numpy-ndarray – Tarik Billa

Specific type annotation for NumPy ndarray using mypy

January 8, 2024 by Tarik

What you are looking for is the numpy.typing.NDArray class: https://numpy.org/doc/stable/reference/typing.html#numpy.typing.NDArray numpy.typing.NDArray[A] is an alias for numpy.ndarray[Any, numpy.dtype[A]]: import numpy as np import numpy.typing as npt a: npt.NDArray[np.complex64] = np.zeros((3, 3), dtype=np.complex64) # reveal_type(a) # -> numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[numpy.typing._32Bit, numpy.typing._32Bit]]] print(a) prints [[0.+0.j 0.+0.j 0.+0.j] [0.+0.j 0.+0.j 0.+0.j] [0.+0.j 0.+0.j 0.+0.j]] Note that even though you annotate … Read more

How to convert a 3d numpy array to 2d

December 26, 2023 by Tarik

In [27]: x = np.arange(16).reshape((4,2,2)) In [28]: x.reshape(2,2,2,2).swapaxes(1,2).reshape(4,-1) Out[28]: array([[ 0, 1, 4, 5], [ 2, 3, 6, 7], [ 8, 9, 12, 13], [10, 11, 14, 15]]) I’ve posted more general functions for reshaping/unshaping arrays into blocks, here.

Numpy mean of nonzero values

December 13, 2023 by Tarik

Get the count of non-zeros in each row and use that for averaging the summation along each row. Thus, the implementation would look something like this – np.true_divide(matrix.sum(1),(matrix!=0).sum(1)) If you are on an older version of NumPy, you can use float conversion of the count to replace np.true_divide, like so – matrix.sum(1)/(matrix!=0).sum(1).astype(float) Sample run – … Read more

What is the purpose of meshgrid in NumPy?

October 2, 2023 by Tarik

The purpose of meshgrid is to create a rectangular grid out of an array of x values and an array of y values. So, for example, if we want to create a grid where we have a point at each integer value between 0 and 4 in both the x and y directions. To create … Read more

Cannot convert list to array: ValueError: only one element tensors can be converted to Python scalars

August 17, 2023 by Tarik

It seems like you have a list of tensors. For each tensor you can see its size() (no need to convert to list/numpy). If you insist, you can convert a tensor to numpy array using numpy(): Return a list of tensor shapes: >> [t.size() for t in my_list_of_tensors] Returns a list of numpy arrays: >> … Read more

Transforming a row vector into a column vector in Numpy

June 7, 2023 by Tarik

you can use the transpose operation to do this: Example: In [2]: a = np.array([[1,2], [3,4], [5,6]]) In [5]: a.shape Out[5]: (3, 2) In [6]: a_trans = a.T #or: np.transpose(a), a.transpose() In [8]: a_trans.shape Out[8]: (2, 3) In [7]: a_trans Out[7]: array([[1, 3, 5], [2, 4, 6]]) Note that the original array a will still … Read more

How to print a Numpy array without brackets?

May 1, 2023 by Tarik

You can use the join method from string: >>> a = [1,2,3,4,5] >>> ‘ ‘.join(map(str, a)) “1 2 3 4 5”

How does the axis parameter from NumPy work?

April 29, 2023 by Tarik

Clearly, e.shape == (3, 2, 2) Sum over an axis is a reduction operation so the specified axis disappears. Hence, e.sum(axis=0).shape == (2, 2) e.sum(axis=1).shape == (3, 2) e.sum(axis=2).shape == (3, 2) Intuitively, we are “squashing” the array along the chosen axis, and summing the numbers that get squashed together.

what does numpy ndarray shape do?

April 2, 2023 by Tarik

yourarray.shape or np.shape() or np.ma.shape() returns the shape of your ndarray as a tuple; And you can get the (number of) dimensions of your array using yourarray.ndim or np.ndim(). (i.e. it gives the n of the ndarray since all arrays in NumPy are just n-dimensional arrays (shortly called as ndarrays)) For a 1D array, the … Read more

Deprecation status of the NumPy matrix class

March 13, 2023 by Tarik

tl; dr: the numpy.matrix class is getting deprecated. There are some high-profile libraries that depend on the class as a dependency (the largest one being scipy.sparse) which hinders proper short-term deprecation of the class, but users are strongly encouraged to use the ndarray class (usually created using the numpy.array convenience function) instead. With the introduction … Read more