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fix backend issues

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This commit is contained in:
ykcheungab
2026-09-13 17:51:14 +08:00
parent 73592f085f
commit 0f4552cd4e
7 changed files with 190 additions and 195 deletions
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apps/studio/config/compound_eye.png
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apps/studio/src/orisys_studio/recording.py
+1
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@@ -199,6 +199,7 @@ class RecordingCoordinator:
"""Start a recording. Raises when the directory cannot be created."""
directory = self.recorder.start(
root=root,
config=config,
session_id=int(self.session_store.session_id),
metadata=metadata,
calibration_id=calibration_id,
shared/src/orisys_app_shared/force/source.py
+1 -1
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@@ -63,7 +63,7 @@ class SourceWindow:
means.append(NA)
stds.append(NA)
continue
peaks.append(float(np.nanmax(column)))
peaks.append(float(column[np.argmax(np.abs(column))]))
means.append(float(np.nanmean(column)))
stds.append(float(np.nanstd(column)))
span = float(self.times[-1] - self.times[0]) if self.times.size > 1 else 0.0
shared/src/orisys_app_shared/record/depth.py
+23 -15
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@@ -186,9 +186,8 @@ class DepthRecomputer:
still produced, and the caller is told it may differ from live).
Finding a reset event is **not** by itself a recovered state: the reset
frame has to exist in the index *and* in the video, and it has to be in
the same segment, because the SDK cannot carry its state across a segment
boundary.
frame has to exist in the index *and* in the video. Every intervening
segment must be read with the same processor to preserve its state.
"""
warnings: list[str] = []
segment_path = self.reader.segment_path(frame.segment)
@@ -205,6 +204,12 @@ class DepthRecomputer:
# The boundary frame is not in the video, so the state at that
# point cannot be rebuilt: replay from here is an approximation.
warnings.append("reset_frame_not_in_video")
elif any(
entry.dropped or not entry.in_video
for entry in self.reader.info().frames
if origin.frame_id <= entry.frame_id <= frame.frame_id
):
warnings.append("state_missing_frames")
elif origin.segment == frame.segment:
plan = ReplayPlan(
segment=segment_path,
@@ -228,21 +233,24 @@ class DepthRecomputer:
# The reset is in an earlier segment. The processor survives a
# source swap, so the state *can* be carried: read the tail of
# the reset's segment, then continue in the target's.
reset_segment = self.reader.segment_path(origin.segment)
last_of_reset_segment = self._last_segment_frame(origin.segment)
if reset_segment is None or last_of_reset_segment is None:
steps = []
for segment in range(int(origin.segment), int(frame.segment) + 1):
source = self.reader.segment_path(segment)
last = stop_at if segment == frame.segment else self._last_segment_frame(segment)
if source is None or not source.is_file() or last is None:
steps = []
break
steps.append(ReplayStep(
source=source,
to_frame=int(last),
reset_after=int(origin.segment_frame) if segment == origin.segment else None,
))
if not steps:
warnings.append("state_across_segment")
else:
plan = ReplayPlan(
segment=segment_path,
steps=(
ReplayStep(
source=reset_segment,
to_frame=int(last_of_reset_segment),
reset_after=int(origin.segment_frame),
),
ReplayStep(source=segment_path, to_frame=stop_at),
),
steps=tuple(steps),
stop_at=stop_at,
reset_frame_id=int(reset_frame),
anchor="reset",
@@ -405,7 +413,7 @@ class DepthRecomputer:
while self._position < target:
depth = self._read_one()
if depth is None:
break
raise RuntimeError(f"replay source ended before frame {target}: {step.source}")
last = depth
if step.reset_after is not None and self._position == int(step.reset_after):
# The operator's zeroing: the live run cleared the tracker here.
shared/src/orisys_app_shared/record/experiment.py
+8 -3
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@@ -32,7 +32,8 @@ import queue
import threading
import time
from collections import deque
from dataclasses import dataclass, field
from dataclasses import dataclass, field, replace
from uuid import uuid4
from datetime import datetime, timezone
from pathlib import Path
from typing import Any, Optional
@@ -308,6 +309,7 @@ class ExperimentRecorder:
root: Path,
session_id: int,
metadata: dict[str, Any],
config: Optional[RecordConfig] = None,
calibration_id: str = "",
calibration_version: str = "",
preroll=(),
@@ -325,10 +327,13 @@ class ExperimentRecorder:
f"cannot start recording from state {self._state!r}"
)
self._state = STATE_STARTING
# A running writer owns its configuration. Copy only after the
# lifecycle checks, so caller mutations cannot change this run.
self.config = replace(config if config is not None else self.config)
stamp = datetime.now(timezone.utc).strftime("%Y%m%dT%H%M%SZ")
directory = Path(root) / f"{stamp}_session{session_id:04d}"
directory = Path(root) / f"{stamp}_session{session_id:04d}_{uuid4().hex}"
try:
directory.mkdir(parents=True, exist_ok=True)
directory.mkdir(parents=True, exist_ok=False)
except Exception as exc: # noqa: BLE001 - reported to the caller
# A directory that cannot be created is a *terminal* failure, not a
# stuck ``starting``: the operator can fix the path and press record
shared/src/orisys_app_shared/record/index.py
+146 -104
View File
@@ -11,15 +11,15 @@ the interval being drawn. It also builds a multi-level overview (per-bucket
min/max/count) while streaming the file once, which is what a whole-session strip
needs and what it cannot get by sampling a few thousand rows.
Nothing here touches Qt, and nothing here trusts the file to be in order: a
legacy recording is sorted at load time (see ``playback.RecordingReader``).
Nothing here touches Qt. Unordered recordings keep a stable time-to-byte-offset
mapping, shared by all interval reads and statistics.
"""
from __future__ import annotations
import csv
import logging
from bisect import bisect_left, bisect_right
from array import array
from dataclasses import dataclass, field
from pathlib import Path
from typing import Iterable, Iterator, Optional
@@ -95,7 +95,7 @@ class ForceWindow:
means.append(float("nan"))
stds.append(float("nan"))
continue
peaks.append(float(np.nanmax(column)))
peaks.append(float(column[np.argmax(np.abs(column))]))
means.append(float(np.nanmean(column)))
stds.append(float(np.nanstd(column)))
span = 0.0
@@ -153,6 +153,10 @@ class RecordingIndex:
self._rows = 0
self._byte_size = 0
self._built = False
self._offsets = None # Only unordered files need one byte offset per row.
self._columns = {}
self.ordered = True
self.dropped_rows = 0
# ------------------------------------------------------------------ building
@property
@@ -175,35 +179,43 @@ class RecordingIndex:
valid: list[bool] = []
frame_ids: list[int] = []
checkpoints: list[_Checkpoint] = []
offsets = array("Q")
self.dropped_rows = 0
if path.is_file():
with path.open("rb") as handle:
header = handle.readline().decode("utf-8", "replace").strip()
columns = {name: index for index, name in enumerate(header.split(","))}
time_column = columns.get("t_rel_s", 2)
valid_column = columns.get("valid", 9)
frame_column = columns.get("frame_id", 1)
self._columns = columns
offset = handle.tell()
for row, line in enumerate(handle):
next_offset = handle.tell()
text = line.decode("utf-8", "replace").rstrip("\r\n")
if row % self.checkpoint_rows == 0:
record = self._parse_row(line)
if record is None:
self.dropped_rows += 1
offset = next_offset
continue
frame_id, timestamp, _raw, _newtons, is_valid = record
logical_row = len(times)
if logical_row % self.checkpoint_rows == 0:
checkpoints.append(
_Checkpoint(row=row, time=_time_of(text), offset=offset)
_Checkpoint(row=logical_row, time=timestamp, offset=offset)
)
fields = next(csv.reader([text])) if text else []
if len(fields) > max(time_column, valid_column, frame_column):
try:
times.append(float(fields[time_column]))
valid.append(fields[valid_column].strip() == "1")
frame_ids.append(int(fields[frame_column]))
except (TypeError, ValueError):
times.append(float("nan"))
valid.append(False)
frame_ids.append(-1)
times.append(timestamp)
valid.append(is_valid)
frame_ids.append(frame_id)
offsets.append(offset)
offset = next_offset
self.times = np.asarray(times, dtype=np.float64)
self.valid = np.asarray(valid, dtype=bool)
self.frame_ids = np.asarray(frame_ids, dtype=np.int64)
self.ordered = bool(np.all(self.times[1:] >= self.times[:-1]))
self._offsets = None
if not self.ordered:
order = np.argsort(self.times, kind="stable")
self.times = self.times[order]
self.valid = self.valid[order]
self.frame_ids = self.frame_ids[order]
self._offsets = np.asarray(offsets, dtype=np.uint64)[order]
self._checkpoints = checkpoints
self._rows = int(self.times.size)
try:
@@ -213,6 +225,21 @@ class RecordingIndex:
self._built = True
return self
def _parse_row(self, line: bytes):
"""Parse atomically; malformed rows never shift one column alone."""
try:
fields = next(csv.reader([line.decode("utf-8", "replace")]))
def cell(name):
return fields[self._columns[name]]
frame_id = int(cell("frame_id"))
timestamp = float(cell("t_rel_s"))
if not np.isfinite(timestamp) or not -(2**63) <= frame_id < 2**63:
return None
values = tuple(_parse(cell(name)) for name in _FORCE_COLUMNS)
return frame_id, timestamp, values[:3], values[3:], cell("valid").strip() == "1"
except (KeyError, IndexError, ValueError, StopIteration, csv.Error):
return None
def ensure_built(self) -> "RecordingIndex":
if not self._built:
self.build()
@@ -220,6 +247,7 @@ class RecordingIndex:
# ------------------------------------------------------------------- queries
def extent(self) -> tuple[float, float]:
self.ensure_built()
if self._rows == 0:
return (0.0, 0.0)
return (float(self.times[0]), float(self.times[-1]))
@@ -235,8 +263,8 @@ class RecordingIndex:
return (0, 0)
if float(t1) < float(t0):
t0, t1 = t1, t0
start = max(0, bisect_left(self.times.tolist(), float(t0)) - 1)
stop = min(self._rows, bisect_right(self.times.tolist(), float(t1)))
start = int(self.times.searchsorted(float(t0), side="left"))
stop = int(self.times.searchsorted(float(t1), side="right"))
return (start, max(start, stop))
def _checkpoint_before(self, row: int) -> _Checkpoint:
@@ -260,9 +288,9 @@ class RecordingIndex:
With ``max_points`` the rows are decimated **while streaming**: each
bucket contributes the extreme row of every axis in ``unit``, so a long
interval never has to exist in memory in full. The extremes are taken in
both the raw and the requested unit's axis, which is why a shear spike
survives a flat normal channel.
interval never has to exist in memory in full. Extrema are taken independently on all three axes in the requested unit,
so a shear spike survives a flat normal channel. A bucket keeps at most
nine rows; budgets smaller than nine may therefore return nine points.
"""
self.ensure_built()
start = max(0, min(int(start), self._rows))
@@ -276,72 +304,54 @@ class RecordingIndex:
newton_unit = str(unit).upper().startswith("N")
budget = int(max_points) if max_points else 0
total = stop - start
bucket = (
max(1, total // max(1, budget // 6))
if budget and total > budget * 2
else 1
)
checkpoint = self._checkpoint_before(start)
pending: list[tuple] = []
# At most six extrema, two endpoints and a missing-data marker per
# bucket. No bucket holds a list proportional to the recording length.
bucket = max(1, (total + max(1, budget // 9) - 1) // max(1, budget // 9)) if budget and total > budget else 1
picked: list[tuple] = []
extrema = {}
first = last = missing = None
count = 0
def flush() -> None:
if not pending:
return
def flush():
nonlocal first, last, missing, count
chosen = {item[0]: item for item in extrema.values()}
for item in (first, last, missing):
if item is not None:
chosen[item[0]] = item
picked.extend(item[1:] for item in sorted(chosen.values(), key=lambda item: item[0]))
extrema.clear()
first = last = missing = None
count = 0
for item in self.iter_rows(start, stop):
# item: logical row, frame id, time, raw, newtons, validity.
if bucket == 1:
picked.extend(pending)
else:
values = np.asarray(
[row[3] if newton_unit else row[2] for row in pending],
dtype=np.float64,
)
for axis in range(3):
column = values[:, axis]
finite = np.isfinite(column)
if not finite.any():
picked.append(item[1:])
continue
ordered = np.where(finite, column, -np.inf)
for index in {int(np.argmin(ordered)), int(np.argmax(ordered))}:
picked.append(pending[index])
pending.clear()
with path.open("rb") as handle:
# Every checkpoint offset points at a *data* row: the build records
# ``tell()`` after the header, so there is nothing to skip here.
handle.seek(checkpoint.offset)
for row, line in enumerate(handle, start=checkpoint.row):
if row >= stop:
break
if row < start:
if first is None:
first = item
last = item
values = item[4] if newton_unit else item[3]
for axis, value in enumerate(values):
if not item[5] or not np.isfinite(value):
if missing is None:
missing = item
continue
fields = next(csv.reader([line.decode("utf-8", "replace")]))
if len(fields) < 11:
continue
try:
t_rel = float(fields[2])
frame_id = int(fields[1])
except (TypeError, ValueError):
continue
values = [_parse(fields[index]) for index in (3, 4, 5, 6, 7, 8)]
pending.append(
(
frame_id,
t_rel,
tuple(values[:3]),
tuple(values[3:]),
fields[9].strip() == "1",
)
)
if len(pending) >= bucket:
for side in ('min', 'max'):
key = (axis, side)
previous = extrema.get(key)
old = previous[4 if newton_unit else 3][axis] if previous is not None else None
if old is None or (value < old if side == 'min' else value > old):
extrema[key] = item
count += 1
if count >= bucket:
flush()
flush()
if not picked:
return _empty_window()
# A row can be the extreme of several axes; keep one copy, in time order.
unique = {row[0]: row for row in picked}
rows = sorted(unique.values(), key=lambda row: row[1])
rows = picked # Already in stable time order; duplicate frame IDs are not deduplicated.
return ForceWindow(
times=np.asarray([row[1] for row in rows], dtype=np.float64),
raw=np.asarray([row[2] for row in rows], dtype=np.float64).reshape(-1, 3),
@@ -352,35 +362,67 @@ class RecordingIndex:
)
def iter_rows(self, start: int = 0, stop: Optional[int] = None) -> Iterator[tuple]:
"""Yield ``(row, frame_id, t_rel_s, raw3, newtons3, valid)`` in file order."""
"""Yield logical rows in stable time order, seeking only the selection."""
self.ensure_built()
path = self.path
if not path.is_file():
return
start = max(0, int(start))
stop = self._rows if stop is None else min(int(stop), self._rows)
with path.open("rb") as handle:
handle.readline() # header
for row, line in enumerate(handle):
if start >= stop or not self.path.is_file():
return
with self.path.open("rb") as handle:
if self._offsets is not None:
for row in range(start, stop):
handle.seek(int(self._offsets[row]))
record = self._parse_row(handle.readline())
if record is not None:
yield (row, *record)
return
checkpoint = self._checkpoint_before(start)
handle.seek(checkpoint.offset)
row = checkpoint.row
for line in handle:
record = self._parse_row(line)
if record is None:
continue
if row >= start:
yield (row, *record)
row += 1
if row >= stop:
return
if row < start:
def statistics(self, t0: float, t1: float, *, unit: str = "raw") -> WindowStats:
"""Exact selected-row statistics with constant working memory."""
start, stop = self.row_range(t0, t1)
counts = np.zeros(3, dtype=np.int64)
means = np.zeros(3)
m2 = np.zeros(3)
peaks = np.full(3, np.nan)
samples = 0
first = last = None
newton = str(unit).upper().startswith("N")
for _, _, timestamp, raw, newtons, valid in self.iter_rows(start, stop):
if first is None:
first = timestamp
last = timestamp
if not valid:
continue
fields = next(csv.reader([line.decode("utf-8", "replace")]))
if len(fields) < 11:
continue
try:
frame_id = int(fields[1])
t_rel = float(fields[2])
except (TypeError, ValueError):
continue
values = [_parse(fields[index]) for index in (3, 4, 5, 6, 7, 8)]
yield (
row,
frame_id,
t_rel,
tuple(values[:3]),
tuple(values[3:]),
fields[9].strip() == "1",
values = np.asarray(newtons if newton else raw)
mask = np.isfinite(values)
samples += int(mask.any())
for axis in np.flatnonzero(mask):
value = values[axis]
counts[axis] += 1
delta = value - means[axis]
means[axis] += delta / counts[axis]
m2[axis] += delta * (value - means[axis])
if not np.isfinite(peaks[axis]) or abs(value) > abs(peaks[axis]):
peaks[axis] = value
available = counts > 0
stds = np.full(3, np.nan)
stds[available] = np.sqrt(np.maximum(0, m2[available] / counts[available]))
means[~available] = np.nan
return WindowStats(
duration_s=0.0 if first is None else last - first,
samples=samples, peaks=tuple(peaks), means=tuple(means), stds=tuple(stds),
)
# ------------------------------------------------------------------ overview
shared/src/orisys_app_shared/record/playback.py
+7 -68
View File
@@ -179,8 +179,8 @@ class RecordingReader:
newtons = window.newtons
valid = window.valid
frame_ids = window.frame_ids
forces_ordered = True
dropped = 0
forces_ordered = index.ordered
dropped = index.dropped_rows
else:
(times, raw, newtons, valid, frame_ids, dropped, forces_ordered) = (
self._load_forces()
@@ -244,71 +244,10 @@ class RecordingReader:
return rows, ordered
def _load_forces(self):
path = self.directory / "forces.csv"
if not path.is_file():
# A directory with no data (an empty or half-written recording) is
# readable: it simply has no samples, and nothing is out of order.
empty = np.empty(0, dtype=np.float64)
return (
empty,
np.empty((0, 3)),
np.empty((0, 3)),
np.empty(0, bool),
np.empty(0, int),
0,
True,
)
def parse(text: str) -> float:
text = (text or "").strip()
if not text:
# An empty cell means "not available"; it must never become 0.
return float("nan")
try:
return float(text)
except ValueError:
return float("nan")
times: list[float] = []
raw: list[tuple[float, float, float]] = []
newtons: list[tuple[float, float, float]] = []
valid: list[bool] = []
frame_ids: list[int] = []
dropped = 0
with path.open(encoding="utf-8", newline="") as handle:
for row in csv.DictReader(handle):
try:
times.append(float(row["t_rel_s"]))
frame_ids.append(int(row["frame_id"]))
except (KeyError, TypeError, ValueError):
dropped += 1
continue
raw.append(
(parse(row.get("FN_raw")), parse(row.get("FX_raw")), parse(row.get("FY_raw")))
)
newtons.append(
(parse(row.get("FN_N")), parse(row.get("FX_N")), parse(row.get("FY_N")))
)
valid.append((row.get("valid") or "0").strip() == "1")
times_arr = np.asarray(times, dtype=np.float64)
raw_arr = np.asarray(raw, dtype=np.float64).reshape(-1, 3)
newtons_arr = np.asarray(newtons, dtype=np.float64).reshape(-1, 3)
valid_arr = np.asarray(valid, dtype=bool)
ids_arr = np.asarray(frame_ids, dtype=np.int64)
# Older recordings can have rows out of time order (the writer used to
# drain a backlog before the queue). Every window query below assumes
# sorted time, so sort once here and report it instead of answering
# ``searchsorted`` on unsorted input.
ordered = _is_time_ordered(times)
if not ordered and times_arr.size:
order = np.argsort(times_arr, kind="stable")
times_arr = times_arr[order]
raw_arr = raw_arr[order]
newtons_arr = newtons_arr[order]
valid_arr = valid_arr[order]
ids_arr = ids_arr[order]
return times_arr, raw_arr, newtons_arr, valid_arr, ids_arr, dropped, ordered
index = self.index()
window = index.read_rows(0, index.rows)
return (window.times, window.raw, window.newtons, window.valid,
window.frame_ids, index.dropped_rows, index.ordered)
# ------------------------------------------------------------------ queries
def frame_at(self, t_rel_s: float) -> Optional[RecordingFrame]:
@@ -475,7 +414,7 @@ class RecordingReader:
def statistics(self, t0: float, t1: float, *, unit: str = "raw"):
"""Statistics of an interval, computed from the interval's own rows."""
return self.window(t0, t1, unit=unit).statistics(unit)
return self.index().statistics(t0, t1, unit=unit)
# ------------------------------------------------------------------ policy
def depth_policy(self) -> dict: