numpy.arccosh()
  • References/Python/NumPy/Routines/Mathematical functions

numpy.arccosh(x[, out]) = Inverse hyperbolic cosine, element-wise.

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numpy.expm1()
  • References/Python/NumPy/Routines/Mathematical functions

numpy.expm1(x[, out]) = Calculate exp(x) - 1 for all elements in the array.

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numpy.i0()
  • References/Python/NumPy/Routines/Mathematical functions

numpy.i0(x)

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numpy.diff()
  • References/Python/NumPy/Routines/Mathematical functions

numpy.diff(a, n=1, axis=-1)

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numpy.round_()
  • References/Python/NumPy/Routines/Mathematical functions

numpy.round_(a, decimals=0, out=None)

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numpy.sinh()
  • References/Python/NumPy/Routines/Mathematical functions

numpy.sinh(x[, out]) = Hyperbolic sine, element-wise. Equivalent to 1/2 * (np.exp(x) - np.exp(-x)) or -1j

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numpy.nansum()
  • References/Python/NumPy/Routines/Mathematical functions

numpy.nansum(a, axis=None, dtype=None, out=None, keepdims=0)

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numpy.remainder()
  • References/Python/NumPy/Routines/Mathematical functions

numpy.remainder(x1, x2[, out]) = Return element-wise remainder of division. Computes the remainder complementary to the

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numpy.gradient()
  • References/Python/NumPy/Routines/Mathematical functions

numpy.gradient(f, *varargs, **kwargs)

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numpy.minimum()
  • References/Python/NumPy/Routines/Mathematical functions

numpy.minimum(x1, x2[, out]) = Element-wise minimum of array elements. Compare two arrays and returns a new array containing

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