5820074586

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enable a unit test of qubit-wise grouping (#10598) (#10599)

(cherry picked from commit 45e6f7fb4)

Co-authored-by: Takashi Imamichi <31178928+t-imamichi@users.noreply.github.com>

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93.75

/qiskit/pulse/library/waveform.py

# This code is part of Qiskit.
#
# (C) Copyright IBM 2020.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#
# Any modifications or derivative works of this code must retain this
# copyright notice, and modified files need to carry a notice indicating
# that they have been altered from the originals.

"""A pulse that is described by complex-valued sample points."""
from typing import Dict, List, Optional, Union, Any

import numpy as np

from qiskit.pulse.exceptions import PulseError
from qiskit.pulse.library.pulse import Pulse


class Waveform(Pulse):
    """A pulse specified completely by complex-valued samples; each sample is played for the
    duration of the backend cycle-time, dt.
    """

    def __init__(
        self,
        samples: Union[np.ndarray, List[complex]],
        name: Optional[str] = None,
        epsilon: float = 1e-7,
        limit_amplitude: Optional[bool] = None,
    ):
        """Create new sample pulse command.

        Args:
            samples: Complex array of the samples in the pulse envelope.
            name: Unique name to identify the pulse.
            epsilon: Pulse sample norm tolerance for clipping.
                If any sample's norm exceeds unity by less than or equal to epsilon
                it will be clipped to unit norm. If the sample
                norm is greater than 1+epsilon an error will be raised.
            limit_amplitude: Passed to parent Pulse
        """

        super().__init__(duration=len(samples), name=name, limit_amplitude=limit_amplitude)
        samples = np.asarray(samples, dtype=np.complex_)
        self.epsilon = epsilon
        self._samples = self._clip(samples, epsilon=epsilon)

    @property
    def samples(self) -> np.ndarray:
        """Return sample values."""
        return self._samples

    def _clip(self, samples: np.ndarray, epsilon: float = 1e-7) -> np.ndarray:
        """If samples are within epsilon of unit norm, clip sample by reducing norm by (1-epsilon).

        If difference is greater than epsilon error is raised.

        Args:
            samples: Complex array of the samples in the pulse envelope.
            epsilon: Pulse sample norm tolerance for clipping.
                If any sample's norm exceeds unity by less than or equal to epsilon
                it will be clipped to unit norm. If the sample
                norm is greater than 1+epsilon an error will be raised.

        Returns:
            Clipped pulse samples.

        Raises:
            PulseError: If there exists a pulse sample with a norm greater than 1+epsilon.
        """
        samples_norm = np.abs(samples)
        to_clip = (samples_norm > 1.0) & (samples_norm <= 1.0 + epsilon)

        if np.any(to_clip):
            # first try normalizing by the abs value
            clip_where = np.argwhere(to_clip)
            clip_angle = np.angle(samples[clip_where])
            clipped_samples = np.exp(1j * clip_angle, dtype=np.complex_)

            # if norm still exceed one subtract epsilon
            # required for some platforms
            clipped_sample_norms = np.abs(clipped_samples)
            to_clip_epsilon = clipped_sample_norms > 1.0
            if np.any(to_clip_epsilon):
                clip_where_epsilon = np.argwhere(to_clip_epsilon)
                clipped_samples_epsilon = (1 - epsilon) * np.exp(
                    1j * clip_angle[clip_where_epsilon], dtype=np.complex_
                )
                clipped_samples[clip_where_epsilon] = clipped_samples_epsilon

            # update samples with clipped values
            samples[clip_where] = clipped_samples
            samples_norm[clip_where] = np.abs(clipped_samples)

        if np.any(samples_norm > 1.0) and self._limit_amplitude:
            amp = np.max(samples_norm)
            raise PulseError(
                f"Pulse contains sample with norm {amp} greater than 1+epsilon."
                " This can be overruled by setting Pulse.limit_amplitude."
            )

        return samples

    def is_parameterized(self) -> bool:
        """Return True iff the instruction is parameterized."""
        return False

    @property
    def parameters(self) -> Dict[str, Any]:
        """Return a dictionary containing the pulse's parameters."""
        return {}

    def __eq__(self, other: Pulse) -> bool:
        return (
            super().__eq__(other)
            and self.samples.shape == other.samples.shape
            and np.allclose(self.samples, other.samples, rtol=0, atol=self.epsilon)
        )

    def __hash__(self) -> int:
        return hash(self.samples.tobytes())

    def __repr__(self) -> str:
        opt = np.get_printoptions()
        np.set_printoptions(threshold=50)
        np.set_printoptions(**opt)
        return "{}({}{})".format(
            self.__class__.__name__,
            repr(self.samples),
            f", name='{self.name}'" if self.name is not None else "",
        )

1	# This code is part of Qiskit.
2	#
3	# (C) Copyright IBM 2020.
4	#
5	# This code is licensed under the Apache License, Version 2.0. You may
6	# obtain a copy of this license in the LICENSE.txt file in the root directory
7	# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
8	#
9	# Any modifications or derivative works of this code must retain this
10	# copyright notice, and modified files need to carry a notice indicating
11	# that they have been altered from the originals.
12
13	"""A pulse that is described by complex-valued sample points."""	1✔
14	from typing import Dict, List, Optional, Union, Any	1✔
15
16	import numpy as np	1✔
17
18	from qiskit.pulse.exceptions import PulseError	1✔
19	from qiskit.pulse.library.pulse import Pulse	1✔
20
21
22	class Waveform(Pulse):	1✔
23	"""A pulse specified completely by complex-valued samples; each sample is played for the	1✔
24	duration of the backend cycle-time, dt.
25	"""
26
27	def __init__(	1✔
28	self,
29	samples: Union[np.ndarray, List[complex]],
30	name: Optional[str] = None,
31	epsilon: float = 1e-7,
32	limit_amplitude: Optional[bool] = None,
33	):
34	"""Create new sample pulse command.
35
36	Args:
37	samples: Complex array of the samples in the pulse envelope.
38	name: Unique name to identify the pulse.
39	epsilon: Pulse sample norm tolerance for clipping.
40	If any sample's norm exceeds unity by less than or equal to epsilon
41	it will be clipped to unit norm. If the sample
42	norm is greater than 1+epsilon an error will be raised.
43	limit_amplitude: Passed to parent Pulse
44	"""
45
46	super().__init__(duration=len(samples), name=name, limit_amplitude=limit_amplitude)	1✔
47	samples = np.asarray(samples, dtype=np.complex_)	1✔
48	self.epsilon = epsilon	1✔
49	self._samples = self._clip(samples, epsilon=epsilon)	1✔
50
51	@property	1✔
52	def samples(self) -> np.ndarray:	1✔
53	"""Return sample values."""
54	return self._samples	1✔
55
56	def _clip(self, samples: np.ndarray, epsilon: float = 1e-7) -> np.ndarray:	1✔
57	"""If samples are within epsilon of unit norm, clip sample by reducing norm by (1-epsilon).
58
59	If difference is greater than epsilon error is raised.
60
61	Args:
62	samples: Complex array of the samples in the pulse envelope.
63	epsilon: Pulse sample norm tolerance for clipping.
64	If any sample's norm exceeds unity by less than or equal to epsilon
65	it will be clipped to unit norm. If the sample
66	norm is greater than 1+epsilon an error will be raised.
67
68	Returns:
69	Clipped pulse samples.
70
71	Raises:
72	PulseError: If there exists a pulse sample with a norm greater than 1+epsilon.
73	"""
74	samples_norm = np.abs(samples)	1✔
75	to_clip = (samples_norm > 1.0) & (samples_norm <= 1.0 + epsilon)	1✔
76
77	if np.any(to_clip):	1✔
78	# first try normalizing by the abs value
79	clip_where = np.argwhere(to_clip)	1✔
80	clip_angle = np.angle(samples[clip_where])	1✔
81	clipped_samples = np.exp(1j * clip_angle, dtype=np.complex_)	1✔
82
83	# if norm still exceed one subtract epsilon
84	# required for some platforms
85	clipped_sample_norms = np.abs(clipped_samples)	1✔
86	to_clip_epsilon = clipped_sample_norms > 1.0	1✔
87	if np.any(to_clip_epsilon):	1✔
88	clip_where_epsilon = np.argwhere(to_clip_epsilon)	×
89	clipped_samples_epsilon = (1 - epsilon) * np.exp(	×
90	1j * clip_angle[clip_where_epsilon], dtype=np.complex_
91	)
92	clipped_samples[clip_where_epsilon] = clipped_samples_epsilon	×
93
94	# update samples with clipped values
95	samples[clip_where] = clipped_samples	1✔
96	samples_norm[clip_where] = np.abs(clipped_samples)	1✔
97
98	if np.any(samples_norm > 1.0) and self._limit_amplitude:	1✔
99	amp = np.max(samples_norm)	1✔
100	raise PulseError(	1✔
101	f"Pulse contains sample with norm {amp} greater than 1+epsilon."
102	" This can be overruled by setting Pulse.limit_amplitude."
103	)
104
105	return samples	1✔
106
107	def is_parameterized(self) -> bool:	1✔
108	"""Return True iff the instruction is parameterized."""
109	return False	1✔
110
111	@property	1✔
112	def parameters(self) -> Dict[str, Any]:	1✔
113	"""Return a dictionary containing the pulse's parameters."""
114	return {}	1✔
115
116	def __eq__(self, other: Pulse) -> bool:	1✔
117	return (	1✔
118	super().__eq__(other)
119	and self.samples.shape == other.samples.shape
120	and np.allclose(self.samples, other.samples, rtol=0, atol=self.epsilon)
121	)
122
123	def __hash__(self) -> int:	1✔
124	return hash(self.samples.tobytes())	1✔
125
126	def __repr__(self) -> str:	1✔
127	opt = np.get_printoptions()	1✔
128	np.set_printoptions(threshold=50)	1✔
129	np.set_printoptions(**opt)	1✔
130	return "{}({}{})".format(	1✔
131	self.__class__.__name__,
132	repr(self.samples),
133	f", name='{self.name}'" if self.name is not None else "",
134	)

Qiskit / qiskit-terra / 5820074586

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