Source code for holoviews.plotting.mpl.renderer

import sys
import base64
from io import BytesIO
from tempfile import NamedTemporaryFile
from contextlib import contextmanager
from itertools import chain
from distutils.version import LooseVersion

import matplotlib as mpl
from matplotlib import pyplot as plt
from param.parameterized import bothmethod

import param
from ...core import HoloMap
from ...core.options import Store

from ..renderer import Renderer, MIME_TYPES, HTML_TAGS
from .widgets import MPLSelectionWidget, MPLScrubberWidget
from .util import get_tight_bbox

class OutputWarning(param.Parameterized):pass
outputwarning = OutputWarning(name='Warning')

mpl_msg_handler = """
/* Backend specific body of the msg_handler, updates displayed frame */
var target = $('#fig_{plot_id}');
var img = $('<div />').html(msg);
target.children().each(function () {{ $(this).remove() }})

# <format name> : (animation writer, format,  anim_kwargs, extra_args)
    'webm': ('ffmpeg', 'webm', {},
             ['-vcodec', 'libvpx-vp9', '-b', '1000k']),
    'mp4': ('ffmpeg', 'mp4', {'codec': 'libx264'},
            ['-pix_fmt', 'yuv420p']),
    'gif': ('imagemagick', 'gif', {'fps': 10}, []),
    'scrubber': ('html', None, {'fps': 5}, None)

if LooseVersion(mpl.__version__) >= '2.2':
    ANIMATION_OPTS['gif'] = ('pillow', 'gif', {'fps': 10}, [])

[docs]class MPLRenderer(Renderer): """ Exporter used to render data from matplotlib, either to a stream or directly to file. The __call__ method renders an HoloViews component to raw data of a specified matplotlib format. The save method is the corresponding method for saving a HoloViews objects to disk. The save_fig and save_anim methods are used to save matplotlib figure and animation objects. These match the two primary return types of plotting class implemented with matplotlib. """ drawn = {} backend = param.String('matplotlib', doc="The backend name.") dpi=param.Integer(72, doc=""" The render resolution in dpi (dots per inch)""") fig = param.ObjectSelector(default='auto', objects=['png', 'svg', 'pdf', 'html', None, 'auto'], doc=""" Output render format for static figures. If None, no figure rendering will occur. """) holomap = param.ObjectSelector(default='auto', objects=['widgets', 'scrubber', 'webm','mp4', 'gif', None, 'auto'], doc=""" Output render multi-frame (typically animated) format. If None, no multi-frame rendering will occur.""") interactive = param.Boolean(default=False, doc=""" Whether to enable interactive plotting allowing interactive plotting with explicitly calling show.""") mode = param.ObjectSelector(default='default', objects=['default']) mode_formats = {'fig': {'default': ['png', 'svg', 'pdf', 'html', None, 'auto']}, 'holomap': {'default': ['widgets', 'scrubber', 'webm','mp4', 'gif', 'html', None, 'auto']}} counter = 0 # Define appropriate widget classes widgets = {'scrubber': MPLScrubberWidget, 'widgets': MPLSelectionWidget} # Define the handler for updating matplotlib plots comm_msg_handler = mpl_msg_handler def __call__(self, obj, fmt='auto'): """ Render the supplied HoloViews component or MPLPlot instance using matplotlib. """ plot, fmt = self._validate(obj, fmt) if plot is None: return if isinstance(plot, tuple(self.widgets.values())): data = plot() else: with mpl.rc_context(rc=plot.fig_rcparams): data = self._figure_data(plot, fmt, **({'dpi':self.dpi} if self.dpi else {})) data = self._apply_post_render_hooks(data, obj, fmt) return data, {'file-ext':fmt, 'mime_type':MIME_TYPES[fmt]}
[docs] def show(self, obj): """ Renders the supplied object and displays it using the active GUI backend. """ if self.interactive: if isinstance(obj, list): return [self.get_plot(o) for o in obj] return self.get_plot(obj) from .plot import MPLPlot MPLPlot._close_figures = False try: plots = [] objects = obj if isinstance(obj, list) else [obj] for o in objects: plots.append(self.get_plot(o)) except: MPLPlot._close_figures = True raise MPLPlot._close_figures = True return plots[0] if len(plots) == 1 else plots
[docs] @classmethod def plot_options(cls, obj, percent_size): """ Given a holoviews object and a percentage size, apply heuristics to compute a suitable figure size. For instance, scaling layouts and grids linearly can result in unwieldy figure sizes when there are a large number of elements. As ad hoc heuristics are used, this functionality is kept separate from the plotting classes themselves. Used by the IPython Notebook display hooks and the save utility. Note that this can be overridden explicitly per object using the fig_size and size plot options. """ from .plot import MPLPlot factor = percent_size / 100.0 obj = obj.last if isinstance(obj, HoloMap) else obj options = Store.lookup_options(cls.backend, obj, 'plot').options fig_size = options.get('fig_size', MPLPlot.fig_size)*factor return dict({'fig_size':fig_size}, **MPLPlot.lookup_options(obj, 'plot').options)
@bothmethod def get_size(self_or_cls, plot): w, h = plot.state.get_size_inches() dpi = self_or_cls.dpi if self_or_cls.dpi else plot.state.dpi return (int(w*dpi), int(h*dpi))
[docs] def diff(self, plot): """ Returns the latest plot data to update an existing plot. """ if self.fig == 'auto': figure_format = self.params('fig').objects[0] else: figure_format = self.fig return self.html(plot, figure_format)
def _figure_data(self, plot, fmt='png', bbox_inches='tight', as_script=False, **kwargs): """ Render matplotlib figure object and return the corresponding data. If as_script is True, the content will be split in an HTML and a JS component. Similar to IPython.core.pylabtools.print_figure but without any IPython dependency. """ if fmt in ['gif', 'mp4', 'webm']: if sys.version_info[0] == 3 and mpl.__version__[:-2] in ['1.2', '1.3']: raise Exception("<b>Python 3 matplotlib animation support broken &lt;= 1.3</b>") with mpl.rc_context(rc=plot.fig_rcparams): anim = plot.anim(fps=self.fps) data = self._anim_data(anim, fmt) else: fig = plot.state traverse_fn = lambda x: x.handles.get('bbox_extra_artists', None) extra_artists = list(chain(*[artists for artists in plot.traverse(traverse_fn) if artists is not None])) kw = dict( format=fmt, facecolor=fig.get_facecolor(), edgecolor=fig.get_edgecolor(), dpi=self.dpi, bbox_inches=bbox_inches, bbox_extra_artists=extra_artists ) kw.update(kwargs) # Attempts to precompute the tight bounding box try: kw = self._compute_bbox(fig, kw) except: pass bytes_io = BytesIO() fig.canvas.print_figure(bytes_io, **kw) data = bytes_io.getvalue() if as_script: b64 = base64.b64encode(data).decode("utf-8") (mime_type, tag) = MIME_TYPES[fmt], HTML_TAGS[fmt] src = HTML_TAGS['base64'].format(mime_type=mime_type, b64=b64) html = tag.format(src=src, mime_type=mime_type, css='') return html, '' if fmt == 'svg': data = data.decode('utf-8') return data def _anim_data(self, anim, fmt): """ Render a matplotlib animation object and return the corresponding data. """ (writer, _, anim_kwargs, extra_args) = ANIMATION_OPTS[fmt] if extra_args != []: anim_kwargs = dict(anim_kwargs, extra_args=extra_args) if self.fps is not None: anim_kwargs['fps'] = max([int(self.fps), 1]) if self.dpi is not None: anim_kwargs['dpi'] = self.dpi if not hasattr(anim, '_encoded_video'): with NamedTemporaryFile(suffix='.%s' % fmt) as f:, writer=writer, **anim_kwargs) video = open(, "rb").read() return video def _compute_bbox(self, fig, kw): """ Compute the tight bounding box for each figure once, reducing number of required canvas draw calls from N*2 to N+1 as a function of the number of frames. Tight bounding box computing code here mirrors: matplotlib.backend_bases.FigureCanvasBase.print_figure as it hasn't been factored out as a function. """ fig_id = id(fig) if kw['bbox_inches'] == 'tight': if not fig_id in MPLRenderer.drawn: fig.set_dpi(self.dpi) fig.canvas.draw() extra_artists = kw.pop("bbox_extra_artists", []) pad = mpl.rcParams['savefig.pad_inches'] bbox_inches = get_tight_bbox(fig, extra_artists, pad=pad) MPLRenderer.drawn[fig_id] = bbox_inches kw['bbox_inches'] = bbox_inches else: kw['bbox_inches'] = MPLRenderer.drawn[fig_id] return kw @classmethod @contextmanager def state(cls): try: cls._rcParams = dict(mpl.rcParams) yield finally: mpl.rcParams.clear() mpl.rcParams.update(cls._rcParams)
[docs] @classmethod def load_nb(cls, inline=True): """ Initialize matplotlib backend """ import matplotlib.pyplot as plt backend = plt.get_backend() if backend not in ['agg', 'module://ipykernel.pylab.backend_inline']: plt.switch_backend('agg')