Source code for porespy.visualization._plots

import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d.art3d import Poly3DCollection

__all__ = [

[docs]def bar(results, h='pdf', **kwargs): # pragma: no cover r""" Convenience wrapper for matplotlib's ``bar``. This automatically: * fetches the ``bin_centers`` * fetches the bin heights from the specified ``h`` * sets the bin widths * sets the edges to black Parameters ---------- results : object The objects returned by various functions in the ``porespy.metrics`` submodule, such as ``chord_length_distribution``. h : str The value to use for bin heights. The default is ``pdf``, but ``cdf`` is another option. Depending on the function the named-tuple may have different options. kwargs : keyword arguments All other keyword arguments are passed to ``bar``, including ``edgecolor`` if you wish to overwrite the default black. Returns ------- fig: Matplotlib figure handle Examples -------- `Click here <>`_ to view online example. """ if 'edgecolor' not in kwargs: kwargs['edgecolor'] = 'k' fig =, height=getattr(results, h), width=results.bin_widths, **kwargs) xlab = [attr for attr in results.__dir__() if not attr.startswith('_')][0] plt.xlabel(xlab) plt.ylabel(h) return fig
[docs]def imshow(*im, ind=None, axis=None, **kwargs): # pragma: no cover r""" Convenience wrapper for matplotlib's ``imshow``. This automatically: * slices a 3D image in the middle of the last axis * uses a masked array to make 0's white * sets the origin to 'lower' so bottom-left corner is [0, 0] * disables interpolation Parameters ---------- im : ndarray The 2D or 3D image (or images) to show. If 2D then all other arguments are ignored. ind : int The slice to show if ``im`` is 3D. If not given then the middle of the image is used. axis : int The axis to show if ``im`` is 3D. If not given, then the last axis of the image is used, so an 'lower' slice is shown. **kwargs All other keyword arguments are passed to ``plt.imshow`` Note ---- ``im`` can also be a series of unnamed arguments, in which case all received images will be shown using ``subplot``. Examples -------- `Click here <>`_ to view online example. """ if 'origin' not in kwargs.keys(): kwargs['origin'] = 'lower' if 'interpolation' not in kwargs.keys(): kwargs['interpolation'] = 'none' if not isinstance(im, tuple): im = tuple([im]) for i, image in enumerate(im): if image.ndim == 3: if axis is None: axis = 2 if ind is None: ind = int(image.shape[axis]/2) image = image.take(indices=ind, axis=axis) image =, mask=image == 0) fig = plt.subplot(1, len(im), i+1) plt.imshow(image, **kwargs) return fig
[docs]def show_mesh(mesh): # pragma: no cover r""" Visualizes the mesh of a region as obtained by ``get_mesh`` function in the ``metrics`` submodule. Parameters ---------- mesh : tuple A mesh returned by ``skimage.measure.marching_cubes`` Returns ------- fig : Matplotlib figure A handle to a matplotlib 3D axis Examples -------- `Click here <>`_ to view online example. """ try: verts = mesh.vertices except AttributeError: verts = mesh.verts lim_max = np.amax(verts, axis=0) lim_min = np.amin(verts, axis=0) # Display resulting triangular mesh using Matplotlib. fig = plt.figure() ax = fig.add_subplot(111, projection='3d') # Fancy indexing: `verts[faces]` to generate a collection of triangles mesh = Poly3DCollection(verts[mesh.faces]) mesh.set_edgecolor('k') ax.add_collection3d(mesh) ax.set_xlabel("x-axis") ax.set_ylabel("y-axis") ax.set_zlabel("z-axis") ax.set_xlim(lim_min[0], lim_max[0]) ax.set_ylim(lim_min[1], lim_max[1]) ax.set_zlim(lim_min[2], lim_max[2]) return fig