def load_and_plot_diff_mm(varl,to_case,from_cases,startyear, endyear,
avg_over_lev=avg_over_lev,
pmin=pmin,nr_cols=2,
pressure_adjust=pressure_adjust,
p_level=None,
relative=False,
width=6., height=2.3):
cases = [to_case] + from_cases
maps_dic = get_averaged_fields.get_maps_cases(cases,varl,startyear, endyear,
avg_over_lev=avg_over_lev,
pmin=pmin,
pressure_adjust=pressure_adjust, p_level=p_level)
nr_rows = int(np.ceil(len(varl)/nr_cols))
nr_cols = len(from_cases)
fig, axs = subplots_map(nr_rows, nr_cols, figsize=[width*nr_cols,height*nr_rows])
for i, var in enumerate(varl):
if len(varl) == 1: saxs = axs
else: saxs = axs[i,:]
plot_map_diff_only(var, [to_case,*from_cases], maps_dic, relative=relative, cbar_equal=True,
cbar_loc='side', tight_layout=False, inverse_diff=True, axs=saxs)
#for from_case,i in zip(from_cases,range(nr_cols)):
# sax = axs[:,i]
# plot_diff(maps_dic, varl, [from_case,to_case],nr_cols=nr_cols, relative=relative, width=width, axs=sax)
subp_insert_abc(axs, pos_y=0.1)
return axs
def map_sub(ax3, cases, relative, var, var_map, varl, kwargs_diff=None):
if var_map is not None:
var = var_map
maps_dic = get_averaged_fields.get_maps_cases(
cases,
varl,
startyear,
endyear,
avg_over_lev=avg_over_lev,
pmin=pmin,
pressure_adjust=pressure_adjust)
plot_map_diff_only(
var,
cases,
maps_dic,
relative=relative,
cbar_equal=True,
kwargs_diff=kwargs_diff,
axs=ax3, #cmap_diff='RdBu_r',
cbar_loc='under',
tight_layout=False)
pmin=pmin,
time_mask=period,
pressure_adjust=pressure_adjust,
p_level=p_level)
nr_cols = len(from_cases)
nr_rows = int(np.ceil(len(varl)))
fig, axs = subplots_map(nr_rows,
nr_cols,
figsize=[width * nr_cols, asp_rat * width * nr_rows])
for i, var in enumerate(varl):
saxs = axs[i, :]
plot_map_diff_only(var, [to_case, *from_cases],
maps_dic,
relative=(var in varl_rel),
cbar_equal=True,
kwargs_diff={},
axs=saxs,
cmap_diff='RdBu_r',
cbar_loc='side',
tight_layout=False,
inverse_diff=True)
#for from_case,i in zip(from_cases,range(nr_cols)):
# sax = axs[:,i]
# for var, ax in zip(varl, sax.flatten()):
# plot_map_diff_2case(var, from_case,to_case, maps_dic, relative=(var in varl_rel),
# ax=ax, cmap_diff='RdBu_r')
subp_insert_abc(axs, pos_y=0.1)
#plot_diff(maps_dic, varl, cases[::-1],nr_cols=1, relative=relative)
#load_and_plot_diff_mm(varl,to_case,from_cases, startyear, endyear, avg_over_lev, pmin=pmin, relative=relative, pressure_adjust=pressure_adjust,nr_cols=1, width=5.5)
ax.grid(False, which='both')
sns.despine(ax=ax)
ax.set_yscale('log')
set_scalar_formatter(ax)
# maps:
if var_map is not None:
var=var_map
maps_dic = get_averaged_fields.get_maps_cases(cases,[var],startyear, endyear,
avg_over_lev=avg_over_lev,
pmin=pmin,
pressure_adjust=pressure_adjust)
plot_map_diff_only(var, cases, maps_dic, relative=True, cbar_equal=True,
kwargs_diff={}, axs=ax3, cmap_diff='RdBu_r', cbar_loc='under')
#plt.tight_layout()
return
def plt_prof_map_together_ls(var1,var2, areas, cases, asp_rat=1, width=5.5, varl_map=None):
nvars = 2
fig = plt.figure(figsize = [width*nvars,asp_rat*width*nvars])
gs = gridspec.GridSpec(2, nvars+1,height_ratios=[1,1.], width_ratios=[5,5,1])#width_ratios=[2, 1])
axs_prof = []
axs_maps = []
ax1 = plt.subplot(gs[1,0])
ax2 = None#plt.subplot(gs[1,1+i*2])
ax3 = plt.subplot(gs[0,0], projection=ccrs.Robinson())
print(var1,areas, cases, [ax1,ax3])
