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from dataclasses import dataclass
import numpy as np
import pandas as pd
import matplotlib as mpl
import pytest
from numpy.testing import assert_array_equal
from seaborn._marks.base import Mark, Mappable, resolve_color
class TestMappable:
def mark(self, **features):
@dataclass
class MockMark(Mark):
linewidth: float = Mappable(rc="lines.linewidth")
pointsize: float = Mappable(4)
color: str = Mappable("C0")
fillcolor: str = Mappable(depend="color")
alpha: float = Mappable(1)
fillalpha: float = Mappable(depend="alpha")
m = MockMark(**features)
return m
def test_repr(self):
assert str(Mappable(.5)) == "<0.5>"
assert str(Mappable("CO")) == "<'CO'>"
assert str(Mappable(rc="lines.linewidth")) == "<rc:lines.linewidth>"
assert str(Mappable(depend="color")) == "<depend:color>"
assert str(Mappable(auto=True)) == "<auto>"
def test_input_checks(self):
with pytest.raises(AssertionError):
Mappable(rc="bogus.parameter")
with pytest.raises(AssertionError):
Mappable(depend="nonexistent_feature")
def test_value(self):
val = 3
m = self.mark(linewidth=val)
assert m._resolve({}, "linewidth") == val
df = pd.DataFrame(index=pd.RangeIndex(10))
assert_array_equal(m._resolve(df, "linewidth"), np.full(len(df), val))
def test_default(self):
val = 3
m = self.mark(linewidth=Mappable(val))
assert m._resolve({}, "linewidth") == val
df = pd.DataFrame(index=pd.RangeIndex(10))
assert_array_equal(m._resolve(df, "linewidth"), np.full(len(df), val))
def test_rcparam(self):
param = "lines.linewidth"
val = mpl.rcParams[param]
m = self.mark(linewidth=Mappable(rc=param))
assert m._resolve({}, "linewidth") == val
df = pd.DataFrame(index=pd.RangeIndex(10))
assert_array_equal(m._resolve(df, "linewidth"), np.full(len(df), val))
def test_depends(self):
val = 2
df = pd.DataFrame(index=pd.RangeIndex(10))
m = self.mark(pointsize=Mappable(val), linewidth=Mappable(depend="pointsize"))
assert m._resolve({}, "linewidth") == val
assert_array_equal(m._resolve(df, "linewidth"), np.full(len(df), val))
m = self.mark(pointsize=val * 2, linewidth=Mappable(depend="pointsize"))
assert m._resolve({}, "linewidth") == val * 2
assert_array_equal(m._resolve(df, "linewidth"), np.full(len(df), val * 2))
def test_mapped(self):
values = {"a": 1, "b": 2, "c": 3}
def f(x):
return np.array([values[x_i] for x_i in x])
m = self.mark(linewidth=Mappable(2))
scales = {"linewidth": f}
assert m._resolve({"linewidth": "c"}, "linewidth", scales) == 3
df = pd.DataFrame({"linewidth": ["a", "b", "c"]})
expected = np.array([1, 2, 3], float)
assert_array_equal(m._resolve(df, "linewidth", scales), expected)
def test_color(self):
c, a = "C1", .5
m = self.mark(color=c, alpha=a)
assert resolve_color(m, {}) == mpl.colors.to_rgba(c, a)
df = pd.DataFrame(index=pd.RangeIndex(10))
cs = [c] * len(df)
assert_array_equal(resolve_color(m, df), mpl.colors.to_rgba_array(cs, a))
def test_color_mapped_alpha(self):
c = "r"
values = {"a": .2, "b": .5, "c": .8}
m = self.mark(color=c, alpha=Mappable(1))
scales = {"alpha": lambda s: np.array([values[s_i] for s_i in s])}
assert resolve_color(m, {"alpha": "b"}, "", scales) == mpl.colors.to_rgba(c, .5)
df = pd.DataFrame({"alpha": list(values.keys())})
# Do this in two steps for mpl 3.2 compat
expected = mpl.colors.to_rgba_array([c] * len(df))
expected[:, 3] = list(values.values())
assert_array_equal(resolve_color(m, df, "", scales), expected)
def test_color_scaled_as_strings(self):
colors = ["C1", "dodgerblue", "#445566"]
m = self.mark()
scales = {"color": lambda s: colors}
actual = resolve_color(m, {"color": pd.Series(["a", "b", "c"])}, "", scales)
expected = mpl.colors.to_rgba_array(colors)
assert_array_equal(actual, expected)
def test_fillcolor(self):
c, a = "green", .8
fa = .2
m = self.mark(
color=c, alpha=a,
fillcolor=Mappable(depend="color"), fillalpha=Mappable(fa),
)
assert resolve_color(m, {}) == mpl.colors.to_rgba(c, a)
assert resolve_color(m, {}, "fill") == mpl.colors.to_rgba(c, fa)
df = pd.DataFrame(index=pd.RangeIndex(10))
cs = [c] * len(df)
assert_array_equal(resolve_color(m, df), mpl.colors.to_rgba_array(cs, a))
assert_array_equal(
resolve_color(m, df, "fill"), mpl.colors.to_rgba_array(cs, fa)
)
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