scipp.Masks#

class scipp.Masks#

dict-like collection of masks.

Returned by DataArray.masks()

__init__(*args, **kwargs)#

Methods

`__init__`(args, *kwargs)
`clear`(self)
`copy`(self[, deep])	Return a (by default deep) copy.
`get`	Get the value associated with the provided key or the default value.
`is_edges`(self, key[, dim])	Return True if the given key contains bin-edges in the given dim.
`items`(self)	view on self's items
`keys`(self)	view on self's keys
`pop`	Remove and return an element.
`popitem`(self)
`update`(self[, other])	Update items from dict-like or iterable.
`values`(self)	view on self's values

__getitem__(self: scipp._scipp.core.Masks, arg0: str) → scipp._scipp.core.Variable#

clear(self: scipp._scipp.core.Masks) → None#

copy(self: scipp._scipp.core.Masks, deep: bool = True) → scipp._scipp.core.Masks#

Return a (by default deep) copy.

If deep=True (the default), a deep copy is made. Otherwise, a shallow copy is made, and the returned data (and meta data) values are new views of the data and meta data values of this object.

get()#

Get the value associated with the provided key or the default value.

Examples

Access a coordinate with a default value:

>>> import scipp as sc
>>> da = sc.DataArray(sc.array(dims=['x'], values=[1, 2, 3]))
>>> da.coords.get('x')  # returns None if 'x' does not exist
>>> da.coords['x'] = sc.arange('x', 3)
>>> da.coords.get('x')
<scipp.Variable> (x: 3)      int64  [dimensionless]  [0, 1, 2]

Access a Dataset item with a default value:

>>> ds = sc.Dataset({'a': sc.array(dims=['x'], values=[1, 2, 3])})
>>> ds.get('b', sc.DataArray(sc.zeros(dims=['x'], shape=[3])))
<scipp.DataArray>
Dimensions: Sizes[x:3, ]
Data:
                            float64  [dimensionless]  (x)  [0, 0, 0]

is_edges(self: scipp._scipp.core.Masks, key: str, dim: str | None = None) → bool#

Return True if the given key contains bin-edges in the given dim.

Bin-edge coordinates have one more element than the corresponding dimension size. They define the boundaries of histogram bins.

Parameters:

key – Name of the coordinate to check.
dim – Dimension to check against. If not provided, checks the coordinate’s single dimension.

Returns:

True if the coordinate is a bin-edge coordinate.

Examples

>>> import scipp as sc
>>> da = sc.DataArray(
...     sc.array(dims=['x'], values=[1.0, 2.0, 3.0]),
...     coords={'x': sc.array(dims=['x'], values=[0.0, 1.0, 2.0, 3.0])}
... )
>>> da.coords.is_edges('x')
True

Point coordinates have the same size as the dimension:

>>> da2 = sc.DataArray(
...     sc.array(dims=['x'], values=[1.0, 2.0, 3.0]),
...     coords={'x': sc.array(dims=['x'], values=[0.5, 1.5, 2.5])}
... )
>>> da2.coords.is_edges('x')
False

items(self: scipp._scipp.core.Masks) → scipp._scipp.core.Masks_items_view#: view on self’s items

keys(self: scipp._scipp.core.Masks) → scipp._scipp.core.Masks_keys_view#: view on self’s keys

pop()#

Remove and return an element.

If key is not found, default is returned if given, otherwise KeyError is raised.

Examples

Remove a coordinate from a DataArray:

>>> import scipp as sc
>>> da = sc.DataArray(
...     sc.array(dims=['x'], values=[1.0, 2.0, 3.0]),
...     coords={'x': sc.arange('x', 3), 'y': sc.arange('x', 3) * 10}
... )
>>> da.coords.pop('y')
<scipp.Variable> (x: 3)      int64  [dimensionless]  [0, 10, 20]
>>> 'y' in da.coords
False

Pop with default value for missing key:

>>> da.coords.pop('z', sc.scalar(0))
<scipp.Variable> ()      int64  [dimensionless]  0

Remove an item from a Dataset:

>>> ds = sc.Dataset({'a': sc.array(dims=['x'], values=[1, 2, 3]),
...                  'b': sc.array(dims=['x'], values=[4, 5, 6])})
>>> ds.pop('b')
<scipp.DataArray>
...
>>> list(ds.keys())
['a']

popitem(self: scipp._scipp.core.Masks) → tuple[str, scipp._scipp.core.Variable]#

update(self: scipp._scipp.core.Masks, other: object = None, /, **kwargs) → None#

Update items from dict-like or iterable.

If other has a .keys() method, then update does: for k in other.keys(): self[k] = other[k].

If other is given but does not have a .keys() method, then update does: for k, v in other: self[k] = v.

In either case, this is followed by: for k in kwargs: self[k] = kwargs[k].

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scipp.Masks#