def make_data( x, y, z ):
"""Creates some simple array data of the given dimensions to test
with."""
x = x.astype( 'f' )
y = y.astype( 'f' )
z = z.astype( 'f' )
arr_list = [x, y, z]
n_arr = len( arr_list )
ogrid = []
for i, arr in enumerate( arr_list ):
shape = ones( ( n_arr, ), dtype='int' )
shape[i] = len( arr )
arr_i = ncopy( arr ).reshape( tuple( shape ) )
ogrid.append( arr_i )
x, y, z = ogrid
scalars = x * z * y #(numpy.sin(x*y*z)/(x*y*z))
# The copy makes the data contiguous and the transpose makes it
# suitable for display via tvtk. Please note that we assume here
# that the ArraySource is configured to not transpose the data.
s = transpose( scalars ).copy()
# Reshaping the array is needed since the transpose messes up the
# dimensions of the data. The scalars themselves are ravel'd and
# used internally by VTK so the dimension does not matter for the
# scalars.
s.shape = s.shape[::-1]
return s
def orthogonalize( arr_list ):
'''Orthogonalize a list of one-dimensional arrays.
'''
n_arr = len( arr_list )
ogrid = []
for i, arr in enumerate( arr_list ):
shape = ones( ( n_arr, ), dtype = 'int' )
shape[i] = len( arr )
arr_i = ncopy( arr ).reshape( tuple( shape ) )
ogrid.append( arr_i )
return ogrid
def orthogonalize( arr_list ):
'''Orthogonalize a list of one-dimensional arrays.
'''
n_arr = len( arr_list )
ogrid = []
for i, arr in enumerate( arr_list ):
shape = ones( ( n_arr, ), dtype='int' )
shape[i] = len( arr )
arr_i = ncopy( arr ).reshape( tuple( shape ) )
ogrid.append( arr_i )
return ogrid