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