def regr_map_standard(run, index):
assert run in ['ctrl', 'rcp', 'lpd', 'lpi']
assert index in ['SOM', 'AMO', 'TPI']
SST_regr_standard(index)
ds = xr.open_dataset(f'{path_results}/SST/{index}_regr_{run}.nc',
decode_times=False)
regr_map(ds=ds, index=index, run=run)
return
def plot_yrly_regr_maps(self, run):
assert run in ['ctrl', 'lpd', 'had']
tslices = ['']
if run == 'ctrl': tslices.extend(['_100_248', '_151_299'])
elif run == 'lpd': tslices.extend(['_268_416', '_417_565'])
for j, tslice in enumerate(tslices):
print(j)
fn = f'{path_samoc}/SST/{self.index}_regr{tslice}_{run}.nc'
ds = xr.open_dataset(fn)
regr_map(ds=ds, index=self.index, run=run, fn=tslice)
def plot_regression_map(self, run=None):
self.load_regression_files()
if run is None:
for run in ['ctrl', 'rcp', 'lpd', 'lpi', 'had']:
regr_map(ds=self.all_regrs[run],
index=self.index,
run=run,
fn=None)
else:
assert run in ['ctrl', 'rcp', 'lpd', 'lpi', 'had']
regr_map(ds=self.all_regrs[run],
index=self.index,
run=run,
fn=None)
def regr_map_diff_times(run, index):
assert run in ['lpd', 'lpi']
assert index in ['SOM', 'AMO', 'TPI']
if run == 'lpd':
times = ['200_1', '200_2', '412']
SST_regr_lpd(index)
elif run == 'lpi':
times = ['800_1', '800_2', '1480']
SST_regr_lpi(index)
for i in range(3):
ds = xr.open_dataset(
f'{path_results}/SST/{index}_regr_{run}_{times[i]}.nc',
decode_times=False)
regr_map(ds=ds, index=index, run=run, fn=times[i])
return
assert os.path.exists(fn)
ds = xr.open_dataset(fn, decode_times=False)
except:
print(
f'{idx} file for segment {tslice[0]}-{tslice[1]} does not exist.'
)
continue
# visualization
print('plotting')
fn_map = f'{path_results}/SST/{idx}_regr_map_{run}_{tslice[0]}_{tslice[1]}'
try:
assert os.path.exists(fn_map)
except:
regr_map(ds=ds, index=idx, run=run, fn=fn_map)
# compare to observations
print('calculating spatial correlations')
segment = ds.slope
if run == 'ctrl':
segment.coords['TLAT'] = TLAT
da.values[k] = AF().spatial_correlation(field_A=had,
field_B=segment,
selection=region)
da.to_netcdf(fn_new)
# spatial correlation plot
plt.figure()