hzfan commented on a change in pull request #15388: Doc
URL: https://github.com/apache/incubator-mxnet/pull/15388#discussion_r298881285
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File path: python/mxnet/ndarray/numpy/_op.py
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@@ -720,6 +742,137 @@ def _unary_func_helper(x, fn_array, fn_scalar, out=None,
**kwargs):
else:
raise TypeError('type {} not supported'.format(str(type(x))))
+@set_module('mxnet.ndarray.numpy')
+def trunc(x, out=None, **kwargs):
+ r"""
+ trunc(x, out=None)
+
+ Return the truncated value of the input, element-wise.
+
+ The truncated value of the scalar `x` is the nearest integer `i` which
+ is closer to zero than `x` is. In short, the fractional part of the
+ signed number `x` is discarded.
+
+ Parameters
+ ----------
+ x : ndarray or scalar
+ Input data.
+ out : ndarray or None, optional
+ A location into which the result is stored.
+
+ Returns
+ -------
+ y : ndarray or scalar
+ The truncated value of each element in `x`.
+ This is a scalar if `x` is a scalar.
+
+ Notes
+ -----
+ This function differs to the original numpy.trunc in the following aspects:
+ - Do not support 'where', a parameter in numpy which indicates where
to calculate.
+ - Cannot cast type automatically. Dtype of 'out' must be same as the
expected one.
+ - Cannot broadcast automatically. Shape of 'out' must be same as the
expected one.
+ - If 'x' is plain python numeric, the result won't be stored in out.
+
+ Examples
+ --------
+ >>> a = np.array([-1.7, -1.5, -0.2, 0.2, 1.5, 1.7, 2.0])
+ >>> np.trunc(a)
+ array([-1., -1., -0., 0., 1., 1., 2.])
+ """
+ return _unary_func_helper(x, _npi.trunc, _np.trunc, out=out, **kwargs)
+
+@set_module('mxnet.ndarray.numpy')
+def logical_not(x, out=None, **kwargs):
+ r"""
+ logical_not(x, out=None)
+
+ Compute the truth value of NOT x element-wise.
+
+ Parameters
+ ----------
+ x : ndarray or scalar
+ Logical NOT is applied to the elements of `x`.
+ out : ndarray or None, optional
+ A location into which the result is stored.
+
+ Returns
+ -------
+ y : bool or ndarray of bool
+ Boolean result with the same shape as `x` of the NOT operation
+ on elements of `x`.
+ This is a scalar if `x` is a scalar.
+
+ Notes
+ -----
+ This function differs to the original numpy.logical_not in the following
aspects:
+ - Do not support 'where', a parameter in numpy which indicates where
to calculate.
+ - Cannot cast type automatically. Dtype of 'out' must be same as the
expected one.
+ - Cannot broadcast automatically. Shape of 'out' must be same as the
expected one.
+ - If 'x' is plain python numeric, the result won't be stored in out.
+
+ Examples
+ --------
+ ***>>> x= np.array([True, False, 0, 1])
+ >>> np.logical_not(x)
+ array([0., 1., 1., 0.])
+
+ >>> x = np.arange(5)
+ >>> np.logical_not(x<3)
+ array([0., 0., 0., 1., 1.])
+ """
+ return _unary_func_helper(x, _npi.logical_not, _np.logical_not, out=out,
**kwargs)
+
+@set_module('mxnet.ndarray.numpy')
+def arccosh(x, out=None, **kwargs):
+ r"""
+ arccosh(x, out=None)
+
+ Inverse hyperbolic cosine, element-wise.
+
+ Parameters
+ ----------
+ x : ndarray or scalar
+ Input array.
+ out : ndarray or None, optional
+ A location into which the result is stored.
+
+ Returns
+ -------
+ arccosh : ndarray
+ Array of the same shape as `x`.
+ This is a scalar if `x` is a scalar.
+
+ Notes
+ -----
+ `arccosh` is a multivalued function: for each `x` there are infinitely
+ many numbers `z` such that `cosh(z) = x`. The convention is to return the
+ `z` whose imaginary part lies in `[-pi, pi]` and the real part in
+ ``[0, inf]``.
+
+ For real-valued input data types, `arccosh` always returns real output.
+ For each value that cannot be expressed as a real number or infinity, it
+ yields ``nan`` and sets the `invalid` floating point error flag.
+
+ For complex-valued input, `arccosh` is a complex analytical function that
+ has a branch cut `[-inf, 1]` and is continuous from above on it.
+
+ This function differs to the original numpy.logical_not in the following
aspects:
+ - Do not support 'where', a parameter in numpy which indicates where
to calculate.
+ - Cannot cast type automatically. Dtype of 'out' must be same as the
expected one.
+ - Cannot broadcast automatically. Shape of 'out' must be same as the
expected one.
+ - If 'x' is plain python numeric, the result won't be stored in out.
Review comment:
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