nanmax(a, axis=None, keepdims=False, split_every=None, out=None)
This docstring was copied from numpy.nanmax.
Some inconsistencies with the Dask version may exist.
NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic (IEEE 754). This means that Not a Number is not equivalent to infinity. Positive infinity is treated as a very large number and negative infinity is treated as a very small (i.e. negative) number.
If the input has a integer type the function is equivalent to np.max.
Array containing numbers whose maximum is desired. If a is not an array, a conversion is attempted.
Axis or axes along which the maximum is computed. The default is to compute the maximum of the flattened array.
Alternate output array in which to place the result. The default is None
; if provided, it must have the same shape as the expected output, but the type will be cast if necessary. See ufuncs-output-type
for more details.
If this is set to True, the axes which are reduced are left in the result as dimensions with size one. With this option, the result will broadcast correctly against the original a.
If the value is anything but the default, then keepdims
will be passed through to the max
method of sub-classes of :None:None:`ndarray`. If the sub-classes methods does not implement keepdims
any exceptions will be raised.
The minimum value of an output element. Must be present to allow computation on empty slice. See :None:None:`~numpy.ufunc.reduce` for details.
Elements to compare for the maximum. See :None:None:`~numpy.ufunc.reduce` for details.
An array with the same shape as a, with the specified axis removed. If a is a 0-d array, or if axis is None, an ndarray scalar is returned. The same dtype as a is returned.
Return the maximum of an array or maximum along an axis, ignoring any NaNs. When all-NaN slices are encountered a RuntimeWarning
is raised and NaN is returned for that slice.
amax
The maximum value of an array along a given axis, propagating any NaNs.
fmax
Element-wise maximum of two arrays, ignoring any NaNs.
isfinite
Shows which elements are neither NaN nor infinity.
isnan
Shows which elements are Not a Number (NaN).
maximum
Element-wise maximum of two arrays, propagating any NaNs.
nanmin
The minimum value of an array along a given axis, ignoring any NaNs.
>>> a = np.array([[1, 2], [3, np.nan]]) # doctest: +SKIPThis example is valid syntax, but we were not able to check execution
... np.nanmax(a) # doctest: +SKIP 3.0
>>> np.nanmax(a, axis=0) # doctest: +SKIP array([3., 2.])This example is valid syntax, but we were not able to check execution
>>> np.nanmax(a, axis=1) # doctest: +SKIP array([2., 3.])
When positive infinity and negative infinity are present:
This example is valid syntax, but we were not able to check execution>>> np.nanmax([1, 2, np.nan, np.NINF]) # doctest: +SKIP 2.0This example is valid syntax, but we were not able to check execution
>>> np.nanmax([1, 2, np.nan, np.inf]) # doctest: +SKIP infSee :
The following pages refer to to this document either explicitly or contain code examples using this.
dask.array.ufunc.fmin
dask.array.reductions.min
dask.array.reductions.max
dask.array.ufunc.minimum
dask.array.ufunc.fmax
dask.array.reductions.make_arg_reduction.<locals>.wrapped
dask.array.reductions.nanmin
dask.array.ufunc.maximum
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