How do I compare two large 2D arrays in Python for exact equality?

Question

As stated in the title. I am trying to compare two large(21x21) grids containing elments of single dots and single dashes to see if each element at each index is the same. Using array1 == array2 produces the following error:

The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

However, I have not encountered a good explanation of the a.all/a.any syntax. What goes before the dot? What params do they take?

Edit: I have been avoiding using NumPy, but theres no way around it. NumPy is imported. Any ideas?

Portion of the code where I am creating a default grid of dots and dashes:

defaultgrid = [['.' for x in range(width)] for y in range(height)]

for x in range(1, 21, 2):
    defaultgrid[x] = [" ", " ", " ", " ", " ", " ", " ", " ", " ", " ", " ", " ", " ", " ", " ", " ", " ", " ", " ",
                      " ", " "]

for x in range(0, 21, 2):
    defaultgrid[x] = [".", " ", ".", " ", ".", " ", ".", " ", ".", " ", ".", " ", ".", " ", ".", " ", ".", " ", ".",
                      " ", "."]

Answer 1

How about comparing the strings of the arrays?

Str(arr1) == str(arr2)

Answer 2

If you're sure that you want to use Numpy then a way to solve your error The truth value of an array..... is following:

1. If you have two numpy arrays arr1 and arr2 then everywhere compare them for equality not by if arr1 == arr2: but by if np.array_equal(arr1, arr2): .

2. Alternatively if you're sure that your two arrays have same size (dimensionality) and type then you can compare them for equality also like this if np.all(arr1 == arr2): .

3. If you don't use Numpy then two nested lists can be just compared as if arr1 == arr2: .

You were saying that you used numpy only to do np.copy() . To make a deep copy of a list you can use standard copy.deepcopy() (you have to import copy ).