apply the ufunc outer function in numpy

**1. Understanding the Core Concept**

More formally, if `A` has shape `(m, n, ...)` and `B` has shape `(p, q, ...)`, then the output array will have shape `(m, n, ..., p, q, ...)`. Each element of the output array, say at index `(i, j, ..., k, l, ...)` will be the result of applying the ufunc to `A[i, j, ...]` and `B[k, l, ...]`.

**2. Syntax and Parameters**

* **`A`:** The first input array.
* **`B`:** The second input array.
* **`out` (optional):** A location into which the result is stored. If provided, it must have a shape that matches the expected output shape. If not provided or is `None`, a freshly-allocated array is returned. This can be useful for in-place modification and memory optimization.

**3. Fundamental Examples with Numerical Arrays**

Let's start with some basic examples using numerical arrays a ...

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