You are reading an old version of the documentation (v1.5.1). For the latest version see

We're updating the default styles for Matplotlib 2.0

Learn what to expect in the new updates



This Page

images_contours_and_fields example code: interpolation_none_vs_nearest.pyΒΆ

(Source code)

Displays the difference between interpolation = 'none' and
interpolation = 'nearest'.

Interpolation = 'none' and interpolation = 'nearest' are equivalent when
converting a figure to an image file, such as a PNG.
Interpolation = 'none' and interpolation = 'nearest' behave quite
differently, however, when converting a figure to a vector graphics file,
such as a PDF.  As shown, Interpolation = 'none' works well when a big
image is scaled down, while interpolation = 'nearest' works well when a
small image is blown up.

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.cbook as cbook

# Load big image
big_im_path = cbook.get_sample_data('necked_tensile_specimen.png')
big_im = plt.imread(big_im_path)
# Define small image
small_im = np.array([[0.25, 0.75, 1.0, 0.75], [0.1, 0.65, 0.5, 0.4],
                     [0.6, 0.3, 0.0, 0.2], [0.7, 0.9, 0.4, 0.6]])

# Create a 2x2 table of plots
fig = plt.figure(figsize=[8.0, 7.5])
ax = plt.subplot(2, 2, 1)
ax.imshow(big_im, interpolation='none')
ax = plt.subplot(2, 2, 2)
ax.imshow(big_im, interpolation='nearest')
ax = plt.subplot(2, 2, 3)
ax.imshow(small_im, interpolation='none')
ax = plt.subplot(2, 2, 4)
ax.imshow(small_im, interpolation='nearest')
plt.subplots_adjust(left=0.24, wspace=0.2, hspace=0.1,
                    bottom=0.05, top=0.86)

# Label the rows and columns of the table
fig.text(0.03, 0.645, 'Big Image\nScaled Down', ha='left')
fig.text(0.03, 0.225, 'Small Image\nBlown Up', ha='left')
fig.text(0.383, 0.90, "Interpolation = 'none'", ha='center')
fig.text(0.75, 0.90, "Interpolation = 'nearest'", ha='center')

# If you were going to run this example on your local machine, you
# would save the figure as a PNG, save the same figure as a PDF, and
# then compare them.  The following code would suffice.
txt = fig.text(0.452, 0.95, 'Saved as a PNG', fontsize=18)
# plt.savefig('None_vs_nearest-png.png')
# txt.set_text('Saved as a PDF')
# plt.savefig('None_vs_nearest-pdf.pdf')

# Here, however, we need to display the PDF on a webpage, which means
# the PDF must be converted into an image.  For the purposes of this
# example, the 'Nearest_vs_none-pdf.pdf' has been pre-converted into
#'Nearest_vs_none-pdf.png' at 80 dpi.  We simply need to load and
# display it.
pdf_im_path = cbook.get_sample_data('None_vs_nearest-pdf.png')
pdf_im = plt.imread(pdf_im_path)
fig2 = plt.figure(figsize=[8.0, 7.5])

Keywords: python, matplotlib, pylab, example, codex (see Search examples)