Matplotlib Contour Plot in python

In this example we show how to draw contour using matplotlib in python

Contour plots which are also called level plots are a way to show a three-dimensional surface on a two-dimensional plane. It graphs two predictor variables X Y on the y-axis and a response variable Z as contours.

These contours are also sometimes called z-slices or iso-response values.

One common usage is to visualize density, altitudes or heights of the mountain as well as in the meteorological department.

Syntax

matplotlib.pyplot.contour(*args, data=None, **kwargs)

Plot contour lines.

Call signature:

contour([X, Y,] Z, [levels], **kwargs)

contour and contourf draw contour lines and filled contours, respectively. Except as noted, function signatures and return values are the same for both versions.

Parameters

X, Y – array-like, optional

The coordinates of the values in Z.

X and Y must both be 2D with the same shape as Z (e.g. created via numpy.meshgrid), or they must both be 1-D such that len(X) == N is the number of columns in Z and len(Y) == M is the number of rows in Z.

X and Y must both be ordered monotonically.

If not given, they are assumed to be integer indices, i.e. X = range(N), Y = range(M).

Z(M, N) –  array-like

The height values over which the contour is drawn.

levels – int or array-like, optional

Determines the number and positions of the contour lines / regions.

If an int n, use MaxNLocator, which tries to automatically choose no more than n+1 “nice” contour levels between vmin and vmax.

If array-like, draw contour lines at the specified levels. The values must be in increasing order.

Examples

Basic Example

import numpy as np
import matplotlib.pyplot as plot

xlist = np.linspace(-3.0, 3.0, 100)
ylist = np.linspace(-3.0, 3.0, 100)
X, Y = np.meshgrid(xlist, ylist)
Z = np.sqrt(X**2 + Y**2)
fig,ax=plot.subplots(1,1)
cp = ax.contourf(X, Y, Z)
fig.colorbar(cp) # Add a colorbar to a plot

ax.set_title('Filled Contours Plot')
#ax.set_xlabel('x (cm)')
ax.set_ylabel('y (cm)')
plot.show()

This displayed the following

Coloured Example

import numpy as np
import matplotlib.pyplot as plot

xlist = np.linspace(-2.0, 2.0, 100)
ylist = np.linspace(-2.0, 2.0, 100)
X, Y = np.meshgrid(xlist, ylist)
Z = np.sqrt(X**2 + Y**2)

plot.figure()

contour = plot.contour(X, Y, Z)
plot.clabel(contour, colors = 'k', fmt = '%2.1f', fontsize=10)
c = ('red', 'yellow', 'blue', '0.4', 'c', 'm')
contour_filled = plot.contourf(X, Y, Z, colors=c)
plot.colorbar(contour_filled)

plot.title('Filled Contours Plot')
plot.xlabel('x (cm)')
plot.ylabel('y (cm)')
plot.show()

This displayed the following

Levels Example

import numpy as np
import matplotlib.pyplot as plot

xlist = np.linspace(-3.0, 3.0, 100)
ylist = np.linspace(-3.0, 3.0, 100)
X, Y = np.meshgrid(xlist, ylist)

Z = np.sqrt(X ** 2 + Y ** 2 )
plot.figure()

levels = [0.0, 0.2, 0.5, 0.9, 1.5, 2.5, 3.5]
contour = plot.contour(X, Y, Z, levels, colors='k')
plot.clabel(contour, colors = 'k', fmt = '%2.1f', fontsize=10)
contour_filled = plot.contourf(X, Y, Z, levels)
plot.colorbar(contour_filled)

plot.title('Plot from level list')
plot.xlabel('x (cm)')
plot.ylabel('y (cm)')
plot.show()

This displayed the following

More examples

Some more examples to try

import matplotlib.pyplot as plot
import numpy as np

xlist = np.linspace(-5.0, 5.0, 100)
ylist = ylist = np.linspace(-5.0, 5.0, 100)
X, Y = np.meshgrid(xlist, ylist)

#creating hyperbolic plane
Z = (X**2)/4 - (Y**2)/9

fig, ax = plot.subplots()

#drawing filled contour plot
cb = ax.contourf(X, Y, Z)
#Adding a colorbar to the plot
fig.colorbar(cb) 

ax.set_title('Filled Contour Plot')
ax.set_xlabel('x (cm)')
ax.set_ylabel('y (cm)')

plot.show()