def contourf_latday(var, clev=None, title='', nc_pref=40, grp=None,
xlims=(-120, 200), xticks=np.arange(-120, 201, 30),
ylims=(-60, 60), yticks=np.arange(-60, 61, 20),
ssn_length=None):
vals = var.values.T
lat = atm.get_coord(var, 'lat')
days = atm.get_coord(var, 'dayrel')
if var.name.lower() == 'precip':
cmap = 'hot_r'
extend = 'max'
else:
cmap = 'RdBu_r'
extend = 'both'
if clev == None:
symmetric = atm.symm_colors(vals)
cint = atm.cinterval(vals, n_pref=nc_pref, symmetric=symmetric)
clev = atm.clevels(vals, cint, symmetric=symmetric)
cticks_dict = {'precip' : np.arange(0, 13, 2),
'T200' : np.arange(-208, 227, 2),
'U200' : np.arange(-60, 61, 10),
'PSI500' : np.arange(-800, 801, 200)}
cticks = cticks_dict.get(var.name)
plt.contourf(days, lat, vals, clev, cmap=cmap, extend=extend)
plt.colorbar(ticks=cticks)
fmt_axes(xlims, xticks, ylims, yticks)
plt.grid()
plt.title(title)
plt.axvline(0, color='k')
if ssn_length is not None:
plt.axvline(ssn_length, color='k')
if grp is not None and grp.row == grp.ncol - 1:
plt.xlabel('Rel Day')
if grp is not None and grp.col == 0:
plt.ylabel('Latitude')
def contourf_lat_time(lat, days, plotdata, clev=None, title='', cmap='RdBu_r',
onset_nm='', zero_line=False, ax=None):
if ax is None:
ax = plt.gca()
vals = plotdata.values.T
vals = np.ma.array(vals, mask=np.isnan(vals))
ncont = 40
symmetric = atm.symm_colors(plotdata)
if clev == None:
cint = atm.cinterval(vals, n_pref=ncont, symmetric=symmetric)
clev = atm.clevels(vals, cint, symmetric=symmetric)
cf = ax.contourf(days, lat, vals, clev, cmap=cmap)
plt.colorbar(mappable=cf, ax=ax)
#plot_colorbar(symmetric, ax=ax, mappable=cf)
if symmetric and zero_line:
ax.contour(days, lat, vals, [0], colors='k')
ax.grid(True)
ax.set_ylabel('Latitude')
ax.set_xlabel('Day Relative to %s Onset' % onset_nm)
ax.set_title(title)
xmin, xmax = ax.get_xlim()
if xmax > 60:
ax.set_xticks(range(int(xmin), int(xmax) + 1, 30))
plt.draw()
cmin = -cmax
else:
cmin, cmax = climits[varnm][0], climits[varnm][1]
# Lat-lon maps of composites
for j, key in enumerate(keys):
grp.next()
if comp_attrs[key]['axis'] == 1:
cmap = get_colormap(varnm, anom_plot)
else:
cmap = 'RdBu_r'
atm.pcolor_latlon(dat[key], axlims=axlims, cmap=cmap, fancy=False)
plt.xticks(range(40, 121, 20))
if comp_attrs[key]['axis'] == 1:
plt.clim(cmin, cmax)
else:
symmetric = atm.symm_colors(dat[key])
if symmetric:
cmax = np.nanmax(abs(dat[key]))
plt.clim(-cmax, cmax)
plt.title(varstr + ' ' + key.upper(), fontsize=11)
if grp.col > 0:
plt.gca().set_yticklabels([])
if grp.row < nrow - 1:
plt.gca().set_xticklabels([])
# Line plots of sector averages
grp.next()
if varnm == 'precip':
legend_opts['loc'] = 'upper center'
else:
legend_opts['loc'] = 'lower center'
title = '%s %d-%dE' % (varstr, lon1, lon2)
