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  1. numpy.multiply — NumPy v2.2 Manual

    numpy.multiply# numpy. multiply (x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True [, signature]) = <ufunc 'multiply'> # Multiply arguments …

  2. Broadcasting — NumPy v2.2 Manual

    For example, if you have a 256x256x3 array of RGB values, and you want to scale each color in the image by a different value, you can multiply the image by a one-dimensional array with 3 …

  3. numpy.matmul — NumPy v2.2 Manual

    The matmul function implements the semantics of the @ operator introduced in Python 3.5 following PEP 465. It uses an optimized BLAS library when possible (see numpy.linalg). …

  4. numpy.dot — NumPy v2.2 Manual

    If either a or b is 0-D (scalar), it is equivalent to multiply and using numpy.multiply(a, b) or a * b is preferred. If a is an N-D array and b is a 1-D array, it is a sum product over the last axis of a …

  5. Array Broadcasting in Numpy — NumPy v1.20 Manual

    Jan 31, 2021 · A two dimensional array multiplied by a one dimensional array results in broadcasting if number of 1-d array elements matches the number of 2-d array columns.

  6. numpy.prod — NumPy v2.2 Manual

    >>> np. prod (a, axis = 1) array([ 2., 12.]) >>> np. prod (a, axis = 0) array([3., 8.]) Or select specific elements to include: >>> np . prod ([ 1. , np . nan , 3. ], where = [ True , False , True ]) …

  7. numpy.cross — NumPy v2.2 Manual

    Return the cross product of two (arrays of) vectors. The cross product of a and b in \(R^3\) is a vector perpendicular to both a and b. If a and b are arrays of vectors, the vectors are defined …

  8. numpy.linalg.multi_dot — NumPy v2.2 Manual

    Compute the dot product of two or more arrays in a single function call, while automatically selecting the fastest evaluation order. multi_dot chains numpy.dot and uses optimal …

  9. numpy.outer — NumPy v2.2 Manual

    np.multiply.outer(a.ravel(), b.ravel()) is the equivalent. linalg.outer An Array API compatible variation of np.outer , which accepts 1-dimensional inputs only.

  10. Array creation — NumPy v2.2 Manual

    There are 6 general mechanisms for creating arrays: Conversion from other Python structures (i.e. lists and tuples) Intrinsic NumPy array creation functions (e.g. arange, ones, zeros, etc.) …

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