Index

def cast(py) -> "Scalar":
    """
    1. cast Real number (or list/tuple of Real numbers)
    to [`Scalar Literal`][bloqade.ir.scalar.Literal].

    2. cast str (or list/tuple of Real numbers)
    to [`Scalar Variable`][bloqade.ir.scalar.Variable].

    Args:
        py (Union[str,Real,Tuple[Real],List[Real]]): python object to cast

    Returns:
        Scalar
    """
    ret = trycast(py)
    if ret is None:
        raise TypeError(f"Cannot cast {type(py)} to Scalar Literal")

    return ret

@beartype
def constant(duration: ScalarType, value: ScalarType) -> Constant:
    """Create a Constant waveform.

    Args:
        duration (ScalarType): Duration of the Constant waveform.
        value (ScalarType): Value of the Constant waveform.s

    Returns:
        Constant: A Constant waveform.
    """
    return Constant(value, duration)

@beartype
def dumps(
    o: Any,
    use_decimal: bool = True,
    **json_kwargs,
) -> str:
    """Serialize object to string

    Args:
        o (Any): the object to serialize
        use_decimal (bool, optional): use decimal.Decimal for numbers. Defaults to True.
        **json_kwargs: other arguments passed to json.dumps

    Returns:
        str: the serialized object as a string
    """
    if not isinstance(o, Serializer.types):
        raise TypeError(
            f"Object of type {type(o)} is not JSON serializable. "
            f"Only {Serializer.types} are supported."
        )
    return json.dumps(o, cls=Serializer, use_decimal=use_decimal, **json_kwargs)

def get_capabilities(use_experimental: bool = False) -> "QuEraCapabilities":
    """Get the device capabilities for Aquila

    Args:
        use_experimental (bool): Get experimental capabilities instead of
            standard ones. By default value is False.

    Returns:
        QuEraCapabilities: capabilities object for Aquila device.


    Note:
        Units of time, distance, and energy are microseconds (us),
        micrometers (um), and rad / us, respectively.

        For a comprehensive list of capabilities,
        see the [Hardware Reference](../../reference/hardware-capabilities.md)
        page
    """

    from bloqade.analog.submission.capabilities import get_capabilities

    # manually convert to units
    return get_capabilities(use_experimental=use_experimental).scale_units(
        Decimal("1e6"), Decimal("1e-6")
    )

@beartype
def linear(duration: ScalarType, start: ScalarType, stop: ScalarType) -> Linear:
    """Create a Linear waveform.

    Args:
        duration (ScalarType): Duration of linear waveform
        start (ScalarType): Starting value of linear waveform
        stop (ScalarType): Ending value of linear waveform

    Returns:
        Linear: Linear waveform
    """
    return Linear(start, stop, duration)

@beartype
def load(fp: Union[TextIO, str], use_decimal: bool = True, **json_kwargs):
    """Load object from file

    Args:
        fp (Union[TextIO, str]): the file path or file object
        use_decimal (bool, optional): use decimal.Decimal for numbers. Defaults to True.
        **json_kwargs: other arguments passed to json.load

    Returns:
        Any: the deserialized object
    """
    load_bloqade()
    if isinstance(fp, str):
        with open(fp, "r") as f:
            return json.load(
                f,
                object_hook=Serializer.object_hook,
                use_decimal=use_decimal,
                **json_kwargs,
            )
    else:
        return json.load(
            fp,
            object_hook=Serializer.object_hook,
            use_decimal=use_decimal,
            **json_kwargs,
        )

@beartype
def loads(s: str, use_decimal: bool = True, **json_kwargs):
    """Load object from string

    Args:
        s (str): the string to load
        use_decimal (bool, optional): use decimal.Decimal for numbers. Defaults to True.
        **json_kwargs: other arguments passed to json.loads

    Returns:
        Any: the deserialized object
    """
    load_bloqade()
    return json.loads(
        s, object_hook=Serializer.object_hook, use_decimal=use_decimal, **json_kwargs
    )

@beartype
def piecewise_constant(
    durations: List[ScalarType], values: List[ScalarType]
) -> Waveform:
    """Create a piecewise linear waveform.

    Create a piecewise constant waveform from a list of durations and values. The
    value `duration[i]` corresponds to the length of time for the i'th segment
    with a value of `values[i]`.

    Args:
        durations (List[ScalarType]): The duration of each segment
        values (List[ScalarType]): The values for each segment

    Raises:
        ValueError: If the length of `values` is not the same as the length of
        `durations`.

    Returns:
        Waveform: The piecewise linear waveform.
    """
    if len(durations) != len(values):
        raise ValueError(
            "The length of values must be the same as the length of durations"
        )

    if len(durations) == 0:
        raise ValueError("The durations and values lists must not be empty.")

    pwc_wf = Constant(values[0], durations[0])
    for duration, value in zip(durations[1:], values[1:]):
        pwc_wf = pwc_wf.append(Constant(value, duration))

    return pwc_wf

@beartype
def piecewise_linear(durations: List[ScalarType], values: List[ScalarType]) -> Waveform:
    """Create a piecewise linear waveform.

    Create a piecewise linear waveform from a list of durations and values. The
    value `duration[i]` is of the linear segment between `values[i]` and `values[i+1]`.

    Args:
        durations (List[ScalarType]): The duration of each segment
        values (List[ScalarType]): The values for each segment

    Raises:
        ValueError: If the length of `values` is not one greater than the length of
        `durations`.

    Returns:
        Waveform: The piecewise linear waveform.
    """

    if len(durations) + 1 != len(values):
        raise ValueError(
            "The length of values must be one greater than the length of durations"
        )

    if len(durations) == 0:
        raise ValueError("The durations and values lists must not be empty.")

    pwl_wf = Linear(values[0], values[1], durations[0])
    for duration, start, stop in zip(durations[1:], values[1:-1], values[2:]):
        pwl_wf = pwl_wf.append(Linear(start, stop, duration))

    return pwl_wf

@beartype
def rydberg_h(
    atoms_positions: Any,
    detuning: Optional[Waveform] = None,
    amplitude: Optional[Waveform] = None,
    phase: Optional[Waveform] = None,
    static_params: Dict[str, Any] = {},
    batch_params: Union[List[Dict[str, Any]], Dict[str, Any]] = [],
    args: List[str | Variable] = [],
) -> Routine:
    """Create a rydberg program with uniform detuning, amplitude, and phase.

    Args:
        atoms_positions (Any): Description of geometry of atoms in system.
        detuning (Optional[Waveform], optional): Waveform for detuning.
            Defaults to None.
        amplitude (Optional[Waveform], optional): Waveform describing the amplitude of
            the rabi term. Defaults to None.
        phase (Optional[Waveform], optional): Waveform describing the phase of rabi
            term. Defaults to None.
        static_params (Dict[str, Any], optional): Define static parameters of your
            program. Defaults to {}.
        batch_params (Union[List[Dict[str, Any]], Dict[str, Any]], optional):
            Parmaters for a batch of tasks. Defaults to [].
        args (List[str], optional): List of arguments to leave till runtime.
            Defaults to [].

    Returns:
        Routine: An object that can be used to dispatch a rydberg program to
            multiple backends.
    """
    from bloqade.analog import start
    from bloqade.analog.atom_arrangement import AtomArrangement

    if isinstance(atoms_positions, AtomArrangement):
        prog = atoms_positions
    else:
        prog = start.add_position(atoms_positions)

    if detuning is not None:
        prog = prog.rydberg.detuning.uniform.apply(detuning)

    if amplitude is not None:
        prog = prog.rydberg.rabi.amplitude.uniform.apply(amplitude)

    if phase is not None:
        prog = prog.rydberg.rabi.phase.uniform.apply(phase)

    if not isinstance(prog, Assignable):
        raise ValueError(
            "At least one of detuning, amplitude, or phase must be provided."
        )

    prog = prog.assign(**static_params)

    if isinstance(batch_params, dict):
        prog = prog.batch_assign(**batch_params)
    else:
        prog = prog.batch_assign(batch_params)

    prog = prog.args(args)

    return prog.parse()

@beartype
def save(
    o: Any,
    fp: Union[TextIO, str],
    use_decimal=True,
    **json_kwargs,
) -> None:
    """Serialize object to file

    Args:
        o (Any): the object to serialize
        fp (Union[TextIO, str]): the file path or file object
        use_decimal (bool, optional): use decimal.Decimal for numbers. Defaults to True.
        **json_kwargs: other arguments passed to json.dump

    Returns:
        None
    """
    if not isinstance(o, Serializer.types):
        raise TypeError(
            f"Object of type {type(o)} is not JSON serializable. "
            f"Only {Serializer.types} are supported."
        )
    if isinstance(fp, str):
        with open(fp, "w") as f:
            json.dump(o, f, cls=Serializer, use_decimal=use_decimal, **json_kwargs)
    else:
        json.dump(o, fp, cls=Serializer, use_decimal=use_decimal, **json_kwargs)

def tree_depth(depth: int = None):
    """Setting globally maximum depth for tree printing

    If `depth=None`, return current depth.
    If `depth` is provided, setting current depth to `depth`

    Args:
        depth (int, optional): the user specified depth. Defaults to None.

    Returns:
        int: current updated depth
    """
    if depth is not None:
        _ir.tree_print.MAX_TREE_DEPTH = depth
    return _ir.tree_print.MAX_TREE_DEPTH

def var(py: str) -> "Variable":
    """cast string (or list/tuple of strings)
    to [`Variable`][bloqade.ir.scalar.Variable].

    Args:
        py (Union[str, List[str]]): a string or list/tuple of strings

    Returns:
       Union[Variable]
    """
    ret = tryvar(py)
    if ret is None:
        raise TypeError(f"Cannot cast {type(py)} to Variable")

    return ret