Source code for pymor.gui.jupyter

# This file is part of the pyMOR project (
# Copyright 2013-2018 pyMOR developers and contributors. All rights reserved.
# License: BSD 2-Clause License (

"""This module provides plotting support inside the Jupyter notebook.

To use these routines you first have to execute ::

        %matplotlib notebook

inside the given notebook.

import numpy as np

from pymor.core.config import config
from pymor.gui.matplotlib import MatplotlibPatchAxes
from pymor.vectorarrays.interfaces import VectorArrayInterface

[docs]def visualize_patch(grid, U, bounding_box=([0, 0], [1, 1]), codim=2, title=None, legend=None, separate_colorbars=False, rescale_colorbars=False, columns=2): """Visualize scalar data associated to a two-dimensional |Grid| as a patch plot. The grid's |ReferenceElement| must be the triangle or square. The data can either be attached to the faces or vertices of the grid. Parameters ---------- grid The underlying |Grid|. U |VectorArray| of the data to visualize. If `len(U) > 1`, the data is visualized as a time series of plots. Alternatively, a tuple of |VectorArrays| can be provided, in which case a subplot is created for each entry of the tuple. The lengths of all arrays have to agree. bounding_box A bounding box in which the grid is contained. codim The codimension of the entities the data in `U` is attached to (either 0 or 2). title Title of the plot. legend Description of the data that is plotted. Most useful if `U` is a tuple in which case `legend` has to be a tuple of strings of the same length. separate_colorbars If `True`, use separate colorbars for each subplot. rescale_colorbars If `True`, rescale colorbars to data in each frame. columns The number of columns in the visualizer GUI in case multiple plots are displayed at the same time. """ assert isinstance(U, VectorArrayInterface) \ or (isinstance(U, tuple) and all(isinstance(u, VectorArrayInterface) for u in U) and all(len(u) == len(U[0]) for u in U)) U = (U.to_numpy().astype(np.float64, copy=False),) if isinstance(U, VectorArrayInterface) else \ tuple(u.to_numpy().astype(np.float64, copy=False) for u in U) if not config.HAVE_MATPLOTLIB: raise ImportError('cannot visualize: import of matplotlib failed') if not config.HAVE_IPYWIDGETS and len(U[0]) > 1: raise ImportError('cannot visualize: import of ipywidgets failed') if isinstance(legend, str): legend = (legend,) assert legend is None or isinstance(legend, tuple) and len(legend) == len(U) if len(U) < 2: columns = 1 class Plot: def __init__(self): if separate_colorbars: if rescale_colorbars: self.vmins = tuple(np.min(u[0]) for u in U) self.vmaxs = tuple(np.max(u[0]) for u in U) else: self.vmins = tuple(np.min(u) for u in U) self.vmaxs = tuple(np.max(u) for u in U) else: if rescale_colorbars: self.vmins = (min(np.min(u[0]) for u in U),) * len(U) self.vmaxs = (max(np.max(u[0]) for u in U),) * len(U) else: self.vmins = (min(np.min(u) for u in U),) * len(U) self.vmaxs = (max(np.max(u) for u in U),) * len(U) import matplotlib.pyplot as plt rows = int(np.ceil(len(U) / columns)) self.figure = figure = plt.figure() self.plots = plots = [] axes = [] for i, (vmin, vmax) in enumerate(zip(self.vmins, self.vmaxs)): ax = figure.add_subplot(rows, columns, i+1) axes.append(ax) plots.append(MatplotlibPatchAxes(figure, grid, bounding_box=bounding_box, vmin=vmin, vmax=vmax, codim=codim, colorbar=separate_colorbars)) if legend: ax.set_title(legend[i]) plt.tight_layout() if not separate_colorbars: figure.colorbar(plots[0].p, ax=axes) def set(self, U, ind): if rescale_colorbars: if separate_colorbars: self.vmins = tuple(np.min(u[ind]) for u in U) self.vmaxs = tuple(np.max(u[ind]) for u in U) else: self.vmins = (min(np.min(u[ind]) for u in U),) * len(U) self.vmaxs = (max(np.max(u[ind]) for u in U),) * len(U) for u, plot, vmin, vmax in zip(U, self.plots, self.vmins, self.vmaxs): plot.set(u[ind], vmin=vmin, vmax=vmax) plot = Plot() plot.set(U, 0) if len(U[0]) > 1: from ipywidgets import interact, IntSlider def set_time(t): plot.set(U, t) interact(set_time, t=IntSlider(min=0, max=len(U[0])-1, step=1, value=0)) return plot