Source code for finesse.plotting.tools

import logging

from .style import use
from ..env import warn

LOGGER = logging.getLogger(__name__)

DEFAULT_FORMATS = ("svg",)


def _in_ipython():
    """Checks whether the current script is running under IPython.

    Returns
    -------
    bool
        True if __IPYTHON__ is defined, otherwise False.
    """
    try:
        __IPYTHON__
    except NameError:
        return False
    else:
        return True


[docs]def init(mode="display", dpi=None, fmts=None): """Sets up default plotting parameters for a desired display mode. Parameters ---------- mode : str Display mode to use, either 'display' or 'paper'. dpi : int, optional DPI (Dots per inch) to display and save figures with. Defaults to current setting. fmts : list of str, optional List of image formats to allow for display when running under IPython; defaults to :data:`.DEFAULT_FORMATS`. """ import matplotlib as mpl if fmts is None: fmts = DEFAULT_FORMATS if _in_ipython(): try: from IPython.display import set_matplotlib_formats ipy = get_ipython() try: ipy.magic("matplotlib inline") except KeyError: try: ipy.magic("matplotlib qt") except KeyError: warn("Could not set matplotlib backend. Tried inline and Qt.") finally: set_matplotlib_formats(*fmts) except NameError: pass # TODO (sjr) handle plotting options in user config if mode == "display": use(["default"]) elif mode == "paper": if not _in_ipython(): mpl.use("pgf") use(["default", "paper"]) else: raise (BaseException("Plotting mode must be either 'display' or 'paper'.")) if dpi is not None: dpi = int(dpi) mpl.rcParams.update({"figure.dpi": dpi}) mpl.rcParams.update({"savefig.dpi": dpi}) # always apply white background and remove transparency. Make plots readable # when using dark background/themes in jupyter notebooks and such mpl.rcParams.update( { "figure.facecolor": (1.0, 1.0, 1.0, 1.0), } # red with alpha = 30% )
[docs]def add_colorbar(im, **kwargs): """Adds a vertical color bar to an image plot. Parameters ---------- im : :class:`matplotlib.image.AxesImage` An image plot, e.g. return value of a call to ``plt.imshow()``. Returns ------- Handle to the colorbar. """ ## Credit to: https://joseph-long.com/writing/colorbars/ from mpl_toolkits.axes_grid1 import make_axes_locatable import matplotlib.pyplot as plt last_axes = plt.gca() ax = im.axes fig = ax.figure divider = make_axes_locatable(ax) cax = divider.append_axes("right", size="5%", pad=0.05) cbar = fig.colorbar(im, cax=cax, **kwargs) plt.sca(last_axes) return cbar