I have two numpy arrays of the same shape. I want to subtract once from the other. I have tried two methods but numpy is not returning correct values.

Here is a short example which demonstrates how numpy array creation works with fill_value:

How can I round a floating-point number to the nearest even digit with a precision of 4 decimal places in Python? I tried using the np.round function and the built-in round function, but they don’t seem to work for me. For example, with a negative number like -2.6825, I want the rounding to give me -2.6830, but it currently gives me -2.6820. What is the way to achieve rounding half to even?

I have various array shapes where I am trying to use np.select(). My code for selected_results works for this case:

I’m working with a 3d “image” and am trying to figure out how to more efficiently map out uniquely joined areas (blood vessels in this case). I have 1’s and 2’s along with empty spaces that are 0’s. My current solution for creating a map of where these vessels are is to create an array where

Given parameters

I have multiple Nx3 points, and I sequentially generate a new value for each from its corresponding multivariate Gaussian, each with 1×3 mean and 3×3 cov. So, together, I have arrays: Nx3 array of points, Nx3 array of means and Nx3x3 array of covs.

I installed numpy and ran the following code:

I have strings containing str representations of numpy values. I also have a list of the original dtypes, such as numpy.dtypes.Int64DType. I do not know all possible dtypes in advance. I can for the life of me not figure out how to convert the string back to a scalar of the correct dtype.

I have a numpy array that has times in the first column and the other columns contain signal values. The objective is to use a peak finding algorithm for all the signal value columns and get the peaks and their corresponding times. My code looks like this: