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finding the max of a column in an array

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python

def maxvalues():        
for n in range(1,15):
    dummy=[]
    for k in range(len(MotionsAndMoorings)):
        dummy.append(MotionsAndMoorings[k][n])
    max(dummy)
    L = [x + [max(dummy)]] ## to be corrected (adding columns with value max(dummy))
## suggest code to add new row to L and for next function call, it should save values here.

i have an array of size (k x n) and i need to pick the max values of the first column in that array. Please suggest if there is a simpler way other than what i tried? and my main aim is to append it to L in columns rather than rows. If i just append, it is adding values at the end. I would like to this to be done in columns for row 0 in L, because i'll call this function again and add a new row to L and do the same. Please suggest.

like image 373
KGV Avatar asked Mar 13 '16 05:03

KGV


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2 Answers

General suggestions for your code

First of all it's not very handy to access globals in a function. It works but it's not considered good style. So instead of using:

def maxvalues():
    do_something_with(MotionsAndMoorings)

you should do it with an argument:

def maxvalues(array):
    do_something_with(array)

MotionsAndMoorings = something
maxvalues(MotionsAndMoorings) # pass it to the function.

The next strange this is you seem to exlude the first row of your array:

for n in range(1,15):

I think that's unintended. The first element of a list has the index 0 and not 1. So I guess you wanted to write:

for n in range(0,15):

or even better for arbitary lengths:

for n in range(len(array[0])): # I chose the first row length here not the number of columns

Alternatives to your iterations

But this would not be very intuitive because the max function already implements some very nice keyword (the key) so you don't need to iterate over the whole array:

import operator
column = 2
max(array, key=operator.itemgetter(column))[column]

this will return the row where the i-th element is maximal (you just define your wanted column as this element). But the maximum will return the whole row so you need to extract just the i-th element.

So to get a list of all your maximums for each column you could do:

[max(array, key=operator.itemgetter(column))[column] for column in range(len(array[0]))]

For your L I'm not sure what this is but for that you should probably also pass it as argument to the function:

def maxvalues(array, L): # another argument here

but since I don't know what x and L are supposed to be I'll not go further into that. But it looks like you want to make the columns of MotionsAndMoorings to rows and the rows to columns. If so you can just do it with:

dummy = [[MotionsAndMoorings[j][i] for j in range(len(MotionsAndMoorings))] for i in range(len(MotionsAndMoorings[0]))]

that's a list comprehension that converts a list like:

[[1, 2, 3], [4, 5, 6], [0, 2, 10], [0, 2, 10]]

to an "inverted" column/row list:

[[1, 4, 0, 0], [2, 5, 2, 2], [3, 6, 10, 10]]

Alternative packages

But like roadrunner66 already said sometimes it's easiest to use a library like numpy or pandas that already has very advanced and fast functions that do exactly what you want and are very easy to use.

For example you convert a python list to a numpy array simple by:

import numpy as np
Motions_numpy = np.array(MotionsAndMoorings)

you get the maximum of the columns by using:

maximums_columns = np.max(Motions_numpy, axis=0)

you don't even need to convert it to a np.array to use np.max or transpose it (make rows to columns and the colums to rows):

transposed = np.transpose(MotionsAndMoorings)

I hope this answer is not to unstructured. Some parts are suggestions to your function and some are alternatives. You should pick the parts that you need and if you have any trouble with it, just leave a comment or ask another question. :-)

like image 178
MSeifert Avatar answered Sep 20 '22 10:09

MSeifert


An example with a random input array, showing that you can take the max in either axis easily with one command.

import numpy as np

aa= np.random.random([4,3]) 
print aa
print
print np.max(aa,axis=0)
print
print np.max(aa,axis=1)

Output:

[[ 0.51972266  0.35930957  0.60381998]
 [ 0.34577217  0.27908173  0.52146593]
 [ 0.12101346  0.52268843  0.41704152]
 [ 0.24181773  0.40747905  0.14980534]]

[ 0.51972266  0.52268843  0.60381998]

[ 0.60381998  0.52146593  0.52268843  0.40747905]
like image 40
roadrunner66 Avatar answered Sep 20 '22 10:09

roadrunner66