my_colors = ('#340003', '#ae000c', '#ff2e1b', '#ff5f26', '#ff9d37', '#fbe78a',
'#ffffff', '#b0f0f7', '#93d3f6', '#76bbf3', '#4ba7ef', '#3498ed', '#2372c9') #13
pm.plotmap(anomaly_corrigida[0, :, :], newlats-1./2., newlons-1./2., latsouthpoint=y1, latnorthpoint=y2,
lonwestpoint=x1, loneastpoint=x2, fig_name=figname_anom, barloc='right',
barcolor=my_colors, barlevs=levs, fig_title=figtitle, barinf='both', ocean_mask=1)
background = Image.open(figname_anom)
foreground = Image.open("/home/marcelo/FSCT-ECHAM46/FUNCEME_LOGO.png")
foreground = foreground.resize((90, 70), Image.ANTIALIAS)
background.paste(foreground, (334, 461), foreground)
background.save(figname_anom, optimize=True, quality=95)
########## Tercil mais provável para toda a região do globo ##########
file_out = "{5}/prob_echam46_issue_{0}{1}_target_{2}{3}_{4}_median.nc".format(fcst_month, fcst_year, target_months, target_year, hind_period, outdir)
below, normal, above, f_signal, f_std, o_pad, fcst_sig_anom = cs.compute_probability(fcst, hind, obs, n_years)
cn.create_netcdf_probs(below, normal, above, newlats, newlons, fileout=file_out)
########## Curva para o CE ##########
# Retorna matriz com os pontos sobre o Ceará
shapef = '/home/marcelo/FSCT-ECHAM46/pontos_ce.txt'
pointsgrid, lonlatgrid, mymatriz = dg.pointinside(newlats, newlons, shapefile=shapef)
# Aplica máscara para os pontos sobre o Ceará
points_over_ce_fcst = np.ma.array(fcst[0, :, :], mask=mymatriz)
points_over_ce_hind = np.ma.array(hind, mask=np.tile(mymatriz, (hind.shape[0], 1)))
points_over_ce_obs = np.ma.array(obs, mask=np.tile(mymatriz, (obs.shape[0], 1)))
mean_ce_fcst = np.zeros(1)
mean_ce_hind = np.zeros(int(n_years))
mean_ce_obs = np.zeros(int(n_years))
# tercil mais provável 2011-2016
for i, y in enumerate(xrange(2011, 2017)):
below, normal, above, f_signal, f_std, o_pad, fcst_sig_anom = \
cs.compute_probability(pcp[30 + i, :, :], pcp[0:30, :, :],
obs[0:30, :, :])
if not os.path.exists('figs_expsolar/map_tercis'):
os.makedirs('figs_expsolar/map_tercis')
file_out = 'figs_expsolar/map_tercis' \
'/prob_echam46_issue_{0}{1}_target_{2}{3}_{4}.nc' \
.format("JAN", y, "FMA", y, "8110")
cn.create_netcdf_probs(below, normal, above, nla, nlo, fileout=file_out)
figout = 'figs_expsolar/map_tercis' \
'/bra_precip_persistida_{1}_{2}-{3}_{4}_{0}' \
'_echam46_1dg_cmap_tercilmaisprovavel.png' \
.format("JAN", "8110", y, "FMA", y)
figtitle = "ECHAM4.6 - {0}/{1} - {2}/{3}\nPROB PREC (%) ({4})" \
.format("JAN", y, "FMA", y, "8110")
pm.maptercis(file_out, figtitle, figout)
os.remove(file_out)
# tercil mais provável 2011-2016 experimento
for i, y in enumerate(xrange(2011, 2017)):
