def contourf_latday(var,
is_precip=False,
clev=None,
cticks=None,
climits=None,
nc_pref=40,
grp=None,
xlims=(-120, 200),
xticks=np.arange(-120, 201, 30),
ylims=(-60, 60),
yticks=np.arange(-60, 61, 20),
dlist=None,
grid=False,
ind_nm='onset',
xlabels=True):
"""Create a filled contour plot of data on latitude-day grid.
"""
var = atm.subset(var, {'lat': ylims})
vals = var.values.T
lat = atm.get_coord(var, 'lat')
days = atm.get_coord(var, 'dayrel')
if var.min() < 0:
symmetric = True
else:
symmetric = False
if is_precip:
cmap = 'PuBuGn'
extend = 'max'
else:
cmap = 'RdBu_r'
extend = 'both'
if clev == None:
cint = atm.cinterval(vals, n_pref=nc_pref, symmetric=symmetric)
clev = atm.clevels(vals, cint, symmetric=symmetric)
elif len(atm.makelist(clev)) == 1:
if is_precip:
clev = np.arange(0, 10 + clev / 2.0, clev)
else:
clev = atm.clevels(vals, clev, symmetric=symmetric)
plt.contourf(days, lat, vals, clev, cmap=cmap, extend=extend)
plt.colorbar(ticks=cticks)
plt.clim(climits)
atm.ax_lims_ticks(xlims, xticks, ylims, yticks)
plt.grid(grid)
if dlist is not None:
for d0 in dlist:
plt.axvline(d0, color='k')
if xlabels:
plt.gca().set_xticklabels(xticks)
plt.xlabel('Days Since ' + ind_nm.capitalize())
else:
plt.gca().set_xticklabels([])
if grp is not None and grp.col == 0:
plt.ylabel('Latitude')
return None
def plotyy(data1, data2=None, xname='dayrel', data1_styles=None,
y2_opts={'color' : 'r', 'alpha' : 0.6, 'linewidth' : 2},
xlims=None, xticks=None, ylims=None, yticks=None, y2_lims=None,
xlabel='', y1_label='', y2_label='', legend=False,
legend_kw={'fontsize' : 9, 'handlelength' : 2.5},
x0_axvlines=None, grid=True):
"""Plot data1 and data2 together on different y-axes."""
data1, data2 = atm.to_dataset(data1), atm.to_dataset(data2)
for nm in data1.data_vars:
if data1_styles is None:
plt.plot(data1[xname], data1[nm], label=nm)
elif isinstance(data1_styles[nm], dict):
plt.plot(data1[xname], data1[nm], label=nm, **data1_styles[nm])
else:
plt.plot(data1[xname], data1[nm], data1_styles[nm], label=nm)
atm.ax_lims_ticks(xlims, xticks, ylims, yticks)
plt.grid(grid)
if x0_axvlines is not None:
for x0 in x0_axvlines:
plt.axvline(x0, color='k')
plt.xlabel(xlabel)
plt.ylabel(y1_label)
axes = [plt.gca()]
if data2 is not None:
plt.sca(plt.gca().twinx())
for nm in data2.data_vars:
plt.plot(data2[xname], data2[nm], label=nm, **y2_opts)
if y2_lims is not None:
plt.ylim(y2_lims)
if 'linewidth' in y2_opts:
y2_opts.pop('linewidth')
atm.fmt_axlabels('y', y2_label, **y2_opts)
atm.ax_lims_ticks(xlims, xticks)
axes = axes + [plt.gca()]
if legend:
if data2 is None:
plt.legend(**legend_kw)
else:
atm.legend_2ax(axes[0], axes[1], **legend_kw)
return axes
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),
dlist=None, grid=False):
vals = var.values.T
lat = atm.get_coord(var, 'lat')
days = atm.get_coord(var, 'dayrel')
if var.min() >= 0:
cmap, extend, symmetric = 'PuBuGn', 'max', False
else:
cmap, extend, symmetric = 'RdBu_r', 'both', True
if clev == None:
cint = atm.cinterval(vals, n_pref=nc_pref, symmetric=symmetric)
clev = atm.clevels(vals, cint, symmetric=symmetric)
elif len(atm.makelist(clev)) == 1:
if var.name == 'PREC':
clev = np.arange(0, 10 + clev/2.0, clev)
else:
clev = atm.clevels(vals, clev, symmetric=symmetric)
cticks_dict = {'PRECTOT' : np.arange(0, 13, 2),
'PREC' : np.arange(0, 11, 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)
atm.ax_lims_ticks(xlims, xticks, ylims, yticks)
plt.grid(grid)
plt.title(title)
if dlist is not None:
for d0 in dlist:
plt.axvline(d0, 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 plot_index_years(index, nrow=3, ncol=4,
fig_kw={'figsize' : (11, 7), 'sharex' : True,
'sharey' : True},
gridspec_kw={'left' : 0.1, 'right' : 0.95, 'wspace' : 0.05,
'hspace' : 0.1},
incl_fit=False, suptitle='', xlabel='Day', ylabel='Index',
xlims=None, ylims=None, xticks=np.arange(0, 401, 100),
grid=True):
"""Plot daily timeseries of monsoon onset/retreat index each year.
"""
years = atm.get_coord(index, 'year')
days = atm.get_coord(index, 'day')
grp = atm.FigGroup(nrow, ncol, fig_kw=fig_kw, gridspec_kw=gridspec_kw,
suptitle=suptitle)
for year in years:
grp.next()
ind = atm.subset(index, {'year' : (year, year)}, squeeze=True)
ts = ind['tseries']
d0_list = [ind['onset'], ind['retreat']]
plt.plot(days, ts, 'k')
for d0 in d0_list:
plt.axvline(d0, color='k')
if incl_fit and 'tseries_fit_onset' in ind:
plt.plot(days, ind['tseries_fit_onset'], 'r')
if incl_fit and 'tseries_fit_retreat' in ind:
plt.plot(days, ind['tseries_fit_retreat'], 'b')
atm.text(year, (0.05, 0.9))
atm.ax_lims_ticks(xlims=xlims, ylims=ylims, xticks=xticks)
plt.grid(grid)
if grp.row == grp.nrow - 1:
plt.xlabel(xlabel)
if grp.col == 0:
plt.ylabel(ylabel)
return grp
