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MultiParameter

Return multiple items at once, where each item can be a single value or an array.

Note: Most of the kwarg names here are the plural of those used in Parameter and ArrayParameter. In particular, MultiParameter is the ONLY one that uses units, all the others use unit.

MultiParameter is, for now, only gettable.

import numpy as np

from qcodes.parameters import ManualParameter, MultiParameter

class SingleIQPair(MultiParameter):
    def __init__(self, scale_param):
        # only name, names, and shapes are required
        # this version returns two scalars (shape = `()`)
        super().__init__(
            "single_iq",
            names=("I", "Q"),
            shapes=((), ()),
            labels=("In phase amplitude", "Quadrature amplitude"),
            units=("V", "V"),
            # including these setpoints is unnecessary here, but
            # if you have a parameter that returns a scalar alongside
            # an array you can represent the scalar as an empty sequence.
            setpoints=((), ()),
            docstring="param that returns two single values, I and Q",
        )
        self._scale_param = scale_param

    def get_raw(self):
        scale_val = self._scale_param()
        return (scale_val, scale_val / 2)


scale = ManualParameter("scale", initial_value=2)
iq = SingleIQPair(scale_param=scale)

# simple get
print("simple get:", iq())

simple get: (2, 1.0)

class IQArray(MultiParameter):
    def __init__(self, scale_param):
        # names, labels, and units are the same
        super().__init__(
            "iq_array",
            names=("I", "Q"),
            shapes=((5,), (5,)),
            labels=("In phase amplitude", "Quadrature amplitude"),
            units=("V", "V"),
            # note that EACH item needs a sequence of setpoint arrays
            # so a 1D item has its setpoints wrapped in a length-1 tuple
            setpoints=(((0, 1, 2, 3, 4),), ((0, 1, 2, 3, 4),)),
            docstring="param that returns two single values, I and Q",
        )
        self._scale_param = scale_param
        self._indices = np.array([0, 1, 2, 3, 4])

    def get_raw(self):
        scale_val = self._scale_param()
        return (self._indices * scale_val, self._indices * scale_val / 2)


iq_array = IQArray(scale_param=scale)

# simple get
print("simple get", iq_array())

simple get (array([0, 2, 4, 6, 8]), array([0., 1., 2., 3., 4.]))