SaveProbabilities#

class SaveProbabilities(num_qubits, label='probabilities', unnormalized=False, pershot=False, conditional=False)[source]#

Bases: SaveAverageData

Save measurement outcome probabilities vector.

Instruction to save measurement probabilities vector.

Parameters:

num_qubits (int) – the number of qubits for the snapshot type.
label (str) – the key for retrieving saved data from results.
unnormalized (bool) – If True return save the unnormalized accumulated probabilities over all shots [Default: False].
pershot (bool) – if True save a list of probabilities for each shot of the simulation rather than the average over all shots [Default: False].
conditional (bool) – if True save the probabilities data conditional on the current classical register values [Default: False].

Attributes

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 behavioral 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 parametrized gate with a particular set of parameters for the purposes of distinguishing it in a Target from the full parametrized 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.

num_clbits#: Return the number of clbits.

num_qubits#: Return the number of qubits.

params#: The parameters of this Instruction. Ideally these will be gate angles.

unit#: Get the time unit of duration.

Methods

add_decomposition(decomposition)[source]#: Add a decomposition of the instruction to the SessionEquivalenceLibrary.

assemble()[source]#: Assemble a QasmQobjInstruction

Deprecated since version 1.2: The method qiskit.circuit.instruction.Instruction.assemble() is deprecated as of qiskit 1.2. It will be removed in the 2.0 release. The Qobj class and related functionality are part of the deprecated BackendV1 workflow, and no longer necessary for BackendV2. If a user workflow requires Qobj it likely relies on deprecated functionality and should be updated to use BackendV2.

broadcast_arguments(qargs, cargs)[source]#

Validation of the arguments.

Parameters:

qargs (List) – List of quantum bit arguments.
cargs (List) – List of classical bit arguments.

Yields:

Tuple(List, List) – 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.

c_if(classical, val)[source]#: Set a classical equality condition on this instruction between the register or cbit classical and value val.

Note

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

copy(name=None)[source]#

Copy of the instruction.

Parameters:: name (str) – 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:: qiskit.circuit.Instruction

inverse(annotated=False)[source]#: Special case. Return self.

is_parameterized()[source]#: Return whether the Instruction contains compile-time parameters.

repeat(n)[source]#

Creates an instruction with self repeated :math`n` times.

If this operation has a conditional, the output instruction will have the same conditional and the inner repeated operations will be unconditional; instructions within a compound definition cannot be conditioned on registers within Qiskit’s data model. This means that it is not valid to apply a repeated instruction to a clbit that it both writes to and reads from in its condition.

Parameters:: n (int) – Number of times to repeat the instruction
Returns:: Containing the definition.
Return type:: qiskit.circuit.Instruction
Raises:: CircuitError – If n < 1.

reverse_ops()[source]#

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:

qiskit.circuit.Instruction

soft_compare(other: Instruction) → bool[source]#

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:: bool

to_mutable()[source]#

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(parameter)[source]#: Instruction parameters has no validation or normalization.