Replace values in a 2D array with different random numbers

Question

I have a 2D array (image) in which I want to replace array values greater than some threshold with a random number in some range. My attempt was to use numpy.random.uniform, as so

Z[Z > some_value] = uniform(lower_limit,upper_limit)

However I've found that this replaces all values above the threshold with the same random value. I would like to replace all array values above the threshold with a different random value each.

I think this would require some interation over the entire array for which I would need to generate a random value if the condition is met. How would I do this?

Sam Myers · Accepted Answer · 2016-03-07 23:26:40Z

1

You are correct that iteration would be the correct way to go. Let's do a list comprehension.

[uniform(lower_limit, upper_limit) if i > some_value else i
 for i in Z]

Let's step through it. Take an individual value. If it is greater than the threshold, use a randomly generated one, otherwise the original value.

uniform(lower_limit, upper_limit) if i > some_value else i

Repeat this for every element in Z

for i in Z

For a 2D array, nest multiple comprehensions. Imagine that the above solution was to hit everything in one row and then repeat it for every row.

[[uniform(lower_limit, upper_limit) if i > some_value else i
  for i in row]
  for row in Z]

edited Mar 7, 2016 at 23:26

answered Mar 7, 2016 at 21:30

Sam Myers

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5 Comments

maelstromscientist Over a year ago

After implementing this I am getting the error ValueError: The truth value of an array with more than one element is ambiguous. I'm guessing this is because it is a 2d array? Is there a way to iterate using the above list comprehension and preserve the shape of the array (2d) without having to convert it to a 1d array?

Sam Myers Over a year ago

@maelstromscientist My apologies, updated with new example. Iterating (using a list comprehension of course) over each 1D array in your 2D array should work for you.

maelstromscientist Over a year ago

Nevermind, I had a silly mistake with variable names and once that was fixed it worked great. Thanks!

Sam Myers Over a year ago

Huh. No idea. It may be time to split the offending piece of code out. def small_or_random(num): ... then simplify the comprehension to [[small_or_random(i) for i in row] for row in Z]. That should be much easier to debug / reason about.

Christian K. Over a year ago

@maelstromscientist You should start to get used to the mechanisms provided by numpy to work with whole arrays at once instead of doing operations element-wise by looping or using list-comprehensions. It is advantageous both in terms of speed and readability. See my answer.

Christian K. · Accepted Answer · 2016-03-07 23:41:52Z

0

Check the third argument to uniform. Using size=N will yield an array of random values with length N. Thus

z[z>some_value] = np.random.uniform(lower, upper, len(z>some_value))

will do what you want.

answered Mar 7, 2016 at 23:41

Christian K.

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