import { useState } from 'react'
import { useBayesianPosteriors, useRegimeClusters, useRegimeTransitions, usePatternEmbeddings, api } from '../hooks/useApi'
import { useMutation, useQueryClient } from '@tanstack/react-query'
import clsx from 'clsx'
import { Brain, GitBranch, Layers, Cpu, RefreshCw, AlertTriangle } from 'lucide-react'

// ── Bayesian Posteriors ───────────────────────────────────────────────────────

function BayesianTable({ data }: { data: any[] }) {
  if (!data || data.length === 0) {
    return (
      <div className="text-center py-10 text-slate-500">
        <Brain className="w-8 h-8 mx-auto mb-2 opacity-20" />
        <div>Pas encore de données bayésiennes</div>
        <div className="text-xs mt-1">Les posteriors se calculent après des trades matures (≥35% de l'horizon)</div>
      </div>
    )
  }

  const withData = data.filter(d => d.sample_size > 0)
  const withoutData = data.filter(d => d.sample_size === 0)

  return (
    <div className="space-y-4">
      {withData.length > 0 && (
        <div className="overflow-x-auto">
          <table className="w-full text-xs">
            <thead>
              <tr className="text-slate-500 border-b border-slate-700/30">
                <th className="text-left py-2 pr-3 font-medium">Pattern</th>
                <th className="text-right py-2 px-2 font-medium">Prior GPT</th>
                <th className="text-right py-2 px-2 font-medium">WR Bayésien</th>
                <th className="text-right py-2 px-2 font-medium">IC 95%</th>
                <th className="text-right py-2 px-2 font-medium">Trades matures</th>
                <th className="text-right py-2 px-2 font-medium">Dérive</th>
                <th className="text-center py-2 px-2 font-medium">Confiance</th>
              </tr>
            </thead>
            <tbody className="divide-y divide-slate-800/50">
              {withData.map((d: any) => {
                const wr = d.bayesian_win_rate_pct
                const wrColor = wr >= 60 ? 'text-emerald-400' : wr >= 40 ? 'text-amber-400' : 'text-red-400'
                const drift = d.prior_vs_posterior_drift
                const driftColor = Math.abs(drift) < 0.05 ? 'text-slate-400'
                  : drift > 0 ? 'text-emerald-400' : 'text-red-400'
                const confColor = d.confidence_level === 'haute' ? 'text-emerald-400'
                  : d.confidence_level === 'moyenne' ? 'text-amber-400' : 'text-slate-500'
                return (
                  <tr key={d.pattern_id} className="hover:bg-dark-700/30 transition-colors">
                    <td className="py-2 pr-3">
                      <div className="text-white font-medium truncate max-w-[180px]">{d.pattern_name}</div>
                      <div className="text-slate-600 font-mono text-[10px]">{d.asset_class ?? '—'}</div>
                    </td>
                    <td className="text-right py-2 px-2 font-mono text-slate-400">
                      {Math.round(d.prior_probability * 100)}%
                    </td>
                    <td className={clsx('text-right py-2 px-2 font-mono font-bold', wrColor)}>
                      {wr}%
                    </td>
                    <td className="text-right py-2 px-2 font-mono text-slate-500 text-[10px]">
                      [{Math.round(d.lower_ci_95 * 100)}%–{Math.round(d.upper_ci_95 * 100)}%]
                    </td>
                    <td className="text-right py-2 px-2 text-slate-300 font-mono">
                      {d.sample_size}
                    </td>
                    <td className={clsx('text-right py-2 px-2 font-mono', driftColor)}>
                      {drift >= 0 ? '+' : ''}{Math.round(drift * 100)}%
                    </td>
                    <td className={clsx('text-center py-2 px-2 text-[10px] font-bold uppercase', confColor)}>
                      {d.confidence_level}
                    </td>
                  </tr>
                )
              })}
            </tbody>
          </table>
        </div>
      )}
      {withoutData.length > 0 && (
        <div className="text-xs text-slate-600 mt-1">
          {withoutData.length} pattern(s) sans trades matures — prior GPT uniquement
        </div>
      )}
    </div>
  )
}

// ── Regime Transition Matrix ──────────────────────────────────────────────────

function TransitionMatrix({ data }: { data: any }) {
  if (!data || !data.matrix || Object.keys(data.matrix).length === 0) {
    return (
      <div className="text-center py-8 text-slate-500">
        <GitBranch className="w-8 h-8 mx-auto mb-2 opacity-20" />
        <div>Pas encore de transitions détectées</div>
        <div className="text-xs mt-1">Les clusters se remplissent au fil des cycles</div>
      </div>
    )
  }

  const { matrix, labels, cluster_ids } = data
  const ids: number[] = cluster_ids ?? Object.keys(matrix).map(Number)

  return (
    <div className="overflow-x-auto">
      <div className="text-xs text-slate-500 mb-2">
        Probabilité de transition d'un régime à l'autre (lignes = source, colonnes = destination)
        · {data.n_transitions} transitions totales
      </div>
      <table className="text-xs border-collapse">
        <thead>
          <tr>
            <th className="text-slate-500 p-2 font-normal text-right pr-3">De ↓ / Vers →</th>
            {ids.map(dst => (
              <th key={dst} className="p-2 font-medium text-slate-300 text-center min-w-[90px]">
                <div className="text-[10px] text-slate-500">C{dst}</div>
                <div className="truncate max-w-[88px]">{(labels?.[dst] ?? `Cluster ${dst}`).split(' ').slice(0, 2).join(' ')}</div>
              </th>
            ))}
          </tr>
        </thead>
        <tbody>
          {ids.map(src => (
            <tr key={src} className="border-t border-slate-800/40">
              <td className="p-2 text-right pr-3 font-medium text-slate-300">
                <div className="text-[10px] text-slate-500">C{src}</div>
                <div className="text-xs truncate max-w-[120px]">{(labels?.[src] ?? `Cluster ${src}`).split(' ').slice(0, 2).join(' ')}</div>
              </td>
              {ids.map(dst => {
                const prob = matrix?.[src]?.[dst] ?? 0
                const pct = Math.round(prob * 100)
                const bg = src === dst
                  ? 'bg-blue-500/20 text-blue-300'
                  : pct >= 50 ? 'bg-emerald-500/20 text-emerald-300'
                  : pct >= 25 ? 'bg-amber-500/10 text-amber-300'
                  : 'text-slate-600'
                return (
                  <td key={dst} className={clsx('p-2 text-center font-mono font-bold rounded', bg)}>
                    {pct > 0 ? `${pct}%` : '—'}
                  </td>
                )
              })}
            </tr>
          ))}
        </tbody>
      </table>
      <div className="text-[10px] text-slate-600 mt-2">
        Diagonal = reste dans le même cluster · Vert = transition dominante · Bleu = auto-transition
      </div>
    </div>
  )
}

// ── Cluster History Timeline ──────────────────────────────────────────────────

const CLUSTER_COLORS: Record<number, string> = {
  0: 'bg-red-500',
  1: 'bg-emerald-500',
  2: 'bg-orange-500',
  3: 'bg-yellow-500',
  4: 'bg-slate-400',
}

function ClusterTimeline({ data }: { data: any[] }) {
  if (!data || data.length === 0) {
    return (
      <div className="text-center py-6 text-slate-500 text-xs">
        Aucun cluster détecté encore — lancez un cycle pour démarrer
      </div>
    )
  }

  // Afficher les 30 derniers points
  const recent = [...data].reverse().slice(0, 30)

  return (
    <div className="space-y-2">
      <div className="flex gap-1 flex-wrap">
        {Object.entries(CLUSTER_COLORS).map(([k, col]) => (
          <span key={k} className="flex items-center gap-1 text-[10px] text-slate-400">
            <span className={clsx('w-2 h-2 rounded-full inline-block', col)} />
            C{k}
          </span>
        ))}
      </div>
      <div className="flex gap-0.5 flex-wrap">
        {recent.map((r: any, i: number) => (
          <div
            key={i}
            title={`${r.timestamp?.slice(0, 16)} · ${r.cluster_label} · ${r.dominant_regime}${r.anomaly_flag ? ' ⚠️ anomalie' : ''}`}
            className={clsx(
              'w-5 h-5 rounded cursor-default',
              CLUSTER_COLORS[r.cluster_id] ?? 'bg-slate-600',
              r.anomaly_flag ? 'ring-2 ring-white/50' : ''
            )}
          />
        ))}
      </div>
      <div className="text-[10px] text-slate-600">
        Chaque carré = 1 snapshot · Blanc cerclé = anomalie détectée · {data.length} entrées au total
      </div>

      {/* Latest cluster detail */}
      {data[0] && (
        <div className="mt-3 p-3 rounded bg-dark-700/60 border border-slate-700/30 text-xs">
          <div className="text-slate-400 mb-1">Cluster actuel</div>
          <div className="flex items-center gap-2">
            <span className={clsx('w-3 h-3 rounded-full', CLUSTER_COLORS[data[0].cluster_id])} />
            <span className="text-white font-semibold">{data[0].cluster_label}</span>
            <span className="text-slate-500">({data[0].dominant_regime})</span>
            {data[0].anomaly_flag ? (
              <span className="flex items-center gap-1 text-amber-400 font-bold">
                <AlertTriangle className="w-3 h-3" /> Anomalie
              </span>
            ) : null}
          </div>
          <div className="text-slate-600 mt-0.5">{data[0].timestamp?.slice(0, 16)}</div>
        </div>
      )}
    </div>
  )
}

// ── Embeddings Summary ────────────────────────────────────────────────────────

function EmbeddingsSummary({ data }: { data: any[] }) {
  if (!data || data.length === 0) {
    return (
      <div className="text-center py-6 text-slate-500 text-xs">
        <Cpu className="w-6 h-6 mx-auto mb-1 opacity-20" />
        Aucun embedding disponible — ils se génèrent automatiquement lors du filtrage des patterns
      </div>
    )
  }
  return (
    <div className="space-y-2">
      <div className="text-xs text-slate-500">{data.length} patterns vectorisés</div>
      <div className="overflow-x-auto">
        <table className="w-full text-xs">
          <thead>
            <tr className="text-slate-500 border-b border-slate-700/30">
              <th className="text-left py-1.5 pr-3 font-medium">Pattern</th>
              <th className="text-left py-1.5 px-2 font-medium">Classe</th>
              <th className="text-right py-1.5 px-2 font-medium">Modèle</th>
              <th className="text-right py-1.5 px-2 font-medium">Mis à jour</th>
            </tr>
          </thead>
          <tbody className="divide-y divide-slate-800/30">
            {data.slice(0, 20).map((e: any, i: number) => (
              <tr key={i} className="hover:bg-dark-700/20">
                <td className="py-1.5 pr-3 text-white truncate max-w-[200px]">{e.name ?? e.pattern_id}</td>
                <td className="py-1.5 px-2 text-slate-400">{e.asset_class ?? '—'}</td>
                <td className="py-1.5 px-2 text-right font-mono text-slate-500">{e.model_version}</td>
                <td className="py-1.5 px-2 text-right text-slate-600">{e.updated_at?.slice(0, 10)}</td>
              </tr>
            ))}
          </tbody>
        </table>
      </div>
    </div>
  )
}

// ── Main Page ─────────────────────────────────────────────────────────────────

export default function AnalyticsAdvanced() {
  const [regimeDays, setRegimeDays] = useState(90)
  const qc = useQueryClient()

  const { data: bayesData, isLoading: loadingBayes } = useBayesianPosteriors()
  const { data: clustersData, isLoading: loadingClusters } = useRegimeClusters(regimeDays)
  const { data: transData, isLoading: loadingTrans } = useRegimeTransitions(180)
  const { data: embData, isLoading: loadingEmb } = usePatternEmbeddings()

  const posteriors: any[] = (bayesData as any)?.posteriors ?? []
  const clusters: any[] = (clustersData as any)?.clusters ?? []
  const embeddings: any[] = (embData as any)?.embeddings ?? []

  const bayesUpdate = useMutation({
    mutationFn: () => api.post('/analytics/bayesian/update').then(r => r.data),
    onSuccess: () => qc.invalidateQueries({ queryKey: ['bayesian-posteriors'] }),
  })

  const regimeDetect = useMutation({
    mutationFn: () => api.post('/analytics/regime-detect').then(r => r.data),
    onSuccess: () => {
      qc.invalidateQueries({ queryKey: ['regime-clusters'] })
      qc.invalidateQueries({ queryKey: ['regime-transitions'] })
    },
  })

  const patternsWithData = posteriors.filter((p: any) => p.sample_size > 0)
  const avgBayesWR = patternsWithData.length
    ? Math.round(patternsWithData.reduce((s: number, p: any) => s + p.bayesian_win_rate_pct, 0) / patternsWithData.length)
    : null
  const latestCluster = clusters[0]

  return (
    <div className="p-6 space-y-6">
      {/* Header */}
      <div className="flex items-start justify-between gap-4">
        <div>
          <h1 className="text-xl font-bold text-white flex items-center gap-2">
            <Brain className="w-5 h-5 text-purple-400" /> Analytics Avancées — Phase 4
          </h1>
          <p className="text-xs text-slate-500 mt-0.5">
            Bayesian updating · Clustering de régimes · Embeddings sémantiques
          </p>
        </div>
        <div className="flex gap-2">
          <button
            onClick={() => bayesUpdate.mutate()}
            disabled={bayesUpdate.isPending}
            className="flex items-center gap-1.5 px-3 py-1.5 text-xs bg-purple-600/20 hover:bg-purple-600/30 border border-purple-500/30 text-purple-300 rounded transition-colors disabled:opacity-50"
          >
            <RefreshCw className={clsx('w-3 h-3', bayesUpdate.isPending && 'animate-spin')} />
            Bayesian update
          </button>
          <button
            onClick={() => regimeDetect.mutate()}
            disabled={regimeDetect.isPending}
            className="flex items-center gap-1.5 px-3 py-1.5 text-xs bg-blue-600/20 hover:bg-blue-600/30 border border-blue-500/30 text-blue-300 rounded transition-colors disabled:opacity-50"
          >
            <RefreshCw className={clsx('w-3 h-3', regimeDetect.isPending && 'animate-spin')} />
            Détecter régime
          </button>
        </div>
      </div>

      {/* KPIs */}
      <div className="grid grid-cols-2 sm:grid-cols-4 gap-3">
        <div className="card">
          <div className="text-2xl font-bold text-purple-400 font-mono">
            {patternsWithData.length}
          </div>
          <div className="text-xs text-slate-500 mt-1">Patterns bayésiens actifs</div>
        </div>
        <div className="card">
          <div className="text-2xl font-bold text-white font-mono">
            {avgBayesWR !== null ? `${avgBayesWR}%` : '—'}
          </div>
          <div className="text-xs text-slate-500 mt-1">Win rate bayésien moyen</div>
        </div>
        <div className="card">
          <div className={clsx('text-2xl font-bold font-mono', latestCluster ? CLUSTER_COLORS[latestCluster.cluster_id]?.replace('bg-', 'text-') ?? 'text-slate-400' : 'text-slate-500')}>
            {latestCluster ? `C${latestCluster.cluster_id}` : '—'}
          </div>
          <div className="text-xs text-slate-500 mt-1">
            {latestCluster?.cluster_label ?? 'Aucun cluster'}
          </div>
        </div>
        <div className="card">
          <div className="text-2xl font-bold text-blue-400 font-mono">{embeddings.length}</div>
          <div className="text-xs text-slate-500 mt-1">Patterns vectorisés</div>
        </div>
      </div>

      {/* Bayesian Posteriors */}
      <div className="card">
        <div className="flex items-center justify-between mb-3">
          <div className="text-sm font-semibold text-white flex items-center gap-2">
            <Brain className="w-4 h-4 text-purple-400" />
            Posteriors bayésiens par pattern
            <span className="text-xs text-slate-500 font-normal">Beta(α,β) · IC 95%</span>
          </div>
          {bayesUpdate.data && (
            <span className="text-xs text-emerald-400">{bayesUpdate.data.message}</span>
          )}
        </div>
        {loadingBayes ? (
          <div className="space-y-2">{[1,2,3].map(i => <div key={i} className="h-8 bg-dark-700 animate-pulse rounded" />)}</div>
        ) : (
          <BayesianTable data={posteriors} />
        )}

        <div className="mt-3 p-3 bg-dark-700/40 rounded text-xs text-slate-500 border border-slate-700/20">
          <strong className="text-slate-400">Lecture :</strong> Prior GPT = probabilité annoncée par GPT-4o ·
          WR Bayésien = win rate observé avec lissage Laplace (β a priori faible) ·
          Dérive = écart posterior − prior · IC 95% basé sur la distribution Beta
        </div>
      </div>

      {/* Regime Clustering */}
      <div className="grid grid-cols-1 lg:grid-cols-2 gap-4">
        {/* Cluster timeline */}
        <div className="card">
          <div className="flex items-center justify-between mb-3">
            <div className="text-sm font-semibold text-white flex items-center gap-2">
              <Layers className="w-4 h-4 text-blue-400" />
              Historique des clusters
            </div>
            <select
              value={regimeDays}
              onChange={e => setRegimeDays(Number(e.target.value))}
              className="bg-dark-700 border border-slate-700 rounded px-2 py-1 text-xs text-slate-300"
            >
              <option value={30}>30 jours</option>
              <option value={90}>90 jours</option>
              <option value={180}>180 jours</option>
            </select>
          </div>
          {loadingClusters ? (
            <div className="h-20 bg-dark-700 animate-pulse rounded" />
          ) : (
            <ClusterTimeline data={clusters} />
          )}
        </div>

        {/* Transition matrix */}
        <div className="card">
          <div className="text-sm font-semibold text-white flex items-center gap-2 mb-3">
            <GitBranch className="w-4 h-4 text-blue-400" />
            Matrice de transition
            <span className="text-xs text-slate-500 font-normal">P(régime j | régime i)</span>
          </div>
          {loadingTrans ? (
            <div className="h-32 bg-dark-700 animate-pulse rounded" />
          ) : (
            <TransitionMatrix data={transData} />
          )}
        </div>
      </div>

      {/* Embeddings */}
      <div className="card">
        <div className="text-sm font-semibold text-white flex items-center gap-2 mb-3">
          <Cpu className="w-4 h-4 text-emerald-400" />
          Embeddings sémantiques
          <span className="text-xs text-slate-500 font-normal">
            text-embedding-3-small · Similarité cosinus remplace Jaccard
          </span>
        </div>
        {loadingEmb ? (
          <div className="h-20 bg-dark-700 animate-pulse rounded" />
        ) : (
          <EmbeddingsSummary data={embeddings} />
        )}
        <div className="mt-3 p-3 bg-dark-700/40 rounded text-xs text-slate-500 border border-slate-700/20">
          <strong className="text-slate-400">Comment ça marche :</strong> Chaque nouveau pattern suggéré est vectorisé et comparé
          aux patterns existants via similarité cosinus (seuil : 0.75). Si la similarité est &gt; 0.75,
          le pattern est rejeté comme doublon sémantique — plus précis que Jaccard qui ne voit que les mots communs.
        </div>
      </div>
    </div>
  )
}