# ClassicalFunction

`qiskit.circuit.classicalfunction.ClassicalFunction(source, name=None)`

GitHub(opens in a new tab)

Bases: `ClassicalElement`

Represent a classical function and its logic network.

Creates a `ClassicalFunction`

from Python source code in `source`

.

The code should be a single function with types.

**Parameters**

**source**(*str*(opens in a new tab)) – Python code with type hints.**name**(*str*(opens in a new tab)) – Optional. Default: “*classicalfunction*”. ClassicalFunction name.

**Raises**

**QiskitError** – If source is not a string.

## Attributes

### args

Returns the classicalfunction arguments

### base_class

Get the base class of this instruction. This is guaranteed to be in the inheritance tree of `self`

.

The “base class” of an instruction is the lowest class in its inheritance tree that the object should be considered entirely compatible with for _all_ circuit applications. This typically means that the subclass is defined purely to offer some sort of programmer convenience over the base class, and the base class is the “true” class for a behavioural perspective. In particular, you should *not* override `base_class`

if you are defining a custom version of an instruction that will be implemented differently by hardware, such as an alternative measurement strategy, or a version of a parametrised gate with a particular set of parameters for the purposes of distinguishing it in a `Target`

from the full parametrised gate.

This is often exactly equivalent to `type(obj)`

, except in the case of singleton instances of standard-library instructions. These singleton instances are special subclasses of their base class, and this property will return that base. For example:

```
>>> isinstance(XGate(), XGate)
True
>>> type(XGate()) is XGate
False
>>> XGate().base_class is XGate
True
```

In general, you should not rely on the precise class of an instruction; within a given circuit, it is expected that `Instruction.name`

should be a more suitable discriminator in most situations.

### condition

The classical condition on the instruction.

### condition_bits

Get Clbits in condition.

### decompositions

Get the decompositions of the instruction from the SessionEquivalenceLibrary.

### definition

Return definition in terms of other basic gates.

### duration

Get the duration.

### label

Return instruction label

### mutable

Is this instance is a mutable unique instance or not.

If this attribute is `False`

the gate instance is a shared singleton and is not mutable.

### name

Return the name.

### network

Returns the logical network

### num_clbits

Return the number of clbits.

### num_qubits

Return the number of qubits.

### params

return instruction params.

### qregs

The list of qregs used by the classicalfunction

### scopes

Returns the scope dict

### truth_table

Returns (and computes) the truth table

### types

Dumps a list of scopes with their variables and types.

**Returns**

A list of scopes as dicts, where key is the variable name and value is its type.

**Return type**

list(opens in a new tab)(dict(opens in a new tab))

### unit

Get the time unit of duration.

## Methods

### add_decomposition

`add_decomposition(decomposition)`

Add a decomposition of the instruction to the SessionEquivalenceLibrary.

### assemble

`assemble()`

Assemble a QasmQobjInstruction

### broadcast_arguments

`broadcast_arguments(qargs, cargs)`

Validation and handling of the arguments and its relationship.

For example, `cx([q[0],q[1]], q[2])`

means `cx(q[0], q[2]); cx(q[1], q[2])`

. This method yields the arguments in the right grouping. In the given example:

```
in: [[q[0],q[1]], q[2]],[]
outs: [q[0], q[2]], []
[q[1], q[2]], []
```

The general broadcasting rules are:

If len(qargs) == 1:

`[q[0], q[1]] -> [q[0]],[q[1]]`

If len(qargs) == 2:

`[[q[0], q[1]], [r[0], r[1]]] -> [q[0], r[0]], [q[1], r[1]] [[q[0]], [r[0], r[1]]] -> [q[0], r[0]], [q[0], r[1]] [[q[0], q[1]], [r[0]]] -> [q[0], r[0]], [q[1], r[0]]`

If len(qargs) >= 3:

`[q[0], q[1]], [r[0], r[1]], ...] -> [q[0], r[0], ...], [q[1], r[1], ...]`

**Parameters**

**qargs**(*list*(opens in a new tab)) – List of quantum bit arguments.**cargs**(*list*(opens in a new tab)) – List of classical bit arguments.

**Returns**

A tuple with single arguments.

**Raises**

**CircuitError** – If the input is not valid. For example, the number of arguments does not match the gate expectation.

**Return type**

*Iterable*(opens in a new tab)[tuple(opens in a new tab)[list(opens in a new tab), list(opens in a new tab)]]

### c_if

`c_if(classical, val)`

Set a classical equality condition on this instruction between the register or cbit `classical`

and value `val`

.

This is a setter method, not an additive one. Calling this multiple times will silently override any previously set condition; it does not stack.

### compile

`compile()`

Parses and creates the logical circuit

### control

`control(num_ctrl_qubits=1, label=None, ctrl_state=None, annotated=False)`

Return the controlled version of itself.

Implemented either as a controlled gate (ref. `ControlledGate`

) or as an annotated operation (ref. `AnnotatedOperation`

).

**Parameters**

**num_ctrl_qubits**(*int*(opens in a new tab)) – number of controls to add to gate (default:`1`

)**label**(*str*(opens in a new tab)*| None*) – optional gate label. Ignored if implemented as an annotated operation.**ctrl_state**(*int*(opens in a new tab)*|**str*(opens in a new tab)*| None*) – the control state in decimal or as a bitstring (e.g.`'111'`

). If`None`

, use`2**num_ctrl_qubits-1`

.**annotated**(*bool*(opens in a new tab)) – indicates whether the controlled gate can be implemented as an annotated gate.

**Returns**

Controlled version of the given operation.

**Raises**

**QiskitError** – unrecognized mode or invalid ctrl_state

### copy

`copy(name=None)`

Copy of the instruction.

**Parameters**

**name** (*str*(opens in a new tab)) – name to be given to the copied circuit, if `None`

then the name stays the same.

**Returns**

a copy of the current instruction, with the name updated if it was provided

**Return type**

### inverse

`inverse(annotated=False)`

Invert this instruction.

If annotated is False, the inverse instruction is implemented as a fresh instruction with the recursively inverted definition.

If annotated is True, the inverse instruction is implemented as `AnnotatedOperation`

, and corresponds to the given instruction annotated with the “inverse modifier”.

Special instructions inheriting from Instruction can implement their own inverse (e.g. T and Tdg, Barrier, etc.) In particular, they can choose how to handle the argument `annotated`

which may include ignoring it and always returning a concrete gate class if the inverse is defined as a standard gate.

**Parameters**

**annotated** (*bool*(opens in a new tab)) – if set to True the output inverse gate will be returned as `AnnotatedOperation`

.

**Returns**

The inverse operation.

**Raises**

**CircuitError** – if the instruction is not composite and an inverse has not been implemented for it.

### is_parameterized

`is_parameterized()`

Return True .IFF. instruction is parameterized else False

### power

`power(exponent)`

Creates a unitary gate as gate^exponent.

**Parameters**

**exponent** (*float*(opens in a new tab)) – Gate^exponent

**Returns**

To which to_matrix is self.to_matrix^exponent.

**Return type**

.library.UnitaryGate

**Raises**

**CircuitError** – If Gate is not unitary

### repeat

`repeat(n)`

Creates an instruction with gate repeated n amount of times.

**Parameters**

**n** (*int*(opens in a new tab)) – Number of times to repeat the instruction

**Returns**

Containing the definition.

**Return type**

**Raises**

**CircuitError** – If n < 1.

### reverse_ops

`reverse_ops()`

For a composite instruction, reverse the order of sub-instructions.

This is done by recursively reversing all sub-instructions. It does not invert any gate.

**Returns**

**a new instruction with**

sub-instructions reversed.

**Return type**

### simulate

`simulate(bitstring)`

Evaluate the expression on a bitstring.

This evaluation is done classically.

**Parameters**

**bitstring** (*str*(opens in a new tab)) – The bitstring for which to evaluate.

**Returns**

result of the evaluation.

**Return type**

### simulate_all

`simulate_all()`

Returns a truth table.

**Returns**

a bitstring with a truth table

**Return type**

### soft_compare

`soft_compare(other)`

Soft comparison between gates. Their names, number of qubits, and classical bit numbers must match. The number of parameters must match. Each parameter is compared. If one is a ParameterExpression then it is not taken into account.

**Parameters**

**other** (*instruction*) – other instruction.

**Returns**

are self and other equal up to parameter expressions.

**Return type**

### synth

`synth(registerless=True, synthesizer=None)`

Synthesis the logic network into a `QuantumCircuit`

.

**Parameters**

**registerless**(*bool*(opens in a new tab)) – Default`True`

. If`False`

uses the parameter names to create**Otherwise**(*registers with those names.*) –**register.**(*creates a circuit with a flat quantum*) –**synthesizer**(*Callable*(opens in a new tab)*[[ClassicalElement],**QuantumCircuit**] | None*) – Optional. If None tweedledum’s pkrm_synth is used.

**Returns**

A circuit implementing the logic network.

**Return type**

### to_matrix

`to_matrix()`

Return a Numpy.array for the gate unitary matrix.

**Returns**

if the Gate subclass has a matrix definition.

**Return type**

np.ndarray

**Raises**

**CircuitError** – If a Gate subclass does not implement this method an exception will be raised when this base class method is called.

### to_mutable

`to_mutable()`

Return a mutable copy of this gate.

This method will return a new mutable copy of this gate instance. If a singleton instance is being used this will be a new unique instance that can be mutated. If the instance is already mutable it will be a deepcopy of that instance.

### validate_parameter

`validate_parameter(parameter)`

Gate parameters should be int, float, or ParameterExpression