在python 2.7中查找矩阵中每一列等于或大于1时的行号

Question

I am trying to write some code that will tell me the row number when each column in a "matrix" is equal to or greater than one. I have to use python 2.7 for this code. Previously I solved it using numpy (see explanation below) but the software where I have to implement it does not support numpy or python 3.

I have a list like the following:

data = [0.9338022866253757, 0.9438022866253757, 0.9538022866253757, 0.9638022866253757, 0.9738022866253757, 0.9838022866253757,
0.9526111539604993, 0.9626111539604993, 0.9726111539604994, 0.9826111539604994, 0.9926111539604994, 1.0026111539604994,
0.9638333594112685, 0.9738333594112685, 0.9838333594112684, 0.9938333594112684, 1.0038333594112685, 1.0138333594112683,
0.9718956496941793, 0.9818956496941793, 0.9918956496941793, 1.0018956496941793, 1.0118956496941793, 1.0218956496941793,
0.9782070486192962, 0.9882070486192962, 0.9982070486192962, 1.0082070486192962, 1.0182070486192962, 1.0282070486192962]

This list should be divided into something resembling a matrix, I do this with the following function and split it into lists of length 6 within another list like this:

def split(arr, size):
    arrs = []
    while len(arr) > size:
        pice = arr[:size]
        arrs.append(pice)
        arr = arr[size:]
    arrs.append(arr)
    return arrs

data_split = split(data,6)
print(data_split)

Output:

data_split = [[0.9338022866253757, 0.9438022866253757, 0.9538022866253757, 0.9638022866253757, 0.9738022866253757, 0.9838022866253757],
[0.9526111539604993, 0.9626111539604993, 0.9726111539604994, 0.9826111539604994, 0.9926111539604994, 1.0026111539604994],
[0.9638333594112685, 0.9738333594112685, 0.9838333594112684, 0.9938333594112684, 1.0038333594112685, 1.0138333594112683],
[0.9718956496941793, 0.9818956496941793, 0.9918956496941793, 1.0018956496941793, 1.0118956496941793, 1.0218956496941793],
[0.9782070486192962, 0.9882070486192962, 0.9982070486192962, 1.0082070486192962, 1.0182070486192962, 1.0282070486192962]]

This is where I am stuck, the data_split is obviously not a real matrix and I cant figure out how to do the operations I want such that I can find the the first entry in each column where the number reaches 1 or greater than 1.

The result of this should be:

[0 0 0 3 2 1]

Explanation of the output:

Column 0, 1 and 2 never reaches the number 1 so the result is 0. Column 3 reaches 1 at row number 3, column 4 reaches 1 at the row number 2 and last column reaches 1 at row number 1.

In Python 3

Previously I used numpy to solve this problem but the program which I'm writing the code for does not support it. The working Python 3 code with numpy is as follows:

import numpy as np
data = np.array([0.93380229, 0.94380229, 0.95380229, 0.96380229, 0.97380229, 0.98380229,
 0.95261115, 0.96261115, 0.97261115, 0.98261115, 0.99261115, 1.00261115,
 0.96383336, 0.97383336, 0.98383336, 0.99383336, 1.00383336, 1.01383336,
 0.97189565, 0.98189565, 0.99189565, 1.00189565, 1.01189565, 1.02189565,
 0.97820705, 0.98820705, 0.99820705, 1.00820705, 1.01820705, 1.02820705])

# data is rewritten into matrix vector form using split and stack
data_split = np.split(data,5)
data_stack = np.stack(data_split)
print(data_stack)

Output:

data_stack = [[0.93380229 0.94380229 0.95380229 0.96380229 0.97380229 0.98380229]
 [0.95261115 0.96261115 0.97261115 0.98261115 0.99261115 1.00261115]
 [0.96383336 0.97383336 0.98383336 0.99383336 1.00383336 1.01383336]
 [0.97189565 0.98189565 0.99189565 1.00189565 1.01189565 1.02189565]
 [0.97820705 0.98820705 0.99820705 1.00820705 1.01820705 1.02820705]]

Then I turn the matrix into a true false matrix:

over1 = data_stack >= 1

Output:

over1 = [[False False False False False False]
 [False False False False False  True]
 [False False False False  True  True]
 [False False False  True  True  True]
 [False False False  True  True  True]]

Finally I find first occurence of true in each column:

# row number where 1 was reached
index = np.argmax(over1, axis=0)
print(index)

Output:

index = [0 0 0 3 2 1]

Answer 1

You can try this:

data = [0.9338022866253757, 0.9438022866253757, 0.9538022866253757, 0.9638022866253757, 0.9738022866253757, 0.9838022866253757,
0.9526111539604993, 0.9626111539604993, 0.9726111539604994, 0.9826111539604994, 0.9926111539604994, 1.0026111539604994,
0.9638333594112685, 0.9738333594112685, 0.9838333594112684, 0.9938333594112684, 1.0038333594112685, 1.0138333594112683,
0.9718956496941793, 0.9818956496941793, 0.9918956496941793, 1.0018956496941793, 1.0118956496941793, 1.0218956496941793,
0.9782070486192962, 0.9882070486192962, 0.9982070486192962, 1.0082070486192962, 1.0182070486192962, 1.0282070486192962]

cols = 6
lst = [[]]*cols

for i, e in enumerate(data):
  n = i%6
  lst[n] = lst[n] + [e]

def get_first_above_one(l):
  for i,e in enumerate(l):
    if e > 1:
      return i
  return 0

[get_first_above_one(l) for l in lst]
#Out[61]: [0, 0, 0, 3, 2, 1]