Broadcasting in NumPy denotes the ability to guess a common, compatible shape between two arrays. For instance, when adding a vector (one-dimensional array) and a scalar (zero-dimensional array), the scalar is extended to a vector, in order to allow for the addition. The general mechanism is called broadcasting. We will first review that mechanism from a mathematical point of view, and then proceed to give the precise rules for broadcasting in NumPy. The mathematical view might give a mathematically trained reader easier access to broadcasting, while other readers might want to skip the mathematical details and directly continue reading Section 5.5.2: Broadcasting arrays.
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