<filename>solarforecastarbiter/plotting/tests/test_plotting_utils.py
import pandas as pd
from pandas.testing import assert_index_equal
import pytest


from matplotlib import cm
from matplotlib.colors import Normalize
from solarforecastarbiter.plotting import utils


@pytest.mark.parametrize('var,exp', [
    ('ghi', 'GHI (W/m^2)'),
    ('dc_power', 'DC Power (MW)')
])
def test_format_variable_name(var, exp):
    out = utils.format_variable_name(var)
    assert out == exp


@pytest.mark.parametrize('dobj,removal', [
    (pd.Series, slice(5, 10)),
    (pd.DataFrame, slice(12, 15))
])
def test_align_index(dobj, removal):
    index = pd.date_range(start='now', freq='5min',
                          periods=20, name='timestamp')
    data = dobj(index=index, dtype=float)
    data = data.drop(index[removal])
    out = utils.align_index(data, pd.Timedelta('5min'))
    assert_index_equal(out.index, index)


def test_align_index_new_length():
    index = pd.date_range(start='now', freq='5min',
                          periods=20, name='timestamp')
    data = pd.Series(index=index, dtype=float)
    out = utils.align_index(data, pd.Timedelta('1min'))
    nindex = pd.date_range(start=index[0], end=index[-1], freq='1min',
                           name='timestamp')
    assert_index_equal(out.index, nindex)


def test_align_index_limit():
    index = pd.date_range(start='now', freq='5min',
                          periods=20, name='timestamp')
    data = pd.Series(index=index, dtype=float)
    out = utils.align_index(data, pd.Timedelta('5min'),
                            limit=pd.Timedelta('60min'))
    nindex = pd.date_range(start=index[-13], end=index[-1], freq='5min',
                           name='timestamp')
    assert_index_equal(out.index, nindex)


@pytest.mark.parametrize('label,method', [
    ('instant', 'line'),
    ('beginning', 'step'),
    ('ending', 'step'),
    ('event', 'step'),
    pytest.param('other', '', marks=pytest.mark.xfail(raises=ValueError))
])
def test_line_or_step(label, method):
    out = utils.line_or_step(label)
    assert out[0] == method
    assert isinstance(out[1], dict)
    assert isinstance(out[2], dict)


@pytest.mark.parametrize('label', [
    'instant',
    'beginning',
    'ending',
    'event',
    pytest.param('other', marks=pytest.mark.xfail(raises=ValueError))
])
def test_line_or_step_plotly(label):
    out = utils.line_or_step_plotly(label)
    assert isinstance(out, dict)


color_map = cm.get_cmap('viridis')
color_scaler = cm.ScalarMappable(
    Normalize(vmin=0, vmax=1),
    color_map,
)


@pytest.mark.parametrize('percentile,expected', [
    (100, '#fde725'),
    (90, '#bddf26'),
    (50, '#21918c'),
    (20, '#414487'),
    (5, '#471365'),
    (1, '#450457'),
])
def test_distribution_fill_color(percentile, expected):
    assert utils.distribution_fill_color(color_scaler, percentile) == expected


@pytest.mark.parametrize('cvs,expected', [
    ([5, 20, 50, 80, 95], True),
    ([5.0, 20.0, 50.0, 80.0, 95.0], True),
    ([5.0, 50.0, 80.0, 95.0], False),
    ([5, 50, 8, 9], False),
    ([5, 10, 20, 30, 50, 60, 70, 75, 80, 90], False),
    ([5], False),
])
def test_percentiles_are_symmetric(cvs, expected):
    assert utils.percentiles_are_symmetric(cvs) == expected

<filename>solarforecastarbiter/plotting/tests/test_plotting_utils.py
import pandas as pd
from pandas.testing import assert_index_equal
import pytest


from matplotlib import cm
from matplotlib.colors import Normalize
from solarforecastarbiter.plotting import utils


@pytest.mark.parametrize('var,exp', [
    ('ghi', 'GHI (W/m^2)'),
    ('dc_power', 'DC Power (MW)')
])
def test_format_variable_name(var, exp):
    out = utils.format_variable_name(var)
    assert out == exp


@pytest.mark.parametrize('dobj,removal', [
    (pd.Series, slice(5, 10)),
    (pd.DataFrame, slice(12, 15))
])
def test_align_index(dobj, removal):
    index = pd.date_range(start='now', freq='5min',
                          periods=20, name='timestamp')
    data = dobj(index=index, dtype=float)
    data = data.drop(index[removal])
    out = utils.align_index(data, pd.Timedelta('5min'))
    assert_index_equal(out.index, index)


def test_align_index_new_length():
    index = pd.date_range(start='now', freq='5min',
                          periods=20, name='timestamp')
    data = pd.Series(index=index, dtype=float)
    out = utils.align_index(data, pd.Timedelta('1min'))
    nindex = pd.date_range(start=index[0], end=index[-1], freq='1min',
                           name='timestamp')
    assert_index_equal(out.index, nindex)


def test_align_index_limit():
    index = pd.date_range(start='now', freq='5min',
                          periods=20, name='timestamp')
    data = pd.Series(index=index, dtype=float)
    out = utils.align_index(data, pd.Timedelta('5min'),
                            limit=pd.Timedelta('60min'))
    nindex = pd.date_range(start=index[-13], end=index[-1], freq='5min',
                           name='timestamp')
    assert_index_equal(out.index, nindex)


@pytest.mark.parametrize('label,method', [
    ('instant', 'line'),
    ('beginning', 'step'),
    ('ending', 'step'),
    ('event', 'step'),
    pytest.param('other', '', marks=pytest.mark.xfail(raises=ValueError))
])
def test_line_or_step(label, method):
    out = utils.line_or_step(label)
    assert out[0] == method
    assert isinstance(out[1], dict)
    assert isinstance(out[2], dict)


@pytest.mark.parametrize('label', [
    'instant',
    'beginning',
    'ending',
    'event',
    pytest.param('other', marks=pytest.mark.xfail(raises=ValueError))
])
def test_line_or_step_plotly(label):
    out = utils.line_or_step_plotly(label)
    assert isinstance(out, dict)


color_map = cm.get_cmap('viridis')
color_scaler = cm.ScalarMappable(
    Normalize(vmin=0, vmax=1),
    color_map,
)


@pytest.mark.parametrize('percentile,expected', [
    (100, '#fde725'),
    (90, '#bddf26'),
    (50, '#21918c'),
    (20, '#414487'),
    (5, '#471365'),
    (1, '#450457'),
])
def test_distribution_fill_color(percentile, expected):
    assert utils.distribution_fill_color(color_scaler, percentile) == expected


@pytest.mark.parametrize('cvs,expected', [
    ([5, 20, 50, 80, 95], True),
    ([5.0, 20.0, 50.0, 80.0, 95.0], True),
    ([5.0, 50.0, 80.0, 95.0], False),
    ([5, 50, 8, 9], False),
    ([5, 10, 20, 30, 50, 60, 70, 75, 80, 90], False),
    ([5], False),
])
def test_percentiles_are_symmetric(cvs, expected):
    assert utils.percentiles_are_symmetric(cvs) == expected
