Array manipulation routines#

This is the list of nodes available within VisuAlea in the numpy.manipulation package. The reference documentation is generated from numpy files, see also API reference on Numpy

Changing array shape#

reshape(a, /[, shape, order, newshape, copy])

Gives a new shape to an array without changing its data.

ravel(a[, order])

Return a contiguous flattened array.

ndarray.flatten([order])

Return a copy of the array collapsed into one dimension.

Transpose-like operations#

transpose(a[, axes])

Returns an array with axes transposed.

Changing number of dimensions#

Changing kind of array#

Joining arrays#

hstack(tup, *[, dtype, casting])

Stack arrays in sequence horizontally (column wise).

vstack(tup, *[, dtype, casting])

Stack arrays in sequence vertically (row wise).

Splitting arrays#

Tiling arrays#

Adding and removing elements#

unique(ar[, return_index, return_inverse, ...])

Find the unique elements of an array.

Rearranging elements#

Window functions#

window is a wrapper of the flowwing numpy’s window functions.

bartlett(M)

Return the Bartlett window.

blackman(M)

Return the Blackman window.

hamming(M)

Return the Hamming window.

hanning(M)

Return the Hanning window.

kaiser(M, beta)

Return the Kaiser window.

Utilities#

axis_rotation_matrix: Create a 4x4 matrix that represents a rotation around one axis

Comparison functions#

Warning

Do not use the Python keywords and and or to combine logical array expressions. These keywords will test the truth value of the entire array (not element-by-element as you might expect). Use the bitwise operators & and | instead.

Warning

The bit-wise operators & and | are the proper way to perform element-by-element array comparisons. Be sure you understand the operator precedence: (a > 2) & (a < 5) is the proper syntax because a > 2 & a < 5 will result in an error due to the fact that 2 & a is evaluated first.