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importnumpyasnpa=np.array([1,2,3])b=np.array([4,5,6])res=np.dstack((a,b))print(res)

Output

[[[1 4]  [2 5]  [3 6]]]

Arrays a and b are stacked along the third axis, creating a 3D array with shape (1, 3, 2).

Syntax

numpy.dstack(tup)

Parameters:

tup (sequence of array_like): Arrays to be stacked depth-wise (axis=2); must have the same shape except along the third axis.

Returns:This method returns a stacked array with one more dimension (axis=2) than the input arrays.

Examples

Example 1: Depth-wise stacking of 2D arrays

importnumpyasnpa=np.array([[1,2],[3,4]])b=np.array([[5,6],[7,8]])res=np.dstack((a,b))print(res)

Output

[[[1 5]  [2 6]] [[3 7]  [4 8]]]

Each corresponding element from arrays a and b is stacked into a new depth layer.

Example 2: Stacking arrays of different shapes (raises an error)

importnumpyasnpa=np.array([[1,2,3]])b=np.array([[4,5]])res=np.dstack((a,b))

Output

ValueError: all the input array dimensions except for the concatenation axis must match exactly, but along dimension 1, the array at index 0 has size 3 and the array at index 1 has size 2...

Arrays must match in shape except along the stacking axis (axis=2).

Example 3: Depth-wise stacking with negative numbers

importnumpyasnpa=np.array([-1,-2,-3])b=np.array([4,5,6])res=np.dstack((a,b))print(res)

Output

[[[-1  4]  [-2  5]  [-3  6]]]

Works with negative integers too. The resulting array stacks corresponding elements into a new depth dimension.

Splitting Arrays in NumPy

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Introduction

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