Source code for silx.test.utils
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"""Utilities for writing tests.
- :func:`temp_dir` provides a with context to create/delete a temporary
directory.
"""
__authors__ = ["T. Vincent"]
__license__ = "MIT"
__date__ = "03/01/2019"
import sys
import contextlib
import os
import numpy
import shutil
import tempfile
from ..resources import ExternalResources
utilstest = ExternalResources(
project="silx",
url_base="http://www.silx.org/pub/silx/",
env_key="SILX_DATA",
timeout=60,
)
"This is the instance to be used. Singleton-like feature provided by module"
class _TestOptions(object):
def __init__(self):
self.WITH_QT_TEST = True
"""Qt tests are included"""
self.WITH_QT_TEST_REASON = ""
"""Reason for Qt tests are disabled if any"""
self.WITH_OPENCL_TEST = True
"""OpenCL tests are included"""
self.WITH_OPENCL_TEST_REASON = ""
"""Reason for OpenCL tests are disabled if any"""
self.WITH_GL_TEST = True
"""OpenGL tests are included"""
self.WITH_GL_TEST_REASON = ""
"""Reason for OpenGL tests are disabled if any"""
self.TEST_LOW_MEM = False
"""Skip tests using too much memory"""
self.TEST_LOW_MEM_REASON = ""
"""Reason for low_memory tests are disabled if any"""
def configure(self, parsed_options=None):
"""Configure the TestOptions class from the command line arguments and the
environment variables
"""
if parsed_options is not None and not parsed_options.gui:
self.WITH_QT_TEST = False
self.WITH_QT_TEST_REASON = "Skipped by command line"
elif os.environ.get("WITH_QT_TEST", "True") == "False":
self.WITH_QT_TEST = False
self.WITH_QT_TEST_REASON = "Skipped by WITH_QT_TEST env var"
elif sys.platform.startswith("linux") and not os.environ.get("DISPLAY", ""):
self.WITH_QT_TEST = False
self.WITH_QT_TEST_REASON = "DISPLAY env variable not set"
if parsed_options is not None and not parsed_options.opencl:
self.WITH_OPENCL_TEST_REASON = "Skipped by command line"
self.WITH_OPENCL_TEST = False
elif os.environ.get("SILX_OPENCL", "True") == "False":
self.WITH_OPENCL_TEST_REASON = "Skipped by SILX_OPENCL env var"
self.WITH_OPENCL_TEST = False
if not self.WITH_OPENCL_TEST:
# That's an easy way to skip OpenCL tests
# It disable the use of OpenCL on the full silx project
os.environ["SILX_OPENCL"] = "False"
if parsed_options is not None and not parsed_options.opengl:
self.WITH_GL_TEST = False
self.WITH_GL_TEST_REASON = "Skipped by command line"
elif os.environ.get("WITH_GL_TEST", "True") == "False":
self.WITH_GL_TEST = False
self.WITH_GL_TEST_REASON = "Skipped by WITH_GL_TEST env var"
elif sys.platform.startswith("linux") and not os.environ.get("DISPLAY", ""):
self.WITH_GL_TEST = False
self.WITH_GL_TEST_REASON = "DISPLAY env variable not set"
else:
try:
import OpenGL
except ImportError:
self.WITH_GL_TEST = False
self.WITH_GL_TEST_REASON = "OpenGL package not available"
if parsed_options is not None and parsed_options.low_mem:
self.TEST_LOW_MEM = True
self.TEST_LOW_MEM_REASON = "Skipped by command line"
elif os.environ.get("SILX_TEST_LOW_MEM", "True") == "False":
self.TEST_LOW_MEM = True
self.TEST_LOW_MEM_REASON = "Skipped by SILX_TEST_LOW_MEM env var"
if self.WITH_QT_TEST:
try:
from silx.gui import qt
except ImportError:
self.WITH_QT_TEST = False
self.WITH_QT_TEST_REASON = "Qt is not installed"
else:
if sys.platform == "win32" and qt.qVersion() == "5.9.2":
self.SKIP_TEST_FOR_ISSUE_936 = True
# Temporary directory context #################################################
[docs]
@contextlib.contextmanager
def temp_dir():
"""with context providing a temporary directory.
>>> import os.path
>>> with temp_dir() as tmp:
... print(os.path.isdir(tmp)) # Use tmp directory
"""
tmp_dir = tempfile.mkdtemp()
try:
yield tmp_dir
finally:
shutil.rmtree(tmp_dir)
# Synthetic data and random noise #############################################
[docs]
def add_gaussian_noise(y, stdev=1.0, mean=0.0):
"""Add random gaussian noise to synthetic data.
:param ndarray y: Array of synthetic data
:param float mean: Mean of the gaussian distribution of noise.
:param float stdev: Standard deviation of the gaussian distribution of
noise.
:return: Array of data with noise added
"""
noise = numpy.random.normal(mean, stdev, size=y.size)
noise.shape = y.shape
return y + noise
[docs]
def add_poisson_noise(y):
"""Add random noise from a poisson distribution to synthetic data.
:param ndarray y: Array of synthetic data
:return: Array of data with noise added
"""
yn = numpy.random.poisson(y)
yn.shape = y.shape
return yn
[docs]
def add_relative_noise(y, max_noise=5.0):
"""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:
:math:`yn = y * (1. + noise / 100.)`
:param ndarray y: Array of synthetic data
:param float max_noise: Maximum percentage of noise
:return: Array of data with noise added
"""
noise = max_noise * (2 * numpy.random.random(size=y.size) - 1)
noise.shape = y.shape
return y * (1.0 + noise / 100.0)
