Note

This section is only a reference describing the function, please see the chapter on mlab: Python scripting for 3D plotting for an introduction to mlab and how to interact with and assemble the functions of mlab.

Please see the section on Running mlab scripts for instructions on running the examples.

Sources

array2d_source

mayavi.tools.pipeline.array2d_source(*args, **kwargs)

Creates structured 2D data from a 2D array.

Function signatures:

array2d_source(s, ...)
array2d_source(x, y, s, ...)
array2d_source(x, y, f, ...)

If 3 positional arguments are passed the last one must be an array s, or a callable, f, that returns an array. x and y give the coordinates of positions corresponding to the s values.

x and y can be 1D or 2D arrays (such as returned by numpy.ogrid or numpy.mgrid), but the points should be located on an orthogonal grid (possibly non-uniform). In other words, all the points sharing a same index in the s array need to have the same x or y value.

If only 1 array s is passed the x and y arrays are assumed to be made from the indices of arrays, and an uniformly-spaced data set is created.

Keyword arguments:

name:

the name of the vtk object created.

figure:

optionally, the figure on which to add the data source. If None, the source is not added to any figure, and will be added automatically by the modules or filters. If False, no figure will be created by modules or filters applied to the source: the source can only be used for testing, or numerical algorithms, not visualization.

mask:

Mask points specified in a boolean masking array.

builtin_image

mayavi.tools.pipeline.builtin_image(metadata=<mayavi.core.metadata.SourceMetadata object at 0x7f59defcf970>)

Create a vtk image data source

builtin_surface

mayavi.tools.pipeline.builtin_surface(metadata=<mayavi.core.metadata.SourceMetadata object at 0x7f59defcffb0>)

Create a vtk poly data source

chaco_file

mayavi.tools.pipeline.chaco_file(metadata=<mayavi.core.metadata.SourceMetadata object at 0x7f59c93eaca0>)

Open a Chaco file

grid_source

mayavi.tools.pipeline.grid_source(x, y, z, **kwargs)

Creates 2D grid data.

x, y, z are 2D arrays giving the positions of the vertices of the surface. The connectivity between these points is implied by the connectivity on the arrays.

For simple structures (such as orthogonal grids) prefer the array2dsource function, as it will create more efficient data structures.

Keyword arguments:

name:

the name of the vtk object created.

scalars:

optional scalar data.

figure:

optionally, the figure on which to add the data source. If None, the source is not added to any figure, and will be added automatically by the modules or filters. If False, no figure will be created by modules or filters applied to the source: the source can only be used for testing, or numerical algorithms, not visualization.

mask:

Mask points specified in a boolean masking array.

line_source

mayavi.tools.pipeline.line_source(*args, **kwargs)

Creates line data.

Function signatures:

line_source(x, y, z, ...)
line_source(x, y, z, s, ...)
line_source(x, y, z, f, ...)

If 4 positional arguments are passed the last one must be an array s,
or a callable, f, that returns an array.

Keyword arguments:

name:

the name of the vtk object created.

figure:

optionally, the figure on which to add the data source. If None, the source is not added to any figure, and will be added automatically by the modules or filters. If False, no figure will be created by modules or filters applied to the source: the source can only be used for testing, or numerical algorithms, not visualization.

open

mayavi.tools.pipeline.open(filename, figure=None)

Open a supported data file given a filename. Returns the source object if a suitable reader was found for the file.

If ‘figure’ is False, no view is opened, and the code does not need GUI or openGL context.

parametric_surface

mayavi.tools.pipeline.parametric_surface(metadata=<mayavi.core.metadata.SourceMetadata object at 0x7f59abb768e0>)

Create a parametric surface source

point_load

mayavi.tools.pipeline.point_load(metadata=<mayavi.core.metadata.SourceMetadata object at 0x7f59abb76ed0>)

Simulates a point load on a cube of data (for tensors)

scalar_field

mayavi.tools.pipeline.scalar_field(*args, **kwargs)

Creates a scalar field data.

Function signatures:

scalar_field(s, ...)
scalar_field(x, y, z, s, ...)
scalar_field(x, y, z, f, ...)

If only 1 array s is passed the x, y and z arrays are assumed to be made from the indices of arrays.

If the x, y and z arrays are passed they are supposed to have been generated by numpy.mgrid. The function builds a scalar field assuming the points are regularily spaced.

If 4 positional arguments are passed the last one must be an array s, or a callable, f, that returns an array.

Keyword arguments:

name:

the name of the vtk object created.

figure:

optionally, the figure on which to add the data source. If None, the source is not added to any figure, and will be added automatically by the modules or filters. If False, no figure will be created by modules or filters applied to the source: the source can only be used for testing, or numerical algorithms, not visualization.

scalar_scatter

mayavi.tools.pipeline.scalar_scatter(*args, **kwargs)

Creates scattered scalar data.

Function signatures:

scalar_scatter(s, ...)
scalar_scatter(x, y, z, s, ...)
scalar_scatter(x, y, z, s, ...)
scalar_scatter(x, y, z, f, ...)

If only 1 array s is passed the x, y and z arrays are assumed to be made from the indices of vectors.

If 4 positional arguments are passed the last one must be an array s, or a callable, f, that returns an array.

Keyword arguments:

name:

the name of the vtk object created.

figure:

optionally, the figure on which to add the data source. If None, the source is not added to any figure, and will be added automatically by the modules or filters. If False, no figure will be created by modules or filters applied to the source: the source can only be used for testing, or numerical algorithms, not visualization.

triangular_mesh_source

mayavi.tools.pipeline.triangular_mesh_source(x, y, z, triangles, **kwargs)

Creates 2D mesh by specifying points and triangle connectivity.

x, y, z are 2D arrays giving the positions of the vertices of the surface. The connectivity between these points is given by listing triplets of vertices inter-connected. These vertices are designed by there position index.

Keyword arguments:

name:

the name of the vtk object created.

scalars:

optional scalar data.

figure:

optionally, the figure on which to add the data source. If None, the source is not added to any figure, and will be added automatically by the modules or filters. If False, no figure will be created by modules or filters applied to the source: the source can only be used for testing, or numerical algorithms, not visualization.

vector_field

mayavi.tools.pipeline.vector_field(*args, **kwargs)

Creates vector field data.

Function signatures:

vector_field(u, v, w, ...)
vector_field(x, y, z, u, v, w, ...)
vector_field(x, y, z, f, ...)

If only 3 arrays u, v, w are passed the x, y and z arrays are assumed to be made from the indices of vectors.

If the x, y and z arrays are passed, they should have been generated by numpy.mgrid or numpy.ogrid. The function builds a scalar field assuming the points are regularily spaced on an orthogonal grid.

If 4 positional arguments are passed the last one must be a callable, f, that returns vectors.

Keyword arguments:

name:

the name of the vtk object created.

scalars:

optional scalar data.

figure:

optionally, the figure on which to add the data source. If None, the source is not added to any figure, and will be added automatically by the modules or filters. If False, no figure will be created by modules or filters applied to the source: the source can only be used for testing, or numerical algorithms, not visualization.

vector_scatter

mayavi.tools.pipeline.vector_scatter(*args, **kwargs)

Creates scattered vector data.

Function signatures:

vector_scatter(u, v, w, ...)
vector_scatter(x, y, z, u, v, w, ...)
vector_scatter(x, y, z, f, ...)

If only 3 arrays u, v, w are passed the x, y and z arrays are assumed to be made from the indices of vectors.

If 4 positional arguments are passed the last one must be a callable, f, that returns vectors.

Keyword arguments:

name:

the name of the vtk object created.

scalars:

optional scalar data.

figure:

optionally, the figure on which to add the data source. If None, the source is not added to any figure, and will be added automatically by the modules or filters. If False, no figure will be created by modules or filters applied to the source: the source can only be used for testing, or numerical algorithms, not visualization.

vertical_vectors_source

mayavi.tools.pipeline.vertical_vectors_source(*args, **kwargs)

Creates a set of vectors pointing upward, useful eg for bar graphs.

Function signatures:

vertical_vectors_source(s, ...)
vertical_vectors_source(x, y, s, ...)
vertical_vectors_source(x, y, f, ...)
vertical_vectors_source(x, y, z, s, ...)
vertical_vectors_source(x, y, z, f, ...)

If only one positional argument is passed, it can be a 1D, 2D, or 3D array giving the length of the vectors. The positions of the data points are deducted from the indices of array, and an uniformly-spaced data set is created.

If 3 positional arguments (x, y, s) are passed the last one must be an array s, or a callable, f, that returns an array. x and y give the 2D coordinates of positions corresponding to the s values. The vertical position is assumed to be 0.

If 4 positional arguments (x, y, z, s) are passed, the 3 first are arrays giving the 3D coordinates of the data points, and the last one is an array s, or a callable, f, that returns an array giving the data value.

Keyword arguments:

name:

the name of the vtk object created.

figure:

optionally, the figure on which to add the data source. If None, the source is not added to any figure, and will be added automatically by the modules or filters. If False, no figure will be created by modules or filters applied to the source: the source can only be used for testing, or numerical algorithms, not visualization.

volume_file

mayavi.tools.pipeline.volume_file(metadata=<mayavi.core.metadata.SourceMetadata object at 0x7f59defb0a40>)

Open a Volume file