fig, axes = plt.subplots(nrows=2, ncols=4,figsize=(19,13))
fig.patch.set_facecolor('white')
count = 0
for ax in axes.flat:
try:
area = areas[count]
except:
ax.axis('off')
continue
area = areas[count]
area_grid = area_boundaries[area]
area_tag = area_tags[area]
area_label = area_labels[area]
cut_test = modules.area_cut(area,lats,lons,tags,area_grid,area_tag)
cut_refs = refs[cut_test]
y_array = np.average(pressures[cut_test,:],axis=0)
print obs_seasonal_waveforms.shape
obs_seasonal_waveform_cut = obs_seasonal_waveforms[cut_test,:,:]
obs_seasonal_amp_cut = obs_seasonal_amplitudes[cut_test,:]
obs_seasonal_ph_cut = obs_seasonal_phases[cut_test,:]
model_seasonal_waveform_cut = model_seasonal_waveforms[cut_test,:,:]
model_seasonal_amp_cut = model_seasonal_amplitudes[cut_test,:]
model_seasonal_ph_cut = model_seasonal_phases[cut_test,:]
print obs_seasonal_waveform_cut.shape
print len(cut_refs)
obs_no2_data = obs_no2_data[:,start_obs_ind:end_obs_ind]
for ax in axes.flat:
try:
area = areas[count]
except:
ax.axis('off')
continue
area_grid = area_boundaries[area]
area_tag = area_tags[area]
area_label = area_labels[area]
print area
cut_test_o3 = modules.area_cut(area,obs_o3_lats,obs_o3_lons,obs_o3_tags,area_grid,area_tag)
cut_test_no2 = modules.area_cut(area,obs_no2_lats,obs_no2_lons,obs_no2_tags,area_grid,area_tag)
cut_test_co = modules.area_cut(area,obs_co_lats,obs_co_lons,obs_co_tags,area_grid,area_tag)
obs_o3_cut = obs_o3_data[cut_test_o3,:]
obs_no2_cut = obs_no2_data[cut_test_no2,:]
obs_co_cut = obs_co_data[cut_test_co,:]
print obs_o3_cut.shape
print obs_no2_cut.shape
print obs_co_cut.shape
if obs_o3_cut.shape[0] == 0:
count+=1
continue
if obs_no2_cut.shape[0] == 0:
fig.patch.set_facecolor('white')
count = 0
for ax in axes.flat:
try:
area = areas[count]
except:
ax.axis('off')
continue
print area
area_grid = area_boundaries[area]
area_tag = area_tags[area]
area_label = area_labels[area]
cut_test = modules.area_cut(area, obs_lats, obs_lons, tags, area_grid,
area_tag)
obs_d_w = np.nanmean(obs_daily_waveforms[cut_test, :], axis=0)
obs_s_w = np.nanmean(obs_seasonal_waveforms[cut_test, :], axis=0)
model_d_w = np.nanmean(model_daily_waveforms[cut_test, :], axis=0)
model_s_w = np.nanmean(model_seasonal_waveforms[cut_test, :], axis=0)
if plot_type == 'd':
ave_obs_waveform = obs_d_w
ave_model_waveform = model_d_w
if plot_type == 's':
ave_obs_waveform = obs_s_w
ave_model_waveform = model_s_w
if ave_or_no == 'n':
obs_no2_data = obs_no2_data[:, start_obs_ind:end_obs_ind]
for ax in axes.flat:
try:
area = areas[count]
except:
ax.axis('off')
continue
area_grid = area_boundaries[area]
area_tag = area_tags[area]
area_label = area_labels[area]
print area
cut_test_o3 = modules.area_cut(area, obs_o3_lats, obs_o3_lons, obs_o3_tags,
area_grid, area_tag)
cut_test_no2 = modules.area_cut(area, obs_no2_lats, obs_no2_lons,
obs_no2_tags, area_grid, area_tag)
cut_test_co = modules.area_cut(area, obs_co_lats, obs_co_lons, obs_co_tags,
area_grid, area_tag)
obs_o3_cut = obs_o3_data[cut_test_o3, :]
obs_no2_cut = obs_no2_data[cut_test_no2, :]
obs_co_cut = obs_co_data[cut_test_co, :]
print obs_o3_cut.shape
print obs_no2_cut.shape
print obs_co_cut.shape
if obs_o3_cut.shape[0] == 0:
count += 1
#count = 0
#for ax in axes.flat:
#try:
#area = areas[count]
#except:
#ax.axis('off')
#continue
count = 0
for area in areas:
print area
area_grid = area_boundaries[area]
area_country = area_countries[area]
area_label = area_labels[area]
cut_test = modules.area_cut(area,obs_lats,obs_lons,tags,area_grid,obs_country,area_country,obs_refs)
print len(obs_daily_waveform[cut_test,:])
obs_d_w = np.nanmean(obs_daily_waveform[cut_test,:],axis=0)
obs_s_w = np.nanmean(obs_seasonal_waveform[cut_test,:],axis=0)
if plot_type == 'd':
ave_obs_waveform = obs_d_w
max_ph = np.argmax(ave_obs_waveform)
max_amp = (np.max(ave_obs_waveform) - np.min(ave_obs_waveform))/2.
ave = np.average(ave_obs_waveform)
if plot_type == 's':
ave_obs_waveform = obs_s_w
max_ph = np.argmax(ave_obs_waveform)/24.
max_amp = (np.max(ave_obs_waveform) - np.min(ave_obs_waveform))/2.
ave = np.average(ave_obs_waveform)
ax.axis('off')
continue
print area
obs_ave_o3 = []
obs_twentyfifth_o3 = []
obs_seventyfifth_o3 = []
geoschem_ave_o3 = []
geoschem_twentyfifth_o3 = []
geoschem_seventyfifth_o3 = []
area_grid = area_boundaries[area]
area_tag = area_tags[area]
area_label = area_labels[area]
cut_test_o3 = modules.area_cut(area,obs_lats_o3,obs_lons_o3,tags_o3,area_grid,area_tag)
obs_cut_o3 = obs_o3[cut_test_o3,:]
geoschem_cut_o3 = geoschem_o3[:,cut_test_o3]
n_sites_o3 = obs_cut_o3.shape[0]
print 'nsites = ',n_sites_o3
if n_sites_o3 > 0:
for m in range(len(dates_year)):
obs_area_year = []
geoschem_area_year = []
print dates_year[m]
obs_s = np.where(obs_date ==int(dates_year[m]))[0]
