Pulling data from a numpy array

Question

I have a numpy ndarray that I made using numpy.loadtxt. I want to pull an entire row from it based on a condition in the third column. Something like : if array[2][i] is meeting my conditions, then get array[0][i] and array [1][i] as well. I'm new to python, and all of the numpy features, so I'm looking for the best way to do this. Ideally, I'd like to pull 2 rows at a time, but I wont always have an even number of rows, so I imagine that is a problem

import numpy as np

'''
Created on Jan 27, 2013

@author:
'''
class Volume:

    f ='/Users/Documents/workspace/findMinMax/crapc.txt'
    m = np.loadtxt(f, unpack=True, usecols=(1,2,3), ndmin = 2)


    maxZ = max(m[2])
    minZ = min(m[2])
    print("Maximum Z value: " + str(maxZ))
    print("Minimum Z value: " + str(minZ))

    zIncrement = .5
    steps = maxZ/zIncrement
    currentStep = .5
    b = []

    for i in m[2]:#here is my problem
         while currentStep < steps: 
            if m[2][i] < currentStep and m[2][i] > currentStep - zIncrement:
                b.append(m[2][i]) 
            if len(b) < 2:
                currentStep + zIncrement

                print(b)

Here is some code that I did in java that is the general idea of what I want:

while( e < a.length - 1){
for(int i = 0; i < a.length - 1; i++){
        if(a[i][2] < stepSize && a[i][2] > stepSize - 2){

            x.add(a[i][0]);
            y.add(a[i][1]);
            z.add(a[i][2]);
        }
        if(x.size()  < 1){
            stepSize += 1;
        }
    }
}

That makes sense! I'm sorry I wasn't clear. I haven't learned to think like a programmer yet. I'm a bio student that has to learn this. :/ — pioneer903
– pioneer903, Commented Feb 3, 2013 at 22:20

aseyboldt · Accepted Answer · 2013-02-03 22:16:06Z

2

First of all, you probably don't want to put your code in that class definition...

import numpy as np


def main():
    m = np.random.random((3, 4))
    mask = (m[2] > 0.5) & (m[2] < 0.8)  # put your conditions here
                                        # instead of 0.5 and 0.8 you can use
                                        # an array if you like
    m[:, mask]

if __name__ == '__main__':
    main()

mask is a boolean array, m[:, mask] is the array you want

m[2] is the third row of m. If you type m[2] + 2 you get a new array with the old values + 2. m[2] > 0.5 creates an array with boolean values. It is best to try this stuff out with ipython (www.ipython.org)

In the expression m[:, mask] the : means "take all rows", mask describes which columns should be included.

Update

Next try :-)

for i in range(0, len(m), 2):
    two_rows = m[i:i+2]

edited Feb 3, 2013 at 22:16

answered Feb 3, 2013 at 21:28

aseyboldt

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9 Comments

pioneer903 Over a year ago

I don't understand how I can go over the entire ndarray like this. Can you please elaborate?

pioneer903 Over a year ago

I think that we are misunderstanding, its my fault, I'm not good with explaining ideas

aseyboldt Over a year ago

what part did I not understand correctly? You might want to have a look at scipy.org/Tentative_NumPy_Tutorial

pioneer903 Over a year ago

I think that we are misunderstanding, its my fault, I'm not good with explaining ideas. please correct my understanding. I believe my array looks like this -1 0 0.29 1 2 2.96 2 -2 3.0 so I thought m[2] would specify the whole 3rd column and m[2][0] would be the first value in that column? Basically, I want to grab the two rows at the top. I'm only using the incrementors because I want to only grab 2 rows at once, and the distance between them matters.

aseyboldt Over a year ago

It might also help if you said what you are trying to accomplish

|

flonk · Accepted Answer · 2013-02-06 20:51:21Z

0

If you can write your condition as a simple function

def condition(value):
    # return True or False depending on value

then you could select your subarrays like this:

cond = condition(a[2])
subarray0 = a[0,cond]
subarray1 = a[1,cond]

answered Feb 6, 2013 at 20:51

flonk

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2 Comments

pioneer903 Over a year ago

can you elaborate on what the true or false does. I am not completely getting you. I'm sorry, I'm still learning.

flonk Over a year ago

I mean, it depends on what your condition is. If you're lucky, you can express the condition using standard functions, such that it can operate on the array a[2] without an elementwise loop, for example return value>0 or return (value.abs()>0.5)*(np.sin(value)<0.3) works elementwise also if value is an array without slowing the code by loops.

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