AIM-PIbd-32-Kurbanova-A-A/aimenv/Lib/site-packages/matplotlib/mathtext.py

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2024-10-02 22:15:59 +04:00
r"""
A module for parsing a subset of the TeX math syntax and rendering it to a
Matplotlib backend.
For a tutorial of its usage, see :ref:`mathtext`. This
document is primarily concerned with implementation details.
The module uses pyparsing_ to parse the TeX expression.
.. _pyparsing: https://pypi.org/project/pyparsing/
The Bakoma distribution of the TeX Computer Modern fonts, and STIX
fonts are supported. There is experimental support for using
arbitrary fonts, but results may vary without proper tweaking and
metrics for those fonts.
"""
import functools
import logging
import matplotlib as mpl
from matplotlib import _api, _mathtext
from matplotlib.ft2font import LOAD_NO_HINTING
from matplotlib.font_manager import FontProperties
from ._mathtext import ( # noqa: reexported API
RasterParse, VectorParse, get_unicode_index)
_log = logging.getLogger(__name__)
get_unicode_index.__module__ = __name__
##############################################################################
# MAIN
class MathTextParser:
_parser = None
_font_type_mapping = {
'cm': _mathtext.BakomaFonts,
'dejavuserif': _mathtext.DejaVuSerifFonts,
'dejavusans': _mathtext.DejaVuSansFonts,
'stix': _mathtext.StixFonts,
'stixsans': _mathtext.StixSansFonts,
'custom': _mathtext.UnicodeFonts,
}
def __init__(self, output):
"""
Create a MathTextParser for the given backend *output*.
Parameters
----------
output : {"path", "agg"}
Whether to return a `VectorParse` ("path") or a
`RasterParse` ("agg", or its synonym "macosx").
"""
self._output_type = _api.check_getitem(
{"path": "vector", "agg": "raster", "macosx": "raster"},
output=output.lower())
def parse(self, s, dpi=72, prop=None, *, antialiased=None):
"""
Parse the given math expression *s* at the given *dpi*. If *prop* is
provided, it is a `.FontProperties` object specifying the "default"
font to use in the math expression, used for all non-math text.
The results are cached, so multiple calls to `parse`
with the same expression should be fast.
Depending on the *output* type, this returns either a `VectorParse` or
a `RasterParse`.
"""
# lru_cache can't decorate parse() directly because prop
# is mutable; key the cache using an internal copy (see
# text._get_text_metrics_with_cache for a similar case).
prop = prop.copy() if prop is not None else None
antialiased = mpl._val_or_rc(antialiased, 'text.antialiased')
return self._parse_cached(s, dpi, prop, antialiased)
@functools.lru_cache(50)
def _parse_cached(self, s, dpi, prop, antialiased):
from matplotlib.backends import backend_agg
if prop is None:
prop = FontProperties()
fontset_class = _api.check_getitem(
self._font_type_mapping, fontset=prop.get_math_fontfamily())
load_glyph_flags = {
"vector": LOAD_NO_HINTING,
"raster": backend_agg.get_hinting_flag(),
}[self._output_type]
fontset = fontset_class(prop, load_glyph_flags)
fontsize = prop.get_size_in_points()
if self._parser is None: # Cache the parser globally.
self.__class__._parser = _mathtext.Parser()
box = self._parser.parse(s, fontset, fontsize, dpi)
output = _mathtext.ship(box)
if self._output_type == "vector":
return output.to_vector()
elif self._output_type == "raster":
return output.to_raster(antialiased=antialiased)
def math_to_image(s, filename_or_obj, prop=None, dpi=None, format=None,
*, color=None):
"""
Given a math expression, renders it in a closely-clipped bounding
box to an image file.
Parameters
----------
s : str
A math expression. The math portion must be enclosed in dollar signs.
filename_or_obj : str or path-like or file-like
Where to write the image data.
prop : `.FontProperties`, optional
The size and style of the text.
dpi : float, optional
The output dpi. If not set, the dpi is determined as for
`.Figure.savefig`.
format : str, optional
The output format, e.g., 'svg', 'pdf', 'ps' or 'png'. If not set, the
format is determined as for `.Figure.savefig`.
color : str, optional
Foreground color, defaults to :rc:`text.color`.
"""
from matplotlib import figure
parser = MathTextParser('path')
width, height, depth, _, _ = parser.parse(s, dpi=72, prop=prop)
fig = figure.Figure(figsize=(width / 72.0, height / 72.0))
fig.text(0, depth/height, s, fontproperties=prop, color=color)
fig.savefig(filename_or_obj, dpi=dpi, format=format)
return depth