random-seed

If I use the Python function random.seed(my_seed) in one class in my module, will this seed remain for all the other classes instantiated in this module? Yes, the seed is set for the (hidden) global Random() instance in the module. From the documentation : The functions supplied by this module are actually bound methods of a hidden instance of the random.Random class. You can instantiate your own instances of Random to get generators that don’t share state. Use separate Random() instances if you need to keep the seeds separate; you can pass in a new seed when you instantiate it: >>> from

I have fixtures with initial data that needs to reside in my database (countries, regions, carriers, etc.). I have a task rake db:seed that will seed a database. namespace :db do desc "Load seed fixtures (from db/fixtures) into the current environment's database." task :seed => :environment do require 'active_record/fixtures' Dir.glob(RAILS_ROOT + '/db/fixtures/yamls/*.yml').each do |file| Fixtures.create_fixtures('db/fixtures/yamls', File.basename(file, '.*')) end end end I am a bit worried because this task wipes my database clean and loads the initial data. The fact that this is even

Though I have referred about the meaning of seed in google,I can't get the exact answer that I want.Can anybody explain with an example? It's an initial value for a random number generator to base its sequence of random numbers on. If you seed two random number generators with the same value, they'll produce the same sequence of numbers. This is useful for testing purposes. In production, you typically seed a random number generator with a value that's hard to guess, like the millisecond value from your system clock. A seed is used to initialize a pseudorandom number generator. It is a

I get a task to generate tens of thousands random number in c++. I've googled a lot about random number in c++ and look up the c++ reference, but I got confused now. As I know, random_device is a non-deterministic random number generator, but every time I re-run my program, the random number generated by random_device is the same. So how do I set a seed for random_device to make the random number is different when I restart my program? And I've read that "std::random_device could run out of entropy if you try to get a lot of numbers from it. That could cause it to block until you move the

I'm trying to write a unit test for some of my code that uses scikit-learn. However, my unit tests seem to be non-deterministic. AFAIK, the only places in my code where scikit-learn uses any randomness are in its LogisticRegression model and its train_test_split , so I have the following: RANDOM_SEED = 5 self.lr = LogisticRegression(random_state=RANDOM_SEED) X_train, X_test, y_train, test_labels = train_test_split(docs, labels, test_size=TEST_SET_PROPORTION, random_state=RANDOM_SEED) But this doesn't seem to work -- even when I pass a fixed docs and a fixed labels , the prediction