silx.test:

silx.test

This package provides access to the full silx test suite.

It is possible to disable tests depending on Qt by setting silx.test.utils.test_options.WITH_QT_TEST = False It will skip all tests from silx.test.gui.

run_tests()[source]

Run test complete test_suite

silx.test.utils

Utilities for writing tests.

  • temp_dir() provides a with context to create/delete a temporary directory.
utilstest = <silx.resources.ExternalResources object>

This is the instance to be used. Singleton-like feature provided by module

test_options = <silx.test.utils._TestOptions object>

Singleton providing configuration information for all the tests

temp_dir(*args, **kwds)[source]

with context providing a temporary directory.

>>> import os.path
>>> with temp_dir() as tmp:
...     print(os.path.isdir(tmp))  # Use tmp directory
add_gaussian_noise(y, stdev=1.0, mean=0.0)[source]

Add random gaussian noise to synthetic data.

Parameters:
  • y (ndarray) – Array of synthetic data
  • mean (float) – Mean of the gaussian distribution of noise.
  • stdev (float) – Standard deviation of the gaussian distribution of noise.
Returns:

Array of data with noise added
add_poisson_noise(y)[source]

Add random noise from a poisson distribution to synthetic data.

Parameters:y (ndarray) – Array of synthetic data
Returns:Array of data with noise added
add_relative_noise(y, max_noise=5.0)[source]

Add relative random noise to synthetic data. The maximum noise level is given in percents.

An array of noise in the interval [-max_noise, max_noise] (continuous uniform distribution) is generated, and applied to the data the following way:

\(yn = y * (1. + noise / 100.)\)

Parameters:
  • y (ndarray) – Array of synthetic data
  • max_noise (float) – Maximum percentage of noise
Returns:

Array of data with noise added

silx.gui.utils.testutils