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How to use _default_to_regular method in molecule

Best Python code snippet using molecule_python

collections.py

Source:collections.py

...553        >>> expected = {'a': {'b': {'c': {True: None}}}, 'd': {'e': {'f': {True: None}}}}554        >>> trie.as_dict() == expected555        True556        """557        def _default_to_regular(d):558            """559            Source: http://stackoverflow.com/a/26496899/4760801560            :param d: Nested ``defaultdict`` to convert to regular ``dict``561            :type d: defaultdict(str -> defaultdict(...))562            :return: A dict representation of the defaultdict563            :rtype: dict(str -> dict(str -> ...))564            :Example:565            >>> from collections import defaultdict566            >>> d = defaultdict(defaultdict)567            >>> d["one"]["two"] = "three"568            >>> d569            defaultdict(<type 'collections.defaultdict'>, {'one': defaultdict(None, {'two': 'three'})})570            >>> _default_to_regular(d)571            {'one': {'two': 'three'}}572            """573            if isinstance(d, defaultdict):574                d = {k: _default_to_regular(v) for k, v in d.items()}575            return d...

_util.py

Source:_util.py

...236                # intent, doesn't mean the intent should be denied as well.237            # sync up domain-intent238            if intents and all(intent.mask_state == MaskState.deny for intent in intents):239                domain.mask_state = MaskState.deny240    def _default_to_regular(self, d):241        if isinstance(d, defaultdict):242            d = {k: self._default_to_regular(v) for k, v in d.items()}243        return d244    def to_dict(self) -> dict:245        """246        This function serializes TreeNlp into a dict structure by only adding keys representing247        allow MaskState nodes and not adding keys for deny and unset MaskState nodes.248        """249        self._sync_nodes()250        # The results has three nested dicts: {domain: {intent: {entity: role: {}}}}251        result = defaultdict(lambda: defaultdict(lambda: defaultdict(dict)))252        for domain in self.get_domain_nodes():253            if domain.mask_state:254                result[domain.nlp_name] = defaultdict(lambda: defaultdict(dict))255            for intent in self.get_intent_nodes(domain.nlp_name):256                if intent.mask_state:257                    result[domain.nlp_name][intent.nlp_name] = defaultdict(dict)258                for entity in self.get_entity_nodes(domain.nlp_name,259                                                    intent.nlp_name):260                    if entity.mask_state:261                        result[domain.nlp_name][intent.nlp_name][entity.nlp_name] = {}262                    for role in self.get_role_nodes(domain.nlp_name,263                                                    intent.nlp_name,264                                                    entity.nlp_name):265                        if role.mask_state:266                            result[domain.nlp_name][intent.nlp_name][267                                entity.nlp_name][role.nlp_name] = {}268        serialize_results = self._default_to_regular(result)...

samples.py

Source:samples.py

...33        return {34            _GLOBAL: defaultdict(new_qty_dict),35            _LOCAL: defaultdict(new_qdict),36        }37def _default_to_regular(d: dict | defaultdict) -> dict:38    """Helper function to convert defaultdicts to regular dicts."""39    if isinstance(d, dict):40        d = {k: _default_to_regular(v) for k, v in d.items()}41    return d42@dataclass43class _TargetSlot:44    """Auxiliary class to store target information.45    Recopy of the sequence._TimeSlot but without the unrelevant `type` field,46    unrelevant at the sample level.47    NOTE: While it store targets, targets themselves are insufficient to48    conclude on the addressing of the samples. Additional info is needed:49    compare against a known register or the original sequence information.50    """51    ti: int52    tf: int53    targets: set[QubitId]54@dataclass55class _SlmMask:56    """Auxiliary class to store the SLM mask configuration."""57    targets: set[QubitId] = field(default_factory=set)58    end: int = 059@dataclass60class ChannelSamples:61    """Gathers samples of a channel."""62    amp: np.ndarray63    det: np.ndarray64    phase: np.ndarray65    slots: list[_TargetSlot] = field(default_factory=list)66    def __post_init__(self) -> None:67        assert len(self.amp) == len(self.det) == len(self.phase)68        self.duration = len(self.amp)69        for t in self.slots:70            assert t.ti < t.tf  # well ordered slots71        for t1, t2 in zip(self.slots, self.slots[1:]):72            assert t1.tf <= t2.ti  # no overlaps on a given channel73    def extend_duration(self, new_duration: int) -> ChannelSamples:74        """Extends the duration of the samples.75        Pads the amplitude and detuning samples with zeros and the phase with76        its last value (or zero if empty).77        Args:78            new_duration: The new duration for the samples (in ns).79                Must be greater than or equal to the current duration.80        Returns:81            The extended channel samples.82        """83        extension = new_duration - self.duration84        if extension < 0:85            raise ValueError("Can't extend samples to a lower duration.")86        new_amp = np.pad(self.amp, (0, extension))87        new_detuning = np.pad(self.det, (0, extension))88        new_phase = np.pad(89            self.phase,90            (0, extension),91            mode="edge" if self.phase.size > 0 else "constant",92        )93        return ChannelSamples(new_amp, new_detuning, new_phase, self.slots)94    def is_empty(self) -> bool:95        """Whether the channel is effectively empty.96        The channel is considered empty if all amplitude and detuning97        samples are zero.98        """99        return np.count_nonzero(self.amp) + np.count_nonzero(self.det) == 0100    def modulate(101        self, channel_obj: Channel, max_duration: Optional[int] = None102    ) -> ChannelSamples:103        """Modulates the samples for a given channel.104        It assumes that the phase starts at its initial value and is kept at105        its final value. The same could potentially be done for the detuning,106        but it's not as safe of an assumption so it's not done for now.107        Args:108            channel_obj: The channel object for which to modulate the samples.109            max_duration: The maximum duration of the modulation samples. If110                defined, truncates them to have a duration less than or equal111                to the given value.112        Returns:113            The modulated channel samples.114        """115        times = slice(0, max_duration)116        new_amp = channel_obj.modulate(self.amp)[times]117        new_detuning = channel_obj.modulate(self.det)[times]118        new_phase = channel_obj.modulate(self.phase, keep_ends=True)[times]119        return ChannelSamples(new_amp, new_detuning, new_phase, self.slots)120@dataclass121class SequenceSamples:122    """Gather samples for each channel in a sequence."""123    channels: list[str]124    samples_list: list[ChannelSamples]125    _ch_objs: dict[str, Channel]126    _slm_mask: _SlmMask = field(default_factory=_SlmMask)127    @property128    def channel_samples(self) -> dict[str, ChannelSamples]:129        """Mapping between the channel name and its samples."""130        return dict(zip(self.channels, self.samples_list))131    @property132    def max_duration(self) -> int:133        """The maximum duration among the channel samples."""134        return max(samples.duration for samples in self.samples_list)135    def used_bases(self) -> set[str]:136        """The bases with non-zero pulses."""137        return {138            ch_obj.basis139            for ch_obj, ch_samples in zip(140                self._ch_objs.values(), self.samples_list141            )142            if not ch_samples.is_empty()143        }144    def to_nested_dict(self, all_local: bool = False) -> dict:145        """Format in the nested dictionary form.146        This is the format expected by `pulser_simulation.Simulation()`.147        Args:148            all_local: Forces all samples to be distributed by their149                individual targets, even when applied by a global channel.150        Returns:151            A nested dictionary splitting the samples according to their152            addressing ('Global' or 'Local'), the targeted basis153            and, in the 'Local' case, the targeted qubit.154        """155        bases = {ch_obj.basis for ch_obj in self._ch_objs.values()}156        in_xy = False157        if "XY" in bases:158            assert bases == {"XY"}159            in_xy = True160        d = _prepare_dict(self.max_duration, in_xy=in_xy)161        for chname, samples in zip(self.channels, self.samples_list):162            cs = (163                samples.extend_duration(self.max_duration)164                if samples.duration != self.max_duration165                else samples166            )167            addr = self._ch_objs[chname].addressing168            basis = self._ch_objs[chname].basis169            if addr == _GLOBAL and not all_local:170                start_t = self._slm_mask.end171                d[_GLOBAL][basis][_AMP][start_t:] += cs.amp[start_t:]172                d[_GLOBAL][basis][_DET][start_t:] += cs.det[start_t:]173                d[_GLOBAL][basis][_PHASE][start_t:] += cs.phase[start_t:]174                if start_t == 0:175                    # Prevents lines below from running unnecessarily176                    continue177                unmasked_targets = cs.slots[0].targets - self._slm_mask.targets178                for t in unmasked_targets:179                    d[_LOCAL][basis][t][_AMP][:start_t] += cs.amp[:start_t]180                    d[_LOCAL][basis][t][_DET][:start_t] += cs.det[:start_t]181                    d[_LOCAL][basis][t][_PHASE][:start_t] += cs.phase[:start_t]182            else:183                for s in cs.slots:184                    for t in s.targets:185                        ti = s.ti186                        if t in self._slm_mask.targets:187                            ti = max(ti, self._slm_mask.end)188                        times = slice(ti, s.tf)189                        d[_LOCAL][basis][t][_AMP][times] += cs.amp[times]190                        d[_LOCAL][basis][t][_DET][times] += cs.det[times]191                        d[_LOCAL][basis][t][_PHASE][times] += cs.phase[times]192        return _default_to_regular(d)193    def __repr__(self) -> str:194        blocks = [195            f"{chname}:\n{cs!r}"196            for chname, cs in zip(self.channels, self.samples_list)197        ]...

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