Matplotlib Quick Reference
[Pages:2]Matplotlib Quick Reference
Matti Pastell, University of Helsinki.
Import pylab
from pylab import *
Line plots
x = linspace(0, 2*pi, 100) y = sin(x) y2 = cos(x) plot(x, y) plot(x, y2, 'og') title('sin(x) and cos(x)') xlabel('x') ylabel('f(x)') legend(['sin(x)', 'cos(x)'], loc = 3)
12
10
8
6
4
2
0
22
0
2
4
6
8
10
Bar plot
y = [9, 12, 7] errors = [1.3, 0.9, 2] x = arange(len(y)) bar(x, y, yerr=errors, ecolor="red",
capsize=10)
Fixed x-error and variable y-error
1.0
0.5
0.0
0.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0
Histogram
x = randn(1000) hist(x, bins=20)
14
1.0
sin(x) and cos(x)
12
160
10
140
0.5
8
120
f(x)
0.0
6
100
4
80
0.5
sin(x)
cos(x)
1.00
1
2
3x4
5
6
7
2
00.0
0.5
1.0
1.5
2.0
2.5
3.0
Errorbars
60
40
20
04
3
2
10
1
2
3
4
Scatter plot
x = arange(0.1, 4, 0.5) y = exp(-x)
Boxplot
x = arange(10) y = x + randn(len(x))
y_error = 0.1 + 0.2*np.sqrt(x) x_error = 0.1
y2 = x + randn(len(x))
errorbar(x, y, xerr = x_error,
scatter(x, y, s=100, alpha=0.7)
yerr = y_error, fmt='o', ecolor="red") x = randn(100, 5)
scatter(x, y2, s=100, marker="d", color="red") title('Fixed x-error and variable y-error')
boxplot(x)
3
2
1
0
1
2
31
2
3
4
5
Stem plot
x = range(10) y = rand(10) stem(x, y)
1.0
0.8
0.6
0.4
0.2
0.00 1 2 3 4 5 6 7 8 9
Contour
x = linspace(-3, 3, 200) y=x X,Y = meshgrid(x, y) Z = bivariate_normal(X, Y, sigmaxy=0.5) contourf(X, Y, Z) colorbar() xlabel('X') ylabel('Y') title(r"$\sigma_{XY}$ = 0.5")
3
XY = 0.5
0.200
0.175 2
0.150 1
0.125
Y
0
0.100
0.075 1
0.050 2
0.025
33
2
10
1
2
3 0.000
X
Surface plot
from mpl_toolkits.mplot3d import Axes3D fig = figure() ax = fig.add_subplot(111, projection='3d') ax.plot_surface(X, Y, Z, cmap="jet")
0.20
0.15
0.10
0.05
0.00
3
2
3
2
10
1
2
3
1 0 1 2 3
Subplots
n = 128. x = arange(n)/n y = sin(0.125*pi*n*x**2) subplot(221) plot(x,y,'r') xlabel('x') ylabel(r'$sin(0.125n \cdot x^2)$') subplot(222)
x = arange(0, 2*pi, 0.2) y = sin(x) stem(x,y) axis([0, 2*pi, -1.2, 1.2]) xlabel('x') ylabel('sinx(x)') subplot(223) y = randn(1000) hist(y) xlabel('bin') ylabel('count') subplot(224) boxplot(y) ylabel('y')
sin(0.125n ?x2 )
1.0
1.0
0.5
0.5
sinx(x)
0.0
0.0
0.5
0.5
1.00.0 250
0.2
0.4 x 0.6
0.8
1.0 1.0 0
4
1
2
3x 4
5
6
200
3
2
150
1
y
100
0
50
1 2
03 2 1 0 1 2 3 4 3
1
bin
count
Links
? Matplotlib tutorial: ~rougier/teaching/matplotlib/
? Examples gallery: gallery.html
? Matplotlib colormaps 2013/05/02/matplotlib_colormaps/
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