"""
Global configuration and fixture setup for pytest.

This configuration depends on the :mod:`skg.tests.options` plugin.
"""

from errno import EEXIST
from os import makedirs
from os.path import join
from warnings import warn

import numpy as np
from pytest import fixture

from .noise import white_normal, white_triangular, white_uniform


@fixture(scope='session')
def plots(request):
    """
    Enables debugging for the fixtures/tests that care about it.

    This fixture will only be set to `True` if the `--plots`
    command-line option is set through the :mod:`skg.tests.options`
    plugin.
    """
    if request.config.getoption('--plots'):
        try:
            import matplotlib
            matplotlib.use('Agg')
            import matplotlib.pyplot
        except ImportError:
            warn('Unable to import matplotlib: '
                 'plotting will not be enabled.')
            return False

        try:
            makedirs(join(request.config.rootdir, '.skg_test'))
        except OSError as e:
            if e.errno != EEXIST:
                raise
        return True

    return False


@fixture(scope='session')
def quality_metric():
    """
    Sets up the quality metric dictionary before running all tests, and
    publishes to an HTML file when complete.
    """
    quality_metric = {}
    yield quality_metric
    # TODO: Publish as HTML page


@fixture(scope='module', params=[
    0x0000, #0x1111, 0x1234, 0xBEEF, 0xCAFE, 0xDEAD, 0xFFFF
])
def seed(request):
    """
    Sets the seed for in numpy.random.

    Return the seed value, so it can be used by plots as part of the
    label.
    """
    seed = request.param
    np.random.seed(seed)
    return seed


@fixture(scope='module', params=[
    white_normal, white_uniform, white_triangular
])
def noise_distribution(request):
    """
    A sequence of noise distribution types.

    All distribututions are implemented as functions that accept an
    amplitude and optionally the output size. The distributions are
    centered and symmetrical about zero.

    1. White Gaussian (normal) noise: amplitude is the standard
       deviation.
    2. Uniform noise: amplitude is the upper and lower bounds of the
       distribution.
    3. Triangular noise: amplitude is the upper and lower bounds of the
       distribution.
    """
    return request.param

"""
Global configuration and fixture setup for pytest.

This configuration depends on the :mod:`skg.tests.options` plugin.
"""

from errno import EEXIST
from os import makedirs
from os.path import join
from warnings import warn

import numpy as np
from pytest import fixture

from .noise import white_normal, white_triangular, white_uniform


@fixture(scope='session')
def plots(request):
    """
    Enables debugging for the fixtures/tests that care about it.

    This fixture will only be set to `True` if the `--plots`
    command-line option is set through the :mod:`skg.tests.options`
    plugin.
    """
    if request.config.getoption('--plots'):
        try:
            import matplotlib
            matplotlib.use('Agg')
            import matplotlib.pyplot
        except ImportError:
            warn('Unable to import matplotlib: '
                 'plotting will not be enabled.')
            return False

        try:
            makedirs(join(request.config.rootdir, '.skg_test'))
        except OSError as e:
            if e.errno != EEXIST:
                raise
        return True

    return False


@fixture(scope='session')
def quality_metric():
    """
    Sets up the quality metric dictionary before running all tests, and
    publishes to an HTML file when complete.
    """
    quality_metric = {}
    yield quality_metric
    # TODO: Publish as HTML page


@fixture(scope='module', params=[
    0x0000, #0x1111, 0x1234, 0xBEEF, 0xCAFE, 0xDEAD, 0xFFFF
])
def seed(request):
    """
    Sets the seed for in numpy.random.

    Return the seed value, so it can be used by plots as part of the
    label.
    """
    seed = request.param
    np.random.seed(seed)
    return seed


@fixture(scope='module', params=[
    white_normal, white_uniform, white_triangular
])
def noise_distribution(request):
    """
    A sequence of noise distribution types.

    All distribututions are implemented as functions that accept an
    amplitude and optionally the output size. The distributions are
    centered and symmetrical about zero.

    1. White Gaussian (normal) noise: amplitude is the standard
       deviation.
    2. Uniform noise: amplitude is the upper and lower bounds of the
       distribution.
    3. Triangular noise: amplitude is the upper and lower bounds of the
       distribution.
    """
    return request.param

Global configuration and fixture setup for pytest.  This configuration depends on the :mod:`skg.tests.options` plugin. Enables debugging for the fixtures/tests that care about it.      This fixture will only be set to `True` if the `--plots`     command-line option is set through the :mod:`skg.tests.options`     plugin. Sets up the quality metric dictionary before running all tests, and     publishes to an HTML file when complete. # TODO: Publish as HTML page #0x1111, 0x1234, 0xBEEF, 0xCAFE, 0xDEAD, 0xFFFF Sets the seed for in numpy.random.      Return the seed value, so it can be used by plots as part of the     label. A sequence of noise distribution types.      All distribututions are implemented as functions that accept an     amplitude and optionally the output size. The distributions are     centered and symmetrical about zero.      1. White Gaussian (normal) noise: amplitude is the standard        deviation.     2. Uniform noise: amplitude is the upper and lower bounds of the        distribution.     3. Triangular noise: amplitude is the upper and lower bounds of the        distribution.