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I want to multiply all elements in a numpy array. If there's an array like [1, 2, 3, 4, 5], I want to get value of 1 * 2 * 3 * 4 * 5.
I tried this by making my own method, but size of array is very large, it takes very longs time to calculate because I'm using numpy it would be helpful if numpy supports this operation.
I tried to find out through numpy documents, but I failed. Is there a method which does this operation? If there is, is there a way to get values along a rank in an matrix?
371
You can use np. multiply to multiply two same-sized arrays together. This computes something called the Hadamard product. In the Hadamard product, the two inputs have the same shape, and the output contains the element-wise product of each of the input values.
Method 1: Multiply NumPy array by a scalar using the * operator. The first method to multiply the NumPy array is the use of the ' * ' operator. It will directly multiply all the elements of the NumPy array whether it is a Single Dimensional or Multi-Dimensional array.
multiply() in Python. numpy. multiply() function is used when we want to compute the multiplication of two array. It returns the product of arr1 and arr2, element-wise.
I believe what you need is, numpy.prod.
From the documentation:
Examples
By default, calculate the product of all elements:
>>> np.prod([1.,2.]) 2.0Even when the input array is two-dimensional:
>>> np.prod([[1.,2.],[3.,4.]]) 24.0But we can also specify the axis over which to multiply:
>>> np.prod([[1.,2.],[3.,4.]], axis=1) array([ 2., 12.])
So for your case, you need:
>>> np.prod([1,2,3,4,5])
120
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