def outlier_frequency_plot(path, angles, threshold):
f, ax = base_plot()
ax.plot(100 * np.cumsum(np.abs(angles) > threshold) / angles.size)
ax.set_xlabel("Match number")
ax.set_ylabel("Outlier fraction (%)")
ax.set_ylim([0, 100])
f.savefig(path, bbox_inches='tight')
plt.close(f)
def outlier_frequency_plot(path, angles, threshold):
f, ax = base_plot()
ax.plot(100 * np.cumsum(np.abs(angles) > threshold) / angles.size)
ax.set_xlabel("Match number")
ax.set_ylabel("Outlier fraction (%)")
ax.set_ylim([0, 100])
f.savefig(path, bbox_inches='tight')
plt.close(f)
def plot_covariance_matrix(S, labels):
"Plot a covariance matrix with Hinton-ish diagram"
covariance_matrix_font_size = 18
f, ax = base_plot(figsize=(4,4))
ax.invert_yaxis()
# ax.imshow(S, interpolation="nearest", cmap="gray")
n = S.shape[0]
ax.spines["bottom"].set_visible(False)
ax.spines["left"].set_visible(False)
ax.get_xaxis().tick_top()
ax.get_xaxis().set_ticks_position('none')
ax.get_yaxis().set_ticks_position('none')
ax.set_xticks(np.arange(n))
ax.set_yticks(np.arange(n))
ax.set_xticklabels(labels, fontsize=covariance_matrix_font_size)
ax.set_yticklabels(labels, fontsize=covariance_matrix_font_size)
def format_cov(c):
if np.allclose(c, 0.0):
return "0"
elif np.allclose(c, 1.0):
return "1"
elif np.allclose(c, -1.0):
return "-1"
else:
return "{0:0.2f}".format(c).replace("-0", "-").lstrip("0")
def covcolor(c):
return [1.0 - abs(c)]*3
def textcolor_for_cov(c):
return "white" if abs(c) > 0.5 else "black"
for x in range(n):
for y in range(n):
blob(ax, x, y, abs(S[x, y]), covcolor(S[x,y]))
ax.text(x, y, format_cov(S[x, y]),
fontsize=covariance_matrix_font_size,
horizontalalignment="center",
verticalalignment="center",
color=textcolor_for_cov(S[x, y]))
return f, ax
def plot_distribution(X):
f, ax = base_plot(figsize=(8,4))
ax.hist(X, normed=True, bins=X.size/6)
ax.set_ylabel("Frequency")
return f, ax
def plot_scatter(X, Y):
f, ax = base_plot(figsize=(8,4))
ax.plot(X, Y, '.')
ax.set_xlabel("X")
ax.set_ylabel("Y")
return f, ax
#!/usr/bin/env python3
import sys
import os
import os.path
import numpy as np
import matplotlib.pyplot as plt
from features_common import match_angle, base_plot
if __name__ == "__main__":
if len(sys.argv) >= 2:
path = sys.argv[1]
else:
path = "."
shape = np.loadtxt(os.path.join(path, "shape.txt"))
matches = np.loadtxt(os.path.join(path, "matches.txt"), comments="#")
angles = match_angle(matches, shape)
f, ax = base_plot()
ax.vlines(np.arange(angles.size), 0, angles)
ax.set_ylim([-80, 80])
ax.set_xlabel("Feature number (by distance)")
ax.set_ylabel("Angle")
plt.show(f)
plt.close(f)