Conditionals¶

sspace.conditionals.both(a, b)[source]¶

True if both conditions a and b are true

Parameters:	a: _Condition b: _Condition
Returns:	returns a `_Condition`

Examples

>>> from sspace import Space
>>> space = Space()
>>> a = space.uniform('a', 1, 2, quantization=0.01)
>>> b = space.uniform('b', 1, 2, quantization=0.01)
>>> b.enable_if(both(gt(a, 2), lt(a, 1)))

sspace.conditionals.contains(name, value)[source]¶

True if the sampled value of the hyper-parameter self is contained by value

Parameters:	name: _Dimension hyper-parameter expression value: List List of values
Returns:	returns a `_Condition`

Examples

>>> from sspace import Space
>>> space = Space()
>>> a = space.uniform('a', 1, 2, quantization=0.01)
>>> b = space.uniform('b', 1, 2, quantization=0.01)
>>> b.enable_if(contains(a, [1, 2, 3]))

sspace.conditionals.either(a, b)[source]¶

True if one of the conditions a and b are true

Parameters:	a: _Condition b: _Condition
Returns:	returns a `_Condition`

Examples

>>> from sspace import Space
>>> space = Space()
>>> a = space.uniform('a', 1, 2, quantization=0.01)
>>> b = space.uniform('b', 1, 2, quantization=0.01)
>>> b.enable_if(either(gt(a, 2), lt(a, 1)))

sspace.conditionals.eq(name, value)[source]¶

True if the sampled value of the hyper-parameter self is equal to value

Parameters:	name: _Dimension hyper-parameter expression value: Union[float, int, str]
Returns:	returns a `_Condition`

Examples

>>> from sspace import Space
>>> space = Space()
>>> a = space.uniform('a', 1, 2, quantization=0.01)
>>> b = space.uniform('b', 1, 2, quantization=0.01)
>>> b.enable_if(eq(a, 1))

sspace.conditionals.gt(name, value)[source]¶

True if the sampled value of the hyper-parameter self is greater than value

Parameters:	name: _Dimension hyper-parameter expression value: Union[float, int, str]
Returns:	returns a `_Condition`

Examples

>>> from sspace import Space
>>> space = Space()
>>> a = space.uniform('a', 1, 2, quantization=0.01)
>>> b = space.uniform('b', 1, 2, quantization=0.01)
>>> b.enable_if(gt(a, 1))

sspace.conditionals.lt(name, value)[source]¶

True if the sampled value of the hyper-parameter self is less than value

Parameters:	name: _Dimension hyper-parameter expression value: Union[float, int, str]
Returns:	returns a `_Condition`

Examples

>>> from sspace import Space
>>> space = Space()
>>> a = space.uniform('a', 1, 2, quantization=0.01)
>>> b = space.uniform('b', 1, 2, quantization=0.01)
>>> b.enable_if(lt(a, 1))

sspace.conditionals.ne(name, value)[source]¶

True if the sampled value of the hyper-parameter self is not equal to value

Parameters:	name: _Dimension hyper-parameter expression value: Union[float, int, str]
Returns:	returns a `_Condition`

Examples

>>> from sspace import Space
>>> space = Space()
>>> a = space.uniform('a', 1, 2, quantization=0.01)
>>> b = space.uniform('b', 1, 2, quantization=0.01)
>>> b.enable_if(ne(a, 1))