o j< @sdZddlmZdedefddZdedefddZdMded edefd d Zd ededefddZ d ededefddZ dNdededefddZ dNdededefddZ dededefddZ dedefddZdedefd d!ZdOded edefd#d$ZdPded edefd&d'Zd(ed)edefd*d+Zd(ed,edefd-d.Zd/ed0edefd1d2Zded3ed4ed5edef d6d7Zded8edefd9d:Zd edefd;d<Zd edefd=d>Zd?ed@edefdAdBZdOded edefdCdDZd edefdEdFZdedGedHedIedef dJdKZdLS)QuE indicators.py Pure functions for VWAP, EMA, ATR, slope, and price-structure detection (higher highs/lows, consolidation, extension). Shared by scorer.py (premarket scoring) and entry_engine.py (opening confirmation) so both stages use identical math — the whole point of "confirm the prediction" is that premarket and open must be measuring the same things. All functions take plain lists/dicts of bar-like data: bar = {"t": timestamp, "o": open, "h": high, "l": low, "c": close, "v": volume} so they work identically against Alpaca bars or synthetic premarket snapshots. )meanbarsreturncCsnd}d}|D]}|d|d|dd}|||d7}||d7}q|dkr3|r1|ddSdS||S) z6Volume-weighted average price over the given bar list.hlc@vr)rtotal_pvtotal_vbtypicalr r F/var/www/screener/trade/premarket_backup_2026-09-08_2010/indicators.pyvwapsrcCspg}d}d}|D]-}|d|d|dd}|||d7}||d7}||dkr0||n|dq|S)z7Running VWAP value at each bar (for slope calculation).rrrrr r rappend)routcum_pvcum_vrrr r r vwap_series s  rlookbackcCs0t|}t||dkrdS|d|d|S)z6Positive => VWAP rising over the last `lookback` bars.rr )rlen)rrseriesr r r vwap_slope-srvaluesperiodcCsF|sdSd|d}|d}|ddD] }|||d|}q|S)Nrrrr )rr ker r r rema5s r$cCsR|sgSd|d}|dg}|ddD]}||||dd|q|S)Nr!rrr r)rr r"rr r r r ema_series?s   r%c Cst|dkrdSg}tdt|D]-}||d||d||dd}}}t||t||t||}||qt||krL|| dn|}|rTt|SdS)zhzrsi..rgI@cs g|] }||dqS)rr r3r+closesr rr4ls cSsg|] }|dkr |ndqSrrr r3dr r rr4mscSsg|] }|dkr | ndqSr9r r:r r rr4nsNrY@?)rr'r) rr deltasgainslossesavg_gainavg_lossr+rsr r7rrsiVsrDcurrent_volumeavg_volume_baselinecCs|dkrdS||S)Nrrr )rErFr r rrelative_volumesrGvolumescCsLt|}|dkr dS|d}t|d|pd}t||dp!d}||S)z Ratio of the average of the most recent half of the window vs the earlier half. >1 means volume is accelerating (matches the project spec's "developing" vs "fading" example). r=r!Ng& .>r)rr)rHnmidearlyrecentr r rvolume_accelerationsrNr8cCs8t|dks |ddkrdS|d|d|ddS)z>Simple normalized momentum: % change from first to last close.r!rrr r<)rr7r r rprice_momentumsrOrIcst||krdS|| d}dd|Ddd|DtfddtdtD}tfd dtdtD}t|d}tdt|d }d d ko[d d k}||koe||koe|S) u True if, over the last `lookback` bars, each bar's high is >= the prior bar's high (allowing 1 tick tolerance) and lows are trending up overall — i.e. a healthy stairstep rather than a single spike. FNcSr0rr r2r r rr4r5z/is_higher_highs_higher_lows..cSr0rr r2r r rr4r5c3(|]}||dkrdVqdSrNr r6highsr r &z.is_higher_highs_higher_lows..rc3rRrSr r6lowsr rrVrWffffff?r rrsumr'r(round)rrr. higher_highs higher_lowssteps threshold net_higherr rUrYris_higher_highs_higher_lowss     rdcCst|dkrdSt||kr|| dn|}dd|D}dd|D}dd|D}|r2t|nd}|d kr:dSt|t||dS) z Returns range-as-percent-of-price over the lookback window. Lower = tighter consolidation (generally healthier pre-breakout). r!r<NcSr0rPr r2r r rr4r5z+consolidation_tightness..cSr0rQr r2r r rr4r5cSr0r1r r2r r rr4r5r=r)rrr(min)rrr.rUrYr8 avg_pricer r rconsolidation_tightnesss rh current_pricereference_highcCs|dkrdS|||dSNrrr<r )rirjr r rdistance_from_high_pctrl vwap_valuecCs|dkrdS|||dSrkr )rirnr r rextension_from_vwap_pctrmrobidaskcCs<|dks|dkr dS||d}|dkrdS|||dS)Nrr<@r )rprqrKr r r spread_pcts  rs resistance buffer_pct hold_barscs@t||krdS|d|dtfdd|| dDS)u True if the last `hold_bars` closes have all been above resistance * (1 + buffer_pct/100) — i.e. the breakout held rather than spiking through and immediately failing. Frr<c3s|] }|dkVqdS)rNr r2triggerr rrVz%breakout_confirmed..N)rall)rrtrurvr rwrbreakout_confirmeds  r{max_retrace_pctc Cst|dkrdSdd|D}t|dkr |t|ddnd}|dks.|t|dkr0dS||}||drBt||dn|}||d}|dkrPdS|||d }|d|k}||koc|S) z Detects: price made a local high, pulled back no more than max_retrace_pct of the prior up-move, then resumed making new highs. Used to allow "healthy pullback followed by continuation" entries rather than only fresh breakouts. reFcSr0r1r r2r r rr4r5z.pullback_then_continuation..rNr rr<)rindexr(rf) rr|r8peak_idxpeaktroughmove_upretraceresumedr r rpullback_then_continuations &    rcst|}|dkr dStt|}t||t||tfddt||D}tfdd|D}|dkr.c3s|] }|dVqdS)r!Nr )r3r)rr rrVryr)rlistr'r\zip)rrJxsnumdenr rr linreg_slopes   rcCs4|sdSt|t|}|dkrdSt||dS)u Regression slope expressed as a percentage of the series' own mean, per bar — makes slope comparable across stocks at very different price levels (a $6 stock and a $14 stock can both be scored on the same "% per bar" scale). rrr<)r\rr)rrr r rnormalized_slope_pcts r slope_pctflat_threshold_pctcCs||krdS|| kr dSdS)z Buckets a normalized slope (see normalized_slope_pct) into "positive" / "flat" / "negative" against a symmetric dead-zone around zero, so small noise doesn't get labeled as a trend. positivenegativeflatr )rrr r rclassify_slope$s  rcst||krdS|| d}dd|Ddd|DtfddtdtD}tfd dtdtD}t|d}tdt|d }d d ko[d d k}||koe||koe|S) u The deteriorating-structure mirror of is_higher_highs_higher_lows(): True if a clear majority of steps in the window make a strictly LOWER high and a strictly lower low, AND the window is net lower overall (first vs last) — same net-direction guard used on the healthy-structure check, so a choppy down-up-down sequence can't pass on step-count alone. FNcSr0rPr r2r r rr4=r5z-is_lower_highs_lower_lows..cSr0rQr r2r r rr4>r5c3(|]}||dkrdVqdSrSr r6rTr rrV?rWz,is_lower_highs_lower_lows..rc3rrSr r6rXr rrV@rWrZr rr[)rrr. lower_highs lower_lowsr`ra net_lowerr rcris_lower_highs_lower_lows1s     rcCspt|}|dkr dSt|}|dd}t||}|||}|}|||d}|dkr0dS|||dS)u Percent change implied by a least-squares regression line fit across `values`, from the fitted line's value at the first point to its value at the last — NOT (values[-1] - values[0]) / values[0], which is exactly the two-point noise problem linreg_slope()'s docstring already warns about for a raw first/last delta. This is deliberately a different shape of number from normalized_slope_pct(): that one is "%-per-bar," which shrinks in magnitude as the window gets longer (the same total move spread over more bars) — useful for classify_slope()'s per-bar dead-zone, but not for comparing "how far did this move, net" across windows of very different lengths. Using the fitted line's own endpoints instead of the raw first/last bars keeps that comparison meaningful at any window length while still being robust to a single noisy bar at either end. r!rrrrrr<)rrr\)rrJsloperr intercept fit_startfit_endr r rregression_fit_pct_changeWs   rmin_barsmin_decline_pctrecovery_threshold_pctc Cs\t||krdSdd|D}|d}tdd|D}t|}t||}|| ko-||kS)uE True only when BOTH hold — same "signals must agree" pattern as intraday_health._is_severe(): - regression_fit_pct_change() over ALL of `bars` (the full session so far, not a short lookback) is down at least min_decline_pct — the day, net, is still heading down, not just the last few bars. - current price remains at least recovery_threshold_pct below the highest high anywhere in that same history — a bounce that has already reclaimed the session high isn't "still in a downtrend" no matter what the regression over the whole window says, so this can't fire on a name that's already fully recovered. Requires at least min_bars of bars; with less history than that, "the session's trend so far" isn't a meaningful question yet (a stock 3 minutes off the open has no session trend), so this fails safe to False rather than judging a fresh candidate on noise — same fail-safe-to-normal-behavior pattern used elsewhere in this project (e.g. entry_engine._apply_time_window_overrides()). FcSr0r1r r2r r rr4r5z)is_extended_downtrend..r css|]}|dVqdS)rNr r2r r rrVsz(is_extended_downtrend..)rr(rrl) rrrrr8ri session_highfit_pct_changedist_from_highr r ris_extended_downtrendws  rN)r)r&)rI)re)__doc__ statisticsrrfloatrrintrr$r%r/rDrGrNrOboolrdrhrlrorsr{rrrstrrrrrr r r rs:      *   &