Files
radar_system/python_app/gui/runtime/history.py
T
Ayzen d283ecfdf1 keep sweeps in acquisition order through history replays
The processor appended sweeps the GUI fed back to its own history, so its next replay
published them twice and out of order, and the B-scan came out with rotated columns.
Fed-back sweeps now stay out of that history, results are kept in timestamp order,
picking the displayed combo only redraws and only new sweeps are recorded to disk.
2026-10-02 16:05:32 +03:00

159 lines
6.7 KiB
Python

"""Helpers for GUI-side runtime history management."""
from __future__ import annotations
from collections import deque
from typing import TypeVar
from python_app.models.dataset_model import ResultCollection, SweepCollection
from python_app.models.run_config_model import RunConfigModel
from python_app.orchestration.preprocess_assets import PREPROCESS_ASSET_KEYS, preprocess_asset_model
THistoryCollection = TypeVar("THistoryCollection", SweepCollection, ResultCollection)
def collection_key(collection: SweepCollection | ResultCollection) -> tuple[int, int]:
"""Identity of a sweep through the pipeline: its result keeps the same id and timestamp.
`monotonic_ns` is stamped by `data_preprocessor` on the system monotonic clock, so
it also orders sweeps by acquisition, across runs too (ids restart from 1).
"""
return int(collection.collection_id), int(collection.monotonic_ns)
def record_result_history(
result_history: deque[ResultCollection],
collection: ResultCollection,
) -> bool:
"""Record a result, keeping the history in acquisition order; return whether it is new.
A result of a sweep already present replaces it (the sweep was reprocessed).
Any other result goes after the newest older one: normally at the end, as the
result of a new sweep, but the processor reprocessing its retained sweeps also
delivers sweeps whose first result the GUI missed, and appending those would
show them out of order.
"""
key = collection_key(collection)
position = len(result_history)
while position > 0:
existing = result_history[position - 1]
if collection_key(existing) == key:
result_history[position - 1] = collection
return False
if existing.monotonic_ns < collection.monotonic_ns:
break
position -= 1
if position == len(result_history):
result_history.append(collection)
return True
if len(result_history) == result_history.maxlen:
if position == 0:
return False # older than everything kept, so it would be the first to go
result_history.popleft()
position -= 1
result_history.insert(position, collection)
return False
def remove_last_aligned_histories(
raw_history: list[SweepCollection],
preprocessed_history: list[SweepCollection],
result_history: list[ResultCollection],
) -> tuple[list[SweepCollection], list[SweepCollection], list[ResultCollection]]:
"""Remove the newest aligned history entry using results as preferred anchor."""
retained_raw = list(raw_history)
retained_preprocessed = list(preprocessed_history)
retained_results = list(result_history)
if retained_results:
target_key = _tail_occurrence_key(retained_results, len(retained_results) - 1)
retained_results.pop()
_remove_by_tail_occurrence_key(retained_raw, target_key)
_remove_by_tail_occurrence_key(retained_preprocessed, target_key)
return retained_raw, retained_preprocessed, retained_results
if retained_preprocessed:
target_key = _tail_occurrence_key(retained_preprocessed, len(retained_preprocessed) - 1)
retained_preprocessed.pop()
_remove_by_tail_occurrence_key(retained_raw, target_key)
return retained_raw, retained_preprocessed, retained_results
if retained_raw:
retained_raw.pop()
return retained_raw, retained_preprocessed, retained_results
def build_processor_run_signature(
config: RunConfigModel,
) -> tuple[object, ...]:
"""Build signature of settings that change the data SHAPE the data_processor parses.
Excludes the preprocess set names on purpose: the data_processor does not consume
calibration/reference sets (those are applied upstream by the data_preprocessor), so
changing a set must NOT restart the processor. Restarting it would also tear down the
locator TCP server it hosts and drop every connected client. Only genuine shape changes
(radar model, sweep, switch layout, combos) require a processor restart.
"""
combos_signature = tuple((int(combo.input), int(combo.output)) for combo in config.combos)
sweep_points_signature: object = "adc" if config.is_kamil_adc else int(config.radar.sweep.points)
return (
str(config.radar.model),
str(config.radar.driver_mode),
str(config.radar.serial),
tuple(str(value) for value in config.radar.multi_device.slave_serials),
bool(config.radar.multi_device.force_external_reference),
float(config.radar.sweep.start_hz),
float(config.radar.sweep.stop_hz),
sweep_points_signature,
float(config.radar.sweep.if_bandwidth_hz),
float(config.radar.sweep.power_dbm),
str(config.input_switch.driver_mode),
str(config.input_switch.driver),
int(config.input_switch.positions),
bool(config.input_switch.invert_logic),
str(config.output_switch.driver_mode),
str(config.output_switch.driver),
int(config.output_switch.positions),
bool(config.output_switch.invert_logic),
combos_signature,
)
def build_run_history_signature(
config: RunConfigModel,
) -> tuple[object, ...]:
"""Build full signature for GUI display-history reset (processor shape + preprocess sets).
Display history still resets when the reference/calibration set changes (the on-screen
B-scan would otherwise mix old- and new-reference frames), even though the processor
process itself is intentionally kept alive across that change.
"""
preprocess_signature = tuple(preprocess_asset_model(config, key).set_name for key in PREPROCESS_ASSET_KEYS)
return build_processor_run_signature(config) + (preprocess_signature,)
def _tail_occurrence_key(history: list[THistoryCollection], index: int) -> tuple[int, int]:
"""Return `(collection_id, occurrence_from_tail)` for the item at `index`."""
collection_id = int(history[index].collection_id)
occurrence_from_tail = 0
for cursor in range(len(history) - 1, index, -1):
if int(history[cursor].collection_id) == collection_id:
occurrence_from_tail += 1
return collection_id, occurrence_from_tail
def _remove_by_tail_occurrence_key(history: list[THistoryCollection], key: tuple[int, int]) -> bool:
"""Remove newest matching entry identified by `(collection_id, occurrence_from_tail)`."""
collection_id, target_occurrence = key
occurrence_from_tail = 0
for index in range(len(history) - 1, -1, -1):
if int(history[index].collection_id) != collection_id:
continue
if occurrence_from_tail == target_occurrence:
history.pop(index)
return True
occurrence_from_tail += 1
return False