Basic plots with matplotlib

In [1]:

import numpy as np
import matplotlib.pyplot as plt

Displaying matrices

In [2]:

img = np.fromfunction(lambda i, j:  (i-5)**2 + (j-5)**2,
                      (11,11))

In [3]:

g = plt.imshow(img, interpolation='nearest')

In [4]:

plt.show()
../_images/scratch_Python06C_5_0.png

To set display on by default

In [5]:

%matplotlib inline

In [6]:

g = plt.imshow(img, interpolation='nearest')
../_images/scratch_Python06C_8_0.png

Images as arrays

In [7]:

from scipy import misc
face = misc.imread('figs/face.png')

In [8]:

face.shape

Out[8]:

(768, 1024, 3)

In [9]:

face

Out[9]:

array([[[121, 112, 131],
        [138, 129, 148],
        [153, 144, 165],
        ...,
        [119, 126,  74],
        [131, 136,  82],
        [139, 144,  90]],

       [[ 89,  82, 100],
        [110, 103, 121],
        [130, 122, 143],
        ...,
        [118, 125,  71],
        [134, 141,  87],
        [146, 153,  99]],

       [[ 73,  66,  84],
        [ 94,  87, 105],
        [115, 108, 126],
        ...,
        [117, 126,  71],
        [133, 142,  87],
        [144, 153,  98]],

       ...,
       [[ 87, 106,  76],
        [ 94, 110,  81],
        [107, 124,  92],
        ...,
        [120, 158,  97],
        [119, 157,  96],
        [119, 158,  95]],

       [[ 85, 101,  72],
        [ 95, 111,  82],
        [112, 127,  96],
        ...,
        [121, 157,  96],
        [120, 156,  94],
        [120, 156,  94]],

       [[ 85, 101,  74],
        [ 97, 113,  84],
        [111, 126,  97],
        ...,
        [120, 156,  95],
        [119, 155,  93],
        [118, 154,  92]]], dtype=uint8)

In [10]:

plt.imshow(face);
../_images/scratch_Python06C_13_0.png

Line plots

In [11]:

x = np.linspace(-5, 5, 50)
y = x**2

In [12]:

plt.plot(x, y);
../_images/scratch_Python06C_16_0.png 
In [13]:

plt.plot(x, y, '--');
../_images/scratch_Python06C_17_0.png 
In [14]:

plt.plot(x, y, linestyle='dashed');
../_images/scratch_Python06C_18_0.png 
In [15]:

plt.plot(x, y, 'o');
../_images/scratch_Python06C_19_0.png 
In [16]:

plt.plot(x, y, marker='o', markersize=5, color='salmon',
         linestyle='solid',);
../_images/scratch_Python06C_20_0.png

Scatter plots

In [17]:

x = np.random.multivariate_normal(np.zeros(2), np.eye(2), 250)
v = 50*(x**2).sum(1)

plt.scatter(x[:,0], x[:,1], s=v, c=v, alpha=0.5)
plt.axis('square');
plt.axis([-3,3,-3,3])
plt.xticks([])
plt.yticks([]);
../_images/scratch_Python06C_22_0.png

Histograms

In [18]:

x = np.random.randn(100)

In [19]:

plt.hist(x);
../_images/scratch_Python06C_25_0.png 
In [20]:

for i in range(5):
    x = np.random.normal(i, 1, 100)
    plt.hist(x, bins=15, alpha=0.5, normed=True);
../_images/scratch_Python06C_26_0.png

Multiple plots

In [21]:

nrows = 2
ncols = 3
fig, axes = plt.subplots(nrows, ncols, figsize=(ncols*2, nrows*2))
for i, ax in enumerate(axes.ravel()):
    ax.plot(x, x**i)
    ax.grid(True)
    ax.set_xticklabels([])
    ax.set_yticklabels([])
    ax.set_title('Degree {}'.format(i))
../_images/scratch_Python06C_28_0.png

Styles

In [22]:

x = np.linspace(-5, 5, 50)
y = x**2

In [23]:

plt.style.available

Out[23]:

['_classic_test',
 'bmh',
 'classic',
 'dark_background',
 'fivethirtyeight',
 'ggplot',
 'grayscale',
 'seaborn-bright',
 'seaborn-colorblind',
 'seaborn-dark-palette',
 'seaborn-dark',
 'seaborn-darkgrid',
 'seaborn-deep',
 'seaborn-muted',
 'seaborn-notebook',
 'seaborn-paper',
 'seaborn-pastel',
 'seaborn-poster',
 'seaborn-talk',
 'seaborn-ticks',
 'seaborn-white',
 'seaborn-whitegrid',
 'seaborn']

In [24]:

with plt.style.context('ggplot'):
    plt.plot(x, y);
../_images/scratch_Python06C_32_0.png 
In [25]:

with plt.style.context('dark_background'):
    plt.plot(x, y);
../_images/scratch_Python06C_33_0.png 
In [26]:

with plt.xkcd():
    plt.plot(x, y);
../_images/scratch_Python06C_34_0.png 
In [ ]: