def demo_fixed_pad_axes():
fig = plt.figure(2, (6, 6))
# The first & third items are for padding and the second items are for the axes.
# sizes are in inch.
h = [
Size.Fixed(1.0),
Size.Scaled(1.),
Size.Fixed(.2),
]
v = [
Size.Fixed(0.7),
Size.Scaled(1.),
Size.Fixed(.5),
]
divider = Divider(fig, (0.0, 0.0, 1., 1.), h, v, aspect=False)
# the width and height of the rectangle is ignored.
ax = LocatableAxes(fig, divider.get_position())
ax.set_axes_locator(divider.new_locator(nx=1, ny=1))
fig.add_axes(ax)
ax.plot([1, 2, 3])
def demo_fixed_pad_axes():
fig = plt.figure(2, (6, 6))
# The first & third items are for padding and the second items are for the
# axes. Sizes are in inches.
h = [Size.Fixed(1.0), Size.Scaled(1.), Size.Fixed(.2)]
v = [Size.Fixed(0.7), Size.Scaled(1.), Size.Fixed(.5)]
divider = Divider(fig, (0.0, 0.0, 1., 1.), h, v, aspect=False)
# the width and height of the rectangle is ignored.
ax = LocatableAxes(fig, divider.get_position())
ax.set_axes_locator(divider.new_locator(nx=1, ny=1))
fig.add_axes(ax)
ax.plot([1, 2, 3])
def demo_fixed_size_axes():
fig1 = plt.figure(1, (10, 5))
# The first items are for padding and the second items are for the axes.
# sizes are in inch.
h = [Size.Fixed(1.0), Size.Fixed(7.5)]
v = [Size.Fixed(0.7), Size.Fixed(4.5)]
divider = Divider(fig1, (0.0, 0.0, 1., 1.), h, v, aspect=False)
# the width and height of the rectangle is ignored.
ax = LocatableAxes(fig1, divider.get_position())
ax.set_axes_locator(divider.new_locator(nx=1, ny=1))
fig1.add_axes(ax)
ax.plot([1, 2, 3])
def plot_variance_multi(savefile,
data,
labels,
colors,
ylabel,
ylim,
ylim_unit=1,
ylim_scale=5,
colors2=None,
hline=None,
vline=None,
locator=-1,
draw_dist=True,
subsample=1):
plt.clf()
plt.rcParams["font.size"] = 14
colors2 = colors if colors2 is None else colors2
m = len(data)
#fig, ax = plt.subplots(1, 1)
fig = plt.figure(1, figsize=(4, 4))
# The first items are for padding and the second items are for the axes.
# sizes are in inch.
h = [Size.Fixed(0.65), Size.Fixed(5.5)]
v = [Size.Fixed(0.7), Size.Fixed(4.)]
divider = Divider(fig, (0.0, 0.0, 1., 1.), h, v, aspect=False)
# the width and height of the rectangle is ignored.
ax = LocatableAxes(fig, divider.get_position())
ax.set_axes_locator(divider.new_locator(nx=1, ny=1))
fig.add_axes(ax)
if not hasattr(draw_dist, '__getitem__'):
v = draw_dist
draw_dist = [v for i in range(m)]
print(draw_dist)
for k in range(m)[::-1]:
plot_m = numpy.median(data[k], 0)
sorted = numpy.sort(data[k], 0)
n = data[k].shape[0]
T = data[k].shape[1]
t = numpy.arange(0, T)
fin = plot_m[-1]
best = sorted[0][-1]
alpha = 1.0 / (n // 2) * 0.4
if subsample > 1:
t = subsample_data(t, subsample)
plot_m = subsample_data(plot_m, subsample)
sorted = subsample_data(sorted, subsample)
if k == 0:
if ylim is None:
ymax = min([fin * ylim_scale, sorted[-1, 0], 90])
ymin = numpy.floor(numpy.max(best / ylim_unit - 0.5,
0)) * ylim_unit
ymin = 0
ylim = [ymin, numpy.ceil(ymax / ylim_unit) * ylim_unit]
else:
ylim = ylim
# 3: 0
if draw_dist[k]:
print('k', k)
for i in range(n // 2):
ax.fill_between(t,
sorted[-1 - i],
sorted[i],
facecolor=colors2[k],
alpha=alpha)
for k in range(m)[::-1]:
plot_m = numpy.median(data[k], 0)
t = numpy.arange(0, T)
if subsample > 1:
t = subsample_data(t, subsample)
plot_m = subsample_data(plot_m, subsample)
ax.plot(t, plot_m, lw=1, color=colors[k], ls='-', label=labels[k])
if hline is not None:
ax.plot((0, T), (hline, hline), color='gray', ls=':')
if vline is not None:
ax.plot((vline, vline), (ylim[0], ylim[1]), color='gray', ls=':')
ax.legend(loc='upper right')
ax.set_xlabel('Iterations')
ax.set_ylabel(ylabel)
ax.set_xlim([0, T])
ax.set_ylim(ylim)
if locator >= 0:
ax.yaxis.set_major_locator(MultipleLocator(locator))
ax.grid()
plt.savefig(savefile + '.png')
plt.savefig(savefile + '.pdf')