A PyQT GUI application for converting InfoLease report outputs into Excel files. Handles parsing and summarizing. Learns where files are meant to be store and compiles monthly and yearly summaries.
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InfoLeaseExtract/venv/Lib/site-packages/pandas/tests/plotting/test_style.py

159 lines
5.1 KiB

import pytest
from pandas import Series
pytest.importorskip("matplotlib")
from pandas.plotting._matplotlib.style import get_standard_colors
pytestmark = pytest.mark.slow
class TestGetStandardColors:
@pytest.mark.parametrize(
"num_colors, expected",
[
(3, ["red", "green", "blue"]),
(5, ["red", "green", "blue", "red", "green"]),
(7, ["red", "green", "blue", "red", "green", "blue", "red"]),
(2, ["red", "green"]),
(1, ["red"]),
],
)
def test_default_colors_named_from_prop_cycle(self, num_colors, expected):
import matplotlib as mpl
from matplotlib.pyplot import cycler
mpl_params = {
"axes.prop_cycle": cycler(color=["red", "green", "blue"]),
}
with mpl.rc_context(rc=mpl_params):
result = get_standard_colors(num_colors=num_colors)
assert result == expected
@pytest.mark.parametrize(
"num_colors, expected",
[
(1, ["b"]),
(3, ["b", "g", "r"]),
(4, ["b", "g", "r", "y"]),
(5, ["b", "g", "r", "y", "b"]),
(7, ["b", "g", "r", "y", "b", "g", "r"]),
],
)
def test_default_colors_named_from_prop_cycle_string(self, num_colors, expected):
import matplotlib as mpl
from matplotlib.pyplot import cycler
mpl_params = {
"axes.prop_cycle": cycler(color="bgry"),
}
with mpl.rc_context(rc=mpl_params):
result = get_standard_colors(num_colors=num_colors)
assert result == expected
@pytest.mark.parametrize(
"num_colors, expected_name",
[
(1, ["C0"]),
(3, ["C0", "C1", "C2"]),
(
12,
[
"C0",
"C1",
"C2",
"C3",
"C4",
"C5",
"C6",
"C7",
"C8",
"C9",
"C0",
"C1",
],
),
],
)
def test_default_colors_named_undefined_prop_cycle(self, num_colors, expected_name):
import matplotlib as mpl
import matplotlib.colors as mcolors
with mpl.rc_context(rc={}):
expected = [mcolors.to_hex(x) for x in expected_name]
result = get_standard_colors(num_colors=num_colors)
assert result == expected
@pytest.mark.parametrize(
"num_colors, expected",
[
(1, ["red", "green", (0.1, 0.2, 0.3)]),
(2, ["red", "green", (0.1, 0.2, 0.3)]),
(3, ["red", "green", (0.1, 0.2, 0.3)]),
(4, ["red", "green", (0.1, 0.2, 0.3), "red"]),
],
)
def test_user_input_color_sequence(self, num_colors, expected):
color = ["red", "green", (0.1, 0.2, 0.3)]
result = get_standard_colors(color=color, num_colors=num_colors)
assert result == expected
@pytest.mark.parametrize(
"num_colors, expected",
[
(1, ["r", "g", "b", "k"]),
(2, ["r", "g", "b", "k"]),
(3, ["r", "g", "b", "k"]),
(4, ["r", "g", "b", "k"]),
(5, ["r", "g", "b", "k", "r"]),
(6, ["r", "g", "b", "k", "r", "g"]),
],
)
def test_user_input_color_string(self, num_colors, expected):
color = "rgbk"
result = get_standard_colors(color=color, num_colors=num_colors)
assert result == expected
@pytest.mark.parametrize(
"num_colors, expected",
[
(1, [(0.1, 0.2, 0.3)]),
(2, [(0.1, 0.2, 0.3), (0.1, 0.2, 0.3)]),
(3, [(0.1, 0.2, 0.3), (0.1, 0.2, 0.3), (0.1, 0.2, 0.3)]),
],
)
def test_user_input_color_floats(self, num_colors, expected):
color = (0.1, 0.2, 0.3)
result = get_standard_colors(color=color, num_colors=num_colors)
assert result == expected
@pytest.mark.parametrize(
"color, num_colors, expected",
[
("Crimson", 1, ["Crimson"]),
("DodgerBlue", 2, ["DodgerBlue", "DodgerBlue"]),
("firebrick", 3, ["firebrick", "firebrick", "firebrick"]),
],
)
def test_user_input_named_color_string(self, color, num_colors, expected):
result = get_standard_colors(color=color, num_colors=num_colors)
assert result == expected
@pytest.mark.parametrize("color", ["", [], (), Series([], dtype="object")])
def test_empty_color_raises(self, color):
with pytest.raises(ValueError, match="Invalid color argument"):
get_standard_colors(color=color, num_colors=1)
@pytest.mark.parametrize(
"color",
[
"bad_color",
("red", "green", "bad_color"),
(0.1,),
(0.1, 0.2),
(0.1, 0.2, 0.3, 0.4, 0.5), # must be either 3 or 4 floats
],
)
def test_bad_color_raises(self, color):
with pytest.raises(ValueError, match="Invalid color"):
get_standard_colors(color=color, num_colors=5)