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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

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