def plot_gram_matrix(x_train, gamma, n_reduce=None):
kmatrix = gram_matrix(x_train, gamma)
if n_reduce is not None:
kmatrix = kmatrix[:n_reduce, :n_reduce]
plt.pcolor(kmatrix, cmap=plt.cm.PuRd)
plt.colorbar()
plt.xlim([0, kmatrix.shape[0]])
plt.ylim([0, kmatrix.shape[0]])
plt.gca().invert_yaxis()
plt.gca().xaxis.tick_top()
plt.show()
def plot_regularization_path(alphas,
coefs,
features_labels,
n_features_labels=None,
legend_size='medium'):
"""
:param alphas:
:param coefs:
:param features_labels:
:param n_features_labels:
:param legend_size:
:return:
"""
plt.figure(figsize=(12, 6))
ax = plt.gca()
ax.plot(alphas, coefs)
ax.set_xscale('log')
plt.xlabel('Alpha')
plt.ylabel('Coefficients')
plt.legend(features_labels[:n_features_labels]
if n_features_labels is not None else features_labels,
loc='upper right',
fontsize=legend_size)
plt.show()
def plot_correlation_circle(self,
n_plan=None,
labels=None,
label_rotation=0,
lims=None,
save_as_img=False,
plot_size=(10, 8)):
"""
"""
factorial_plan_nb = self.default_factorial_plan_nb if n_plan is None else n_plan
# Build a list of tuples (example : [(0, 1), (2, 3), ... ])
axis_ranks = [(x, x + 1) for x in range(0, factorial_plan_nb, 2)]
pcs = self.pca.components_
for d1, d2 in axis_ranks:
if d2 < self.n_comp:
fig, ax = plt.subplots(figsize=plot_size)
# Fix factorial plan limits
if lims is not None:
xmin, xmax, ymin, ymax = lims
elif pcs.shape[1] < 30:
xmin, xmax, ymin, ymax = -1, 1, -1, 1
else:
xmin, xmax, ymin, ymax = min(pcs[d1, :]), max(
pcs[d1, :]), min(pcs[d2, :]), max(pcs[d2, :])
# affichage des flèches
# s'il y a plus de 30 flèches, on n'affiche pas le triangle à leur extrémité
if pcs.shape[1] < 30:
plt.quiver(np.zeros(pcs.shape[1]),
np.zeros(pcs.shape[1]),
pcs[d1, :],
pcs[d2, :],
angles='xy',
scale_units='xy',
scale=1,
color="grey")
# (doc : https://matplotlib.org/api/_as_gen/matplotlib.pyplot.quiver.html)
else:
lines = [[[0, 0], [x, y]] for x, y in pcs[[d1, d2]].T]
ax.add_collection(
LineCollection(lines, axes=ax, alpha=.1,
color='black'))
# Display variables labels
if labels is not None:
for i, (x, y) in enumerate(pcs[[d1, d2]].T):
if xmin <= x <= xmax and ymin <= y <= ymax:
plt.text(x,
y,
labels[i],
fontsize='14',
ha='center',
va='center',
rotation=label_rotation,
color="blue",
alpha=0.5) # fontsize : 14
# Plot circle
circle = plt.Circle((0, 0), 1, facecolor='none', edgecolor='b')
plt.gca().add_artist(circle)
# définition des limites du graphique
plt.xlim(xmin, xmax)
plt.ylim(ymin, ymax)
# affichage des lignes horizontales et verticales
plt.plot([-1, 1], [0, 0], color='grey', ls='--')
plt.plot([0, 0], [-1, 1], color='grey', ls='--')
# Axes labels with % explained variance
plt.xlabel('F{} ({}%)'.format(d1 + 1,
round(100 * self.evr[d1], 1)),
labelpad=20)
plt.ylabel('F{} ({}%)'.format(d2 + 1,
round(100 * self.evr[d2], 1)),
labelpad=20)
plt.title("Cercle des corrélations (F{} et F{})".format(
d1 + 1, d2 + 1),
pad=20)
if save_as_img:
plt.tight_layout()
plt.savefig(
'corr_circle_{}.jpg'.format(1 if d1 == 0 else d1))
plt.show(block=False)