From 652699208718bdd4f45c8f2be8c5e2c35253ae37 Mon Sep 17 00:00:00 2001
From: tomrink <rink@ssec.wisc.edu>
Date: Wed, 21 Jul 2021 21:12:08 -0500
Subject: [PATCH] minor...
---
modules/icing/pirep_goes.py | 21 ++++++++++++++++++++-
1 file changed, 20 insertions(+), 1 deletion(-)
diff --git a/modules/icing/pirep_goes.py b/modules/icing/pirep_goes.py
index d45fa102..9407a655 100644
--- a/modules/icing/pirep_goes.py
+++ b/modules/icing/pirep_goes.py
@@ -12,6 +12,7 @@ import datetime
from datetime import timezone
import glob
from skyfield import api, almanac
+import xarray as xr
goes_date_format = '%Y%j%H'
goes16_directory = '/arcdata/goes/grb/goes16' # /year/date/abi/L1b/RadC
@@ -303,12 +304,24 @@ def run(pirep_dct, outfile=None, outfile_l1b=None, dt_str_start=None, dt_str_end
create_file(outfile_l1b, data_dct, l1b_ds_list, l1b_ds_types, lon_c, lat_c, time_s, fl_alt_s, ice_int_s, unq_ids)
+# ------------ This code will not be needed when we implement a Fully Connected CNN -----------------------------------
+# Example GOES file to retrieve GEOS parameters in MetPy form (CONUS)
+exmp_file = '/Users/tomrink/data/OR_ABI-L1b-RadC-M6C14_G16_s20193140811215_e20193140813588_c20193140814070.nc'
+
+
def make_for_full_domain_predict(clvrx_file, name_list=l1b_ds_list):
w_x = 16
w_y = 16
xlen = 2500
ylen = 1500
+ exmpl_ds = xr.open_dataset(exmp_file)
+ mdat = exmpl_ds.metpy.parse_cf('Rad')
+ geos = mdat.metpy.cartopy_crs
+ #xlen = mdat.x
+ #ylen = mdat.y
+ exmpl_ds.close()
+
h5f = h5py.File(clvrx_file, 'r')
grd_dct = {name: None for name in name_list}
@@ -331,11 +344,17 @@ def make_for_full_domain_predict(clvrx_file, name_list=l1b_ds_list):
i_0 = 0
j_0 = 0
+ cc = []
+ ll = []
+
for didx, ds_name in enumerate(name_list):
for j in range(4, n_y-4, 1):
j_ul = j_0 + j * w_y
for i in range(4, n_x-4, 1):
i_ul = i_0 + i * w_x
+ if didx == 0:
+ ll.append(j_ul)
+ cc.append(i_ul)
grd_dct_n[ds_name].append(grd_dct[ds_name][j_ul:j_ul+w_y, i_ul:i_ul+w_x])
grd_dct = {name: None for name in name_list}
@@ -344,7 +363,7 @@ def make_for_full_domain_predict(clvrx_file, name_list=l1b_ds_list):
h5f.close()
- return grd_dct, grd_dct[name_list[0]].shape[0]
+ return grd_dct, ll, cc
def analyze(ice_dct, no_ice_dct):
--
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