Source code for pygimli.viewer.pv.drawer

import numpy as np

import pygimli as pg

from .utils import pgMesh2pvMesh

pv = pg.optImport('pyvista', requiredFor="properly visualize 3D data")

[docs]def drawMesh(ax, mesh, notebook=False, **kwargs): """ Parameters ---------- ax: pyvista.Plotter [optional] The plotter to draw everything. If none is given, one will be created. mesh: pg.Mesh The mesh to show. notebook: bool [False] Sets the plotter up for jupyter notebook/lab. cmap: str ['viridis'] The colormap string. Returns ------- ax: pyvista.Plotter [optional] The plotter """ # sort out a few kwargs to not confuse the plotter initialization show_edges = kwargs.pop('show_edges', True) opacity = kwargs.pop('alpha', 1) cmap = kwargs.pop('cmap', None) color = kwargs.pop('color', 'k') style = kwargs.pop('style', 'wireframe') returnActor = kwargs.pop('returnActor', False) if ax is None: # if notebook: # ax = pv.PlotterITK(**kwargs) # else: ax = pv.Plotter(notebook=notebook, **kwargs) ax.show_bounds(all_edges=True, minor_ticks=True) ax.add_axes() if isinstance(mesh, pg.Mesh): mesh = pgMesh2pvMesh(mesh) _actor = ax.add_mesh( mesh, # type: pv.UnstructuredGrid cmap=cmap, color=color, style=style, show_edges=show_edges, opacity=opacity, ) if returnActor: return ax, _actor else: return ax
[docs]def drawModel(ax=None, mesh=None, data=None, **kwargs): """ Draw the mesh with given data. Parameters ---------- ax: pyvista.Plotter [None] Pyvista's basic Plotter to add the mesh to. mesh: pg.Mesh The Mesh to plot. data: iterable Data that should be displayed with the mesh. Returns ------- ax: pyvista.Plotter [optional] The plotter """ if all(v is None for v in [ax, mesh, data]): pg.critical("At least mesh or data should not be None") return None if data is not None or len(mesh.dataMap()) != 0: kwargs['style'] = 'surface' kwargs['color'] = None mesh = pgMesh2pvMesh(mesh, data, kwargs.pop('label', None)) if 'cmap' not in kwargs: kwargs['cmap'] = 'viridis' return drawMesh(ax, mesh, **kwargs)
[docs]def drawSensors(ax, sensors, diam=0.01, color='grey', **kwargs): """ Draw the sensor positions to given mesh or the the one in given plotter. Parameters ---------- ax: pyvista.Plotter The plotter to draw everything. If none is given, one will be created. sensors: iterable Array-like object containing tuple-like (x, y, z) positions. diam: float [0.01] Radius of sphere markers. color: str ['grey'] Color of sphere markers. Returns ------- ax: pyvista.Plotter The plotter containing the mesh and drawn electrode positions. """ for pos in sensors: s = pv.Sphere(radius=diam / 2, center=pos) ax.add_mesh(s, color=color, **kwargs) return ax
[docs]def drawSlice(ax, mesh, normal=[1, 0, 0], **kwargs): """ Parameters ---------- ax: pyvista.Plotter The Plotter to draw on. mesh: pg.Mesh The mesh to take the slice out of. normal: list [[1, 0, 0]] Coordinates to orientate the slice. Returns ------- ax: pyvista.Plotter The plotter containing the mesh and drawn electrode positions. Note ---- Possible kwargs are: normal: tuple(float), str origin: tuple(float) generate_triangles: bool, optional contour: bool, optional They can be found at """ label = kwargs.pop('label', None) data = kwargs.pop('data', None) mesh = pgMesh2pvMesh(mesh, data, label) try: single_slice = mesh.slice(normal, **kwargs) except AssertionError as e: # 'contour' kwarg only works with point data and breaks execution pg.error(e) else: # REVIEW: bounds and axes might be confused with the outline..?! outline = mesh.outline() ax.add_mesh(outline, color="k") ax.add_mesh(single_slice) return ax
[docs]def drawStreamLines(ax, mesh, data, label=None, radius=0.01, **kwargs): """ Draw streamlines of given data. PyVista streamline needs a vector field of gradient data per cell. Parameters ---------- ax: pyvista.Plotter [None] The plotter that should be used for visualization. mesh: pyvista.UnstructuredGrid|pg.Mesh [None] Structure to plot the streamlines in to. If its a pv grid a check is performed if the data set is already contained. data: iterable [None] Values used for streamlining. label: str Label for the data set. Will be searched for within the data. radius: float [0.01] Radius for the streamline tubes. Note ---- All kwargs will be forwarded to pyvistas streamline filter: """ if isinstance(mesh, pg.Mesh): # create gradient of cell data if not provided if np.ndim(data) == 1: grad = pg.solver.grad(mesh, data) else: grad = data # ensure that it's point/node data in the mesh if len(grad) == mesh.cellCount(): grad = pg.meshtools.cellDataToNodeData(mesh, grad) # add data to the mesh and convert to pyvista grid mesh = pgMesh2pvMesh(mesh, grad.T, label) elif isinstance(mesh, pv.UnstructuredGrid): if label not in mesh.point_arrays: # conversion needed mesh.cell_data_to_point_data() if label is None: label = list(mesh.point_arrays.keys())[0] kwargs['vectors'] = label streamlines = mesh.streamlines(**kwargs) ax.add_mesh(