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CLN: Matplotlib imports in style #58921

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Merged
merged 2 commits into from
Jun 4, 2024
Merged

CLN: Matplotlib imports in style #58921

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91ba54e
Use import_optional_dependency in style.py
mroeschke Jun 2, 2024
7c51285
Merge remote-tracking branch 'upstream/main' into cln/matplotlib/style
mroeschke Jun 4, 2024
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150 changes: 67 additions & 83 deletions pandas/io/formats/style.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4,7 +4,6 @@

from __future__ import annotations

from contextlib import contextmanager
import copy
from functools import partial
import operator
Expand Down Expand Up @@ -56,7 +55,6 @@

if TYPE_CHECKING:
from collections.abc import (
Generator,
Hashable,
Sequence,
)
Expand Down Expand Up @@ -84,22 +82,6 @@

from pandas import ExcelWriter

try:
import matplotlib as mpl
import matplotlib.pyplot as plt

has_mpl = True
except ImportError:
has_mpl = False


@contextmanager
def _mpl(func: Callable) -> Generator[tuple[Any, Any], None, None]:
if has_mpl:
yield plt, mpl
else:
raise ImportError(f"{func.__name__} requires matplotlib.")


####
# Shared Doc Strings
Expand Down Expand Up @@ -3832,61 +3814,61 @@ def _background_gradient(
else: # else validate gmap against the underlying data
gmap = _validate_apply_axis_arg(gmap, "gmap", float, data)

with _mpl(Styler.background_gradient) as (_, _matplotlib):
smin = np.nanmin(gmap) if vmin is None else vmin
smax = np.nanmax(gmap) if vmax is None else vmax
rng = smax - smin
# extend lower / upper bounds, compresses color range
norm = _matplotlib.colors.Normalize(smin - (rng * low), smax + (rng * high))
smin = np.nanmin(gmap) if vmin is None else vmin
smax = np.nanmax(gmap) if vmax is None else vmax
rng = smax - smin
_matplotlib = import_optional_dependency(
"matplotlib", extra="Styler.background_gradient requires matplotlib."
)
# extend lower / upper bounds, compresses color range
norm = _matplotlib.colors.Normalize(smin - (rng * low), smax + (rng * high))

if cmap is None:
rgbas = _matplotlib.colormaps[_matplotlib.rcParams["image.cmap"]](norm(gmap))
else:
rgbas = _matplotlib.colormaps.get_cmap(cmap)(norm(gmap))

def relative_luminance(rgba) -> float:
"""
Calculate relative luminance of a color.

The calculation adheres to the W3C standards
(https://www.w3.org/WAI/GL/wiki/Relative_luminance)

Parameters
----------
color : rgb or rgba tuple

Returns
-------
float
The relative luminance as a value from 0 to 1
"""
r, g, b = (
x / 12.92 if x <= 0.04045 else ((x + 0.055) / 1.055) ** 2.4
for x in rgba[:3]
)
return 0.2126 * r + 0.7152 * g + 0.0722 * b

if cmap is None:
rgbas = _matplotlib.colormaps[_matplotlib.rcParams["image.cmap"]](
norm(gmap)
def css(rgba, text_only) -> str:
if not text_only:
dark = relative_luminance(rgba) < text_color_threshold
text_color = "#f1f1f1" if dark else "#000000"
return (
f"background-color: {_matplotlib.colors.rgb2hex(rgba)};"
f"color: {text_color};"
)
else:
rgbas = _matplotlib.colormaps.get_cmap(cmap)(norm(gmap))

def relative_luminance(rgba) -> float:
"""
Calculate relative luminance of a color.

The calculation adheres to the W3C standards
(https://www.w3.org/WAI/GL/wiki/Relative_luminance)

Parameters
----------
color : rgb or rgba tuple

Returns
-------
float
The relative luminance as a value from 0 to 1
"""
r, g, b = (
x / 12.92 if x <= 0.04045 else ((x + 0.055) / 1.055) ** 2.4
for x in rgba[:3]
)
return 0.2126 * r + 0.7152 * g + 0.0722 * b

def css(rgba, text_only) -> str:
if not text_only:
dark = relative_luminance(rgba) < text_color_threshold
text_color = "#f1f1f1" if dark else "#000000"
return (
f"background-color: {_matplotlib.colors.rgb2hex(rgba)};"
f"color: {text_color};"
)
else:
return f"color: {_matplotlib.colors.rgb2hex(rgba)};"
return f"color: {_matplotlib.colors.rgb2hex(rgba)};"

if data.ndim == 1:
return [css(rgba, text_only) for rgba in rgbas]
else:
return DataFrame(
[[css(rgba, text_only) for rgba in row] for row in rgbas],
index=data.index,
columns=data.columns,
)
if data.ndim == 1:
return [css(rgba, text_only) for rgba in rgbas]
else:
return DataFrame(
[[css(rgba, text_only) for rgba in row] for row in rgbas],
index=data.index,
columns=data.columns,
)


def _highlight_between(
Expand Down Expand Up @@ -4124,20 +4106,22 @@ def css_calc(x, left: float, right: float, align: str, color: str | list | tuple
rgbas = None
if cmap is not None:
# use the matplotlib colormap input
with _mpl(Styler.bar) as (_, _matplotlib):
cmap = (
_matplotlib.colormaps[cmap]
if isinstance(cmap, str)
else cmap # assumed to be a Colormap instance as documented
)
norm = _matplotlib.colors.Normalize(left, right)
rgbas = cmap(norm(values))
if data.ndim == 1:
rgbas = [_matplotlib.colors.rgb2hex(rgba) for rgba in rgbas]
else:
rgbas = [
[_matplotlib.colors.rgb2hex(rgba) for rgba in row] for row in rgbas
]
_matplotlib = import_optional_dependency(
"matplotlib", extra="Styler.bar requires matplotlib."
)
cmap = (
_matplotlib.colormaps[cmap]
if isinstance(cmap, str)
else cmap # assumed to be a Colormap instance as documented
)
norm = _matplotlib.colors.Normalize(left, right)
rgbas = cmap(norm(values))
if data.ndim == 1:
rgbas = [_matplotlib.colors.rgb2hex(rgba) for rgba in rgbas]
else:
rgbas = [
[_matplotlib.colors.rgb2hex(rgba) for rgba in row] for row in rgbas
]

assert isinstance(align, str) # mypy: should now be in [left, right, mid, zero]
if data.ndim == 1:
Expand Down