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
plt_da.drop(drop_coords).groupby('time.hour').mean().plot(x='hour',yscale='log', ylim=[3,500], label=case_name, norm=mcolors.LogNorm(vmin=10,vmax=8e3), cmap='Reds')
# %%
from sectional_v2.util.plot.colors import get_case_col#(case)
# %%
import matplotlib.colors as mcolors
st = '2008-03-01'
et = '2008-06-01'
cmap='viridis'
var = 'NCONC01'
fig, axs = plt.subplots(1, figsize=[8,5], sharex=True)
for i in np.arange(len(stations)):
for case_name in cases_sec + cases_orig:
col = get_case_col(case_name)
ax = axs#[0]
plt_ds = dic_sd[case_name]
#['dNdlogD_mod']+dic_sd[case_name]['dNdlogD_sec'])
plt_ds = plt_ds.sel(time=slice(st,et)).isel(station=i, lev=-1)
plt_da = plt_ds[var]# + plt_ds['dNdlogD_sec']
plt_da = plt_da.groupby('time.hour').median()#.median('station')
plt_da.plot( yscale='log', c =col, label='_nolegend_', alpha=0.2)#, linewidth=0.2)#x='hour')#, yscale='log', ylim=[3,500], , norm=mcolors.LogNorm(vmin=10,vmax=8e3), cmap=cmap, ax=ax)
#ax.set_title(f'{case_name}, {stations[i]}')
for case_name in cases_sec + cases_orig:
col = get_case_col(case_name)
ax = axs#[0]
plt_ds = dic_sd[case_name]
#['dNdlogD_mod']+dic_sd[case_name]['dNdlogD_sec'])
plt_ds = plt_ds.sel(time=slice(st,et)).isel( lev=-1)
plt_da = plt_ds[var]# + plt_ds['dNdlogD_sec']
plot_grid(dic_finish, subs='AUT', ylim=[0, 8e3])
# %%
from sectional_v2.constants import collocate_locations
station = 'ASP'
colors_source = get_cmap_dic(dic_finish.keys())
colors_source['EUSAAR'] = 'k'
for station in dic_finish[cases[0]].coords['station'].values:
fig, axs = plt.subplots(2, 2)
seasons = ['SPR', 'SUM', 'AUT', 'WIN']
for seas, ax in zip(seasons, axs.flatten()):
for key in dic_finish.keys():
plt_median_perc(dic_clean[key]['dNdlog10dp'],
station,
key,
color=get_case_col(key),
ax=ax,
subs=seas,
percs=[16, 84],
yscale='log',
ylim=[10, 1e4])
ax.set_title(station + ', ' + seas)
plt.legend()
plt.show()
# %%
from sectional_v2.constants import collocate_locations
station = 'ASP'
colors_source = get_cmap_dic(dic_finish.keys())
colors_source['EUSAAR'] = 'k'
for station in dic_finish[cases[0]].coords['station'].values:
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()
# %%
plot_grid(dic_finish,subs = 'AUT', ylim=[0,8e3])
# %%
# %%
from sectional_v2.constants import collocate_locations
station='ASP'
colors_source = get_cmap_dic(dic_finish.keys())
colors_source['EUSAAR']='k'
for station in dic_finish[cases[0]].coords['station'].values:
fig, axs = plt.subplots(2,2)
seasons = ['SPR', 'SUM','AUT','WIN']
for seas, ax in zip(seasons, axs.flatten()):
for key in dic_finish.keys():
plt_median_perc(dic_finish[key]['dNdlog10dp'], station, key,
color=get_case_col(key),
ax=ax,
subs=seas, percs=[16,84], yscale='log', ylim=[10,1e4])
ax.set_title(station+', '+ seas)
plt.legend()
plt.show()
# %%
from sectional_v2.constants import collocate_locations
station='ASP'
colors_source = get_cmap_dic(dic_finish.keys())
colors_source['EUSAAR']='k'
for station in dic_finish[cases[0]].coords['station'].values:
fig, axs = plt.subplots(2,2)
seasons = ['SPR', 'SUM','AUT','WIN']