Given three classes (5,6,7) of two arrays:

Given three classes (5,6,7) of two arrays:

I have array of floating points Nx2 which is representing the reprojected 3D -> 2D coordinates in a 2D image. I need to find closest (integer) pixel. The naive solution is pretty simple:

I am trying to read a simple dataset to a 1D numpy array with Python.
However, the data was written with Fortran (regular ASCII) and groups repeated values together.
For example:

I have been trying to install numpy to run some code that was made by someone else. The issue I am having is that when I run the code a numpy Import Error is thrown telling me that I am missing required c files.

I have this tensor dimension:

I have a class Point3D that creates a vertical numpy matrix and can be edited:

I have this sparse vector val with this Pythonic ways:

I’m migrating some python C extension to numpy 2. The extension basically gets a list of 2D numpy arrays and generates a new 2D array by combining them (average, median, etc,). The difficulty is that the input and output arrays are byteswapped. I cannot byteswap the input arrays to machine order (they are too many to fit in memory). So

I am working on a project that involves calculating a velocity vector field using the Particle Image Velocimetry (PIV) technique from two grayscale images. The goal is to implement a function piv() that processes pairs of images to derive velocity vectors (U, V) at defined interrogation points (X, Y). Each interrogation point corresponds to an interrogation window in the first image and a search window in the second image.