From 4a544737521495ed9d6b7ba73fafd5838bdaed50 Mon Sep 17 00:00:00 2001
From: Angel Farguell Caus <angel.farguell@gmail.com>
Date: Tue, 2 Jul 2019 17:38:23 -0600
Subject: [PATCH] new experiments in forecast.py, solve infrared_perimeters.py
 problem, and reading GOES16 data

---
 forecast.py            |  7 +++++--
 infrared_perimeters.py | 11 +++++++----
 read_goes.py           | 10 ++++++----
 3 files changed, 18 insertions(+), 10 deletions(-)

diff --git a/forecast.py b/forecast.py
index 1a5ad44..1856dc1 100644
--- a/forecast.py
+++ b/forecast.py
@@ -6,7 +6,7 @@ from utils import Dict
 import re, glob, sys, os
 
 
-def process_tign_g(lon,lat,tign_g,bounds,ctime,dx,dy,wrfout_file='',dt_for=900.,plot=False):
+def process_tign_g(lon,lat,tign_g,bounds,ctime,dx,dy,wrfout_file='',dt_for=3600.,plot=False):
     """
     Process forecast from lon, lat, and tign_g
 
@@ -157,7 +157,7 @@ def process_forecast_wrfout(wrfout_file,bounds,plot=False):
 
 if __name__ == "__main__":
     import saveload as sl
-    real = True
+    real = False
 
     if real:
         plot = True
@@ -176,6 +176,9 @@ if __name__ == "__main__":
         if 'point' in ideal.keys():
             p = [[ideal['point'][0]],[ideal['point'][1]],[ideal['point'][2]]]
             data.update(process_ignitions(p,ideal['bounds']))
+        elif 'points' in ideal.keys():
+            p = [[point[0] for point in ideal['points']],[point[1] for point in ideal['points']],[point[2] for point in ideal['points']]]
+            data.update(process_ignitions(p,ideal['bounds']))
         etime = time_iso2num(ideal['ctime'].replace('_','T'))
         time_num_int = (etime-ideal['tign_g'].max(),etime)
         sl.save((data,ideal['lon'],ideal['lat'],time_num_int),'data')
diff --git a/infrared_perimeters.py b/infrared_perimeters.py
index 02f2365..9e0e433 100644
--- a/infrared_perimeters.py
+++ b/infrared_perimeters.py
@@ -122,9 +122,10 @@ def process_infrared_perimeters(dst,bounds,maxp=1000,ngrid=50,plot=False):
                 # read name of the file
                 name = re.findall(r'<name>(.*?)</name>',f_str,re.DOTALL)[0]
                 # read date of the perimeter
-                date = re.match(r'.*([0-9]{2}-[0-9]{2}-[0-9]{4} [0-9]{4})',name).groups()[0]
+                date = re.match(r'.*([0-9]+)-([0-9]+)-([0-9]+) ([0-9]{2})([0-9]{2})',name).groups()
+                date = (date[2],date[0],date[1],date[3],date[4])
                 # create ISO time of the date
-                time_iso = date[6:10]+'-'+date[0:2]+'-'+date[3:5]+'T'+date[11:13]+':'+date[13:15]+':00'
+                time_iso = '%04d-%02d-%02dT%02d:%02d:00' % tuple([ int(d) for d in date ])
                 # create numerical time from the ISO time
                 time_num = time_iso2num(time_iso)
                 # create datetime element from the ISO time
@@ -217,8 +218,10 @@ def process_infrared_perimeters(dst,bounds,maxp=1000,ngrid=50,plot=False):
 
 if __name__ == "__main__":
     plot = True
-    bounds = (-115.97282409667969, -115.28449249267578, 43.808258056640625, 44.302913665771484)
-    dst = './pioneer/perim'
+    #bounds = (-115.97282409667969, -115.28449249267578, 43.808258056640625, 44.302913665771484)
+    #dst = './pioneer/perim'
+    bounds = (-113.85068, -111.89413, 39.677563, 41.156837)
+    dst = './patch/perim'
 
     p = process_infrared_perimeters(dst,bounds,plot=plot)
     sl.save(p,'perimeters')
diff --git a/read_goes.py b/read_goes.py
index 477dbe9..1c8956a 100644
--- a/read_goes.py
+++ b/read_goes.py
@@ -17,7 +17,7 @@ ncf=Dataset(file,'r')
 add_seconds=ncf.variables['t'][0]
 # Datetime of image scan
 dt=datetime(2000, 1, 1, 12)+timedelta(seconds=float(add_seconds.data))
-print 'dt = ' 
+print 'dt = '
 print dt
 
 # Detections in RGB array
@@ -61,7 +61,7 @@ print sat_lon
 sat_sweep=ncf.variables['goes_imager_projection'].sweep_angle_axis
 print 'sat_sweep = '
 print sat_sweep
-# The projection x and y coordinates equals 
+# The projection x and y coordinates equals
 # the scanning angle (in radians) multiplied by the satellite height (https://proj4.org/operations/projections/geos.html)
 X=ncf.variables['x'][:] * sat_h
 Y=ncf.variables['y'][:] * sat_h
@@ -79,6 +79,7 @@ lats[np.isnan(R)]=np.nan
 lons[np.isnan(R)]=np.nan
 
 # create new netCDF file with lat/lon info
+'''
 newfile = "appended" + file
 w_ncf = Dataset(newfile, 'w')
 with Dataset(file) as src, w_ncf as dst:
@@ -93,7 +94,7 @@ with Dataset(file) as src, w_ncf as dst:
     for name, variable in src.variables.iteritems():
         x = dst.createVariable(name, variable.datatype, variable.dimensions)
         dst.variables[name][:] = src.variables[name][:]
-        
+
     # add new lat/lon info
     dst.createDimension('longitude', None)
     dst.createDimension('lattitude', None)
@@ -104,6 +105,7 @@ with Dataset(file) as src, w_ncf as dst:
     dst.variables['lattitude'][:] = lats
     # close the new file
     dst.close()
+'''
 
 # Make a new map object for the HRRR model domain map projection
 mH = Basemap(resolution='l', projection='lcc', area_thresh=5000, \
@@ -137,7 +139,7 @@ l = {'latitude': 41.812,
 #     'longitude': -108.538}
 
 mZ = Basemap(projection='lcc', resolution='i',
-            width=3E5, height=3E5, 
+            width=3E5, height=3E5,
             lat_0=l['latitude'], lon_0=l['longitude'],)
 
 # Now we can plot the GOES data on a zoomed in map centered on the Sugarloaf wildfire
-- 
2.11.4.GIT