CODEWITHSUNDEEP
pythonlistfor-loopsimulationprobability
d789w
d789w

Reputation: 377

Print elements of a list based on probabilities in for loop

Based on the probabilities of p, if p < 0.5 I would like to take letters of the corresponding positions of list1.

For example:

for i in range(5):
    list1 = ['A', 'B', 'C', 'D', 'E']
    p = np.random.uniform(low= 0.0, high= 1.0, size=5)
    print(p)

Output is: 

[ 0.46565909  0.741431    0.65590764  0.87347741  0.38465195]
[ 0.62172525  0.80688763  0.40391766  0.28042554  0.34544989]
[ 0.00138961  0.56959351  0.69043625  0.59473154  0.84042555]
[ 0.18535428  0.63470281  0.27882709  0.78731892  0.63624727]
[ 0.89383216  0.72008758  0.66048462  0.94064897  0.1484418 ]

So based on the probabilities I would like my output to be:

['A', 'E']
['C', 'D', 'E']
['A']
['A', 'C']
['E']

Upvotes: 0

Views: 228

Answers (4)

iGian
iGian

Reputation: 11183

Just another option:

[ [l for r, l in zip(np.random.uniform(low= 0.0, high= 1.0, size=5), list1) if r > 0.5] for i in range(5) ]

#=> [['A'], ['D', 'E'], ['B', 'C'], ['D'], ['B', 'C', 'E']]

Upvotes: 1

Naga kiran
Naga kiran

Reputation: 4607

you can apply direct less than operator if you change your list to numpy array

for i in range(5):
    list1 = np.asarray(['A', 'B', 'C', 'D', 'E'])
    p = np.random.uniform(low= 0.0, high= 1.0, size=5)
    print(list1[p < 0.5])

Out:

['C']
['A' 'D']
['A' 'B' 'C' 'D']
['A' 'B' 'E']
['A' 'B' 'D']

Upvotes: 1

Inon Peled
Inon Peled

Reputation: 711

One way to solve this is with np.where, as suggested in another answer here.

Alternatively, in the style of functional programming, filter the list of letters by a function that "tosses the coin", namely:

filter(lambda letter: np.random.uniform() < 0.5, list1)

Or, equivalently:

(letter for letter in list1 if np.random.uniform() < 0.5)

Upvotes: 0

Osman Mamun
Osman Mamun

Reputation: 2882

Use np.where to get the indices where the values are less than 0.5 and then print those elements:

for i in range(5):
    list1 = ['A', 'B', 'C', 'D', 'E']
    mask = np.where(np.random.uniform(low= 0.0, high= 1.0, size=5) < 0.5)
    print([list1[i] for i in mask[0]])

#output (The output is stochastic meaning they will change on each iteration unless you use fixed random state)
['C']
['A', 'B', 'C', 'E']
['D', 'E']
['A', 'C', 'D']
['B', 'C', 'E']

Upvotes: 3

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