Creating a numpy array from a method using numpy array

Question

I have a 2D numpy-array as input for a basic sigmoid-classifier. I would like the classifier to return an array with the probabilities.

import numpy as np


def sigmoid(x):
    sigm = 1 / (1 + np.exp(-x))
    return sigm


def p(D, w, b):
    prob=sigmoid(np.dot(D[:][7],w)+b)
    return prob

How can I change p() so that it returns a 1D numpy array with the probabilities listed in order of the input data ?

Atm "prob" is an array of length 14, however the input array "D" is over 400 in size, so there is an error somewhere in the logic.

b is the bias of the function (int); w can be a numpy array or an int; D is a Matrix (2D array), however for now only the data in column 7 is important for the function — Valentin Metz
– Valentin Metz, Commented Mar 27, 2019 at 22:03
I understand this, but are the dimensions of D 400x14 for example? In this case, you'd be multiplying a single vector of length 14. To get the column, you'd have to do D[:,7] . — Ardweaden
– Ardweaden, Commented Mar 27, 2019 at 22:06
You are indeed correct and this just solved it. Thank you. If you write it as an answer I will mark it correct, so it may help others. — Valentin Metz
– Valentin Metz, Commented Mar 27, 2019 at 22:11

Ardweaden · Accepted Answer · 2019-03-27 22:34:21Z

1

EDIT: The issue is the incorrect slicing of the array. One has to use D[:,7] instead of D[:][7] to extract a column.

Perhaps like this:

import numpy as np


def sigmoid(x):
    sigm = 1 / (1 + np.exp(-x))
    return sigm


def p(D, w, b):
    prob=sigmoid(np.dot(D[:][7],w)+b)
    return np.ravel(prob)

edited Mar 27, 2019 at 22:34

answered Mar 27, 2019 at 21:38

Ardweaden

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2 Comments

Valentin Metz Over a year ago

prob already is an array. np.ravel() does not change anything. I will clarify the question.

hpaulj Over a year ago

That [:] is superfluous.

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