hacking_the_matrix.py

import numpy as np
from numpy.lib.stride_tricks import as_strided

# Makes a new matrix like this:
# input: [0, 1, 2, 3]
# output: [[0, 1], [1, 2], [2, 3]]
# But, does it all in memory using `as_strided`, so it's speedy.
# And if you make a mistake, you can see fake numbers


data = np.arange(4)

print(data)

new_data = as_strided(
  data,
  shape=(
    data.shape[0] - 1,  # Figure out what size the array should be
    2,  # I want to add another dimension of size 2
  ),
  strides=(
    data.strides[0],
    data.strides[0],  # not a typo. To move one element over in the 2nd dimension, 
                      # move one step in the first stride direction 
  ),
  writeable=False,  # eek, as_strided mucks around in memory. Make this read-only to avoid hacking too much.
)

print(new_data)