From c2a4f147faa60467f56bd2308645baf8be56c256 Mon Sep 17 00:00:00 2001
From: tomrink <rink@ssec.wisc.edu>
Date: Sun, 2 Jan 2022 09:35:12 -0600
Subject: [PATCH] snapshot...
---
modules/icing/pirep_goes.py | 112 ++++++++++++++++++++++++++----------
1 file changed, 82 insertions(+), 30 deletions(-)
diff --git a/modules/icing/pirep_goes.py b/modules/icing/pirep_goes.py
index 7efbb790..83018033 100644
--- a/modules/icing/pirep_goes.py
+++ b/modules/icing/pirep_goes.py
@@ -4,8 +4,8 @@ import pickle
import matplotlib.pyplot as plt
import os
from util.util import get_time_tuple_utc, GenericException, add_time_range_to_filename, is_night, is_day, \
- check_oblique, make_times, find_bin_index, get_timestamp, homedir, write_icing_file, make_for_full_domain_predict, \
- make_for_full_domain_predict2
+ check_oblique, get_timestamp, homedir, write_icing_file, make_for_full_domain_predict, \
+ make_for_full_domain_predict2, get_indexes_within_threshold
from util.plot import make_icing_image
from util.geos_nav import get_navigation, get_lon_lat_2d_mesh
from util.setup import model_path_day, model_path_night
@@ -1627,8 +1627,8 @@ def normalize(data, param, mean_std_dict, add_noise=False, noise_scale=1.0, seed
return data
-lon_space = np.linspace(-180, 180, 361)
-lat_space = np.linspace(-90, 90, 181)
+lon_space = np.linspace(-180, 180, 721)
+lat_space = np.linspace(-90, 90, 361)
def spatial_filter(icing_dict):
@@ -1637,6 +1637,7 @@ def spatial_filter(icing_dict):
grd_y_hi = lat_space.shape[0] - 1
grd_bins = np.full((lat_space.shape[0], lon_space.shape[0]), 0)
+ grd_bins_keys = [[[] for i in range(lon_space.shape[0])] for j in range(lat_space.shape[0])]
for key in keys:
rpts = icing_dict.get(key)
@@ -1653,33 +1654,84 @@ def spatial_filter(icing_dict):
continue
grd_bins[lat_idx, lon_idx] += 1
+ grd_bins_keys[lat_idx][lon_idx].append(key)
- return grd_bins
-
-
-# def spatial_filter2(icing_dict):
-# keys = icing_dict.keys()
-# grd_x_hi = lon_space.shape[0] - 1
-# grd_y_hi = lat_space.shape[0] - 1
-#
-# grd_bins = np.full((lat_space.shape[0], lon_space.shape[0]), 0)
-#
-# for key in keys:
-# tup = icing_dict.get(key)
-# lat = tup[0]
-# lon = tup[1]
-#
-# lon_idx = np.searchsorted(lon_space, lon)
-# lat_idx = np.searchsorted(lat_space, lat)
-#
-# if lon_idx < 0 or lon_idx > grd_x_hi:
-# continue
-# if lat_idx < 0 or lat_idx > grd_y_hi:
-# continue
-#
-# grd_bins[lat_idx, lon_idx] += 1
-#
-# return grd_bins
+ return grd_bins, grd_bins_keys
+
+
+def spatial_filter2(icing_dict):
+ keys = icing_dict.keys()
+ grd_x_hi = lon_space.shape[0] - 1
+ grd_y_hi = lat_space.shape[0] - 1
+
+ grd_bins = np.full((lat_space.shape[0], lon_space.shape[0]), 0)
+ grd_bins_keys = [[[] for i in range(lon_space.shape[0])] for j in range(lat_space.shape[0])]
+
+ for key in keys:
+ tup = icing_dict.get(key)
+ lat = tup[0]
+ lon = tup[1]
+
+ lon_idx = np.searchsorted(lon_space, lon)
+ lat_idx = np.searchsorted(lat_space, lat)
+
+ if lon_idx < 0 or lon_idx > grd_x_hi:
+ continue
+ if lat_idx < 0 or lat_idx > grd_y_hi:
+ continue
+
+ grd_bins[lat_idx, lon_idx] += 1
+ grd_bins_keys[lat_idx][lon_idx].append(key)
+
+ return grd_bins, grd_bins_keys
+
+
+def process_boeing(boeing_dct, pirep_dct, threshold=3000):
+
+ boeing_times = list(boeing_dct.keys())
+ pirep_times = np.array(list(pirep_dct.keys()))
+
+ pt_s = []
+ bt_s = []
+ bi_s = []
+ for k, bt in enumerate(boeing_times):
+ idx_s, v_s = get_indexes_within_threshold(pirep_times, bt, threshold=threshold)
+ if len(idx_s) > 0:
+ bt_s.append(bt)
+ bi_s.append(k)
+ pt_s.append(v_s[0])
+
+ boeing_times = np.array(boeing_times)
+
+ sub_pirep_dct = {}
+ sub_boeing_dct = {}
+ for key in pt_s:
+ sub_pirep_dct[key] = pirep_dct.get(key)
+ for key in bt_s:
+ sub_boeing_dct[key] = boeing_dct.get(key)
+
+ grd_bins, _ = spatial_filter(sub_pirep_dct)
+ grd_bins_boeing, key_bins = spatial_filter2(sub_boeing_dct)
+
+ grd_bins = np.where(grd_bins > 0, 1, grd_bins)
+ grd_bins_boeing = np.where(grd_bins_boeing > 0, 1, grd_bins_boeing)
+
+ ovrlp_grd_bins = grd_bins + grd_bins_boeing
+ print(np.sum(ovrlp_grd_bins == 2))
+
+ ovlp_keys = []
+ for j in range(lat_space.shape[0]):
+ for i in range(lon_space.shape[0]):
+ if ovrlp_grd_bins[j, i] == 2:
+ keys = key_bins[j][i]
+ nkeys = len(keys)
+ for k in range(nkeys):
+ ovlp_keys.append(keys[k])
+ set_a = set(ovlp_keys)
+ set_b = set(boeing_times)
+ print(len(set_a), len(set_b))
+ set_b.difference_update(set_a)
+ print(len(set_b))
# dt_str_0: start datetime string in format YYYY-MM-DD_HH:MM (default)
--
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