Numpy MaskedArray.cumprod() function | Python

Numpy MaskedArray.cumprod() function | Python

numpy.ma.MaskedArray.cumprod() is a method for the MaskedArray object in the NumPy library. A MaskedArray is an array-like structure that allows for masking certain values, meaning these values are ignored or considered invalid in any computation.

The cumprod() method returns the cumulative product of the elements along a given axis, considering the masked values (i.e., it will ignore masked elements in the cumulative product).

Let's see how it works:

Example

import numpy as np import numpy.ma as ma # Create a MaskedArray x = ma.array([1, 2, 3, 4], mask=[0, 1, 0, 0]) print("Original MaskedArray:") print(x) # Compute the cumulative product y = x.cumprod() print("\nCumulative product:") print(y)

Output:

Original MaskedArray: [1 -- 3 4] Cumulative product: [1 1 3 12]

In the example above, the original MaskedArray has a masked value at index 1 (denoted by --). When we compute the cumulative product with cumprod(), this masked value is ignored. Therefore, the cumulative product of [1, 2, 3, 4] would be [1, 2, 6, 24], but since 2 is masked, the result is [1, 1, 3, 12].

Parameters

  • axis: It's optional and specifies the axis along which the cumulative product is computed. By default, it is None, meaning the data is flattened first.

Returns

A new MaskedArray with the same shape as the input containing the cumulative product.

It's important to note that if your masked array contains a True value in the mask for all elements along a specified axis, the result will be masked for that axis too.

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