numpy.sinh()

numpy.sinh(x[, out]) =

Hyperbolic sine, element-wise.

Equivalent to 1/2 * (np.exp(x) - np.exp(-x)) or -1j * np.sin(1j*x).

Parameters:

Parameters:	x : array_like Input array. out : ndarray, optional Output array of same shape as `x`.
Returns:	y : ndarray The corresponding hyperbolic sine values.
Raises:	ValueError: invalid return array shape if `out` is provided and `out.shape` != `x.shape` (See Examples)

x : array_like

Input array.

out : ndarray, optional

Output array of same shape as x.

Returns:

y : ndarray

The corresponding hyperbolic sine values.

Raises:

ValueError: invalid return array shape

if out is provided and out.shape != x.shape (See Examples)

Notes

If out is provided, the function writes the result into it, and returns a reference to out. (See Examples)

References

M. Abramowitz and I. A. Stegun, Handbook of Mathematical Functions. New York, NY: Dover, 1972, pg. 83.

Examples

>>> np.sinh(0)
0.0
>>> np.sinh(np.pi*1j/2)
1j
>>> np.sinh(np.pi*1j) # (exact value is 0)
1.2246063538223773e-016j
>>> # Discrepancy due to vagaries of floating point arithmetic.

>>> # Example of providing the optional output parameter
>>> out2 = np.sinh([0.1], out1)
>>> out2 is out1
True

>>> # Example of ValueError due to provision of shape mis-matched `out`
>>> np.sinh(np.zeros((3,3)),np.zeros((2,2)))
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ValueError: invalid return array shape

Links:

https://docs.scipy.org/doc/numpy-1.11.0/reference/generated/numpy.sinh.html

doc_NumPy

2025-01-10 15:47:30

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