Merge branch 'master' into enhancement/add_license_texts

Conflicts:
	gms_preprocessing/algorithms/classification.py
	gms_preprocessing/processing/multiproc.py
	tests/test_image_classifier.py

.gitlab-ci.yml

@@ -34,6 +34,8 @@ test_gms_preprocessing:
     # - cd ../../
     # make tests
 
+    - pip install git+https://gitext.gfz-potsdam.de/geomultisens/spechomo.git  # TODO remove as soon as this is included in the CI container
+
     # run tests
     - make nosetests
     - make docs

README.rst

@@ -27,7 +27,7 @@ Status
      :target: https://pyup.io/repos/github/geomultisens/gms_preprocessing/
      :alt: Updates
 
-.. image:: https://gitext.gfz-potsdam.de/geomultisens/gms_preprocessing/badges/master/build.svg
+.. image:: https://gitext.gfz-potsdam.de/geomultisens/gms_preprocessing/badges/master/pipeline.svg
         :target: https://gitext.gfz-potsdam.de/geomultisens/gms_preprocessing/commits/master
 .. image:: https://gitext.gfz-potsdam.de/geomultisens/gms_preprocessing/badges/master/coverage.svg
         :target: http://geomultisens.gitext.gfz-potsdam.de/gms_preprocessing/coverage/
@@ -55,7 +55,7 @@ Level-2 processing:
 ^^^^^^^^^^^^^^^^^^^
 
 * spatial homogenization
-* spectral homogenization
+* spectral homogenization (using `SpecHomo <https://gitext.gfz-potsdam.de/geomultisens/spechomo>`_
 * estimation of accuracy layers
 
 => application oriented analysis dataset

gms_preprocessing/algorithms/L1A_P.py

@@ -97,13 +97,13 @@ class L1A_object(GMS_object):
         self.proc_status = proc_status or 'initialized'  # if proc_status = 'running' is given by L1A_map
 
     def import_rasterdata(self):
-        if re.search("ALOS", self.satellite, re.I):
+        if re.search(r"ALOS", self.satellite, re.I):
             '''First 22 lines are nodata: = maybe due to an issue of the GDAL CEOS driver.
             But: UL of metadata refers to [row =0, col=21]! So the imported GeoTransform is correct when
             the first 21 columns are deleted.'''
             self.archive_to_rasObj(self.path_archive, self.path_InFilePreprocessor,
                                    subset=['block', [[None, None], [21, None]]])
-        elif re.search("Terra", self.satellite, re.I):
+        elif re.search(r"Terra", self.satellite, re.I):
             self.ASTER_HDF_to_rasObj(self.path_archive, path_output=self.path_InFilePreprocessor)
         else:
             self.archive_to_rasObj(self.path_archive, path_output=self.path_InFilePreprocessor)
@@ -135,23 +135,23 @@ class L1A_object(GMS_object):
 
         image_files = []
         is_ALOS_Landsat_S2 = \
-            re.search('ALOS', self.satellite) or re.search('Landsat', self.satellite) or \
-            re.search('Sentinel-2', self.satellite)
+            re.search(r'ALOS', self.satellite) or re.search(r'Landsat', self.satellite) or \
+            re.search(r'Sentinel-2', self.satellite)
         n_files2search = len(full_LayerBandsAssignment) if is_ALOS_Landsat_S2 else 1
 
         for File in HLP_F.sorted_nicely(files_in_archive):
             search_res = \
-                re.search("IMG-0[0-9]-[\s\S]*", File) if re.search('ALOS', self.satellite) else \
-                re.search("[\S]*_B[1-9][0-9]?[\S]*.TIF", File) if re.search('Landsat', self.satellite) else \
-                re.search("[0-9]*.tif", File) if re.search('RapidEye', self.satellite) else \
-                re.search("imagery.tif", File) if re.search('SPOT', self.satellite) else \
-                re.search("[\S]*.SAFE/GRANULE/%s/IMG_DATA/[\S]*_B[0-9][\S]*.jp2"
-                          % self.entity_ID, File) if re.search('Sentinel-2', self.satellite) else None
+                re.search(r"IMG-0[0-9]-[\s\S]*", File) if re.search(r'ALOS', self.satellite) else \
+                re.search(r"[\S]*_B[1-9][0-9]?[\S]*.TIF", File) if re.search(r'Landsat', self.satellite) else \
+                re.search(r"[0-9]*.tif", File) if re.search(r'RapidEye', self.satellite) else \
+                re.search(r"imagery.tif", File) if re.search(r'SPOT', self.satellite) else \
+                re.search(r"[\S]*.SAFE/GRANULE/%s/IMG_DATA/[\S]*_B[0-9][\S]*.jp2"
+                          % self.entity_ID, File) if re.search(r'Sentinel-2', self.satellite) else None
 
             if search_res:
-                if re.search('Sentinel-2', self.satellite):
+                if re.search(r'Sentinel-2', self.satellite):
                     # add only those files that are corresponding to subsystem (e.g. S2A10: fullLBA = ['2','3','4','8'])
-                    if 1 in [1 if re.search("[\S]*_B[0]?%s.jp2" % LBAn, os.path.basename(File)) else 0
+                    if 1 in [1 if re.search(r"[\S]*_B[0]?%s.jp2" % LBAn, os.path.basename(File)) else 0
                              for LBAn in full_LayerBandsAssignment]:
                         image_files.append(File)
                 else:
@@ -163,7 +163,7 @@ class L1A_object(GMS_object):
             # validate number of expected files #
             #####################################
 
-            if re.search('ETM+', self.sensor) and self.acq_datetime > datetime.datetime(year=2003, month=5, day=31):
+            if re.search(r'ETM+', self.sensor) and self.acq_datetime > datetime.datetime(year=2003, month=5, day=31):
                 expected_files_count = 2 * len(full_LayerBandsAssignment)
             else:
                 expected_files_count = len(full_LayerBandsAssignment)
@@ -321,9 +321,9 @@ class L1A_object(GMS_object):
         self.arr_desc = \
             'DN' if self.MetaObj.PhysUnit == 'DN' else \
             'Rad' if self.MetaObj.PhysUnit == "W * m-2 * sr-1 * micrometer-1" else \
-            'TOA_Ref' if re.search('TOA_Reflectance', self.MetaObj.PhysUnit, re.I) else \
-            'BOA_Ref' if re.search('BOA_Reflectance', self.MetaObj.PhysUnit, re.I) else \
-            'Temp' if re.search('Degrees Celsius', self.MetaObj.PhysUnit, re.I) else None
+            'TOA_Ref' if re.search(r'TOA_Reflectance', self.MetaObj.PhysUnit, re.I) else \
+            'BOA_Ref' if re.search(r'BOA_Reflectance', self.MetaObj.PhysUnit, re.I) else \
+            'Temp' if re.search(r'Degrees Celsius', self.MetaObj.PhysUnit, re.I) else None
 
         assert self.arr_desc, 'GMS_obj contains an unexpected physical unit: %s' % self.MetaObj.PhysUnit
 
@@ -413,7 +413,7 @@ class L1A_object(GMS_object):
                         (PI * U__earth_sun_distance_correction_factor);
                     L = (U__earth_sun_distance_correction_factor * rToa * e0__SOLAR_IRRADIANCE_For_band * cos(
                         Z__Sun_Angles_Grid_Zenith_Values)) / PI;"""
-                    if re.search('Sentinel-2', self.satellite, re.I):
+                    if re.search(r'Sentinel-2', self.satellite, re.I):
                         warnings.warn('Physical gain values unclear for Sentinel-2! This may cause errors when '
                                       'calculating radiance from TOA Reflectance. ESA provides only 12 gain values for '
                                       '13 bands and it not clear for which bands the gains are provided.')
@@ -478,7 +478,7 @@ class L1A_object(GMS_object):
             os.chdir(os.path.dirname(self.path_archive))
         rasObj = GEOP.GEOPROCESSING(self.MetaObj.Dataname, self.logger)
         if rasObj.geotransform == (0.0, 1.0, 0.0, 0.0, 0.0, 1.0) and rasObj.projection == '':
-            if re.search('ALOS', self.satellite) and self.MetaObj.ProcLCode == '1B2':
+            if re.search(r'ALOS', self.satellite) and self.MetaObj.ProcLCode == '1B2':
                 self.GeoTransProj_ok, self.GeoAlign_ok = False, True
             else:
                 self.GeoTransProj_ok, self.GeoAlign_ok = False, False
@@ -569,7 +569,7 @@ class L1A_object(GMS_object):
                        'mask_nodata') and self.mask_nodata is not None, "The L1A object needs to have a nodata mask."
         self.logger.info('Calculating true data corner positions (image and world coordinates)...')
 
-        # if re.search('ETM+', self.sensor) and self.acq_datetime > datetime.datetime(year=2003, month=5, day=31,
+        # if re.search(r'ETM+', self.sensor) and self.acq_datetime > datetime.datetime(year=2003, month=5, day=31,
         #                                                                             tzinfo=datetime.timezone.utc):
         if is_dataset_provided_as_fullScene(self.GMS_identifier):
             self.trueDataCornerPos = calc_FullDataset_corner_positions(self.mask_nodata, algorithm='numpy',
@@ -599,7 +599,7 @@ class L1A_object(GMS_object):
 
         else:
 
-            if re.search('AVNIR', self.sensor):
+            if re.search(r'AVNIR', self.sensor):
                 self.fullSceneCornerPos = calc_FullDataset_corner_positions(self.mask_nodata, algorithm='numpy',
                                                                             assert_four_corners=False)
                 # set true data corner positions (lon/lat coordinates)
@@ -610,7 +610,7 @@ class L1A_object(GMS_object):
             else:
                 # RapidEye or Sentinel-2 data
 
-                if re.search('Sentinel-2', self.satellite):
+                if re.search(r'Sentinel-2', self.satellite):
                     # get fullScene corner coordinates by database query
                     # -> calculate footprints for all granules of the same S2 datatake
                     # -> merge them and calculate overall corner positions

gms_preprocessing/algorithms/L1C_P.py

@@ -291,7 +291,7 @@ class AtmCorr(object):
         # append AtmCorr object to input L1C objects
         # [setattr(L1C_obj, 'AtmCorr', self) for L1C_obj in self.inObjs] # too big for serialization
 
-        if not re.search('Sentinel-2', self.inObjs[0].satellite, re.I):
+        if not re.search(r'Sentinel-2', self.inObjs[0].satellite, re.I):
             self.logger.debug('Calculation of acquisition geometry arrays is currently only validated for Sentinel-2!')
             # validation possible by comparing S2 angles provided by ESA with own angles  # TODO
 
@@ -671,7 +671,7 @@ class AtmCorr(object):
         :return: <np.ndarray> 2D array (with 20m resolution in case of Sentinel-2)
         """
         # determine which input GMS object is used to generate DEM
-        if re.search('Sentinel-2', self.inObjs[0].satellite):
+        if re.search(r'Sentinel-2', self.inObjs[0].satellite):
             # in case of Sentinel-2 the 20m DEM must be passed
             inObj4dem = [obj for obj in self.inObjs if obj.arr.xgsd == 20]
             if not inObj4dem:

gms_preprocessing/algorithms/L2B_P.py

@@ -99,7 +99,10 @@ class L2B_object(L2A_object):
         # perform spectral homogenization of image data #
         #################################################
 
-        SpH = SpectralHomogenizer(classifier_rootDir=CFG.path_spechomo_classif, logger=self.logger, CPUs=CFG.CPUs)
+        from ..processing.multiproc import is_mainprocess
+        SpH = SpectralHomogenizer(classifier_rootDir=CFG.path_spechomo_classif,
+                                  logger=self.logger,
+                                  CPUs=CFG.CPUs if is_mainprocess() else 1)
 
         if method == 'LI' or CFG.datasetid_spectral_ref is None:
             # linear interpolation (if intended by user or in case of custom spectral characteristics of target sensor)

gms_preprocessing/algorithms/cloud_masking.py

@@ -502,7 +502,7 @@ class Cloud_Mask_Creator(object):
         self.GMS_obj.logger.info("Calculating cloud mask based on '%s' algorithm..." % self.algorithm)
 
         if self.algorithm == 'FMASK':
-            if re.search('Landsat', self.GMS_obj.satellite, re.I):
+            if re.search(r'Landsat', self.GMS_obj.satellite, re.I):
                 FMR = FMASK_Runner_Landsat(self.GMS_obj.path_archive, self.GMS_obj.satellite)
 
             else:

gms_preprocessing/algorithms/geoprocessing.py

@@ -112,7 +112,7 @@ class GEOPROCESSING(object):
                 #                     '/vsitar' '.gz': '/vsigzip'}
                 p1 = [geodata.split(i)[0] + i for i in ['.zip', '.tar', '.tar.gz', '.gz', '.tgz']
                       if len(geodata.split(i)) > 1 and geodata.split(i)[1].startswith('/')][0]
-                path2check = os.path.abspath('.' + re.search('/vsi[\s\S]*(/[\s\S,.]*)', p1, re.I).group(1))
+                path2check = os.path.abspath('.' + re.search(r'/vsi[\s\S]*(/[\s\S,.]*)', p1, re.I).group(1))
             assert os.path.exists(path2check), "ERROR: data %s does not exist!" % path2check
             assert self.inDs is not None, "ERROR: Could not open %s!" % self.filename
         elif isinstance(geodata, gdal.Dataset):
@@ -704,7 +704,7 @@ class GEOPROCESSING(object):
                     with open(os.path.splitext(path_output)[0] + '.hdr', 'r') as inF:
                         lines = inF.readlines()
 
-                    outContent = ''.join([i for i in lines if not re.search('map info', i, re.I)])
+                    outContent = ''.join([i for i in lines if not re.search(r'map info', i, re.I)])
                     with open(os.path.splitext(path_output)[0] + '.hdr', 'w') as outF:
                         outF.write(outContent)
 
@@ -718,7 +718,7 @@ class GEOPROCESSING(object):
             #
             #     with open(os.path.splitext(path_output)[0] + '.hdr', 'r') as inF:
             #         lines      = inF.readlines()
-            #         outContent = ''.join([line if not re.search('coordinate system string', line, re.I) else
+            #         outContent = ''.join([line if not re.search(r'coordinate system string', line, re.I) else
             #                               'coordinate system string = %s' % self.projection for line in lines])
             #
             #     with open(os.path.splitext(path_output)[0] + '.hdr', 'w') as outF:

gms_preprocessing/misc/database_tools.py

@@ -604,9 +604,9 @@ def get_filename_by_entityID(conn_DB, entityid, satellite):
     :param satellite:   <str> satellite name to which the entity ID is belonging
     """
 
-    if re.search('Landsat', satellite, re.I):
+    if re.search(r'Landsat', satellite, re.I):
         filename = '%s.tar.gz' % entityid
-    elif re.search('Sentinel-2', satellite, re.I):
+    elif re.search(r'Sentinel-2', satellite, re.I):
         filename = get_info_from_postgreSQLdb(conn_DB, 'scenes', ['filename'],
                                               {'entityid': entityid}, records2fetch=1)[0][0]
     else:
@@ -794,12 +794,18 @@ class GMS_JOB(object):
             if isinstance(datadict['filenames'], str) and datadict['filenames'].endswith('.csv'):
                 datadict['filenames'] = None  # TODO implement csv reader here
                 raise NotImplementedError
+
             else:
                 temp_gdf = GeoDataFrame(datadict, columns=['satellite', 'sensor', 'filenames'])
-                if re.search('Landsat-7', datadict['satellite'], re.I) and re.search('ETM+', datadict['sensor'], re.I):
+
+                if re.search(r'Landsat-7', datadict['satellite'], re.I) and \
+                   re.search(r'ETM+', datadict['sensor'], re.I):
+
                     from .helper_functions import Landsat_entityID_decrypter as LED
 
-                    def get_L7_sensor(fN): return LED(fN.split('.tar.gz')[0]).sensorIncSLC
+                    def get_L7_sensor(fN):
+                        return LED(fN.split('.tar.gz')[0]).sensorIncSLC
+
                     temp_gdf['sensor'] = list(temp_gdf['filenames'].map(get_L7_sensor))
 
                 all_gdfs.append(temp_gdf)
@@ -1428,7 +1434,7 @@ def archive_exists_on_fileserver(conn_DB, entityID):
         archive_fold = os.path.join(CFG.path_archive, satellite, sensor)
         assert os.path.exists(archive_fold), 'Archive folder not found: %s.' % archive_fold
 
-        if re.search('Landsat', satellite, re.I):
+        if re.search(r'Landsat', satellite, re.I):
             exists = os.path.exists(os.path.join(archive_fold, entityID + '.tar.gz'))
         else:
             raise NotImplementedError

gms_preprocessing/misc/definition_dicts.py

@@ -52,7 +52,7 @@ def get_GMS_sensorcode(GMS_id):
     # type: (GMS_identifier) -> str
 
     Satellite, Sensor, Subsystem = (GMS_id.satellite, GMS_id.sensor, GMS_id.subsystem)
-    Sensor = Sensor[:-1] if re.match('SPOT', Satellite, re.I) and Sensor[-1] not in ['1', '2'] else Sensor
+    Sensor = Sensor[:-1] if re.match(r'SPOT', Satellite, re.I) and Sensor[-1] not in ['1', '2'] else Sensor
     meta_sensorcode = Satellite + '_' + Sensor + ('_' + Subsystem if Subsystem not in ["", None] else "")
     sensorcode_dic = {
         'ALOS_AVNIR-2': 'AVNIR-2',

gms_preprocessing/misc/path_generator.py

@@ -311,8 +311,8 @@ def get_path_srf_file(GMS_id, bandname=''):
     """
 
     satellite, sensor = GMS_id.satellite, GMS_id.sensor
-    satellite = 'RapidEye' if re.match('RapidEye', satellite, re.I) else satellite
-    sensor = sensor[:-1] if re.match('SPOT', satellite, re.I) and sensor[-1] not in ['1', '2'] else sensor
+    satellite = 'RapidEye' if re.match(r'RapidEye', satellite, re.I) else satellite
+    sensor = sensor[:-1] if re.match(r'SPOT', satellite, re.I) and sensor[-1] not in ['1', '2'] else sensor
     filename = 'band_%s' % bandname if bandname else ''
     return os.path.join(CFG.path_SRFs, satellite, sensor, filename)
 
@@ -325,8 +325,8 @@ def get_path_snr_model(GMS_id):
     """
 
     satellite, sensor = (GMS_id.satellite, GMS_id.sensor)
-    satellite = 'RapidEye' if re.match('RapidEye', satellite, re.I) else satellite
-    sensor = sensor[:-1] if re.match('SPOT', satellite, re.I) and sensor[-1] not in ['1', '2'] else sensor
+    satellite = 'RapidEye' if re.match(r'RapidEye', satellite, re.I) else satellite
+    sensor = sensor[:-1] if re.match(r'SPOT', satellite, re.I) and sensor[-1] not in ['1', '2'] else sensor
     return os.path.join(CFG.path_SNR_models, satellite, sensor, 'SNR_model.csv')
 
 

gms_preprocessing/misc/spatial_index_mediator.py

@@ -83,7 +83,7 @@ class SpatialIndexMediatorServer:
         running = 'is running' in outputStr
 
         # get PID
-        _process_id = re.search('with pid ([\d]*)', outputStr)
+        _process_id = re.search(r'with pid ([\d]*)', outputStr)
         if _process_id and _process_id.group(1):
             process_id = int(_process_id.group(1))
         else:
@@ -108,7 +108,7 @@ class SpatialIndexMediatorServer:
     def stop(self):
         outputStr = self._communicate('stop')
 
-        if outputStr == 'success' or re.search('index-mediator-server stopped', outputStr, re.I):
+        if outputStr == 'success' or re.search(r'index-mediator-server stopped', outputStr, re.I):
             return 'stopped'
         else:
             warnings.warn("\nStopping Spatial Index Mediator Server failed with message '%s'!"

gms_preprocessing/model/gms_object.py

@@ -375,7 +375,7 @@ class GMS_object(object):
     def georef(self):
         """Returns True if the current dataset can serve as spatial reference."""
 
-        return True if self.image_type == 'RSD' and re.search('OLI', self.sensor, re.I) else False
+        return True if self.image_type == 'RSD' and re.search(r'OLI', self.sensor, re.I) else False
 
     @property
     def coreg_needed(self):
@@ -1159,7 +1159,7 @@ class GMS_object(object):
         # apply cloud mask to image data and all products derived from image data
         # (only if image data represents BOA-Ref and cloud areas are not to be filled with TOA-Ref)
 
-        if re.search('BOA_Reflectance', GMS_obj_merged.MetaObj.PhysUnit, re.I) and not CFG.ac_fillnonclear_areas:
+        if re.search(r'BOA_Reflectance', GMS_obj_merged.MetaObj.PhysUnit, re.I) and not CFG.ac_fillnonclear_areas:
             # fill non-clear areas with no data values (for all bands)
             for pixVal in nonclear_pixVals:
                 mask_nonclear = GMS_obj_merged.mask_clouds[:] == pixVal
@@ -1210,7 +1210,7 @@ class GMS_object(object):
     @classmethod
     def from_tiles(cls, list_GMS_tiles):
         # type: (list) -> GMS_object
-        """Merge separate GMS objects with different spatial coverage but belonging to the same scene-ID to ONE GMS object.
+        """Merge separate GMS objects with different spatial coverage but belonging to one scene-ID to ONE GMS object.
 
         :param list_GMS_tiles: <list> of GMS objects that have been created by cut_GMS_obj_into_blocks()
         """

gms_preprocessing/options/config.py

@@ -617,7 +617,7 @@ class JobConfig(object):
                     ds["entity_ID"] = row["entityid"]
                     ds["filename"] = row["filename"]
 
-                    ds['sensor'] = 'ETM+' if re.search('ETM+', ds['sensor']) else ds['sensor']
+                    ds['sensor'] = 'ETM+' if re.search(r'ETM+', ds['sensor']) else ds['sensor']
                     if self.skip_thermal and ds['subsystem'] == 'TIR':
                         continue  # removes ASTER TIR in case of skip_thermal
                     ds['subsystem'] = '' if ds['subsystem'] is None else ds['subsystem']
@@ -625,17 +625,17 @@ class JobConfig(object):
                     if self.skip_pan and ds['sensormode'] == 'P':
                         continue  # removes e.g. SPOT PAN in case of skip_pan
 
-                    if re.search("Sentinel-2A", ds['satellite'], re.I):
+                    if re.search(r"Sentinel-2A", ds['satellite'], re.I):
                         for subsystem in ['S2A10', 'S2A20', 'S2A60']:
                             sub_ds = ds.copy()
                             sub_ds['subsystem'] = subsystem
                             data_list.append(sub_ds)
-                    elif re.search("Sentinel-2B", ds['satellite'], re.I):
+                    elif re.search(r"Sentinel-2B", ds['satellite'], re.I):
                         for subsystem in ['S2B10', 'S2B20', 'S2B60']:
                             sub_ds = ds.copy()
                             sub_ds['subsystem'] = subsystem
                             data_list.append(sub_ds)
-                    elif re.search("Terra", ds['satellite'], re.I):
+                    elif re.search(r"Terra", ds['satellite'], re.I):
                         for subsystem in ['VNIR1', 'VNIR2', 'SWIR', 'TIR']:
                             sub_ds = ds.copy()
                             sub_ds['subsystem'] = subsystem

gms_preprocessing/processing/multiproc.py

@@ -21,7 +21,8 @@
 # You should have received a copy of the GNU Lesser General Public License along
 # with this program.  If not, see <http://www.gnu.org/licenses/>.
 
-from multiprocessing import Pool
+
+from multiprocessing import Pool, current_process
 from itertools import chain
 
 from ..options.config import GMS_config as CFG
@@ -93,3 +94,9 @@ def imap_unordered(func, args, CPUs=None, flatten_output=False):
             return list(ch)
     else:
         return list(results)
+
+
+def is_mainprocess():
+    # type: () -> bool
+    """Return True if the current process is the main process and False if it is a multiprocessing child process."""
+    return current_process().name == 'MainProcess'

gms_preprocessing/processing/process_controller.py

@@ -180,7 +180,7 @@ class ProcessController(object):
                 AllWrittenProcL_dueLog = []
             else:
                 logfile = open(path_log, 'r').read()
-                AllWrittenProcL_dueLog = re.findall(":*(\S*\s*) data successfully saved.", logfile, re.I)
+                AllWrittenProcL_dueLog = re.findall(r":*(\S*\s*) data successfully saved.", logfile, re.I)
                 if not AllWrittenProcL_dueLog and path_logfile == path_logfile_merged_ss:  # AllWrittenProcL_dueLog = []
                     self.logger.info('%s: According to logfile no completely processed data exist at any '
                                      'processing level. Dataset has to be reprocessed.' % dataset['entity_ID'])

requirements.txt

@@ -2,6 +2,7 @@ py_tools_ds>=0.12.4
 geoarray>=0.8.0
 arosics>=0.8.5
 git+https://gitext.gfz-potsdam.de/EnMAP/sicor.git
+git+https://gitext.gfz-potsdam.de/geomultisens/spechomo.git
 matplotlib
 numpy
 scikit-learn

setup.py

@@ -41,6 +41,7 @@ requirements = [
     'pandas', 'numba', 'spectral>=0.16', 'geopandas', 'iso8601', 'pyinstrument', 'geoalchemy2', 'sqlalchemy',
     'psycopg2', 'py_tools_ds>=0.12.4', 'geoarray>=0.8.0', 'arosics>=0.8.7', 'six', 'tqdm', 'jsmin', 'cerberus',
     'nested_dict', 'openpyxl', 'timeout_decorator', 'redis', 'retools', 'redis-semaphore', 'psutil',
+    'spechomo @ git+https://gitext.gfz-potsdam.de/geomultisens/spechomo#egg=spechomo'
     # spectral<0.16  has some problems with writing signed integer 8bit data
     # fmask # conda install -c conda-forge python-fmask
     # 'pyhdf', # conda install --yes -c conda-forge pyhdf
@@ -78,6 +79,8 @@ setup(
         'Programming Language :: Python :: 3.4',
         'Programming Language :: Python :: 3.5',
         'Programming Language :: Python :: 3.6',
+        'Programming Language :: Python :: 3.7',
+        'Programming Language :: Python :: 3.8',
     ],
     test_suite='tests',
     tests_require=test_requirements