plt.vlines(x=min(rlon_o[buffer:-buffer]),
ymin=min(rlat_o[buffer:-buffer]),
ymax=max(rlat_o[buffer:-buffer]),
color='black',
linewidth=4)
plt.vlines(x=max(rlon_o[buffer:-buffer]),
ymin=min(rlat_o[buffer:-buffer]),
ymax=max(rlat_o[buffer:-buffer]),
color='black',
linewidth=4)
Plot_CCLM(dir_mistral='NETCDFS_CCLM/03/member_relax_3_big_00/post/',
name=name_2,
bcolor='black',
var=Vari,
flag='FALSE',
color_map='TRUE',
alph=1,
grids='FALSE',
grids_color='red',
rand_obs='TRUE',
NN=NN)
xs, ys, zs = rp.transform_points(
pc,
np.array([-17, 105.0]), # Adjust for other domains!
np.array([3, 60])).T # Adjust for other domains!
ax.set_xlim(xs)
ax.set_ylim(ys)
plt.savefig(DIR_exp + 'NAMES' + "/" + pdf_name)
plt.close()
# RMSE time-series
fontsize=15)
plt.hlines(y=min(rlat_f), xmin=min(rlon_f), xmax=max(rlon_f), color='red',linestyles= 'dashed', linewidth=2)
plt.hlines(y=max(rlat_f), xmin=min(rlon_f), xmax=max(rlon_f), color='red',linestyles= 'dashed', linewidth=2)
plt.vlines(x=min(rlon_f), ymin=min(rlat_f), ymax=max(rlat_f), color='red',linestyles= 'dashed', linewidth=2)
plt.vlines(x=max(rlon_f), ymin=min(rlat_f), ymax=max(rlat_f), color='red',linestyles= 'dashed', linewidth=2)
plt.hlines(y=min(rlat_o), xmin=min(rlon_o), xmax=max(rlon_o), color='black',linestyles= 'dashed', linewidth=2)
plt.hlines(y=max(rlat_o), xmin=min(rlon_o), xmax=max(rlon_o), color='black',linestyles= 'dashed', linewidth=2)
plt.vlines(x=min(rlon_o), ymin=min(rlat_o), ymax=max(rlat_o), color='black',linestyles= 'dashed', linewidth=2)
plt.vlines(x=max(rlon_o), ymin=min(rlat_o), ymax=max(rlat_o), color='black',linestyles= 'dashed', linewidth=2)
plt.hlines(y=min(rlat_o[buffer:-buffer]), xmin=min(rlon_o[buffer:-buffer]), xmax=max(rlon_o[buffer:-buffer]), color='black', linewidth=4)
plt.hlines(y=max(rlat_o[buffer:-buffer]), xmin=min(rlon_o[buffer:-buffer]), xmax=max(rlon_o[buffer:-buffer]), color='black', linewidth=4)
plt.vlines(x=min(rlon_o[buffer:-buffer]), ymin=min(rlat_o[buffer:-buffer]), ymax=max(rlat_o[buffer:-buffer]), color='black', linewidth=4)
plt.vlines(x=max(rlon_o[buffer:-buffer]), ymin=min(rlat_o[buffer:-buffer]), ymax=max(rlat_o[buffer:-buffer]), color='black', linewidth=4)
Plot_CCLM(dir_mistral='/work/bb0962/work4/member_relax_3_big/post/',name=name_2,bcolor='black',var='T_2M',flag='FALSE',color_map='TRUE', alph=1, grids='FALSE', grids_color='red', rand_obs='TRUE', NN=NN)
#plt.title("Shift "+ str(4)+pdf_name)
xs, ys, zs = rp.transform_points(pc,
np.array([-17, 105.0]),
np.array([3, 60])).T
# rp = ccrs.RotatedPole(pole_longitude=-162.0,
# pole_latitude=39.25,
# globe=ccrs.Globe(semimajor_axis=6370000,
# semiminor_axis=6370000))
ax.set_xlim(xs)
ax.set_ylim(ys)
# Plot_CCLM(bcolor='black', grids='FALSE', flag='FALSE')
plt.savefig(pdf_name)
plt.close()
def plot_rmse_spread(PDF="name.pdf",
vari="RMSE",
VAL=np.zeros((10, 10, 10)),
x=10,
y=10,
col=['k', 'r', 'b', 'g', 'm']):
#Plot_CCLM(dir_mistral='/work/bb1029/b324045/work5/03/member_relax_3_big_00/post/', name=name_2, bcolor='black',
# var=Vari, flag='FALSE', color_map='TRUE', alph=1, grids='FALSE', grids_color='red', rand_obs='FALSE',
# NN=NN)
Plot_CCLM(dir_mistral='NETCDFS_CCLM/eobs/',
name=name_2,
bcolor='black',
var=Vari,
flag='FALSE',
color_map='TRUE',
alph=1,
grids='FALSE',
grids_color='red',
rand_obs='FALSE',
NN=NN)
if vari == "RMSE":
# v = np.linspace(0, .8, 9, endpoint=True)
v = np.linspace(0, 3.2, 9, endpoint=True)
else:
# v = np.linspace(0, .8, 9, endpoint=True)
v = np.linspace(0, .8, 9, endpoint=True)
if vari == "RMSE":
cs = plt.contourf(lons_f1,
lats_f1,
VAL,
v,
transform=ccrs.PlateCarree(),
cmap=plt.cm.terrain)
# cs = plt.pcolor(lons_f1,lats_f1,VAL, cmap=plt.cm.terrain)
cb = plt.colorbar(cs)
cb.set_label('RMSE [K]', fontsize=20)
cb.ax.tick_params(labelsize=20)
else:
if vari == "SPREAD":
# cs = plt.pcolor(lons_f1, lats_f1, VAL,cmap=plt.cm.terrain)
cs = plt.contourf(lons_f1,
lats_f1,
VAL,
v,
transform=ccrs.PlateCarree(),
cmap=plt.cm.terrain)
cb = plt.colorbar(cs)
cb.set_label('SPREAD [K]', fontsize=20)
cb.ax.tick_params(labelsize=20)
plt.hlines(y=min(rlat_o[buffer:-buffer]),
xmin=min(rlon_o[buffer:-buffer]),
xmax=max(rlon_o[buffer:-buffer]),
color='black',
linewidth=4)
plt.hlines(y=max(rlat_o[buffer:-buffer]),
xmin=min(rlon_o[buffer:-buffer]),
xmax=max(rlon_o[buffer:-buffer]),
color='black',
linewidth=4)
plt.vlines(x=min(rlon_o[buffer:-buffer]),
ymin=min(rlat_o[buffer:-buffer]),
ymax=max(rlat_o[buffer:-buffer]),
color='black',
linewidth=4)
plt.vlines(x=max(rlon_o[buffer:-buffer]),
ymin=min(rlat_o[buffer:-buffer]),
ymax=max(rlat_o[buffer:-buffer]),
color='black',
linewidth=4)
# added 22.08.2017
plt.ylim([min(rlat_o[buffer:-buffer]), max(rlat_o[buffer:-buffer])])
plt.xlim([min(rlon_o[buffer:-buffer]), max(rlon_o[buffer:-buffer])])
plt.savefig(PDF)
plt.close()
plt.vlines(x=min(rlon_o[buffer:-buffer]),
ymin=min(rlat_o[buffer:-buffer]),
ymax=max(rlat_o[buffer:-buffer]),
color='black',
linewidth=4)
plt.vlines(x=max(rlon_o[buffer:-buffer]),
ymin=min(rlat_o[buffer:-buffer]),
ymax=max(rlat_o[buffer:-buffer]),
color='black',
linewidth=4)
Plot_CCLM(dir_mistral='/work/bb0962/work3/member_relax_3_big/post/',
name='member_relax_3_T_2M_ts_monmean_1995.nc',
bcolor='black',
var='T_2M',
flag='FALSE',
color_map='TRUE',
alph=1,
grids='FALSE',
grids_color='red',
rand_obs='TRUE',
NN=NN)
plt.title("Shift " + str(4) + pdf_name)
xs, ys, zs = rp.transform_points(pc, np.array([-17, 105.0]), np.array([3,
60])).T
# rp = ccrs.RotatedPole(pole_longitude=-162.0,
# pole_latitude=39.25,
# globe=ccrs.Globe(semimajor_axis=6370000,
# semiminor_axis=6370000))
ax.set_xlim(xs)
ax.set_ylim(ys)
ymin=min(rlat_o[buffer:-buffer]),
ymax=max(rlat_o[buffer:-buffer]),
color='black',
linewidth=4)
plt.vlines(x=max(rlon_o[buffer:-buffer]),
ymin=min(rlat_o[buffer:-buffer]),
ymax=max(rlat_o[buffer:-buffer]),
color='black',
linewidth=4)
Plot_CCLM(dir_mistral='/NETCDFS_CCLM/eobs/',
name=name_2,
bcolor='black',
var=Vari,
flag='FALSE',
color_map='TRUE',
alph=1,
grids='FALSE',
grids_color='red',
rand_obs='TRUE',
NN=NN)
xs, ys, zs = rp.transform_points(
pc,
np.array([-17, 105.0]), # Adjust for other domains!
np.array([3, 60])).T # Adjust for other domains!
ax.set_xlim(xs)
ax.set_ylim(ys)
plt.ylim([min(rlat_o[buffer:-buffer]), max(rlat_o[buffer:-buffer])])
plt.xlim([min(rlon_o[buffer:-buffer]), max(rlon_o[buffer:-buffer])])