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I have a 2D array of zeros (called labels) and a list of its coordinates (called centers). For each of the centers I would like to put a progressive number in a 5x5 cluster around it inside the label ...

I would like to extract elements of a given multidimensional numpy array, using another array of indices. However it doesn't behave in the way I expected. Below is a simple example: import numpy as np ...

I have a numpy array x with shape [4, 5, 3] I have a 2D array of indices i with shape [4, 3], referring to indices along dimension 1 (of length 5) in x I'd like to extract a sub-array y from x, with ...

I have multiple numpy arrays with two columns each: one containing a measurement, the other one the year of that measurement. The length and start/end points of those arrays are all different. My goal ...

I am attempting to index a stacked 3-D Numpy array (named stack) by a group of 2-D indices contained inside of a separate Numpy array (named piece). The separate array contains several groups of 2-D ...

I have 2 numpy arrays x_original and y_original each 50x12060 float numbers representing X and Y values that can be plotted on X-Y coordinates. I can use a filter condition on Y values like filteredY =...

I have an numpy array which I want to to find index of values from it. Here is the code: for i, memb_e in enumerate(memb_e): if memb_e == 1: x1 = e[i] y1 = 1 print(x1) for i, ...

I could not for the life of me get array indexing to work properly with higher dimensional lexsort. I have an ndarray lines of shape (N, 2, 3). You can think of it as N pairs (start and end of a line) ...

here is my situation. Suppose you have an array A of some elements, A is np.ndarray, and B - also np.ndarray, where B[i] is how many times I'd like to take element A[i] for the output. Example: A = np....

I've created vector x and I need to create a vector z by removing the 3rd and 6th elements of x. I cannot just create a vector by simply typing in the elements that should be in z. I have to index ...

I am trying to index a 3-dimensional torch tensor based on timesteps acquired with torch.nonzeroes (for a latency decoder in a Neuromorphic Computing project), but am unsure on how to proceed. My ...

I've attatched the following code that shows how I look up the index value from two arrays, then choose the Z-value corresponding to that index value. The mesh_data_X and mesh_data_Y arrays are both ...

Here is the toy version of the problem I am facing: Given the following two numpy arrays: img = np.array([[0,1,1,2], [0,2,1,1]]) number = np.array([[0,0.1,0.1,0.2], [0.1,0,0.2,0.2]]) both img and ...

If the array is np.array([1, 3, 1, 5, 5, 5, 6, 3, 6, 3]), then I want to get array like this; np.array([0, 0, 1, 0, 1, 2, 0, 1, 1, 2]). Is there any numpy options? Or do I have to make new function?

I have a question regarding indexing in numpy arrays. Problem that arised: While running my code I get the following error description: ValueError: zero-size array to reduction operation minimum which ...