Print Nicely with pprint() All of our examples have used print() (or just the variable name, in the interactive interpreter) to print things. Sometimes, the results are hard to read. We need a pretty printer such as pprint() Get Random We played with random.choice() at the beginning o...
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1import numpy as np 2 3def complex_matrix(xmin, xmax, ymin, ymax, pixel_density): 4 re = np.linspace(xmin, xmax, int((xmax - xmin) * pixel_density)) 5 im = np.linspace(ymin, ymax, int((ymax - ymin) * pixel_density)) 6 return re[np.newaxis, :] + im[:, np.newaxis...
This list isn’t exhaustive as there are more representations, such as the matrix representation of complex numbers. Having the choice lets you pick the most convenient one to tackle a given problem. For example, you’re going to need the exponential form to calculate discrete Fourier transform...
print_statement() if __name__ == '__main__': cprofile.run('main()') output: array created successfully 400041 function calls in 0.091 seconds ordered by: standard name ncalls tottime percall cumtime percall filename:lineno(function) 1 0.004 0.004 0.091 0.091 <ipython-input-10-4dd6137...
window_size = 3 # wsize default 3; 5; 7 for SGBM reduced size image; 15 for SGBM full size image (1300px and above); 5 Works nicely left_matcher = cv2.StereoSGBM_create( minDisparity=-1, numDisparities=5*16, # max_disp has to be dividable by 16 f. E. HH 192, 256 ...
name) ru.printMatrix(sizeBinsA, "Size [Nodes]", timeBinsA + ['>'], "Runtime [h]", useD, "Usage [kAU]") ru.printMatrix(sizeBinsA, "Size [Nodes]", timeBinsA + ['>'], "Runtime [h]", jobD, "Jobs") meanByUse = appTotWeight/appTotUse pJob = 100.0 * appSumA[2]/totjobs...
matrix = [[1,2,3], [4,5,6], [7,8,9]] transpose = {j: {i: matrix[i][j]foriinrange(3)}forjinrange(3)}print(transpose)# Output: {0: {0: 1, 1: 4, 2: 7}, 1: {0: 2, 1: 5, 2: 8}, 2: {0: 3, 1: 6, 2: 9}} ...
It is nicely implemented in the statsmodel package. It accepts a 2D array with 2 columns as the main argument. The values are in the first column and the predictor (X) is in the second column. The Null hypothesis is: the series in the second column, does not Granger cause the series...
from __future__ import print_function # 从python未来的版本中import输出函数,主要是Python的print不需要括号,而Python3需要括号 import torch # torch中定义了多维张量的运算API,例如创建、索引、切片、连接、转置、加减乘除 import torch.nn as nn # 包含搭建网络层的模块(Modules)和一系列的loss函数,例如全连接...