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histogram aggregation + parser extension for BW interval fields

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Three layered changes that together make histogram charts visually
match BW's printout (one bar per interval, not per codec block):

1. bw_ascii_report parser captures histogram fields it previously
   dropped:
     - Histogram Start/Stop Time + Date → datetime
     - Number of Intervals + Interval Size (string + parsed seconds)
     - <Channel> Peak Time + Peak Date → datetime (per-channel)
     - Peak Vector Sum Date (combined with PVS Time → datetime;
       clears the bogus seconds parse that interpreted "22:33:52"
       as 22.0)
   New _parse_iso_date() handles BW's ISO format for histograms
   (waveforms use "May 8, 2026" long form).  New _parse_interval_size()
   handles "1 minute" / "5 minutes" / "15 seconds" etc.

2. _bw_report_to_dict() projects the new fields into a new
   bw_report.histogram block in the sidecar.

3. /db/events/{id}/waveform.json wraps the existing path 1 (HDF5)
   output with _maybe_aggregate_histogram(): when the event is a
   histogram AND the sidecar has bw_report.histogram.n_intervals,
   group the codec's per-block samples into N intervals via
   max-per-group and return the aggregated array.  time_axis gains
   histogram_aggregated / n_intervals / interval_size_s / interval_times
   fields.

Frontend (both modal chart in sfm_webapp.html + standalone event
browser) uses interval_times as x-axis labels when provided (BW-style
HH:MM:SS), falls back to interval index.

Defensive: aggregation is no-op when the sidecar lacks the histogram
block (events ingested before this change).  Activates automatically
on prod once a watcher re-forward populates new sidecars.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
This commit is contained in:
serversdown
2026-05-27 20:23:05 +00:00
parent ad2b553c7b
commit d21e3b5298
6 changed files with 254 additions and 10 deletions
Download Patch File Download Diff File Expand all files Collapse all files
minimateplus/bw_ascii_report.py
+121
View File
@@ -144,6 +144,23 @@ class BwAsciiReport:
# ── Vector sum ──────────────────────────────────────────────────────────
peak_vector_sum_ips: Optional[float] = None
peak_vector_sum_time_s: Optional[float] = None
# Histograms additionally have an absolute date+time for the PVS
# (it occurred at a specific interval). Waveform reports show
# only the relative-time value above.
peak_vector_sum_when: Optional[datetime.datetime] = None
# ── Histogram-specific fields (populated only when Event Type starts
# with 'Histogram' / 'Full Histogram' / 'Histogram + Continuous') ──
histogram_start: Optional[datetime.datetime] = None
histogram_stop: Optional[datetime.datetime] = None
histogram_n_intervals: Optional[int] = None # e.g. 4, 1436
histogram_interval_size_str: Optional[str] = None # "1 minute" / "5 minutes" / "15 seconds"
histogram_interval_size_s: Optional[float] = None # parsed to seconds
# Per-channel absolute peak time+date (histogram-specific). For
# waveform events these are None — those reports use the channel's
# time_of_peak_s (relative to trigger) instead. Keyed by channel
# name ("Tran", "Vert", "Long", "MicL").
channel_peak_when: Dict[str, datetime.datetime] = field(default_factory=dict)
# ── Sensor self-check (per channel) ─────────────────────────────────────
sensor_check: Dict[str, SensorCheck] = field(default_factory=dict)
@@ -223,6 +240,46 @@ def _parse_event_date(s: str) -> Optional[datetime.date]:
return None
def _parse_iso_date(s: str) -> Optional[datetime.date]:
"""Parse "2026-05-16" → date. Histograms use ISO format for their
Start Date / Stop Date / Peak Date fields; waveforms use the
"May 8, 2026" long form which `_parse_event_date` handles."""
s = s.strip()
try:
return datetime.date.fromisoformat(s)
except ValueError:
return None
_INTERVAL_UNIT_SECONDS = {
"second": 1, "seconds": 1, "sec": 1, "secs": 1,
"minute": 60, "minutes": 60, "min": 60, "mins": 60,
"hour": 3600, "hours": 3600, "hr": 3600, "hrs": 3600,
}
def _parse_interval_size(s: str) -> Optional[float]:
"""Parse "1 minute" / "5 minutes" / "15 seconds" / "2 seconds" → seconds.
Handles the BW Compliance Setup → Histogram Interval values verbatim
("2 seconds", "5 seconds", "15 seconds", "1 minute", "5 minutes",
"15 minutes") plus a few defensive variants.
"""
if not s:
return None
parts = s.strip().split()
if len(parts) < 2:
return None
try:
n = float(parts[0])
except ValueError:
return None
unit_per_s = _INTERVAL_UNIT_SECONDS.get(parts[1].lower())
if unit_per_s is None:
return None
return n * unit_per_s
def _parse_event_time(s: str) -> Optional[datetime.time]:
"""Parse "15:56:35" → time."""
s = s.strip()
@@ -336,6 +393,15 @@ def parse_report(text: Union[str, bytes], *, parse_samples: bool = False) -> BwA
in_user_notes_block = False
user_note_position = 0
# Histogram-field staging — BW writes <Channel> Peak Time and
# <Channel> Peak Date on separate lines (and similarly Histogram
# Start Time / Date). We stash the partial value when the time
# line arrives and combine it when the matching date line arrives.
_hist_start_time: Optional[datetime.time] = None
_hist_stop_time: Optional[datetime.time] = None
_pending_peak_time: Dict[str, Optional[datetime.time]] = {}
_pvs_time_raw: Optional[str] = None # last Peak Vector Sum Time value, raw
while i < n:
raw_line = lines[i]
i += 1
@@ -427,11 +493,66 @@ def parse_report(text: Union[str, bytes], *, parse_samples: bool = False) -> BwA
elif stat == "Peak Acceleration": cs.peak_accel_g = num
elif stat == "Peak Displacement": cs.peak_disp_in = num
# ── Histogram-specific fields ────────────────────────────────────────
# Histograms have Start/Stop time+date pairs + an interval count
# and size, plus per-channel absolute Peak Time/Date instead of
# the waveform's relative Time of Peak.
elif key == "Histogram Start Time":
_hist_start_time = _parse_event_time(value)
elif key == "Histogram Start Date":
_d = _parse_iso_date(value)
if _d and _hist_start_time:
report.histogram_start = datetime.datetime.combine(_d, _hist_start_time)
elif key == "Histogram Stop Time":
_hist_stop_time = _parse_event_time(value)
elif key == "Histogram Stop Date":
_d = _parse_iso_date(value)
if _d and _hist_stop_time:
report.histogram_stop = datetime.datetime.combine(_d, _hist_stop_time)
elif key == "Number of Intervals":
try:
report.histogram_n_intervals = int(float(value.strip()))
except ValueError:
pass
elif key == "Interval Size":
report.histogram_interval_size_str = value.strip()
report.histogram_interval_size_s = _parse_interval_size(value)
# ── Per-channel histogram Peak Date / Peak Time ──
# Lines like "Tran Peak Time : 22:31:38" + "Tran Peak Date : 2026-05-16"
elif key in ("Tran Peak Time", "Vert Peak Time", "Long Peak Time", "MicL Time"):
ch_name = "MicL" if key == "MicL Time" else key.split(" ", 1)[0]
_pending_peak_time[ch_name] = _parse_event_time(value)
elif key in ("Tran Peak Date", "Vert Peak Date", "Long Peak Date", "MicL Date"):
ch_name = "MicL" if key == "MicL Date" else key.split(" ", 1)[0]
_d = _parse_iso_date(value)
_t = _pending_peak_time.get(ch_name)
if _d and _t:
report.channel_peak_when[ch_name] = datetime.datetime.combine(_d, _t)
# ── Vector Sum ───────────────────────────────────────────────────────
elif key == "Peak Vector Sum":
report.peak_vector_sum_ips = _parse_number(value)
elif key == "Peak Vector Sum Time":
report.peak_vector_sum_time_s = _parse_number(value)
_pvs_time_raw = value
elif key == "Peak Vector Sum Date":
# Histogram-mode PVS gets paired with a date. We may have
# captured 'Peak Vector Sum Time' as either a relative
# seconds float (waveform) or an HH:MM:SS string we
# interpreted as a number. For histograms, BW writes
# "Peak Vector Sum Time : 22:33:52" which _parse_number
# parses as 22.0 (loses information). When Peak Vector Sum
# Date arrives, re-parse the previous PVS time line as a
# clock time and combine into an absolute datetime.
_d = _parse_iso_date(value)
if _d and _pvs_time_raw is not None:
_t = _parse_event_time(_pvs_time_raw)
if _t:
report.peak_vector_sum_when = datetime.datetime.combine(_d, _t)
# The earlier seconds parse was bogus for histograms;
# clear it so consumers don't think it's a real offset.
report.peak_vector_sum_time_s = None
# ── Microphone block ────────────────────────────────────────────────
elif key == "Microphone":
minimateplus/event_file_io.py
+15
View File
@@ -171,6 +171,10 @@ def _bw_report_to_dict(report: BwAsciiReport) -> dict:
"vector_sum": {
"ips": report.peak_vector_sum_ips,
"time_s": report.peak_vector_sum_time_s,
# Histogram events have an absolute date+time for the PVS
# (the interval at which it occurred); waveform events
# only have the time_s offset.
"when": report.peak_vector_sum_when.isoformat() if report.peak_vector_sum_when else None,
},
},
"mic": {
@@ -185,6 +189,17 @@ def _bw_report_to_dict(report: BwAsciiReport) -> dict:
"long": _sc("Long"),
"mic": _sc("MicL"),
},
# Histogram-specific fields (None on waveform-mode events).
# Per-channel absolute peak time/date for histograms — for
# waveforms see channels[ch]["time_of_peak_s"] instead.
"histogram": {
"start": report.histogram_start.isoformat() if report.histogram_start else None,
"stop": report.histogram_stop.isoformat() if report.histogram_stop else None,
"n_intervals": report.histogram_n_intervals,
"interval_size": report.histogram_interval_size_str,
"interval_size_s": report.histogram_interval_size_s,
"channel_peak_when": {ch: dt.isoformat() for ch, dt in report.channel_peak_when.items()},
},
"monitor_log": monitor_log,
"pc_sw_version": report.pc_sw_version,
}