fixed h5 retriever

Author: MarconiS

neonwranglerpy/lib/clip_plot.py

@@ -10,7 +10,7 @@ def clip_plot(plt, list_data, bff=12, savepath=""):
     # plt['easting'] = plt['easting'].astype(int)
     # plt['northing'] = plt['northing'].astype(int)
     # tile = plt["plt_e"].values.astype(str) + "_" + plt["plt_n"].values.astype(str)
-    tiles = str(plt["plt_e"]) + "_" + str(plt["plt_n"])
+    tiles = str(plt.plt_e[0]) + "_" + str(plt.plt_n[0])
     tiles = [f for f in list_data if tiles in f]
     missed_plots = []
 

neonwranglerpy/lib/crop_plot_data.py

@@ -19,7 +19,7 @@ def crop_data_to_plot(plt,
                       dpID='DP3.30006.001',
                       dataset_path="",
                       target_year=2018,
-                      bff=520,
+                      bff=20,
                       tasks=1,
                       parallelized=False,
                       savepath=""):

neonwranglerpy/lib/extract_hsi_to_tif.py

@@ -48,21 +48,25 @@ def h5refl2array(refl_filename, remove_water_bands=True):
     sns_zn = hdf5_file[sitename]['Reflectance/Metadata/to-sensor_zenith_angle'][()]
     # get solar angles as array to leverage flightpaths mosaic
     flightpaths = [
-        hdf5_file[sitename]['Reflectance/Metadata/Ancillary_Imagery/Data_Selection_Index']
-        [()]
+        hdf5_file[sitename][
+            'Reflectance/Metadata/Ancillary_Imagery/Data_Selection_Index'][()]
     ]
     sol_zn = [
-        hdf5_file[sitename]['Reflectance/Metadata/Ancillary_Imagery/Data_Selection_Index']
-        [()]
+        hdf5_file[sitename][
+            'Reflectance/Metadata/Ancillary_Imagery/Data_Selection_Index'][()]
     ]
     sol_az = [
-        hdf5_file[sitename]['Reflectance/Metadata/Ancillary_Imagery/Data_Selection_Index']
-        [()]
+        hdf5_file[sitename][
+            'Reflectance/Metadata/Ancillary_Imagery/Data_Selection_Index'][()]
     ]
-    for pt in range(len(solar_angles)):
-        sol_az[flightpaths == solar_angles[pt][0]] = solar_angles[pt][1]
-        sol_zn[flightpaths == solar_angles[pt][0]] = solar_angles[pt][2]
+    # turn sol_az and sol_zn into arrays
+    sol_zn = np.array(sol_zn)
+    sol_az = np.array(sol_az)
 
+    for pt in range(len(solar_angles)):
+        good_pixels = flightpaths == solar_angles[pt][0]
+        sol_az[good_pixels] = solar_angles[pt][1]
+        sol_zn[good_pixels] = solar_angles[pt][2]
 
 #
     mapInfo_string = str(metadata['mapInfo'])
@@ -101,8 +105,9 @@ def tile_solar_angle(full_path):
     file_attrs_string = str(list(hdf5_file.items()))
     file_attrs_string_split = file_attrs_string.split("'")
     sitename = file_attrs_string_split[1]
-    flight_paths = hdf5_file[sitename]
-    ["Reflectance/Metadata/Ancillary_Imagery/Data_Selection_Index"].attrs["Data_Files"]
+    flight_paths = hdf5_file[
+        sitename]["Reflectance/Metadata/Ancillary_Imagery/Data_Selection_Index"
+                  ].attrs["Data_Files"]
     flight_paths = str(flight_paths).split(",")
     which_paths = np.unique(
         hdf5_file[sitename]["Reflectance/Metadata/Ancillary_Imagery/Data_Selection_Index"]
@@ -291,7 +296,12 @@ def generate_raster(h5_path,
             os.path.basename(rgb_filename))[0] + "_hyperspectral{}.tif".format(suffix)
 
     # stach solar and sensor data to be used for corrections
-    sol_sens_angle = np.array([sol_az, sol_zn, sns_az, sns_zn])
+    sol_az_reshaped = sol_az.squeeze()  # Remove the extra dimension
+    sol_zn_reshaped = sol_zn.squeeze()  # Remove the extra dimension
+    sns_az_reshaped = sns_az  # No need to reshape sns_az
+    sns_zn_reshaped = sns_zn
+
+    sol_sens_angle = np.array([sol_az_reshaped, sol_zn_reshaped, sns_az_reshaped, sns_zn_reshaped])
     solar_tilename = os.path.splitext(
         os.path.basename(rgb_filename))[0] + "_solar_sensor_angle{}.tif".format(suffix)
     # Save georeference crop to file

tests/test_h5refl2array.py

@@ -0,0 +1,35 @@
+import unittest
+import numpy as np
+import h5py
+import os
+
+class TestFunc(unittest.TestCase):
+
+    def setUp(self):
+        # Prepare a dummy hdf5 file for testing
+        self.filename = "testfile.h5"
+        with h5py.File(self.filename, 'w') as f:
+            # create datasets in the hdf5 file similar to the actual data the function expects
+            ## Omitted here for brevity
+
+    def test_reflection2array(self):
+        reflArray, metadata, sol_az, sol_zn, sns_az, sns_zn = h5refl2array(self.filename)
+
+        # Test the type of the returned objects
+        self.assertTrue(isinstance(reflArray, np.ndarray))
+        self.assertTrue(isinstance(metadata, dict))
+        self.assertTrue(isinstance(sol_az, list))
+        self.assertTrue(isinstance(sol_zn, list))
+        self.assertTrue(isinstance(sns_az, np.ndarray))
+        self.assertTrue(isinstance(sns_zn, np.ndarray))
+
+        # Test the shape or any other property of the returned objects
+        # This will really depend on what you're expecting
+        ## Omitted here for brevity
+
+    def tearDown(self):
+        # Removes the test file
+        os.remove(self.filename)
+
+if __name__ == '__main__':
+    unittest.main()