Tips of Numpy

Given two identical size of ndarray, how to shuffle the two arrays and keep elements of the first array corresponding to the elemenets of the second array?

Numpy provides the ndarray a special ability, called index array. You could put an array in the square bracket, [], to get the permutation.

For example

a = np.arange(10) # -> array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
b = a[[3, 2, 1, 4, 5, 6, 9, 8, 7, 0]] # -> array([3, 2, 1, 4, 5, 6, 9, 8, 7, 0])
c = a[[3, 2, 1, 0]] # -> array([3, 2, 1, 0])

So you could use numpy.random.permutation function to generate the index array and use it to shuffle multiple arrays.

For example

def randomize(a, b):
    # Generate the permutation index array.
    permutation = np.random.permutation(a.shape[0])
    # Shuffle the arrays by giving the permutation in the square brackets.
    shuffled_a = dataset[permutation]
    shuffled_b = labels[permutation]
    return shuffled_a, shuffled_b

---

Boolean statments are commonly used in combination with the and operator and the or operator.

For example

# Creating an image.
img1 = np.zeros([20, 20]) + 3
img1[4:-4, 4:-4] = 6
img1[7:-7, 7:-7] = 9

# Ley's filter out all values larger than 2 and less than 6.
index1 = img1 > 2
index2 = img1 < 6
compound_index = index1 & index2

img2 = np.copy(img1)
img2[compound_index] = 0

And let’s see the figure.