pygimli.viewer.pv#

Pyvista based drawing functions used by pygimli.viewer.

Overview#

Functions

drawMesh(ax, mesh[, notebook])

Draw a mesh into a given plotter.

drawModel([ax, mesh, data])

Draw a mesh with given data.

drawSensors(ax, sensors[, diam, color])

Draw the sensor positions to given mesh or the the one in given plotter.

drawSlice(ax, mesh[, normal])

Draw a slice in a 3D mesh for given pygimli mesh.

drawStreamLines(ax, mesh, data[, label, radius])

Draw streamlines of given data.

pgMesh2pvMesh(mesh[, data, label, boundaries])

pyGIMLi's mesh format is different from pyvista's needs, some preparation is necessary.

showMesh3D(mesh, data, **kwargs)

Calling the defined function to show the 3D object.

toPVMesh(mesh[, data, label, boundaries])

pyGIMLi's mesh format is different from pyvista's needs, some preparation is necessary.

Functions#

pygimli.viewer.pv.drawMesh(ax, mesh, notebook=False, **kwargs)#

Draw a mesh into a given plotter.

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.

  • bc (pyvista color ['#EEEEEE']) – Background color.

  • style (str['surface']) – Possible options: “surface”, “wireframe”, “points”

  • label (str) – Data to be plotted. If None the first is taken.

Returns:

ax – The plotter

Return type:

pyvista.Plotter [optional]

Examples using pygimli.viewer.pv.drawMesh

3D surface ERT inversion

3D surface ERT inversion

3D gravity modelling and inversion

3D gravity modelling and inversion

3D magnetics modelling and inversion

3D magnetics modelling and inversion
pygimli.viewer.pv.drawModel(ax=None, mesh=None, data=None, **kwargs)#

Draw a 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 – The plotter

Return type:

pyvista.Plotter [optional]

pygimli.viewer.pv.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 – The plotter containing the mesh and drawn electrode positions.

Return type:

pyvista.Plotter

Examples using pygimli.viewer.pv.drawSensors

Refraction in 3D

Refraction in 3D
pygimli.viewer.pv.drawSlice(ax, mesh, normal=[1, 0, 0], **kwargs)#

Draw a slice in a 3D mesh for given pygimli mesh.

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.

  • Keyword arguments passed to pyvista.slice

  • —————————————–

  • normal ([float, float, float] | str) – normal vector constructing the slice

  • origin ([float, float, float]) – origin for the slice (by default mesh center)

  • generate_triangles (bool [False]) – generate triangle mesh

  • contour (bool [False]) – draw contours instead

  • Keyword arguments passed to pyvista.add_mesh

  • ——————————————–

  • cmap|cMap (str [None]) – colormap

  • log_scale|logScale (bool [False]) – use logarithmic colormap scaling

  • clim ([float, float]) – color limits as tuple/list

  • cMin, cMax (float) – color limits in pg style

  • More information at

  • https (//docs.pyvista.org/api/core/_autosummary/pyvista.CompositeFilters.slice.html)

Examples using pygimli.viewer.pv.drawSlice

3D Darcy flow

3D Darcy flow
pygimli.viewer.pv.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 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: https://docs.pyvista.org/api/core/_autosummary/pyvista.DataSetFilters.streamlines.html

Examples using pygimli.viewer.pv.drawStreamLines

3D Darcy flow

3D Darcy flow
pygimli.viewer.pv.pgMesh2pvMesh(mesh, data=None, label=None, boundaries=False)[source]#

pyGIMLi’s mesh format is different from pyvista’s needs, some preparation is necessary.

Parameters:

  • mesh (pg.Mesh) – Structure generated by pyGIMLi to display.

  • data (iterable) – Parameter to distribute to cells/nodes.

pygimli.viewer.pv.showMesh3D(mesh, data, **kwargs)[source]#

Calling the defined function to show the 3D object.

pygimli.viewer.pv.toPVMesh(mesh, data=None, label=None, boundaries=False)#

pyGIMLi’s mesh format is different from pyvista’s needs, some preparation is necessary.

Parameters:

  • mesh (pg.Mesh) – Structure generated by pyGIMLi to display.

  • data (iterable) – Parameter to distribute to cells/nodes.