def plot_jointplot(ddic, eusaar, nsec, unit, var, xl, ul=1.5, ll=4.):
data = ddic[nsec] # ".keys()
data = data['log']
# fi, axs = plt.subplots(2, sharex=True)
xl = var + '_' + eusaar
yl = var + '_' + nsec
g = sns.jointplot(x=xl, y=yl, data=data, kind="hex", gridsize=20)
# x0, x1 = g.ax_joint.get_xlim()
# y0, y1 = g.ax_joint.get_ylim()
# ul = 3.8#max(x0, y0)
# ll = 1#min(x1, y1)
lims = [ul, ll]
ul_int = np.floor(ul)
ll_int = np.ceil(ll) + 1
g.ax_joint.set_yticks(np.arange(ul_int, ll_int))
g.ax_joint.set_xticks(np.arange(ul_int, ll_int))
g.ax_joint.set_yticklabels(10 ** np.arange(ul_int, ll_int)) # np.arange(1,6))
g.ax_joint.set_xticklabels(10 ** np.arange(ul_int, ll_int)) # np.arange(1,6))
g.ax_joint.set_xlabel('%s: %s %s' % (var, get_nice_name_case(eusaar), unit)) # np.arange(1,6))
g.ax_joint.set_ylabel('%s: %s %s' % (var, get_nice_name_case(nsec), unit)) # np.arange(1,6))
g.ax_joint.plot(lims, lims, ':k')
g.ax_joint.set_xlim(lims) # , lims)#, ':k')
g.ax_joint.set_ylim(lims) # , lims)#, ':k')
plt.plot()
plt.tight_layout()
fp = plot_path + '/%s_jointplot_%s_allstations_%s' % (var, nsec, version)
print(fp)
plt.savefig(fp + '.png')
plt.savefig(fp + '.pdf')
plt.show()
return xl
def set_title_diff(case_ctrl, case_oth, relative, glob_diff=''):
nn_ctrl = get_nice_name_case(case_ctrl)
nn_oth = get_nice_name_case(case_oth)
if relative:
return f'{nn_oth} to {nn_ctrl}{glob_diff}'
else:
return f'{nn_oth}-{nn_ctrl}{glob_diff}'
def plt_station(_df, _df_16, _df_84, ax, st, var, ylim,
yscale='linear'):
ax.set_xticks(range(1, 12, 2))
_df_s = _df[_df['station'] == st]
_df_s16 = _df_16[_df_16['station'] == st]
_df_s84 = _df_84[_df_84['station'] == st]
x = _df_s['month']
y = _df_s
lines = []
labels = []
for source in _df_s['source'].unique():
_df_ss16 = _df_s16[_df_s16['source'] == source].set_index('month').reindex(range(1, 13))
_df_ss84 = _df_s84[_df_s84['source'] == source].set_index('month').reindex(range(1, 13))
ax.fill_between(_df_ss16.index, _df_ss16[var], _df_ss84[var], color=get_case_col(source), alpha=0.3)
for source in _df_s['source'].unique():
_df_ss = _df_s[_df_s['source'] == source].set_index('month').reindex(range(1, 13))
# print(_df_ss[var])
line = ax.plot(_df_ss.index, _df_ss[var], color=get_case_col(source), label=source, marker='*', markersize=4)
lines = lines + line # s[0]
labels.append(get_nice_name_case(source))
ax.set_yscale(yscale)
ca = coll_ltr.loc[st, dall_c]
ax.set_title(st)#+',' +ca)
if ylim is not None:
ax.set_ylim(ylim)
ax.set_xlim([.8,12.2])
return labels, lines
def corr_plt_latlon(var_c, varl_to, cases_ctrl=cases_orig, case_oth=cases_sec[0], cmap='RdBu_r', pmin=850.):
# %%
cbar_orientation = 'vertical'
cases_ctrl = cases_orig
case_oth = cases_sec[0]
ncol = len(cases_ctrl)
nrow = len(varl_to)
subfig_size = 2.6
asp_ratio = 1.6
figsize = [subfig_size * ncol * asp_ratio, subfig_size * nrow]
# noinspection PyTypeChecker
fig, axs = subplots_map(nrow, ncol, figsize=figsize, sharex=True, sharey=True)
norm_dic = dict(
NCONC01=colors.SymLogNorm(vmin=-1e3, vmax=1e3, linthresh=10),
NMR01=colors.SymLogNorm(vmin=-10, vmax=10, linthresh=.1),
AWNC_incld=colors.SymLogNorm(vmin=-20, vmax=20, linthresh=.1),
AREL_incld=colors.SymLogNorm(vmin=-5, vmax=5, linthresh=.1)
)
for j, var in enumerate(varl_to):
saxs = axs[j, :]
for i, case in enumerate(cases_ctrl):
ax = saxs[i]
_vars = [var, var_c]
_ds = cases_dic[case_oth][_vars]- cases_dic[case][_vars]
_ds = _ds.sel(lev=slice(pmin,None))
_da_corr = corr(_ds[var],_ds[var_c], dim=['time','lev'])
nn_ctrl = get_nice_name_case(case)
nn_oth = get_nice_name_case(case_oth)
title = f'Correlation $\Delta V = V_x - V_y$),\n x={nn_oth}, y={nn_ctrl}'
_da_corr.load()
label = f'corr($\Delta${get_fancy_var_name(var)},$\Delta${get_fancy_var_name(var_c)})'#)
plt_kwargs ={}
plt_kwargs = make_cbar_kwargs(label, plt_kwargs, cbar_orientation)
plt_map(_da_corr, ax=ax, cmap=cmap,
# cbar_orientation='vertical',
# #ax=ax,
# #norm=norm_dic[var],
# #relative=False,
# #ylim=[1e3, 200],
**plt_kwargs)
ax.set_title(title)
for ax in axs.flatten():
ax.set_ylabel('')
ax.set_xlabel('')
#for ax in axs[:, 0]:
# ax.set_ylabel('Pressure [hPa]')
for ax in axs[-1, :]:
ax.set_xlabel('Latitude [$^\circ$N]')
fig.tight_layout()
#fn = filen_base + f'corr_NMR_N_clouds_{case_oth}' + '_'.join(cases_ctrl) + f'{startyear}-{endyear}'
#plt.savefig(fn + '.pdf')
#plt.savefig(fn + '.png')
plt.show()
# %%
return _da_corr
def set_title_abs(case_ctrl, glob_diff=''):
nn_ctrl = get_nice_name_case(case_ctrl)
return f'{nn_ctrl}{glob_diff}'
def plot_grid(dic_finish,
subs='TOT',
st_ls=None,
name='all_stations',
ylim=[5, 8.8e3],
yscale='linear',
plot_sec=True,
nr_col=4,
figsize=None,
ylim_ZEP=[0, 500]):
colors_source = get_cmap_dic(dic_finish.keys())
colors_source['EUSAAR'] = 'k'
dic_ds = dic_finish
t_cs = dic_ds[list(dic_ds.keys())[0]]
st_ls = list(get_ordered_stations())
# st_ls = list(loc_tr[loc_tr['Region']==reg].index)
print(list(st_ls))
if len(st_ls) > nr_col:
nr_row = int(np.ceil(len(st_ls) / nr_col))
else:
nr_row = 1
nr_col = len(st_ls)
if figsize is None:
figsize = [10 / 4 * nr_col, 10 / 6 * nr_row]
fig, axs = plt.subplots(nr_row,
nr_col,
sharex=True,
sharey=True,
figsize=figsize)
axs_nf = axs
if nr_row > 1: axs = axs.flatten()
for station, ax in zip(st_ls, axs):
lines = []
labels = []
for key in dic_finish.keys():
_ds = dic_finish[key]
#if 'dNdlog10dp_sec' in _ds:
# plt_perc(dic_finish[key]['dNdlog10dp_sec'], station, key,
# color=get_case_col(key),
# ax=ax,
# subs=subs, percs=[16,84], yscale=yscale, ylim=ylim)
## plt_perc(dic_finish[key]['dNdlog10dp_mod'], station, key,
# color=get_case_col(key),
# ax=ax,
# subs=subs, percs=[16,84], yscale=yscale, ylim=ylim)
#else:
plt_perc(dic_finish[key]['dNdlog10dp'],
station,
key,
color=get_case_col(key),
ax=ax,
subs=subs,
percs=[16, 84],
yscale=yscale,
ylim=ylim)
for key in dic_finish.keys():
_ds = dic_finish[key]
#if 'dNdlog10dp_sec' in _ds:
# line =plt_median(dic_finish[key]['dNdlog10dp_sec'], station, key,
# color=get_case_col(key),
# ax=ax,
# subs=subs, percs=[16,84], yscale=yscale, ylim=ylim)
# line =plt_median(dic_finish[key]['dNdlog10dp_mod'], station, key,
# color=get_case_col(key),
# ax=ax,
# subs=subs, percs=[16,84], yscale=yscale, ylim=ylim)
#else:
if 'dNdlog10dp_sec' in _ds:
line = plt_median(dic_finish[key]['dNdlog10dp_sec'].where(
dic_finish[key]['dNdlog10dp_sec'] > 0),
station,
key,
color=get_case_col(key),
ax=ax,
subs=subs,
percs=[16, 84],
yscale=yscale,
ylim=ylim,
plt_kwargs={'linestyle': 'dashed'})
line = plt_median(dic_finish[key]['dNdlog10dp'],
station,
key,
color=get_case_col(key),
ax=ax,
subs=subs,
percs=[16, 84],
yscale=yscale,
ylim=ylim)
lines = lines + line
labels.append(get_nice_name_case(key))
if station == 'ZEP':
axins = insert_ZEP(ax)
for key in dic_finish.keys():
plt_perc(dic_finish[key]['dNdlog10dp'],
station,
key,
color=get_case_col(key),
ax=axins,
subs=subs,
percs=[16, 84],
yscale=yscale,
ylim=ylim_ZEP)
for key in dic_finish.keys():
plt_median(dic_finish[key]['dNdlog10dp'],
station,
key,
color=get_case_col(key),
ax=axins,
subs=subs,
percs=[16, 84],
yscale=yscale,
ylim=ylim_ZEP)
if 'dNdlog10dp_sec' in _ds:
plt_median(dic_finish[key]['dNdlog10dp_sec'],
station,
key,
color=get_case_col(key),
ax=axins,
subs=subs,
percs=[16, 84],
yscale=yscale,
ylim=ylim_ZEP)
ax.indicate_inset_zoom(
axins,
edgecolor='r',
)
fix_ins(axins)
if subs == 'TOT':
cat = coll_ltr.loc[station, dall_c]
ax.set_title(station) #+' '+cat)
else:
cat = coll_ltr.loc[station, dall_c]
ax.set_title(station + ' ' + subs) #+', '+cat)
ax.grid(True)
ax.spines['left'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.spines['top'].set_visible(False)
ax.tick_params(axis=u'y', which=u'both', length=0)
if nr_row > 1:
for ii in range(nr_row):
for jj in range(nr_col):
if ii != nr_row - 1:
axs_nf[ii, jj].set_xlabel('')
if jj != 0:
axs_nf[ii, jj].set_ylabel('')
else:
axs_nf[ii, jj].set_ylabel('dN/dlog$_{10}$D [cm$^{-3}$]')
fig.tight_layout()
lgn = fig.legend(
lines,
labels,
bbox_to_anchor=(0, 1., 1, 0.5), # (0, -0.04, 1., .1),
loc='lower center',
ncol=4,
# mode="expand",
borderaxespad=0.,
fontsize=11,
frameon=False) # bbox_to_anchor=(0, 1., 1, 0.5))
#fig.legend(lines, labels, bbox_to_anchor=(0,1.,1,0.5),#(0, -0.04, 1., .1),
# loc='lower center', ncol=4,
# #mode="expand",
# borderaxespad=0., fontsize=11, frameon=False)# bbox_to_anchor=(0, 1., 1, 0.5))
fn = paths_plotsave[
'eusaar'] + '/sizedist/%s_overview_yscale_%s_sec%s_%s.' % (
name.replace(' ', '-'), yscale, plot_sec, subs)
print(fn)
make_folders(fn)
plt.savefig(fn + 'png', bbox_extra_artists=(lgn, ), bbox_inches='tight')
plt.savefig(fn + 'pdf', bbox_extra_artists=(lgn, ), bbox_inches='tight')
plt.show()