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advanced-plots.py
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# -----------------------------------------------------------------------------
# Matplotlib cheat sheet
# Released under the BSD License
# -----------------------------------------------------------------------------
# Scripts to generate all the advanced plots
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
fig = plt.figure(figsize=(0.4, 0.4))
mpl.rcParams['axes.linewidth'] = 0.5
mpl.rcParams['xtick.major.size'] = 0.0
mpl.rcParams['ytick.major.size'] = 0.0
d = 0.01
ax = fig.add_axes([d, d, 1-2*d, 1-2*d])
# Stairs plot
# -----------------------------------------------------------------------------
X = np.linspace(0, 2*np.pi, 9)
Y = 2*np.sin(3*X)
Y[7:] = 0
ax.stairs(Y, color="C1", linewidth=0.75)
ax.set_xlim(0, 8), ax.set_xticks(np.arange(1, 8))
ax.set_ylim(-4, 4), ax.set_yticks(np.arange(-4, 4))
ax.set_axisbelow(True)
ax.grid(linewidth=0.125)
plt.savefig("../figures/advanced-stairs.pdf")
ax.clear()
# Violin plot
# -----------------------------------------------------------------------------
np.random.seed(10)
D = np.random.normal((3, 5, 4), (0.75, 1.00, 0.75), (200, 3))
VP = ax.violinplot(D, [2, 4, 6], widths=1.5,
showmeans=False, showmedians=False, showextrema=False)
for body in VP['bodies']:
body.set_facecolor('C1')
body.set_alpha(1)
ax.set_xlim(0, 8), ax.set_xticks(np.arange(1, 8))
ax.set_ylim(0, 8), ax.set_yticks(np.arange(1, 8))
ax.set_axisbelow(True)
ax.grid(linewidth=0.125)
plt.savefig("../figures/advanced-violin.pdf")
ax.clear()
# Boxplot
# -----------------------------------------------------------------------------
np.random.seed(10)
D = np.random.normal((3, 5, 4), (1.25, 1.00, 1.25), (100, 3))
VP = ax.boxplot(D, positions=[2, 4, 6], widths=1.5, patch_artist=True,
showmeans=False, showfliers=False,
medianprops={"color": "white",
"linewidth": 0.25},
boxprops={"facecolor": "C1",
"edgecolor": "white",
"linewidth": 0.25},
whiskerprops={"color": "C1",
"linewidth": 0.75},
capprops={"color": "C1",
"linewidth": 0.75})
ax.set_xlim(0, 8), ax.set_xticks(np.arange(1, 8))
ax.set_ylim(0, 8), ax.set_yticks(np.arange(1, 8))
ax.set_axisbelow(True)
ax.grid(linewidth=0.125)
plt.savefig("../figures/advanced-boxplot.pdf")
ax.clear()
# Barbs plot
# -----------------------------------------------------------------------------
np.random.seed(1)
X = [[2, 4, 6]]
Y = [[1.5, 3, 2]]
U = -np.ones((1, 3)) * 0
V = -np.ones((1, 3)) * np.linspace(50, 100, 3)
ax.barbs(X, Y, U, V, barbcolor="C1", flagcolor="C1", length=5, linewidth=0.5)
ax.set_xlim(0, 8), ax.set_xticks(np.arange(1, 8))
ax.set_ylim(0, 8), ax.set_yticks(np.arange(1, 8))
ax.set_axisbelow(True)
ax.grid(linewidth=0.125)
plt.savefig("../figures/advanced-barbs.pdf")
ax.clear()
# Event plot
# -----------------------------------------------------------------------------
np.random.seed(1)
X = [2, 4, 6]
D = np.random.gamma(4, size=(3, 50))
ax.eventplot(D, colors="C1", orientation="vertical", lineoffsets=X,
linewidth=0.25)
ax.set_xlim(0, 8), ax.set_xticks(np.arange(1, 8))
ax.set_ylim(0, 8), ax.set_yticks(np.arange(1, 8))
ax.set_axisbelow(True)
ax.grid(linewidth=0.125)
plt.savefig("../figures/advanced-event.pdf")
ax.clear()
# Errorbar plot
# -----------------------------------------------------------------------------
np.random.seed(1)
X = [2, 4, 6]
Y = [4, 5, 4]
E = np.random.uniform(0.5, 1.5, 3)
ax.errorbar(X, Y, E, color="C1", linewidth=0.75, capsize=1)
ax.set_xlim(0, 8), ax.set_xticks(np.arange(1, 8))
ax.set_ylim(0, 8), ax.set_yticks(np.arange(1, 8))
ax.set_axisbelow(True)
ax.grid(linewidth=0.125)
plt.savefig("../figures/advanced-errorbar.pdf")
ax.clear()
# Hexbin plot
# -----------------------------------------------------------------------------
np.random.seed(1)
X = np.random.uniform(1.5, 6.5, 100)
Y = np.random.uniform(1.5, 6.5, 100)
C = np.random.uniform(0, 1, 10000)
ax.hexbin(X, Y, C, gridsize=4, linewidth=0.25, edgecolor="white",
cmap=plt.get_cmap("Wistia"), alpha=1.0)
ax.set_xlim(0, 8), ax.set_xticks(np.arange(1, 8))
ax.set_ylim(0, 8), ax.set_yticks(np.arange(1, 8))
ax.set_axisbelow(True)
ax.grid(linewidth=0.125)
plt.savefig("../figures/advanced-hexbin.pdf")
ax.clear()
# Hist plot
# -----------------------------------------------------------------------------
np.random.seed(1)
X = 4 + np.random.normal(0, 1.5, 200)
ax.hist(X, bins=8, facecolor="C1", linewidth=0.25, edgecolor="white")
ax.set_xlim(0, 8), ax.set_xticks(np.arange(1, 8))
ax.set_ylim(0, 80), ax.set_yticks(np.arange(1, 80, 10))
ax.set_axisbelow(True)
ax.grid(linewidth=0.125)
plt.savefig("../figures/advanced-hist.pdf")
ax.clear()
# Xcorr plot
# -----------------------------------------------------------------------------
np.random.seed(3)
Y = np.random.uniform(-4, 4, 250)
X = np.random.uniform(-4, 4, 250)
ax.xcorr(X, Y, usevlines=True, maxlags=6, normed=True, lw=1,
color="C1")
ax.set_xlim(-8, 8), ax.set_xticks(np.arange(-8, 8, 2))
ax.set_ylim(-.25, .25), ax.set_yticks(np.linspace(-.25, .25, 9))
ax.set_axisbelow(True)
ax.grid(linewidth=0.125)
plt.savefig("../figures/advanced-xcorr.pdf")
ax.clear()