Pull out use of weights

viirs2cris_collect.py

@@ -23,8 +23,6 @@ sd = SD(first_file)
 n = sd.select('VIIRS_N').get()
 rads_sum = sd.select('VIIRS_Radiance_Sum').get()
 rads_squared_sum = sd.select('VIIRS_Radiance_Squared_Sum').get()
-total_weights = sd.select('VIIRS_Total_Weights').get()
-weighted_sum = sd.select('VIIRS_Weighted_Sum').get()
 flags = sd.select('VIIRS_Flags').get()
 
 # now fold in data from the other intermediate files
@@ -33,8 +31,6 @@ for filename in other_files:
     n += sd.select('VIIRS_N').get()
     rads_sum += sd.select('VIIRS_Radiance_Sum').get()
     rads_squared_sum += sd.select('VIIRS_Radiance_Squared_Sum').get()
-    total_weights += sd.select('VIIRS_Total_Weights').get()
-    weighted_sum += sd.select('VIIRS_Weighted_Sum').get()
     flags |= sd.select('VIIRS_Flags').get()
 
 # initialize output arrays
@@ -42,19 +38,13 @@ rad_mean = np.empty(n.shape, np.float64)
 rad_std = np.empty(n.shape, np.float64)
 bt_mean = np.empty(n.shape, np.float64)
 std_bt = np.empty(n.shape, np.float64)
-weighted_mean = np.empty(n.shape, np.float64)
-bt_weighted_mean = np.empty(n.shape, np.float64)
 
 # calculate radiance mean and standard deviation
 rad_mean[:] = rads_sum / n
 rad_std[:] = np.sqrt((rads_squared_sum / n) - (rad_mean * rad_mean))
 
-# calculate weighted mean
-weighted_mean[:] = weighted_sum / total_weights
-
 # now convert the radiances to brightness temperature
 bt_mean[:] = viirs_bright(rad_mean)
-bt_weighted_mean[:] = viirs_bright(weighted_mean)
 
 # to get a feel for the standard deviation in terms of
 # brightness temperature, see what BT difference results from
@@ -68,18 +58,14 @@ rad_mean[missing_idxs] = -9999.0
 rad_std[missing_idxs] = -9999.0
 bt_mean[missing_idxs] = -9999.0
 std_bt[missing_idxs] = -9999.0
-weighted_mean[missing_idxs] = -9999.0
-bt_weighted_mean[missing_idxs] = -9999.0
 flags[missing_idxs] |= MISSING
 
 # output to HDF
 writer = HdfWriter(output_file)
 writer.write('VIIRS_N', n)
-writer.write('VIIRS_Radiance_Unweighted', rad_mean, fill=-9999.0)
-writer.write('VIIRS_Radiance', weighted_mean, fill=-9999.0)
+writer.write('VIIRS_Radiance', rad_mean, fill=-9999.0)
 writer.write('VIIRS_Radiance_Std', rad_std, fill=-9999.0)
-writer.write('VIIRS_Brightness_Temp_Unweighted', bt_mean, fill=-9999.0)
-writer.write('VIIRS_Brightness_Temp', bt_weighted_mean, fill=-9999.0)
+writer.write('VIIRS_Brightness_Temp', bt_mean, fill=-9999.0)
 writer.write('VIIRS_Std_Brightness', std_bt, fill=-9999.0)
 writer.write('VIIRS_Flags', flags)
 

viirs2cris_single.py

@@ -18,7 +18,7 @@ def read_viirs_radiances(sdr_filenames):
 
     for i, sdr_filename in enumerate(sdr_filenames):
 
-        f = h5py.File(sdr_filename)
+        f = h5py.File(sdr_filename, 'r')
         g = f['/All_Data']
         g, = g.values()
 
@@ -49,7 +49,6 @@ coll_sd = SD.SD(coll_filename)
 num_coll = coll_sd.select('Number_Of_VIIRS_FOV')[:]
 viirs_along_idx = coll_sd.select('VIIRS_Along_Track_IDX')[:]
 viirs_across_idx = coll_sd.select('VIIRS_Across_Track_IDX')[:]
-viirs_weight = coll_sd.select('Weights')[:]
 
 num_cris_scans, num_cris_angs, num_cris_dets = num_coll.shape
 
@@ -59,10 +58,6 @@ rad_sum_arr = np.empty([3, num_cris_scans, num_cris_angs, num_cris_dets],
                        np.float64)
 rad_squared_sum_arr = np.empty([3, num_cris_scans, num_cris_angs, num_cris_dets],
                                np.float64)
-total_weights_arr = np.empty([3, num_cris_scans, num_cris_angs, num_cris_dets],
-                             np.float64)
-weighted_sum_arr = np.empty([3, num_cris_scans, num_cris_angs, num_cris_dets],
-                            np.float64)
 flags_arr = np.zeros([3, num_cris_scans, num_cris_angs, num_cris_dets],
                      np.int8)
 
@@ -73,8 +68,6 @@ for cris_row in range(num_cris_scans):
             n = n_arr[:,cris_row,cris_col,cris_det]
             rads_sum = rad_sum_arr[:,cris_row,cris_col,cris_det]
             rads_squared_sum = rad_squared_sum_arr[:,cris_row,cris_col,cris_det]
-            total_weights = total_weights_arr[:,cris_row,cris_col,cris_det]
-            weighted_sum = weighted_sum_arr[:,cris_row,cris_col,cris_det]
             flags = flags_arr[:,cris_row,cris_col,cris_det]
 
             num = num_coll[cris_row,cris_col,cris_det]
@@ -82,12 +75,9 @@ for cris_row in range(num_cris_scans):
                 n[:] = 0
                 rads_sum[:] = 0.0
                 rads_squared_sum[:] = 0.0
-                total_weights[:] = 0.0
-                weighted_sum[:] = 0.0
                 continue
             along_idx = viirs_along_idx[cris_row,cris_col,cris_det,:num] - 1
             across_idx = viirs_across_idx[cris_row,cris_col,cris_det,:num] - 1
-            weight = viirs_weight[cris_row,cris_col,cris_det,:num]
             rads = in_rads[:,along_idx,across_idx]
 
             # if there's any invalid data amongst the collocated VIIRS
@@ -102,16 +92,11 @@ for cris_row in range(num_cris_scans):
             rads[bad_idxs] = 0.0
             rads_sum[:] = rads.sum(axis=1)
             rads_squared_sum[:] = (rads * rads).sum(axis=1)
-            total_weights[:] = \
-                (np.logical_not(bad_idxs) * weight).sum(axis=1)
-            weighted_sum[:] = (rads * weight).sum(axis=1)
 
 # write results to HDF
 writer = HdfWriter(out_filename)
 writer.write('VIIRS_N', n_arr)
 writer.write('VIIRS_Radiance_Sum', rad_sum_arr)
 writer.write('VIIRS_Radiance_Squared_Sum', rad_squared_sum_arr)
-writer.write('VIIRS_Total_Weights', total_weights_arr)
-writer.write('VIIRS_Weighted_Sum', weighted_sum_arr)
 writer.write('VIIRS_Flags', flags_arr)