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scan.py: real bid-depth liquidity flag, real-variance flow bound, profit/area

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- max_units_at_impact(): walks the LIVE bid book for a genuine, ticker-
  specific instant-exit liquidity check, replacing a flat 25%-of-flow
  guess (a price-vs-volume elasticity regression was tried first and
  abandoned - confounded by demand-driven volume on real data). Surfaced
  as an [exit-thin] WARNING flag, not a hard cap - a single order-book
  snapshot is less reliable than the 30-day flow aggregate that still
  drives n_lim/filtering (using it as a hard cap once silently zeroed
  out a real recipe from one noisy snapshot).
- tref_precise(): real variance of daily traded volume instead of a
  Poisson unit-independence bound, wired into stage 2 only (bounded
  candidate set, cached). Also fixed: was averaging only over trading
  days, overstating flow ~3x for sparse tickers.
- n_out(): dropped the demand-coverage term, which penalized thin
  resting-bid books even though production sells via patient asks taken
  by walk-up buyers with no resting bid at all.
- --sort area: profit/day per tile of TOTAL footprint, now including the
  single-tier hab area a building's workforce drags along (was building
  area only).
- --deprec/--reclaim-frac: amortizes unreclaimed capex, not full capex -
  real FIO reclaim data showed 50-86% returned even at near-100%
  condition, contradicting a 100%->0 decay-curve assumption.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
This commit is contained in:
dodox
2026-10-10 23:06:49 +02:00
co-authored by Claude Sonnet 5
parent 11f54276b3
commit 3f67cc7ed5
3 changed files with 135 additions and 33 deletions
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tools/scan.py
+40 -19
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@@ -33,7 +33,9 @@ def main():
ap.add_argument("--cargo", type=float, default=500.0, help="t and m3 per trip (starter ship)")
ap.add_argument("--no-hq", action="store_true", help="ignore HQ from state (new base without the HQ)")
ap.add_argument("--permits-used", type=int, help="override permits used (affects faction bonus multiplier), e.g. 2 for a second base")
ap.add_argument("--deprec", type=float, default=0, help="demolish-later mode: building value decays linearly to 0 over this many days (game: ~60); subtracts capex/deprec per day")
ap.add_argument("--deprec", type=float, default=0, help="demolish-later mode: assumed holding days before demolition; amortizes the UNRECLAIMED portion of capex (capex x (1 - --reclaim-frac)) over that period, NOT full capex - real FIO reclaimables data (this account's own buildings, 2026-10-10) showed ~50-86%% returned even at near-100%% condition, contradicting a 100%%->0 time-decay story. See docs/decisions.md.")
ap.add_argument("--reclaim-frac", type=float, default=0.65, help="fraction of capex recovered on demolition - real observed range 50-86%% across 7 owned building types (CM a low outlier at ~7%%, excluded); single base/age, small sample, treat as a rough placeholder not a calibrated curve")
ap.add_argument("--max-impact", type=float, default=10.0, help="max %% the realized price may degrade below vwap7/bid when walking the LIVE bid book for your planned daily output (puga.saturation.max_units_at_impact) - feeds the [exit-thin] warning flag: can you instantly DUMP a day of output into resting bids if you needed cash now, not whether your patient asks clear (that's the market/lim columns). See docs/decisions.md")
ap.add_argument("--input", help="only recipes consuming this ticker as an input, e.g. --input AL for recipes built on top of your own AL chain")
ap.add_argument("--planet", help="planet natural id: adds extraction (EXT/COL/RIG) from its resources, uses its fertility and active COGC; new base (not in state) => no HQ, permits+1")
ap.add_argument("--own", type=int, default=1, help="how many buildings WE would run; yield/payback is measured at this size (default 1). --min-n is only a market-size filter")
@@ -45,7 +47,7 @@ def main():
ap.add_argument("--max-n", type=int, default=50, help="cap N* (capital/attention limit)")
ap.add_argument("--budget", type=float, help="capital limit in AIC: caps N and drops recipes whose single-building capex exceeds it")
ap.add_argument("--mcg", type=float, default=4.0, help="MCG per area (4 on normal planets)")
ap.add_argument("--sort", default="roi", choices=["roi", "total", "roi1"])
ap.add_argument("--sort", default="roi", choices=["roi", "total", "roi1", "area"])
ap.add_argument("--top", type=int, default=30)
ap.add_argument("--k", type=int, default=80, help="candidates refined with order books")
ap.add_argument("--show-thin", action="store_true")
@@ -83,10 +85,11 @@ def main():
return None
return sum(n * p for n, p in parts) + a.mcg * b["AreaCost"] * mcg
hab_head = {}
hab_head, hab_area = {}, {}
for tier, hab in (("pioneer", "HB1"), ("settler", "HB2"), ("technician", "HB3"), ("engineer", "HB4"), ("scientist", "HB5")):
c = bcost(hab)
hab_head[tier] = None if c is None else c / econ.HAB_CAP[hab][tier]
hab_area[tier] = econ.HAB_AREA[hab] / econ.HAB_CAP[hab][tier]
def wage(tier): # per worker per day, both luxuries supplied, at ask
tot = 0.0
@@ -156,7 +159,7 @@ def main():
mm[t] = x.mm_buy # market maker floor: unlimited depth at mm_buy
continue
thin |= sat.is_thin(tr, x.demand, qo)
n = sat.n_out(tr, 0, x.demand, qo) # stage 1: flow + demand only; queue penalty applied in stage 2 with the book
n = sat.n_out(tr, 0, qo) # stage 1: flow only; queue penalty applied in stage 2 with the book
if n < n_lim:
n_lim, lim = n, t
if n_lim == float("inf"):
@@ -170,7 +173,8 @@ def main():
rough = sum(io["out"][t] * price0[t] for t in io["out"]) - sum(io["in"][t] * ask(t) for t in io["in"]) - wcost
staff = "".join(TIER_CODE[t] for t in keep) + ("" if len(keep) == len(need) else "-")
cands.append(dict(rec=rec, b=b, io=io, eff=eff, capex=capex, wcost=wcost, n_lim=n_lim, lim=lim, thin=thin, mm=mm,
rough_roi=100 * rough / capex, top=top, staff=staff, ins=ins, outs=outs))
rough_roi=100 * rough / capex, top=top, staff=staff, ins=ins, outs=outs,
hab_area_per_bld=sum(heads[t] * hab_area[t] for t in keep)))
cands.sort(key=lambda c: c["rough_roi"], reverse=True)
rows = []
@@ -184,6 +188,9 @@ def main():
def asks_of(t):
return sorted((o["ItemCost"], (o["ItemCount"] or 0)) for o in raw_book(t)["SellingOrders"])
def bids_of(t):
return [(o["ItemCost"], (o["ItemCount"] or 0)) for o in raw_book(t)["BuyingOrders"] if o.get("ItemCost")]
def band_of(t):
if t not in bandcache:
ob = raw_book(t)
@@ -192,21 +199,29 @@ def main():
bandcache[t] = (lo, hi)
return bandcache[t]
def demand_of(t):
bids = ((o["ItemCost"], o["ItemCount"] or 0) for o in raw_book(t)["BuyingOrders"])
return sat.effective_demand(bids, band_of(t))
for c in cands[:a.k]:
io, mm = c["io"], c["mm"]
# stage 2: queue penalty from competing asks near market price only, and demand within the tradeable band
n2 = float("inf")
# stage 2: queue penalty from competing asks near market price, flow from REAL daily-volume
# variance (tref_precise) now that we're down to a bounded candidate set worth the extra fetch
n2, bid_thin = float("inf"), False
for t, qo in io["out"].items():
if t in mm:
continue
x = Q(t)
se = sat.effective_supply(asks_of(t), x.vwap7 or x.ask, band=band_of(t))
n2 = min(n2, sat.n_out(sat.tref(x.traded7, x.traded30), se, demand_of(t), qo))
n2 = min(n2, sat.n_out(sat.tref_precise(t, a.cx, x.traded7, x.traded30), se, qo))
# Bid-book depth is a single LIVE SNAPSHOT (orders get added/withdrawn constantly) -
# not reliable enough to use as a hard cap like the flow-based n_out above, which
# aggregates real traded volume over 30 days. Surfaced as a warning flag instead, and
# measures a DIFFERENT thing than market/lim: not "can my patient asks clear" (that's
# p_patient()/n_out, ask-side, the real production-selling mechanism), but "could I
# instantly dump a day of output into resting BIDS right now if I needed cash" - panic-
# exit liquidity, not production price impact. A "yes" here doesn't guarantee it holds
# up over time, and a "no" might just be an unlucky instant - re-check before acting.
depth_units = sat.max_units_at_impact(bids_of(t), x.vwap7 or x.bid, a.max_impact)
bid_thin |= depth_units < qo
c["n_lim"] = float(a.max_n) if n2 == float("inf") else n2
c["bid_thin"] = bid_thin
if c["n_lim"] < a.min_n and not a.show_thin:
continue
@@ -217,7 +232,7 @@ def main():
if t in mm:
p = mm[t]
else:
p = sat.p_patient(asks_of(t), sat.tref(x.traded7, x.traded30), N * qo, x.bid, x.vwap7, x.vwap30, x.ask, band_of(t)[1])
p = sat.p_patient(asks_of(t), sat.tref_precise(t, a.cx, x.traded7, x.traded30), N * qo, x.bid, x.vwap7, x.vwap30, x.ask, band_of(t)[1])
rev += N * qo * p
cost = 0.0
for t, qi in io["in"].items():
@@ -232,7 +247,7 @@ def main():
c["tons"] = max(wi, wo)
frt = max(wi, wo, vi, vo) / a.cargo * a.trip_cost
c["frt"] = frt
dep = N * c["capex"] / a.deprec if a.deprec else 0.0 # value lost per day if demolished after holding
dep = N * c["capex"] * (1 - a.reclaim_frac) / a.deprec if a.deprec else 0.0 # unreclaimed capex lost per day if demolished after holding
return rev - cost - N * c["wcost"] - frt - dep
if a.budget and c["capex"] > a.budget:
@@ -247,22 +262,28 @@ def main():
netN = evaluate(n_star)
if netN is None:
continue
area = n_star * ((c["b"].get("AreaCost") or 0) + c.get("hab_area_per_bld", 0.0))
rows.append(dict(roi1=100 * net1 / c["capex"], roiN=100 * netN / n_star / c["capex"], total=netN, n=n_star,
n_lim=c["n_lim"], lim=c["lim"], capex=c["capex"] * n_star, eff=c["eff"], bld=c["b"]["Ticker"],
top=c["top"], staff=c["staff"], tons=c.get("tons", 0), frt=c.get("frt", 0), h=c["rec"]["TimeMs"] / 3.6e6, thin=c["thin"],
top=c["top"], staff=c["staff"], tons=c.get("tons", 0), frt=c.get("frt", 0), h=c["rec"]["TimeMs"] / 3.6e6,
thin=c["thin"], bid_thin=c.get("bid_thin", False),
area=area, profit_area=netN / area if area else 0.0,
rec=" ".join(f"{v:g}{k}" for k, v in c["ins"].items()) + " -> " + " ".join(f"{v:g}{k}" for k, v in c["outs"].items())))
key = {"roi": "roiN", "roi1": "roi1", "total": "total"}[a.sort]
key = {"roi": "roiN", "roi1": "roi1", "total": "total", "area": "profit_area"}[a.sort]
rows.sort(key=lambda r: r[key], reverse=True)
if a.json:
import json
Path(a.json).write_text(json.dumps(rows))
print(f"# {a.cx} tier<={a.tier or 'any'} cogc={a.cogc or '-'} faction={faction or '-'} ({pu}/{pt} permits) min-n>={a.min_n} sorted by {a.sort}")
print("# yld/d is profit/day / capex as a %, for OUR size (--own buildings, default 1) incl. our own price impact; this is NOT a compoundable rate (1/payback, see docs/decisions.md) - pback is the number to actually reason about. market = buildings the market could absorb (--min-n filters on it, nothing else). Net of freight. Patient asks near VWAP, inputs ask-walked; all estimates")
print(f"{'yld/d':>6} {'pback':>6} {'own':>3} {'market':>6} {'lim':4} {'profit/d':>11} {'capex':>9} {'eff':>4} {'bld':4} {'staff':5} {'t/d':>5} {'frt/d':>6} {'h':>5} recipe")
print("# profit/area ranks by AIC/day per tile of TOTAL footprint - production building AreaCost PLUS the single-tier hab area its own workforce drags along (heads/100 x hab area, e.g. a 100-head pioneer building pulls a full HB1) - once a base's area cap binds (not cash), this is the real allocation criterion, not yld/d. --sort area to rank by it.")
print("# [exit-thin] = INSTANT-DUMP liquidity check, not production price impact: right now, the LIVE bid book can't absorb even 1 day of 1 building's output within --max-impact%% if you needed to sell immediately. A single snapshot (orders change constantly), NOT folded into market/lim (which measures patient ask-side selling via real 30d flow, the actual production mechanism). Re-check before acting on it.")
print(f"{'yld/d':>6} {'pback':>6} {'own':>3} {'market':>6} {'lim':4} {'profit/d':>11} {'capex':>9} {'area':>5} {'$/area':>7} {'eff':>4} {'bld':4} {'staff':5} {'t/d':>5} {'frt/d':>6} {'h':>5} recipe")
for r in rows[:a.top]:
pback = f"{100/r['roiN']:6.1f}" if r['roiN'] > 0 else " inf"
print(f"{r['roiN']:6.1f} {pback} {r['n']:3d} {r['n_lim']:6.1f} {r['lim']:4} {r['total']:11.0f} {r['capex']:9.0f} {r['eff']*100:4.0f} {r['bld']:4} {r['staff']:5} {r['tons']:5.0f} {r['frt']:6.0f} "
f"{r['h']:5.1f} {r['rec']}{' [thin]' if r['thin'] else ''}")
flags = (' [thin]' if r['thin'] else '') + (' [exit-thin]' if r['bid_thin'] else '')
print(f"{r['roiN']:6.1f} {pback} {r['n']:3d} {r['n_lim']:6.1f} {r['lim']:4} {r['total']:11.0f} {r['capex']:9.0f} {r['area']:5.0f} {r['profit_area']:7.1f} {r['eff']*100:4.0f} {r['bld']:4} {r['staff']:5} {r['tons']:5.0f} {r['frt']:6.0f} "
f"{r['h']:5.1f} {r['rec']}{flags}")
if __name__ == "__main__":