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Distribute value over list

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-1

Given the amount S=25 and list L = [10,20,30] I want to distribute S over L in the following way:
output -> [10, 15, 0]

I wrote the following code, which does the job:

S = 25
l = [10,20,30]
res= []
b = True

for value in l:
 if b == True: 
 if S - value >0:
 res.append(value)
 else:
 res.append(S)
 b= False
 S -= value
 else:
 res.append(0)

Is it possible to rewrite it, maybe as a one-liner? (numpy is allowed)

python list numpy

share|improve this question

edited Feb 19 '18 at 0:55

Kirill

asked Feb 19 '18 at 0:38

KirillKirill

1144 bronze badges

add a comment | 

-1

Given the amount S=25 and list L = [10,20,30] I want to distribute S over L in the following way:
output -> [10, 15, 0]

I wrote the following code, which does the job:

S = 25
l = [10,20,30]
res= []
b = True

for value in l:
 if b == True: 
 if S - value >0:
 res.append(value)
 else:
 res.append(S)
 b= False
 S -= value
 else:
 res.append(0)

Is it possible to rewrite it, maybe as a one-liner? (numpy is allowed)

python list numpy

share|improve this question

edited Feb 19 '18 at 0:55

Kirill

asked Feb 19 '18 at 0:38

KirillKirill

1144 bronze badges

add a comment | 

Given the amount S=25 and list L = [10,20,30] I want to distribute S over L in the following way:
output -> [10, 15, 0]

I wrote the following code, which does the job:

S = 25
l = [10,20,30]
res= []
b = True

for value in l:
 if b == True: 
 if S - value >0:
 res.append(value)
 else:
 res.append(S)
 b= False
 S -= value
 else:
 res.append(0)

Is it possible to rewrite it, maybe as a one-liner? (numpy is allowed)

python list numpy

share|improve this question

edited Feb 19 '18 at 0:55

Kirill

asked Feb 19 '18 at 0:38

KirillKirill

1144 bronze badges

S = 25
l = [10,20,30]
res= []
b = True

for value in l:
 if b == True: 
 if S - value >0:
 res.append(value)
 else:
 res.append(S)
 b= False
 S -= value
 else:
 res.append(0)

share|improve this question

edited Feb 19 '18 at 0:55

Kirill

asked Feb 19 '18 at 0:38

KirillKirill

1144 bronze badges

share|improve this question

edited Feb 19 '18 at 0:55

Kirill

asked Feb 19 '18 at 0:38

KirillKirill

1144 bronze badges

asked Feb 19 '18 at 0:38

KirillKirill

1144 bronze badges

asked Feb 19 '18 at 0:38

KirillKirill

1144 bronze badges

3 Answers
3

active

oldest

votes

2

Slightly shorter and more readable:

def distribute(S, L):
 res = []
 for e in L:
 res.append(min(e, S))
 S = max(0, S-e)
 return res

While you can make this (or anything really) a one-liner, I wouldn't force it. It's better to keep things readable.

You can also use an equivalent generator function:

def distribute(S, L):
 for e in L:
 yield min(e, S)
 S = max(0, S-e)

list(distribute(S, l))

share|improve this answer

edited Feb 19 '18 at 1:07

jpp

107k2121 gold badges8989 silver badges134134 bronze badges

answered Feb 19 '18 at 0:57

viraptorviraptor

25.3k77 gold badges8282 silver badges155155 bronze badges

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  I added a (in my opinion) more pythonic generator. Your solution is still very good. +1
  
  – jpp
  Feb 19 '18 at 1:08
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  I love the latter one. Cool!
  
  – Kirill
  Feb 19 '18 at 1:10
  

  
  
  
  

add a comment | 

1

This is one way, but please do not get attached to one-liners for the sake of them being one-liners. Often they are not the best method, either in terms of readability or performance.

from itertools import accumulate

S = 25
l = [10, 20, 30]

res = [i if j <= S else max(0, S-k) 
 for i, j, k in zip(l, accumulate(l), accumulate([0]+l))]

# [10, 15, 0]

share|improve this answer

edited Feb 19 '18 at 1:04

answered Feb 19 '18 at 0:50

jppjpp

107k2121 gold badges8989 silver badges134134 bronze badges

add a comment | 

0

numpy

Since OP specifically asked for numpy, let's assume this is about large arrays. I think distribute in the OP subject was a key word, because this is very similar to conversion between PDF and CDF (https://en.wikipedia.org/wiki/Cumulative_distribution_function) and the inverse:

a = numpy.array([10, 20, 30])
c = a.cumsum() # [10, 30, 60]
b = c.clip(0, 25) # [20, 25, 25]
numpy.ediff1d(b, to_begin=b[0]) # [10, 15, 0]

share|improve this answer

answered Mar 28 at 7:32

Dima TisnekDima Tisnek

7,43322 gold badges3838 silver badges8787 bronze badges

add a comment | 

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2

Slightly shorter and more readable:

def distribute(S, L):
 res = []
 for e in L:
 res.append(min(e, S))
 S = max(0, S-e)
 return res

While you can make this (or anything really) a one-liner, I wouldn't force it. It's better to keep things readable.

You can also use an equivalent generator function:

def distribute(S, L):
 for e in L:
 yield min(e, S)
 S = max(0, S-e)

list(distribute(S, l))

share|improve this answer

edited Feb 19 '18 at 1:07

jpp

107k2121 gold badges8989 silver badges134134 bronze badges

answered Feb 19 '18 at 0:57

viraptorviraptor

25.3k77 gold badges8282 silver badges155155 bronze badges

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  I added a (in my opinion) more pythonic generator. Your solution is still very good. +1
  
  – jpp
  Feb 19 '18 at 1:08
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  I love the latter one. Cool!
  
  – Kirill
  Feb 19 '18 at 1:10
  

  
  
  
  

add a comment | 

2

Slightly shorter and more readable:

def distribute(S, L):
 res = []
 for e in L:
 res.append(min(e, S))
 S = max(0, S-e)
 return res

While you can make this (or anything really) a one-liner, I wouldn't force it. It's better to keep things readable.

You can also use an equivalent generator function:

def distribute(S, L):
 for e in L:
 yield min(e, S)
 S = max(0, S-e)

list(distribute(S, l))

share|improve this answer

edited Feb 19 '18 at 1:07

jpp

107k2121 gold badges8989 silver badges134134 bronze badges

answered Feb 19 '18 at 0:57

viraptorviraptor

25.3k77 gold badges8282 silver badges155155 bronze badges

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  I added a (in my opinion) more pythonic generator. Your solution is still very good. +1
  
  – jpp
  Feb 19 '18 at 1:08
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  I love the latter one. Cool!
  
  – Kirill
  Feb 19 '18 at 1:10
  

  
  
  
  

add a comment | 

Slightly shorter and more readable:

def distribute(S, L):
 res = []
 for e in L:
 res.append(min(e, S))
 S = max(0, S-e)
 return res

While you can make this (or anything really) a one-liner, I wouldn't force it. It's better to keep things readable.

You can also use an equivalent generator function:

def distribute(S, L):
 for e in L:
 yield min(e, S)
 S = max(0, S-e)

list(distribute(S, l))

share|improve this answer

edited Feb 19 '18 at 1:07

jpp

107k2121 gold badges8989 silver badges134134 bronze badges

answered Feb 19 '18 at 0:57

viraptorviraptor

25.3k77 gold badges8282 silver badges155155 bronze badges

def distribute(S, L):
 res = []
 for e in L:
 res.append(min(e, S))
 S = max(0, S-e)
 return res

def distribute(S, L):
 for e in L:
 yield min(e, S)
 S = max(0, S-e)

list(distribute(S, l))

share|improve this answer

edited Feb 19 '18 at 1:07

jpp

107k2121 gold badges8989 silver badges134134 bronze badges

answered Feb 19 '18 at 0:57

viraptorviraptor

25.3k77 gold badges8282 silver badges155155 bronze badges

edited Feb 19 '18 at 1:07

jpp

107k2121 gold badges8989 silver badges134134 bronze badges

edited Feb 19 '18 at 1:07

jpp

107k2121 gold badges8989 silver badges134134 bronze badges

answered Feb 19 '18 at 0:57

viraptorviraptor

25.3k77 gold badges8282 silver badges155155 bronze badges

answered Feb 19 '18 at 0:57

viraptorviraptor

25.3k77 gold badges8282 silver badges155155 bronze badges

1

This is one way, but please do not get attached to one-liners for the sake of them being one-liners. Often they are not the best method, either in terms of readability or performance.

from itertools import accumulate

S = 25
l = [10, 20, 30]

res = [i if j <= S else max(0, S-k) 
 for i, j, k in zip(l, accumulate(l), accumulate([0]+l))]

# [10, 15, 0]

share|improve this answer

edited Feb 19 '18 at 1:04

answered Feb 19 '18 at 0:50

jppjpp

107k2121 gold badges8989 silver badges134134 bronze badges

add a comment | 

1

This is one way, but please do not get attached to one-liners for the sake of them being one-liners. Often they are not the best method, either in terms of readability or performance.

from itertools import accumulate

S = 25
l = [10, 20, 30]

res = [i if j <= S else max(0, S-k) 
 for i, j, k in zip(l, accumulate(l), accumulate([0]+l))]

# [10, 15, 0]

share|improve this answer

edited Feb 19 '18 at 1:04

answered Feb 19 '18 at 0:50

jppjpp

107k2121 gold badges8989 silver badges134134 bronze badges

add a comment | 

This is one way, but please do not get attached to one-liners for the sake of them being one-liners. Often they are not the best method, either in terms of readability or performance.

from itertools import accumulate

S = 25
l = [10, 20, 30]

res = [i if j <= S else max(0, S-k) 
 for i, j, k in zip(l, accumulate(l), accumulate([0]+l))]

# [10, 15, 0]

share|improve this answer

edited Feb 19 '18 at 1:04

answered Feb 19 '18 at 0:50

jppjpp

107k2121 gold badges8989 silver badges134134 bronze badges

from itertools import accumulate

S = 25
l = [10, 20, 30]

res = [i if j <= S else max(0, S-k) 
 for i, j, k in zip(l, accumulate(l), accumulate([0]+l))]

# [10, 15, 0]

share|improve this answer

edited Feb 19 '18 at 1:04

answered Feb 19 '18 at 0:50

jppjpp

107k2121 gold badges8989 silver badges134134 bronze badges

answered Feb 19 '18 at 0:50

jppjpp

107k2121 gold badges8989 silver badges134134 bronze badges

answered Feb 19 '18 at 0:50

jppjpp

107k2121 gold badges8989 silver badges134134 bronze badges

0

numpy

Since OP specifically asked for numpy, let's assume this is about large arrays. I think distribute in the OP subject was a key word, because this is very similar to conversion between PDF and CDF (https://en.wikipedia.org/wiki/Cumulative_distribution_function) and the inverse:

a = numpy.array([10, 20, 30])
c = a.cumsum() # [10, 30, 60]
b = c.clip(0, 25) # [20, 25, 25]
numpy.ediff1d(b, to_begin=b[0]) # [10, 15, 0]

share|improve this answer

answered Mar 28 at 7:32

Dima TisnekDima Tisnek

7,43322 gold badges3838 silver badges8787 bronze badges

add a comment | 

0

numpy

Since OP specifically asked for numpy, let's assume this is about large arrays. I think distribute in the OP subject was a key word, because this is very similar to conversion between PDF and CDF (https://en.wikipedia.org/wiki/Cumulative_distribution_function) and the inverse:

a = numpy.array([10, 20, 30])
c = a.cumsum() # [10, 30, 60]
b = c.clip(0, 25) # [20, 25, 25]
numpy.ediff1d(b, to_begin=b[0]) # [10, 15, 0]

share|improve this answer

answered Mar 28 at 7:32

Dima TisnekDima Tisnek

7,43322 gold badges3838 silver badges8787 bronze badges

add a comment | 

numpy

Since OP specifically asked for numpy, let's assume this is about large arrays. I think distribute in the OP subject was a key word, because this is very similar to conversion between PDF and CDF (https://en.wikipedia.org/wiki/Cumulative_distribution_function) and the inverse:

a = numpy.array([10, 20, 30])
c = a.cumsum() # [10, 30, 60]
b = c.clip(0, 25) # [20, 25, 25]
numpy.ediff1d(b, to_begin=b[0]) # [10, 15, 0]

share|improve this answer

answered Mar 28 at 7:32

Dima TisnekDima Tisnek

7,43322 gold badges3838 silver badges8787 bronze badges

a = numpy.array([10, 20, 30])
c = a.cumsum() # [10, 30, 60]
b = c.clip(0, 25) # [20, 25, 25]
numpy.ediff1d(b, to_begin=b[0]) # [10, 15, 0]

share|improve this answer

answered Mar 28 at 7:32

Dima TisnekDima Tisnek

7,43322 gold badges3838 silver badges8787 bronze badges

answered Mar 28 at 7:32

Dima TisnekDima Tisnek

7,43322 gold badges3838 silver badges8787 bronze badges

answered Mar 28 at 7:32

Dima TisnekDima Tisnek

7,43322 gold badges3838 silver badges8787 bronze badges