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Commit c8d6c377 authored by tomrink's avatar tomrink
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minor

parent 28239b72
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...@@ -331,69 +331,6 @@ def run(pirep_dct, outfile=None, outfile_l1b=None, dt_str_start=None, dt_str_end ...@@ -331,69 +331,6 @@ 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) 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}
cnt_a = 0
for didx, ds_name in enumerate(name_list):
gvals = get_grid_values_all(h5f, ds_name)
if gvals is not None:
grd_dct[ds_name] = gvals
cnt_a += 1
if cnt_a > 0 and cnt_a != len(name_list):
raise GenericException('weirdness')
grd_dct_n = {name: [] for name in name_list}
n_x = int(xlen/w_x)
n_y = int(ylen/w_y)
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}
for didx, ds_name in enumerate(name_list):
grd_dct[ds_name] = np.stack(grd_dct_n[ds_name])
h5f.close()
return grd_dct, ll, cc
# -------------------------------------------------------------------------------------------
def analyze(ice_dct, no_ice_dct): def analyze(ice_dct, no_ice_dct):
last_file = None last_file = None
...@@ -1575,3 +1512,66 @@ def analyze_moon_phase(icing_dict): ...@@ -1575,3 +1512,66 @@ def analyze_moon_phase(icing_dict):
cnt += 1 cnt += 1
print(len(icing_dict), cnt) print(len(icing_dict), cnt)
# ------------ 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}
cnt_a = 0
for didx, ds_name in enumerate(name_list):
gvals = get_grid_values_all(h5f, ds_name)
if gvals is not None:
grd_dct[ds_name] = gvals
cnt_a += 1
if cnt_a > 0 and cnt_a != len(name_list):
raise GenericException('weirdness')
grd_dct_n = {name: [] for name in name_list}
n_x = int(xlen/w_x)
n_y = int(ylen/w_y)
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}
for didx, ds_name in enumerate(name_list):
grd_dct[ds_name] = np.stack(grd_dct_n[ds_name])
h5f.close()
return grd_dct, ll, cc
# -------------------------------------------------------------------------------------------
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