Made airs2modis_pre output filename explicit

airs2modis.py

@@ -8,14 +8,15 @@ from pyhdf.SD import SD, SDC
 from util import HdfWriter
 
 # verify command line inputs
-if len(sys.argv) != 3:
-    print 'usage: python %s <airs_file> <output_file>' % sys.argv[0]
+if len(sys.argv) != 4:
+    print 'usage: python %s <airs_file> <pre_file> <output_file>' % sys.argv[0]
     sys.exit(1)
 airs_filename = sys.argv[1]
-output_filename = sys.argv[2]
+pre_filename = sys.argv[2]
+output_filename = sys.argv[3]
 
 # open our "helper" data file (see airs2modis_pre.py)
-helper_sd = SD('airs2modis.hdf')
+helper_sd = SD(pre_filename)
 
 # read in the mask of good AIRS channels and apply it to the AIRS
 # radiances from our input granule. note that the mask is stored as

airs2modis_pre.py

@@ -68,12 +68,13 @@ def read_airs_chan_data(filename):
     return mask, freqs[mask], nedts[mask]
 
 # verify command line arguments
-if len(sys.argv) != 3:
-    print ('usage: python %s <airs_chan_props_file> <modis_srf_file>' %
-           sys.argv[0])
+if len(sys.argv) != 4:
+    print ('usage: python %s' % sys.argv[0] +
+               ' <airs_chan_props_file> <modis_srf_file> <output_file>')
     sys.exit(1)
 chan_props_file = sys.argv[1]
 srf_file = sys.argv[2]
+output_file = sys.argv[3]
 
 # read in the MODIS SRF data
 srf_data = read_modis_srf_data(srf_file)
@@ -108,7 +109,7 @@ bt350 = 350.0 * numpy.ones((freqs.size,), numpy.float64)
 r350 = inverse_bright_wavenumber(freqs, bt350)
 
 # write out the arrays to HDF
-writer = HdfWriter('airs2modis.hdf')
+writer = HdfWriter(output_file)
 writer.write('Channel_Mask', mask)
 writer.write('Channel_Weights', response)
 writer.write('Channel_Noise_Rating', noise)