Пример #1
0
from PyFuncemeClimateTools import PlotMaps as pm
from PyFuncemeClimateTools import CreateNetCDF as cn
from read_data import read_data


pcp, pcpe, obs = read_data()

nla = np.linspace(-90., 90., 181)

nlo = np.linspace(-180., 179., 360)

x, y = np.meshgrid(nlo, nla)

y1, y2, x1, x2 = -60., 15., -90., -30.

correl = cs.compute_pearson(pcp[0:30, :, :], obs[0:30, :, :])

figtitle = u'ECHAM4.6 x CMAP - {0}/{1} ({2})\nCorrelação - Precip Acum' \
           .format('JAN', 'FMA', '8110')

if not os.path.exists('figs_expsolar/map_correl'):
    os.makedirs('figs_expsolar/map_correl')

figname = 'figs_expsolar/map_correl' \
          '/bra_precip_persistida_{0}_null-{1}_null_{2}_echam46_1dg_cmap_' \
          'correlacao.png' \
          .format('8110', 'FMA', 'JAN')

levs = (-1.0, -0.9, -0.7, -0.5, -0.3, 0.3, 0.5, 0.7, 0.9, 1.0)  # 10

my_colors = ('#2372c9', '#3498ed', '#4ba7ef', '#76bbf3', '#93d3f6',
    print 'lons:', obs_lons

    outdir = '{0}{1}-{2}-rsm97'.format(fcst_month, fcst_year, hind_period)
    if not os.path.exists(outdir):
        os.makedirs(outdir)

    print " === OUTPUT DIR: {0} ===\n".format(outdir)

    # Limites do mapa para fazer o plot
    # y1, y2, x1, x2 = -40., 40., -150., 70.  # Globo
    #~ y1, y2, x1, x2 = -89., 89., -178., 178.  # Globo
    #~ y1, y2, x1, x2 = -23., 9., -75., -34.  # Região Reliability
    y1, y2, x1, x2 = -21.3, 7., -55.6, -34  # América do sul

    ###########  CORRELAÇÃO  ###########
    correl = cs.compute_pearson(hind, obs, n_years)
    figtitle = u'RSM97 x UTEXAS - {0}/{1} ({2})\nCorrelação - Precip Acum'.format(fcst_month_name, target_months, hind_period_name)
    figname = "{3}/bra_precip_persistida_{0}_null-{1}_null_{2}_rsm97_1dg_utexas_correlacao.png".format(hind_period_name, target_months, n_fcst_month, outdir)
    levs = (-1.0, -0.9, -0.7, -0.5, -0.3,
             0.3,  0.5,  0.7,  0.9,  1.0) #10
    my_colors = ('#2372c9', '#3498ed', '#4ba7ef', '#76bbf3', '#93d3f6',
                 '#b0f0f7', '#ffffff', '#fbe78a', '#ff9d37', '#ff5f26',
                 '#ff2e1b', '#ff0219', '#ae000c') #13
    pm.plotmap(correl, obs_lats-0.54/2., obs_lons-0.54/2., latsouthpoint=y1, latnorthpoint=y2,
        lonwestpoint=x1, loneastpoint=x2, fig_name=figname, barloc='right',
        barcolor=my_colors, barlevs=levs, fig_title=figtitle, barinf='neither', ocean_mask=1)
    background = Image.open(figname)
    foreground = Image.open("/home/marcelo/FSCT-ECHAM46/FUNCEME_LOGO.png")
    foreground = foreground.resize((90, 70), Image.ANTIALIAS)
    background.paste(foreground, (313, 460), foreground)
    background.save(figname, optimize=True, quality=95)
Пример #3
0
above = np.loadtxt("echam46_above.txt")
normal = np.loadtxt("echam46_normal.txt")
below = np.loadtxt("echam46_below.txt")

print "\n => Plot diagram...\n"

mytitle = "Diagrama de atributos: {2}/{1} - ({0})".format(hind_period, target_months, fcst_month)
figura, ax = plot_reliability(below[:,0], below[:,1], maintitle=mytitle, cor='blue')
figura, ax = plot_reliability(normal[:,0], normal[:,1], maintitle=mytitle, first=False, fig=figura, cor='y')
figura, ax = plot_reliability(above[:,0], above[:,1], maintitle=mytitle, first=False, fig=figura, cor='red')
name_fig = "bra_precip_persistida_{0}_null-{1}_null_{2}_echam46_1dg_cmap_reliability.png".format(hind_period, target_months, n_fcst_month)
plt.savefig(name_fig)
plt.close()


correl = cs.compute_pearson(pcp_model, pcp_obs, timelen=14.)

# correl_aux, lons_aux = shiftgrid(180., correl, lons, start=False)

figtitle = u'RSM97 x PRECL - FMA - 02-15\nPersistida - 0.54x0.54 - Correlação - Precip Acum'

figname = "correl_rsm97per_x_precl_jfm_0215.png"

levs = (-1.0, -0.9, -0.7, -0.5, -0.3,
         0.3,  0.5,  0.7,  0.9,  1.0) #10

my_colors = ('#2372c9', '#3498ed', '#4ba7ef', '#76bbf3', '#93d3f6',
             '#b0f0f7', '#ffffff', '#fbe78a', '#ff9d37', '#ff5f26',
             '#ff2e1b', '#ff0219', '#ae000c') #13

print "\n... salvando figura ..."