def set_labels(ylabel: str, xlabel: str):
for i, y, x in [
(1, True, False),
(2, False, False),
(3, True, False),
(4, False, False),
(5, True, True),
(6, False, True),
]:
plt.subplot(3, 2, i)
ax = plt.gca()
if y:
plt.ylabel(ylabel)
else:
ax.axes.yaxis.set_ticklabels([])
if x:
plt.xlabel(xlabel)
ax.axes.xaxis.set_ticklabels([])
ymin, ymax = np.inf, -np.inf
for i in range(1, 6 + 1):
plt.subplot(3, 2, i)
ymin = min(ymin, plt.ylim()[0])
ymax = max(ymax, plt.ylim()[1])
for i in range(1, 6 + 1):
plt.subplot(3, 2, i)
plt.ylim((ymin, ymax))
def demo(name, mu, sigma, strategies):
t0 = time()
Q, R, A = multistrat(mu=mu,
sigma=sigma,
strategies=strategies,
epochs=1100)
multiplot(A, R, strategies)
plt.ylim(1)
print name, "ran in", time() - t0, "s"
show(name.replace(' ', '_'))
plot_qs(Q, mu, strategies)
show(name.replace(' ', '_') + "-q")
def matrix_subplots(
c: Config,
resp_matrix: ResponsesMatrix,
num_subplots: int,
num_x: int,
z_frac: float,
rows: int = 4,
save: str = None,
plot_func=None,
):
"""For each subplot plot matrix fem using the given function."""
cols = int(num_subplots / rows)
if cols != num_subplots / rows:
print_w(f"Rows don't divide number of simulations, cols = {cols}" +
f", sims = {num_subplots / rows}" +
f", num_subplots = {num_subplots}, rows = {rows}")
cols += 1
y_min, y_max = 0, 0
# Plot each IL and bridge deck side.
for i, response_frac in enumerate(np.linspace(0, 1, rows * cols)):
plt.subplot(rows, cols, i + 1)
plot_bridge_deck_side(c.bridge, show=False, equal_axis=False)
rs = plot_func(c,
resp_matrix,
i,
response_frac,
z_frac=z_frac,
num_x=num_x)
plt.axvline(x=c.bridge.x(x_frac=response_frac), color="red")
# Keep track of min and max on y axis (only when non-zero fem).
if any(rs):
_y_min, _y_max = plt.gca().get_ylim()
y_min, y_max = min(y_min, _y_min), max(y_max, _y_max)
# Ensure y_min == -y_max.
y_min = min(y_min, -y_max)
y_max = max(-y_min, y_max)
for i, _ in enumerate(np.linspace(0, 1, rows * cols)):
plt.subplot(rows, cols, i + 1)
plt.ylim(y_min, y_max)
plt.tight_layout()
if save:
plt.savefig(save)
plt.close()
colors = "rgbky"
for si, sigma in enumerate([SIGMA1, SIGMA2, SIGMA3]):
t0 = time()
Q, R, A = multistrat(mu=MU,
sigma=sigma,
strategies=strats,
epochs=5000)
fig = plt.figure(figsize=(12, 5))
ax = fig.add_subplot(spec[0])
for i, s in enumerate(strats):
plt.plot(R[i].mean(axis=0),
label=s.__name__,
alpha=0.5,
c=colors[i])
plt.legend(fontsize=10, loc="lower right")
plt.title("Average reward over {} runs".format(len(R[0])))
fig.add_subplot(spec[1], sharey=ax)
bp = plt.boxplot(R.mean(axis=2).T, labels=[s.__name__ for s in strats])
for box, color in zip(bp['boxes'], colors):
box.set_color(color)
plt.xticks([])
plt.ylim(3)
name = "Ex_2_sigma{}".format(si + 1)
print name, time() - t0, "s"
show(name)
def zoom_in():
plt.ylim(min_z, max_z)
plt.xlim(min_x, max_x)