Add AIRS support for SNO extraction

intercal/airs.py

+
+import numpy as np
+import pyhdf.HDF
+import pyhdf.SD
+import pyhdf.VS
+
+class AirsGranule(object):
+
+    num_fors_per_scan = 90
+    num_fovs_per_for = 1
+
+    has_imaginary_radiance = False
+
+    num_files = 1
+
+    def __init__(self, filename):
+        self.sd = pyhdf.SD.SD(filename)
+        self.wavenumber = self.read_wavenumber(filename)
+
+    def read_wavenumber(self, filename):
+        num_channels = 2378
+        nested_list = pyhdf.HDF.HDF(filename).vstart().attach('nominal_freq').read(num_channels)
+        return np.array(nested_list).flatten()
+
+    @property
+    def num_scans(self):
+        return self.sd.datasets()['radiances'][1][0]
+
+    def read_latitude(self, latitude):
+        latitude[:,:,0] = self.sd.select('Latitude')[:]
+
+    def read_longitude(self, longitude):
+        longitude[:,:,0] = self.sd.select('Longitude')[:]
+
+    def read_radiance(self, radiance, imaginary):
+        if imaginary:
+            raise ValueError('no imaginary radiances for AIRS')
+        radiance[:,:,0,:] = self.sd.select('radiances')[:]
+

intercal/main.py

@@ -6,6 +6,7 @@ import os
 import h5py
 import numpy as np
 
+from .airs import AirsGranule
 from .cris import CrisGranule
 from .iasi import IasiGranule
 from .super_granule import SuperGranule
@@ -14,13 +15,14 @@ from .util import gcdist
 def _parse_args():
 
     parser = argparse.ArgumentParser()
-    parser.add_argument('metop_time', type=parse_datetime)
-    parser.add_argument('npp_time', type=parse_datetime)
+    parser.add_argument('platform_1')
+    parser.add_argument('time_1', type=parse_datetime)
+    parser.add_argument('platform_2')
+    parser.add_argument('time_2', type=parse_datetime)
     parser.add_argument('latitude', type=float)
     parser.add_argument('longitude', type=float)
     parser.add_argument('max_distance', type=float)
-    parser.add_argument('iasi_platform', choices=['metop-a', 'metop-b'])
-    parser.add_argument('sensor', choices=['cris', 'iasi'])
+    parser.add_argument('sensor', choices=['airs', 'cris', 'iasi'])
     parser.add_argument('files', nargs='+', metavar='file')
     return parser.parse_args()
 
@@ -30,7 +32,7 @@ def parse_datetime(s):
 
 def _create_granule(sensor, files):
 
-    granule_cls = {'cris': CrisGranule, 'iasi': IasiGranule}[sensor]
+    granule_cls = {'airs': AirsGranule, 'cris': CrisGranule, 'iasi': IasiGranule}[sensor]
     return SuperGranule(granule_cls, files)
 
 def _filter_by_proximity(granule, lat, lon, max_distance):
@@ -86,9 +88,15 @@ def unix_time(t):
 
 def output_file_name(args):
 
-    earlier_time = min(args.metop_time, args.npp_time)
-    return 'sno_{}_npp_{}_{}.h5'.format(args.iasi_platform.lower(), args.sensor.lower(),
-                                        earlier_time.strftime('%Y-%m-%dT%H-%M'))
+    earlier_time = min(args.time_1, args.time_2)
+    return 'sno_{}_{}_{}_{}.h5'.format(platform_tag(args.platform_1).lower(),
+                                       platform_tag(args.platform_2).lower(),
+                                       args.sensor.lower(),
+                                       earlier_time.strftime('%Y-%m-%dT%H-%M'))
+
+def platform_tag(platform):
+    tags = {'AQUA': 'Aqua', 'METOP-A': 'Metop-A', 'METOP-B': 'Metop-B', 'SUOMI NPP': 'NPP'}
+    return tags[platform]
 
 def main():
 
@@ -103,9 +111,10 @@ def main():
             _process_spectra(
                 granule, granule.imaginary_radiance, scan_idx, for_idx, fov_idx,
                 output_file, 'Imaginary')
-        output_file.create_dataset('Metop-{}_Time'.format(args.iasi_platform[-1].upper()),
-                                   data=unix_time(args.metop_time))
-        output_file.create_dataset('NPP_Time', data=unix_time(args.npp_time))
+        output_file.create_dataset('{}_Time'.format(platform_tag(args.platform_1)),
+                                   data=unix_time(args.time_1))
+        output_file.create_dataset('{}_Time'.format(platform_tag(args.platform_2)),
+                                   data=unix_time(args.time_2))
         output_file.create_dataset('SNO_Latitude', data=args.latitude)
         output_file.create_dataset('SNO_Longitude', data=args.longitude)
         output_file.create_dataset('Input_Files', data=[os.path.basename(f) for f in args.files])