diff --git a/components.d.ts b/components.d.ts index 21fa9bb..b7cb66b 100644 --- a/components.d.ts +++ b/components.d.ts @@ -34,6 +34,7 @@ declare module '@vue/runtime-core' { ElPagination: typeof import('element-plus/es')['ElPagination'] ElProgress: typeof import('element-plus/es')['ElProgress'] ElRadio: typeof import('element-plus/es')['ElRadio'] + ElRadioButton: typeof import('element-plus/es')['ElRadioButton'] ElRadioGroup: typeof import('element-plus/es')['ElRadioGroup'] ElRow: typeof import('element-plus/es')['ElRow'] ElSelect: typeof import('element-plus/es')['ElSelect'] diff --git a/src/views/pages/Analysis.vue b/src/views/pages/Analysis.vue index 5766284..b98e89f 100644 --- a/src/views/pages/Analysis.vue +++ b/src/views/pages/Analysis.vue @@ -2,17 +2,61 @@
-

数据分析

-
+

订单数据分析

+
+ +
+ +
+ + + + + + + + - + + +
+
+ + +
+
+
+ {{ trendDirection }} {{ Math.abs(trendPercentage).toFixed(1) }}% +
+
{{ periodLabel }}趋势
+
+
+
{{ statistics.growth.toFixed(1) }}%
+
环比增长
+
+
+
{{ statistics.volatility.toFixed(1) }}%
+
波动率
@@ -21,56 +65,159 @@
平均值
{{ statistics.mean }}
+
{{ getDataUnit() }}
最大值
{{ statistics.max }}
+
峰值
最小值
{{ statistics.min }}
+
谷值
-
总数
+
总计
{{ statistics.sum }}
+
累计
标准差
{{ statistics.stdDev }}
+
离散度
+
+
+
中位数
+
{{ statistics.median }}
+
中值
+
+
+ + +
+

数据对比分析

+
+ + 周对比 + 月对比 + 季度对比 + + +
+
+
+
当前周期
+
{{ currentPeriodSum }}
+
+
+
上个周期
+ +
+
+
增长率
+
+ {{ growthRate > 0 ? '+' : '' }}{{ growthRate.toFixed(1) }}% +
+
-

当前数据

+
+

{{ getChartTitle() }}

+
+ + 折线图 + 柱状图 + 面积图 + +
+



-
-

未来趋势

- - 线性回归 - 指数回归 - 多项式回归 - ARIMA回归 - +
+
+

未来趋势预测

+ + 线性回归 + 指数回归 + 多项式回归 + ARIMA回归 + +
+
+ + 天 +
+
+
+
+
+ 预测准确度: + {{ predictionAccuracy.toFixed(1) }}% +
+
+ 置信区间: + 95% +
+ +
+

数据洞察

+
+
+
+
📈
+
+

趋势分析

+

{{ getTrendInsight() }}

+
+
+
+
🎯
+
+

异常检测

+

{{ getAnomalyInsight() }}

+
+
+
+
💡
+
+

建议

+

{{ getRecommendation() }}

+
+
+
+
+
-

编辑数据

+

编辑{{ getDataUnit() }}数据

-
- - +
+ + +
+
+ + + +
+
@@ -86,7 +233,7 @@ import { ref, computed, watch } from 'vue'; import VChart from 'vue-echarts'; import { use } from 'echarts/core'; import { CanvasRenderer } from 'echarts/renderers'; -import { LineChart } from 'echarts/charts'; +import { LineChart, BarChart } from 'echarts/charts'; import { TitleComponent, TooltipComponent, @@ -95,97 +242,328 @@ import { } from 'echarts/components'; import * as echarts from 'echarts/core'; -const ModelMethod = ref('1') +// 新增响应式数据 +const dataType = ref('amount'); +const chartType = ref('line'); +const dateRange = ref([]); +const comparisonPeriod = ref('week'); +const predictionDays = ref(5); +const showEditDialog = ref(false); + +// 数据集合 +const originalData = ref({ + amount: [120, 132, 301, 134, 90, 230, 210, 100, 400], + count: [45, 52, 68, 41, 33, 78, 65, 48, 89], + customers: [28, 31, 45, 29, 21, 42, 38, 26, 56] +}); + +const chartData = computed(() => originalData.value[dataType.value]); +const tempChartData = ref([...chartData.value]); + +const ModelMethod = ref('1'); +const { graphic } = echarts; // 注册必要的组件 use([ CanvasRenderer, LineChart, + BarChart, TitleComponent, TooltipComponent, LegendComponent, GridComponent ]); -const { graphic } = echarts; - -// 响应式数据 -const chartData = ref([120, 132, 301, 134, 90, 230, 210, 100, 400]); -const showEditDialog = ref(false); -const tempChartData = ref([...chartData.value]); - -// 计算统计信息 +// 增强的统计信息 const statistics = computed(() => { const data = chartData.value; const sum = data.reduce((acc, val) => acc + val, 0); const mean = Math.round((sum / data.length) * 100) / 100; const max = Math.max(...data); const min = Math.min(...data); + + // 中位数 + const sorted = [...data].sort((a, b) => a - b); + const median = sorted.length % 2 === 0 + ? (sorted[sorted.length / 2 - 1] + sorted[sorted.length / 2]) / 2 + : sorted[Math.floor(sorted.length / 2)]; - // 计算方差 + // 方差和标准差 const variance = Math.round((data.reduce((acc, val) => acc + Math.pow(val - mean, 2), 0) / data.length) * 100) / 100; - - // 计算标准差 const stdDev = Math.round(Math.sqrt(variance) * 100) / 100; + // 增长率 + const growth = data.length > 1 ? + ((data[data.length - 1] - data[data.length - 2]) / data[data.length - 2]) * 100 : 0; + + // 波动率 (变异系数) + const volatility = mean !== 0 ? (stdDev / mean) * 100 : 0; + return { - mean, + mean: Math.round(mean), max, min, sum, - stdDev + stdDev, + median: Math.round(median), + growth, + volatility }; }); -// 图表配置 -const mapOptions = computed(() => ({ - xAxis: { - type: 'category', - boundaryGap: false, - data: chartData.value.map((_, index) => `${index + 1}`), - }, - yAxis: { - type: 'value', - }, - grid: { - top: '5%', - left: '3%', - right: '3%', - bottom: '5%', - containLabel: true, - }, - color: ['#1976d2'], - tooltip: { - trigger: 'axis', - backgroundColor: 'rgba(0,0,0,0.8)', - borderColor: '#1976d2', - textStyle: { - color: '#fff' - } - }, - series: [ - { - type: 'line', - areaStyle: { - color: new graphic.LinearGradient(0, 0, 0, 1, [ - { - offset: 0, - color: 'rgba(25, 118, 210, 0.8)', - }, - { - offset: 1, - color: 'rgba(25, 118, 210, 0)', - }, - ]), - }, - lineStyle: { - width: 4, - }, - symbolSize: 8, +// 趋势分析 +const trendAnalysis = computed(() => { + const data = chartData.value; + if (data.length < 2) return { direction: 'stable', percentage: 0 }; + + const recent = data.slice(-3); + const early = data.slice(0, 3); + + const recentAvg = recent.reduce((sum, val) => sum + val, 0) / recent.length; + const earlyAvg = early.reduce((sum, val) => sum + val, 0) / early.length; + + const percentage = earlyAvg !== 0 ? ((recentAvg - earlyAvg) / earlyAvg) * 100 : 0; + + return { + direction: percentage > 5 ? 'up' : percentage < -5 ? 'down' : 'stable', + percentage + }; +}); + +const trendDirection = computed(() => { + const trend = trendAnalysis.value.direction; + return trend === 'up' ? '↗' : trend === 'down' ? '↘' : '→'; +}); + +const trendClass = computed(() => { + return `trend-${trendAnalysis.value.direction}`; +}); + +const trendPercentage = computed(() => trendAnalysis.value.percentage); + +const periodLabel = computed(() => { + const labels = { week: '周', month: '月', quarter: '季度' }; + return labels[comparisonPeriod.value] || '周期'; +}); + +// 对比数据 +const currentPeriodSum = computed(() => { + const data = chartData.value; + const halfLength = Math.floor(data.length / 2); + return data.slice(halfLength).reduce((sum, val) => sum + val, 0); +}); + +const previousPeriodSum = computed(() => { + const data = chartData.value; + const halfLength = Math.floor(data.length / 2); + return data.slice(0, halfLength).reduce((sum, val) => sum + val, 0); +}); + +const growthRate = computed(() => { + return previousPeriodSum.value !== 0 + ? ((currentPeriodSum.value - previousPeriodSum.value) / previousPeriodSum.value) * 100 + : 0; +}); + +const growthRateClass = computed(() => { + return growthRate.value > 0 ? 'positive' : growthRate.value < 0 ? 'negative' : 'neutral'; +}); + +const predictionAccuracy = computed(() => { + // 模拟预测准确度计算 + const baseAccuracy = 85; + const dataLength = chartData.value.length; + const variability = statistics.value.volatility; + + let accuracy = baseAccuracy - Math.min(variability * 0.5, 20) + Math.min(dataLength * 2, 10); + return Math.max(60, Math.min(95, accuracy)); +}); + +// 工具函数 +const getDataUnit = () => { + const units = { amount: '元', count: '单', customers: '人' }; + return units[dataType.value] || ''; +}; + +const getDataTypeLabel = () => { + const labels = { amount: '订单金额', count: '订单数量', customers: '客户数' }; + return labels[dataType.value] || '数据'; +}; + +const getChartTitle = () => { + const titles = { + amount: '订单金额趋势', + count: '订单数量趋势', + customers: '客户数量趋势' + }; + return titles[dataType.value] || '数据趋势'; +}; + +// 数据操作方法 +const switchDataType = () => { + tempChartData.value = [...chartData.value]; +}; + +const insertRandomData = () => { + const ranges = { + amount: [50, 500], + count: [20, 100], + customers: [10, 80] + }; + const [min, max] = ranges[dataType.value]; + const newValue = Math.floor(Math.random() * (max - min + 1)) + min; + originalData.value[dataType.value].push(newValue); +}; + +const exportData = () => { + const data = chartData.value; + const csv = data.map((value, index) => `${index + 1},${value}`).join('\n'); + const blob = new Blob([`序号,${getDataTypeLabel()}\n${csv}`], { type: 'text/csv' }); + const url = URL.createObjectURL(blob); + const a = document.createElement('a'); + a.href = url; + a.download = `${getDataTypeLabel()}_${new Date().toISOString().split('T')[0]}.csv`; + a.click(); + URL.revokeObjectURL(url); +}; + +const refreshData = () => { + // 模拟数据刷新 + const ranges = { + amount: [80, 450], + count: [25, 95], + customers: [15, 75] + }; + const [min, max] = ranges[dataType.value]; + originalData.value[dataType.value] = originalData.value[dataType.value].map(() => + Math.floor(Math.random() * (max - min + 1)) + min + ); +}; + +const filterDataByDate = () => { + // 模拟日期筛选逻辑 + if (dateRange.value && dateRange.value.length === 2) { + console.log('筛选日期范围:', dateRange.value); + // 这里可以实现真实的日期筛选逻辑 + } +}; + +const generateComparisonData = () => { + // 模拟生成对比数据 + console.log('生成', comparisonPeriod.value, '对比数据'); +}; + +// 批量操作 +const batchMultiply = () => { + tempChartData.value = tempChartData.value.map(val => Math.round(val * 2)); +}; + +const batchAdd = () => { + tempChartData.value = tempChartData.value.map(val => val + 100); +}; + +const resetData = () => { + tempChartData.value = [120, 132, 301, 134, 90, 230, 210, 100, 400]; +}; + +const deleteDataPoint = (index) => { + tempChartData.value.splice(index, 1); +}; + +const addDataPoint = () => { + const ranges = { + amount: [50, 500], + count: [20, 100], + customers: [10, 80] + }; + const [min, max] = ranges[dataType.value]; + tempChartData.value.push(Math.floor(Math.random() * (max - min + 1)) + min); +}; + +// 洞察分析 +const getTrendInsight = () => { + const trend = trendAnalysis.value; + if (trend.direction === 'up') { + return `数据呈上升趋势，增长${Math.abs(trend.percentage).toFixed(1)}%，表现良好。`; + } else if (trend.direction === 'down') { + return `数据呈下降趋势，下降${Math.abs(trend.percentage).toFixed(1)}%，需要关注。`; + } + return '数据相对稳定，波动较小。'; +}; + +const getAnomalyInsight = () => { + const data = chartData.value; + const mean = statistics.value.mean; + const stdDev = statistics.value.stdDev; + const anomalies = data.filter(val => Math.abs(val - mean) > 2 * stdDev); + + if (anomalies.length > 0) { + return `检测到${anomalies.length}个异常值，建议进一步分析原因。`; + } + return '未检测到明显异常值，数据质量良好。'; +}; + +const getRecommendation = () => { + const growth = statistics.value.growth; + const volatility = statistics.value.volatility; + + if (growth > 10 && volatility < 20) { + return '保持当前策略，继续扩大市场份额。'; + } else if (growth < -10) { + return '建议优化营销策略，提升业务表现。'; + } else if (volatility > 30) { + return '数据波动较大，建议稳定业务流程。'; + } + return '继续监控关键指标，优化业务策略。'; +}; + +// 增强的图表配置 +const mapOptions = computed(() => { + const baseOption = { + xAxis: { + type: 'category', + boundaryGap: chartType.value === 'bar', + data: chartData.value.map((_, index) => `${index + 1}`), + }, + yAxis: { + type: 'value', + name: getDataUnit(), + }, + grid: { + top: '5%', + left: '3%', + right: '3%', + bottom: '5%', + containLabel: true, + }, + color: ['#1976d2'], + tooltip: { + trigger: 'axis', + backgroundColor: 'rgba(0,0,0,0.8)', + borderColor: '#1976d2', + textStyle: { color: '#fff' }, + formatter: (params) => { + const point = params[0]; + return `${getDataTypeLabel()}: ${point.value}${getDataUnit()}`; + } + }, + series: [{ + type: chartType.value === 'area' ? 'line' : chartType.value, data: chartData.value, - } - ], -})); + smooth: chartType.value === 'line', + symbolSize: 8, + lineStyle: chartType.value === 'line' ? { width: 4 } : undefined, + areaStyle: chartType.value === 'area' ? { + color: new graphic.LinearGradient(0, 0, 0, 1, [ + { offset: 0, color: 'rgba(25, 118, 210, 0.8)' }, + { offset: 1, color: 'rgba(25, 118, 210, 0)' } + ]) + } : undefined + }] + }; + + return baseOption; +}); // 线性回归预测 function linearRegression(data) { @@ -298,51 +676,44 @@ const predictData = computed(() => { const data = chartData.value; const predictions = []; - // 确保有足够的数据进行预测 - if (data.length < 3) return Array(5).fill(data[data.length - 1] || 0); + if (data.length < 3) return Array(predictionDays.value).fill(data[data.length - 1] || 0); - for (let i = 0; i < 5; i++) { + for (let i = 0; i < predictionDays.value; i++) { let predictedValue; const currentData = [...data, ...predictions]; - const len = currentData.length; switch (ModelMethod.value) { - case '1': // 线性回归 + case '1': predictedValue = linearRegression(currentData); break; - case '2': // 指数平滑 + case '2': predictedValue = exponentialSmoothing(currentData, 0.3); break; - case '3': // 多项式回归 (二次) + case '3': predictedValue = polynomialRegression(currentData, 2); break; - case '4': // ARIMA简化版本 + case '4': predictedValue = arimaSimplified(currentData); break; } - // 季节性调整 (模拟周期性波动) - const seasonalFactor = Math.sin((len + i) * Math.PI / 6) * 0.1 + 1; + const seasonalFactor = Math.sin((currentData.length + i) * Math.PI / 6) * 0.1 + 1; predictedValue *= seasonalFactor; - // 趋势衰减 (距离越远，趋势影响越小) const trendDecay = Math.exp(-i * 0.1); const baseline = currentData.slice(-Math.min(5, currentData.length)) .reduce((sum, val) => sum + val, 0) / Math.min(5, currentData.length); predictedValue = baseline + (predictedValue - baseline) * trendDecay; - // 添加渐减的随机噪声 const noiseIntensity = 15 * Math.exp(-i * 0.3); const noise = (Math.random() - 0.5) * noiseIntensity; - // 确保预测值合理 predictedValue = Math.max(0, Math.round(predictedValue + noise)); - // 异常值检测和修正 if (predictions.length > 0) { const lastPrediction = predictions[predictions.length - 1]; - const maxChange = Math.abs(lastPrediction * 0.3); // 最大变化30% + const maxChange = Math.abs(lastPrediction * 0.3); if (Math.abs(predictedValue - lastPrediction) > maxChange) { const direction = predictedValue > lastPrediction ? 1 : -1; @@ -360,13 +731,14 @@ const predictOptions = computed(() => ({ xAxis: { type: 'category', boundaryGap: false, - data: predictData.value.map((_, index) => `${index + chartData.value.length + 1}`), + data: predictData.value.map((_, index) => `预测${index + 1}`), }, yAxis: { type: 'value', + name: getDataUnit(), }, grid: { - top: '5%', + top: '10%', left: '3%', right: '3%', bottom: '5%', @@ -377,33 +749,25 @@ const predictOptions = computed(() => ({ trigger: 'axis', backgroundColor: 'rgba(0,0,0,0.8)', borderColor: '#dccc13', - textStyle: { - color: '#fff' + textStyle: { color: '#fff' }, + formatter: (params) => { + const point = params[0]; + return `预测${getDataTypeLabel()}: ${point.value}${getDataUnit()}`; } }, - series: [ - { - type: 'line', - areaStyle: { - color: new graphic.LinearGradient(0, 0, 0, 1, [ - { - offset: 0, - color: 'rgba(255, 246, 143, 0.8)', - }, - { - offset: 1, - color: 'rgba(255, 246, 143, 0)', - }, - ]), - }, - smooth: true, - lineStyle: { - width: 4, - }, - symbolSize: 8, - data: predictData.value, - } - ], + series: [{ + type: 'line', + areaStyle: { + color: new graphic.LinearGradient(0, 0, 0, 1, [ + { offset: 0, color: 'rgba(255, 246, 143, 0.8)' }, + { offset: 1, color: 'rgba(255, 246, 143, 0)' } + ]) + }, + smooth: true, + lineStyle: { width: 4 }, + symbolSize: 8, + data: predictData.value, + }] })); // 方法 @@ -413,7 +777,7 @@ const closeDialog = () => { }; const saveData = () => { - chartData.value = [...tempChartData.value]; + originalData.value[dataType.value] = [...tempChartData.value]; showEditDialog.value = false; }; @@ -438,6 +802,8 @@ watch(showEditDialog, (newVal) => { align-items: center; margin-bottom: 20px; padding: 0 10px; + flex-wrap: wrap; + gap: 15px; } .title { @@ -446,6 +812,10 @@ watch(showEditDialog, (newVal) => { font-weight: 600; } +.date-filter { + min-width: 250px; +} + .edit-btn { background: linear-gradient(45deg, #1976d2, #42a5f5); color: white; @@ -458,15 +828,53 @@ watch(showEditDialog, (newVal) => { box-shadow: 0 2px 8px rgba(25, 118, 210, 0.3); } +.edit-btn.small { + padding: 5px 15px; + font-size: 12px; +} + .edit-btn:hover { transform: translateY(-2px); box-shadow: 0 4px 15px rgba(25, 118, 210, 0.4); background: linear-gradient(45deg, #1565c0, #2196f3); } +/* 快速统计 */ +.quick-stats { + display: flex; + gap: 15px; + margin-bottom: 20px; + flex-wrap: wrap; +} + +.quick-stat-item { + background: white; + padding: 15px 20px; + border-radius: 12px; + box-shadow: 0 2px 10px rgba(25, 118, 210, 0.1); + text-align: center; + min-width: 120px; +} + +.quick-stat-value, .trend-indicator { + font-size: 20px; + font-weight: bold; + margin-bottom: 5px; +} + +.quick-stat-label { + font-size: 12px; + color: #666; +} + +.trend-up { color: #4caf50; } +.trend-down { color: #f44336; } +.trend-stable { color: #ff9800; } + +/* 统计卡片增强 */ .stats-container { display: grid; - grid-template-columns: repeat(auto-fit, minmax(200px, 1fr)); + grid-template-columns: repeat(auto-fit, minmax(180px, 1fr)); gap: 15px; margin-bottom: 25px; } @@ -497,29 +905,166 @@ watch(showEditDialog, (newVal) => { font-size: 24px; font-weight: bold; color: #1976d2; + margin-bottom: 5px; } -.chart-container { +.stat-trend { + font-size: 12px; + color: #999; +} + +/* 对比分析 */ +.comparison-section { background: white; padding: 20px; border-radius: 12px; box-shadow: 0 2px 10px rgba(25, 118, 210, 0.1); + margin-bottom: 25px; +} + +.comparison-controls { + display: flex; + justify-content: space-between; + align-items: center; + margin-bottom: 20px; +} + +.comparison-stats { + display: grid; + grid-template-columns: repeat(auto-fit, minmax(150px, 1fr)); + gap: 20px; +} + +.comparison-item { + text-align: center; +} + +.comparison-label { + font-size: 14px; + color: #666; + margin-bottom: 8px; +} + +.comparison-value { + font-size: 24px; + font-weight: bold; +} + +.comparison-value.current { color: #1976d2; } +.comparison-value.previous { color: #666; } +.comparison-value.positive { color: #4caf50; } +.comparison-value.negative { color: #f44336; } +.comparison-value.neutral { color: #ff9800; } + +/* 图表容器增强 */ +.chart-container, .predict-chart-container { + background: white; + padding: 20px; + border-radius: 12px; + box-shadow: 0 2px 10px rgba(25, 118, 210, 0.1); + margin-bottom: 25px; +} + +.chart-container { border: 3px solid #1976d2; } .predict-chart-container { - background: white; - padding: 20px; - border-radius: 12px; - box-shadow: 0 2px 10px rgba(25, 118, 210, 0.1); border: 3px solid #dccc13; } +.chart-header { + display: flex; + justify-content: space-between; + align-items: center; + margin-bottom: 20px; +} + +.chart-controls { + display: flex; + gap: 10px; +} + +.prediction-controls { + display: flex; + align-items: center; + gap: 10px; +} + +.prediction-accuracy { + display: flex; + gap: 30px; + margin-bottom: 15px; + padding: 10px; + background: #f5f5f5; + border-radius: 8px; +} + +.accuracy-item { + display: flex; + align-items: center; + gap: 5px; +} + +.accuracy-value { + font-weight: bold; + color: #4caf50; +} + +.confidence-value { + font-weight: bold; + color: #2196f3; +} + .map-chart { width: 100%; height: 400px; } +/* 数据洞察面板 */ +.insights-panel { + background: white; + padding: 20px; + border-radius: 12px; + box-shadow: 0 2px 10px rgba(25, 118, 210, 0.1); + margin-bottom: 25px; +} + +.insights-grid { + display: grid; + grid-template-columns: repeat(auto-fit, minmax(300px, 1fr)); + gap: 20px; +} + +.insight-card { + display: flex; + align-items: flex-start; + gap: 15px; + padding: 20px; + background: #f8f9fa; + border-radius: 8px; + border-left: 4px solid #1976d2; +} + +.insight-icon { + font-size: 24px; + flex-shrink: 0; +} + +.insight-content h4 { + margin: 0 0 8px 0; + color: #1976d2; + font-size: 16px; +} + +.insight-content p { + margin: 0; + color: #666; + font-size: 14px; + line-height: 1.4; +} + +/* 对话框增强 */ .dialog-overlay { position: fixed; top: 0; @@ -538,7 +1083,7 @@ watch(showEditDialog, (newVal) => { background: white; border-radius: 15px; width: 90%; - max-width: 500px; + max-width: 600px; max-height: 80vh; overflow: hidden; box-shadow: 0 10px 30px rgba(25, 118, 210, 0.3); @@ -585,10 +1130,34 @@ watch(showEditDialog, (newVal) => { overflow-y: auto; } +.batch-operations { + display: flex; + gap: 10px; + margin-bottom: 20px; + padding-bottom: 15px; + border-bottom: 1px solid #eee; +} + +.batch-btn { + padding: 8px 15px; + border: 1px solid #ddd; + border-radius: 5px; + background: #f8f9fa; + cursor: pointer; + transition: all 0.3s ease; + font-size: 12px; +} + +.batch-btn:hover { + background: #e9ecef; + border-color: #1976d2; +} + .input-group { display: flex; align-items: center; margin-bottom: 15px; + gap: 10px; } .input-group label { @@ -612,6 +1181,36 @@ watch(showEditDialog, (newVal) => { box-shadow: 0 0 0 3px rgba(25, 118, 210, 0.1); } +.delete-point-btn { + background: #f44336; + color: white; + border: none; + width: 24px; + height: 24px; + border-radius: 50%; + cursor: pointer; + font-size: 14px; + display: flex; + align-items: center; + justify-content: center; +} + +.add-point-btn { + width: 100%; + padding: 10px; + border: 2px dashed #1976d2; + background: none; + color: #1976d2; + border-radius: 8px; + cursor: pointer; + margin-top: 10px; + transition: all 0.3s ease; +} + +.add-point-btn:hover { + background: #e3f2fd; +} + .dialog-footer { display: flex; justify-content: flex-end; @@ -653,4 +1252,29 @@ watch(showEditDialog, (newVal) => { transform: translateY(-1px); box-shadow: 0 4px 12px rgba(25, 118, 210, 0.4); } + +/* 响应式设计 */ +@media (max-width: 768px) { + .toolbar { + flex-direction: column; + align-items: stretch; + } + + .quick-stats { + flex-direction: column; + } + + .comparison-stats { + grid-template-columns: 1fr; + } + + .chart-header { + flex-direction: column; + gap: 15px; + } + + .insights-grid { + grid-template-columns: 1fr; + } +} \ No newline at end of file