cond

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cond#

class brainpy.math.cond(pred, true_fun, false_fun, operands=())[source]#

Simple conditional statement (if-else) with instance of Variable.

>>> import brainpy.math as bm
>>> a = bm.Variable(bm.zeros(2))
>>> b = bm.Variable(bm.ones(2))
>>> def true_f():  a.value += 1
>>> def false_f(): b.value -= 1
>>>
>>> bm.cond(True, true_f, false_f)
>>> a, b
Variable([1., 1.], dtype=float32), Variable([1., 1.], dtype=float32)
>>>
>>> bm.cond(False, true_f, false_f)
>>> a, b
Variable([1., 1.], dtype=float32), Variable([0., 0.], dtype=float32)
Parameters:

  • pred (bool) – Boolean scalar type, indicating which branch function to apply.

  • true_fun (Union[Callable, Array, Array, Number]) – Function to be applied if pred is True. This function must receive one arguement for operands.

  • false_fun (Union[Callable, Array, Array, Number]) – Function to be applied if pred is False. This function must receive one arguement for operands.

  • operands (Any) – Operands (A) input to branching function depending on pred. The type can be a scalar, array, or any pytree (nested Python tuple/list/dict) thereof.

  • dyn_vars (optional, Variable, sequence of Variable, dict) –

    The dynamically changed variables.

    Deprecated since version 2.4.0: No longer need to provide dyn_vars. This function is capable of automatically collecting the dynamical variables used in the target func.

  • child_objs (optional, dict, sequence of BrainPyObject, BrainPyObject) –

    The children objects used in the target function.

    Deprecated since version 2.4.0: No longer need to provide dyn_vars. This function is capable of automatically collecting the dynamical variables used in the target func.

Returns:

res – The conditional results.

Return type:

Any

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