// settings.jsx v12 — 系统设置：指标字典 · 分析提醒 · 数据备份 · 安全可靠性 // 职责：读写 app.jsx 传入的全局配置（metricConfig / scoringAlgo / riskConfig） // P1-D: ICCConfigSection — 力板指标 ICC 输入，持久化至 localStorage 'perf_v2_icc'，通过 DASHBOARD_DATA.ICC_USER 暴露 // P1-E: RiskTab — 四级交通灯（acwr/cmjDrop/mRSIDrop），替代旧双阈值结构 const { useState: sUseState, useRef: sUseRef, useMemo: sUseMemo, useEffect: sUseEffect } = React; // ────────────────────────────────────────────────────────────────────────── // Modal shell // ────────────────────────────────────────────────────────────────────────── function SettingsModal({ open, onClose, asPage, tab, onTabChange, groups, onGroupsChange, athletes, onAthletesChange, seasons, currentSeason, algo, onAlgoChange, riskConfig, onRiskConfigChange, trendConfig, onTrendConfigChange, onResetToDefaults, onDeleteAthlete, onCountAthleteData, onClearForceSessions, forceStorageUsageBytes, forceSessionStores, onForceBackupExport, onForceBackupImport, onForceTraceUsage, legacyImportPlanner, onApplyLegacyImport, getLegacyImportMapping, onSaveLegacyImportMapping, onSeasonsChange }) { if (!open && !asPage) return null; const tabs = [ { id: 'account', label: '账号与权限', icon: 'user', group: '工作区', description: '查看登录身份、工作区角色，并由管理员管理现有成员权限。' }, { id: 'metrics', label: '指标字典', icon: 'sliders', group: '指标字典', description: '管理指标名称、单位、方向与参考阈值；录入仍在测试页面完成。' }, { id: 'scoring', label: '评分与趋势', icon: 'target', group: '分析与提醒', description: '设置个体评分方式，以及团队趋势图的显示偏好。' }, { id: 'insights', label: '洞察规则', icon: 'star', group: '分析与提醒', description: '管理重点指标和洞察规则的触发范围。' }, { id: 'risk', label: '提醒阈值', icon: 'bolt', group: '分析与提醒', description: '配置现有提醒阈值；这些提示不替代专业判断。' }, { id: 'data', label: '数据与备份', icon: 'download', group: '数据与备份', description: '导入、导出、Force 专用备份，以及本地数据清理。' }, { id: 'quality', label: '可靠性与审计', icon: 'history', group: '安全与可靠性', description: '查看已录入数据覆盖率、异常值与测量可靠性。' }, ]; const activeTab = tabs.find(t => t.id === tab) || tabs[0]; const tabGroups = [ { label: '工作区', tabs: tabs.filter(t => t.group === '工作区') }, { label: '指标字典', tabs: tabs.filter(t => t.group === '指标字典') }, { label: '分析与提醒', tabs: tabs.filter(t => t.group === '分析与提醒') }, { label: '数据与备份', tabs: tabs.filter(t => t.group === '数据与备份') }, { label: '安全与可靠性', tabs: tabs.filter(t => t.group === '安全与可靠性') }, ]; return (
e.stopPropagation()} style={asPage ? { background: 'var(--panel)', border: '1px solid var(--border)', borderRadius: 12, width: '100%', maxWidth: 1420, margin: '0 auto', minHeight: 0, display: 'flex', flexDirection: 'column', overflow: 'hidden', } : { background: 'var(--panel)', border: '1px solid var(--border-strong)', borderRadius: 12, width: 880, maxWidth: '100%', maxHeight: '90vh', boxShadow: 'var(--mac-shadow, 0 20px 60px rgba(0,0,0,.5))', display: 'flex', flexDirection: 'column', overflow: 'hidden', animation: 'fadeUp .25s ease both', }}> {/* header */}
System settings

系统设置 · {activeTab.label}

{activeTab.description}
{!asPage && }
{/* body */}
{tab === 'account' && } {tab === 'metrics' && } {tab === 'scoring' && } {tab === 'insights' && } {tab === 'quality' && } {tab === 'data' && } {tab === 'risk' && }
); } const ACCOUNT_ROLE_COPY = { owner: ['所有者', '完整权限，并负责工作区归属。'], admin: ['管理员', '管理成员、数据与审核流程。'], scientist: ['运动科学家', '写入监控数据并确认审核结果。'], coach: ['教练', '维护运动员、日常记录与训练草案。'], viewer: ['只读成员', '仅查看获准的工作区记录。'], }; const ACCOUNT_CAPABILITY_COPY = { 'members.manage': '管理成员', 'athletes.write': '编辑运动员', 'monitoring.write': '写入监控摘要', 'reviews.confirm': '确认审核结果', 'records.read': '读取记录', 'audit.read': '查看审计记录', 'daily.write': '写入日常记录', 'drafts.write': '创建训练草案', }; function AccountPermissionsTab({ athletes = [] }) { const runtime = window.AxisAuthRuntime; const context = runtime && runtime.getContext ? runtime.getContext() : null; const canManage = !!(runtime && runtime.can && runtime.can('members.manage') && context?.mode === 'cloud'); const [members, setMembers] = sUseState([]); const [status, setStatus] = sUseState(canManage ? 'loading' : 'idle'); const [message, setMessage] = sUseState(''); const [syncing, setSyncing] = sUseState(false); const [syncMessage, setSyncMessage] = sUseState(''); const loadMembers = React.useCallback(async () => { if (!canManage) return; setStatus('loading'); setMessage(''); try { setMembers(await runtime.listMembers()); setStatus('ready'); } catch (error) { setStatus('error'); setMessage(String(error?.message || error)); } }, [canManage]); sUseEffect(() => { loadMembers(); }, [loadMembers]); if (!context) return
登录上下文尚未就绪。
; const capabilities = runtime.capabilities ? runtime.capabilities() : []; const roleCopy = ACCOUNT_ROLE_COPY[context.role] || ACCOUNT_ROLE_COPY.viewer; async function changeRole(member, role) { setMessage(''); try { await runtime.updateMemberRole(member.id, role); setMembers(current => current.map(row => row.id === member.id ? { ...row, role } : row)); setMessage('成员角色已更新。'); } catch (error) { setMessage(String(error?.message || error)); } } async function syncStructuredData() { if (!window.confirm('将当前花名册、人口学信息和已保存的数值指标结果同步到当前云端工作区。原始曲线、CSV、知识库和 AI 私有资料不会上传。继续？')) return; setSyncing(true); setSyncMessage(''); try { const result = await runtime.syncStructuredSnapshot(athletes); setSyncMessage(`同步完成：${result.athleteCount} 名运动员，${result.metricCount} 条指标结果。`); } catch (error) { setSyncMessage(`同步失败：${String(error?.message || error)}`); } finally { setSyncing(false); } } return (
当前身份

{context.displayName || context.email}

{context.email}

工作区{context.workspaceName}{context.mode === 'local' ? '仅本机模式' : 'Supabase 云端工作区'}
当前角色

{roleCopy[0]}

{context.role}

{roleCopy[1]}

{capabilities.map(capability => {ACCOUNT_CAPABILITY_COPY[capability] || capability})}
成员权限

现有工作区成员

{canManage && }
{context.mode === 'local' &&

本地模式没有远程成员。部署环境登录后才启用角色管理。

} {context.mode === 'cloud' && !canManage &&

只有所有者或管理员可以调整成员角色。

} {status === 'loading' &&

正在读取成员…

} {status === 'error' &&

无法读取成员：{message}

} {canManage && status === 'ready' &&
{members.map(member => { const profile = member.profiles || {}; const isSelf = member.user_id === context.userId; const choices = window.AxisPermissionModel.roles.filter(role => role !== 'owner' || member.role === 'owner'); return
{profile.display_name || profile.email || member.user_id}{profile.email || member.user_id}{isSelf ? ' · 当前账号' : ''}
; })}
} {message && status !== 'error' &&

{message}

}

MVP 不开放自助注册或伪装邀请。新账号由管理员在 Supabase 控制台预建，再在此分配角色。

结构化同步

运动员档案与指标结果

上传花名册、人口学信息及用户已保存的数值指标结果。原始力台曲线、CSV、知识库、AI 私有记忆与报告文件始终留在本机。

{context.mode === 'cloud' && runtime.can('athletes.write') ? :

当前模式或角色不允许上传结构化数据。

} {syncMessage &&

{syncMessage}

}
{context.mode === 'cloud' && }
); } function SettingsIARail({ activeTab, tabGroups, onTabChange }) { return ( ); } // ────────────────────────────────────────────────────────────────────────── // Metrics tab — editable table of all metrics, grouped // ────────────────────────────────────────────────────────────────────────── function MetricsTab({ groups, onGroupsChange, athletes, onAthletesChange }) { const [selectedGroupId, setSelectedGroupId] = sUseState(groups[0]?.id || ''); const [groupSearch, setGroupSearch] = sUseState(''); const [metricSearch, setMetricSearch] = sUseState(''); const [newGroupLabel, setNewGroupLabel] = sUseState(''); const metricGridColumns = 'minmax(180px,1.45fr) minmax(72px,.55fr) minmax(130px,.85fr) minmax(140px,1fr) minmax(210px,1.45fr) 32px'; const selectedGroupIndex = groups.findIndex(g => g.id === selectedGroupId); const selectedGroup = groups[selectedGroupIndex] || groups[0] || null; sUseEffect(() => { if (!groups.length) return; if (!groups.some(group => group.id === selectedGroupId)) setSelectedGroupId(groups[0].id); }, [groups, selectedGroupId]); const stripMetricValues = (metricIds) => { const ids = new Set(metricIds); onAthletesChange(athletes.map(athlete => ({ ...athlete, seasons: Object.fromEntries(Object.entries(athlete.seasons || {}).map(([season, values]) => [ season, Object.fromEntries(Object.entries(values || {}).filter(([metricId]) => !ids.has(metricId))), ])), ...(athlete.provenance ? { provenance: Object.fromEntries(Object.entries(athlete.provenance).map(([season, values]) => [ season, Object.fromEntries(Object.entries(values || {}).filter(([metricId]) => !ids.has(metricId))), ])), } : {}), }))); }; const updateMetric = (gIdx, mIdx, patch) => { const next = groups.map((g, i) => { if (i !== gIdx) return g; return { ...g, metrics: g.metrics.map((m, j) => j === mIdx ? { ...m, ...patch } : m) }; }); onGroupsChange(next); }; const removeMetric = (gIdx, mIdx) => { const removed = groups[gIdx].metrics[mIdx]; if (!removed || !window.confirm(`删除指标“${removed.label}”？所有运动员历史记录中的该指标值也会被删除。`)) return; const next = groups.map((g, i) => i === gIdx ? { ...g, metrics: g.metrics.filter((_, j) => j !== mIdx) } : g); onGroupsChange(next); stripMetricValues([removed.id]); }; const addMetric = (gIdx) => { const newId = `custom_${Date.now()}`; // No manual worst/avg/best — auto-computed once data is recorded. const newM = { id: newId, label: window.t('New metric'), unit: '', dir: 'higher', worst: 0, avg: 0, best: 0 }; const next = groups.map((g, i) => i === gIdx ? { ...g, metrics: [...g.metrics, newM] } : g); onGroupsChange(next); // seed empty values onAthletesChange(athletes.map(a => ({ ...a, seasons: Object.fromEntries(Object.entries(a.seasons).map(([s, v]) => [s, { ...v }])), }))); }; const renameGroup = (gIdx, label) => { onGroupsChange(groups.map((g, i) => i === gIdx ? { ...g, label } : g)); }; const addGroup = () => { const label = newGroupLabel.trim(); if (!label) return; const id = `custom_group_${Date.now()}`; const accents = ['#3b82f6', '#14b8a6', '#f59e0b', '#8b5cf6', '#ef4444']; onGroupsChange([...groups, { id, label, accent: accents[groups.length % accents.length], metrics: [] }]); setSelectedGroupId(id); setNewGroupLabel(''); setMetricSearch(''); }; const removeGroup = () => { if (!selectedGroup || groups.length <= 1) return; const metricIds = (selectedGroup.metrics || []).map(metric => metric.id); if (!window.confirm(`删除类别“${selectedGroup.label}”及其中 ${metricIds.length} 个指标？相关历史值也会被删除。`)) return; const next = groups.filter(group => group.id !== selectedGroup.id); onGroupsChange(next); stripMetricValues(metricIds); setSelectedGroupId(next[0]?.id || ''); setMetricSearch(''); }; const filteredGroups = groups.filter(group => !groupSearch.trim() || group.label.toLowerCase().includes(groupSearch.trim().toLowerCase()) ); const visibleMetrics = (selectedGroup?.metrics || []).map((metric, index) => ({ metric, index })).filter(({ metric }) => { const query = metricSearch.trim().toLowerCase(); return !query || `${metric.label} ${metric.id} ${metric.unit || ''}`.toLowerCase().includes(query); }); return (
Edit each metric's label, unit, and direction. The normative worst / avg / best range is computed automatically from the data you record — no need to set it by hand. Use Fixed Range when a metric has a clinical or sport-science reference threshold: values past the threshold are flagged with a red/green indicator on the athlete card.
{selectedGroup ? ( <>
renameGroup(selectedGroupIndex, e.target.value)} style={{ minWidth: 0, flex: 1, background: 'transparent', border: 0, outline: 'none', color: 'var(--text)', fontSize: 14, fontWeight: 650 }}/>
setMetricSearch(e.target.value)} placeholder="搜索名称、ID 或单位…" style={{ width: '100%', background: 'var(--panel-2)', border: '1px solid var(--border)', borderRadius: 6, padding: '7px 9px', color: 'var(--text)', fontSize: 12 }}/>
名称
单位
方向
自动范围
固定范围
{visibleMetrics.map(({ metric: m, index: mIdx }) => (
updateMetric(selectedGroupIndex, mIdx, { label: v })}/>
{m.id}
updateMetric(selectedGroupIndex, mIdx, { unit: v })}/> updateMetric(selectedGroupIndex, mIdx, { dir: v })} options={[ { v: 'higher', label: window.t('↑ higher better') }, { v: 'lower', label: window.t('↓ lower better') }, { v: 'neutral', label: window.t('– neutral') }, ]}/> updateMetric(selectedGroupIndex, mIdx, { fixedRange: fr })}/>
))} {visibleMetrics.length === 0 &&
该类别下没有匹配指标。可清除搜索或新增指标。
} ) :
请先新增一个指标类别。
}
); } function MetricGovernanceNote() { return ( Metric governance. Settings defines labels, units, direction, and reference ranges. Field Test captures observations. Reviewed evidence appears only after a captured source is reviewed by the sports scientist. ); } const fmtNum = (x) => { if (x == null || isNaN(x)) return '—'; if (Math.abs(x) >= 100) return Math.round(x).toString(); if (Math.abs(x) >= 10) return (Math.round(x * 10) / 10).toString(); return (Math.round(x * 100) / 100).toString(); }; function AutoRangeChip({ metric }) { const hasData = metric.worst !== metric.best; if (!hasData) { return (
no data yet
); } return (
{fmtNum(metric.worst)} {fmtNum(metric.avg)} {fmtNum(metric.best)}
); } function FixedRangeCell({ metric, onChange }) { const fr = metric.fixedRange; const enabled = !!fr; if (!enabled) { return ( ); } const good = fr.goodWhen; // 'above' | 'below' return (
onChange({ ...fr, threshold: e.target.value === '' ? 0 : +e.target.value })} placeholder="Threshold" style={{ background: 'var(--panel)', border: '1px solid var(--border)', borderRadius: 4, padding: '5px 8px', color: 'var(--text)', fontSize: 12, fontFamily: 'var(--font-mono)', textAlign: 'right', outline: 'none', minWidth: 0, width: '100%', }} title={`Threshold value in ${metric.unit || '—'}`} onFocus={(e) => e.target.style.borderColor = 'var(--accent)'} onBlur={(e) => e.target.style.borderColor = 'var(--border)'} />
); } const CellInput = ({ value, onChange, numeric }) => ( onChange(e.target.value)} type={numeric ? 'number' : 'text'} step="any" style={{ background: 'var(--panel)', border: '1px solid var(--border)', borderRadius: 4, padding: '5px 8px', color: 'var(--text)', fontSize: 12, outline: 'none', fontFamily: numeric ? 'var(--font-mono)' : 'inherit', textAlign: numeric ? 'right' : 'left', width: '100%', minWidth: 0, }} onFocus={(e) => e.target.style.borderColor = 'var(--accent)'} onBlur={(e) => e.target.style.borderColor = 'var(--border)'} /> ); const CellSelect = ({ value, onChange, options }) => ( ); // ────────────────────────────────────────────────────────────────────────── // Scoring tab // ────────────────────────────────────────────────────────────────────────── const ALGOS = [ { id: 'range', name: 'Range mapping', formula: 'score = (v − worst) / (best − worst) · 100', blurb: 'Linear projection of the athlete\'s value between user-defined worst & best benchmarks. Scores are stable across cohort changes. Best when normative benchmarks are well known.', pros: ['Stable across squad changes', 'Reflects absolute standards', 'Intuitive to explain'], cons: ['Sensitive to manually-set thresholds', 'Ignores squad distribution'], }, { id: 'zscore', name: 'Z-score', formula: 'z = (v − μ) / σ ; score = clamp((z + 2) / 4) · 100', blurb: 'Each value becomes its distance from the squad mean in standard deviations, then mapped so ±2σ covers 0–100. For metrics where lower is better, sign is flipped.', pros: ['Adapts to squad distribution', 'Statistically interpretable', 'Comparable across metrics'], cons: ['Shifts when squad changes', 'Requires n ≥ ~6 for stable σ'], }, { id: 'percentile', name: 'Percentile rank', formula: 'score = rank(v) / N · 100 (within squad, current season)', blurb: 'Score is the share of teammates the athlete outperforms on a given metric. Easy to communicate ("90th percentile in sprint").', pros: ['Most intuitive', 'Robust to outliers', 'Ordinal'], cons: ['Loses magnitude of difference', 'Top performer is always 100'], }, { id: 'swc', name: 'SWC (Smallest Worthwhile Change)', formula: 'SWC = 0.2 · σ; score = clamp(0.5 + (v − μ) / (10·SWC)) · 100', blurb: 'Built on Hopkins\' practically meaningful change: 0.2 × between-athlete SD is the threshold of a real effect. Athletes are scored in multiples of SWC from the mean (±5 SWC covers 0–100).', pros: ['Sport-science standard', 'Aligns with practical thresholds', 'Highlights meaningful gaps'], cons: ['Same SD dependency as Z-score', 'Less intuitive for non-coaches'], }, { id: 'modzscore', name: 'Modified Z (individual baseline)', formula: 'z = (v − T1_mean) / T1_SD · score = clamp((z + 2) / 4) · 100', blurb: 'Uses each athlete\'s own first-season (T1) values as the personal baseline — not the squad mean. Scores reflect change from the individual\'s starting point, eliminating the bias introduced when the whole team improves together. Falls back to squad Z-score for athletes without T1 history.', pros: ['Individual-centred', 'Unaffected by squad-wide improvement', 'McGuigan 2017 standard'], cons: ['Requires T1 history (≥ 1 season)', 'Cross-athlete comparisons less direct'], }, ]; function ScoringTab({ algo, onAlgoChange, trendConfig, onTrendConfigChange }) { const tc = trendConfig || { showDataLabels: false, showBenchmarkLine: false }; const updateTrend = (patch) => onTrendConfigChange && onTrendConfigChange({ ...tc, ...patch }); return (
Choose how raw metric values are mapped onto a 0–100 score. The choice affects radar, group scores, leaderboard, and "Standout vs Squad" tile. Range mapping uses the thresholds you set per metric; the others derive everything from the current squad.
{ALGOS.map(a => { const active = a.id === algo; return ( ); })}
{/* ── Trend Display options ── */}
Optional overlays for the Team Fitness Trend chart. These layers help coaches read absolute values and compare against reference levels at a glance.
updateTrend({ showDataLabels: !tc.showDataLabels })} title="Raw value labels" desc="Print the score value directly on every data point — no hover needed. Useful for reading absolute numbers in screenshots or reports." badge="Option 1" /> updateTrend({ showBenchmarkLine: !tc.showBenchmarkLine })} title="External benchmark line" desc="Draw a dashed reference line at score 50 (the normative midpoint in Range mapping). Shows whether the team is above or below an external population average." badge="Option 3" />
); } function TrendToggleCard({ enabled, onToggle, title, desc, badge }) { return (
{title} {badge && ( {badge} )}
{desc}
{/* toggle switch */}