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
I am not completely satisfied with the default scientific formatting for the tick labels. For example, import numpy as np import pylab pylab.rcParams['text.us
I am trying to answer the following question "A colleague has produced a file with one DNA sequence on each line. Download the file and load it into Python usi
I'm trying to run a simple testfile on a remote Server. But it throws a numpy error for matplotlib.pyplot. Here is the code import matplotlib.pyplot as plt impo
I see there is an array_split and split methods but these are not very handy when you have to split an array of length which is not integer multiple of the chun
I want to fit a plane to some data points and draw it. My current code is this: import numpy as np from mpl_toolkits.mplot3d import Axes3D import matplotlib.py
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