localStorage.setItem("quarto-persistent-tabsets-data", "{}"); + return {}; + } + if (data) { + return JSON.parse(data); + } + } + + function setTabSettings(data) { + localStorage.setItem( + "quarto-persistent-tabsets-data", + JSON.stringify(data) + ); + } + + function setTabState(groupName, groupValue) { + const data = getTabSettings(); + data[groupName] = groupValue; + setTabSettings(data); + } + + function toggleTab(tab, active) { + const tabPanelId = tab.getAttribute("aria-controls"); + const tabPanel = document.getElementById(tabPanelId); + if (active) { + tab.classList.add("active"); + tabPanel.classList.add("active"); + } else { + tab.classList.remove("active"); + tabPanel.classList.remove("active"); + } + } + + function toggleAll(selectedGroup, selectorsToSync) { + for (const [thisGroup, tabs] of Object.entries(selectorsToSync)) { + const active = selectedGroup === thisGroup; + for (const tab of tabs) { + toggleTab(tab, active); + } + } + } + + function findSelectorsToSyncByLanguage() { + const result = {}; + const tabs = Array.from( + document.querySelectorAll(`div[data-group] a[id^='tabset-']`) + ); + for (const item of tabs) { + const div = item.parentElement.parentElement.parentElement; + const group = div.getAttribute("data-group"); + if (!result[group]) { + result[group] = {}; + } + const selectorsToSync = result[group]; + const value = item.innerHTML; + if (!selectorsToSync[value]) { + selectorsToSync[value] = []; + } + selectorsToSync[value].push(item); + } + return result; + } + + function setupSelectorSync() { + const selectorsToSync = findSelectorsToSyncByLanguage(); + Object.entries(selectorsToSync).forEach(([group, tabSetsByValue]) => { + Object.entries(tabSetsByValue).forEach(([value, items]) => { + items.forEach((item) => { + item.addEventListener("click", (_event) => { + setTabState(group, value); + toggleAll(value, selectorsToSync[group]); + }); + }); + }); + }); + return selectorsToSync; + } + + const selectorsToSync = setupSelectorSync(); + for (const [group, selectedName] of Object.entries(getTabSettings())) { + const selectors = selectorsToSync[group]; + // it's possible that stale state gives us empty selections, so we explicitly check here. + if (selectors) { + toggleAll(selectedName, selectors); + } + } +}); + +function throttle(func, wait) { + let waiting = false; + return function () { + if (!waiting) { + func.apply(this, arguments); + waiting = true; + setTimeout(function () { + waiting = false; + }, wait); + } + }; +} + +function nexttick(func) { + return setTimeout(func, 0); +} diff --git a/site_libs/quarto-html/tippy.css b/site_libs/quarto-html/tippy.css new file mode 100644 index 0000000..e6ae635 --- /dev/null +++ b/site_libs/quarto-html/tippy.css @@ -0,0 +1 @@ +.tippy-box[data-animation=fade][data-state=hidden]{opacity:0}[data-tippy-root]{max-width:calc(100vw - 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b/site_libs/quarto-nav/quarto-nav.js @@ -0,0 +1,277 @@ +const headroomChanged = new CustomEvent("quarto-hrChanged", { + detail: {}, + bubbles: true, + cancelable: false, + composed: false, +}); + +window.document.addEventListener("DOMContentLoaded", function () { + let init = false; + + // Manage the back to top button, if one is present. + let lastScrollTop = window.pageYOffset || document.documentElement.scrollTop; + const scrollDownBuffer = 5; + const scrollUpBuffer = 35; + const btn = document.getElementById("quarto-back-to-top"); + const hideBackToTop = () => { + btn.style.display = "none"; + }; + const showBackToTop = () => { + btn.style.display = "inline-block"; + }; + if (btn) { + window.document.addEventListener( + "scroll", + function () { + const currentScrollTop = + window.pageYOffset || document.documentElement.scrollTop; + + // Shows and hides the button 'intelligently' as the user scrolls + if (currentScrollTop - scrollDownBuffer > lastScrollTop) { + hideBackToTop(); + lastScrollTop = currentScrollTop <= 0 ? 0 : currentScrollTop; + } else if (currentScrollTop < lastScrollTop - scrollUpBuffer) { + showBackToTop(); + lastScrollTop = currentScrollTop <= 0 ? 0 : currentScrollTop; + } + + // Show the button at the bottom, hides it at the top + if (currentScrollTop <= 0) { + hideBackToTop(); + } else if ( + window.innerHeight + currentScrollTop >= + document.body.offsetHeight + ) { + showBackToTop(); + } + }, + false + ); + } + + function throttle(func, wait) { + var timeout; + return function () { + const context = this; + const args = arguments; + const later = function () { + clearTimeout(timeout); + timeout = null; + func.apply(context, args); + }; + + if (!timeout) { + timeout = setTimeout(later, wait); + } + }; + } + + function headerOffset() { + // Set an offset if there is are fixed top navbar + const headerEl = window.document.querySelector("header.fixed-top"); + if (headerEl) { + return headerEl.clientHeight; + } else { + return 0; + } + } + + function footerOffset() { + const footerEl = window.document.querySelector("footer.footer"); + if (footerEl) { + return footerEl.clientHeight; + } else { + return 0; + } + } + + function updateDocumentOffsetWithoutAnimation() { + updateDocumentOffset(false); + } + + function updateDocumentOffset(animated) { + // set body offset + const topOffset = headerOffset(); + const bodyOffset = topOffset + footerOffset(); + const bodyEl = window.document.body; + bodyEl.setAttribute("data-bs-offset", topOffset); + bodyEl.style.paddingTop = topOffset + "px"; + + // deal with sidebar offsets + const sidebars = window.document.querySelectorAll( + ".sidebar, .headroom-target" + ); + sidebars.forEach((sidebar) => { + if (!animated) { + sidebar.classList.add("notransition"); + // Remove the no transition class after the animation has time to complete + setTimeout(function () { + sidebar.classList.remove("notransition"); + }, 201); + } + + if (window.Headroom && sidebar.classList.contains("sidebar-unpinned")) { + sidebar.style.top = "0"; + sidebar.style.maxHeight = "100vh"; + } else { + sidebar.style.top = topOffset + "px"; + sidebar.style.maxHeight = "calc(100vh - " + topOffset + "px)"; + } + }); + + // allow space for footer + const mainContainer = window.document.querySelector(".quarto-container"); + if (mainContainer) { + mainContainer.style.minHeight = "calc(100vh - " + bodyOffset + "px)"; + } + + // link offset + let linkStyle = window.document.querySelector("#quarto-target-style"); + if (!linkStyle) { + linkStyle = window.document.createElement("style"); + linkStyle.setAttribute("id", "quarto-target-style"); + window.document.head.appendChild(linkStyle); + } + while (linkStyle.firstChild) { + linkStyle.removeChild(linkStyle.firstChild); + } + if (topOffset > 0) { + linkStyle.appendChild( + window.document.createTextNode(` + section:target::before { + content: ""; + display: block; + height: ${topOffset}px; + margin: -${topOffset}px 0 0; + }`) + ); + } + if (init) { + window.dispatchEvent(headroomChanged); + } + init = true; + } + + // initialize headroom + var header = window.document.querySelector("#quarto-header"); + if (header && window.Headroom) { + const headroom = new window.Headroom(header, { + tolerance: 5, + onPin: function () { + const sidebars = window.document.querySelectorAll( + ".sidebar, .headroom-target" + ); + sidebars.forEach((sidebar) => { + sidebar.classList.remove("sidebar-unpinned"); + }); + updateDocumentOffset(); + }, + onUnpin: function () { + const sidebars = window.document.querySelectorAll( + ".sidebar, .headroom-target" + ); + sidebars.forEach((sidebar) => { + sidebar.classList.add("sidebar-unpinned"); + }); + updateDocumentOffset(); + }, + }); + headroom.init(); + + let frozen = false; + window.quartoToggleHeadroom = function () { + if (frozen) { + headroom.unfreeze(); + frozen = false; + } else { + headroom.freeze(); + frozen = true; + } + }; + } + + window.addEventListener( + "hashchange", + function (e) { + if ( + getComputedStyle(document.documentElement).scrollBehavior !== "smooth" + ) { + window.scrollTo(0, window.pageYOffset - headerOffset()); + } + }, + false + ); + + // Observe size changed for the header + const headerEl = window.document.querySelector("header.fixed-top"); + if (headerEl && window.ResizeObserver) { + const observer = new window.ResizeObserver( + updateDocumentOffsetWithoutAnimation + ); + observer.observe(headerEl, { + attributes: true, + childList: true, + characterData: true, + }); + } else { + window.addEventListener( + "resize", + throttle(updateDocumentOffsetWithoutAnimation, 50) + ); + } + setTimeout(updateDocumentOffsetWithoutAnimation, 250); + + // fixup index.html links if we aren't on the filesystem + if (window.location.protocol !== "file:") { + const links = window.document.querySelectorAll("a"); + for (let i = 0; i < links.length; i++) { + if (links[i].href) { + links[i].href = links[i].href.replace(/\/index\.html/, "/"); + } + } + + // Fixup any sharing links that require urls + // Append url to any sharing urls + const sharingLinks = window.document.querySelectorAll( + "a.sidebar-tools-main-item" + ); + for (let i = 0; i < sharingLinks.length; i++) { + const sharingLink = sharingLinks[i]; + const href = sharingLink.getAttribute("href"); + if (href) { + sharingLink.setAttribute( + "href", + href.replace("|url|", window.location.href) + ); + } + } + + // Scroll the active navigation item into view, if necessary + const navSidebar = window.document.querySelector("nav#quarto-sidebar"); + if (navSidebar) { + // Find the active item + const activeItem = navSidebar.querySelector("li.sidebar-item a.active"); + if (activeItem) { + // Wait for the scroll height and height to resolve by observing size changes on the + // nav element that is scrollable + const resizeObserver = new ResizeObserver((_entries) => { + // The bottom of the element + const elBottom = activeItem.offsetTop; + const viewBottom = navSidebar.scrollTop + navSidebar.clientHeight; + + // The element height and scroll height are the same, then we are still loading + if (viewBottom !== navSidebar.scrollHeight) { + // Determine if the item isn't visible and scroll to it + if (elBottom >= viewBottom) { + navSidebar.scrollTop = elBottom; + } + + // stop observing now since we've completed the scroll + resizeObserver.unobserve(navSidebar); + } + }); + resizeObserver.observe(navSidebar); + } + } + } +}); diff --git a/site_libs/quarto-search/autocomplete.umd.js b/site_libs/quarto-search/autocomplete.umd.js new file mode 100644 index 0000000..619c57c --- /dev/null +++ b/site_libs/quarto-search/autocomplete.umd.js @@ -0,0 +1,3 @@ +/*! @algolia/autocomplete-js 1.7.3 | MIT License | © Algolia, Inc. and contributors | https://github.com/algolia/autocomplete */ +!function(e,t){"object"==typeof exports&&"undefined"!=typeof module?t(exports):"function"==typeof define&&define.amd?define(["exports"],t):t((e="undefined"!=typeof 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Apache Software License 2.0 + * + * http://www.apache.org/licenses/LICENSE-2.0 + */ +var e,t;e=this,t=function(){"use strict";function e(e,t){var n=Object.keys(e);if(Object.getOwnPropertySymbols){var r=Object.getOwnPropertySymbols(e);t&&(r=r.filter((function(t){return Object.getOwnPropertyDescriptor(e,t).enumerable}))),n.push.apply(n,r)}return n}function t(t){for(var n=1;ne.length)&&(t=e.length);for(var n=0,r=new Array(t);n0&&void 0!==arguments[0]?arguments[0]:1,t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:3,n=new Map,r=Math.pow(10,t);return{get:function(t){var i=t.match(C).length;if(n.has(i))return n.get(i);var o=1/Math.pow(i,.5*e),c=parseFloat(Math.round(o*r)/r);return n.set(i,c),c},clear:function(){n.clear()}}}var $=function(){function e(){var t=arguments.length>0&&void 0!==arguments[0]?arguments[0]:{},n=t.getFn,i=void 0===n?I.getFn:n,o=t.fieldNormWeight,c=void 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a/site_libs/quarto-search/quarto-search.js b/site_libs/quarto-search/quarto-search.js new file mode 100644 index 0000000..f5d852d --- /dev/null +++ b/site_libs/quarto-search/quarto-search.js @@ -0,0 +1,1140 @@ +const kQueryArg = "q"; +const kResultsArg = "show-results"; + +// If items don't provide a URL, then both the navigator and the onSelect +// function aren't called (and therefore, the default implementation is used) +// +// We're using this sentinel URL to signal to those handlers that this +// item is a more item (along with the type) and can be handled appropriately +const kItemTypeMoreHref = "0767FDFD-0422-4E5A-BC8A-3BE11E5BBA05"; + +window.document.addEventListener("DOMContentLoaded", function (_event) { + // Ensure that search is available on this page. If it isn't, + // should return early and not do anything + var searchEl = window.document.getElementById("quarto-search"); + if (!searchEl) return; + + const { autocomplete } = window["@algolia/autocomplete-js"]; + + let quartoSearchOptions = {}; + let language = {}; + const searchOptionEl = window.document.getElementById( + "quarto-search-options" + ); + if (searchOptionEl) { + const jsonStr = searchOptionEl.textContent; + quartoSearchOptions = JSON.parse(jsonStr); + language = quartoSearchOptions.language; + } + + // note the search mode + if (quartoSearchOptions.type === "overlay") { + searchEl.classList.add("type-overlay"); + } else { + searchEl.classList.add("type-textbox"); + } + + // Used to determine highlighting behavior for this page + // A `q` query param is expected when the user follows a search + // to this page + const currentUrl = new URL(window.location); + const query = currentUrl.searchParams.get(kQueryArg); + const showSearchResults = currentUrl.searchParams.get(kResultsArg); + const mainEl = window.document.querySelector("main"); + + // highlight matches on the page + if (query !== null && mainEl) { + // perform any highlighting + highlight(escapeRegExp(query), mainEl); + + // fix up the URL to remove the q query param + const replacementUrl = new URL(window.location); + replacementUrl.searchParams.delete(kQueryArg); + window.history.replaceState({}, "", replacementUrl); + } + + // function to clear highlighting on the page when the search query changes + // (e.g. if the user edits the query or clears it) + let highlighting = true; + const resetHighlighting = (searchTerm) => { + if (mainEl && highlighting && query !== null && searchTerm !== query) { + clearHighlight(query, mainEl); + highlighting = false; + } + }; + + // Clear search highlighting when the user scrolls sufficiently + const resetFn = () => { + resetHighlighting(""); + window.removeEventListener("quarto-hrChanged", resetFn); + window.removeEventListener("quarto-sectionChanged", resetFn); + }; + + // Register this event after the initial scrolling and settling of events + // on the page + window.addEventListener("quarto-hrChanged", resetFn); + window.addEventListener("quarto-sectionChanged", resetFn); + + // Responsively switch to overlay mode if the search is present on the navbar + // Note that switching the sidebar to overlay mode requires more coordinate (not just + // the media query since we generate different HTML for sidebar overlays than we do + // for sidebar input UI) + const detachedMediaQuery = + quartoSearchOptions.type === "overlay" ? "all" : "(max-width: 991px)"; + + // If configured, include the analytics client to send insights + const plugins = configurePlugins(quartoSearchOptions); + + let lastState = null; + const { setIsOpen, setQuery, setCollections } = autocomplete({ + container: searchEl, + detachedMediaQuery: detachedMediaQuery, + defaultActiveItemId: 0, + panelContainer: "#quarto-search-results", + panelPlacement: quartoSearchOptions["panel-placement"], + debug: false, + openOnFocus: true, + plugins, + classNames: { + form: "d-flex", + }, + translations: { + clearButtonTitle: language["search-clear-button-title"], + detachedCancelButtonText: language["search-detached-cancel-button-title"], + submitButtonTitle: language["search-submit-button-title"], + }, + initialState: { + query, + }, + getItemUrl({ item }) { + return item.href; + }, + onStateChange({ state }) { + // Perhaps reset highlighting + resetHighlighting(state.query); + + // If the panel just opened, ensure the panel is positioned properly + if (state.isOpen) { + if (lastState && !lastState.isOpen) { + setTimeout(() => { + positionPanel(quartoSearchOptions["panel-placement"]); + }, 150); + } + } + + // Perhaps show the copy link + showCopyLink(state.query, quartoSearchOptions); + + lastState = state; + }, + reshape({ sources, state }) { + return sources.map((source) => { + try { + const items = source.getItems(); + + // Validate the items + validateItems(items); + + // group the items by document + const groupedItems = new Map(); + items.forEach((item) => { + const hrefParts = item.href.split("#"); + const baseHref = hrefParts[0]; + const isDocumentItem = hrefParts.length === 1; + + const items = groupedItems.get(baseHref); + if (!items) { + groupedItems.set(baseHref, [item]); + } else { + // If the href for this item matches the document + // exactly, place this item first as it is the item that represents + // the document itself + if (isDocumentItem) { + items.unshift(item); + } else { + items.push(item); + } + groupedItems.set(baseHref, items); + } + }); + + const reshapedItems = []; + let count = 1; + for (const [_key, value] of groupedItems) { + const firstItem = value[0]; + reshapedItems.push({ + ...firstItem, + type: kItemTypeDoc, + }); + + const collapseMatches = quartoSearchOptions["collapse-after"]; + const collapseCount = + typeof collapseMatches === "number" ? collapseMatches : 1; + + if (value.length > 1) { + const target = `search-more-${count}`; + const isExpanded = + state.context.expanded && + state.context.expanded.includes(target); + + const remainingCount = value.length - collapseCount; + + for (let i = 1; i < value.length; i++) { + if (collapseMatches && i === collapseCount) { + reshapedItems.push({ + target, + title: isExpanded + ? language["search-hide-matches-text"] + : remainingCount === 1 + ? `${remainingCount} ${language["search-more-match-text"]}` + : `${remainingCount} ${language["search-more-matches-text"]}`, + type: kItemTypeMore, + href: kItemTypeMoreHref, + }); + } + + if (isExpanded || !collapseMatches || i < collapseCount) { + reshapedItems.push({ + ...value[i], + type: kItemTypeItem, + target, + }); + } + } + } + count += 1; + } + + return { + ...source, + getItems() { + return reshapedItems; + }, + }; + } catch (error) { + // Some form of error occurred + return { + ...source, + getItems() { + return [ + { + title: error.name || "An Error Occurred While Searching", + text: + error.message || + "An unknown error occurred while attempting to perform the requested search.", + type: kItemTypeError, + }, + ]; + }, + }; + } + }); + }, + navigator: { + navigate({ itemUrl }) { + if (itemUrl !== offsetURL(kItemTypeMoreHref)) { + window.location.assign(itemUrl); + } + }, + navigateNewTab({ itemUrl }) { + if (itemUrl !== offsetURL(kItemTypeMoreHref)) { + const windowReference = window.open(itemUrl, "_blank", "noopener"); + if (windowReference) { + windowReference.focus(); + } + } + }, + navigateNewWindow({ itemUrl }) { + if (itemUrl !== offsetURL(kItemTypeMoreHref)) { + window.open(itemUrl, "_blank", "noopener"); + } + }, + }, + getSources({ state, setContext, setActiveItemId, refresh }) { + return [ + { + sourceId: "documents", + getItemUrl({ item }) { + if (item.href) { + return offsetURL(item.href); + } else { + return undefined; + } + }, + onSelect({ + item, + state, + setContext, + setIsOpen, + setActiveItemId, + refresh, + }) { + if (item.type === kItemTypeMore) { + toggleExpanded(item, state, setContext, setActiveItemId, refresh); + + // Toggle more + setIsOpen(true); + } + }, + getItems({ query }) { + if (query === null || query === "") { + return []; + } + + const limit = quartoSearchOptions.limit; + if (quartoSearchOptions.algolia) { + return algoliaSearch(query, limit, quartoSearchOptions.algolia); + } else { + // Fuse search options + const fuseSearchOptions = { + isCaseSensitive: false, + shouldSort: true, + minMatchCharLength: 2, + limit: limit, + }; + + return readSearchData().then(function (fuse) { + return fuseSearch(query, fuse, fuseSearchOptions); + }); + } + }, + templates: { + noResults({ createElement }) { + const hasQuery = lastState.query; + + return createElement( + "div", + { + class: `quarto-search-no-results${ + hasQuery ? "" : " no-query" + }`, + }, + language["search-no-results-text"] + ); + }, + header({ items, createElement }) { + // count the documents + const count = items.filter((item) => { + return item.type === kItemTypeDoc; + }).length; + + if (count > 0) { + return createElement( + "div", + { class: "search-result-header" }, + `${count} ${language["search-matching-documents-text"]}` + ); + } else { + return createElement( + "div", + { class: "search-result-header-no-results" }, + `` + ); + } + }, + footer({ _items, createElement }) { + if ( + quartoSearchOptions.algolia && + quartoSearchOptions.algolia["show-logo"] + ) { + const libDir = quartoSearchOptions.algolia["libDir"]; + const logo = createElement("img", { + src: offsetURL( + `${libDir}/quarto-search/search-by-algolia.svg` + ), + class: "algolia-search-logo", + }); + return createElement( + "a", + { href: "http://www.algolia.com/" }, + logo + ); + } + }, + + item({ item, createElement }) { + return renderItem( + item, + createElement, + state, + setActiveItemId, + setContext, + refresh + ); + }, + }, + }, + ]; + }, + }); + + window.quartoOpenSearch = () => { + setIsOpen(false); + setIsOpen(true); + focusSearchInput(); + }; + + // Remove the labeleledby attribute since it is pointing + // to a non-existent label + if (quartoSearchOptions.type === "overlay") { + const inputEl = window.document.querySelector( + "#quarto-search .aa-Autocomplete" + ); + if (inputEl) { + inputEl.removeAttribute("aria-labelledby"); + } + } + + // If the main document scrolls dismiss the search results + // (otherwise, since they're floating in the document they can scroll with the document) + window.document.body.onscroll = () => { + setIsOpen(false); + }; + + if (showSearchResults) { + setIsOpen(true); + focusSearchInput(); + } +}); + +function configurePlugins(quartoSearchOptions) { + const autocompletePlugins = []; + const algoliaOptions = quartoSearchOptions.algolia; + if ( + algoliaOptions && + algoliaOptions["analytics-events"] && + algoliaOptions["search-only-api-key"] && + algoliaOptions["application-id"] + ) { + const apiKey = algoliaOptions["search-only-api-key"]; + const appId = algoliaOptions["application-id"]; + + // Aloglia insights may not be loaded because they require cookie consent + // Use deferred loading so events will start being recorded when/if consent + // is granted. + const algoliaInsightsDeferredPlugin = deferredLoadPlugin(() => { + if ( + window.aa && + window["@algolia/autocomplete-plugin-algolia-insights"] + ) { + window.aa("init", { + appId, + apiKey, + useCookie: true, + }); + + const { createAlgoliaInsightsPlugin } = + window["@algolia/autocomplete-plugin-algolia-insights"]; + // Register the insights client + const algoliaInsightsPlugin = createAlgoliaInsightsPlugin({ + insightsClient: window.aa, + onItemsChange({ insights, insightsEvents }) { + const events = insightsEvents.map((event) => { + const maxEvents = event.objectIDs.slice(0, 20); + return { + ...event, + objectIDs: maxEvents, + }; + }); + + insights.viewedObjectIDs(...events); + }, + }); + return algoliaInsightsPlugin; + } + }); + + // Add the plugin + autocompletePlugins.push(algoliaInsightsDeferredPlugin); + return autocompletePlugins; + } +} + +// For plugins that may not load immediately, create a wrapper +// plugin and forward events and plugin data once the plugin +// is initialized. This is useful for cases like cookie consent +// which may prevent the analytics insights event plugin from initializing +// immediately. +function deferredLoadPlugin(createPlugin) { + let plugin = undefined; + let subscribeObj = undefined; + const wrappedPlugin = () => { + if (!plugin && subscribeObj) { + plugin = createPlugin(); + if (plugin && plugin.subscribe) { + plugin.subscribe(subscribeObj); + } + } + return plugin; + }; + + return { + subscribe: (obj) => { + subscribeObj = obj; + }, + onStateChange: (obj) => { + const plugin = wrappedPlugin(); + if (plugin && plugin.onStateChange) { + plugin.onStateChange(obj); + } + }, + onSubmit: (obj) => { + const plugin = wrappedPlugin(); + if (plugin && plugin.onSubmit) { + plugin.onSubmit(obj); + } + }, + onReset: (obj) => { + const plugin = wrappedPlugin(); + if (plugin && plugin.onReset) { + plugin.onReset(obj); + } + }, + getSources: (obj) => { + const plugin = wrappedPlugin(); + if (plugin && plugin.getSources) { + return plugin.getSources(obj); + } else { + return Promise.resolve([]); + } + }, + data: (obj) => { + const plugin = wrappedPlugin(); + if (plugin && plugin.data) { + plugin.data(obj); + } + }, + }; +} + +function validateItems(items) { + // Validate the first item + if (items.length > 0) { + const item = items[0]; + const missingFields = []; + if (item.href == undefined) { + missingFields.push("href"); + } + if (!item.title == undefined) { + missingFields.push("title"); + } + if (!item.text == undefined) { + missingFields.push("text"); + } + + if (missingFields.length === 1) { + throw { + name: `Error: Search index is missing the ${missingFields[0]} field.`, + message: `The items being returned for this search do not include all the required fields. Please ensure that your index items include the ${missingFields[0]} field or use index-fields in your _quarto.yml file to specify the field names.`, + }; + } else if (missingFields.length > 1) { + const missingFieldList = missingFields + .map((field) => { + return `${field}`; + }) + .join(", "); + + throw { + name: `Error: Search index is missing the following fields: ${missingFieldList}.`, + message: `The items being returned for this search do not include all the required fields. Please ensure that your index items includes the following fields: ${missingFieldList}, or use index-fields in your _quarto.yml file to specify the field names.`, + }; + } + } +} + +let lastQuery = null; +function showCopyLink(query, options) { + const language = options.language; + lastQuery = query; + // Insert share icon + const inputSuffixEl = window.document.body.querySelector( + ".aa-Form .aa-InputWrapperSuffix" + ); + + if (inputSuffixEl) { + let copyButtonEl = window.document.body.querySelector( + ".aa-Form .aa-InputWrapperSuffix .aa-CopyButton" + ); + + if (copyButtonEl === null) { + copyButtonEl = window.document.createElement("button"); + copyButtonEl.setAttribute("class", "aa-CopyButton"); + copyButtonEl.setAttribute("type", "button"); + copyButtonEl.setAttribute("title", language["search-copy-link-title"]); + copyButtonEl.onmousedown = (e) => { + e.preventDefault(); + e.stopPropagation(); + }; + + const linkIcon = "bi-clipboard"; + const checkIcon = "bi-check2"; + + const shareIconEl = window.document.createElement("i"); + shareIconEl.setAttribute("class", `bi ${linkIcon}`); + copyButtonEl.appendChild(shareIconEl); + inputSuffixEl.prepend(copyButtonEl); + + const clipboard = new window.ClipboardJS(".aa-CopyButton", { + text: function (_trigger) { + const copyUrl = new URL(window.location); + copyUrl.searchParams.set(kQueryArg, lastQuery); + copyUrl.searchParams.set(kResultsArg, "1"); + return copyUrl.toString(); + }, + }); + clipboard.on("success", function (e) { + // Focus the input + + // button target + const button = e.trigger; + const icon = button.querySelector("i.bi"); + + // flash "checked" + icon.classList.add(checkIcon); + icon.classList.remove(linkIcon); + setTimeout(function () { + icon.classList.remove(checkIcon); + icon.classList.add(linkIcon); + }, 1000); + }); + } + + // If there is a query, show the link icon + if (copyButtonEl) { + if (lastQuery && options["copy-button"]) { + copyButtonEl.style.display = "flex"; + } else { + copyButtonEl.style.display = "none"; + } + } + } +} + +/* Search Index Handling */ +// create the index +var fuseIndex = undefined; +async function readSearchData() { + // Initialize the search index on demand + if (fuseIndex === undefined) { + // create fuse index + const options = { + keys: [ + { name: "title", weight: 20 }, + { name: "section", weight: 20 }, + { name: "text", weight: 10 }, + ], + ignoreLocation: true, + threshold: 0.1, + }; + const fuse = new window.Fuse([], options); + + // fetch the main search.json + const response = await fetch(offsetURL("search.json")); + if (response.status == 200) { + return response.json().then(function (searchDocs) { + searchDocs.forEach(function (searchDoc) { + fuse.add(searchDoc); + }); + fuseIndex = fuse; + return fuseIndex; + }); + } else { + return Promise.reject( + new Error( + "Unexpected status from search index request: " + response.status + ) + ); + } + } + return fuseIndex; +} + +function inputElement() { + return window.document.body.querySelector(".aa-Form .aa-Input"); +} + +function focusSearchInput() { + setTimeout(() => { + const inputEl = inputElement(); + if (inputEl) { + inputEl.focus(); + } + }, 50); +} + +/* Panels */ +const kItemTypeDoc = "document"; +const kItemTypeMore = "document-more"; +const kItemTypeItem = "document-item"; +const kItemTypeError = "error"; + +function renderItem( + item, + createElement, + state, + setActiveItemId, + setContext, + refresh +) { + switch (item.type) { + case kItemTypeDoc: + return createDocumentCard( + createElement, + "file-richtext", + item.title, + item.section, + item.text, + item.href + ); + case kItemTypeMore: + return createMoreCard( + createElement, + item, + state, + setActiveItemId, + setContext, + refresh + ); + case kItemTypeItem: + return createSectionCard( + createElement, + item.section, + item.text, + item.href + ); + case kItemTypeError: + return createErrorCard(createElement, item.title, item.text); + default: + return undefined; + } +} + +function createDocumentCard(createElement, icon, title, section, text, href) { + const iconEl = createElement("i", { + class: `bi bi-${icon} search-result-icon`, + }); + const titleEl = createElement("p", { class: "search-result-title" }, title); + const titleContainerEl = createElement( + "div", + { class: "search-result-title-container" }, + [iconEl, titleEl] + ); + + const textEls = []; + if (section) { + const sectionEl = createElement( + "p", + { class: "search-result-section" }, + section + ); + textEls.push(sectionEl); + } + const descEl = createElement("p", { + class: "search-result-text", + dangerouslySetInnerHTML: { + __html: text, + }, + }); + textEls.push(descEl); + + const textContainerEl = createElement( + "div", + { class: "search-result-text-container" }, + textEls + ); + + const containerEl = createElement( + "div", + { + class: "search-result-container", + }, + [titleContainerEl, textContainerEl] + ); + + const linkEl = createElement( + "a", + { + href: offsetURL(href), + class: "search-result-link", + }, + containerEl + ); + + const classes = ["search-result-doc", "search-item"]; + if (!section) { + classes.push("document-selectable"); + } + + return createElement( + "div", + { + class: classes.join(" "), + }, + linkEl + ); +} + +function createMoreCard( + createElement, + item, + state, + setActiveItemId, + setContext, + refresh +) { + const moreCardEl = createElement( + "div", + { + class: "search-result-more search-item", + onClick: (e) => { + // Handle expanding the sections by adding the expanded + // section to the list of expanded sections + toggleExpanded(item, state, setContext, setActiveItemId, refresh); + e.stopPropagation(); + }, + }, + item.title + ); + + return moreCardEl; +} + +function toggleExpanded(item, state, setContext, setActiveItemId, refresh) { + const expanded = state.context.expanded || []; + if (expanded.includes(item.target)) { + setContext({ + expanded: expanded.filter((target) => target !== item.target), + }); + } else { + setContext({ expanded: [...expanded, item.target] }); + } + + refresh(); + setActiveItemId(item.__autocomplete_id); +} + +function createSectionCard(createElement, section, text, href) { + const sectionEl = createSection(createElement, section, text, href); + return createElement( + "div", + { + class: "search-result-doc-section search-item", + }, + sectionEl + ); +} + +function createSection(createElement, title, text, href) { + const descEl = createElement("p", { + class: "search-result-text", + dangerouslySetInnerHTML: { + __html: text, + }, + }); + + const titleEl = createElement("p", { class: "search-result-section" }, title); + const linkEl = createElement( + "a", + { + href: offsetURL(href), + class: "search-result-link", + }, + [titleEl, descEl] + ); + return linkEl; +} + +function createErrorCard(createElement, title, text) { + const descEl = createElement("p", { + class: "search-error-text", + dangerouslySetInnerHTML: { + __html: text, + }, + }); + + const titleEl = createElement("p", { + class: "search-error-title", + dangerouslySetInnerHTML: { + __html: ` ${title}`, + }, + }); + const errorEl = createElement("div", { class: "search-error" }, [ + titleEl, + descEl, + ]); + return errorEl; +} + +function positionPanel(pos) { + const panelEl = window.document.querySelector( + "#quarto-search-results .aa-Panel" + ); + const inputEl = window.document.querySelector( + "#quarto-search .aa-Autocomplete" + ); + + if (panelEl && inputEl) { + panelEl.style.top = `${Math.round(panelEl.offsetTop)}px`; + if (pos === "start") { + panelEl.style.left = `${Math.round(inputEl.left)}px`; + } else { + panelEl.style.right = `${Math.round(inputEl.offsetRight)}px`; + } + } +} + +/* Highlighting */ +// highlighting functions +function highlightMatch(query, text) { + if (text) { + const start = text.toLowerCase().indexOf(query.toLowerCase()); + if (start !== -1) { + const startMark = ""; + const endMark = ""; + + const end = start + query.length; + text = + text.slice(0, start) + + startMark + + text.slice(start, end) + + endMark + + text.slice(end); + const startInfo = clipStart(text, start); + const endInfo = clipEnd( + text, + startInfo.position + startMark.length + endMark.length + ); + text = + startInfo.prefix + + text.slice(startInfo.position, endInfo.position) + + endInfo.suffix; + + return text; + } else { + return text; + } + } else { + return text; + } +} + +function clipStart(text, pos) { + const clipStart = pos - 50; + if (clipStart < 0) { + // This will just return the start of the string + return { + position: 0, + prefix: "", + }; + } else { + // We're clipping before the start of the string, walk backwards to the first space. + const spacePos = findSpace(text, pos, -1); + return { + position: spacePos.position, + prefix: "", + }; + } +} + +function clipEnd(text, pos) { + const clipEnd = pos + 200; + if (clipEnd > text.length) { + return { + position: text.length, + suffix: "", + }; + } else { + const spacePos = findSpace(text, clipEnd, 1); + return { + position: spacePos.position, + suffix: spacePos.clipped ? "…" : "", + }; + } +} + +function findSpace(text, start, step) { + let stepPos = start; + while (stepPos > -1 && stepPos < text.length) { + const char = text[stepPos]; + if (char === " " || char === "," || char === ":") { + return { + position: step === 1 ? stepPos : stepPos - step, + clipped: stepPos > 1 && stepPos < text.length, + }; + } + stepPos = stepPos + step; + } + + return { + position: stepPos - step, + clipped: false, + }; +} + +// removes highlighting as implemented by the mark tag +function clearHighlight(searchterm, el) { + const childNodes = el.childNodes; + for (let i = childNodes.length - 1; i >= 0; i--) { + const node = childNodes[i]; + if (node.nodeType === Node.ELEMENT_NODE) { + if ( + node.tagName === "MARK" && + node.innerText.toLowerCase() === searchterm.toLowerCase() + ) { + el.replaceChild(document.createTextNode(node.innerText), node); + } else { + clearHighlight(searchterm, node); + } + } + } +} + +function escapeRegExp(string) { + return string.replace(/[.*+?^${}()|[\]\\]/g, "\\$&"); // $& means the whole matched string +} + +// highlight matches +function highlight(term, el) { + const termRegex = new RegExp(term, "ig"); + const childNodes = el.childNodes; + + // walk back to front avoid mutating elements in front of us + for (let i = childNodes.length - 1; i >= 0; i--) { + const node = childNodes[i]; + + if (node.nodeType === Node.TEXT_NODE) { + // Search text nodes for text to highlight + const text = node.nodeValue; + + let startIndex = 0; + let matchIndex = text.search(termRegex); + if (matchIndex > -1) { + const markFragment = document.createDocumentFragment(); + while (matchIndex > -1) { + const prefix = text.slice(startIndex, matchIndex); + markFragment.appendChild(document.createTextNode(prefix)); + + const mark = document.createElement("mark"); + mark.appendChild( + document.createTextNode( + text.slice(matchIndex, matchIndex + term.length) + ) + ); + markFragment.appendChild(mark); + + startIndex = matchIndex + term.length; + matchIndex = text.slice(startIndex).search(new RegExp(term, "ig")); + if (matchIndex > -1) { + matchIndex = startIndex + matchIndex; + } + } + if (startIndex < text.length) { + markFragment.appendChild( + document.createTextNode(text.slice(startIndex, text.length)) + ); + } + + el.replaceChild(markFragment, node); + } + } else if (node.nodeType === Node.ELEMENT_NODE) { + // recurse through elements + highlight(term, node); + } + } +} + +/* Link Handling */ +// get the offset from this page for a given site root relative url +function offsetURL(url) { + var offset = getMeta("quarto:offset"); + return offset ? offset + url : url; +} + +// read a meta tag value +function getMeta(metaName) { + var metas = window.document.getElementsByTagName("meta"); + for (let i = 0; i < metas.length; i++) { + if (metas[i].getAttribute("name") === metaName) { + return metas[i].getAttribute("content"); + } + } + return ""; +} + +function algoliaSearch(query, limit, algoliaOptions) { + const { getAlgoliaResults } = window["@algolia/autocomplete-preset-algolia"]; + + const applicationId = algoliaOptions["application-id"]; + const searchOnlyApiKey = algoliaOptions["search-only-api-key"]; + const indexName = algoliaOptions["index-name"]; + const indexFields = algoliaOptions["index-fields"]; + const searchClient = window.algoliasearch(applicationId, searchOnlyApiKey); + const searchParams = algoliaOptions["params"]; + const searchAnalytics = !!algoliaOptions["analytics-events"]; + + return getAlgoliaResults({ + searchClient, + queries: [ + { + indexName: indexName, + query, + params: { + hitsPerPage: limit, + clickAnalytics: searchAnalytics, + ...searchParams, + }, + }, + ], + transformResponse: (response) => { + if (!indexFields) { + return response.hits.map((hit) => { + return hit.map((item) => { + return { + ...item, + text: highlightMatch(query, item.text), + }; + }); + }); + } else { + const remappedHits = response.hits.map((hit) => { + return hit.map((item) => { + const newItem = { ...item }; + ["href", "section", "title", "text"].forEach((keyName) => { + const mappedName = indexFields[keyName]; + if ( + mappedName && + item[mappedName] !== undefined && + mappedName !== keyName + ) { + newItem[keyName] = item[mappedName]; + delete newItem[mappedName]; + } + }); + newItem.text = highlightMatch(query, newItem.text); + return newItem; + }); + }); + return remappedHits; + } + }, + }); +} + +function fuseSearch(query, fuse, fuseOptions) { + return fuse.search(query, fuseOptions).map((result) => { + const addParam = (url, name, value) => { + const anchorParts = url.split("#"); + const baseUrl = anchorParts[0]; + const sep = baseUrl.search("\\?") > 0 ? "&" : "?"; + anchorParts[0] = baseUrl + sep + name + "=" + value; + return anchorParts.join("#"); + }; + + return { + title: result.item.title, + section: result.item.section, + href: addParam(result.item.href, kQueryArg, query), + text: highlightMatch(query, result.item.text), + }; + }); +} diff --git a/sitemap.xml b/sitemap.xml new file mode 100644 index 0000000..29ecf1e --- /dev/null +++ b/sitemap.xml @@ -0,0 +1,95 @@ + + + + https://michaelaye.github.io/planetarypy/index.html + 2024-01-16T00:14:29.042Z + + + https://michaelaye.github.io/planetarypy/tutorials/tutorial.html + 2024-01-16T00:14:28.054Z + + + https://michaelaye.github.io/planetarypy/tutorials/pdw_2023.html + 2024-01-16T00:14:25.546Z + + + https://michaelaye.github.io/planetarypy/api/pds.utils.html + 2024-01-16T00:14:23.350Z + + + https://michaelaye.github.io/planetarypy/api/cassini_iss.html + 2024-01-16T00:14:22.190Z + + + https://michaelaye.github.io/planetarypy/api/pds.indexes.html + 2024-01-16T00:14:21.346Z + + + https://michaelaye.github.io/planetarypy/api/diviner.html + 2024-01-16T00:14:18.878Z + + + https://michaelaye.github.io/planetarypy/api/cassini_uvis.html + 2024-01-16T00:14:17.438Z + + + https://michaelaye.github.io/planetarypy/api/pds.opusapi.html + 2024-01-16T00:14:16.298Z + + + https://michaelaye.github.io/planetarypy/api/pds.ctx_index.html + 2024-01-16T00:14:15.794Z + + + https://michaelaye.github.io/planetarypy/api/config.html + 2024-01-16T00:14:14.978Z + + + https://michaelaye.github.io/planetarypy/api/pds.lroc_index.html + 2024-01-16T00:14:13.922Z + + + https://michaelaye.github.io/planetarypy/api/geotools.html + 2024-01-16T00:14:14.586Z + + + https://michaelaye.github.io/planetarypy/api/utils.html + 2024-01-16T00:14:15.498Z + + + https://michaelaye.github.io/planetarypy/api/exceptions.html + 2024-01-16T00:14:16.054Z + + + https://michaelaye.github.io/planetarypy/api/hirise.html + 2024-01-16T00:14:16.842Z + + + https://michaelaye.github.io/planetarypy/api/pds.apps.html + 2024-01-16T00:14:18.606Z + + + https://michaelaye.github.io/planetarypy/api/ctx.html + 2024-01-16T00:14:21.014Z + + + https://michaelaye.github.io/planetarypy/api/pds.crism_index.html + 2024-01-16T00:14:21.878Z + + + https://michaelaye.github.io/planetarypy/api/spice.kernels.html + 2024-01-16T00:14:23.010Z + + + https://michaelaye.github.io/planetarypy/tutorials/pdw2023_demo.html + 2024-01-16T00:14:24.626Z + + + https://michaelaye.github.io/planetarypy/tutorials/apps_demo.html + 2024-01-16T00:14:27.202Z + + + https://michaelaye.github.io/planetarypy/tutorials/spice_howtos.html + 2024-01-16T00:14:28.362Z + + diff --git a/styles.css b/styles.css new file mode 100644 index 0000000..b46c209 --- /dev/null +++ b/styles.css @@ -0,0 +1,18 @@ +.cell-output pre { + margin-left: 0.8rem; + margin-top: 0; + background: none; + border-left: 2px solid lightsalmon; + border-top-left-radius: 0; + border-top-right-radius: 0; + } + + .cell-output .sourceCode { + background: none; + margin-top: 0; + } + + .cell > .sourceCode { + margin-bottom: 0; + } + \ No newline at end of file diff --git a/tutorials/PDW2023_Demo_files/figure-html/cell-19-output-1.png b/tutorials/PDW2023_Demo_files/figure-html/cell-19-output-1.png new file mode 100644 index 0000000..d4dd4b3 Binary files /dev/null and b/tutorials/PDW2023_Demo_files/figure-html/cell-19-output-1.png differ diff --git a/tutorials/apps_demo.html b/tutorials/apps_demo.html new file mode 100644 index 0000000..b1932b7 --- /dev/null +++ b/tutorials/apps_demo.html @@ -0,0 +1,2725 @@ + + + + + + + + + +planetarypy - PlanetaryPy Demo + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

PlanetaryPy Demo

+
+ + + +
+ + + + +
+ + +
+ + +
+

Time and Network utils

+
+

Times

+
+
from planetarypy import utils
+
+
+

Do you remember that the string conversion code for “day-of-year” is %j ?

+
+
+

Do we want newcomers search for that in Python docs?

+
+
+
times = ["2002-137", "2005-234T13:00:00.123"]
+
+
+
isotimes = [utils.nasa_time_to_iso(t) for t in times]
+isotimes
+
+
['2002-05-17', '2005-08-22T13:00:00.123000']
+
+
+
+
[utils.iso_to_nasa_time(t) for t in isotimes]
+
+
['2002-137', '2005-234T13:00:00.123000']
+
+
+
+
+

Network

+
+
utils.check_url_exists("https://michaelaye.github.io")
+
+
True
+
+
+
+
utils.check_url_exists?
+
+
+
Signature: utils.check_url_exists(url)
+Docstring: <no docstring>
+File:      ~/Dropbox/src/nbplanetary/planetarypy/utils.py
+Type:      function
+
+
+
+
+
utils.have_internet()
+
+
True
+
+
+
+
utils.url_retrieve(
+    "https://michaelaye.github.io/talks/2021-conda-workshop-kharkiv/conda_talk_Kharkiv_conference.pdf",
+    "talk_slides.pdf",
+)
+
+ +
+
+
+
+
+

PDS Indexes

+
+
from planetarypy.pds.apps import find_indexes, get_index, find_instruments
+
+
+
find_indexes?
+
+
+
Signature: find_indexes(instrument: str) -> list
+Docstring: Find existing indexes for an instrument.
+File:      ~/Dropbox/src/nbplanetary/planetarypy/pds/apps.py
+Type:      function
+
+
+
+
+
find_indexes('cassini.uvis')
+
+
['index',
+ 'moon_summary',
+ 'ring_summary',
+ 'saturn_summary',
+ 'supplemental_index',
+ 'versions']
+
+
+
+
find_indexes('go.ssi')  # Galileo orbiter SSImager
+
+
['edr']
+
+
+
+
get_index?
+
+
+
Signature:
+get_index(
+    instr: str,
+    index_name: str = '',
+    refresh: bool = True,
+    force: bool = False,
+) -> pandas.core.frame.DataFrame
+Docstring: Example: get_index("cassini.iss", "index")
+File:      ~/Dropbox/src/nbplanetary/planetarypy/pds/apps.py
+Type:      function
+
+
+
+
+
get_index("cassini.uvis.ring_summary")
+
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
VOLUME_IDFILE_SPECIFICATION_NAMERING_OBSERVATION_IDMINIMUM_RIGHT_ASCENSIONMAXIMUM_RIGHT_ASCENSIONMINIMUM_DECLINATIONMAXIMUM_DECLINATIONMINIMUM_RING_RADIUSMAXIMUM_RING_RADIUSFINEST_RING_INTERCEPT_RESOLUTION...RING_CENTER_DISTANCESUB_SOLAR_RING_LONGITUDESUB_OBSERVER_RING_LONGITUDERING_CENTER_PHASE_ANGLERING_CENTER_INCIDENCE_ANGLERING_CENTER_NORTH_BASED_INCIDENCE_ANGLERING_CENTER_EMISSION_ANGLERING_CENTER_NORTH_BASED_EMISSION_ANGLESOLAR_RING_OPENING_ANGLEOBSERVER_RING_OPENING_ANGLE
0COUVIS_0006DATA/D2004_002/EUV2004_002_12_16.LBLS/CO/UVIS/2004-002T12-16/EUV34.15449337.8151419.6797629.7124151074925.3663066570.28987709.0...86724352.465283.109215.93862.78664.404115.59673.661106.339-25.596-16.34
1COUVIS_0006DATA/D2004_002/EUV2004_002_12_32.LBLS/CO/UVIS/2004-002T12-32/EUV34.15555737.8173139.780739.81348521741.8122900680.92487173.0...86719417.82283.109215.93862.78764.404115.59673.661106.339-25.596-16.34
2COUVIS_0006DATA/D2004_002/EUV2004_002_12_47.LBLS/CO/UVIS/2004-002T12-47/EUV34.15410737.8169359.8772499.90987864757.6812839690.54686667.0...86714483.175283.11215.93862.78764.404115.59673.661106.339-25.596-16.34
3COUVIS_0006DATA/D2004_002/EUV2004_002_13_03.LBLS/CO/UVIS/2004-002T13-03/EUV34.15519337.8191529.97817610.010898541745.3552872984.47486145.0...86709548.529283.11215.93862.78764.404115.59673.661106.339-25.596-16.34
4COUVIS_0006DATA/D2004_002/EUV2004_002_13_18.LBLS/CO/UVIS/2004-002T13-18/EUV34.15724337.82233210.07784510.1105361068459.1252999016.49585635.0...86704613.884283.111215.93862.78864.404115.59673.661106.339-25.596-16.34
..................................................................
167406COUVIS_0060DATA/D2017_258/FUV2017_258_04_31.LBLS/CO/UVIS/2017-258T04-31/FUV355.15626793.92438-69.312846-14.507954126726.8831083278.078246.61634...263974.558178.94826.85699.68163.31963.31940.35940.35926.68149.641
167407COUVIS_0060DATA/D2017_258/FUV2017_258_07_00.LBLS/CO/UVIS/2017-258T07-00/FUV82.69282382.747154-4.328498-4.268149-999.0-999.0-999.0...251887.753178.94926.66199.19263.31963.31939.69639.69626.68150.304
167408COUVIS_0060DATA/D2017_258/FUV2017_258_07_15.LBLS/CO/UVIS/2017-258T07-15/FUV54.35867176.196366-4.00728213.298744-999.0-999.0-999.0...157806.504178.95168.0476.00963.31963.31934.94634.94626.68155.054
167409COUVIS_0060DATA/D2017_258/HDAC2017_258_02_14.LBLS/CO/UVIS/2017-258T02-14/HDAC129.674881143.379042-58.332263-48.522644204871.745219390.53617773.0...447586.578178.9429.923115.55963.31963.31953.07353.07326.68136.927
167410COUVIS_0060DATA/D2017_258/HDAC2017_258_02_15.LBLS/CO/UVIS/2017-258T02-15/HDAC92.532639116.78171-67.582806-63.39221898954.702230819.67712312.0...357220.013178.94515.877109.15663.31963.31947.6247.6226.68142.38
+ +

167411 rows × 59 columns

+
+
+
+
+
get_index('go.ssi.edr')
+
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
SPACECRAFT_CLOCK_START_COUNTMISSION_NAMEINSTRUMENT_IDDATA_SET_IDIMAGE_IDOBSERVATION_IDPRODUCT_TYPETARGET_NAMEIMAGE_TIMEFILTER_NAME...SUB_SPACECRAFT_LINESUB_SPACECRAFT_LINE_SAMPLECENTER_RING_RADIUSVOLUME_IDFILE_SPECIFICATION_NAMECOMPRESSION_TYPEENCODING_MIN_COMPRESSION_RATIOENCODING_MAX_COMPRESSION_RATIOENCODING_COMPRESSION_RATIOPROCESSING_HISTORY_TEXT
030611.0GALILEOSSIGO-V/E-SSI-2-REDR-V1.1UNKPOST_LAUNCH_CHECKOUTREDRBLACK_SKYNaTCLEAR...-999.0-999.0-999GO_0002RAW_CAL/C0003061100R.IMGNONE0.00.00.0VICAR programs run: CATLABEL,BADLABEL,COPY.
130612.0GALILEOSSIGO-V/E-SSI-2-REDR-V1.1UNKPOST_LAUNCH_CHECKOUTREDRBLACK_SKYNaTCLEAR...-999.0-999.0-999GO_0002RAW_CAL/C0003061200R.IMGNONE0.00.00.0VICAR programs run: CATLABEL,BADLABEL,COPY.
230613.0GALILEOSSIGO-V/E-SSI-2-REDR-V1.1UNKPOST_LAUNCH_CHECKOUTREDRBLACK_SKYNaTCLEAR...-999.0-999.0-999GO_0002RAW_CAL/C0003061300R.IMGNONE0.00.00.0VICAR programs run: CATLABEL,BADLABEL,COPY.
330614.0GALILEOSSIGO-V/E-SSI-2-REDR-V1.1UNKPOST_LAUNCH_CHECKOUTREDRBLACK_SKYNaTCLEAR...-999.0-999.0-999GO_0002RAW_CAL/C0003061400R.IMGNONE0.00.00.0VICAR programs run: CATLABEL,BADLABEL,COPY.
430619.0GALILEOSSIGO-V/E-SSI-2-REDR-V1.1UNKPOST_LAUNCH_CHECKOUTREDRBLACK_SKYNaTCLEAR...-999.0-999.0-999GO_0002RAW_CAL/C0003061900R.IMGNONE0.00.00.0VICAR programs run: CATLABEL,BADLABEL,COPY.
..................................................................
149046006608.22GALILEOSSIGO-J/JSA-SSI-4-REDR-V1.029N003329NSFLTFLD03REDRNON_SCIENCNaTIR-7270...-999.0-999.0-999GO_0023G29/REPAIRED/C0600660822S.IMGINTEGER COSINE TRANSFORM38.91816.98676.488VICAR programs run:SSIMERGE,F2,FASTMOS,FASTMOS...
149056006608.23GALILEOSSIGO-J/JSA-SSI-4-REDR-V1.029N003329NSFLTFLD03REDRNON_SCIENCNaTIR-7270...-999.0-999.0-999GO_0023G29/REPAIRED/C0600660823S.IMGHUFFMAN0.00.00.0VICAR programs run:SSIMERGE,F2,FASTMOS,FASTMOS...
149066006609.68GALILEOSSIGO-J/JSA-SSI-4-REDR-V1.029N003429NSFLTFLD03REDRNON_SCIENCNaTIR-8890...-999.0-999.0-999GO_0023G29/REPAIRED/C0600660968S.IMGINTEGER COSINE TRANSFORM6.0544.928.212VICAR programs run:SSIMERGE,F2,FASTMOS,FASTMOS...
149076006609.69GALILEOSSIGO-J/JSA-SSI-4-REDR-V1.029N003429NSFLTFLD03REDRNON_SCIENCNaTIR-8890...-999.0-999.0-999GO_0023G29/REPAIRED/C0600660969S.IMGHUFFMAN0.00.00.0VICAR programs run:SSIMERGE,F2,FASTMOS,FASTMOS...
149084203615.0GALILEOSSIGO-J/JSA-SSI-2-REDR-V1.011I000311ISECLIPS01REDRIONaTCLEAR...254.092334.653-999GO_0023REDO/E11/IO/C0420361500R.IMGINTEGER COSINE TRANSFORM8.3546.8439.709VICAR programs run: SSIMERGE,UNMOSAIC,CATLABEL...
+ +

14909 rows × 52 columns

+
+
+
+
+
find_indexes("cassini.iss")
+
+
['index', 'inventory', 'moon_summary', 'ring_summary', 'saturn_summary']
+
+
+
+
get_index("cassini.iss.saturn_summary")
+
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
VOLUME_IDFILE_SPECIFICATION_NAMEOPUS_IDTARGET_NAMEMINIMUM_PLANETOCENTRIC_LATITUDEMAXIMUM_PLANETOCENTRIC_LATITUDEMINIMUM_PLANETOGRAPHIC_LATITUDEMAXIMUM_PLANETOGRAPHIC_LATITUDEMINIMUM_IAU_LONGITUDEMAXIMUM_IAU_LONGITUDE...MAXIMUM_EMISSION_ANGLESUB_SOLAR_PLANETOCENTRIC_LATITUDESUB_SOLAR_PLANETOGRAPHIC_LATITUDESUB_OBSERVER_PLANETOCENTRIC_LATITUDESUB_OBSERVER_PLANETOGRAPHIC_LATITUDESUB_SOLAR_IAU_LONGITUDESUB_OBSERVER_IAU_LONGITUDECENTER_RESOLUTIONCENTER_DISTANCECENTER_PHASE_ANGLE
0COISS_2001data/1454725799_1455008789/N1454725799_1.LBLco-iss-n1454725799SATURN-999.0-999.0-999.0-999.0-999.0-999.0...-999.0-25.411-30.279-16.324-19.796107.986176.558424.6760670874998.94764.07
1COISS_2001data/1454725799_1455008789/N1454726579_1.LBLco-iss-n1454726579SATURN-999.0-999.0-999.0-999.0-999.0-999.0...-999.0-25.411-30.279-16.324-19.796115.305183.877424.6512170870851.37164.07
2COISS_2001data/1454725799_1455008789/N1454727359_1.LBLco-iss-n1454727359SATURN-999.0-999.0-999.0-999.0-999.0-999.0...-999.0-25.411-30.279-16.324-19.796122.625191.197424.6263570866703.09464.071
3COISS_2001data/1454725799_1455008789/N1454728139_1.LBLco-iss-n1454728139SATURN-999.0-999.0-999.0-999.0-999.0-999.0...-999.0-25.411-30.279-16.324-19.796129.94198.513424.6015170862557.20764.071
4COISS_2001data/1454725799_1455008789/N1454728919_1.LBLco-iss-n1454728919SATURN-999.0-999.0-999.0-999.0-999.0-999.0...-999.0-25.411-30.279-16.324-19.796137.264205.837424.5766470858406.79464.071
..................................................................
405116COISS_2116data/1884113741_1884114531/W1884114471_1.LBLco-iss-w1884114471SATURN-999.0-999.0-999.0-999.0-999.0-999.0...51.9726.68231.70129.26234.552263.71579.08175.81817634269.821123.878
405117COISS_2116data/1884113741_1884114531/N1884114501_1.LBLco-iss-n1884114501SATURN-999.0-999.0-999.0-999.0-999.0-999.0...30.55826.68231.70129.26934.56263.99679.3577.59837634053.296123.87
405118COISS_2116data/1884113741_1884114531/W1884114501_1.LBLco-iss-w1884114501SATURN-999.0-999.0-999.0-999.0-999.0-999.0...52.19226.68231.70129.2734.56264.00479.36475.79162634047.739123.87
405119COISS_2116data/1884113741_1884114531/N1884114531_1.LBLco-iss-n1884114531SATURN-999.0-999.0-999.0-999.0-999.0-999.0...30.66526.68231.70129.27734.568264.27879.6337.59578633836.731123.863
405120COISS_2116data/1884113741_1884114531/W1884114531_2.LBLco-iss-w1884114531SATURN-999.0-999.0-999.0-999.0-999.0-999.0...52.47426.68231.70129.27734.568264.28679.64175.76561633830.161123.862
+ +

405121 rows × 35 columns

+
+
+
+
+
find_indexes('mro.ctx')
+
+
['edr']
+
+
+
+
get_index('mro.ctx', 'edr', refresh=False)
+
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
VOLUME_IDFILE_SPECIFICATION_NAMEORIGINAL_PRODUCT_IDPRODUCT_IDIMAGE_TIMEINSTRUMENT_IDINSTRUMENT_MODE_IDLINE_SAMPLESLINESSPATIAL_SUMMING...SUB_SOLAR_LATITUDESUB_SPACECRAFT_LONGITUDESUB_SPACECRAFT_LATITUDESOLAR_DISTANCESOLAR_LONGITUDELOCAL_TIMEIMAGE_SKEW_ANGLERATIONALE_DESCDATA_QUALITY_DESCORBIT_NUMBER
0MROX_0001DATA/CRU_000001_9999_XN_99N999W.IMG4A_04_0001000400CRU_000001_9999_XN_99N999W2005-08-30 15:40:21.549CTXNIFL505610241...0.00.00.00.0278.8910.160.0Instrument checkout image of spaceOK-4242
1MROX_0001DATA/CRU_000002_9999_XN_99N999W.IMG4A_04_0001000500CRU_000002_9999_XN_99N999W2005-09-08 15:59:45.313CTXNIFL5056153601...0.00.00.00.0284.484.60.0Calibration image of the MoonOK-4126
2MROX_0001DATA/CRU_000003_9999_XN_99N999W.IMG4A_04_0001000600CRU_000003_9999_XN_99N999W2005-09-08 16:03:37.927CTXNIFL505620481...0.00.00.00.0284.484.660.0Calibration image of Omega Centauri (globular ...OK-4126
3MROX_0001DATA/CRU_000004_9999_XN_99N999W.IMG4A_04_0001000700CRU_000004_9999_XN_99N999W2005-09-08 16:08:23.841CTXNIFL505620481...0.00.00.00.0284.484.740.0Calibration image of Omega Centauri (globular ...OK-4126
4MROX_0001DATA/CRU_000005_9999_XN_99N999W.IMG4A_04_0001000800CRU_000005_9999_XN_99N999W2005-09-08 16:11:18.649CTXNIFL5056215041...0.00.00.00.0284.484.790.0Calibration image of the MoonOK-4126
..................................................................
142363MROX_4656DATA/U17_077781_1107_XI_69S045W.IMG4A_04_118B04B300U17_077781_1107_XI_69S045W2023-03-01 00:01:37.834CTXITL505671681...12.7446.17-69.47243271024.830.815.4290.1Southern autumn frost streak area in Viking 2 ...OK77781
142364MROX_4656DATA/U17_077781_1560_XN_24S055W.IMG4A_04_118A04B400U17_077781_1560_XN_24S055W2023-03-01 00:15:17.076CTXNIFL5056307201...12.7455.44-24.08243270437.830.8114.9690.2Ride-along with HiRISEOK77781
142365MROX_4656DATA/U17_077781_1683_XN_11S057W.IMG4A_04_118A04B500U17_077781_1683_XN_11S057W2023-03-01 00:19:04.486CTXNIFL5056317441...12.7457.0-11.7243270441.730.8114.9190.2Terrain north of Coprates ChasmaOK77781
142366MROX_4656DATA/U17_077781_2027_XI_22N061W.IMG4A_04_118B04B600U17_077781_2027_XI_22N061W2023-03-01 00:29:24.818CTXITL5056522241...12.7461.2522.78243271031.730.8114.8289.8Kasei Valles regionOK77781
142367MROX_4656DATA/U17_077781_2440_XN_64N067W.IMG4A_04_118A04B700U17_077781_2440_XN_64N067W2023-03-01 00:43:08.662CTXNIFL505671681...12.7468.7664.02243272920.630.8214.5989.9Ride-along with HiRISEOK77781
+ +

142368 rows × 51 columns

+
+
+
+
+
find_instruments('cassini')
+
+
['iss', 'uvis']
+
+
+
+
find_instruments('mro')
+
+
['hirise', 'ctx']
+
+
+
+
find_instruments('lro')
+
+
['diviner', 'lola', 'lroc']
+
+
+
+
+

Instrument data

+
+
from planetarypy.uvis import DataManager
+
+
+
index = get_index("cassini.uvis.index")
+
+
+
index.tail()
+
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
FILE_NAMEOBSERVATION_TYPESTART_TIMESTOP_TIMETARGET_NAMEDATA_SET_IDSPACECRAFT_CLOCK_START_COUNTSPACECRAFT_CLOCK_STOP_COUNTINTEGRATION_DURATIONCOMPRESSION_TYPE...SUB_SOLAR_LONGITUDESUB_SPACECRAFT_LATITUDESUB_SPACECRAFT_LONGITUDEPHASE_ANGLEEMISSION_ANGLESOLAR_INCIDENCE_ANGLECENTRAL_BODY_DISTANCEDWELL_TIMEH_LEVELD_LEVEL
203240/COUVIS_0060/DATA/D2017_258/FUV2017_258_04_31.LBL<NA>2017-09-15 04:31:53.0052017-09-15 09:04:56.755SOLAR WINDCO-S-UVIS-2-CUBE-V1.41/1884145299.160UNK8191.875SQRT_9...-999.0-999.0-999.0-999.0-999.0-999-999.0-999<NA><NA>
203241/COUVIS_0060/DATA/D2017_258/FUV2017_258_07_00.LBL<NA>2017-09-15 07:00:27.6972017-09-15 07:13:40.447SOLAR WINDCO-S-UVIS-2-SPEC-V1.41/1884154214.096UNK2.625SQRT_9...-999.0-999.0-999.0-999.0-999.0-999-999.0-999<NA><NA>
203242/COUVIS_0060/DATA/D2017_258/FUV2017_258_07_15.LBL<NA>2017-09-15 07:15:04.4422017-09-15 10:31:51.692SOLAR WINDCO-S-UVIS-2-SPEC-V1.41/1884155091.032UNK2.625SQRT_9...-999.0-999.0-999.0-999.0-999.0-999-999.0-999<NA><NA>
203243/COUVIS_0060/DATA/D2017_258/HDAC2017_258_02_14...<NA>2017-09-15 02:14:02.4332017-09-15 02:14:06.433SOLAR WINDCO-S-UVIS-2-SSB-V1.41/1884137029.000UNK-999.0NONE...-999.0-999.0-999.0-999.0-999.0-999-999.01(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0)(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0)
203244/COUVIS_0060/DATA/D2017_258/HDAC2017_258_02_15...<NA>2017-09-15 02:15:25.0582017-09-15 02:17:33.058SOLAR WINDCO-S-UVIS-2-SSB-V1.41/1884137111.160UNK-999.0NONE...-999.0-999.0-999.0-999.0-999.0-999-999.032(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0)(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0)
+ +

5 rows × 28 columns

+
+
+
+
+
dm = DataManager("EUV2017_258_07_00")
+
+
+
dm.calib_label_path
+
+
Path('/home/ayek72/mnt/slowdata/planetarypy/missions/cassini/uvis/EUV2017_258_07_00/EUV2017_258_07_00_CAL_3.LBL')
+
+
+
+
dm.raw_data_path
+
+
Path('/home/ayek72/mnt/slowdata/planetarypy/missions/cassini/uvis/EUV2017_258_07_00/EUV2017_258_07_00.DAT')
+
+
+
+
dm.raw_label_path
+
+
Path('/home/ayek72/mnt/slowdata/planetarypy/missions/cassini/uvis/EUV2017_258_07_00/EUV2017_258_07_00.LBL')
+
+
+
+
from planetarypy.hirise import ProductPathfinder
+
+ + +
+
+ +
+
+ +
+
+
+
ppf = ProductPathfinder("PSP_003092_0985_RED")
+
+
+
ppf.local_label_path
+
+
Path('/home/ayek72/mnt/slowdata/planetarypy/missions/mro/hirise/PSP_003092_0985/PSP_003092_0985_RED.LBL')
+
+
+
+
ppf.abrowse_path
+
+
Path('EXTRAS/RDR/PSP/ORB_003000_003099/PSP_003092_0985/PSP_003092_0985_RED.abrowse.jpg')
+
+
+
+
ppf.homepage
+
+
'https://uahirise.org/PSP_003092_0985'
+
+
+
+
ppf.nomap_jp2_url
+
+
URL('https://hirise-pds.lpl.arizona.edu/PDS/EXTRAS/RDR/PSP/ORB_003000_003099/PSP_003092_0985/PSP_003092_0985_RED.NOMAP.JP2')
+
+
+
+
from planetarypy.hirise import RGB_NOMAP
+
+
+
rgb = RGB_NOMAP("PSP_003092_0985")
+
+
+
rgb.local_path
+
+
Path('/home/ayek72/mnt/slowdata/planetarypy/missions/mro/hirise/PSP_003092_0985/PSP_003092_0985_RGB.NOMAP.JP2')
+
+
+ + +
+ +
+ + +
+ + + + \ No newline at end of file diff --git a/tutorials/assets/NAIF_archives.png b/tutorials/assets/NAIF_archives.png new file mode 100644 index 0000000..807cea5 Binary files /dev/null and b/tutorials/assets/NAIF_archives.png differ diff --git a/tutorials/pdw2023_demo.html b/tutorials/pdw2023_demo.html new file mode 100644 index 0000000..76c4680 --- /dev/null +++ b/tutorials/pdw2023_demo.html @@ -0,0 +1,4010 @@ + + + + + + + + + +planetarypy - Demo of PlanetaryPy + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Demo of PlanetaryPy

+
+ + + +
+ + + + +
+ + +
+ + +
+
import planetarypy as plpy
+
+
+
plpy.__version__
+
+
'0.30.0'
+
+
+
+
from planetarypy.pds.apps import get_index, find_indexes
+
+
+
!head -n 50 $HOME/.planetarypy_config.toml
+
+
storage_root = "/home/ayek72/mnt/slowdata/planetarypy"
+
+[missions.cassini.iss.indexes.index]
+# 'index' is the ID of the originally delivered index
+# inventory, moon_summary, ring_summary, and saturn_summary are other indexes produced
+# by the Rings-Moons Systems PDS node
+url = "https://pds-rings.seti.org/holdings/metadata/COISS_2xxx/COISS_2999/COISS_2999_index.lbl"
+timestamp = "2021-02-21T15:55:27"
+
+[missions.cassini.iss.indexes.inventory]
+url = "https://pds-rings.seti.org/holdings/metadata/COISS_2xxx/COISS_2999/COISS_2999_inventory.lbl"
+
+[missions.cassini.iss.indexes.moon_summary]
+url = "https://pds-rings.seti.org/holdings/metadata/COISS_2xxx/COISS_2999/COISS_2999_moon_summary.lbl"
+timestamp = "2019-06-08T16:28:22"
+
+[missions.cassini.iss.indexes.ring_summary]
+url = "https://pds-rings.seti.org/holdings/metadata/COISS_2xxx/COISS_2999/COISS_2999_ring_summary.lbl"
+timestamp = "2022-08-08T11:54:51.140376"
+
+[missions.cassini.iss.indexes.saturn_summary]
+url = "https://pds-rings.seti.org/holdings/metadata/COISS_2xxx/COISS_2999/COISS_2999_saturn_summary.lbl"
+timestamp = "2022-12-21T18:10:29.248055"
+
+
+[missions.cassini.uvis.indexes.index]
+url = "https://pds-rings.seti.org/holdings/metadata/COUVIS_0xxx/COUVIS_0999/COUVIS_0999_index.lbl"
+timestamp = "2022-09-01T14:14:10.014705"
+
+[missions.cassini.uvis.indexes.moon_summary]
+url = "https://pds-rings.seti.org/holdings/metadata/COUVIS_0xxx/COUVIS_0999/COUVIS_0999_moon_summary.lbl"
+
+[missions.cassini.uvis.indexes.ring_summary]
+url = "https://pds-rings.seti.org/holdings/metadata/COUVIS_0xxx/COUVIS_0999/COUVIS_0999_ring_summary.lbl"
+timestamp = "2022-08-08T11:53:16.071844"
+
+[missions.cassini.uvis.indexes.saturn_summary]
+url = "https://pds-rings.seti.org/holdings/metadata/COUVIS_0xxx/COUVIS_0999/COUVIS_0999_saturn_summary.lbl"
+
+[missions.cassini.uvis.indexes.supplemental_index]
+url = "https://pds-rings.seti.org/holdings/metadata/COUVIS_0xxx/COUVIS_0999/COUVIS_0999_supplemental_index.lbl"
+
+[missions.cassini.uvis.indexes.versions]
+url = "https://pds-rings.seti.org/holdings/metadata/COUVIS_0xxx/COUVIS_0999/COUVIS_0999_versions.lbl"
+
+
+
+[missions.mro.hirise.indexes.dtm]
+url = "https://hirise-pds.lpl.arizona.edu/PDS/INDEX/DTMCUMINDEX.LBL"
+
+
+
+
+
find_indexes("cassini.iss")
+
+
['index', 'inventory', 'moon_summary', 'ring_summary', 'saturn_summary']
+
+
+
+
find_indexes("cassini.uvis")
+
+
['index',
+ 'moon_summary',
+ 'ring_summary',
+ 'saturn_summary',
+ 'supplemental_index',
+ 'versions']
+
+
+
+
df = get_index("cassini.iss.index")
+df.head()
+
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
FILE_NAMEFILE_SPECIFICATION_NAMEVOLUME_IDANTIBLOOMING_STATE_FLAGBIAS_STRIP_MEANCALIBRATION_LAMP_STATE_FLAGCOMMAND_FILE_NAMECOMMAND_SEQUENCE_NUMBERDARK_STRIP_MEANDATA_CONVERSION_TYPE...TWIST_ANGLETARGET_LISTUPPER_LEFT_LATITUDEUPPER_LEFT_LONGITUDEUPPER_RIGHT_LATITUDEUPPER_RIGHT_LONGITUDEDATA_SET_NAMEINSTRUMENT_HOST_IDPRODUCT_TYPESTANDARD_DATA_PRODUCT_ID
0N1454725799_1.IMGdata/1454725799_1455008789/N1454725799_1.IMGCOISS_2001OFF14.869863<NA>OPNAV_848_3.ioi80.012BIT...89.513591S2_2004,HELENE,TELESTO,RHEA-100000000000000005366162204393472.0-100000000000000005366162204393472.0-100000000000000005366162204393472.0-100000000000000005366162204393472.0CASSINI ORBITER SATURN ISSNA/ISSWA 2 EDR VERSI...COEDRISS_EDR
1N1454726579_1.IMGdata/1454725799_1455008789/N1454726579_1.IMGCOISS_2001OFF14.860078<NA>OPNAV_864_3.ioi80.012BIT...89.647635TITAN-100000000000000005366162204393472.0-100000000000000005366162204393472.0-100000000000000005366162204393472.0-100000000000000005366162204393472.0CASSINI ORBITER SATURN ISSNA/ISSWA 2 EDR VERSI...COEDRISS_EDR
2N1454727359_1.IMGdata/1454725799_1455008789/N1454727359_1.IMGCOISS_2001OFF14.87867<NA>OPNAV_880_3.ioi80.012BIT...89.679084HYPERION-100000000000000005366162204393472.0-100000000000000005366162204393472.0-100000000000000005366162204393472.0-100000000000000005366162204393472.0CASSINI ORBITER SATURN ISSNA/ISSWA 2 EDR VERSI...COEDRISS_EDR
3N1454728139_1.IMGdata/1454725799_1455008789/N1454728139_1.IMGCOISS_2001OFF14.842465<NA>OPNAV_912_3.ioi80.012BIT...88.677516PHOEBE-100000000000000005366162204393472.0-100000000000000005366162204393472.0-100000000000000005366162204393472.0-100000000000000005366162204393472.0CASSINI ORBITER SATURN ISSNA/ISSWA 2 EDR VERSI...COEDRISS_EDR
4N1454728919_1.IMGdata/1454725799_1455008789/N1454728919_1.IMGCOISS_2001OFF14.86497<NA>OPNAV_896_3.ioi80.012BIT...89.79891IAPETUS-100000000000000005366162204393472.0-100000000000000005366162204393472.0-100000000000000005366162204393472.0-100000000000000005366162204393472.0CASSINI ORBITER SATURN ISSNA/ISSWA 2 EDR VERSI...COEDRISS_EDR
+ +

5 rows × 140 columns

+
+
+
+
+
df.columns
+
+
Index(['FILE_NAME', 'FILE_SPECIFICATION_NAME', 'VOLUME_ID',
+       'ANTIBLOOMING_STATE_FLAG', 'BIAS_STRIP_MEAN',
+       'CALIBRATION_LAMP_STATE_FLAG', 'COMMAND_FILE_NAME',
+       'COMMAND_SEQUENCE_NUMBER', 'DARK_STRIP_MEAN', 'DATA_CONVERSION_TYPE',
+       ...
+       'TWIST_ANGLE', 'TARGET_LIST', 'UPPER_LEFT_LATITUDE',
+       'UPPER_LEFT_LONGITUDE', 'UPPER_RIGHT_LATITUDE', 'UPPER_RIGHT_LONGITUDE',
+       'DATA_SET_NAME', 'INSTRUMENT_HOST_ID', 'PRODUCT_TYPE',
+       'STANDARD_DATA_PRODUCT_ID'],
+      dtype='object', length=140)
+
+
+
+
df.set_index("IMAGE_MID_TIME").loc['20170914 00':'20170914 15']
+
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
FILE_NAMEFILE_SPECIFICATION_NAMEVOLUME_IDANTIBLOOMING_STATE_FLAGBIAS_STRIP_MEANCALIBRATION_LAMP_STATE_FLAGCOMMAND_FILE_NAMECOMMAND_SEQUENCE_NUMBERDARK_STRIP_MEANDATA_CONVERSION_TYPE...TWIST_ANGLETARGET_LISTUPPER_LEFT_LATITUDEUPPER_LEFT_LONGITUDEUPPER_RIGHT_LATITUDEUPPER_RIGHT_LONGITUDEDATA_SET_NAMEINSTRUMENT_HOST_IDPRODUCT_TYPESTANDARD_DATA_PRODUCT_ID
IMAGE_MID_TIME
2017-09-14 13:26:59.927N1884091007_1.IMGdata/1884017637_1884113741/N1884091007_1.IMGCOISS_2116OFF21.611872<NA>trigger_25245_3.ioi252451.21844412BIT...4.868274<NA>-100000000000000005366162204393472.0-100000000000000005366162204393472.0-100000000000000005366162204393472.0-100000000000000005366162204393472.0CASSINI ORBITER SATURN ISSNA/ISSWA 2 EDR VERSI...COEDRISS_EDR
2017-09-14 13:31:18.910N1884091266_1.IMGdata/1884017637_1884113741/N1884091266_1.IMGCOISS_2116OFF21.594259<NA>trigger_25245_3.ioi252451.22223612BIT...4.812541<NA>-100000000000000005366162204393472.0-100000000000000005366162204393472.0-100000000000000005366162204393472.0-100000000000000005366162204393472.0CASSINI ORBITER SATURN ISSNA/ISSWA 2 EDR VERSI...COEDRISS_EDR
2017-09-14 13:35:41.908N1884091529_1.IMGdata/1884017637_1884113741/N1884091529_1.IMGCOISS_2116OFF21.87019<NA>trigger_25245_3.ioi252451.22957412BIT...4.77302DAPHNIS-100000000000000005366162204393472.0-100000000000000005366162204393472.0-100000000000000005366162204393472.0-100000000000000005366162204393472.0CASSINI ORBITER SATURN ISSNA/ISSWA 2 EDR VERSI...COEDRISS_EDR
2017-09-14 13:40:04.906N1884091792_1.IMGdata/1884017637_1884113741/N1884091792_1.IMGCOISS_2116OFF21.843445<NA>trigger_25245_3.ioi252451.25403612BIT...4.748047<NA>-100000000000000005366162204393472.0-100000000000000005366162204393472.0-100000000000000005366162204393472.0-100000000000000005366162204393472.0CASSINI ORBITER SATURN ISSNA/ISSWA 2 EDR VERSI...COEDRISS_EDR
2017-09-14 13:44:27.905N1884092055_1.IMGdata/1884017637_1884113741/N1884092055_1.IMGCOISS_2116OFF21.885845<NA>trigger_25245_3.ioi252451.26320912BIT...4.736484<NA>-100000000000000005366162204393472.0-100000000000000005366162204393472.0-100000000000000005366162204393472.0-100000000000000005366162204393472.0CASSINI ORBITER SATURN ISSNA/ISSWA 2 EDR VERSI...COEDRISS_EDR
2017-09-14 13:48:50.903N1884092318_1.IMGdata/1884017637_1884113741/N1884092318_1.IMGCOISS_2116OFF21.558872<NA>trigger_25245_3.ioi252451.26002912BIT...4.737905<NA>-100000000000000005366162204393472.0-100000000000000005366162204393472.0-100000000000000005366162204393472.0-100000000000000005366162204393472.0CASSINI ORBITER SATURN ISSNA/ISSWA 2 EDR VERSI...COEDRISS_EDR
2017-09-14 13:53:13.901N1884092581_1.IMGdata/1884017637_1884113741/N1884092581_1.IMGCOISS_2116OFF21.606491<NA>trigger_25245_3.ioi252451.24828812BIT...4.750201<NA>-100000000000000005366162204393472.0-100000000000000005366162204393472.0-100000000000000005366162204393472.0-100000000000000005366162204393472.0CASSINI ORBITER SATURN ISSNA/ISSWA 2 EDR VERSI...COEDRISS_EDR
+ +

7 rows × 139 columns

+
+
+
+
+

Cassini ISS

+
+
from planetarypy.ciss import ISS
+
+
+
iss = ISS("N1884091529_1")
+
+
Found 1 obsids.
+
+
+
+
iss.download_raw()
+
+
File exists. Use `overwrite=True` to download fresh.
+
+
+
+
iss.local_label_path
+
+
Path('/home/ayek72/mnt/slowdata/planetarypy/missions/cassini/iss/N1884091529_1/N1884091529_1.LBL')
+
+
+
+
import pdr
+
+
+
do = pdr.open(iss.local_data_path)
+
+
+
type(do)
+
+
pdr.pdr.Data
+
+
+
+
do.read_metadata()['IMAGE_MID_TIME']
+
+
'2017-257T13:35:41.908'
+
+
+
+
do.show("IMAGE")
+
+

+
+
+
+
+

CTX

+
+
from planetarypy.ctx import CTX
+
+
+
edrs = get_index('mro.ctx.edr', refresh=True)
+
+ +
+
+ +
+
+
Downloaded /home/ayek72/mnt/slowdata/planetarypy/missions/mro/ctx/indexes/edr/cumindex.lbl and /home/ayek72/mnt/slowdata/planetarypy/missions/mro/ctx/indexes/edr/cumindex.tab
+Done.
+An updated index is available. Downloading...
+
+
+
+
edrs.tail()
+
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
VOLUME_IDFILE_SPECIFICATION_NAMEORIGINAL_PRODUCT_IDPRODUCT_IDIMAGE_TIMEINSTRUMENT_IDINSTRUMENT_MODE_IDLINE_SAMPLESLINESSPATIAL_SUMMING...SUB_SOLAR_LATITUDESUB_SPACECRAFT_LONGITUDESUB_SPACECRAFT_LATITUDESOLAR_DISTANCESOLAR_LONGITUDELOCAL_TIMEIMAGE_SKEW_ANGLERATIONALE_DESCDATA_QUALITY_DESCORBIT_NUMBER
145081MROX_4759DATA/U20_078960_2636_XN_83N240W.IMG4A_04_1190031700U20_078960_2636_XN_83N240W2023-05-31 21:52:13.062CTXNIFL505671681...24.07239.7483.7249218523.371.5713.790.0Ride-along with HiRISEOK78960
145082MROX_4759DATA/U20_078961_1433_XI_36S229W.IMG4A_04_1191031800U20_078961_1433_XI_36S229W2023-05-31 23:06:16.597CTXITL5056235521...24.07231.42-36.98249219468.271.5915.6290.2Pursat Crater and terrain to the northOK78961
145083MROX_4759DATA/U20_078961_1778_XN_02S236W.IMG4A_04_1190031900U20_078961_1778_XN_02S236W2023-05-31 23:16:31.929CTXNIFL5056522241...24.07235.91-2.19249218165.171.615.3490.1Northern Terra CimmeriaOK78961
145084MROX_4759DATA/U20_078961_2113_XN_31N239W.IMG4A_04_1190031A00U20_078961_2113_XN_31N239W2023-05-31 23:27:38.765CTXNIFL377671681...24.08240.1531.33249217646.671.615.2990.0Ride-along with HiRISEOK78961
145085MROX_4759DATA/U20_078961_2609_XN_80N259W.IMG4A_04_1190031B00U20_078961_2609_XN_80N259W2023-05-31 23:43:31.515CTXNIFL377671681...24.08259.3981.01249218307.871.6114.2289.9Ride-along with HiRISEOK78961
+ +

5 rows × 51 columns

+
+
+
+
+
pid = "U08_074276_1370_XI_43S133W"
+
+
+
ctx = CTX(pid)
+
+
+
ctx.download()
+
+
File exists. Use `overwrite=True` to download fresh.
+
+
+
+
ctx.meta
+
+
volume_id                                                 MROX_4238
+file_specification_name         DATA/U08_074276_1370_XI_43S133W.IMG
+original_product_id                                4A_04_1179029700
+product_id                               U08_074276_1370_XI_43S133W
+image_time                               2022-05-31 22:06:07.945000
+instrument_id                                                   CTX
+instrument_mode_id                                              ITL
+line_samples                                                   5056
+lines                                                         49152
+spatial_summing                                                   1
+scaled_pixel_width                                             5.13
+pixel_aspect_ratio                                             1.18
+emission_angle                                                 5.34
+incidence_angle                                               50.01
+phase_angle                                                   55.16
+center_longitude                                             133.38
+center_latitude                                              -43.14
+upper_left_longitude                                          133.3
+upper_left_latitude                                          -45.66
+upper_right_longitude                                        132.68
+upper_right_latitude                                         -45.61
+lower_left_longitude                                         134.04
+lower_left_latitude                                          -40.68
+lower_right_longitude                                        133.48
+lower_right_latitude                                         -40.63
+mission_phase_name                                              ESP
+target_name                                                    MARS
+spacecraft_clock_start_count                         1338502024:229
+focal_plane_temperature                                       294.5
+line_exposure_duration                                        1.877
+offset_mode_id                                          196/215/209
+sample_first_pixel                                                0
+scaled_image_width                                            25.66
+scaled_image_height                                          297.15
+spacecraft_altitude                                          254.75
+target_center_distance                                      3641.68
+slant_distance                                               255.78
+usage_note                                                        N
+north_azimuth                                                276.51
+sub_solar_azimuth                                             194.3
+sub_solar_longitude                                          187.84
+sub_solar_latitude                                           -21.42
+sub_spacecraft_longitude                                     132.87
+sub_spacecraft_latitude                                      -43.09
+solar_distance                                          207097154.5
+solar_longitude                                              238.12
+local_time                                                    15.62
+image_skew_angle                                               90.4
+rationale_desc                           Landforms in Terra Sirenum
+data_quality_desc                                                OK
+orbit_number                                                  74276
+short_pid                                           U08_074276_1370
+month_col                                                       U08
+Name: 132419, dtype: object
+
+
+
+
ctx.edr_da
+
+ +
+ + + + + + + + + + + + + + +
<xarray.DataArray 'U08_074276_1370 EDR' (y: 49152, x: 5056)>
+[248512512 values with dtype=uint8]
+Coordinates:
+  * x        (x) float64 0.5 1.5 2.5 3.5 ... 5.054e+03 5.054e+03 5.056e+03
+  * y        (y) float64 0.5 1.5 2.5 3.5 ... 4.915e+04 4.915e+04 4.915e+04
+Attributes: (12/19)
+    BANDWIDTH:                  
+    CENTER_FILTER_WAVELENGTH:   
+    DATA_SET_ID:                "MRO-M-CTX-2-EDR-L0-V1.0"
+    FILTER_NAME:                
+    INSTRUMENT_ID:              CTX
+    INSTRUMENT_NAME:            "CONTEXT CAMERA"
+    ...                         ...
+    START_TIME:                 2022-05-31T22:06:07.945
+    STOP_TIME:                  2022-05-31T22:07:40.191
+    TARGET_NAME:                MARS
+    _FillValue:                 0
+    scale_factor:               1.0
+    add_offset:                 0.0
+
+
+
+
!gdalinfo {ctx.source_path}
+
+
Driver: PDS/NASA Planetary Data System
+Files: /remote/trove/geo/planet/Mars/CTX/pds/mrox_4238/U08_074276_1370_XI_43S133W.IMG
+Size is 5056, 49152
+Metadata:
+  BANDWIDTH=
+  CENTER_FILTER_WAVELENGTH=
+  DATA_SET_ID="MRO-M-CTX-2-EDR-L0-V1.0"
+  FILTER_NAME=
+  INSTRUMENT_ID=CTX
+  INSTRUMENT_NAME="CONTEXT CAMERA"
+  MISSION_NAME=
+  NOTE=
+  PRODUCER_INSTITUTION_NAME=
+  PRODUCT_CREATION_TIME=2022-11-04T18:18:50
+  PRODUCT_ID="U08_074276_1370_XI_43S133W"
+  PRODUCT_TYPE=
+  SPACECRAFT_NAME=MARS_RECONNAISSANCE_ORBITER
+  START_TIME=2022-05-31T22:06:07.945
+  STOP_TIME=2022-05-31T22:07:40.191
+  TARGET_NAME=MARS
+Corner Coordinates:
+Upper Left  (    0.0,    0.0)
+Lower Left  (    0.0,49152.0)
+Upper Right ( 5056.0,    0.0)
+Lower Right ( 5056.0,49152.0)
+Center      ( 2528.0,24576.0)
+Band 1 Block=5056x1 Type=Byte, ColorInterp=Undefined
+  NoData Value=0
+
+
+
+
ctx.plot_edr()
+
+ +
+
+ +
+
+
+ +
+
+
+
ctx.edr_da
+
+ +
+ + + + + + + + + + + + + + +
<xarray.DataArray 'U08_074276_1370 EDR' (y: 49152, x: 5056)>
+[248512512 values with dtype=uint8]
+Coordinates:
+  * x        (x) float64 0.5 1.5 2.5 3.5 ... 5.054e+03 5.054e+03 5.056e+03
+  * y        (y) float64 0.5 1.5 2.5 3.5 ... 4.915e+04 4.915e+04 4.915e+04
+Attributes: (12/19)
+    BANDWIDTH:                  
+    CENTER_FILTER_WAVELENGTH:   
+    DATA_SET_ID:                "MRO-M-CTX-2-EDR-L0-V1.0"
+    FILTER_NAME:                
+    INSTRUMENT_ID:              CTX
+    INSTRUMENT_NAME:            "CONTEXT CAMERA"
+    ...                         ...
+    START_TIME:                 2022-05-31T22:06:07.945
+    STOP_TIME:                  2022-05-31T22:07:40.191
+    TARGET_NAME:                MARS
+    _FillValue:                 0
+    scale_factor:               1.0
+    add_offset:                 0.0
+
+
+
+
from planetarypy.hirise import RGB_NOMAP
+
+ + +
+
+ +
+
+ +
+
+ +
+
+
+ +
+
+
+
obsid = "ESP_039983_1390"
+
+
+
rgb = RGB_NOMAP(obsid)
+
+
+
rgb.download()
+
+
File exists. Use `overwrite=True` to download fresh.
+
+
+
+
rgb.url
+
+
URL('https://hirise-pds.lpl.arizona.edu/PDS/EXTRAS/RDR/ESP/ORB_039900_039999/ESP_039983_1390/ESP_039983_1390_RGB.NOMAP.JP2')
+
+
+
+
rgb.download()
+
+
File exists. Use `overwrite=True` to download fresh.
+
+
+
+
rgb.read()
+
+ +
+ + + + + + + + + + + + + + +
<xarray.DataArray (band: 3, y: 20000, x: 2024)>
+dask.array<open_rasterio-50355e7d99e2af88a185d9da4643f0cc<this-array>, shape=(3, 20000, 2024), dtype=uint16, chunksize=(1, 2024, 2024), chunktype=numpy.ndarray>
+Coordinates:
+  * band         (band) int64 1 2 3
+  * x            (x) float64 0.5 1.5 2.5 3.5 ... 2.022e+03 2.022e+03 2.024e+03
+  * y            (y) float64 0.5 1.5 2.5 3.5 4.5 ... 2e+04 2e+04 2e+04 2e+04
+    spatial_ref  int64 0
+Attributes:
+    scale_factor:  1.0
+    add_offset:    0.0
+
+
+
+
+

SPICE

+
+

Archived kernels

+
+
from planetarypy.spice import kernels
+
+
+
kernels.datasets
+
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
pathMission NamePDS3 or PDS4Data Size (GB)Start TimeStop Time
shorthand
bcbc/bc_spiceBepiColombo42.32018-10-202023-06-21
cassinico-s_j_e_v-spice-6-v1.0/cosp_1000Cassini Orbiter362.51997-10-152017-09-15
clementineclem1-l-spice-6-v1.0/clsp_1000Clementine30.81994-01-261994-05-07
dartdart/dart_spiceDART410.02021-11-092050-01-01
dawndawn-m_a-spice-6-v1.0/dawnsp_1000DAWN386.42007-09-272018-10-31
didi-c-spice-6-v1.0/disp_1000Deep Impact30.72005-01-122005-08-09
ds1ds1-a_c-spice-6-v1.0/ds1sp_1000Deep Space 130.91998-10-242001-12-18
epoxidif-c_e_x-spice-6-v1.0/epxsp_1000EPOXI31.02005-08-232011-03-01
em16em16/em16_spiceExoMars TGO 2016410.42016-03-142023-10-01
grailgrail-l-spice-6-v1.0/grlsp_1000GRAIL34.32011-09-102012-12-17
hayabusahay-a-spice-6-v1.0/haysp_1000Hayabusa30.32005-09-112005-11-19
insightinsight/insight_spiceInSight40.92018-05-052022-12-15
junojno-j_e_ss-spice-6-v1.0/jnosp_1000JUNO348.22011-08-052023-04-08
ladeeladee/ladee_spiceLADEE40.62013-09-072050-01-01
lrolro-l-spice-6-v1.0/lrosp_1000Lunar Reconnaissance Orbiter3616.92009-06-182023-09-15
mavenmaven/maven_spiceMAVEN456.62013-11-182023-10-01
opportunitymer1-m-spice-6-v1.0/mer1sp_1000MER 1 (Opportunity)34.12003-07-072018-06-10
spiritmer2-m-spice-6-v1.0/mer2sp_1000MER 2 (Spirit)32.62003-06-102010-05-03
messengermess-e_v_h-spice-6-v1.0/messsp_1000MESSENGER344.82004-08-032015-04-30
mars2020mars2020/mars2020_spiceMars 202040.62020-07-302023-08-31
mexmex-e_m-spice-6-v2.0/mexsp_2000Mars Express310.62003-06-022023-08-31
mgsmgs-m-spice-6-v1.0/mgsp_1000Mars Global Surveyor315.41996-11-062006-11-02
odyody-m-spice-6-v1.0/odsp_1000Mars Odyssey335.22001-04-072023-07-01
mromro-m-spice-6-v1.0/mrosp_1000Mars Reconnaissance Orbiter3324.72005-08-122023-10-01
mslmsl-m-spice-6-v1.0/mslsp_1000Mars Science Laboratory30.62011-11-262023-07-29
nearnear-a-spice-6-v1.0/nearsp_1000NEAR32.41996-05-302001-02-28
nhnh-j_p_ss-spice-6-v1.0/nhsp_1000New Horizons31.62006-01-192019-12-30
orexorex/orex_spiceOSIRIS-REx4424.72016-09-082023-10-02
rosettaro_rl-e_m_a_c-spice-6-v1.0/rossp_1000Rosetta35.92004-03-022017-01-01
stardustsdu-c-spice-6-v1.0/sdsp_1000Stardust31.91999-02-072011-05-01
venus_climate_orbitervco/vco_spiceVenus Climate Orbiter41.92010-05-212023-01-01
vexvex-e_v-spice-6-v2.0/vexsp_2000Venus Express35.02005-11-092015-02-06
vovo1_vo2-m-spice-6-v1.0/vosp_1000Viking Orbiter30.11976-06-161980-07-30
+ +
+
+
+
+
kernels.list_kernels_for_day('bc', '2019-01-01')
+
+
['ck/bc_mmo_sc_cruise_v01.bc',
+ 'ck/bc_mpo_magboom_v01.bc',
+ 'ck/bc_mtm_sc_cruise_v01.bc',
+ 'fk/bc_dsk_surfaces_v03.tf',
+ 'fk/bc_mmo_v13.tf',
+ 'fk/bc_mpo_v34.tf',
+ 'fk/bc_mtm_v12.tf',
+ 'fk/bc_sci_v12.tf',
+ 'fk/earth_topo_201023.tf',
+ 'fk/earthstns_jaxa_20230905.tf',
+ 'fk/estrack_v04.tf',
+ 'fk/rssd0002.tf',
+ 'ik/bc_mmo_mppe_v04.ti',
+ 'ik/bc_mmo_msasi_v03.ti',
+ 'ik/bc_mpo_aux_v01.ti',
+ 'ik/bc_mpo_bela_v09.ti',
+ 'ik/bc_mpo_mertis_v08.ti',
+ 'ik/bc_mpo_mgns_v02.ti',
+ 'ik/bc_mpo_mixs_v06.ti',
+ 'ik/bc_mpo_phebus_v06.ti',
+ 'ik/bc_mpo_serena_v08.ti',
+ 'ik/bc_mpo_simbio-sys_v10.ti',
+ 'ik/bc_mpo_sixs_v08.ti',
+ 'ik/bc_mpo_str_v02.ti',
+ 'ik/bc_mtm_mcam_v05.ti',
+ 'lsk/naif0012.tls',
+ 'pck/earth_000101_231220_230927.bpc',
+ 'pck/gm_de431.tpc',
+ 'pck/pck00011_bc_v00.tpc',
+ 'sclk/bc_mmo_fict_20170228.tsc',
+ 'sclk/bc_mpo_fict_20181127.tsc',
+ 'sclk/bc_mpo_step_20230917.tsc',
+ 'spk/bc_mmo_cruise_v01.bsp',
+ 'spk/bc_mmo_struct_v01.bsp',
+ 'spk/bc_mpo_cog_v03.bsp',
+ 'spk/bc_mpo_struct_v09.bsp',
+ 'spk/bc_mtm_cruise_v01.bsp',
+ 'spk/bc_mtm_struct_v06.bsp',
+ 'spk/bc_sci_v02.bsp',
+ 'spk/de432s.bsp',
+ 'spk/earthstns_itrf93_201023.bsp',
+ 'spk/earthstns_jaxa_20230905.bsp',
+ 'spk/estrack_v04.bsp']
+
+
+
+
mkpath = kernels.get_metakernel_and_files('msl', '2020-01-01', '2020-01-05')
+
+ +
+
+
msl_ra_toolsref_v1.bc:   0%|          | 0/18432 [00:00<?, ?it/s]
+msl_v08.tf:   0%|          | 0/205622 [00:00<?, ?it/s]/325632 [00:00<?, ?it/s]
+msl_surf_rsm_tlmenc_2579_2713_v1.bc:   0%|          | 0/4276224 [00:00<?, ?it/s][A
+msl_surf_hga_tlm_2579_2713_v1.bc:   0%|          | 0/2271232 [00:00<?, ?it/s]
+msl_ra_toolsref_v1.bc: 100%|██████████| 18.0k/18.0k [00:00<00:00, 118kB/s] it/s]
+msl_surf_rsm_tlmenc_2579_2713_v1.bc:   0%|          | 4.00k/4.08M [00:00<02:40, 26.6kB/s]
+msl_surf_ra_tlmres_2579_2713_v1.bc:   0%|          | 4.00k/1.86M [00:00<01:14, 26.0kB/s]
+
+msl_surf_rover_tlm_2579_2713_v1.bc:   1%|▏         | 4.00k/318k [00:00<00:12, 25.1kB/s][A
+msl_surf_rsm_tlmenc_2579_2713_v1.bc:   1%|          | 36.0k/4.08M [00:00<00:31, 133kB/s] 
+msl_surf_ra_tlmres_2579_2713_v1.bc:   2%|▏         | 36.0k/1.86M [00:00<00:14, 132kB/s] 
+msl_surf_rover_tlm_2579_2713_v1.bc:  11%|█▏        | 36.0k/318k [00:00<00:02, 131kB/s] 
+msl_surf_rsm_tlmres_2579_2713_v1.bc:   1%|          | 36.0k/3.56M [00:00<00:28, 131kB/s] 
+msl_surf_rsm_tlmenc_2579_2713_v1.bc:   2%|▏         | 100k/4.08M [00:00<00:16, 260kB/s] A
+msl_surf_ra_tlmres_2579_2713_v1.bc:   5%|▌         | 100k/1.86M [00:00<00:07, 259kB/s] 
+msl_surf_rover_tlm_2579_2713_v1.bc:  31%|███▏      | 100k/318k [00:00<00:00, 258kB/s] 
+msl_surf_rsm_tlmres_2579_2713_v1.bc:   3%|▎         | 100k/3.56M [00:00<00:14, 258kB/s] 
+msl_v08.tf: 100%|██████████| 201k/201k [00:00<00:00, 398kB/s] [00:00<00:08, 257kB/s] 
+msl_surf_ra_tlmenc_2579_2713_v1.bc:   7%|▋         | 212k/3.13M [00:00<00:06, 440kB/s]]
+msl_surf_ra_tlmres_2579_2713_v1.bc:  11%|█         | 212k/1.86M [00:00<00:03, 440kB/s]
+msl_surf_rover_tlm_2579_2713_v1.bc:  62%|██████▏   | 196k/318k [00:00<00:00, 399kB/s]
+msl_surf_rover_tlm_2579_2713_v1.bc: 100%|██████████| 318k/318k [00:00<00:00, 503kB/s]s]
+
+msl_surf_rsm_tlmenc_2579_2713_v1.bc:  10%|█         | 436k/4.08M [00:00<00:04, 800kB/s]
+msl_surf_ra_tlmres_2579_2713_v1.bc:  23%|██▎       | 436k/1.86M [00:00<00:01, 799kB/s]
+msl_surf_rsm_tlmres_2579_2713_v1.bc:  12%|█▏        | 436k/3.56M [00:00<00:04, 798kB/s]
+msl_hbra_20120731_c03.ti: 100%|██████████| 7.77k/7.77k [00:00<00:00, 15.7MB/s]6kB/s]
+msl_surf_rsm_tlmenc_2579_2713_v1.bc:  21%|██        | 884k/4.08M [00:00<00:02, 1.51MB/s]
+msl_surf_ra_tlmres_2579_2713_v1.bc:  46%|████▋     | 884k/1.86M [00:00<00:00, 1.50MB/s]
+msl_surf_rsm_tlmres_2579_2713_v1.bc:  24%|██▍       | 884k/3.56M [00:00<00:01, 1.50MB/s]
+msl_surf_rsm_tlmenc_2579_2713_v1.bc:  43%|████▎     | 1.74M/4.08M [00:01<00:00, 2.89MB/s]
+msl_surf_ra_tlmres_2579_2713_v1.bc: 100%|██████████| 1.86M/1.86M [00:01<00:00, 1.74MB/s]
+
+msl_surf_rsm_tlmres_2579_2713_v1.bc:  49%|████▉     | 1.74M/3.56M [00:01<00:00, 2.88MB/s]
+msl_surf_hga_tlm_2579_2713_v1.bc: 100%|██████████| 2.17M/2.17M [00:01<00:00, 1.98MB/s]
+msl_surf_ra_tlmenc_2579_2713_v1.bc: 100%|██████████| 3.13M/3.13M [00:01<00:00, 2.81MB/s]
+msl_hflb_20120731_c03.ti: 100%|██████████| 7.77k/7.77k [00:00<00:00, 13.2MB/s]
+msl_surf_rsm_tlmenc_2579_2713_v1.bc:  86%|████████▌ | 3.49M/4.08M [00:01<00:00, 5.62MB/s]
+msl_surf_rsm_tlmres_2579_2713_v1.bc: 100%|██████████| 3.56M/3.56M [00:01<00:00, 2.91MB/s]
+
+msl_aux_v00.ti: 100%|██████████| 11.3k/11.3k [00:00<00:00, 29.3MB/s]
+msl_hfra_20120731_c03.ti: 100%|██████████| 7.77k/7.77k [00:00<00:00, 13.2MB/s]
+msl_hblb_20120731_c03.ti: 100%|██████████| 7.76k/7.76k [00:00<00:00, 4.88MB/s]
+msl_hbrb_20120731_c03.ti: 100%|██████████| 7.77k/7.77k [00:00<00:00, 14.4MB/s]
+msl_hfla_20120731_c03.ti: 100%|██████████| 7.77k/7.77k [00:00<00:00, 14.0MB/s]
+msl_mahli_20120731_c02.ti: 100%|██████████| 7.70k/7.70k [00:00<00:00, 14.0MB/s]
+msl_chrmi_20120731_c03.ti: 100%|██████████| 7.38k/7.38k [00:00<00:00, 13.2MB/s]
+msl_hbla_20120731_c03.ti: 100%|██████████| 7.76k/7.76k [00:00<00:00, 14.0MB/s]
+msl_hfrb_20120731_c03.ti: 100%|██████████| 7.77k/7.77k [00:00<00:00, 13.9MB/s]
+msl_nla_20120731_c04.ti: 100%|██████████| 7.70k/7.70k [00:00<00:00, 19.9MB/s]
+msl_mardi_20120731_c02.ti: 100%|██████████| 7.62k/7.62k [00:00<00:00, 13.4MB/s]
+msl_ml_20120731_c03.ti: 100%|██████████| 7.72k/7.72k [00:00<00:00, 15.9MB/s]
+msl_mr_20120731_c03.ti: 100%|██████████| 7.72k/7.72k [00:00<00:00, 4.39MB/s]
+msl_nra_20120731_c04.ti: 100%|██████████| 7.71k/7.71k [00:00<00:00, 14.6MB/s]
+msl_nrb_20130530_c05.ti: 100%|██████████| 7.72k/7.72k [00:00<00:00, 13.9MB/s]
+msl_struct_v01.ti: 100%|██████████| 10.3k/10.3k [00:00<00:00, 16.9MB/s]
+msl_nlb_20130530_c05.ti: 100%|██████████| 7.72k/7.72k [00:00<00:00, 22.5MB/s]
+msl_lmst_ops120808_v1.tsc: 100%|██████████| 5.80k/5.80k [00:00<00:00, 13.8MB/s]
+naif0012.tls: 100%|██████████| 6.70k/6.70k [00:00<00:00, 9.87MB/s]
+mar085s.bsp:   0%|          | 0/89539584 [00:00<?, ?it/s]0:00<?, ?it/s]
+msl_ls_ops120808_iau2000_v1.bsp: 100%|██████████| 8.00k/8.00k [00:00<00:00, 15.9MB/s]
+
+mar085s.bsp:   0%|          | 4.00k/85.4M [00:00<58:05, 25.7kB/s]<00:02, 25.6kB/s]
+msl_76_sclkscet_refit_s8.tsc: 100%|██████████| 55.7k/55.7k [00:00<00:00, 178kB/s] 
+mar085s.bsp:   0%|          | 36.0k/85.4M [00:00<11:22, 131kB/s] 
+msl_surf_rover_loc_2224_2358_v1.bsp:   0%|          | 0/256000 [00:00<?, ?it/s]
+pck00008.tpc: 100%|██████████| 111k/111k [00:00<00:00, 236kB/s] 1kB/s] 
+mar085s.bsp:   0%|          | 84.0k/85.4M [00:00<07:02, 212kB/s]
+msl_surf_rover_loc_2224_2358_v1.bsp:   2%|▏         | 4.00k/250k [00:00<00:09, 25.6kB/s]
+msl_struct_v02.bsp: 100%|██████████| 102k/102k [00:00<00:00, 217kB/s] 
+de425s.bsp:   1%|          | 100k/8.84M [00:00<00:35, 259kB/s] 
+mar085s.bsp:   0%|          | 196k/85.4M [00:00<03:37, 411kB/s] [00:00<?, ?it/s]
+msl_surf_rover_loc_2003_2127_v1.bsp:   0%|          | 0/344064 [00:00<?, ?it/s]131kB/s] 
+mar085s.bsp:   0%|          | 420k/85.4M [00:00<01:54, 780kB/s]9M [00:00<01:45, 25.7kB/s]
+msl_surf_rover_loc_2003_2127_v1.bsp:   1%|          | 4.00k/336k [00:00<00:13, 25.7kB/s][A
+msl_surf_rover_loc_0000_2003_v1.bsp:   1%|▏         | 36.0k/2.59M [00:00<00:20, 131kB/s] 
+mar085s.bsp:   1%|          | 852k/85.4M [00:00<01:00, 1.45MB/s]00:00<?, ?it/s]
+msl_surf_rover_loc_2224_2358_v1.bsp: 100%|██████████| 250k/250k [00:00<00:00, 399kB/s] 
+msl_surf_rover_loc_2003_2127_v1.bsp:  11%|█         | 36.0k/336k [00:00<00:02, 131kB/s] 
+msl_surf_rover_loc_0000_2003_v1.bsp:   3%|▎         | 84.0k/2.59M [00:00<00:12, 212kB/s]
+msl_surf_rover_loc_2003_2127_v1.bsp:  25%|██▌       | 84.0k/336k [00:00<00:01, 211kB/s]]
+msl_surf_rover_loc_2837_2934_v1.bsp:   0%|          | 0/225280 [00:00<?, ?it/s]
+msl_surf_rover_loc_0000_2003_v1.bsp:   7%|▋         | 180k/2.59M [00:00<00:06, 371kB/s] 
+msl_surf_rover_loc_2003_2127_v1.bsp:  49%|████▉     | 164k/336k [00:00<00:00, 330kB/s] ]
+msl_surf_rover_loc_2837_2934_v1.bsp:   2%|▏         | 4.00k/220k [00:00<00:08, 25.3kB/s]
+msl_surf_rover_loc_2003_2127_v1.bsp: 100%|██████████| 336k/336k [00:00<00:00, 524kB/s]]
+
+de425s.bsp:  72%|███████▏  | 6.36M/8.84M [00:01<00:00, 9.82MB/s] [00:00<00:01, 131kB/s] [A
+msl_surf_rover_loc_2837_2934_v1.bsp:  16%|█▋        | 36.0k/220k [00:00<00:01, 130kB/s] 
+msl_surf_rover_loc_0000_2003_v1.bsp:  29%|██▉       | 772k/2.59M [00:00<00:01, 1.32MB/s]
+msl_surf_rover_loc_2579_2713_v1.bsp: 100%|██████████| 294k/294k [00:00<00:00, 468kB/s] 
+de425s.bsp: 100%|██████████| 8.84M/8.84M [00:01<00:00, 6.16MB/s] [00:00<00:00, 211kB/s]
+mar085s.bsp:  14%|█▎        | 11.6M/85.4M [00:01<00:05, 15.1MB/s]0:00<?, ?it/s]
+msl_surf_rover_loc_2837_2934_v1.bsp:  38%|███▊      | 84.0k/220k [00:00<00:00, 211kB/s]
+msl_surf_rover_loc_2127_2224_v1.bsp: 100%|██████████| 206k/206k [00:00<00:00, 329kB/s] s]
+msl_surf_rover_loc_0000_2003_v1.bsp: 100%|██████████| 2.59M/2.59M [00:01<00:00, 2.29MB/s]
+msl_surf_rover_loc_2358_2482_v1.bsp:   1%|▏         | 4.00k/270k [00:00<00:10, 25.8kB/s]
+msl_surf_rover_loc_2837_2934_v1.bsp: 100%|██████████| 220k/220k [00:00<00:00, 350kB/s] 
+msl_surf_rover_loc_2713_2837_v1.bsp:   1%|          | 4.00k/333k [00:00<00:13, 25.6kB/s]
+msl_surf_rover_loc_3192_3289_v1.bsp:   0%|          | 0/313344 [00:00<?, ?it/s]
+msl_surf_rover_loc_2358_2482_v1.bsp: 100%|██████████| 270k/270k [00:00<00:00, 431kB/s] 
+mar085s.bsp:  29%|██▉       | 24.9M/85.4M [00:02<00:03, 19.0MB/s][00:00<00:02, 131kB/s] 
+msl_surf_rover_loc_2934_3068_v1.bsp:   0%|          | 0/423936 [00:00<?, ?it/s]25.4kB/s]
+msl_surf_rover_loc_3068_3192_v1.bsp:   1%|          | 4.00k/355k [00:00<00:14, 25.6kB/s]
+mar085s.bsp:  31%|███       | 26.1M/85.4M [00:02<00:03, 17.0MB/s]0:00<?, ?it/s]
+msl_surf_rover_loc_2713_2837_v1.bsp:  25%|██▌       | 84.0k/333k [00:00<00:01, 211kB/s]
+msl_surf_rover_loc_2934_3068_v1.bsp:   1%|          | 4.00k/414k [00:00<00:16, 25.7kB/s]
+msl_surf_rover_loc_3068_3192_v1.bsp:  10%|█         | 36.0k/355k [00:00<00:02, 131kB/s] 
+mar085s.bsp:  33%|███▎      | 28.5M/85.4M [00:02<00:03, 18.7MB/s][00:00<00:08, 25.7kB/s]
+msl_surf_rover_loc_2713_2837_v1.bsp: 100%|██████████| 333k/333k [00:00<00:00, 527kB/s] ]
+
+msl_surf_rover_loc_2934_3068_v1.bsp:   9%|▊         | 36.0k/414k [00:00<00:02, 131kB/s] [A
+msl_surf_rover_loc_3068_3192_v1.bsp:  28%|██▊       | 100k/355k [00:00<00:01, 258kB/s] 
+mar085s.bsp:  37%|███▋      | 31.8M/85.4M [00:02<00:03, 17.1MB/s][00:00<00:01, 131kB/s] 
+msl_surf_rover_loc_3547_3644_v1.bsp:  11%|█▏        | 36.0k/314k [00:00<00:02, 131kB/s] 
+msl_surf_rover_loc_3192_3289_v1.bsp: 100%|██████████| 306k/306k [00:00<00:00, 485kB/s] 
+msl_surf_rover_loc_2934_3068_v1.bsp:  20%|██        | 84.0k/414k [00:00<00:01, 211kB/s]
+msl_surf_rover_loc_3068_3192_v1.bsp: 100%|██████████| 355k/355k [00:00<00:00, 565kB/s]
+
+msl_surf_rover_loc_3423_3547_v1.bsp:   0%|          | 0/391168 [00:00<?, ?it/s]212kB/s]
+msl_surf_rover_loc_2934_3068_v1.bsp:  43%|████▎     | 180k/414k [00:00<00:00, 371kB/s] 
+msl_surf_rover_loc_2482_2579_v1.bsp: 100%|██████████| 208k/208k [00:00<00:00, 332kB/s] 
+msl_surf_rover_loc_3423_3547_v1.bsp:   1%|          | 4.00k/382k [00:00<00:15, 25.7kB/s]
+msl_surf_rover_loc_3547_3644_v1.bsp: 100%|██████████| 314k/314k [00:00<00:00, 501kB/s] 
+msl_surf_rover_loc_2934_3068_v1.bsp: 100%|██████████| 414k/414k [00:00<00:00, 529kB/s]
+msl_surf_rover_loc_3423_3547_v1.bsp: 100%|██████████| 382k/382k [00:00<00:00, 606kB/s] ]
+msl_surf_rover_loc_3289_3423_v1.bsp:  10%|█         | 36.0k/356k [00:00<00:02, 131kB/s] 
+mar085s.bsp:  57%|█████▋    | 48.5M/85.4M [00:03<00:02, 16.5MB/s]0:00<?, ?it/s]
+msl_surf_rover_loc_3289_3423_v1.bsp:  24%|██▎       | 84.0k/356k [00:00<00:01, 212kB/s]
+msl_surf_rover_loc_3778_3902_v1.bsp:   1%|          | 4.00k/354k [00:00<00:13, 25.7kB/s]
+msl_surf_rover_loc_3289_3423_v1.bsp: 100%|██████████| 356k/356k [00:00<00:00, 566kB/s] ]
+
+mar085s.bsp:  64%|██████▎   | 54.3M/85.4M [00:04<00:01, 16.9MB/s][00:00<00:02, 131kB/s] 
+mar085s.bsp:  67%|██████▋   | 56.8M/85.4M [00:04<00:01, 19.1MB/s][00:00<00:02, 131kB/s] 
+msl_surf_rover_loc_3778_3902_v1.bsp:  24%|██▎       | 84.0k/354k [00:00<00:01, 211kB/s]
+mar085s.bsp:  69%|██████▉   | 58.9M/85.4M [00:04<00:01, 20.0MB/s][00:00<00:01, 210kB/s]
+mar085s.bsp:  70%|███████   | 59.8M/85.4M [00:04<00:01, 16.5MB/s]00:00<00:00, 371kB/s] 
+msl_surf_rover_loc_3778_3902_v1.bsp: 100%|██████████| 354k/354k [00:00<00:00, 557kB/s] 
+mar085s.bsp:  73%|███████▎  | 62.7M/85.4M [00:04<00:01, 19.6MB/s]
+msl_surf_rover_loc_3644_3778_v1.bsp: 100%|██████████| 363k/363k [00:00<00:00, 462kB/s]
+mar085s.bsp: 100%|██████████| 85.4M/85.4M [00:05<00:00, 15.3MB/s]
+
+
+
+
import spiceypy as spice
+
+
+
spice.furnsh(str(mkpath))
+
+
+
mkpath
+
+
Path('/home/ayek72/mnt/slowdata/planetarypy/spice_kernels/msl/msl_v34_200101_200105.tm')
+
+
+
+
!cat {mkpath}
+
+
KPL/MK
+
+   This meta-kernel lists a subset of kernels from the meta-kernel
+   msl_v34.tm provided in the MSL-M-SPICE-6-V1.0 SPICE PDS3 archive,
+   covering the whole or a part of the customer requested time period
+   from 2020-01-01T00:00:00.000 to 2020-01-05T00:00:00.000.
+
+   The documentation describing these kernels can be found in the
+   complete MSL-M-SPICE-6-V1.0 SPICE PDS3 archive available at this URL
+
+   https://naif.jpl.nasa.gov/pub/naif/pds/data/msl-m-spice-6-v1.0/mslsp_1000
+
+   To use this meta-kernel users may need to modify the value of the
+   PATH_VALUES keyword to point to the actual location of the archive's
+   ``data'' directory on their system. Replacing ``/'' with ``\''
+   and converting line terminators to the format native to the user's
+   system may also be required if this meta-kernel is to be used on a
+   non-UNIX workstation.
+
+   This meta-kernel was created by the NAIF node's SPICE PDS archive
+   subsetting service version 2.1 on Fri Dec  1 09:03:32 PST 2023.
+
+ 
+   \begindata
+ 
+      PATH_VALUES     = (
+                         '/home/ayek72/mnt/slowdata/planetarypy/spice_kernels/msl'
+                        )
+ 
+      PATH_SYMBOLS    = (
+                         'KERNELS'
+                        )
+ 
+      KERNELS_TO_LOAD = (
+                         '$KERNELS/lsk/naif0012.tls'
+                         '$KERNELS/pck/pck00008.tpc'
+                         '$KERNELS/sclk/msl_lmst_ops120808_v1.tsc'
+                         '$KERNELS/sclk/msl_76_sclkscet_refit_s8.tsc'
+                         '$KERNELS/fk/msl_v08.tf'
+                         '$KERNELS/ik/msl_aux_v00.ti'
+                         '$KERNELS/ik/msl_chrmi_20120731_c03.ti'
+                         '$KERNELS/ik/msl_hbla_20120731_c03.ti'
+                         '$KERNELS/ik/msl_hblb_20120731_c03.ti'
+                         '$KERNELS/ik/msl_hbra_20120731_c03.ti'
+                         '$KERNELS/ik/msl_hbrb_20120731_c03.ti'
+                         '$KERNELS/ik/msl_hfla_20120731_c03.ti'
+                         '$KERNELS/ik/msl_hflb_20120731_c03.ti'
+                         '$KERNELS/ik/msl_hfra_20120731_c03.ti'
+                         '$KERNELS/ik/msl_hfrb_20120731_c03.ti'
+                         '$KERNELS/ik/msl_mahli_20120731_c02.ti'
+                         '$KERNELS/ik/msl_mardi_20120731_c02.ti'
+                         '$KERNELS/ik/msl_ml_20120731_c03.ti'
+                         '$KERNELS/ik/msl_mr_20120731_c03.ti'
+                         '$KERNELS/ik/msl_nla_20120731_c04.ti'
+                         '$KERNELS/ik/msl_nlb_20130530_c05.ti'
+                         '$KERNELS/ik/msl_nra_20120731_c04.ti'
+                         '$KERNELS/ik/msl_nrb_20130530_c05.ti'
+                         '$KERNELS/ik/msl_struct_v01.ti'
+                         '$KERNELS/spk/msl_struct_v02.bsp'
+                         '$KERNELS/spk/de425s.bsp'
+                         '$KERNELS/spk/mar085s.bsp'
+                         '$KERNELS/spk/msl_ls_ops120808_iau2000_v1.bsp'
+                         '$KERNELS/spk/msl_surf_rover_loc_0000_2003_v1.bsp'
+                         '$KERNELS/spk/msl_surf_rover_loc_2003_2127_v1.bsp'
+                         '$KERNELS/spk/msl_surf_rover_loc_2127_2224_v1.bsp'
+                         '$KERNELS/spk/msl_surf_rover_loc_2224_2358_v1.bsp'
+                         '$KERNELS/spk/msl_surf_rover_loc_2358_2482_v1.bsp'
+                         '$KERNELS/spk/msl_surf_rover_loc_2482_2579_v1.bsp'
+                         '$KERNELS/spk/msl_surf_rover_loc_2579_2713_v1.bsp'
+                         '$KERNELS/spk/msl_surf_rover_loc_2713_2837_v1.bsp'
+                         '$KERNELS/spk/msl_surf_rover_loc_2837_2934_v1.bsp'
+                         '$KERNELS/spk/msl_surf_rover_loc_2934_3068_v1.bsp'
+                         '$KERNELS/spk/msl_surf_rover_loc_3068_3192_v1.bsp'
+                         '$KERNELS/spk/msl_surf_rover_loc_3192_3289_v1.bsp'
+                         '$KERNELS/spk/msl_surf_rover_loc_3289_3423_v1.bsp'
+                         '$KERNELS/spk/msl_surf_rover_loc_3423_3547_v1.bsp'
+                         '$KERNELS/spk/msl_surf_rover_loc_3547_3644_v1.bsp'
+                         '$KERNELS/spk/msl_surf_rover_loc_3644_3778_v1.bsp'
+                         '$KERNELS/spk/msl_surf_rover_loc_3778_3902_v1.bsp'
+                         '$KERNELS/ck/msl_ra_toolsref_v1.bc'
+                         '$KERNELS/ck/msl_surf_hga_tlm_2579_2713_v1.bc'
+                         '$KERNELS/ck/msl_surf_ra_tlmenc_2579_2713_v1.bc'
+                         '$KERNELS/ck/msl_surf_ra_tlmres_2579_2713_v1.bc'
+                         '$KERNELS/ck/msl_surf_rover_tlm_2579_2713_v1.bc'
+                         '$KERNELS/ck/msl_surf_rsm_tlmenc_2579_2713_v1.bc'
+                         '$KERNELS/ck/msl_surf_rsm_tlmres_2579_2713_v1.bc'
+                        )
+ 
+   \begintext
+ 
+
+
+
+ + +
+
+ +
+ + +
+ + + + \ No newline at end of file diff --git a/tutorials/pdw_2023.html b/tutorials/pdw_2023.html new file mode 100644 index 0000000..37628ac --- /dev/null +++ b/tutorials/pdw_2023.html @@ -0,0 +1,1472 @@ + + + + + + + + + + + +planetarypy - On the way to a core PlanetaryPy Package + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

On the way to a core PlanetaryPy Package

+
+ + + +
+ +
+
Author
+
+

Michael Aye

+
+
+ +
+
Published
+
+

June 26, 2023

+
+
+ + +
+ + +
+ + +
+

What is this?

+
    +
  • PlanetaryPy organization is community effort to +
      +
    • develop a core Python package for planetary science
      • +
    • help other planetary science Python programmers to disseminate their work
      • +
    • +
  • This talk is about the core package status only.
    • +
+
+
+
+
+

Core package work plan

+
    +
  • I am since long working on a core package draft.
    • +
  • Nothing is especially clever, the structured unification is the clue!
    • +
  • Shall be submitted (done?) to the community members for review.
    • +
  • After successful review open for public pull requests and hackathons.
    • +
+
+
+
+

Core package focal points

+
    +
  • Easier access, download, and local management of +
      +
    • PDS data
      • +
    • SPICE kernels
      • +
    • +
  • Removing need to learn various web interfaces for different data
    • +
  • Working easier with collections of PDS data
    • +
  • Easy basic SPICE calculations with human readable I/F
    • +
  • Some web and time related utilities
    • +
+
+
+
+
+

PDS Indexes

+
+

PDS Indexes

+
+
+
    +
  • PDS Indexes contain useful meta-data for PDS datasets
    • +
  • planetarypy provides access to these via a config file +
      +
    • pull requests to config file will add more findable indices!
      • +
    • +
  • config file tells planetarypy where to find index
    • +
+
+
    +
  • planetarypy downloads index file and
    • +
  • stored as parquet file, ready for pandas based analysis.
    • +
  • tells user when new index is available
    • +
+
+
+
+
+

Example use

+
+
from planetarypy.pds.apps import get_index
+
+df = get_index("cassini.iss", "index")
+print(df.info())
+df.head(3)["FILE_NAME IMAGE_MID_TIME IMAGE_OBSERVATION_TYPE".split()]
+
+
<class 'pandas.core.frame.DataFrame'>
+RangeIndex: 407299 entries, 0 to 407298
+Columns: 140 entries, FILE_NAME to STANDARD_DATA_PRODUCT_ID
+dtypes: Float64(70), Int64(20), datetime64[ns](7), string(43)
+memory usage: 470.0 MB
+None
+
+
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
FILE_NAMEIMAGE_MID_TIMEIMAGE_OBSERVATION_TYPE
0N1454725799_1.IMG2004-02-06 02:07:06.458OPNAV
1N1454726579_1.IMG2004-02-06 02:20:06.362OPNAV
2N1454727359_1.IMG2004-02-06 02:33:06.397OPNAV
+ +
+
+
+
+
+
+

Instrument data

+
+

Instrument data

+
    +
  • Meant to serve as basic data access, read, and access classes +
      +
    • to be boosted in the future by the GOAT PDS reader pdr by Million, Inc.
      • +
    • +
  • config file controls what data levels are accessible +
      +
    • and how they are stored locally
      • +
    • +
  • currently CTX, HiRISE, UVIS, CISS are supported (Diviner in the works)
    • +
+
+
+

Example use HiRISE

+
+
from planetarypy.hirise import ProductPathfinder as PPF
+
+ppf = PPF("PSP_003092_0985_RED")
+
+print(ppf.jp2_path)
+print(ppf.homepage)
+print(ppf.abrowse_path)
+print(ppf.nomap_thumbnail_path)
+
+ + +
+
+ +
+
+ +
+
+
RDR/PSP/ORB_003000_003099/PSP_003092_0985/PSP_003092_0985_RED.JP2
+https://uahirise.org/PSP_003092_0985
+EXTRAS/RDR/PSP/ORB_003000_003099/PSP_003092_0985/PSP_003092_0985_RED.abrowse.jpg
+EXTRAS/RDR/PSP/ORB_003000_003099/PSP_003092_0985/PSP_003092_0985_RED.NOMAP.thumb.jpg
+
+
+
+
+

Example use CTXCollection

+
+
from planetarypy.ctx import CTXCollection
+
+coll = CTXCollection.by_month("F01")
+print(coll.n_items)
+print(len(coll.get_corrupted()))
+
+
1321
+35
+
+
+
+
+
+

Archived SPICE kernels

+
+

Archived SPICE kernel sets

+
+
+
    +
  • NAIF offers archived mission kernel sets for 33 missions:
    • +
  • Kernels can be subset by time window using Subset link.
    • +
  • planetarypy offers programmatic wrapper around subset feature.
    • +
+
+
    +
  • Zip file unpacked.
    • +
  • Kernel files stored locally and logically.
    • +
  • Meta-kernel edited appropriately and immediately loadable.
    • +
+
+
+

+
+
+

Example use

+
+
from planetarypy.spice import kernels
+
+kernels.datasets.drop("path", axis=1).head()
+
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Mission NamePDS3 or PDS4Data Size (GB)Start TimeStop Time
shorthand
bcBepiColombo42.32018-10-202023-06-21
cassiniCassini Orbiter362.51997-10-152017-09-15
clementineClementine30.81994-01-261994-05-07
dartDART410.02021-11-092050-01-01
dawnDAWN386.42007-09-272018-10-31
+ +
+
+
+
+

Two main user functions:

+
    +
  • get_metakernel_and_files +
      +
    • will check if the kernel files are already locally available
      • +
    • if not, download kernels
      • +
    • returns the path to the edited meta-kernel
      • +
    • +
  • list_kernels_for_day +
      +
    • will only list kernel filenames valid for the given day
      • +
    • +
+
+
+
+
+
+

Generic kernels for illumination calculations

+
+

Generic kernels

+
    +
  • Manages a minimal set for basic illumination calculations
    • +
  • Currently slightly biased for Mars but many other bodies work
    • +
  • Kernels are automatically downloaded and loaded when needed.
    • +
+
+
+

Example use

+
+
from planetarypy.spice.spicer import MoonSpicer
+
+moon = MoonSpicer("2022-02-22")
+print(f"Sol. const: {moon.solar_constant:.1f}")
+moon.set_spoint_by(lat=0, lon=0)
+moon.aspect = 180
+moon.tilt = 30
+print(f"Irradiance on tilted surface element: {moon.F_tilt:.1f}")
+
+
Sol. const: 1388.4 W / m2
+Irradiance on tilted surface element: 412.5 W / m2
+
+
+
+
+
+

Come to the demo session!

+ + +
+ +
+ +
+ + + + \ No newline at end of file diff --git a/tutorials/pdw_2023.html.pptx b/tutorials/pdw_2023.html.pptx new file mode 100644 index 0000000..3c023de Binary files /dev/null and b/tutorials/pdw_2023.html.pptx differ diff --git a/tutorials/spice_howtos.html b/tutorials/spice_howtos.html new file mode 100644 index 0000000..ced8ac6 --- /dev/null +++ b/tutorials/spice_howtos.html @@ -0,0 +1,708 @@ + + + + + + + + + + +planetarypy - SPICE with planetarypy HOWTO + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

SPICE with planetarypy HOWTO

+
+ +
+
+ Several useful SPICE related HOWTOs posssible to do with planetarypy +
+
+ + +
+ + + + +
+ + +
+ + +
+

Surface calculations on the Moon

+
+
from astropy import units as u
+from numpy.linalg import norm
+
+from planetarypy.spice.spicer import MoonSpicer, MarsSpicer
+
+
+
moon = MoonSpicer("2022-02-22")
+
+
+
moon.time.isoformat()
+
+
'2022-02-22T00:00:00'
+
+
+
+
moon.solar_constant
+
+

\(1388.4482 \; \mathrm{\frac{W}{m^{2}}}\)

+
+
+
+
moon.set_spoint_by(lat=0, lon=0)
+
+
+
moon.aspect = 180
+moon.tilt = 30
+
+
+
moon.F_flat
+
+

\(497.68762 \; \mathrm{\frac{W}{m^{2}}}\)

+
+
+
+
moon.F_aspect
+
+

\(449.48514 \; \mathrm{\frac{W}{m^{2}}}\)

+
+
+
+
moon.F_tilt
+
+

\(412.53511 \; \mathrm{\frac{W}{m^{2}}}\)

+
+
+
+
moon.subsolar
+
+
array([  622.78676959, -1621.28270346,   -46.23629622])
+
+
+
+
moon.local_soltime
+
+
'16:35:58'
+
+
+
+
# MoonSpicer returns km (as all calculations in SPICE do)
+# use astropy.units to convert to other values
+norm(moon.body_to_object("EARTH")[0]) * u.km
+
+

\(375365.92 \; \mathrm{km}\)

+
+
+
+
(norm(moon.body_to_object("MARS")[0]) * u.km).to(u.AU)
+
+

\(2.0379563 \; \mathrm{AU}\)

+
+
+
+
mars = MarsSpicer()
+
+
+
mars.utc
+
+
'2023-06-27T18:37:50.876055'
+
+
+
+
mars.l_s
+
+
83.31658188802474
+
+
+
+
mars.goto('inca')
+
+
+
mars.spoint
+
+
(220.09830399469547, -440.60853011059214, -3340.5081261541495)
+
+
+
+
mars.aspect=180
+mars.tilt=30
+
+
+
mars.F_flat
+
+

\(0 \; \mathrm{\frac{W}{m^{2}}}\)

+
+
+
+
mars.F_aspect
+
+

\(0 \; \mathrm{\frac{W}{m^{2}}}\)

+
+
+
+
mars.set_spoint_by(lat=0, lon=0)
+
+
+
mars.F_flat
+
+

\(339.2043 \; \mathrm{\frac{W}{m^{2}}}\)

+
+
+
+
mars.F_tilt
+
+

\(397.92501 \; \mathrm{\frac{W}{m^{2}}}\)

+
+
+ + +
+ +
+ +
+ + + + \ No newline at end of file diff --git a/tutorials/tutorial.html b/tutorials/tutorial.html new file mode 100644 index 0000000..48736d5 --- /dev/null +++ b/tutorials/tutorial.html @@ -0,0 +1,1743 @@ + + + + + + + + + +planetarypy - Tutorial + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Tutorial

+
+ + + +
+ + + + +
+ + +
+ + +
+
from planetarypy.pds.apps import find_indexes, get_index, find_instruments
+
+
+
find_instruments?
+
+
+
Signature: find_instruments(mission: str) -> list
+Docstring: Find existing instruments for a mission.
+File:      ~/Dropbox/src/nbplanetary/planetarypy/pds/apps.py
+Type:      function
+
+
+
+
+
find_instruments("mro")
+
+
['hirise', 'ctx']
+
+
+

Now, seeing that the CTX instrument is supported, one could ask what index files (= catalogs) are available, using the dotted code for mission.instrument:

+
+
find_indexes("mro.ctx")
+
+
['edr']
+
+
+

We only have one index file for EDR data. Let’s get it, using the now 3-segments dot-code (it returns a pandas Dataframe):

+
+
index = get_index('mro.ctx.edr', refresh=False)
+index.head()
+
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
VOLUME_IDFILE_SPECIFICATION_NAMEORIGINAL_PRODUCT_IDPRODUCT_IDIMAGE_TIMEINSTRUMENT_IDINSTRUMENT_MODE_IDLINE_SAMPLESLINESSPATIAL_SUMMING...SUB_SOLAR_LATITUDESUB_SPACECRAFT_LONGITUDESUB_SPACECRAFT_LATITUDESOLAR_DISTANCESOLAR_LONGITUDELOCAL_TIMEIMAGE_SKEW_ANGLERATIONALE_DESCDATA_QUALITY_DESCORBIT_NUMBER
0MROX_0001DATA/CRU_000001_9999_XN_99N999W.IMG4A_04_0001000400CRU_000001_9999_XN_99N999W2005-08-30 15:40:21.549CTXNIFL505610241...0.00.00.00.0278.8910.160.0Instrument checkout image of spaceOK-4242
1MROX_0001DATA/CRU_000002_9999_XN_99N999W.IMG4A_04_0001000500CRU_000002_9999_XN_99N999W2005-09-08 15:59:45.313CTXNIFL5056153601...0.00.00.00.0284.484.60.0Calibration image of the MoonOK-4126
2MROX_0001DATA/CRU_000003_9999_XN_99N999W.IMG4A_04_0001000600CRU_000003_9999_XN_99N999W2005-09-08 16:03:37.927CTXNIFL505620481...0.00.00.00.0284.484.660.0Calibration image of Omega Centauri (globular ...OK-4126
3MROX_0001DATA/CRU_000004_9999_XN_99N999W.IMG4A_04_0001000700CRU_000004_9999_XN_99N999W2005-09-08 16:08:23.841CTXNIFL505620481...0.00.00.00.0284.484.740.0Calibration image of Omega Centauri (globular ...OK-4126
4MROX_0001DATA/CRU_000005_9999_XN_99N999W.IMG4A_04_0001000800CRU_000005_9999_XN_99N999W2005-09-08 16:11:18.649CTXNIFL5056215041...0.00.00.00.0284.484.790.0Calibration image of the MoonOK-4126
+ +

5 rows × 51 columns

+
+
+
+

You might have ssen, that planetarypy realized that the existing index on my disk was outdated and proceeded to get an updated one.

+

The warning is about badly formatted data on the PDS for which planetarypy had to force path names to the correct letter case. This is not something we can influence, but we reported the issue at the PDS, and here, we just let the user know, that we fudged around that issue.

+

Note that the catalog ascii times have been converted to proper datetime objects, using the utility functions in planetarypy.utils. This means that you can use these times to create proper plots over time in case you are interested in catalog statistics.

+
+
index.IMAGE_TIME
+
+
0        2005-08-30 15:40:21.549
+1        2005-09-08 15:59:45.313
+2        2005-09-08 16:03:37.927
+3        2005-09-08 16:08:23.841
+4        2005-09-08 16:11:18.649
+                   ...          
+142363   2023-03-01 00:01:37.834
+142364   2023-03-01 00:15:17.076
+142365   2023-03-01 00:19:04.486
+142366   2023-03-01 00:29:24.818
+142367   2023-03-01 00:43:08.662
+Name: IMAGE_TIME, Length: 142368, dtype: datetime64[ns]
+
+
+

Using standard pandas operations, we can now filte the data down, and identify a data product we are interested in:

+
+
index.columns
+
+
Index(['VOLUME_ID', 'FILE_SPECIFICATION_NAME', 'ORIGINAL_PRODUCT_ID',
+       'PRODUCT_ID', 'IMAGE_TIME', 'INSTRUMENT_ID', 'INSTRUMENT_MODE_ID',
+       'LINE_SAMPLES', 'LINES', 'SPATIAL_SUMMING', 'SCALED_PIXEL_WIDTH',
+       'PIXEL_ASPECT_RATIO', 'EMISSION_ANGLE', 'INCIDENCE_ANGLE',
+       'PHASE_ANGLE', 'CENTER_LONGITUDE', 'CENTER_LATITUDE',
+       'UPPER_LEFT_LONGITUDE', 'UPPER_LEFT_LATITUDE', 'UPPER_RIGHT_LONGITUDE',
+       'UPPER_RIGHT_LATITUDE', 'LOWER_LEFT_LONGITUDE', 'LOWER_LEFT_LATITUDE',
+       'LOWER_RIGHT_LONGITUDE', 'LOWER_RIGHT_LATITUDE', 'MISSION_PHASE_NAME',
+       'TARGET_NAME', 'SPACECRAFT_CLOCK_START_COUNT',
+       'FOCAL_PLANE_TEMPERATURE', 'LINE_EXPOSURE_DURATION', 'OFFSET_MODE_ID',
+       'SAMPLE_FIRST_PIXEL', 'SCALED_IMAGE_WIDTH', 'SCALED_IMAGE_HEIGHT',
+       'SPACECRAFT_ALTITUDE', 'TARGET_CENTER_DISTANCE', 'SLANT_DISTANCE',
+       'USAGE_NOTE', 'NORTH_AZIMUTH', 'SUB_SOLAR_AZIMUTH',
+       'SUB_SOLAR_LONGITUDE', 'SUB_SOLAR_LATITUDE', 'SUB_SPACECRAFT_LONGITUDE',
+       'SUB_SPACECRAFT_LATITUDE', 'SOLAR_DISTANCE', 'SOLAR_LONGITUDE',
+       'LOCAL_TIME', 'IMAGE_SKEW_ANGLE', 'RATIONALE_DESC', 'DATA_QUALITY_DESC',
+       'ORBIT_NUMBER'],
+      dtype='object')
+
+
+
+
index.EMISSION_ANGLE.describe()
+
+
count     142368.0
+mean      4.396005
+std      18.999974
+min            0.0
+25%            0.1
+50%           1.56
+75%           5.94
+max          999.9
+Name: EMISSION_ANGLE, dtype: Float64
+
+
+
+
index.LOCAL_TIME.describe()
+
+
count     142368.0
+mean     15.055919
+std       1.427996
+min            0.0
+25%          14.65
+50%          15.12
+75%          15.53
+max          23.99
+Name: LOCAL_TIME, dtype: Float64
+
+
+
+
angle_filter = index.EMISSION_ANGLE < 1.0
+
+

Let’s also calculate a mean latitude and longitude instead of the image corners, for rough location filtering. As a habit, we recommend to assign lower case letters to column names that we add on top of the PDS ones:

+
+
index = index.assign(
+    lat_mean=(
+        index.UPPER_LEFT_LATITUDE
+        + index.UPPER_RIGHT_LATITUDE
+        + index.LOWER_LEFT_LATITUDE
+        + index.LOWER_RIGHT_LATITUDE) /
+    4)
+
+
+
index = index.assign(
+    lon_mean=(
+        index.UPPER_LEFT_LONGITUDE
+        + index.UPPER_RIGHT_LONGITUDE
+        + index.LOWER_LEFT_LONGITUDE
+        + index.LOWER_RIGHT_LONGITUDE) /
+    4)
+
+
+
index.info()
+
+
<class 'pandas.core.frame.DataFrame'>
+RangeIndex: 142368 entries, 0 to 142367
+Data columns (total 53 columns):
+ #   Column                        Non-Null Count   Dtype         
+---  ------                        --------------   -----         
+ 0   VOLUME_ID                     142368 non-null  string        
+ 1   FILE_SPECIFICATION_NAME       142368 non-null  string        
+ 2   ORIGINAL_PRODUCT_ID           142368 non-null  string        
+ 3   PRODUCT_ID                    142368 non-null  string        
+ 4   IMAGE_TIME                    142368 non-null  datetime64[ns]
+ 5   INSTRUMENT_ID                 142368 non-null  string        
+ 6   INSTRUMENT_MODE_ID            142368 non-null  string        
+ 7   LINE_SAMPLES                  142368 non-null  Int64         
+ 8   LINES                         142368 non-null  Int64         
+ 9   SPATIAL_SUMMING               142368 non-null  Int64         
+ 10  SCALED_PIXEL_WIDTH            142368 non-null  Float64       
+ 11  PIXEL_ASPECT_RATIO            142368 non-null  Float64       
+ 12  EMISSION_ANGLE                142368 non-null  Float64       
+ 13  INCIDENCE_ANGLE               142368 non-null  Float64       
+ 14  PHASE_ANGLE                   142368 non-null  Float64       
+ 15  CENTER_LONGITUDE              142368 non-null  Float64       
+ 16  CENTER_LATITUDE               142368 non-null  Float64       
+ 17  UPPER_LEFT_LONGITUDE          142368 non-null  Float64       
+ 18  UPPER_LEFT_LATITUDE           142368 non-null  Float64       
+ 19  UPPER_RIGHT_LONGITUDE         142368 non-null  Float64       
+ 20  UPPER_RIGHT_LATITUDE          142368 non-null  Float64       
+ 21  LOWER_LEFT_LONGITUDE          142368 non-null  Float64       
+ 22  LOWER_LEFT_LATITUDE           142368 non-null  Float64       
+ 23  LOWER_RIGHT_LONGITUDE         142368 non-null  Float64       
+ 24  LOWER_RIGHT_LATITUDE          142368 non-null  Float64       
+ 25  MISSION_PHASE_NAME            142368 non-null  string        
+ 26  TARGET_NAME                   142368 non-null  string        
+ 27  SPACECRAFT_CLOCK_START_COUNT  142368 non-null  string        
+ 28  FOCAL_PLANE_TEMPERATURE       142368 non-null  Float64       
+ 29  LINE_EXPOSURE_DURATION        142368 non-null  Float64       
+ 30  OFFSET_MODE_ID                142368 non-null  string        
+ 31  SAMPLE_FIRST_PIXEL            142368 non-null  Int64         
+ 32  SCALED_IMAGE_WIDTH            142368 non-null  Float64       
+ 33  SCALED_IMAGE_HEIGHT           142368 non-null  Float64       
+ 34  SPACECRAFT_ALTITUDE           142368 non-null  Float64       
+ 35  TARGET_CENTER_DISTANCE        142368 non-null  Float64       
+ 36  SLANT_DISTANCE                142368 non-null  Float64       
+ 37  USAGE_NOTE                    142368 non-null  string        
+ 38  NORTH_AZIMUTH                 142368 non-null  Float64       
+ 39  SUB_SOLAR_AZIMUTH             142368 non-null  Float64       
+ 40  SUB_SOLAR_LONGITUDE           142368 non-null  Float64       
+ 41  SUB_SOLAR_LATITUDE            142368 non-null  Float64       
+ 42  SUB_SPACECRAFT_LONGITUDE      142368 non-null  Float64       
+ 43  SUB_SPACECRAFT_LATITUDE       142368 non-null  Float64       
+ 44  SOLAR_DISTANCE                142368 non-null  Float64       
+ 45  SOLAR_LONGITUDE               142368 non-null  Float64       
+ 46  LOCAL_TIME                    142368 non-null  Float64       
+ 47  IMAGE_SKEW_ANGLE              142368 non-null  Float64       
+ 48  RATIONALE_DESC                142368 non-null  string        
+ 49  DATA_QUALITY_DESC             142368 non-null  string        
+ 50  ORBIT_NUMBER                  142368 non-null  Int64         
+ 51  lat_mean                      142368 non-null  Float64       
+ 52  lon_mean                      142368 non-null  Float64       
+dtypes: Float64(34), Int64(5), datetime64[ns](1), string(13)
+memory usage: 62.9 MB
+
+
+
+
lat_filter = index.lat_mean.between(-80,-60)
+lon_filter = index.lon_mean.between(0, 10)
+
+
+
index[angle_filter & lat_filter & lon_filter]
+
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
VOLUME_IDFILE_SPECIFICATION_NAMEORIGINAL_PRODUCT_IDPRODUCT_IDIMAGE_TIMEINSTRUMENT_IDINSTRUMENT_MODE_IDLINE_SAMPLESLINESSPATIAL_SUMMING...SUB_SPACECRAFT_LATITUDESOLAR_DISTANCESOLAR_LONGITUDELOCAL_TIMEIMAGE_SKEW_ANGLERATIONALE_DESCDATA_QUALITY_DESCORBIT_NUMBERlat_meanlon_mean
1267MROX_0035DATA/P03_002074_1155_XN_64S004W.IMG4A_04_1008005C00P03_002074_1155_XN_64S004W2007-01-05 01:02:50.418CTXNIFL5056122881...-64.59225779573.9161.5316.0290.1Dunes in Wegener Crater in MOC R15-01815OK2074-64.594.61
4551MROX_0165DATA/P09_004738_1020_XN_78S008W.IMG4A_04_1014016300P09_004738_1020_XN_78S008W2007-07-31 14:55:12.379CTXNIFL5056522241...-77.97210058626.6286.9315.3690.4South polar landformsOK4738-77.9655.9325
4677MROX_0173DATA/P10_004883_1020_XN_78S005W.IMG4A_04_1016007800P10_004883_1020_XN_78S005W2007-08-11 22:05:40.494CTXNIFL5056522241...-78.09211455781.6293.8215.2790.4South polar seasonal cap edgeOK4883-78.084.57
5184MROX_0197DATA/P11_005252_1199_XI_60S008W.IMG4A_04_101900A800P11_005252_1199_XI_60S008W2007-09-09 16:17:03.275CTXITL5056143361...-60.18215826377.3310.9214.5890.1South mid- to high-latitude craterOK5252-60.18758.6425
5395MROX_0209DATA/P11_005384_1066_XN_73S007W.IMG4A_04_1018017C00P11_005384_1066_XN_73S007W2007-09-19 23:03:52.412CTXNIFL5056358401...-73.48217613174.8316.8514.8290.3Sisyphi CaviOK5384-73.487.05
..................................................................
133106MROX_4264DATA/U09_074575_1037_XN_76S005W.IMG4A_04_117A02AC00U09_074575_1037_XN_76S005W2022-06-24 05:06:01.401CTXNIFL5056522241...-76.26206646214.2252.8915.9690.4Sisyphi Cavi regionOK74575-76.25754.98
133926MROX_4298DATA/U10_074878_1161_XN_63S005W.IMG4A_04_117C022300U10_074878_1161_XN_63S005W2022-07-17 19:55:57.184CTXNIFL2528245761...-63.93207381603.7267.8415.3590.2Southern highlandsOK74878-63.945.53
134438MROX_4315DATA/U10_075023_1075_XN_72S001W.IMG4A_04_117C042B00U10_075023_1075_XN_72S001W2022-07-29 03:04:41.315CTXNIFL505671681...-72.61208145471.6274.9415.4190.1Ride-along with HiRISEOK75023-72.62751.005
135612MROX_4352DATA/U12_075498_1055_XN_74S006W.IMG4A_04_1180007200U12_075498_1055_XN_74S006W2022-09-04 03:17:19.126CTXNIFL505671681...-74.52212296356.7297.6915.1390.1Ride-along with HiRISEOK75498-74.5356.62
136976MROX_4402DATA/U13_076012_1155_XN_64S004W.IMG4A_04_118201BB00U13_076012_1155_XN_64S004W2022-10-14 04:35:24.111CTXNIFL505671681...-64.62218924928.8321.0814.7190.1Ride-along with HiRISEOK76012-64.62753.995
+ +

119 rows × 53 columns

+
+
+
+

Copying a PRODUCT_ID, we can now automatically download it via the CTX utilities:

+
+
pid = "P03_002074_1155_XN_64S004W"
+
+
+
from planetarypy import ctx
+
+

Above could issue a warning that is about not finding an ISIS installation, which is required for SOME of this library’s features. Make sure your current environment has the environment variable ISISROOT and ISISDATA defined, so that planetarypy can find the ISIS tools, in case you want to use functions related to them.

+

Now let’s use the CTX class to access data:

+
+
data = ctx.CTX(pid)
+
+
+
data.download()
+
+
File exists. Use `overwrite=True` to download fresh.
+
+
+

The data was downloaded to a mission- and instrument-based storage folder that was defined the first time you imported planetarypy. You can verify it’s location by looking at the config object:

+
+
from planetarypy.config import config
+
+
+
config.storage_root
+
+
Path('/home/ayek72/mnt/slowdata/planetarypy')
+
+
+

We can now read the data into a multi-dimensional xarray, which supports elaborate indexing via its coordinates.

+
+
data.edr_da
+
+ +
+ + + + + + + + + + + + + + +
<xarray.DataArray 'P03_002074_1155 EDR' (y: 12288, x: 5056)>
+[62128128 values with dtype=uint8]
+Coordinates:
+  * x        (x) float64 0.5 1.5 2.5 3.5 ... 5.054e+03 5.054e+03 5.056e+03
+  * y        (y) float64 0.5 1.5 2.5 3.5 ... 1.229e+04 1.229e+04 1.229e+04
+Attributes: (12/19)
+    BANDWIDTH:                  
+    CENTER_FILTER_WAVELENGTH:   
+    DATA_SET_ID:                "MRO-M-CTX-2-EDR-L0-V1.0"
+    FILTER_NAME:                
+    INSTRUMENT_ID:              CTX
+    INSTRUMENT_NAME:            "CONTEXT CAMERA"
+    ...                         ...
+    START_TIME:                 2007-01-05T01:02:50.418
+    STOP_TIME:                  2007-01-05T01:03:13.479
+    TARGET_NAME:                MARS
+    _FillValue:                 0
+    scale_factor:               1.0
+    add_offset:                 0.0
+
+
+

But one also get the image data simply as a numpy array:

+
+
data.edr_da.values
+
+
array([[ 9,  9, 10, ...,  8, 10,  8],
+       [ 9,  8, 10, ...,  9, 10,  9],
+       [ 9,  8, 10, ...,  8, 11, 10],
+       ...,
+       [11, 10, 11, ..., 10, 10, 10],
+       [10,  9, 10, ...,  9, 10, 10],
+       [11, 10, 10, ..., 11, 11, 10]], dtype=uint8)
+
+
+

Or plot the image using holoviews and datashader, so that even large images won’t bog down your browser:

+
+
data.plot_edr()
+
+ +
+
+ +
+
+
+ +
+
+

Note, that the above data is the uncalibrated EDR, so the dynamics of the image seem a little rough. If you have configured the ISIS properly, so that the current Python environment is aware of it (using ISISROOT and ISISDATA env variables), you can calibrate this data yourself now:

+ + + +
+ +
+ + + + \ No newline at end of file