Let's see how to set seed in Python pseudo-random

import numpy as np import pandas as pd random_state = 100 np.random.state = random_state np.random.seed = random_state mu, sigma = 0, 0.25 eps = np.random.normal(mu,sigma,size=100) print(eps[0]) I get different result each times. Update: I can not use np.random.seed(xxx)

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This is my code for now, it is basiclly parametric lines. static final int NUM_LINES = 30; A seed is setup for torch and python random (not numpy random) to randomize data each time dataloader iterator is created, so if you replace your np.random.randint (1000, size=1) by random.randint (0, 1000), data will be random for each epoch. 1 Like. odats (Oleh Dats) August 10, 2020, 4:17pm #13.

Depending on the number of. Directory of the status file should be set by /random/setDirectoryName.

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I also realize that using the same number, like set.seed(123) insures you can reproduce results.. But what I don't get is what do the values themselves mean. I am playing with several functions, and some use set.seed(1) or set.seed(300) or set.seed(12345).What does that number mean (if anything)- and when should I use 2021-03-01 2021-04-24 Description¶. Set one or more properties of one or more atoms. Since atom properties are initially assigned by the read_data, read_restart or create_atoms commands, this command changes those assignments. This can be useful for overriding the default values assigned by the create_atoms command (e.g. charge = 0.0).

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If minInclusive and maxExclusive are equal, then the "exclusive rule" is ignored and minInclusive will be returned.

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