Source code for PVGeo.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

__all__ = [

__displayname__ = 'Interface'

import numpy as np
import pandas as pd
import vtk
from vtk.numpy_interface import dataset_adapter as dsa
from vtk.util import numpy_support as nps

from . import _helpers

[docs]def getVTKtype(typ): """This looks up the VTK type for a give python data type. Return: int : the integer type id specified in vtkType.h """ typ = nps.get_vtk_array_type(typ) if typ is 3: return 13 return typ
[docs]def convertStringArray(arr, name='Strings'): """A helper to convert a numpy array of strings to a vtkStringArray Return: vtkStringArray : the converted array """ vtkarr = vtk.vtkStringArray() for val in arr: vtkarr.InsertNextValue(val) vtkarr.SetName(name) return vtkarr
[docs]def convertArray(arr, name='Data', deep=0, array_type=None, pdf=False): """A helper to convert a NumPy array to a vtkDataArray or vice versa Args: 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 Return: vtkDataArray, ndarray, or DataFrame: 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. """ if isinstance(arr, np.ndarray): if arr.dtype is np.dtype('O'): arr = arr.astype('|S') arr = np.ascontiguousarray(arr) try: arr = np.ascontiguousarray(arr) VTK_data = nps.numpy_to_vtk(num_array=arr, deep=deep, array_type=array_type) except ValueError: typ = getVTKtype(arr.dtype) if typ is 13: VTK_data = convertStringArray(arr) VTK_data.SetName(name) return VTK_data # Otherwise input must be a vtkDataArray if not isinstance(arr, vtk.vtkDataArray): raise _helpers.PVGeoError('Invalid input array.') # Convert from vtkDataArry to NumPy num_data = nps.vtk_to_numpy(arr) if not pdf: return num_data return pd.DataFrame(data=num_data, columns=[arr.GetName()])
[docs]def dataFrameToTable(df, pdo=None): """Converts a pandas DataFrame to a vtkTable""" if not isinstance(df, pd.DataFrame): raise PVGeoError('Input is not a pandas DataFrame') if pdo is None: pdo = vtk.vtkTable() for key in df.keys(): VTK_data = convertArray(df[key].values, name=key) pdo.AddColumn(VTK_data) return wrapvtki(pdo)
[docs]def tableToDataFrame(table): """Converts a vtkTable to a pandas DataFrame""" if not isinstance(table, vtk.vtkTable): raise PVGeoError('Input is not a vtkTable') num = table.GetNumberOfColumns() names = [table.GetColumnName(i) for i in range(num)] data = dsa.WrapDataObject(table).RowData df = pd.DataFrame() for i, n in enumerate(names): df[n] = np.array(data[n]) return df
[docs]def placeArrInTable(ndarr, titles, pdo): """Takes a 1D/2D numpy array and makes a vtkTable of it Args: 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 Return: vtkTable : returns the same input pdo table """ # Put columns into table if len(np.shape(ndarr)) > 2: raise _helpers.PVGeoError('Input np.ndarray must be 1D or 2D to be converted to vtkTable.') if len(np.shape(ndarr)) == 1: # First check if it is an array full of tuples (varying type) if isinstance(ndarr[0], (tuple, np.void)): for i in range(len(titles)): placeArrInTable(ndarr['f%d' % i], [titles[i]], pdo) return wrapvtki(pdo) # Otherwise it is just a 1D array which needs to be 2D else: ndarr = np.reshape(ndarr, (-1, 1)) cols = np.shape(ndarr)[1] for i in range(cols): VTK_data = convertArray(ndarr[:,i]) VTK_data.SetName(titles[i]) pdo.AddColumn(VTK_data) return wrapvtki(pdo)
[docs]def getdTypes(dtype='', endian=None): """This converts char dtypes and an endian to a numpy and VTK data type. Return: tuple (numpy.dtype, int): the numpy data type and the integer type id specified in vtkType.h for VTK data types """ # If native `@` was chosen then do not pass an endian if endian is '@': #print('WARNING: Native endianness no longer supported for packed binary reader. Please chose `>` or `<`. This defaults to big `>`.') endian = '' # No endian specified: elif endian is None: endian = '' # Get numpy and VTK data types and return them both if dtype is 'd': vtktype = vtk.VTK_DOUBLE elif dtype is 'f': vtktype = vtk.VTK_FLOAT elif dtype is 'i': vtktype = vtk.VTK_INT else: raise _helpers.PVGeoError('dtype \'%s\' unknown:' % dtype) # Return data types dtype = np.dtype('%s%s' % (endian, dtype)) return dtype, vtktype
[docs]def pointsToPolyData(points, copy_z=False): """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. Args: 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 Return: vtkPolyData : points with point-vertex cells """ __displayname__ = 'Points to PolyData' __category__ = 'filter' # This prevents an error that occurs when only one point is passed if points.ndim < 2: points = points.reshape((1,-1)) keys = ['Field %d' % i for i in range(points.shape[1] - 3)] # Check if input is anything other than a NumPy array and cast it # e.g. you could send a Pandas dataframe if not isinstance(points, np.ndarray): if isinstance(points, pd.DataFrame): # If a pandas data frame, lets grab the keys keys = points.keys()[3::] points = np.array(points) # If points are not 3D if points.shape[1] < 2: raise RuntimeError('Points must be 3D. Try adding a third dimension of zeros.') atts = points[:, 3::] points = points[:, 0:3] npoints = points.shape[0] # Make VTK cells array cells = np.hstack((np.ones((npoints, 1)), np.arange(npoints).reshape(-1, 1))) cells = np.ascontiguousarray(cells, dtype=np.int64) cells = np.reshape(cells, (2*npoints)) vtkcells = vtk.vtkCellArray() vtkcells.SetCells(npoints, nps.numpy_to_vtk(cells, deep=True, array_type=vtk.VTK_ID_TYPE)) # Convert points to vtk object pts = vtk.vtkPoints() pts.SetData(convertArray(points)) # Create polydata pdata = vtk.vtkPolyData() pdata.SetPoints(pts) pdata.SetVerts(vtkcells) # Add attributes if given scalSet = False for i, key in enumerate(keys): data = convertArray(atts[:, i], name=key) pdata.GetPointData().AddArray(data) if not scalSet: pdata.GetPointData().SetActiveScalars(key) scalSet = True if copy_z: z = convertArray(points[:, 2], name='Elevation') pdata.GetPointData().AddArray(z) return wrapvtki(pdata)
[docs]def addArraysFromDataFrame(pdo, field, df): """Add all of the arrays from a given data frame to an output's data""" for key in df.keys(): VTK_data = convertArray(df[key].values, name=key) _helpers.addArray(pdo, field, VTK_data) return wrapvtki(pdo)
[docs]def convertCellConn(cellConn): """Converts cell connectivity arrays to a cell matrix array that makes sense for VTK cell arrays. """ cellsMat = np.concatenate( ( np.ones((cellConn.shape[0], 1), dtype=np.int64)*cellConn.shape[1], cellConn ), axis=1).ravel() return nps.numpy_to_vtk(cellsMat, deep=True, array_type=vtk.VTK_ID_TYPE)
[docs]def getArray(dataset, name, vtkObj=False): """Given an input dataset, this will return the named array as a NumPy array or a vtkDataArray if spceified """ arr, field = _helpers.searchForArray(dataset, name) if vtkObj: return arr return convertArray(arr)
[docs]def getDataDict(dataset, field='cell'): """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. """ data = {} for key in _helpers.getAllArrayNames(dataset, field): data[key] = np.array(_helpers.getNumPyArray(dataset, field, key)) return data
[docs]def wrapvtki(dataset): """This will wrap any given VTK dataset via the vtkInterface Python package if it is available and return the wrapped data object. If vtki is unavailable, then the given object is returned.""" if isinstance(dataset, vtk.vtkTable): return dataset try: import vtki dataset = vtki.wrap(dataset) except ImportError: pass return dataset