def plotVS_interest_for_all_cases(dsets, diff_dsets, interest = 'FLNT',
left_ylim = None,
right_ylim = None,
linestyles = None):
vspairs = [[p.strip() for p in diff_case.split('-')]
for diff_case in sorted(diff_dsets.keys())]
Nplots = len(vspairs)
fig, axes = plt.subplots(figsize = (11, 3 * Nplots + 2.5), dpi = 300,
nrows = Nplots, ncols = 1)
handles, labels = [], []
for ax, vspair in zip([axes] if Nplots == 1 else axes, vspairs):
x, y = vspair
for model in vspair:
ax = plot_DataArray(ax, dsets[model][interest],
label = '{}'.format(model),
colour = linestyles[model]['colour'],
linestyle = linestyles[model]['linestyle'],
marker = '',
ylabel = interest, ylim = left_ylim)
da = diff_dsets[' - '.join(vspair)][interest]
diff_colour = (0.929, 0.329, 0.972)
ax2 = ax.twinx()
ax2 = plot_DataArray(ax2, da, label = 'difference',
title = '',
colour = diff_colour, linestyle = '-', marker = '',
ylim = right_ylim)
ax2.set_ylabel('')
[label.set_color(diff_colour)
for label in ax2.yaxis.get_ticklabels()]
### background shading for daytime and nighttime
ax2 = daytime_nighttime_shading(ax2, da.coords['time'].to_pandas().index,
hour_daystart = 6, hour_nightstart = 18)
## collect handles and labels for legend later
handles1, labels1 = ax.get_legend_handles_labels()
handles2, labels2 = ax2.get_legend_handles_labels()
handles.extend(handles1 + handles2)
labels.extend(labels1 + labels2)
## Make 1 legend for whole figure
uhandles, ulabels = misc.any_unique_labels(handles, labels)
uhandles, ulabels = zip(*sorted(zip(uhandles, ulabels),
key = lambda x: x[1]))
fig.suptitle(da.attrs['long_name'])
fig.legend(uhandles, ulabels,
loc = 'center', ncol = 3,
bbox_to_anchor = (.45, .91), prop = {'size': 12})
plt.subplots_adjust(wspace = 0., top = .84, bottom = .15)
return fig
def plotVS_timeaveraged_interest_for_all_cases(d3sets, diff_d3sets,
interest = 'CLOUD',
xscale = 'linear',
bot_xlim = None, bot_xlabels_rotate = 0.,
top_xlim = None, top_xlabels_rotate = 0.,
yscale = 'linear', ylim = None,
linestyles = None):
vspairs = [[p.strip() for p in diff_case.split('-')]
for diff_case in sorted(diff_d3sets.keys())]
Nplots = len(vspairs)
fig, axes = plt.subplots(figsize = (9, 9), dpi = 300,
nrows = 1, ncols = Nplots,
sharey = True)
labels, handles = [], []
axes.invert_yaxis() if Nplots ==1 else axes[0].invert_yaxis()
for ax, vspair in zip([axes] if Nplots == 1 else axes, vspairs):
x, y = vspair
for model in vspair:
if interest in ['AREI', 'AREL']:
da = dates.average_over_time(d3sets[model][interest], key = lambda x: x > 0)
else:
da = dates.average_over_time(d3sets[model][interest])
# plot each member in the comparison pair
ax = plot_vertical_profile(ax, da,
label = '{}'.format(model),
colour = linestyles[model]['colour'],
linestyle = linestyles[model]['linestyle'],
xscale = xscale, xlabels_rotate = bot_xlabels_rotate,
yscale = yscale,
xlim = bot_xlim)
ax = axes_beyond_ticks(ax, which = 'x')
# plot difference on twiny
diff_colour = (0.929, 0.329, 0.972)
ax2 = ax.twiny()
da = dates.average_over_time(diff_d3sets[' - '.join(vspair)][interest])
ax2 = plot_vertical_profile(ax2, da,
label = 'difference',
colour = diff_colour, linestyle = '-',
xscale = xscale, xlabels_rotate = top_xlabels_rotate,
yscale = yscale,
xlim = top_xlim)
[ticklabel.set_color(diff_colour) for ticklabel in ax2.xaxis.get_ticklabels()]
ax2 = axes_beyond_ticks(ax2, which = 'x')
ax2.axvline(x = 0, color = 'r', alpha = .5)
handles1, labels1 = ax.get_legend_handles_labels()
handles2, labels2 = ax.get_legend_handles_labels()
handles.extend(handles1 + handles2)
labels.extend(labels1 + labels2)
## Make 1 legend for whole figure
uhandles, ulabels = misc.any_unique_labels(handles, labels)
uhandles, ulabels = zip(*sorted(zip(uhandles, ulabels), key = lambda x: x[1]))
fig.legend(uhandles, ulabels,
loc = 'center', ncol = 3,
bbox_to_anchor = (.35, .91), prop = {'size': 14})
fig.suptitle(da.attrs['long_name'])
plt.figtext(x = 0.02, y = .5, s = 'lev [mbar]', rotation = 90.)
plt.figtext(x = .45, y = 0.08, s = '{} [{}]'.format(interest, da.units))
plt.figtext(x = .7, y = .91, s = 'difference')
if hasattr(ax2, 'xaxis_pow'):
plt.figtext(x = .9, y = 0.08, s = '1e{}'.format(- ax.xaxis_pow))
plt.figtext(x = .9, y = .91, s = '1e{}'.format(- ax2.xaxis_pow))
plt.subplots_adjust(wspace = 0., top = .84, bottom = .15)
return fig
