From 2ecd37a984467558bcbb7b4c551f0bd70b44c9b4 Mon Sep 17 00:00:00 2001
From: tomrink <rink@ssec.wisc.edu>
Date: Wed, 29 May 2024 15:19:17 -0500
Subject: [PATCH] snapshot...
---
modules/contrail/util.py | 6 +++---
1 file changed, 3 insertions(+), 3 deletions(-)
diff --git a/modules/contrail/util.py b/modules/contrail/util.py
index eab33f3d..c898e779 100644
--- a/modules/contrail/util.py
+++ b/modules/contrail/util.py
@@ -116,15 +116,15 @@ def extract(mask_image, image_ts, clavrx_path):
# tmp = horz_shear_3d.sel(Pressure=press, method='nearest')
# tmp = tmp.sel(Longitude=lon, Latitude=lat, method='nearest')
- levels_dict[press_bins[key]].append((press_level, press, lat, lon, temp_value, rh_value, horz_shear_value, static_value, horz_wind_spd_value, vert_shear_value))
+ levels_dict[press_level].append((press, lat, lon, temp_value, rh_value, horz_shear_value, static_value, horz_wind_spd_value, vert_shear_value))
all_list.append((press_level, press, lat, lon, temp_value, rh_value, horz_shear_value, static_value, horz_wind_spd_value, vert_shear_value))
# Create pandas DataFrame for each list of tuples in voxel_dict
voxel_dict_df = {}
for k, v in levels_dict.items():
- print(k, len(v))
+ print('pressure level, number of contrail points: ', k, len(v))
df = pd.DataFrame(v,
- columns=["pressure_level", "pressure", "lat", "lon", "temperature", "relative_humidity",
+ columns=["pressure", "lat", "lon", "temperature", "relative_humidity",
"horz_shear_deform", "static_stability", "horz_wind_speed", "vert_wind_shear"])
voxel_dict_df[k] = df
--
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