Merge pull request #269 from texadactyl/master

Implement enhancement request #264

VERSION-HISTORY.md

@@ -3,6 +3,7 @@ This file is a version history of blimpy amendments, beginning with version 2.0.
 <br>
 |    Date    | Version | Contents |
 | :--: | :--: | :-- |
+| 2022-07-20 | 2.1.1  | Mods to Waterfall class, an alternative to file loading (issue #264). |
 | 2022-07-08 | 2.1.0  | New utility: dsamp (issue #267). |
 | 2022-04-19 | 2.0.40 | Fixed blimpy to show plots when the display supports it (issue #263). |
 | 2022-03-30 | 2.0.39 | examine_h5 in hdf_reader.py is loading too much data (issue #261). |

blimpy/waterfall.py

@@ -60,9 +60,73 @@
 class Waterfall():
     """ Class for loading and writing blimpy data (.fil, .h5) """
 
+
     def __repr__(self):
         return "Waterfall data: %s" % self.filename
 
+
+    def _init_alternate(self, header_dict, data, filename=None):
+
+        # Validate parameters.
+        assert filename is None
+        assert isinstance(header_dict, dict)
+        assert "nchans" in header_dict
+        assert "fch1" in header_dict
+        assert data.ndim == 3
+        assert data.shape[1] == 1
+
+        # Set dummy-file Waterfall object properties.
+        self.filename = None
+        self.ext = self.filename
+        self.file_shape = self.filename
+        self.file_size_bytes = 0
+
+        # The Waterfall "container":
+        class Container():
+            n_beams_in_file = 1
+            n_pols_in_file = 1
+            _d_type = np.float32
+            t_begin = 0
+            freq_axis = 2
+            time_axis = 0
+            beam_axis = 1
+        self.container = Container()
+        self.container.n_channels_in_file  = header_dict["nchans"]
+        self.container._n_bytes = int(header_dict["nbits"] / 8)  # number of bytes per digit.
+        if header_dict['foff'] < 0:
+            self.container.f_end  = header_dict['fch1']
+            self.container.f_begin  = self.container.f_end + self.container.n_channels_in_file * header_dict['foff']
+        else:
+            self.container.f_begin  = header_dict['fch1']
+            self.container.f_end  = self.container.f_begin + self.container.n_channels_in_file * header_dict['foff']
+        self.container.f_start = self.container.f_begin
+        self.container.f_stop = self.container.f_end
+        self.container.t_end = data.shape[0]
+
+        # Set Waterfall object properties.
+        self.header = header_dict
+        self.file_header = header_dict
+        self.n_ints_in_file = data.shape[0]
+        self.selection_shape = data.shape
+        self.n_channels_in_file = header_dict["nchans"]
+        self.freq_axis = 2
+        self.time_axis = 0
+        self.beam_axis = 1
+        self.stokes_axis = 4
+        self.logger = logger
+
+        # Attach data matrix.
+        self.data = data
+
+        # Attach plotting methods.
+        self.plot_spectrum         = six.create_bound_method(plot_spectrum, self)
+        self.plot_waterfall        = six.create_bound_method(plot_waterfall, self)
+        self.plot_kurtosis         = six.create_bound_method(plot_kurtosis, self)
+        self.plot_time_series      = six.create_bound_method(plot_time_series, self)
+        self.plot_all              = six.create_bound_method(plot_all, self)
+        self.plot_spectrum_min_max = six.create_bound_method(plot_spectrum_min_max, self)
+
+
     def __init__(self, filename=None, f_start=None, f_stop=None, t_start=None, t_stop=None,
                  load_data=True, max_load=None, header_dict=None, data_array=None):
         """ Class for loading and plotting blimpy data.
@@ -86,7 +150,8 @@ def __init__(self, filename=None, f_start=None, f_stop=None, t_start=None, t_sto
         """
 
         if (header_dict is not None) or (data_array is not None):
-            raise ValueError("Neither header_dict nor data_array is currently supported.")
+            self._init_alternate(header_dict, data_array, filename=filename)
+            return
 
         if filename is None:
             raise ValueError("Currently, a value for filename must be supplied.")
@@ -192,10 +257,10 @@ def info(self):
         print("%16s : %32s" % ("File shape", self.file_shape))
         print("--- Selection Info ---")
         print("%16s : %32s" % ("Data selection shape", self.selection_shape))
-        if self.header['foff'] < 0:
+        if self.header['foff'] < 0: # descending frequency values
             minfreq = self.container.f_start - self.header['foff']
             maxfreq = self.container.f_stop
-        else:
+        else: # ascending frequency values
             minfreq = self.container.f_start
             maxfreq = self.container.f_stop - self.header['foff']
         print("%16s : %32s" % ("Minimum freq (MHz)", minfreq))
@@ -336,11 +401,11 @@ def blank_dc(self, n_coarse_chan):
 
         if n_coarse_chan < 1:
             logger.warning('Coarse channel number < 1, unable to blank DC bin.')
-            return None
+            return
 
         if not n_coarse_chan % int(n_coarse_chan) == 0:
             logger.warning('Selection does not contain an integer number of coarse channels, unable to blank DC bin.')
-            return None
+            return
 
         n_coarse_chan = int(n_coarse_chan)
 

setup.py

@@ -3,7 +3,7 @@
 """
 from setuptools import setup, find_packages
 
-__version__ = '2.1.0'
+__version__ = '2.1.1'
 
 with open("README.md", "r") as fh:
     long_description = fh.read()

tests/test_waterfall.py

@@ -147,15 +147,3 @@ def test_bug_no_filename():
     with pytest.raises(ValueError):
         bl.Waterfall()
 
-def test_bug_header_dict():
-    print("\n===== test_bug_header")
-    header_dict = { "banana": "is a fruit" }
-    with pytest.raises(ValueError):
-        bl.Waterfall(voyager_h5, header_dict=header_dict)
-
-def test_bug_data_array():
-    print("\n===== test_bug_data_array")
-    data_array = np.arange(1, 11)
-    with pytest.raises(ValueError):
-        bl.Waterfall(voyager_h5, data_array=data_array)
-

tests/test_waterfall2.py

@@ -0,0 +1,48 @@
+import numpy as np
+from astropy import units as u
+from astropy.coordinates import Angle
+import blimpy as bl
+from tests.data import voyager_h5
+
+def test_waterfall_stream_1():
+
+    print("\n===== test_waterfall_stream_1")
+
+    source_name = "Not_Voyager_1"
+    src_raj = Angle("17:10:03.984 hours")
+    src_dej = Angle("12:10:58.8 degrees")
+    tstart = 57650.78209490741
+    tsamp = 18.253611008
+    f_start = 8418.457032646984
+    f_stop = 8421.386717353016
+    n_fine_chans = 20
+    n_tints = 8
+
+    foff = (f_stop - f_start) / float(n_fine_chans)
+
+    header = {"az_start": 0.0, "data_type": 1,
+                   "fch1": f_start, "foff": foff,
+                   "ibeam": 1, "machine_id": 42, "nbeams": 1, "nbits": 32,
+                   "nchans": n_fine_chans, "nifs": 1, "rawdatafile": "nil",
+                   "source_name": source_name, "src_raj": src_raj, "src_dej": src_dej,
+                   "telescope_id": 42,
+                   "tstart": tstart, "tsamp": tsamp, "zs_tart": 0.0}
+
+    data_matrix = np.zeros((n_tints, 1, n_fine_chans), dtype=np.float32)
+
+    wf = bl.Waterfall(header_dict=header, data_array=data_matrix)
+    print("\nwf:", wf)
+    wf.info()
+
+
+def test_waterfall_stream_2():
+
+    print("\n===== test_waterfall_stream_2")
+    wf_voya1 = bl.Waterfall(voyager_h5)
+    wf_voya2 = bl.Waterfall(header_dict=wf_voya1.header, data_array=wf_voya1.data)
+    wf_voya2.info()
+
+
+if __name__ == "__main__":
+    test_waterfall_stream_1()
+    test_waterfall_stream_2()