Category "numpy"

Python: Is there any way to get the n-th order antiderivative of a periodic 3D signal/field without padding data?

As stated in the title, I want to obtain the n-th (e.g. 4-th) order antiderivative of a 3D field (e.g. array with shape (1024,1024,1024) ) with period L on each

How does the axis parameter from NumPy work?

Can someone explain exactly what the axis parameter in NumPy does? I am terribly confused. I'm trying to use the function myArray.sum(axis=num) At first I t

Why ais my output "nan", keras model prediction

I'm trying to make an AI attempting to predict numbers from prime number sequence, but my model outputs "[[nan]]". My csv file is formatted like this: number of

NumPy array value error from training in Auto-Keras with StratifiedKFold

Background My sentiment analysis research comes across a variety of datasets. Recently I've encountered one dataset that somehow I just cannot train successfull

How to repair the corrupted image below using opencv, python, numpy and necessary libraries

import cv2 damaged_image = cv2.imread("Corrupted.png") mask = cv2.imread("mask.png", 0) output = cv2.inpaint(damaged_image, mask, 1, cv2.INPAINT_TELEA) cv2.i

Selecting From multidimensional Numpy array with multidimensional mask

I am trying to build an example to understand image segmentation, you are given an image of shape (1,2,2,3) it's a 2x2 image where each pixel has 3 numbers indi

Trying to convert pandas df to np array, dtaidistance computes list instead

I am attempting to compute the distance matrix for an ndarray that I have converted from pandas. I tried to convert the pandas df currently in this format: move

How can I resolve " InvalidArgumentError: Graph execution error: jpeg::Uncompress failed. Invalid JPEG data or crop window"?

Beginner here. I recently converted my images to grayscale using opencv. Then I used those images for training. When I was training, there was an error. "Invali

Product and summation with 3d and 1d arrays

Given a 3d array X with dimensions (K,n,m) that can be considered as a stack of K (n,m) matrices and a 1d vector b (dim n), the goal is to obtain the resulting

Stack the same row in each layer of a 3D numpy array

Hi is there a way to efficiently stack the same row in each layer of a 3D numpy array? I have an array like this: a = np.array([[["a111","a112","a113"],

numpy.core.multiarray failed to import after installing asammdf package

I try to read the mf4 file which has acoustic signal. from asammdf import MDF data = MDF('file1.mf4') The packages that I installed are asammdf 7.0.7 numpy

Extend a number of list zero into a multi-dimension array in Python

I am new to Python and I am trying to extend an existing list with a list of zero by a number. Below is my code but I believe there is another way to make it si

Solution to a system of non-linear equations in R^2

I am trying to find a solution to the following system where f and g are R^2 -> R^2 functions: f(x1,x2) = (y1,y2) g(y1,y2) = (x1,x2) I tried solving it using

Calculate Decay Rate in Python

I have dataset which somewhat follows an exponentional decay df_A Period Count 0 1600 1 894 2 959 3 773 4 509 5 206 I want

Create numpy array from function applied to (multiple) pandas columns

I have pd.DataFrame containing rows of values: import pandas as pd df = pd.DataFrame({"col1": [1, 2, 3, 4, 5, 6], "col2": [6, 5, 4, 3, 2, 1]}) I now want to f

Functional Programming: How does one create a new column in a multi-index data frame that is a function of another column?

Suppose the below simplified dataframe. (The actual df is much, much bigger.) How does one assign values to a new column f such that f is a function of another

Cryptographically secure pseudo random shuffle a list or array in python

I am in need of a shuffle function that uses CSPRNG (Cryptographically Secure Pseudo Random Number Generator) and can be seeded manually for the same output for

concatenate arrays of different lengths into one multidimensional array

I know that you cant stack or concatenate arrays of different lenghths in NumPy as all matrices need to be rectangular, but is there any other way to achieve th

Is there a Numpy equivalent of C++ std::vector reserve(), push_back() and shrink_to_fit()?

I would like to append elements to en empty Numpy array in-place. I know the maximum array size beforehand. I can't find a direct way to accomplish that, so her

When one of my column in dataframe is nested list, how should i transform it to multi-dimensional np.array?

I have the following data frame. test = { "a": [[[1,2],[3,4]],[[1,2],[3,4]]], "b": [[[1,2],[3,6]],[[1,2],[3,4]]] } df = pd.DataFrame(test) df a b 0