Change matrix negative values to absolute values

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How could I change the negative values into their positive values. I have to write a procedure so no return value or print

I have a matrix:

  [-5,-8,-8,-7,-8],
  [-4,-2,-4,-8,-9],
  [-4,-2,-5,-8,-7]

I want the matrix have positive numbers. So

  [5,8,8,7,8],
  [4,2,4,8,9],
  [4,2,5,8,7]

I have this:

def procedure(matrix):
   map(abs, matrix)

But it does not work at all.

Edit:

Now no return or print

x = [
    [-5, -8, -8, -7, -8],
    [-4, -2, -4, -8, -9],
    [-4, -2, -5, -8, -7],
]  # create matrice (list of lists)


def get_abs(x):
    for line_number in range(len(x)):  # go through lines
        for element_number in range(len(x[line_number])):  # go  through line 
            # get abs
            x[line_number][element_number] = abs(x[line_number][element_number])


get_abs(x)  # get abs

print(x)  # test what we have got

How do I convert all negative elements in a matrix to positive , It might be the case that if the values in the matrix were restricted to a certain range that it would always be possible, at least for certain matrix� When I run a simulation in Matlab, in some iterations of the filter I get a Kalman gain matrix (K) with negative values and/or absolute values greater than 1. In some books I have read that the

You have the right idea, but map() will operate on each row of the matrix as the matrix is a list of lists. Instead you need some kind of loop to apply the abs() function to each element in each row. I would suggest a list-comprehension which has the additional advantage of returning a list rather than a map object.

def procedure(matrix):
    return [[abs(x) for x in row] for row in matrix]

Test:

>>> m = [
...   [-5,-8,-8,-7,-8],
...   [-4,-2,-4,-8,-9],
...   [-4,-2,-5,-8,-7]
... ]
>>> procedure(m)
[
  [5, 8, 8, 7, 8],
  [4, 2, 4, 8, 9],
  [4, 2, 5, 8, 7]
]

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You could also use numpy.array & numpy.absolute

a = [[-5, -8, -8, -7, -8],
     [-4, -2, -4, -8, -9],
     [-4, -2, -5, -8, -7]]

import numpy as np

def procedure(matrix):
    return np.absolute(np.array(matrix))


procedure(a)

Urban and Regional Data Management: UDMS 2007 Annual, Band extractions are called as “pixel extraction”, equal matrix is called as method is: where Pixelij(change): Brightness value of the pixel in the ith row, Absolute value must be used in the formula, because pixel differences could be The negative value must be transformed to the positive value in order to be compared. The absolute value of 10.5 is 10.5 and (–15.5) is 15.5. Subtract the smaller number from the larger and you get 15. 5 – 10. 5 = 5.0. The larger absolute value in the equation is 15.5 and is a negative number so the final result is a negative number. Therefore, the result of 10.5 + (–15.5) = –5.0.

You can use map if you really want to, but you have to cast to a list because it uses lazy evaluation. You must also deal with the inner lists (the rows). The result is not easy to read:

list(map(lambda row: list(map(abs, row)), matrix))

This is cute, but I think most Python programmers would use list comprehensions (or NumPy).

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How to get absolute value of numbers in Python? � Kodify, An absolute value is a number's non-negative value. Get absolute values with Python's abs() function Get absolute values from a Python list or array 36] # Replace the original numbers with the absolute values values� Joseph has a worksheet that contains a list of values. Some of those values are above zero and others are below. He can use the SUM function to calculate a sum of the values, but he really wants to calculate a sum of the absolute value of each item in the list. So, the sum of the three values -33, 14, -5 would be 52 instead of -24.

Computer Processing of Remotely-Sensed Images: An Introduction, The first difference (row 2) indicates the rate of change of the values of f shown in of change of greyscale value is zero, positive when 'going up' a slope and negative when going down. rapidly) are characterised by first differences that are large in absolute value. Table 7.2 (a) Weight matrix for the Laplacian operator. The variables are quarterly data, with some negative values. For example, quarterly GDP values have 234566.56, 345456.23, 678994.67, -345674.21, 879076.00, -12345.00. I would like to use logarithm transformation on them. But how can I deal with the negative values when in fact the negative values are not in single digit? Please advice. Mahmud

Comments
  • without abs(): [[x * -1 if x < 0 else x for x in y] for y in lst]
  • What do you mean by "a procedure"? Do you mean that the function should mutate its argument? (This is bad practise btw, but if that is what your assignment requires, you have to do it.)
  • The OP said "no return value"
  • @MartinBonnersupportsMonica thanks, changed the answer to "no return no print" solution
  • The OP said "no return value"
  • The OP said "no return value"
  • The OP said "no return value"
  • @MartinBonnersupportsMonica This isn't a function, the OP can do whatever they like with it, including wrapping it in a function that mutates some global. (I think that's a rotten idea, so I didn't do it.)