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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You're reading from Scientific Computing with Python - Second Edition
Claus Führer is a professor of scientific computations at Lund University, Sweden. He has an extensive teaching record that includes intensive programming courses in numerical analysis and engineering mathematics across various levels in many different countries and teaching environments. Claus also develops numerical software in research collaboration with industry and received Lund University's Faculty of Engineering Best Teacher Award in 2016.
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Claus Führer is a professor of scientific computations at Lund University, Sweden. He has an extensive teaching record that includes intensive programming courses in numerical analysis and engineering mathematics across various levels in many different countries and teaching environments. Claus also develops numerical software in research collaboration with industry and received Lund University's Faculty of Engineering Best Teacher Award in 2016.
Read more about Claus Führer