PyPlot Zoo¶
A simple zoo of examples for PyPlot, since since the official documentation is frustrating at best.
In [1]:
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D # Used for 3D plots
def _map(*args, **aargs):
return list(map(*args, **aargs))
%matplotlib inline
plt.rcParams['figure.figsize'] = (15, 15)
Colors¶
Color maps¶
In [2]:
cmaps = [('Perceptually Uniform Sequential', [
'viridis', 'plasma', 'inferno', 'magma']),
('Sequential', [
'Greys', 'Purples', 'Blues', 'Greens', 'Oranges', 'Reds',
'YlOrBr', 'YlOrRd', 'OrRd', 'PuRd', 'RdPu', 'BuPu',
'GnBu', 'PuBu', 'YlGnBu', 'PuBuGn', 'BuGn', 'YlGn']),
('Sequential (2)', [
'binary', 'gist_yarg', 'gist_gray', 'gray', 'bone', 'pink',
'spring', 'summer', 'autumn', 'winter', 'cool', 'Wistia',
'hot', 'afmhot', 'gist_heat', 'copper']),
('Diverging', [
'PiYG', 'PRGn', 'BrBG', 'PuOr', 'RdGy', 'RdBu',
'RdYlBu', 'RdYlGn', 'Spectral', 'coolwarm', 'bwr', 'seismic']),
('Qualitative', [
'Pastel1', 'Pastel2', 'Paired', 'Accent',
'Dark2', 'Set1', 'Set2', 'Set3',
'tab10', 'tab20', 'tab20b', 'tab20c']),
('Miscellaneous', [
'flag', 'prism', 'ocean', 'gist_earth', 'terrain', 'gist_stern',
'gnuplot', 'gnuplot2', 'CMRmap', 'cubehelix', 'brg', 'hsv',
'gist_rainbow', 'rainbow', 'jet', 'nipy_spectral', 'gist_ncar'])]
# rmaps = [c for e in cmaps for c in e[1] ]
from matplotlib import cm
rmaps = cm.datad.keys()
print(rmaps)
In [3]:
gradient = np.linspace(0, 1, 256)
gradient = np.tile(gradient, 5).reshape(5, 256)
In [4]:
_, axes = plt.subplots(nrows=len(rmaps), ncols=1, figsize = (80,35))
for axe,cmap in zip(axes, rmaps):
try:
axe.set_title(cmap, y=-.25)
axe.set_axis_off()
axe.imshow(gradient, cmap=cmap)
except ValueError:
pass
Colors¶
Scatter¶
In [5]:
x = np.linspace(0, 20, 50)
y = np.linspace(0, 20, 50)
X, Y = np.meshgrid(x, y)
Z = np.abs(X - Y)
In [6]:
plt.scatter(X, Y, c=Z, cmap='rainbow', linewidth=0)
plt.plot([0, 20], [0, 20])
plt.title("Absolute distance between X and Y")
plt.xlim([0, 20])
plt.xlabel("X")
plt.ylim([0, 20])
plt.ylabel("Y")
c = plt.colorbar()
c.set_label("Z = |X - Y|")
Plot¶
In [7]:
p = np.linspace(0, 1, 100)
h = - p * np.log2(p) - (1-p) * np.log2(1-p)
h[0] = 0
h[-1] = 0
In [8]:
plt.plot(p, h)
plt.plot([.5,.5], [0,1], linewidth=1, color='green')
plt.title("Entropy H(p)")
plt.xlim([0, 1])
xs = np.linspace(0, 1, 11)
plt.xticks(xs, _map(str, xs))
plt.xlabel("p")
plt.ylim([0, 1])
plt.ylabel("H(p)")
Out[8]:
Matrices¶
In [9]:
x = np.linspace(0, 17, 10)
y = np.linspace(0, 20, 20)
X, Y = np.meshgrid(x, y)
Z = X * Y
In [10]:
plt.imshow(Z, interpolation='None', cmap='jet')
plt.title("X * Y")
plt.xticks(range(len(x)), ["{:.2f}".format(e) for e in x], rotation=90)
plt.xlabel("X")
plt.yticks(range(len(y)), ["{:.2f}".format(e) for e in y])
plt.ylabel("Y")
c = plt.colorbar()
c.set_label("Z = X * Y")
Histogram¶
In [11]:
import random
random.seed(0)
v = [sum((random.choice([-1,1]) for _ in range(100))) for _ in range(1000)]
In [12]:
_, _, _ = plt.hist(v, bins=100, range=(-100,100))
plt.xscale('linear')
_ = plt.xticks(range(-100,101, 10))
Multiple histograms¶
In [13]:
random.seed(0)
a = [sum((random.choice([-1,1]) for _ in range(100))) for _ in range(1000)]
b = [random.randint(-100,100) for _ in range(1000)]
In [14]:
bins = np.linspace(-100, 100, 100)
plt.hist(a, bins, alpha=0.5, label='a')
plt.hist(b, bins, alpha=0.5, label='b')
plt.legend(loc='upper right')
Out[14]:
3d functions¶
f(x, y) = z
Trisurf¶
In [15]:
x = np.linspace(-5, 5, 20)
y = np.linspace(-5, 5, 50)
X, Y = np.meshgrid(x, y)
X, Y = X.ravel(), Y.ravel()
Z = [a*b for a,b in zip(X, Y)]
In [16]:
fig = plt.figure()
ax = fig.gca(projection='3d')
ax.set_title("f(x, y) = sin(x*y)")
ax.set_xlabel("x")
ax.set_ylabel("y")
ax.view_init(10, 45)
ax.plot_trisurf(X, Y, Z, linewidth=0.2, antialiased=True, color="red")
Out[16]:
Wireframe¶
In [17]:
p = np.linspace(0.0000, 1, 100)
q = np.linspace(0.0000, 1, 100)
P, Q = np.meshgrid(p, q)
H = -P*np.log(Q) - (1-P)*np.log(1-Q)
In [18]:
fig = plt.figure()
ax = fig.gca(projection='3d')
ax.set_title("Cross entropy H(P,Q)")
ax.set_xlabel("P")
ax.set_ylabel("Q")
ax.view_init(10, 45)
ax.plot_wireframe(P, Q, H, color='blue', antialiased=True)
Out[18]:
Surface¶
In [19]:
x = np.linspace(-5, 5, 100)
y = np.linspace(-5, 5, 100)
X, Y = np.meshgrid(x, y)
Z = np.cos(np.sqrt(X**2 + Y**2))
In [20]:
fig = plt.figure()
ax = fig.gca(projection='3d')
ax.set_title("f(x, y) = cos(sqrt(x^2 + y^2))")
ax.set_xlabel("x")
ax.set_ylabel("y")
ax.view_init(30, 60)
ax.plot_surface(X, Y, Z, cmap='jet', antialiased=True)
Out[20]:
3D scatterplots¶
In [21]:
x = np.linspace(-5, 5, 100)
y = np.linspace(-5, 5, 100)
X, Y = np.meshgrid(x, y)
# X, Y = X.flatten(), Y.flatten()
Z = np.cos(np.sqrt(X**2 + Y**2))
In [22]:
fig = plt.figure()
ax = fig.gca(projection='3d')
ax.set_title("f(x, y) = cos(sqrt(x^2 + y^2))")
ax.set_xlabel("x")
ax.set_ylabel("y")
# ax.view_init(45, 45)
ax.scatter(X, Y, Z, c='gray', s=10, marker='.')
Out[22]:
Contours¶
In [23]:
a = np.linspace(-10,10, 100)
x, y = np.meshgrid(a, a)
r = np.sqrt(x**2 + y**2)
c = r <= 2
In [24]:
plt.title("Example of a contour")
plt.imshow(r, interpolation='none', cmap='gray')
plt.contour(c, interpolation='none', cmap='rainbow')
Out[24]:
Subplots¶
In [25]:
img1 = np.arange(10000).reshape(100,100)
a = np.linspace(-10,10, 100)
x, y = np.meshgrid(a, a)
img2 = np.sqrt(x**2 + y**2)
In [26]:
figs = [(img1, "Nice range"),
(img2, "A thing")]
_, axes = plt.subplots(nrows=1, ncols=len(figs))
for axe, fig in zip(axes, figs):
axe.set_title(fig[1])
axe.imshow(fig[0])
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