The constants make ovulation minus five through ovulation plus one, and
the comment above them claimed a six-day window. Wilcox's six days are
the five before ovulation plus the day itself, measured against a KNOWN
ovulation day. Ours is estimated, usually by back-calculating a luteal
length from a median cycle, so a window drawn tight to the estimate
loses its last day whenever the estimate lands early, and the ovum stays
viable for most of a day after release besides.
The direction is decided by who reads the window. It is surfaced to
people trying to conceive and to people avoiding it, and for the second
group a window one day short is a window that misses. The constants keep
the conservative reading and the comment now states it, with the note
that changing either one is a coordination matter because the iOS client
reimplements the same spec.
The width is pinned by a test rather than left to be re-read off the
numbers the code already uses.
One-shot prettier pass so the new format:check gate starts from a clean
baseline. Formatting only — no behaviour change. Generator-owned and
vendored artifacts stay untouched via .prettierignore.
Below three observed cycles the prediction is a population-prior guess, not a
data-grounded estimate. The web calendar already hid the fertile window and
predicted ovulation in that state; make the gate structural in the DTO mapper
so iOS — and any client reading prediction.* directly — cannot paint a window
the rest of the app refuses to show. ovulationConfirmed stays goal-gated only:
a confirmed shift is observed data, not a prior.
Let a user pick the Sensiplan double-check's second indicator — cervical
mucus (default) or cervix observation — mirroring the published NFP
standard where the temperature primary sign pairs with one chosen
secondary sign.
- `CycleProfile.secondarySymptom` (MUCUS default | CERVIX) drives which
second sign the engine confirms against. Casual users keep temperature
+ mucus untouched; the choice lives behind the advanced cycle settings.
- `CycleDayLog` gains the three standard cervix signs — position
(LOW/HIGH), firmness (FIRM/SOFT), opening/os (CLOSED/OPEN) — as nullable
columns (migration 0157), wired through Zod, the day-log upsert, the
DTO, the sync feed, backup/restore and OpenAPI. Additive and
back-compatible: existing profiles backfill MUCUS, existing day-logs
keep NULL cervix signs, iOS inherits the fields.
- The engine's `confirmSymptothermal` takes the secondary-symptom choice;
on CERVIX it confirms against `detectCervixPeak` (last fertile-cervix
day followed by three closed days — the cervix-closure rule) instead of
the mucus peak. The double-check still requires BOTH the temperature
shift AND the secondary peak: a single cervix sign never confirms, and
the still-learning gate and conservative posture are unchanged.
Engine derived clean-room from the Arbeitsgruppe-NFP / Raith-Paula &
Frank-Herrmann standard.
A stored positive ovulation test (LH surge) was ignored by the
predictor. Wire it in as a Marquette/Fehring anchor: a positive surge
predicts ovulation ~24-36h later, so the estimated ovulation is set one
day after the last positive LH test in the current window, sharpening the
estimate over the calendar back-calculation — most valuable in the
thin-data (<3 cycle) case where the median/luteal back-calc is weak.
The LH surge is a SIGNAL that refines, never a sole assertion: it
re-anchors the still-estimated ovulation but never flips
`ovulationConfirmed` (a single indicator is not the symptothermal
double-check), and a confirmed symptothermal/temperature-trend ovulation
always wins over it. The still-learning gate and the un-confirmed status
are preserved. A stale prior-cycle surge whose next-start lands in the
past is rejected.
Citation: Fehring R.J. — Marquette Method; urinary LH peaks ~1 day before
ovulation.
A fever, illness, alcohol or a late/short-sleep reading can fake or mask
a temperature rise. Add a per-day `temperatureExcluded` flag on
CycleDayLog (migration 0156): when set, the engine drops the reading from
the cover-line baseline AND the shift evaluation, so a spike neither
fabricates nor masks a rise (Sensiplan: the cover line is drawn over the
last six unbracketed values).
Wired end to end — schema + Prisma, the engine's `detectTempShift`
filter, the Zod input/patch schemas, the day-log upsert (partial merge +
change detection), the read DTO, the calendar/insights/coach selects, the
backup round-trip, and the OpenAPI contract (a new boolean on the day-log
and calendar-day DTOs for the iOS client). The log-day sheet gains a
"mark reading as disturbed" toggle that appears once a temperature is
entered, translated across all six locales.
Citation: de.wikipedia "Symptothermale Methode"; myNFP "Temperaturkurve
auswerten" — Störfaktor bracketing.
The mucus peak was taken as the last egg-white/watery day with no
confirmation, so a stray late fertile-mucus entry corrupted the peak.
Implement the Sensiplan Höhepunkt rule: the peak day is the LAST
best-quality (egg-white/watery) day that is followed by at least 3
consecutive drier observed days, each strictly lower quality. The peak is
only confirmable retrospectively, after those 3 days, so a stray late
egg-white entry not yet followed by 3 drier days cannot move an
already-confirmed peak. Quality is scored on the t/f/S/+S ladder;
unobserved days are skipped so a logging gap does not break the count.
Citation: Arbeitsgruppe NFP / Raith-Paula & Frank-Herrmann; myNFP
"Zervixschleim beobachten".
The BBT shift detector only applied the strict 3-over-6 rule (3 readings
above the cover line, the 3rd >=0.2C above), so it under-detected
ovulation on common ovulatory patterns. Add the two published
Ausnahmeregeln:
- 1. Ausnahmeregel (slow/staircase rise): when the 3rd high reading is
above the cover line but not >=0.2C above, a 4th reading that need
only be above the line confirms the shift.
- 2. Ausnahmeregel (one value falls back): when exactly one of the three
readings falls back to/below the cover line, it is discounted and a
4th reading that again clears 0.2C above the line confirms.
The result now carries a `rule` (0|1|2) provenance field and the
`evaluationCompleteDate` (evening of the 3rd or 4th high reading). The
rules follow the Arbeitsgruppe NFP / Raith-Paula & Frank-Herrmann
standard and are mutually exclusive by construction.
The hard upper bound clamped cycle lengths at 45 days, force-excluding any
longer cycle as an outlier before the robust statistics ran. Cycles over 35
days are oligomenorrhea but still real, and adolescent and perimenopausal users
routinely run to fifty days or more — exactly the irregular users for whom an
honest estimate matters most. Clamping their genuine cycles biased the estimate
toward the population middle.
Raise the ceiling to 60 days. It stays a coarse gross-error backstop; the
median-plus-MAD fence and the missed-log heuristic still do the real outlier
work, and because the fence is computed before exclusion, raising the ceiling
does not move it — it only stops the hard rule from pre-empting the fence on
long but consistent cycles.
The symptothermal layer ran against the full day-log history: detectTempShift
returned the earliest 3-over-6 rise and detectMucusPeak the last egg-white day
across all cycles, so a multi-cycle user with historical BBT confirmed a
months-old ovulation and the predicted next-period start landed in the past.
Scope the temperature/mucus detectors to the current cycle window
[lastConfirmedStart − BBT_WINDOW, today], take the latest qualifying temp shift,
and reject any confirmation whose next-start is already in the past.
Resolve luteal length through a single clamp. The predictor clamped to [10,16]
while the calendar adapter and phase mapper used the raw stored value, so the
ovulation dot and the OVULATORY band could land on different days for an
out-of-clamp profile. Export resolveLuteal/clampLuteal, route buildCalendar,
buildPhaseCycles and phaseForDay through it, and tighten the profile-prefs Zod
bound to the same [10,16] range.
Show the fertile window for AVOID_PREGNANCY as well as TRYING_TO_CONCEIVE per the
algorithm spec; it stays hidden for GENERAL_HEALTH/PERIMENOPAUSE.
Bound the day-log reads on the calendar and insights routes to the rendered span
plus the symptothermal lookback instead of the full history; cycle-length stats
already run off the MenstrualCycle rows.
Add mood and blood glucose as phase-crosstab outcome metrics under the same FDR
and per-group day floors. Mood is read from MoodEntry and injected as a synthetic
channel since it is not a measurement row.
Add multi-cycle, luteal-clamp and fertile-window fixtures.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Pure, DB-free cycle prediction and phase-assignment engine under
src/lib/cycle/. The math mirrors the offline-parity spec exactly so the
server and the native client compute byte-identical forecasts from the
same canonical inputs.
- day-math: noon-UTC anchored YYYY-MM-DD arithmetic (dayDiff, addDays,
round-half-up) that stays stable across timezones and DST transitions.
- prediction: robust median+MAD cycle-length estimator over a trailing
12-cycle window with 3-MAD outlier exclusion and missed-log detection;
period-length estimator; one-sigma Low/High date band widened by
logging sparsity; luteal back-calculated ovulation + six-day fertile
window; the CALENDAR -> symptothermal -> temperature-trend method
ladder (sensiplan 3-over-6 + mucus-peak re-implemented from the
published method) with documented blend precedence; a multiplicative
confidence scalar shrinking with length variance, low cycle count, and
sparse logging.
- phase: day-of-cycle -> MENSTRUAL/FOLLICULAR/OVULATORY/LUTEAL boundary
mapping with menstrual precedence on overlap.
- 48 unit tests covering the regular, irregular, cold-start, outlier,
symptothermal, temperature-trend, and every phase-boundary case; all
assertions are timezone-independent and pin exact dates + confidence.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Marc-André Bombeck