if '-Ntoss' in sys.argv:
p = sys.argv.index('-Ntoss')
Nt = int(sys.argv[p+1])
if Nt > 0:
Ntoss = Nt
if '-Nexp' in sys.argv:
p = sys.argv.index('-Nexp')
Ne = int(sys.argv[p+1])
if Ne > 0:
Nexp = Ne
if '-output' in sys.argv:
p = sys.argv.index('-output')
OutputFileName = sys.argv[p+1]
doOutputFile = True
# class instance of our Random class using seed
random = Random(seed)
if doOutputFile:
outfile = open(OutputFileName, 'w')
for e in range(0,Nexp):
for t in range(0,Ntoss):
outfile.write(str(random.Bernoulli(prob))+" ")
outfile.write(" \n")
outfile.close()
else:
for e in range(0,Nexp):
for t in range(0,Ntoss):
print(random.Bernoulli(prob), end=' ')
print(" ")
#! /usr/bin/env python
# imports of external packages to use in our code
import sys
import numpy as np
import matplotlib.pyplot as plt
import math
#import random
from Random2 import Random
random = Random()
#loop Rayleigh through an empty array to create distribution
n=100000
a = []
for x in range(0,n):
a.append(random.Rayleigh())
#plot array
n, bins, patches = plt.hist(a, 50, density=True, facecolor='g', alpha=0.75)
plt.xlabel('x', fontsize = 16, color = "blue")
plt.ylabel('Probability', fontsize = 16, color = "red")
plt.title('Rayleigh distribution')
#plt.legend(['cool green bars'], loc = 'upper left')
plt.grid(True)
plt.show()
p = sys.argv.index('-Nmeas')
Nt = int(sys.argv[p + 1])
if Nt > 0:
Nmeas = Nt
if '-Nexp' in sys.argv:
p = sys.argv.index('-Nexp')
Ne = int(sys.argv[p + 1])
if Ne > 0:
Nexp = Ne
if '-output' in sys.argv:
p = sys.argv.index('-output')
OutputFileName = sys.argv[p + 1]
doOutputFile = True
# class instance of our Random class using seed
random = Random(seed)
if doOutputFile:
outfile = open(OutputFileName, 'w')
outfile.write(str(rate) + " \n")
for e in range(0, Nexp):
for t in range(0, Nmeas):
outfile.write(str(random.Exponential(rate)) + " ")
outfile.write(" \n")
outfile.close()
else:
print(rate)
for e in range(0, Nexp):
for t in range(0, Nmeas):
print(random.Exponential(rate), end=' ')
print(" ")
import numpy as np
import sys
import matplotlib.pyplot as plt
import math
sys.path.append(".")
from Random2 import Random
#global variables
bin_width = 0.
Xmin = 0.
Xmax = 1.
random = Random()
# Rayleigh distribution
# Note: multiply by bin width to match histogram
def Rayleigh(x):
return ((x / (0.1**2)) * np.exp(-x * x / (2 * (0.1**2))))
def PlotRayleigh(x, bin_width):
return bin_width * Rayleigh(x)
# Uniform (flat) distribution
# Note: multiply by bin width to match histogram
def Flat(x):
return 6.1
def __init__(self, seed = 5555):
self.m_random = Random(seed)
class MySort:
"""A crappy sorting class"""
# initialization method for Random class
def __init__(self, seed = 5555):
self.m_random = Random(seed)
# sorts array using bubble sort
def BubbleSort(self, array):
n = len(array)
for i in range(n):
# Create a flag that will allow the function to
# terminate early if there's nothing left to sort
already_sorted = True
# Start looking at each item of the list one by one,
# comparing it with its adjacent value. With each
# iteration, the portion of the array that you look at
# shrinks because the remaining items have already been
# sorted.
for j in range(n - i - 1):
if array[j] > array[j + 1]:
# If the item you're looking at is greater than its
# adjacent value, then swap them
array[j], array[j + 1] = array[j + 1], array[j]
# Since you had to swap two elements,
# set the `already_sorted` flag to `False` so the
# algorithm doesn't finish prematurely
already_sorted = False
# If there were no swaps during the last iteration,
# the array is already sorted, and you can terminate
if already_sorted:
break
return array
# sorts array using insertion sort
def InsertionSort(self, array):
# Loop from the second element of the array until
# the last element
for i in range(1, len(array)):
# This is the element we want to position in its
# correct place
key_item = array[i]
# Initialize the variable that will be used to
# find the correct position of the element referenced
# by `key_item`
j = i - 1
# Run through the list of items (the left
# portion of the array) and find the correct position
# of the element referenced by `key_item`. Do this only
# if `key_item` is smaller than its adjacent values.
while j >= 0 and array[j] > key_item:
# Shift the value one position to the left
# and reposition j to point to the next element
# (from right to left)
array[j + 1] = array[j]
j -= 1
# When you finish shifting the elements, you can position
# `key_item` in its correct location
array[j + 1] = key_item
return array
# sorts array using quicksort
def QuickSort(self, array):
# If the input array contains fewer than two elements,
# then return it as the result of the function
if len(array) < 2:
return array
low, same, high = [], [], []
# Select your `pivot` element randomly
pivot = array[int(self.m_random.rand()*len(array))]
for item in array:
# Elements that are smaller than the `pivot` go to
# the `low` list. Elements that are larger than
# `pivot` go to the `high` list. Elements that are
# equal to `pivot` go to the `same` list.
if item < pivot:
low.append(item)
elif item == pivot:
same.append(item)
elif item > pivot:
high.append(item)
# The final result combines the sorted `low` list
# with the `same` list and the sorted `high` list
return self.QuickSort(low) + same + self.QuickSort(high)
# sorts array using default Python sort
def DefaultSort(self, array):
array.sort()
return array
if '-Nexp' in sys.argv:
p = sys.argv.index('-Nexp')
Ne = int(sys.argv[p + 1])
if Ne > 0:
Nexp = Ne
if '-output' in sys.argv:
p = sys.argv.index('-output')
OutputFileName = sys.argv[p + 1]
doOutputFile = True
#extract individual probabilities from list; may have to automate if you choose to work with dice w/o 6 sides
prob1, prob2, prob3, prob4, prob5, prob6 = prob_list[0], prob_list[
1], prob_list[2], prob_list[3], prob_list[4], prob_list[5]
# class instance of our Random class using seed
random = Random(seed)
if doOutputFile:
outfile = open(OutputFileName, 'w')
for e in range(0, Nexp):
for t in range(0, Nroll):
outfile.write(
str(
random.Diceroll(prob1, prob2, prob3, prob4, prob5,
prob6)) + " ")
outfile.write(" \n")
outfile.close()
else:
for e in range(0, Nexp):
for t in range(0, Nroll):
print(random.Diceroll(prob1, prob2, prob3, prob4, prob5,