Reputation: 233
I am given a 1D array of numbers.
I need to go through the array adding each consecutive element to form a sum. Once this sum reaches a certain value, it forms the first element of a new array. The sum is then reset and the process repeats, thus iterating over the whole array.
For example if given: [1, 3, 4, 5, 2, 5, 3] and requiring the minimum sum to be 5, the new array would be: [8, 5, 7]
Explicity: [1 + 3 + 4, 5, 2 + 5]
I then also need to keep a record of the way the elements were combined for that particular array: I need to be to take a different array of the same length and combine the elements in the same way as above.
e.g. give the array [1, 2, 1, 1, 3, 2, 1] I require the output [4, 1, 5]
Explicity: [1 + 2 + 1, 1, 3 + 2]
I have accomplished this with i loops and increment counters, but it is very ugly. The array named "record" contains the number of old elements summed to make each element of the new array i.e. [3, 1, 2]
import numpy as np
def bin(array, min_sum):
num_points = len(array)
# Create empty output.
output = list()
record = list()
i = 0
while i < num_points:
sum = 0
j = 0
while sum < min_sum:
# Break out if it reaches end of data whilst in loop.
if i+j == num_points:
break
sum += array[i+j]
j += 1
output.append(sum)
record.append(j)
i += j
# The final data point does not reach the min sum.
del output[-1]
return output
if __name__ == "__main__":
array = [1, 3, 4, 5, 2, 5, 3]
print bin(array, 5)
Upvotes: 1
Views: 60
Reputation: 591
You can use short solutions I found out after a long struggle with flattening arrays.
For getting bounded sums use:
f = lambda a,x,j,l: 0 if j>=l else [a[i] for i in range(j,l) if sum(a[j:i])<x]
This outputs:
>>> f = lambda a,x,j,l: 0 if j>=l else [a[i] for i in range(j,l) if sum(a[j:i])< x]
>>> a= [1, 3, 4, 5, 2, 5, 3]
>>> f(a,5,0,7)
[1, 3, 4]
>>> sum(f(a,5,0,7))
8
>>> sum(f(a,5,3,7))
5
>>> sum(f(a,5,4,7))
7
>>>
To get your records use the function:
>>> y = lambda a,x,f,j,l: [] if j>=l else list(np.append(j,np.array(y(a,x,f,j+len(f(a,x,j,l)),l))))
From here, you can get both array of records and sums:
>>> listt=y(a,5,f,0,len(a))
>>> listt
[0.0, 3.0, 4.0, 6.0]
>>> [sum(f(a,5,int(listt[u]),len(a))) for u in range(0,len(listt)-1)]
[8, 5, 7]
>>>
Now, the bit of magic you can even use it as an index-conditional boundary for the second vector:
>>> b=[1, 2, 1, 1, 3, 2, 1]
>>> [sum(f(b,5,int(listt[u]),int(listt[u+1]))) for u in range(0,len(listt)-1)]
[4, 1, 5]
>>>
Upvotes: 0
Reputation: 14695
Here is a straightforward solution. which
computes a list of boolean values where the value is true when accumulated element equals or exceeds the target value and calc
computes an accumulation using this list.
def which(l, s):
w, a = [], 0
for e in l:
a += e
c = (a >= s)
w.append(c)
if c:
a = 0
return w
def calc(l, w):
a = 0
for (e, c) in zip(l, w):
a += e
if c:
yield a
a = 0
here is an interactive demonstration
>>> l1 = [1, 3, 4, 5, 2, 5, 3]
>>> w = which(l1, 5)
>>> w
[False, False, True, True, False, True, False]
>>> list(calc(l1, w))
[8, 5, 7]
>>> l2 = [1, 2, 1, 1, 3, 2, 1]
>>> list(calc(l2, w))
[4, 1, 5]
Upvotes: 1
Reputation: 477230
I would advice you to simply walk through the list. Add it to an accumulator like the_sum
(do not use sum
, since it is a builtin), and in case the_sum
reaches a number higher than the min_sum
, you add it, and reset the_sum
to zero. Like:
def bin(array, min_sum):
result = []
the_sum = 0
for elem in array:
the_sum += elem
if the_sum >= min_sum:
result.append(the_sum)
the_sum = 0
return result
The lines where the accumulator is involved, are put in boldface.
I leave combining the other array the same way as an exercise, but as a hint: use an additional accumulator and zip
to iterate over both arrays concurrently.
Upvotes: 1