Source code for gwdetchar.plot

# coding=utf-8
# Copyright (C) Alex Urban (2019)
#
# This file is part of the GW DetChar python package.
#
# GW DetChar is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# GW DetChar is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with GW DetChar.  If not, see <http://www.gnu.org/licenses/>.

"""Plotting utilities
"""

from matplotlib import rcParams

from gwpy.plot.tex import label_to_latex

__author__ = 'Alex Urban <alexander.urban@ligo.org>'
__credits__ = 'Dan Hoak <daniel.hoak@ligo.org>, ' \
              'Duncan Macleod <duncan.macleod@ligo.org>'


# -- plotting utilities -------------------------------------------------------

[docs] def texify(text): """Helper utility to detect when LaTeX rendering is used, and convert text to a LaTeX-passable representation if necessary Parameters ---------- text : str text to convert to LaTeX representation Returns ------- out : str either a copy or LaTeX representation of `text` See Also -------- gwpy.plot.tex.label_to_latex the underlying method to convert to a LaTeX representation """ if rcParams['text.usetex']: return label_to_latex(text) return text or ''
[docs] def plot_segments(flag, span, facecolor='red', edgecolor='darkred', height=0.8, known={'alpha': 0.6, 'facecolor': 'lightgray', 'edgecolor': 'gray', 'height': 0.4}): """Plot the saturation segments contained within a flag """ name = texify(flag.name) plot = flag.plot( figsize=[12, 2], facecolor=facecolor, edgecolor=edgecolor, height=height, known=known, label=' ', xlim=span, xscale='auto-gps', epoch=span[0], title="{} segments".format(name), ) plot.subplots_adjust(bottom=0.4, top=0.8) return plot