Add RSR reader for the EPIC instrument onboard DSCOVR

CHANGELOG_RSR_DATA.rst

@@ -2,6 +2,12 @@ Changelog for the Relative Spectral Response data
 =================================================
 
 
+Version <v1.2.3> (Fri Oct 20 01:58:29 2023)
+-------------------------------------------
+
+ * Added RSR file for EPIC on DSCOVR (responses not normalized)
+
+
 Version <v1.2.2> (Tue Nov 15 14:44:03 2022)
 -------------------------------------------
 

pyspectral/bandnames.py

@@ -70,7 +70,6 @@
 # MODIS RSR files were made before 'chX' became standard in pyspectral
 BANDNAMES['modis'] = {str(chan_num): str(chan_num) for chan_num in range(1, 37)}
 
-
 BANDNAMES['seviri'] = {'VIS006': 'VIS0.6',
                        'VIS008': 'VIS0.8',
                        'IR_016': 'NIR1.6',
@@ -177,6 +176,17 @@
                     'IR133': 'ch16'
                     }
 
+BANDNAMES['epic'] = {'B317': 'T(317.5) %',
+                     'B325': 'T(325) %',
+                     'B340': 'T(340) %',
+                     'B388': 'T(388) %',
+                     'B443': 'T(443) %',
+                     'B551': 'T(551) %',
+                     'B680': 'T(680) %',
+                     'B688': 'T(687.75) %',
+                     'B764': 'T(764) %',
+                     'B780': 'T(779.5) %'}
+
 BANDNAMES['fci'] = {'vis_04': 'VIS0.4',
                     'vis_05': 'VIS0.5',
                     'vis_06': 'VIS0.6_HR',

pyspectral/etc/pyspectral.yaml

@@ -50,6 +50,9 @@ download_from_internet: True
 #   path: /home/a000680/data/SpectralResponses/modis/aqua
 #   tb2rad_lut_filename: /path/to/radiance/tb/lut/data/tb2rad_lut_aqua_modis_ir3.7.npz
 
+#dscovr-epic:
+#   path: C:/Users/Simon/Downloads/EPIC_Filters_Original_Data.xlsx
+
 
 # NOAA-20-viirs:
 #   # J1_VIIRS_RSR_M1_Detector_Fused_V2.txt

pyspectral/utils.py

@@ -1,7 +1,7 @@
 #!/usr/bin/env python
 # -*- coding: utf-8 -*-
 #
-# Copyright (c) 2014-2022 Pytroll developers
+# Copyright (c) 2014-2023 Pytroll developers
 #
 #
 # This program is free software: you can redistribute it and/or modify
@@ -91,17 +91,20 @@
                'NOAA-21': 'viirs',
                'Suomi-NPP': 'viirs',
                'FY-3B': 'virr',
-               'FY-3C': 'virr'}
+               'FY-3C': 'virr',
+               'DSCOVR': 'epic'}
 
 
 INSTRUMENT_TRANSLATION_DASH2SLASH = {'avhrr-1': 'avhrr/1',
                                      'avhrr-2': 'avhrr/2',
                                      'avhrr-3': 'avhrr/3'}
 
 HTTP_PYSPECTRAL_RSR = "https://zenodo.org/record/7311143/files/pyspectral_rsr_data.tgz"
+HTTP_PYSPECTRAL_RSR = "https://zenodo.org/records/10026657/files/pyspectral_rsr_data.tgz"
+
 
 RSR_DATA_VERSION_FILENAME = "PYSPECTRAL_RSR_VERSION"
-RSR_DATA_VERSION = "v1.2.2"
+RSR_DATA_VERSION = "v1.2.3"
 
 ATM_CORRECTION_LUT_VERSION = {}
 ATM_CORRECTION_LUT_VERSION['antarctic_aerosol'] = {'version': 'v1.0.1',

rsr_convert_scripts/epic_reader.py

@@ -0,0 +1,120 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+#
+# Copyright (c) 2023 Pytroll developers
+#
+#
+# This program is free software: you can redistribute it and/or modify
+# it under the terms of the GNU General Public License as published by
+# the Free Software Foundation, either version 3 of the License, or
+# (at your option) any later version.
+#
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+# GNU General Public License for more details.
+#
+# You should have received a copy of the GNU General Public License
+# along with this program.  If not, see <http://www.gnu.org/licenses/>.
+
+"""Read the DSCOVR-EPIC spectral response functions.
+
+Data from the NASA Goddard website:
+https://avdc.gsfc.nasa.gov/pub/DSCOVR/EPIC_Filter_Data/
+
+"""
+
+import logging
+import os
+
+import numpy as np
+import pandas as pd
+
+from pyspectral.raw_reader import InstrumentRSR
+from pyspectral.utils import convert2hdf5 as tohdf5
+
+LOG = logging.getLogger(__name__)
+
+
+EPIC_BAND_NAMES = {'B317': 'T(317.5) %',
+                   'B325': 'T(325) %',
+                   'B340': 'T(340) %',
+                   'B388': 'T(388) %',
+                   'B443': 'T(443) %',
+                   'B551': 'T(551) %',
+                   'B680': 'T(680) %',
+                   'B688': 'T(687.75) %',
+                   'B764': 'T(764) %',
+                   'B780': 'T(779.5) %'}
+
+#: Default time format
+_DEFAULT_TIME_FORMAT = '%Y-%m-%d %H:%M:%S'
+
+#: Default log format
+_DEFAULT_LOG_FORMAT = '[%(levelname)s: %(asctime)s : %(name)s] %(message)s'
+
+
+class EpicRSR(InstrumentRSR):
+    """Container for the DSCOVR EPIC relative spectral response data."""
+
+    def __init__(self, bandname, platform_name):
+        """Initialize the EPIC RSR class."""
+        super(EpicRSR, self).__init__(
+            bandname, platform_name, EPIC_BAND_NAMES.keys())
+
+        self.instrument = 'epic'
+        self._get_options_from_config()
+
+        LOG.debug("Filename: %s", str(self.path))
+        if os.path.exists(self.path):
+            self._load()
+
+        else:
+            LOG.warning("Couldn't find an existing file for this band: %s",
+                        str(self.bandname))
+
+        # To be compatible with VIIRS....
+        self.filename = self.requested_band_filename
+
+        self.unit = 'micrometer'
+        self.wavespace = 'wavelength'
+
+    def _load(self, scale=10000.0):
+        """Load the EPIC relative spectral responses."""
+        df1 = pd.read_excel(self.path,
+                            sheet_name='Data',
+                            skiprows=4,
+                            engine='openpyxl')
+        # Remove empty row from the data
+        df1.drop(df1.index[0], inplace=True)
+        # Column names don't match band names - so we use a dict to find correct
+        # columns. We also need to find the column with the wavelength data.
+        # This is the column before the actual RSR data for each band.
+        col_pos = df1.columns.get_loc(EPIC_BAND_NAMES[self.bandname])
+        wvl_data = df1.iloc[:, col_pos - 1]
+        srf_data = df1.iloc[:, col_pos]
+
+        # Not all bands have an identical number of RSR points, so we need to
+        # remove NaNs from the data.
+        wvl_data.dropna(inplace=True)
+        srf_data.dropna(inplace=True)
+
+        # Data is in nanometers, so we need to convert to micrometers.
+        self.rsr = {'wavelength': np.array(wvl_data) / 1000,
+                    'response': np.array(srf_data)}
+
+
+if __name__ == "__main__":
+    import sys
+    LOG = logging.getLogger('epic_rsr')
+    handler = logging.StreamHandler(sys.stderr)
+
+    formatter = logging.Formatter(fmt=_DEFAULT_LOG_FORMAT,
+                                  datefmt=_DEFAULT_TIME_FORMAT)
+    handler.setFormatter(formatter)
+    handler.setLevel(logging.DEBUG)
+    LOG.setLevel(logging.DEBUG)
+    LOG.addHandler(handler)
+
+    for platform_name in ['dscovr', ]:
+        tohdf5(EpicRSR, platform_name, list(EPIC_BAND_NAMES.keys()))