import numpy as np
import vtk
from vtk.numpy_interface import dataset_adapter as dsa
import PVGeo
from PVGeo.filters import CombineTables
################################################################################
# Create some input tables
t0 = vtk.vtkTable()
t1 = vtk.vtkTable()
# Populate the tables
n = 100
titles = ('Array 0', 'Array 1', 'Array 2')
arr0 = np.random.random(n) # Table 0
arr1 = np.random.random(n) # Table 0
t0.AddColumn(PVGeo.convert_array(arr0, titles[0]))
t0.AddColumn(PVGeo.convert_array(arr1, titles[1]))
arr2 = np.random.random(n) # Table 1
t1.AddColumn(PVGeo.convert_array(arr2, titles[2]))
arrs = [arr0, arr1, arr2]
################################################################################
# Now use the `CombineTables` filter:
output = CombineTables().apply(t0, t1)
# Here I verify the result
wpdi = dsa.WrapDataObject(output)
for i in range(len(titles)):
arr = wpdi.RowData[titles[i]]
from PVGeo.filters import ReshapeTable
################################################################################
# Create some input table
t0 = vtk.vtkTable()
# Populate the tables
arrs = [None, None, None]
n = 400
ncols = 2
nrows = int(n * len(arrs) / ncols)
titles = ('Array 0', 'Array 1', 'Array 2')
arrs[0] = np.random.random(n)
arrs[1] = np.random.random(n)
arrs[2] = np.random.random(n)
t0.AddColumn(PVGeo.convert_array(arrs[0], titles[0]))
t0.AddColumn(PVGeo.convert_array(arrs[1], titles[1]))
t0.AddColumn(PVGeo.convert_array(arrs[2], titles[2]))
################################################################################
# Use the filter to reshape the table
order = 'F'
newtitles = ['Title %d' % i for i in range(ncols)]
output = ReshapeTable(order=order, ncols=ncols, nrows=nrows,
names=newtitles).apply(t0)
################################################################################
# Check the output against NumPy
wpdi = dsa.WrapDataObject(output)
tarr = np.zeros((nrows, ncols))
for i in range(ncols):