Unlock the Power of Depthwise Stacking
When working with arrays, there are times when you need to combine them in a specific way. This is where the dstack() method comes in – a powerful tool that allows you to stack arrays depthwise.
Understanding the Syntax
The dstack() method takes a single argument: a tuple of arrays to be stacked. The syntax is straightforward: dstack(tup). But what’s essential to keep in mind is that the shape of all arrays in the tuple must be the same, except for the third dimension.
Why Shape Matters
When stacking arrays, the shape of each array plays a critical role. The dstack() method stacks arrays in axis 2 (depthwise), which means the third dimension of each array can be different. However, the other dimensions must be identical. If they’re not, you’ll encounter a ValueError.
Putting it into Practice
Let’s take a look at an example where we stack two arrays of different shapes depthwise. We have array1 with a shape of (2, 2, 2) and array2 with a shape of (2, 2, 1). Despite their differences, we can stack them successfully because only the third dimension of array2 is different from array1.
“`
Output:
[[[1 1]
[1 1]]
[[1]
[1]]]
“`
What Happens When Shapes Don’t Match
But what if the shapes aren’t compatible? Let’s try stacking array1 with array2 having a shape of (2, 3, 1). As expected, this will result in a ValueError because the second dimension of array2 is different from array1.
Output:
ValueError: all the input arrays must have same shape along axes (0, 1)
By understanding how dstack() works and the importance of shape compatibility, you can unlock the full potential of depthwise stacking in your array operations.