def matplotlib_plot(scale, cmap, filename=None):
points = list(ternary.helpers.simplex_iterator(scale))
xs, ys = zip(*map(project, points))
values = range(len(points))
f, axes = plt.subplots(1, 3, figsize=(8.5, 4.5))
styles = ['triangular', 'dual-triangular', 'hexagonal']
ticks_list = [range(scale + 1), range(scale + 2), range(scale + 1)]
shift = True
for ax, style, ticks in zip(axes, styles, ticks_list):
ax.set_aspect('equal')
ax.set_title(style)
ternary.heatmap(dict(zip(points, values)),
scale=scale,
ax=ax,
cmap=cmap,
vmax=len(points) + 1,
style=style,
colorbar=False)
if style == 'dual-triangular' and shift:
xvals = np.array(xs) + .5
yvals = np.array(ys) + 1 / 3
else:
xvals = xs
yvals = ys
ax.scatter(xvals, yvals, s=150, c='c', zorder=3)
ax.set_xticks(ticks)
ax.set_yticks(ticks)
for x, y, value in zip(xvals, yvals, values):
ax.text(x,
y,
str(value),
fontsize=8,
horizontalalignment='center',
verticalalignment='center')
# Colorbar
f.tight_layout()
cbax = f.add_axes([0.025, 0.1, 0.95, 0.10])
norm = mpl.colors.Normalize(vmin=0, vmax=len(points))
ticks = np.linspace(0, len(points), num=len(points) + 1)
cb1 = mpl.colorbar.ColorbarBase(cbax,
cmap=cmap,
norm=norm,
orientation='horizontal')
cb1.set_ticks(ticks)
if filename is not None:
plt.savefig(filename)
return ax
def matplotlib_plot(scale, cmap, filename=None):
points = list(ternary.helpers.simplex_iterator(scale))
xs, ys = zip(*map(project, points))
values = range(len(points))
f, axes = plt.subplots(1,3, figsize=(8.5, 4.5))
styles = ['triangular', 'dual-triangular', 'hexagonal']
ticks_list = [range(scale + 1), range(scale + 2), range(scale + 1)]
shift = True
for ax, style, ticks in zip(axes, styles, ticks_list):
ax.set_aspect('equal')
ax.set_title(style)
ternary.heatmap(dict(zip(points, values)),
scale=scale, ax=ax,
cmap=cmap, vmax=len(points) + 1,
style=style, colorbar=False)
if style == 'dual-triangular' and shift:
xvals = np.array(xs) + .5
yvals = np.array(ys) + 1/3
else:
xvals = xs
yvals = ys
ax.scatter(xvals, yvals, s=150, c='c', zorder=3)
ax.set_xticks(ticks)
ax.set_yticks(ticks)
for x, y, value in zip(xvals, yvals, values):
ax.text(x, y, str(value),
fontsize=8,
horizontalalignment='center',
verticalalignment='center')
# Colorbar
f.tight_layout()
cbax = f.add_axes([0.025, 0.1, 0.95, 0.10])
norm = mpl.colors.Normalize(vmin=0, vmax=len(points))
ticks = np.linspace(0, len(points), num=len(points) + 1)
cb1 = mpl.colorbar.ColorbarBase(cbax, cmap=cmap,
norm=norm,
orientation='horizontal')
cb1.set_ticks(ticks)
if filename is not None:
plt.savefig(filename)
return ax
def tournament_stationary_3(N, mu=None):
"""
Example for a tournament selection matrix.
"""
if not mu:
mu = 3./2 * 1./N
m = [[1,1,1], [0,1,1], [0,0,1]]
num_types = len(m[0])
fitness_landscape = linear_fitness_landscape(m)
incentive = replicator(fitness_landscape)
edges = incentive_process.multivariate_transitions(N, incentive, num_types=num_types, mu=mu)
s = stationary_distribution(edges)
ternary.heatmap(s, scale=N, scientific=True)
d = expected_divergence(edges, q_d=0)
ternary.heatmap(d, scale=N, scientific=True)
pyplot.show()
def tournament_stationary_3(N, mu=None):
"""
Example for a tournament selection matrix.
"""
if not mu:
mu = 3. / 2 * 1. / N
m = [[1, 1, 1], [0, 1, 1], [0, 0, 1]]
num_types = len(m[0])
fitness_landscape = linear_fitness_landscape(m)
incentive = replicator(fitness_landscape)
edges = incentive_process.multivariate_transitions(N,
incentive,
num_types=num_types,
mu=mu)
s = stationary_distribution(edges)
ternary.heatmap(s, scale=N, scientific=True)
d = expected_divergence(edges, q_d=0)
ternary.heatmap(d, scale=N, scientific=True)
pyplot.show()