def dataset_savepath_var(self, var_name, case_name, model_name):
"""
Returns filename of dataset
:param var_name:
:param case_name:
:param model_name:
:return:
"""
fn = self.coll_mod.savepath_coll_ds(
var_name
) #(out_varn, self.model_name, self.case_name, self.from_time, self.to_time)
make_folders(fn)
return fn
outpaths['levlat_means'] = path_outdata + '/means/levlat_means/'
outpaths['profile_means'] = path_outdata + '/means/profile_means/'
outpaths['sizedistrib_files'] = path_outdata + '/sizedistrib_files'
outpaths['collocated'] = path_outdata + '/collocated_ds/'
outpaths['eusaar'] = path_outdata + '/eusaar/'
def get_outdata_path(key):
if key in outpaths:
return outpaths[key]
else:
print('WARNING: key not found in outpaths, constants.py')
return path_outdata + '/' + key
make_folders(path_outdata)
# data info
path_data_info = project_base_path + 'OAS-DEV/oas_dev/data_info/'
# output locations:
locations = [
'LON_116e_LAT_40n', 'LON_24e_LAT_62n', 'LON_63w_LAT_3s', 'LON_13e_LAT_51n'
]
path_locations_file = path_data_info + 'locations.csv'
if os.path.isfile(path_locations_file):
collocate_locations = pd.read_csv(path_locations_file, index_col=0)
else:
_dic = dict(Hyytiala={
'lat': 61.51,
df_merged = pd.merge(df_obs_time.reset_index(), df_mod_time, how='outer')
df_merged
# %% [markdown]
# ## Construnc N30-100 and N50-100
# Mark that N50=N50-500 and N100=N100-500, so
# $$N_{50-100}=N_{50}-N_{100}$$
# %%
df_merged['N30-100'] = df_merged['N30-50']+ df_merged['N50']-df_merged['N100']
df_merged['N50-100'] =df_merged['N50']-df_merged['N100']
# %%
from useful_scit.util.make_folders import make_folders
make_folders(file_out)
df_merged.to_csv(file_out)
# %%
df_merged
# %%
df_merged['source'].unique()
# %%
df_merged#[df_merged['source']=='SECTv11_ctrl_fbvoc']#.unique()
# %%
# %%
if os.path.isfile(fn) and not reload:
ds = xr.open_dataset(fn)
#print(f'found contants file {fn}')
return ds
from_time = '1900-01'
to_time = '2100-02'
fl = filelist_NorESM(case, path, from_time, to_time, model)
file = fl[0]
ds = xr.open_dataset(file)
drop_l = list(set(ds.data_vars) - set(include)) + ['PS']
ds = ds.drop_vars(drop_l) # [include]
ds = xr_fix(ds)
ds = ds.isel(time=0)
ds.squeeze()
make_folders(fn)
ds.to_netcdf(fn)
return ds
def get_vars_for_computed_vars(varNames, model):
"""
Terribly formatted function for adding needed fields to varlist for my self defined variables.
:param varNames:
:param model:
:return:
"""
varnames_mod = []
if model == 'NorESM':
for var in varNames:
if 'SW_rest_Ghan' == var:
case,
from_t,
to_t, [minDiameter, maxDiameter],
False,
time_resolution,
history_field=history_field)
ds_conc = s.get_collocated_dataset()
dic_mod_all[case] = ds_conc
dic_orig[case] = ds_conc #redo=True)
dic_sized[case] = s
# %%
from useful_scit.util.make_folders import make_folders
from dask.diagnostics import ProgressBar
make_folders(path_tmp)
for case in cases_loaded:
ds_case = dic_mod_all[case]
for station in ds_case['station'].values:
fn = get_fn_tmp_station(case, station, from_t, to_t)
ds_ca_st = ds_case.sel(station=station)
#fn = path_tmp + '%s_concat_dNdlogDs.nc'%case
delayed_obj = ds_ca_st.to_netcdf(fn, compute=False)
with ProgressBar():
results = delayed_obj.compute()
dic_mod_all[case].close()
# %%
make_folders(path_tmp)
for case in cases_loaded:
fn = get_fn_tmp(case, from_t, to_t)
#fn = path_tmp + '%s_concat_dNdlogDs.nc'%case
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()