numpy 1.22.4 Pypi GitHub Homepage
Other Docs
ParametersReturns
make_mask_none(newshape, dtype=None)

This function returns a boolean ndarray with all entries False, that can be used in common mask manipulations. If a complex dtype is specified, the type of each field is converted to a boolean type.

Parameters

newshape : tuple

A tuple indicating the shape of the mask.

dtype : {None, dtype}, optional

If None, use a MaskType instance. Otherwise, use a new datatype with the same fields as dtype , converted to boolean types.

Returns

result : ndarray

An ndarray of appropriate shape and dtype, filled with False.

Return a boolean mask of the given shape, filled with False.

See Also

make_mask

Create a boolean mask from an array.

make_mask_descr

Construct a dtype description list from a given dtype.

Examples

This example is valid syntax, but we were not able to check execution
>>> import numpy.ma as ma
... ma.make_mask_none((3,)) array([False, False, False])

Defining a more complex dtype.

This example is valid syntax, but we were not able to check execution
>>> dtype = np.dtype({'names':['foo', 'bar'],
...  'formats':[np.float32, np.int64]})
... dtype dtype([('foo', '<f4'), ('bar', '<i8')])
This example is valid syntax, but we were not able to check execution
>>> ma.make_mask_none((3,), dtype=dtype)
array([(False, False), (False, False), (False, False)],
      dtype=[('foo', '|b1'), ('bar', '|b1')])
See :

Local connectivity graph

Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.

Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)

SVG is more flexible but power hungry; and does not scale well to 50 + nodes.

All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them


GitHub : /numpy/ma/core.py#1637
type: <class 'function'>
Commit: