eustin

import matplotlib.pyplot as plt
import numpy as np
import tensorflow as tf

sentence = "Snoopy is a beagle"

tokens = sentence.split(" ")

print(tokens)

eustin

def calc_prop_matching_pairs(trial_results):
    num_matching_pairs = sum([1 for x in results.values() if x[0] == x[1]])
    num_total_pairs = len(results.values())

    # of all the pairs we have drawn, what proportion were matching pairs of socks?
    prop_matching_pairs = num_matching_pairs / num_total_pairs
    
    print(f"\nprop valid pairs over {NUM_TRIALS:,} trials: {prop_matching_pairs:.2f}")

eustin

def draw_pairs(num_trials):
    
    trial_results = {}
    
    for trial_num in range(num_trials):
        if trial_num % 10000 == 0:
            print(f"running trial number: {trial_num}")
        trial_results[trial_num+1] = np.random.choice(all_socks, 2, replace=False).tolist()
    
    return trial_results

eustin

import numpy as np

np.random.seed(123)