"""Conditional receiver reflection-odd observation of two mediator classes. The complete shared amplitude hierarchy supplies the nominal quadratic term. A class-difference Cauchy remainder and separate actual-source allowance bound its full-law meaning. The report acquires neither a source nor a trajectory. """ from __future__ import annotations from dataclasses import dataclass from fractions import Fraction as Q from ..mathematics._rational_interval import INTERVAL_METHOD, I from ._sine_class_contrast import _contrast_decision, _ContrastDecision from .relational_sine_class_cubic_response import ( _CAUCHY_GAMMA, _LINEAR_NORM, _ORDER, _class_cubic_coefficients, _CubicParameters, _CubicSegment, _mixed_form_projection, _scale_by_shared_gamma, ) from .relational_sine_class_mediation import _CONTACTS, _EDGES, _NODES from .relational_sine_class_superposition import ( _admit_probe_primitives, _ClassProbeHistoryBound, _probe_event_ledger, ) from .relational_sine_port_composition import _parameters __all__ = ("SineClassSpatialObservation", "bound_sine_class_spatial_observation") _OBSERVATION = ((23, 1), (21, -1)) _READING_COUNT = 16 def _higher_even_contrast_remainder(amplitude, total): """One history's already cross-class, degree-four-and-higher allowance.""" if amplitude == 0: return Q(0) g = _CAUCHY_GAMMA return Q(4096, 3) * g**7 * amplitude**4 * total**3 / (1 - 4 * g**2 * amplitude**2) @dataclass(frozen=True) class SineClassSpatialObservation: """A conditional sixteen-reading spatial contrast, with complete errors. Each history reads x23 and x21 independently with the supplied per-node error. Its four-history mixed difference is then compared between classes. Actual source residuals can break nominal reflection symmetry. One uniform work/identity ledger applies per class; it does not equate their sources. """ first_probe_amplitude: Q second_probe_amplitude: Q delay: Q total_duration: Q endpoint_radius: Q readout_error_bound: Q radius: Q contact_work_allowance: Q first_probe_work_allowance: Q second_probe_work_allowance: Q gamma_bounds: I cauchy_bootstrap_margin: Q cauchy_radius_margin: Q cauchy_admitted: bool coefficient_evaluated: bool class_parameters: tuple[_CubicParameters, ...] class_segments: tuple[tuple[_CubicSegment, ...], ...] scaled_class_quadratic_bounds: tuple[tuple[Q, Q], ...] | None complete_quadratic_contrast_bounds: tuple[Q, Q] | None per_history_higher_amplitude_contrast_remainder_upper_bounds: tuple[Q, ...] | None higher_amplitude_contrast_error_upper_bound: Q | None source_contrast_error_upper_bound: Q decision: _ContrastDecision | None response_bound_available: bool exact_contrast_zero: bool uniform_history_bounds: tuple[_ClassProbeHistoryBound, ...] joined_initial_identity_certified: bool contact_work_within_allowance: bool all_identities_certified: bool all_work_within_allowances: bool status: str unavailable_reasons: tuple[str, ...] compared_classes: tuple[tuple[int, ...], ...] = ((1, 1, 1), (1, 2, 1)) nodes: tuple[int, ...] = _NODES edges: tuple[tuple[int, int], ...] = _EDGES contacts: tuple[tuple[int, int], ...] = _CONTACTS observation_node_weights: tuple[tuple[int, int], ...] = _OBSERVATION reading_count: int = _READING_COUNT coefficient_amplitude_degree: int = 2 coefficient_scale_gamma_power: int = 3 time_polynomial_order: int = _ORDER linear_majorant_rate: Q = _LINEAR_NORM cauchy_gamma_upper_bound: Q = _CAUCHY_GAMMA clock: str = "tau=e*t; e=1023/1024" method: str = ( "receiver_odd_quadratic_projection_of_complete_amplitude_time_polynomial64_v1" ) interval_method: str = INTERVAL_METHOD scope: tuple[str, ...] = ( "two_independent_nodal_readings_per_history_not_a_direct_difference_sensor", "x23_minus_x21_then_both_minus_first_minus_second_plus_neither_then_class1_minus_class2", "full54_coordinates_and_all_carried_amplitude_levels_are_retained", "nominal_reflection_odd_projection_is_even_in_the_common_amplitude_parameter", "receiver_quadratic_term_alone_does_not_imply_mediator_sensitivity", "class_difference_is_formed_before_shared_gamma_cubed_enclosure", "each_higher_amplitude_remainder_already_bounds_the_cross_class_difference", "arbitrary_actual_source_errors_are_not_cancelled_by_nominal_parity", "sixteen_independent_reading_errors_and_thirty_two_for_a_separately_noisy_null", "scalar_cancellation_does_not_imply_full_record_vector_overlap", "source_acquisition_identity_work_and_physical_identification_are_separate", "shared_full_coordinate_coefficients_can_be_prior_information_not_unseen_evidence", ) def to_dict(self): from ..sdk.relational_reports import _project return { "schema": "tnfr.sine-class-spatial-observation.v1", "report": _project(self), } def bound_sine_class_spatial_observation( *, first_probe_amplitude, second_probe_amplitude, delay, total_duration, endpoint_radius, readout_error_bound, radius, contact_work_allowance, first_probe_work_allowance, second_probe_work_allowance, ) -> SineClassSpatialObservation: """Bound the receiver spatial statistic from ten freshly admitted primitives. Signed amplitudes, 0<=delay<=total_duration<=2 and 0 0 and radius_margin > 0 exact_zero = a == 0 or b == 0 or s == t parameters, segments = [], [] class_bounds = contrast = remainders = higher_error = decision = None source_error = 16 * eps / (1 - 2 * gamma.hi * t) if exact_zero: class_bounds = ((Q(0), Q(0)),) * 2 contrast = (Q(0), Q(0)) decision = _contrast_decision( contrast, Q(0), delta, exact_zero=True, reading_count=_READING_COUNT ) elif admitted: coefficients = [] for mediator_class in (1, 2): params, history, _ = _class_cubic_coefficients(mediator_class, a, b, s, t) parameters.append(params) segments.append(history) coefficients.append(_mixed_form_projection(history, 1, _OBSERVATION)) class_bounds = tuple( _scale_by_shared_gamma(value, gamma, 3) for value in coefficients ) contrast = _scale_by_shared_gamma(coefficients[0] - coefficients[1], gamma, 3) remainders = tuple( _higher_even_contrast_remainder(value, t) for value in (Q(0), abs(a), abs(b), amplitude) ) higher_error = sum(remainders, Q(0)) decision = _contrast_decision( contrast, higher_error + source_error, delta, reading_count=_READING_COUNT ) ledger = _probe_event_ledger(values, gamma.hi, (None,) * 4) return SineClassSpatialObservation( **values, gamma_bounds=gamma, cauchy_bootstrap_margin=bootstrap, cauchy_radius_margin=radius_margin, cauchy_admitted=admitted, coefficient_evaluated=bool(segments), class_parameters=tuple(parameters), class_segments=tuple(segments), scaled_class_quadratic_bounds=class_bounds, complete_quadratic_contrast_bounds=contrast, per_history_higher_amplitude_contrast_remainder_upper_bounds=remainders, higher_amplitude_contrast_error_upper_bound=higher_error, source_contrast_error_upper_bound=source_error, decision=decision, response_bound_available=decision is not None, exact_contrast_zero=exact_zero, uniform_history_bounds=ledger.histories, joined_initial_identity_certified=ledger.initial_identity, contact_work_within_allowance=ledger.contact_allowed, all_identities_certified=all(h.identity_certified for h in ledger.histories), all_work_within_allowances=all( h.work_within_allowances for h in ledger.histories ), status=decision.status if decision is not None else "unavailable", unavailable_reasons=( () if decision is not None else ("complex_amplitude_domain_not_admitted",) ), )