## MEASUREMENT: does the SHIPPED `Pattern` gun (guns/pattern_matcher.nim, rack
## gun id 5) overshoot radially the way the LINEAR base was shown to?
##
## Background (commit 9cd6e9b): the base `forecastLinear` systematically
## OVERSHOOTS — the enemy is NEARER than the constant-velocity prediction in
## 63-81% of fired bullets and farther in only 4-14%, consistently across all
## six DrussGT captures. A constant short offset (aim distance x0.95 or a fixed
## -20 px) matched or beat the learned radial Tsetlin head on bmPoint.
##
## The gun that actually SHIPS is `Pattern`, not `Linear`. This tool measures the
## SAME signed radial error for Pattern: for every fired virtual bullet,
##
##     radialErr = |actual enemy pos at the base arrival tick - fire pos|
##                 - |Pattern's predicted aim point - fire pos|
##
## (negative = the enemy was NEARER than Pattern predicted = Pattern OVERSHOT).
## The arrival tick mirrors the virtual-bullet resolver exactly:
##   arrOff = max(0, ceil(aimDist / bulletSpeed) - 1), arrivalTick = fireTick + arrOff
## because the tracker advances travelDist by bulletSpeed on the spawn tick and
## resolves when travelDist >= fireDist.
##
## It also reports the raw `forecastLinear` error on the identical states, so a
## reader can see whether Pattern is better or worse than the base on the same
## measurement, and pools per power bin as well as overall.
##
## READ-ONLY: loads tools/fixtures/*drussgt*.jsonl; writes nothing.
##
## Run:
##   nim c -r -d:release --path:common_libs \
##       common_libs/tests/measure_pattern_radial.nim
## Flags: --set=core|all (default core = the six captures of the 9cd6e9b table)

import std/[os, strformat, strutils, json, tables, math, algorithm]
import gun_harness/offline_range
import gun_harness/gun_interface
import gun_harness/virtual_bullets as vb
import guns/pattern_matcher
import guns/lead_forecast

const
  repoRoot = currentSourcePath().parentDir.parentDir.parentDir
  fixturesDir = repoRoot / "tools" / "fixtures"

type
  RoundSpan = tuple[start, count: int]

  Agg = object
    n: int
    sum, asum: float
    errs: seq[float]
    near0, far0: int         ## err < 0 / err > 0
    nearBot, farBot: int     ## err < -BotRadius / err > +BotRadius

proc loadRounds(path: string): seq[RoundSpan] =
  let dir = path.parentDir
  let base = path.extractFilename
  var side = dir / "drussgt_meta" / (base & ".rounds.json")
  if not fileExists(side): side = dir / (base & ".rounds.json")
  if not fileExists(side): return @[]
  let node = parseJson(readFile(side))
  if not node.hasKey("rounds"): return @[]
  for r in node["rounds"]:
    result.add (r["startTick"].getInt(), r["count"].getInt())

proc addErr(a: var Agg, e: float) =
  inc a.n
  a.sum += e
  a.asum += abs(e)
  a.errs.add e
  if e < 0.0: inc a.near0
  elif e > 0.0: inc a.far0
  if e < -BotRadius: inc a.nearBot
  elif e > BotRadius: inc a.farBot

proc median(a: Agg): float =
  if a.errs.len == 0: return 0.0
  var s = a.errs
  s.sort()
  let m = s.len div 2
  if s.len mod 2 == 1: s[m] else: 0.5 * (s[m - 1] + s[m])

proc percentile(a: Agg, p: float): float =
  if a.errs.len == 0: return 0.0
  var s = a.errs
  s.sort()
  let idx = clamp(int(round(p / 100.0 * float(s.len - 1))), 0, s.len - 1)
  s[idx]

proc reportScope(scope: string, agg: var Agg) =
  if agg.n == 0:
    echo &"{scope},0,n/a,n/a,n/a,n/a,n/a,n/a"
    return
  let p10 = agg.percentile(10)
  let p50 = agg.median
  let p90 = agg.percentile(90)
  echo &"{scope},{agg.n},{agg.sum/float(agg.n):.2f},{p50:.2f},{agg.asum/float(agg.n):.2f}," &
       &"{100.0*float(agg.near0)/float(agg.n):.1f},{100.0*float(agg.far0)/float(agg.n):.1f}," &
       &"{100.0*float(agg.nearBot)/float(agg.n):.1f},{100.0*float(agg.farBot)/float(agg.n):.1f}," &
       &"{p10:.1f},{p90:.1f}"

proc coreSet(): seq[string] =
  ## The exact six captures of the committed 9cd6e9b base table, so the Pattern
  ## numbers are directly comparable.
  for n in ["drussgt_vs_crazy", "drussgt_vs_spinbot", "drussgt_vs_drussgt",
            "tr_drussgt_vs_crazy", "tr_drussgt_vs_spinbot",
            "tr_drussgt_vs_modularbot"]:
    result.add(fixturesDir / (n & ".jsonl"))

proc allSet(): seq[string] =
  for kind, p in walkDir(fixturesDir):
    if kind == pcFile and p.extractFilename.contains("drussgt") and
       p.extractFilename.endsWith(".jsonl"):
      result.add p
  result.sort()

proc main() =
  var which = "core"
  for i in 1..paramCount():
    let a = paramStr(i)
    if a.startsWith("--set="): which = a[6..^1]
  let names = if which == "all": allSet() else: coreSet()

  echo "# Patterns radial error — negative = enemy NEARER than predicted (OVERSHOOT)"
  echo "# arrivalTick = fireTick + max(0, ceil(aimDist/speed) - 1); aimDist from the gun's own (px,py)"
  echo "# scope,n,meanPx,medianPx,meanAbsPx,pctNearer(<0),pctFarther(>0),pctNearer(<-18px),pctFarther(>+18px),p10,p90"

  var patAll: Agg
  var linAll: Agg
  var patCore: Agg
  var linCore: Agg
  let coreNames = coreSet()

  for path in names:
    if not fileExists(path): continue
    let fx = loadFixture(path)
    let fxName = path.extractFilename.replace(".jsonl", "")
    var pat: Agg
    var lin: Agg
    # inline replay so we keep the two errors paired
    var pose = initTable[int, tuple[x, y: float]]()
    for s in fx.states: pose[s.tick] = (s.enemyX, s.enemyY)
    var spans = loadRounds(path)
    if spans.len == 0:
      spans = @[(start: fx.states[0].tick, count: fx.states.len)]
    for sp in spans:
      var g = PatternMatcherGun()
      for i in 0..<fx.states.len:
        let state = fx.states[i]
        if state.tick < sp.start or state.tick >= sp.start + sp.count: continue
        for b in 0..<len(vb.PowerBins):
          let speed = bulletSpeed(vb.PowerBins[b])
          let pred = g.predict(state, speed)
          let aimDist = hypot(pred.x - state.selfX, pred.y - state.selfY)
          let at = state.tick + max(0, int(ceil(aimDist / speed)) - 1)
          if at in pose and aimDist > 1e-9:
            let actualR = hypot(pose[at].x - state.selfX, pose[at].y - state.selfY)
            addErr(pat, actualR - aimDist)
          let f = forecastLinear(state, speed)
          let lArr = state.tick + max(0, int(ceil(f.dist / speed)) - 1)
          if lArr in pose:
            let actualR = hypot(pose[lArr].x - state.selfX, pose[lArr].y - state.selfY)
            addErr(lin, actualR - f.dist)
    reportScope("PATTERN_" & fxName, pat)
    reportScope("LINEAR_" & fxName, lin)

    if pat.n > 0:
      inc patAll.n, pat.n
      patAll.sum += pat.sum; patAll.asum += pat.asum
      patAll.near0 += pat.near0; patAll.far0 += pat.far0
      patAll.nearBot += pat.nearBot; patAll.farBot += pat.farBot
      for e in pat.errs: patAll.errs.add e
    if lin.n > 0:
      inc linAll.n, lin.n
      linAll.sum += lin.sum; linAll.asum += lin.asum
      linAll.near0 += lin.near0; linAll.far0 += lin.far0
      linAll.nearBot += lin.nearBot; linAll.farBot += lin.farBot
      for e in lin.errs: linAll.errs.add e
    if path in coreNames:
      inc patCore.n, pat.n
      patCore.sum += pat.sum; patCore.asum += pat.asum
      patCore.near0 += pat.near0; patCore.far0 += pat.far0
      patCore.nearBot += pat.nearBot; patCore.farBot += pat.farBot
      for e in pat.errs: patCore.errs.add e
      inc linCore.n, lin.n
      linCore.sum += lin.sum; linCore.asum += lin.asum
      linCore.near0 += lin.near0; linCore.far0 += lin.far0
      linCore.nearBot += lin.nearBot; linCore.farBot += lin.farBot
      for e in lin.errs: linCore.errs.add e

  echo ""
  reportScope("PATTERN_CORE_POOLED", patCore)
  reportScope("LINEAR_CORE_POOLED", linCore)
  reportScope("PATTERN_ALL_POOLED", patAll)
  reportScope("LINEAR_ALL_POOLED", linAll)

  # distribution of the pooled core Pattern error
  echo "\n# Pattern CORE pooled error distribution (20px bins)"
  var hist = initOrderedTable[string, int]()
  let edges = [-1e9, -150.0, -100.0, -60.0, -20.0, 20.0, 60.0, 100.0, 150.0, 1e9]
  for e in patCore.errs:
    var label = "?"
    for k in 0..<edges.len-1:
      if e >= edges[k] and e < edges[k+1]:
        label = &"[{edges[k]:.0f},{edges[k+1]:.0f})"
        break
    hist[label] = hist.getOrDefault(label) + 1
  for label, c in hist:
    echo &"  {label:<18} {c:>7}  {100.0*float(c)/float(max(1,patCore.n)):5.1f}%"

when isMainModule:
  main()