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Commit 8c39ebbe authored by tomrink's avatar tomrink
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...@@ -961,11 +961,11 @@ def apply_qc_icing_pireps(icing_alt, cld_top_hgt, cld_phase, cld_opd, cld_mask, ...@@ -961,11 +961,11 @@ def apply_qc_icing_pireps(icing_alt, cld_top_hgt, cld_phase, cld_opd, cld_mask,
# keep = np.where(keep, np.invert((cld_phase[i,] == 4) & (cld_opd[i,] < opd_thin_threshold) & (cld_top_hgt[i,] > icing_alt[i])), False) # keep = np.where(keep, np.invert((cld_phase[i,] == 4) & (cld_opd[i,] < opd_thin_threshold) & (cld_top_hgt[i,] > icing_alt[i])), False)
# Test5 # Test5
keep = np.where(keep, (bt_11um[i,] < 270.0), False) #keep = np.where(keep, (bt_11um[i,] < 270.0), False)
# Test6 # Test6
# keep = np.where(keep, (bt_11um[i,] > 228.0), False) # keep = np.where(keep, (bt_11um[i,] > 228.0), False)
# keep = np.where(keep, np.logical_and(bt_11um[i,] > 228.0, bt_11um[i,] < 270.0), False) keep = np.where(keep, np.logical_and(bt_11um[i,] > 228.0, bt_11um[i,] < 270.0), False)
# Test3 # Test3
# keep = np.where(keep, (cld_opd[i,] >= opd_thick_threshold) & (cld_phase[i,] == 4) & (cld_top_hgt[i,] > icing_alt[i]), False) # keep = np.where(keep, (cld_opd[i,] >= opd_thick_threshold) & (cld_phase[i,] == 4) & (cld_top_hgt[i,] > icing_alt[i]), False)
...@@ -1024,8 +1024,7 @@ def apply_qc_no_icing_pireps(icing_alt, cld_top_hgt, cld_phase, cld_opd, cld_mas ...@@ -1024,8 +1024,7 @@ def apply_qc_no_icing_pireps(icing_alt, cld_top_hgt, cld_phase, cld_opd, cld_mas
if (np.sum(keep) / num_keep) < 0.60: if (np.sum(keep) / num_keep) < 0.60:
continue continue
# keep = np.where(keep, np.logical_and(bt_11um[i,] > 228.0, bt_11um[i,] < 273.0), False) keep = np.where(keep, np.logical_and(bt_11um[i,] > 228.0, bt_11um[i,] < 273.0), False)
keep = np.where(keep, bt_11um[i,] < 273.0, False)
# Test6 # Test6
# keep = np.where(keep, (bt_11um[i,] < 228.0), False) # keep = np.where(keep, (bt_11um[i,] < 228.0), False)
...@@ -1726,7 +1725,6 @@ def split_data(times): ...@@ -1726,7 +1725,6 @@ def split_data(times):
[get_timestamp('2022-01-01_00:00'), get_timestamp('2022-01-07_23:59')], [get_timestamp('2022-01-01_00:00'), get_timestamp('2022-01-07_23:59')],
[get_timestamp('2022-03-01_00:00'), get_timestamp('2022-03-07_23:59')]] [get_timestamp('2022-03-01_00:00'), get_timestamp('2022-03-07_23:59')]]
test_time_idxs = [] test_time_idxs = []
for t_rng in time_ranges: for t_rng in time_ranges:
tidxs = np.searchsorted(times, t_rng) tidxs = np.searchsorted(times, t_rng)
......
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