Interface

The interface module provides functions to convert/cast between common VTK and NumPy/Pandas data types. These methods provide a simple to use interface for VTK data types so that users can make changes to VTK data strucutres via Python data structures that are a bit easier to perform numerical operations upon.

add_arrays_from_data_frame

PVGeo.interface.add_arrays_from_data_frame(pdo, field, df)[source]

Add all of the arrays from a given data frame to an output’s data

convert_array

PVGeo.interface.convert_array(arr, name='Data', deep=0, array_type=None, pdf=False)[source]

A helper to convert a NumPy array to a vtkDataArray or vice versa

Parameters

  • arr (ndarray or vtkDataArry) – A numpy array or vtkDataArry to convert

  • name (str) – the name of the data array for VTK

  • deep (bool, int) – if input is numpy array then deep copy values

  • pdf (bool) – if input is vtkDataArry, make a pandas DataFrame of the array

Returns

the converted array (if input is a NumPy ndaray then returns vtkDataArray or is input is vtkDataArray then returns NumPy ndarray). If pdf==True and the input is vtkDataArry, return a pandas DataFrame.

Return type

vtkDataArray, ndarray, or DataFrame

convert_cell_conn

PVGeo.interface.convert_cell_conn(cell_connectivity)[source]

Converts cell connectivity arrays to a cell matrix array that makes sense for VTK cell arrays.

convert_string_array

PVGeo.interface.convert_string_array(arr, name=None)[source]

A helper to convert a numpy array of strings to a vtkStringArray or vice versa. Note that this is terribly inefficient - inefficient support is better than no support :). If you have ideas on how to make this faster, please consider opening a pull request.

data_frame_to_table

PVGeo.interface.data_frame_to_table(df, pdo=None)[source]

Converts a pandas DataFrame to a vtkTable

get_array

PVGeo.interface.get_array(dataset, name, vtk_object=False)[source]

Given an input dataset, this will return the named array as a NumPy array or a vtkDataArray if spceified

get_data_dict

PVGeo.interface.get_data_dict(dataset, field='cell')[source]

Given an input dataset, this will return all the arrays in that object’s cell/point/field/row data as named NumPy arrays in a dictionary.

get_dtypes

PVGeo.interface.get_dtypes(dtype='', endian=None)[source]

This converts char dtypes and an endian to a numpy and VTK data type.

Returns

the numpy data type and the integer type id specified in vtkType.h for VTK data types

Return type

tuple (numpy.dtype, int)

get_vtk_type

PVGeo.interface.get_vtk_type(typ)[source]

This looks up the VTK type for a give python data type. Corrects for string type mapping issues.

Returns

int

Return type

the integer type id specified in vtkType.h

place_array_in_table

PVGeo.interface.place_array_in_table(ndarr, titles, pdo)[source]

Takes a 1D/2D numpy array and makes a vtkTable of it

Parameters

  • ndarr (numpy.ndarray) – The 1D/2D array to be converted to a table

  • titles (list or tuple) – The titles for the arrays in the table. Must have same number of elements as columns in input ndarray

  • pdo (vtkTable) – The output data object pointer

Returns

returns the same input pdo table

Return type

vtkTable

points_to_poly_data

PVGeo.interface.points_to_poly_data(points, copy_z=False)[source]

Create vtkPolyData from a numpy array of XYZ points. If the points have more than 3 dimensions, then all dimensions after the third will be added as attributes. Assume the first three dimensions are the XYZ coordinates.

Parameters

  • points (np.ndarray or pandas.DataFrame) – The points and pointdata

  • copy_z (bool) – A flag on whether to append the z values as a PointData array

Returns

points with point-vertex cells

Return type

vtkPolyData

table_to_data_frame

PVGeo.interface.table_to_data_frame(table)[source]

Converts a vtkTable to a pandas DataFrame