snapshot...

modules/icing/pirep_goes.py

@@ -39,6 +39,18 @@ ds_types = ['f4' for i in range(21)] + ['i4' for i in range(3)]
 #a_clvr_file = '/home/rink/data/clavrx/clavrx_OR_ABI-L1b-RadC-M3C01_G16_s20190020002186.level2.nc'
 a_clvr_file = '/Users/tomrink/data/clavrx/clavrx_OR_ABI-L1b-RadC-M3C01_G16_s20190020002186.level2.nc'
 
+data_dir = '/Users/tomrink/data/icing/'
+icing_files = ['icing_2018010600_2018033022_QC_DAY.h5', 'icing_2018040100_2018063021_QC_DAY.h5', 'icing_2018070101_2018093022_QC_DAY.h5',
+               'icing_2018100115_2018123022_QC_DAY.h5', 'icing_2019010100_2019033023_QC_DAY.h5']
+icing_l1b_files = []
+
+no_icing_files = ['no_icing_2018010600_2018033022_DAY.h5', 'no_icing_2018040100_2018063021_DAY.h5', 'no_icing_2018070101_2018093022_DAY.h5',
+               'no_icing_2018100115_2018123022_DAY.h5', 'no_icing_2019010100_2019033023_DAY.h5']
+no_icing_l1b_files = []
+
+train_params_day = ['cld_height_acha', 'cld_geo_thick', 'supercooled_cloud_fraction', 'cld_temp_acha', 'solar_zenith_angle',
+                    'cld_reff_dcomp', 'cld_opd_dcomp', 'iwc_dcomp', 'lwc_dcomp', 'cloud_phase']
+
 
 def setup():
     ice_dict, no_ice_dict, neg_ice_dict = pirep_icing(pirep_file)
@@ -783,3 +795,55 @@ def apply_qc_icing_pireps(icing_alt, cld_top_hgt, cld_phase, cld_opd, cld_mask,
         idxs.append(i)
 
     return mask, idxs
+
+
+def fov_extract():
+
+    ice_times = []
+    ice_int_s = []
+
+    for fidx in range(len(icing_files)):
+        fname = icing_files[fidx]
+        f = h5py.File(data_dir+fname, 'r')
+
+        times = f['time'][:]
+        num_obs = len(times)
+
+        icing_int = f['icing_intensity'][:]
+
+        cld_mask = f['cloud_mask'][:, 10:30, 10:30]
+        cld_mask = cld_mask.reshape((num_obs, -1))
+
+        cld_top_temp = f['cld_temp_acha'][:, 10:30, 10:30]
+        cld_top_temp = cld_top_temp.reshape((num_obs, -1))
+
+        ice_mask = []
+        for i in range(num_obs):
+            keep_0 = np.logical_or(cld_mask[i,] == 2, cld_mask[i,] == 3)  # cloudy
+            keep_1 = np.invert(np.isnan(cld_top_temp[i,]))
+            keep = keep_0 & keep_1
+            keep = np.where(keep, cld_top_temp[i,] < 273.0, False)
+
+            ice_mask.append(keep)
+
+    for fidx in range(len(no_icing_files)):
+        fname = no_icing_files[fidx]
+        f = h5py.File(data_dir+fname, 'r')
+
+        times = f['time']
+        num_obs = len(times)
+
+        cld_mask = f['cloud_mask'][:, 10:30, 10:30]
+        cld_mask = cld_mask.reshape((num_obs, -1))
+
+        cld_top_temp = f['cld_temp_acha'][:, 10:30, 10:30]
+        cld_top_temp = cld_top_temp.reshape((num_obs, -1))
+
+        no_ice_mask = []
+        for i in range(num_obs):
+            keep_0 = np.logical_or(cld_mask[i,] == 2, cld_mask[i,] == 3)  # cloudy
+            # keep_1 = np.invert(np.isnan(cld_top_temp[i,]))
+            # keep = keep_0 & keep_1
+            # keep = np.where(keep, cld_top_temp[i,] > 273.0, False)
+
+            no_ice_mask.append(keep_0)
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