Category "numpy"

Simulating expectation of continuous random variable

Currently I want to generate some samples to get expectation & variance of it. Given the probability density function: f(x) = {2x, 0 <= x <= 1; 0 othe

How to color a grayscale image based on a mask?

I have two images: A grayscale image, and a binary mask with the same dimensions. How do I color the image on the mask, while the rest of the image remains gray

curve fitting error for optimal parameters while using scipy optimize curvefit in python

I am getting optimization errors while creating map of h3 moments using a self-defined function get_h3 in python for an image file called "image_test". The idea

How to make the dataframe faster ? either by using dictionary or numpy?

I am new to data structures and I would like to make my code faster (this is just part of a bigger code). Using dataframes while looking up variables is slowing

Calculating joint probabilities from two tensors of different sizes in pytorch

I am trying to calculate joint probabilities from two tensors.. It's a little bit confusing for me. Suppose we have : a = torch.Tensor((10, 2)) b = torch.Tensor

How to solve the problem with installing google colab?

Tried to solve a simple problem from google.colab import files import numpy as np file = files.upload() !ls my_array = np.loadtxt('train_vector.csv', delimi

Saving Detected Objects Individually from Point Cloud with RANSAC and DBSCAN

Hello, I am trying to detect objects from point cloud data using RANSAC and DBSCAN algorithms. I need to save these detected objects as separate files and then

tf.data pipeline from large numpy arrays for a multiple input, multiple output Keras model and distributed training

This question relates to the optimal setup for a multiple-input multiple-output Keras (Tensorflow) model given corresponding numpy arrays. For example, suppose

Generating list of hexagonal coordinates

I am gonna try to frame this in an understandable way but please let me know if further clarification is necessary. I am trying to create a list of hexagonal co

NRRD File of brain tumor is not being read into python with pynrrd module

I have nrrd files of the brain tumor. When reading the file into an array with a header and passing the code print(filename), I get an array of zeros. I checked

Handwriting detection with keras : using a `tf.Tensor` as a Python `bool` is not allowed in Graph execution

I've tried to run a code example (hosted on keras.io) regarding the handwriting recognition task. While playing with the code, I faced a TensorFlow-related issu

How to understand inaccurate results while using numpy.log?

I wish to calculate the natural logarithm of a value that is very close to 1, but not exactly one. For example, np.log(1 + 1e-22) is 0 and not some non-zero val

IndexError: too many indices for array: array is 0-dimensional, but 2 were indexed

I want to bring in a text file through PyQt5 and draw a graph with data values. import sys from PyQt5.QtWidgets import QApplication, QMainWindow, QTextEdit, QAc

How can fit a keras model with a dataframe of numpy arrays?

I want to train a model with self-generated matrices (word vectors). My data have the following datatypes: print(type(X)) print(type(X[0])) print(type(X[0][0]))

Finding a specific shape position in the Image

I want to Finding a specific shape position in the Image. Firstly, I have a main image like below and I have multiple icons like below. I want to find the posit

Send heavy data through protobuf. Custom field

I'm developing the API for the application using protobuf and grpc. I need to send the data with the arbitrary size. Sometimes it is small, sometimes huge. For

How can I efficiently bin 3D point cloud data based on point coordinates and desired bin grid size

I have a large point cloud in open3D and I want to basically make a 3D grid and bin the points based on which cube they are in. Other have called it "binning in

Numpy array multiplies a constant and passed to cosine fucntion shows abnormal values

I want to lower the frequency of a cosine function with 100 times: import numpy as np import math import matplotlib.pyplot as plt x = np.arange(0, 100, 0.1) y

Replacing a value in a column with a value from the same column based upon information

I am looking for a way to do Missing value imputation. There is a table of entries over a given time, with an entry per hour done on days. There is a seperate

Matlab System Function and Terminal Runs differently

I have a python code that I want to run in Matlab. It has an `import NumPy statement in it. The code runs without a problem in the terminal. But when I use Matl