In short, the problem I encounter is this: aa = np.arange(-1., 0.001, 0.01) aa[-1] Out[16]: 8.8817841970012523e-16 In reality, this cause a series problem si
Hopefully this is a quick and easy question that is not a repeat. I am looking for a built in numpy function (though it could also be a part of another library)
I need to find the first and the last element of a numpy.ndarray which are above a specified threshold. I found the following solution, which works, but it look
I want to change list to tensor with tf.convert_to_tensor, data is following: data=[ array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.
Suppose I have the following function: def f(x,y): return x*y How do I apply the funtion to each element in an NxM 2D numpy array using the multiprocessi
I'm using redis on an AI project. The idea is to have multiple environment simulators running policies on a lot of cpu cores. The simulators write experience
I was completing the first course of the deeplearning specialization, where the first programming assignment was to build a logistic regression model from scrat
Suppose there exists a numpy array, data. I am trying to do the equivalent of the following cv2.imwrite(filename, data) with open(filename, 'rb') as fp: da
I need to convert a pandas dataframe to a JSON object. However json.dumps(df.to_dict(orient='records')) fails as the boolean columns are not JSON serializa
I have these 2 tensors box_a = torch.randn(1,4) box_b = torch.randn(1,4) and i have a code in pytorch box_a[:, 2:].unsqueeze(1).expand(1, 1, 2) but i want to
I have df: Hour Energy Wh 1 4 2 6 3 9 4 15 I would like to add a column that shows the per hour differenc
I am getting this error and cant understand why the issue is appearing. Below will be the code and error. The result of the last printable workout [-8.545822
I use PyGLM and PyOpenGL I have specified the following Shader Storage Buffer in the Vertex Shader: layout(std430, binding = 1) buffer MVP { mat4 u_proj;
Say I have an array like np.array([[0,0,0,1,0], [0,0,0,0,0], [0,1,0,0,0], [0,0,0,1,0], [0,0,0,0,
I have a weird issue that the result doesn't change for each iteration. The code is the following: import pandas as pd import numpy as np X = np.arange(10,100)
I have been struggling the last days trying to compute the degrees of freedom of two pair of vectors (x and y) following reference of Chelton (1983) which is:
For example, there's an array like below. li = np.array([[1,2,3,4,5], [4,5,6,7,8], [1,2,3,4,5], [4,5,6,7,8],
In Python, how could you check if the type of a number is an integer without checking each integer type, i.e., 'int', 'numpy.int32', or 'numpy.int64'? I though
I want to make a realtime application, which involves finding the edges of a binary mask. I need something fast, without GPU if possible, that runs hopefully be
I have an existing two-column numpy array to which I need to add column names. Passing those in via dtype works in the toy example shown in Block 1 below. With