As part of some simulations I'm running I need to output the cumulative distribution of the output of some algorithms:
tests = []
numtests = 100
for i in range(0, numtests):
#random
zeros = [0] * 1024
ones = [1] * 10
#ones = [randint(0,1023) for _ in range(0,10)]
input = zeros + ones
shuffle(input)
tests.append(HGBSA(input,10))
count = [x[0] for x in tests]
found = [x[1] for x in tests]
found.sort()
num = Counter(found)
freqs = [x for x in num.values()]
cumsum = [sum(item for item in freqs[0:rank+1]) for rank in range(len(freqs))]
normcumsum = [float(x)/numtests for x in cumsum]
print(freqs)
print(cumsum)
print(normcumsum)
print(sorted(num.keys()))
figure(0)
plt.plot(sorted(num.keys()), normcumsum)
plt.xlim(0,100)
plt.show()
As the above code shows, I'm running my algorithm 100 times with randomly generated input and then creating a cumulative distribution from the results.
I want to do a similar thing with other algorithms, and in c++ I could write a template class/template function which took a (pointer to a) method as am argument.
I'd like to ask if there is a way in python to create a function/class which produces the output I want, but takes a function as an input, so I avoid duplicating code all over the place.
This is simple to do in Python. You can pass functions (or classes) around like anything else.
def run_test(test_function):
tests = []
numtests = 100
for i in range(0, numtests):
#random
zeros = [0] * 1024
ones = [1] * 10
#ones = [randint(0,1023) for _ in range(0,10)]
input = zeros + ones
shuffle(input)
tests.append(test_function(input,10))
count = [x[0] for x in tests]
found = [x[1] for x in tests]
found.sort()
num = Counter(found)
freqs = [x for x in num.values()]
cumsum = [sum(item for item in freqs[0:rank+1]) for rank in range(len(freqs))]
normcumsum = [float(x)/numtests for x in cumsum]
print(freqs)
print(cumsum)
print(normcumsum)
print(sorted(num.keys()))
figure(0)
plt.plot(sorted(num.keys()), normcumsum)
plt.xlim(0,100)
plt.show()
run_test(HGBSA)
run_test(SOME_OTHER_FUNCTION)
I am not sure that i understand the question, but sounds like you want to pass a function as function argument? You can do that right of the bat in python as everything is passed by reference and nothing stops you from passing a reference to a function as an argument.
Related
Everybody. I wrote the following code. Please help me, to optimize this, when I submit in some test cases compiler writing time-limit-exceeded 2.069s / 13.33Mb.
import math
N = int(input())
arr = [None]*N; new_list = []
stepen = 0; res = .0;
arr = input().split(" ")
arr = [float(h) for h in arr]
Q = int(input())
for j in range(Q):
x, y = input().split()
new_list.extend([int(x), int(y)])
for i, j in zip(new_list[0::2], new_list[1::2]):
stepen = (j - i)+ 1
res = math.prod(arr[i:j+1])
print(pow(res, 1./stepen))
The slowest thing in your algorithm is the math.prod(arr[i:j+1]). If all the x and y inputs denote the entire range, you will surely TLE, as the calls to prod must loop over the entire range.
In order to avoid this, you must do a prefix product on your array. The idea is this: Keep a second array pref, with the property that pref[i] = arr[i] * pref[i-1]. As a result, pref[i] will be the product of everything at the ith position and before in arr.
Then to find the product between positions i and j, you want pref[j] / pref[i-1]. See if you can figure out why this gives the correct answer.
I've managed to create a for-loop, which provides me with the results that I want, but I'm struggling to collate these results into a single array, so that I can plot it as my x value on a graph.
I have considered collating them into a single list first (but am also struggling to do this).
I have also tried to append, extend, and stack the array below, but nothing seems to work.
When trying to append, I got an error message appears to say that there is not 'value' present.
a = 0.1
x = 0.2
for i in range(1,10):
a = a**3
x = x**2
array = np.array ([a, x])
print (array)
The code above provides 9 individual arrays, as opposed to just 1.
i.e. [(a1, x1), (a2, x2), ... (a9, x9)]
Any suggestions to fix this or alternative methods would be greatly appreciated! Thank you!
okk so you want to store both variable values in this pattern (a1,x1),(a2,x2)....
So this can be done in this way
like first suppose two separate list for a and x , and then merge them into the desired format
the whole code is shown here
import numpy as np
a = 0.1
x = 0.2
list1= []
list2=[]
for i in range(1,10):
a = a**3
x = x**2
list1.append(a)
list2.append(x)
merged_list = [(list1[i], list2[i]) for i in range(0, len(list1))]
print(merged_list)
this will give you the desired output . Thanks for asking
Use append to append value in list
a = 0.1
x = 0.2
array = []
for i in range(1,10):
a = a**3
x = x**2
array.append([a, x])
print(array)
If you want numpy.array
a = np.power(np.repeat(0.1, 10), 3)
x = np.power(np.repeat(0.2, 10), 2)
print(np.array(list(zip(a,x))))
Do you want to append multiple items to a list?
First solution:
l = []
for i in range(1,10):
a = a**3
x = x**2
l.extend([a, x])
print(l)
Second solution:
l = []
for i in range(1,10):
a = a**3
x = x**2
l+= [a, x]
print(l)
Do you want to append multiple items to a numpy array?
array = np.array([])
for i in range(1,10):
a = a**3
x = x**2
array = np.append(array, [a,x])
print(array)
I'm having some troubles trying to use four lists with the zip function.
In particular, I'm getting the following error at line 36:
TypeError: zip argument #3 must support iteration
I've already read that it happens with not iterable objects, but I'm using it on two lists! And if I try use the zip only on the first 2 lists it works perfectly: I have problems only with the last two.
Someone has ideas on how to solve that? Many thanks!
import numpy
#setting initial values
R = 330
C = 0.1
f_T = 1/(2*numpy.pi*R*C)
w_T = 2*numpy.pi*f_T
n = 10
T = 1
w = (2*numpy.pi)/T
t = numpy.linspace(-2, 2, 100)
#making the lists c_k, w_k, a_k, phi_k
c_karray = []
w_karray = []
A_karray = []
phi_karray = []
#populating the lists
for k in range(1, n, 2):
c_k = 2/(k*numpy.pi)
w_k = k*w
A_k = 1/(numpy.sqrt(1+(w_k)**2))
phi_k = numpy.arctan(-w_k)
c_karray.append(c_k)
w_karray.append(w_k)
A_karray.append(A_k)
phi_karray.append(phi_k)
#making the function w(t)
w = []
#doing the sum for each t and populate w(t)
for i in t:
w_i = ([(A_k*c_k*numpy.sin(w_k*i+phi_k)) for c_k, w_k, A_k, phi_k in zip(c_karray, w_karray, A_k, phi_k)])
w.append(sum(w_i)
Probably you mistyped the last 2 elements in zip. They should be A_karray and phi_karray, because phi_k and A_k are single values.
My result for w is:
[-0.11741034896740517,
-0.099189027720991918,
-0.073206290274556718,
...
-0.089754003567358978,
-0.10828235682188027,
-0.1174103489674052]
HTH,
Germán.
I believe you want zip(c_karray, w_karray, A_karray, phi_karray). Additionally, you should produce this once, not each iteration of the for the loop.
Furthermore, you are not really making use of numpy. Try this instead of your loops.
d = numpy.arange(1, n, 2)
c_karray = 2/(d*numpy.pi)
w_karray = d*w
A_karray = 1/(numpy.sqrt(1+(w_karray)**2))
phi_karray = numpy.arctan(-w_karray)
w = (A_karray*c_karray*numpy.sin(w_karray*t[:,None]+phi_karray)).sum(axis=-1)
this probably leads to scipy/numpy, but right now I'm happy with any functionality as I couldn't find anything in those packages. I have a matrix that contains data for a multi-variate distribution (let's say, 2, for the fun of it). Is there any function to compute (higher) moments of that? All I could find was numpy.mean() and numpy.cov() :o
Thanks :)
/edit:
So some more detail: I have multivariate data, that is, a matrix where rows display variables and columns observations. Now I would like to have a simple way of computing the joint moments of that data, as defined in http://en.wikipedia.org/wiki/Central_moment#Multivariate_moments .
I'm pretty new to python/scipy so I'm not sure I'd be the best person to code this one up, especially for the n-variables case (note that the wikipedia definition is for n=2), and I kind of expected there to be some out-of-the-box thing to use as I thought this would be a standard problem.
/edit2:
Just for the future, in case someone wants to do something similar, the following code (which is still under review) should give the sample equivalent of the raw moments E(X^2), E(Y^2), etc. It only works for two variables right now, but it should be extendable if one feels the need. If you see some mistakes or unclean/unpython-nish code, feel free to comment.
from numpy import *
# this function should return something as
# moments[0] = 1
# moments[1] = mean(X), mean(Y)
# moments[2] = 1/n*X'X, 1/n*X'Y, 1/n*Y'Y
# moments[3] = mean(X'X'X), mean(X'X'Y), mean(X'Y'Y),
# mean(Y'Y'Y)
# etc
def getRawMoments(data, moment, axis=0):
a = moment
if (axis==0):
n = float(data.shape[1])
X = matrix(data[0,:]).reshape((n,1))
Y = matrix(data[1,:]).reshape((n,1))
else:
n = float(data.shape[0])
X = matrix(data[:,0]).reshape((n,1))
Y = matrix(data[:,1]).reshape((n,11))
result = 1
Z = hstack((X,Y))
iota = ones((1,n))
moments = {}
moments[0] = 1
#first, generate huge-ass matrix containing all x-y combinations
# for every power-combination k,l such that k+l = i
# for all 0 <= i <= a
for i in arange(1,a):
if i==2:
moments[i] = moments[i-1]*Z
# if even, postmultiply with X.
elif i%2 == 1:
moments[i] = kron(moments[i-1], Z.T)
# Else, postmultiply with X.T
elif i%2==0:
temp = moments[i-1]
temp2 = temp[:,0:n]*Z
temp3 = temp[:,n:2*n]*Z
moments[i] = hstack((temp2, temp3))
# since now we have many multiple moments
# such as x**2*y and x*y*x, filter non-distinct elements
momentsDistinct = {}
momentsDistinct[0] = 1
for i in arange(1,a):
if i%2 == 0:
data = 1/n*moments[i]
elif i == 1:
temp = moments[i]
temp2 = temp[:,0:n]*iota.T
data = 1/n*hstack((temp2))
else:
temp = moments[i]
temp2 = temp[:,0:n]*iota.T
temp3 = temp[:,n:2*n]*iota.T
data = 1/n*hstack((temp2, temp3))
momentsDistinct[i] = unique(data.flat)
return momentsDistinct(result, axis=1)
I am writing a code snippet for a random algebraic equation generator for a larger project. Up to this point, everything has worked well. The main issue is simple. I combined the contents of a dictionary in sequential order. So for sake of argument, say the dictionary is: exdict = {a:1 , b:2 , c:3 , d:4}, I append those to a list as such: exlist = [a, b, c, d, 1, 2, 3, 4]. The length of my list is 8, which half of that is obviously 4. The algorithm is quite simple, whatever random number is generated between 1-4(or as python knows as 0-3 index), if you add half of the length of the list to that index value, you will have the correct value.
I have done research online and on stackoverflow but cannot find any answer that I can apply to my situation...
Below is the bug check version of my code. It prints out each variable as it happens. The issue I am having is towards the bottom, under the ### ITERATIONS & SETUP comment. The rest of the code is there so it can be ran properly. The primary issue is that a + x should be m, but a + x never equals m, m is always tragically lower.
Bug check code:
from random import randint as ri
from random import shuffle as sh
#def randomassortment():
letterss = ['a','b','x','d','x','f','u','h','i','x','k','l','m','z','y','x']
rndmletters = letterss[ri(1,15)]
global newdict
newdict = {}
numberss = []
for x in range(1,20):
#range defines max number in equation
numberss.append(ri(1,20))
for x in range(1,20):
rndmnumber = numberss[ri(1,18)]
rndmletters = letterss[ri(1,15)]
newdict[rndmletters] = rndmnumber
#x = randomassortment()
#print x[]
z = []
# set variable letter : values in list
for a in newdict.keys():
z.append(a)
for b in newdict.values():
z.append(b)
x = len(z)/2
test = len(z)
print 'x is value %d' % (x)
### ITERATIONS & SETUP
iteration = ri(2,6)
for x in range(1,iteration):
a = ri(1,x)
m = a + x
print 'a is value: %d' % (a)
print 'm is value %d' %(m)
print
variableletter = z[a]
variablevalue = z[m]
# variableletter , variablevalue
edit - My questions is ultimately, why is a + x returning a value that isn't a + x. If you run this code, it will print x , a , and m. m is supposed to be the value of a + x, but for some reason, it isnt?
The reason this isn't working as you expect is that your variable x originally means the length of the list, but it's replaced in your for x in range loop- and then you expect it to be equal to the length of the list. You could just change the line to
for i in range(iteration)
instead.
Also note that you could replace all the code in the for loop with
variableletter, variablevalue = random.choice(newdict.items())
Your problem is scope
which x are you looking for here
x = len(z)/2 # This is the first x
print 'x is value %d' % (x)
### ITERATIONS & SETUP
iteration = ri(2,6)
# x in the for loop is referencing the x in range...
for x in range(1,iteration):
a = ri(1,x)
m = a + x