from vacumm.config import data_sample
f = cdms2.open(data_sample('mars3d.t.nc'))
xe = f('xe')
f.close()
xe.long_name = 'Original'
# On crée des trous
# - petits
xe[:4] = MV2.masked
xe[12:16] = MV2.masked
# - gros
xe[40:46] = MV2.masked
# On rempli les petits trous (5 heures max) par interpolation cubique
from vacumm.misc.grid.regridding import fill1d
import time
t0 = time.time()
xef = fill1d(xe, method='cubic', maxgap=5)
print time.time() - t0
xef.long_name = 'Rempli'
xef[:] += xef.max() / 5. # on décalle pour les plots
# Plots
from vacumm.misc.plot import curve2, P, savefigs
P.rc('font', size=9)
curve2(xe, show=False, linewidth=1.5, figsize=(6, 3), top=.88, bottom=.15)
curve2(xef, show=False, linewidth=1.5, title='Niveau de la mer')
P.legend()
savefigs(__file__, pdf=True)
P.close()
kwhov.update(cmap=cmap_jets(stretch=-.4), colorbar=False, xrotation=25.)
kwcurve = dict(kwplot)
kwcurve.update(transpose=True, color='r', yhide=True)
kwplot.update(order='-d', title=True)
kwhov['date_fmt'] = '%Hh'
# - original
#print xe.getTime().asComponentTime()
hov2(xe,
subplot=421,
top=.95,
hspace=.45,
figsize=(5.5, 8),
bottom=.06,
**kwhov)
axlims = P.axis()
curve2(xe[:, 15], 'o', subplot=422, **kwcurve)
xscale(1.1, keep_min=1)
# - nearest
hov2(xe_nea, subplot=423, **kwhov)
P.axis(axlims)
curve2(xe[:, 15], 'o', subplot=424, **kwcurve)
print 'ok'
curve2(xe_nea[:, 15], **kwplot)
xscale(1.1, keep_min=1)
# - linear
hov2(xe_lin, subplot=425, **kwhov)
P.axis(axlims)
curve2(xe[:, 15], 'o', subplot=426, **kwcurve)
curve2(xe_lin[:, 15], **kwplot)
xscale(1.1, keep_min=1)
# - cubic
# -*- coding: utf8 -*-
import cdms2
from vacumm.misc.plot import curve2
from vacumm.config import data_sample
# Trace de la moyenne spatiale
# - lecture
f = cdms2.open(data_sample('mars3d.t.nc'))
tsst = f('temp')
f.close()
# - plot
c = curve2(tsst, title=u'Série temporelle de SST',units = r'$^{\circ}C$',
subplot=211, show=False, )
# Trace de la moyenne meridienne
# - lecture
f = cdms2.open(data_sample('mars3d.xy.nc'))
zsst = cdms2.MV2.average(f('temp'), axis=0)
f.close()
# - plot
curve2(zsst, title=u'SST zonale', color='r', show=False,
subplot=212,top=.9,hspace=.4,left=.15,bottom=.07,
savefigs=__file__)
# -*- coding: utf8 -*-
import cdms2
from vacumm.misc.plot import curve2
from vacumm.config import data_sample
# Trace de la moyenne spatiale
# - lecture
f = cdms2.open(data_sample('mars3d.t.nc'))
tsst = f('temp')
f.close()
# - plot
c = curve2(
tsst,
title=u'Série temporelle de SST',
units=r'$^{\circ}C$',
subplot=211,
show=False,
)
# Trace de la moyenne meridienne
# - lecture
f = cdms2.open(data_sample('mars3d.xy.nc'))
zsst = cdms2.MV2.average(f('temp'), axis=0)
f.close()
# - plot
curve2(zsst,
title=u'SST zonale',
color='r',
show=False,
close=True,
subplot=212,
xy *= 1e-3
else:
units = 'm'
taxis = cdms2.createAxis(xy)
taxis.units = units
taxis.long_name = 'Distance'
tbathy.setAxis(0, taxis)
# Plot
c = curve2(tbathy,
'k',
bgcolor=(.95, .95, 1),
order='d-',
show=False,
yfmt='%gm',
yunits=False,
bottom=0.12,
zorder=10,
figsize=eval(options.figsize),
title=options.title,
ymin=options.zmin,
ymax=options.zmax)
xylims = c.axes.axis()
xx = c.get_xdata(scalar=0)
yy = c.get_ydata(scalar=0)
if xylims[2] < 0.: # ocean
# c.axes.axhspan(xylims[2], 0, color=(.8, .8, 1), zorder=2, linewidth=0)
c.axes.imshow(
N.resize(N.arange(256), (2, 256)).T,
cmap=cmap_custom([((.3, 0, .5), 0), ('#000055', .2), ('#007da9', .7),
('#7cbed3', 1)]), #'ocean',
taxis = create_lat(lats)
else:
xy = N.sqrt((xx-xx[0])**2+(yy-yy[0])**2)
if xy.max()-xy.min()>2500 or options.along=='km':
units = 'km'
xy *= 1e-3
else:
units = 'm'
taxis = cdms2.createAxis(xy)
taxis.units = units
taxis.long_name = 'Distance'
tbathy.setAxis(0, taxis)
# Plot
c = curve2(tbathy, 'k', bgcolor=(.95, .95, 1), order='d-',
show=False, yfmt='%gm', yunits=False, bottom=0.12, zorder=10,
figsize=eval(options.figsize), title=options.title, ymin=options.zmin, ymax=options.zmax)
xylims = c.axes.axis()
xx = c.get_xdata(scalar=0)
yy = c.get_ydata(scalar=0)
if xylims[2]<0.: # ocean
# c.axes.axhspan(xylims[2], 0, color=(.8, .8, 1), zorder=2, linewidth=0)
c.axes.imshow(N.resize(N.arange(256), (2,256)).T,
cmap=cmap_custom([((.3,0,.5),0), ('#000055', .2), ('#007da9', .7), ('#7cbed3',1)]),#'ocean',
extent=[xylims[0], xylims[1], 0., tbathy.min()], aspect='auto')
c.axes.fill_between(xx, yy, xylims[2], color='.5', zorder=9, linewidth=0) # earth
c.axes.axhline(zorder=8, color='b', linewidth=.8) # sea surface
if options.map:
m = minimap((lons, lats), zoom=1./options.mapscale)
xm, ym = m(lons, lats)
m.axes.plot(xm, ym, color='r')
colors[MV2.sqrt(u**2+v**2).filled(0.)>5.] = '#ff0000' # red if modulus > 4.
qv = stick2(u, v, color=colors.tolist(), xticklabels=False, subplot=211,
shadow=True, right=.85, hspace=.2, left=.14, hldays=True,
key=1, key_size=11, key_color='.3', ylabel_color='r', units=r'$m.s^{-1}$',
mod=True, mod_color='.4', mod_linewidth=2, title='Wind', quiver_scale = 50.,
quiver_headwidth=3,quiver_headlength=3,quiver_headaxislength=2,
quiverkey_pos=(.05, 1.05), quiverkey_color='k',
quiver_width=.006, alpha=.8, show=False)
qv.add_text(1.01, 1, 'North', va='top', size=11, fontweight='heavy')
qv.add_text(1.01, 0, 'South', va='bottom', size=11, fontweight='heavy')
# - precipitations
dr = r.clone() # variation != accumulation
dr[:-1] = N.diff(r) ; dr[-1] = r[-1]-r[-2]
lr = bar2(dr, width=.8, subplot=212, hldays=True,
long_name='Precipitations', shadow=True, ylabel = '%(long_name)s [$%(units)s$]',
title=False, dayhl=True, ylabel_color='#008888',zorder=100,
key=2, key_size=11, key_color='.3', log=True, ymin=0.01,
color='#00ffff', linewidth=.2, edgecolor='#888888', show=False)
lr.axes.yaxis.grid(False)
# - pression
p[:] /= 100.
lp = curve2(p, color='g', vminmax=1015, ymaxmin=1025, twin='x',
zorder=150, title=False, ylabel = '%(long_name)s [$%(units)s$]',
ylabel_color='g', shadow=True, show=False)
lp.savefigs(__file__, pdf=True)
# - basse résolution
lon_lr = create_lon((lon.min()+dlon*.7, lon.max()+dlon, dlon*3.3))
# - haute résolution
lon_hr = create_lon((lon.min()+dlon, lon.max()+dlon, dlon/3.3))
# - dict
lons = dict(haute=lon_hr, basse=lon_lr)
# Regrillages et plots
from matplotlib import rcParams ; rcParams['font.size'] = 9
from vacumm.misc.grid.regridding import regrid1d
from vacumm.misc.plot import curve2,savefigs, yscale ; import pylab as P
P.figure(figsize=(5.5, 6))
kwplot = dict(show=False,vmin=v.min(),vmax=v.max(),alpha=.7)
for ilh,resdst in enumerate(['basse', 'haute']):
# Regrillage
vlinear = regrid1d(v, lons[resdst], 'linear')
vremap = regrid1d(v, lons[resdst], 'cellave')
# Plots
P.subplot(2, 1, ilh+1)
curve2(v, 'o', markersize=4, color='k', label=u'Original', hspace=.3, **kwplot)
curve2(vremap, 'o', markersize=2, label=u'Cellave', linewidth=1.2, color='b', **kwplot)
curve2(vlinear, 'o', markersize=2, label=u'Linear', linewidth=1.2, color='r', **kwplot)
yscale(1.1)
P.title(u'Vers la %s resolution'%resdst)
if not ilh: P.legend(loc='lower left').legendPatch.set_alpha(.6)
savefigs(__file__, pdf=True)
# Lecture du niveau de la mer horaire
import cdms2, MV2
from vacumm.config import data_sample
f =cdms2.open(data_sample('mars3d.t.nc'))
xe = f('xe')
f.close()
xe.long_name = 'Original'
# On crée des trous
# - petits
xe[:4] = MV2.masked
xe[12:16] = MV2.masked
# - gros
xe[40:46] = MV2.masked
# On rempli les petits trous (5 heures max) par interpolation cubique
from vacumm.misc.grid.regridding import fill1d
import time ; t0=time.time()
xef = fill1d(xe, method='cubic', maxgap=5)
print time.time()-t0
xef.long_name = 'Rempli'
xef[:] += xef.max()/5. # on décalle pour les plots
# Plots
from vacumm.misc.plot import curve2, P, savefigs
P.rc('font', size=9)
curve2(xe, show=False, linewidth=1.5, figsize=(6, 3), top=.88, bottom=.15)
curve2(xef, show=False, linewidth=1.5, title='Niveau de la mer')
P.legend()
savefigs(__file__, pdf=True)
from vacumm.misc.plot import yhide, xscale, savefigs, hov2, curve2 from vacumm.misc.color import cmap_jets from genutil import minmax vmin, vmax = minmax(xe, xe_lin) kwplot = dict(vmin=vmin, vmax=vmax, show=False) kwhov = dict(kwplot) kwhov.update(cmap=cmap_jets(stretch=-.4), colorbar=False, xrotation=25.) kwcurve = dict(kwplot) kwcurve.update(transpose=True, color='r', yhide=True) kwplot.update(order = '-d', title=True) kwhov['date_fmt'] = '%Hh' # - original #print xe.getTime().asComponentTime() hov2(xe, subplot=421, top=.95, hspace=.45, figsize=(5.5, 8), bottom=.06, **kwhov) axlims = P.axis() curve2(xe[:, 15], 'o', subplot=422, **kwcurve) xscale(1.1, keep_min=1) # - nearest hov2(xe_nea, subplot=423, **kwhov) P.axis(axlims) curve2(xe[:, 15], 'o', subplot=424, **kwcurve) print 'ok' curve2(xe_nea[:, 15], **kwplot) xscale(1.1, keep_min=1) # - linear hov2(xe_lin, subplot=425, **kwhov) P.axis(axlims) curve2(xe[:, 15], 'o', subplot=426, **kwcurve) curve2(xe_lin[:, 15], **kwplot) xscale(1.1, keep_min=1) # - cubic
lon_lr = create_lon((lon.min()+dlon*.7, lon.max()+dlon, dlon*3.3))
# - haute résolution
lon_hr = create_lon((lon.min()+dlon, lon.max()+dlon, dlon/3.3))
# - dict
lons = dict(haute=lon_hr, basse=lon_lr)
# Regrillages et plots
from matplotlib import rcParams ; rcParams['font.size'] = 9
from vacumm.misc.grid.regridding import regrid1d
from vacumm.misc.plot import curve2,savefigs, yscale ; import pylab as P
P.figure(figsize=(5.5, 6))
kwplot = dict(show=False,vmin=v.min(),vmax=v.max(),alpha=.7)
for ilh,resdst in enumerate(['basse', 'haute']):
# Regrillage
vlinear = regrid1d(v, lons[resdst], 'linear')
vremap = regrid1d(v, lons[resdst], 'cellave')
# Plots
P.subplot(2, 1, ilh+1)
curve2(v, 'o', markersize=4, color='k', label=u'Original', hspace=.3, **kwplot)
curve2(vremap, 'o', markersize=2, label=u'Cellave', linewidth=1.2, color='b', **kwplot)
curve2(vlinear, 'o', markersize=2, label=u'Linear', linewidth=1.2, color='r', **kwplot)
yscale(1.1)
P.title(u'Vers la %s resolution'%resdst)
if not ilh: P.legend(loc='lower left').legendPatch.set_alpha(.6)
savefigs(__file__, pdf=True)
P.close()
