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import matplotlib.pyplot as plt | |
import numpy as np | |
x=np.random.randn(10000) | |
plt.hist(x,100) | |
plt.title(r'Normal Distribution with $\mu = 0 and \sigma = 1$ ') | |
plt.savefig('matplotlib_histogram.png') | |
plt.show() |
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import math | |
import matplotlib.pyplot as plt | |
import numpy as np | |
import scipy.stats | |
mean = 0 | |
variance = 1 | |
sigma = math.sqrt(variance) |
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""" | |
helloevolve.py implements a genetic algorithm that starts with a base | |
population of randomly generated strings, iterates over a certain number of | |
generations while implementing 'natural selection', and prints out the most fit | |
string. | |
The parameters of the simulation can be changed by modifying one of the many | |
global variables. To change the "most fit" string, modify OPTIMAL. POP_SIZE | |
controls the size of each generation, and GENERATIONS is the amount of | |
generations that the simulation will loop through before returning the fittest |
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from flask import Flask | |
from flask import request | |
import json | |
import requests | |
import hashlib as hasher | |
import datetime as date | |
node = Flask(__name__) | |
# Define what a Snakecoin block is | |
class Block: |
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import hashlib as hasher | |
import datetime as date | |
# Define what a Snakecoin block is | |
class Block: | |
def __init__(self, index, timestamp, data, previous_hash): | |
self.index = index | |
self.timestamp = timestamp | |
self.data = data | |
self.previous_hash = previous_hash |
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# [ENTER_SOURCE_CODE] | |
# A.G. (c) 2017. All Rights Reserved. | |
# January 4th, 2017 | |
import time | |
class EnterSourceCode: | |
def __init__(self, time, filename, sourcecode, category): | |
self.time = time | |
self.filename = filename |
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# DATETIME: (date at top) | |
# EXPERIMENT: (number and title clearly stated) | |
# (Clear statement of purpose) | |
# PROCEDURE: (succinct description of procedure | |
# SIGNATURE: |
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#include <stdio.h> | |
typedef struct { | |
char * name; | |
int age; | |
} person; | |
int main() { | |
person john; |
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# very simple Mersenne prime search. | |
# AW2016-01-23 | |
import time | |
import math | |
# http://stackoverflow.com/questions/16004407/a-fast-prime-number-sieve-in-python | |
def prime_sieve(n): | |
size = n//2 |
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import math | |
import random | |
def str_to_ascii(text): | |
""" Gets rid of on ASCII characters in text""" | |
return ''.join(ch for ch in text if ord(ch)<128) | |
def maxmatch(T, p, w=2**12-1, max_length=2**5-1): | |
""" finds a maximum match of length k<=2**5-1 in a | |
w long window, T[p:p+k] with T[p-m:p-m+k]. |
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