How can you turn an index array into a mask array in Numpy?

Question

Is it possible to convert an array of indices to an array of ones and zeros, given the range? i.e. [2,3] -> [0, 0, 1, 1, 0], in range of 5

I'm trying to automate something like this:

>>> index_array = np.arange(200,300) array([200, 201, ... , 299])  >>> mask_array = ???           # some function of index_array and 500 array([0, 0, 0, ..., 1, 1, 1, ... , 0, 0, 0])  >>> train(data[mask_array])    # trains with 200~299 >>> predict(data[~mask_array]) # predicts with 0~199, 300~499 

Answer 1

Here's one way:

In [1]: index_array = np.array([3, 4, 7, 9])  In [2]: n = 15  In [3]: mask_array = np.zeros(n, dtype=int)  In [4]: mask_array[index_array] = 1  In [5]: mask_array Out[5]: array([0, 0, 0, 1, 1, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0]) 

If the mask is always a range, you can eliminate index_array, and assign 1 to a slice:

In [6]: mask_array = np.zeros(n, dtype=int)  In [7]: mask_array[5:10] = 1  In [8]: mask_array Out[8]: array([0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0]) 

If you want an array of boolean values instead of integers, change the dtype of mask_array when it is created:

In [11]: mask_array = np.zeros(n, dtype=bool)  In [12]: mask_array Out[12]:  array([False, False, False, False, False, False, False, False, False,        False, False, False, False, False, False], dtype=bool)  In [13]: mask_array[5:10] = True  In [14]: mask_array Out[14]:  array([False, False, False, False, False,  True,  True,  True,  True,         True, False, False, False, False, False], dtype=bool) 

Answer 2

For a single dimension, try:

n = (15,) index_array = [2, 5, 7] mask_array = numpy.zeros(n) mask_array[index_array] = 1 

For more than one dimension, convert your n-dimensional indices into one-dimensional ones, then use ravel:

n = (15, 15) index_array = [[1, 4, 6], [10, 11, 2]] # you may need to transpose your indices! mask_array = numpy.zeros(n) flat_index_array = np.ravel_multi_index(     index_array,     mask_array.shape) numpy.ravel(mask_array)[flat_index_array] = 1