From 45173c0d8e93b7d30d8ca5f60508a0828d55af2e Mon Sep 17 00:00:00 2001
From: tuckersiegel <siegel.tucker@gmail.com>
Date: Mon, 22 Feb 2021 14:33:28 -0500
Subject: [PATCH] normals adjustment
---
to_mongo.py | 40 +++++++++++++++++++++++++++++++---------
1 file changed, 31 insertions(+), 9 deletions(-)
diff --git a/to_mongo.py b/to_mongo.py
index 3cf477a..415fe4f 100644
--- a/to_mongo.py
+++ b/to_mongo.py
@@ -98,15 +98,26 @@ for year in years:
count += 1
+ if len(locs) != 0:
+ new_result = gdd.insert_many(locs)
+
### 30 YEAR NORMALS ###
### Covers from 1981-2010 ###
+db = client["gdd_database"]
+
+gdd = db.normals
+
+gdd.drop()
+
+gdd = db["normals"]
+
+resp = gdd.create_index([ ("location", "2dsphere") ])
+resp = gdd.create_index([ ("year", 1) ])
+
single_year_min = np.zeros((365, 621, 1405))
single_year_max = np.zeros((365, 621, 1405))
-single_year_min[:] = np.nan
-single_year_max[:] = np.nan
-
for year in range(1981, 2010+1):
print (year)
data = xr.open_dataset("data/temps_%s.nc" % year)
@@ -123,16 +134,29 @@ for year in range(1981, 2010+1):
tmin_2 = tmaxs[60:]
tmins = np.concatenate([tmin_1, tmin_2], axis=0)
- tmaxs = np.concatenate([tmin_1, tmin_2], axis=0)
+ tmaxs = np.concatenate([tmax_1, tmin_2], axis=0)
single_year_max += tmaxs/30
single_year_min += tmins/30
-
x = np.where(~np.isnan(np.nanmean(single_year_max, axis=0)))
-x = [(a, b) for a, b in zip(x[0], x[1])]
+# x = [(a, b) for a, b in zip(x[0], x[1])]
-lat = lat[::-1]
+# FORCE LOCATIONS TO COLLEGE PARK, LAT 38.99 LON -76.94 BECAUSE OF ATLAS LIMIT
+
+a1 = np.where(38.5 < lat)[0].tolist()
+a2 = np.where(lat < 39.5)[0].tolist()
+lat_a = np.array(list(set(a1) & set(a2)))
+
+a1 = np.where(-77 < lon)[0].tolist()
+a2 = np.where(lon < -76)[0].tolist()
+lon_a = np.array(list(set(a1) & set(a2)))
+
+x1 = np.array(np.meshgrid(lat_a, lon_a)).T.reshape(len(lat_a) * len(lon_a), 2).tolist()
+x1 = [(z[0], z[1]) for z in x1]
+x2 = [(a, b) for a, b in zip(x[0], x[1])] # fix to x = [..... (x[0], x[1])] and all limiting stuff above and below when atlas limit removed
+
+x = list(set(x1) & set(x2))
tmins = single_year_min
tmaxs = single_year_max
@@ -163,8 +187,6 @@ for i in tqdm.tqdm(x):
t["prism_lat"] = int(a[0])
t["prism_lon"] = int(a[1])
- t["last_date"] = 0#datetime.datetime.strptime(str(soy + np.timedelta64(len(tmin_) - 1, "D")) , "%Y-%m-%d")
- t["year"] = 0
t["min_temps"] = list([float(a) for a in tmin_])
t["max_temps"] = list([float(a) for a in tmax_])
t["_id"] = _id
--
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