Add professional intraday meteorology analysis
This commit is contained in:
2569718930@qq.com
@@ -2921,6 +2921,97 @@
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gap: 10px;
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}
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.root :global(.future-v2-sync-strip-compact) {
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grid-template-columns: repeat(auto-fit, minmax(180px, 1fr));
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gap: 8px;
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}
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.root :global(.future-v2-sync-strip-compact .future-v2-sync-chip) {
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padding: 8px 10px;
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border-radius: 8px;
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background: rgba(15, 23, 42, 0.62);
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}
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.root :global(.future-v2-sync-strip-compact .future-v2-sync-copy span) {
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display: none;
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}
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.root :global(.future-v2-meteorology-brief) {
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display: grid;
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grid-template-columns: minmax(0, 1fr) minmax(320px, 0.56fr);
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gap: 14px;
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padding: 16px;
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border: 1px solid rgba(34, 211, 238, 0.22);
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border-radius: 8px;
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background:
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linear-gradient(180deg, rgba(8, 47, 73, 0.42), rgba(15, 23, 42, 0.78));
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}
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.root :global(.future-v2-meteorology-copy) {
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display: grid;
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gap: 10px;
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min-width: 0;
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}
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.root :global(.future-v2-meteorology-copy h3) {
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margin: 0;
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color: #f8fafc;
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font-size: 18px;
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font-weight: 800;
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line-height: 1.35;
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letter-spacing: 0;
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}
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.root :global(.future-v2-meteorology-meta) {
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display: flex;
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flex-wrap: wrap;
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gap: 8px;
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}
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.root :global(.future-v2-meteorology-meta span) {
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min-height: 26px;
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display: inline-flex;
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align-items: center;
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padding: 5px 8px;
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border: 1px solid rgba(148, 163, 184, 0.18);
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border-radius: 8px;
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background: rgba(15, 23, 42, 0.62);
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color: #cbd5e1;
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font-size: 12px;
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line-height: 1.35;
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}
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.root :global(.future-v2-meteorology-paths) {
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display: grid;
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grid-template-columns: repeat(3, minmax(0, 1fr));
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gap: 8px;
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}
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.root :global(.future-v2-meteorology-paths div) {
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min-width: 0;
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padding: 12px;
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border: 1px solid rgba(34, 211, 238, 0.18);
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border-radius: 8px;
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background: rgba(2, 6, 23, 0.5);
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}
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.root :global(.future-v2-meteorology-paths span) {
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display: block;
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color: var(--text-muted);
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font-size: 11px;
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line-height: 1.3;
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}
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.root :global(.future-v2-meteorology-paths strong) {
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display: block;
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margin-top: 8px;
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color: #67e8f9;
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font-size: 22px;
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font-weight: 800;
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line-height: 1;
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letter-spacing: 0;
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}
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.root :global(.future-v2-sync-chip) {
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display: flex;
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align-items: flex-start;
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@@ -3688,6 +3779,124 @@
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min-height: 340px;
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}
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.root :global(.future-v2-chart-thresholds) {
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display: flex;
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flex-wrap: wrap;
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gap: 8px;
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margin-top: 12px;
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}
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.root :global(.future-v2-chart-thresholds span) {
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min-height: 26px;
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display: inline-flex;
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align-items: center;
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padding: 5px 8px;
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border: 1px solid rgba(34, 211, 238, 0.16);
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border-radius: 8px;
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background: rgba(8, 47, 73, 0.24);
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color: #cbd5e1;
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font-size: 12px;
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line-height: 1.35;
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}
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.root :global(.future-v2-meteorology-grid) {
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display: grid;
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grid-template-columns: minmax(0, 1.25fr) minmax(0, 0.9fr) minmax(0, 0.9fr);
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gap: 12px;
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}
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.root :global(.future-v2-evidence-list) {
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display: grid;
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gap: 8px;
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}
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.root :global(.future-v2-evidence-row) {
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padding: 10px;
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border: 1px solid rgba(148, 163, 184, 0.14);
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border-left-width: 3px;
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border-radius: 8px;
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background: rgba(15, 23, 42, 0.5);
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}
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.root :global(.future-v2-evidence-row.cyan) {
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border-left-color: #22d3ee;
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}
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.root :global(.future-v2-evidence-row.amber) {
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border-left-color: #f59e0b;
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}
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.root :global(.future-v2-evidence-row.blue) {
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border-left-color: #60a5fa;
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}
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.root :global(.future-v2-evidence-head) {
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display: flex;
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justify-content: space-between;
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gap: 10px;
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align-items: flex-start;
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}
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.root :global(.future-v2-evidence-head strong) {
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color: #f8fafc;
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font-size: 13px;
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line-height: 1.35;
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}
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.root :global(.future-v2-evidence-head span) {
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color: var(--text-muted);
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font-size: 11px;
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line-height: 1.35;
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text-align: right;
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}
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.root :global(.future-v2-evidence-row p) {
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margin: 7px 0 0;
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color: var(--text-secondary);
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font-size: 12px;
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line-height: 1.55;
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}
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.root :global(.future-v2-rule-list) {
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display: grid;
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gap: 8px;
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margin: 0;
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padding: 0;
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list-style: none;
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}
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.root :global(.future-v2-rule-list li) {
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position: relative;
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padding-left: 16px;
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color: var(--text-secondary);
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font-size: 12px;
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line-height: 1.55;
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}
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.root :global(.future-v2-rule-list li::before) {
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content: "";
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position: absolute;
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left: 0;
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top: 0.65em;
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width: 6px;
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height: 6px;
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border-radius: 999px;
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background: #22d3ee;
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}
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.root :global(.future-v2-rule-panel:nth-child(2) .future-v2-rule-list li::before) {
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background: #f59e0b;
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}
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.root :global(.future-v2-model-note) {
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margin-top: 12px;
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padding-top: 10px;
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border-top: 1px solid rgba(148, 163, 184, 0.14);
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color: var(--text-muted);
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font-size: 12px;
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line-height: 1.55;
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}
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.root :global(.future-modal-section) {
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background: rgba(255, 255, 255, 0.02);
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border: 1px solid var(--border-subtle);
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@@ -3909,6 +4118,15 @@
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}
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@media (max-width: 960px) {
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.root :global(.future-v2-meteorology-brief),
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.root :global(.future-v2-meteorology-grid) {
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grid-template-columns: 1fr;
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}
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.root :global(.future-v2-meteorology-paths) {
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grid-template-columns: repeat(3, minmax(0, 1fr));
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}
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.root :global(.future-v2-layout) {
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grid-template-columns: 1fr;
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}
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@@ -3934,6 +4152,18 @@
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padding-right: 0;
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}
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.root :global(.future-v2-meteorology-brief) {
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padding: 12px;
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}
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.root :global(.future-v2-meteorology-paths) {
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grid-template-columns: 1fr;
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}
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.root :global(.future-v2-meteorology-copy h3) {
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font-size: 16px;
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}
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.root :global(.future-v2-card),
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.root :global(.future-modal-section) {
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border-radius: 12px;
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@@ -31,6 +31,7 @@ import {
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getTemperatureChartData,
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getWeatherSummary,
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} from "@/lib/dashboard-utils";
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import type { IntradayMeteorologySignal } from "@/lib/dashboard-types";
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function normalizeMarketValue(value?: number | null) {
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if (value == null) return null;
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@@ -175,6 +176,35 @@ function parsePercentFromText(value?: string | number | null) {
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return parseLeadingNumber(text);
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}
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function formatConfidenceLabel(value?: string | null, locale = "zh-CN") {
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const normalized = String(value || "").trim().toLowerCase();
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if (normalized === "high") return locale === "en-US" ? "High" : "高";
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if (normalized === "medium") return locale === "en-US" ? "Medium" : "中";
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if (normalized === "low") return locale === "en-US" ? "Low" : "低";
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return locale === "en-US" ? "Pending" : "待确认";
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}
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function formatSignalDirection(value?: string | null, locale = "zh-CN") {
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const normalized = String(value || "").trim().toLowerCase();
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if (normalized === "support") return locale === "en-US" ? "Support" : "支持升温";
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if (normalized === "suppress") return locale === "en-US" ? "Suppress" : "压制峰值";
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return locale === "en-US" ? "Neutral" : "中性";
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}
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function formatSignalStrength(value?: string | null, locale = "zh-CN") {
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const normalized = String(value || "").trim().toLowerCase();
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if (normalized === "strong") return locale === "en-US" ? "Strong" : "强";
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if (normalized === "medium") return locale === "en-US" ? "Medium" : "中";
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return locale === "en-US" ? "Weak" : "弱";
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}
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function signalTone(signal?: IntradayMeteorologySignal | null) {
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const direction = String(signal?.direction || "").trim().toLowerCase();
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if (direction === "support") return "cyan";
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if (direction === "suppress") return "amber";
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return "blue";
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}
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function getTrendMetricVisual(metric: {
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label?: string;
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value?: string;
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@@ -1081,6 +1111,58 @@ export function FutureForecastModal() {
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}
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return lines.slice(0, 3);
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}, [boundaryRiskView, isToday, locale, localizedAiCommentaryLines, networkLeadView, paceView, showDeferredTodaySections]);
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const intradayMeteorology = detail.intraday_meteorology || {};
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const meteorologySignals = Array.isArray(intradayMeteorology.signal_contributions)
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? intradayMeteorology.signal_contributions
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: [];
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const invalidationRules = Array.isArray(intradayMeteorology.invalidation_rules)
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? intradayMeteorology.invalidation_rules
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: [];
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const confirmationRules = Array.isArray(intradayMeteorology.confirmation_rules)
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? intradayMeteorology.confirmation_rules
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: [];
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const meteorologyHeadline =
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String(intradayMeteorology.headline || "").trim() ||
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todayTradeSummaryLines[0] ||
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(locale === "en-US"
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? "Intraday meteorology layers are still syncing; use the next observation as the anchor."
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: "关键日内气象层仍在同步，先以下一次观测作为判断锚点。");
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const baseCaseBucket =
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String(intradayMeteorology.base_case_bucket || "").trim() ||
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formatBucketLabel(topProbabilityBucket);
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const nextObservationTime =
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String(intradayMeteorology.next_observation_time || "").trim() || "--";
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const baseBucketNumber = parseLeadingNumber(baseCaseBucket);
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const referenceObservedTemp =
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topObservedTemp != null && Number.isFinite(Number(topObservedTemp))
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? Number(topObservedTemp)
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: detail.current?.temp != null
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? Number(detail.current.temp)
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: null;
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const gapToBaseBucket =
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baseBucketNumber != null && referenceObservedTemp != null
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? Math.max(0, baseBucketNumber - referenceObservedTemp)
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: null;
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const pathStatus =
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gapToBaseBucket == null
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? locale === "en-US"
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? "Awaiting anchor"
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: "等待锚点"
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: gapToBaseBucket <= 0.05
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? locale === "en-US"
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? "Base path touched"
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: "基准路径已触达"
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: gapToBaseBucket <= 1.0
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? locale === "en-US"
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? "Base path open"
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: "基准路径开放"
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: locale === "en-US"
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? "Needs peak push"
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: "需要峰值推动";
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const peakWindowText =
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String(intradayMeteorology.peak_window || "").trim() ||
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paceView?.peakWindowText ||
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"--";
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const syncStatusItems = [
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{
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key: "base",
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@@ -1215,7 +1297,49 @@ export function FutureForecastModal() {
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</button>
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</div>
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<div className="modal-body future-modal-body">
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<section className="future-v2-sync-strip" aria-live="polite">
|
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{isToday && (
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<section className="future-v2-meteorology-brief">
|
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<div className="future-v2-meteorology-copy">
|
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<div className="modal-section-kicker">
|
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{locale === "en-US" ? "Professional meteorology read" : "专业气象判断"}
|
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</div>
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<h3>{meteorologyHeadline}</h3>
|
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<div className="future-v2-meteorology-meta">
|
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<span>
|
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{locale === "en-US" ? "Confidence" : "置信度"} ·{" "}
|
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{formatConfidenceLabel(intradayMeteorology.confidence, locale)}
|
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</span>
|
||||
<span>
|
||||
{locale === "en-US" ? "Peak window" : "峰值窗口"} · {peakWindowText}
|
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</span>
|
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<span>
|
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{locale === "en-US" ? "Next observation" : "下一观测"} · {nextObservationTime}
|
||||
</span>
|
||||
</div>
|
||||
</div>
|
||||
<div className="future-v2-meteorology-paths">
|
||||
<div>
|
||||
<span>{locale === "en-US" ? "Base case" : "基准路径"}</span>
|
||||
<strong>{baseCaseBucket || "--"}</strong>
|
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</div>
|
||||
<div>
|
||||
<span>{locale === "en-US" ? "Upside" : "上修路径"}</span>
|
||||
<strong>{intradayMeteorology.upside_bucket || "--"}</strong>
|
||||
</div>
|
||||
<div>
|
||||
<span>{locale === "en-US" ? "Downside" : "下修路径"}</span>
|
||||
<strong>{intradayMeteorology.downside_bucket || "--"}</strong>
|
||||
</div>
|
||||
</div>
|
||||
</section>
|
||||
)}
|
||||
<section
|
||||
className={clsx(
|
||||
"future-v2-sync-strip",
|
||||
isToday && "future-v2-sync-strip-compact",
|
||||
)}
|
||||
aria-live="polite"
|
||||
>
|
||||
{syncStatusItems.map((item) => (
|
||||
<div
|
||||
key={item.key}
|
||||
@@ -1314,6 +1438,22 @@ export function FutureForecastModal() {
|
||||
</span>
|
||||
<strong>{detail.current?.obs_time || "--"}</strong>
|
||||
</div>
|
||||
<div className="future-v2-mini-item">
|
||||
<span>
|
||||
{locale === "en-US" ? "Gap to base" : "距基准档"}
|
||||
</span>
|
||||
<strong>
|
||||
{gapToBaseBucket != null
|
||||
? `${gapToBaseBucket.toFixed(1)}${detail.temp_symbol}`
|
||||
: "--"}
|
||||
</strong>
|
||||
</div>
|
||||
<div className="future-v2-mini-item">
|
||||
<span>
|
||||
{locale === "en-US" ? "Path state" : "路径状态"}
|
||||
</span>
|
||||
<strong>{pathStatus}</strong>
|
||||
</div>
|
||||
<div className="future-v2-mini-item">
|
||||
<span>
|
||||
{locale === "en-US" ? "Sunrise" : "日出时间"}
|
||||
@@ -1484,16 +1624,103 @@ export function FutureForecastModal() {
|
||||
</h3>
|
||||
</div>
|
||||
<DailyTemperatureChart dateStr={dateStr} />
|
||||
<div className="future-v2-chart-thresholds">
|
||||
<span>{locale === "en-US" ? "Base" : "基准"} · {baseCaseBucket || "--"}</span>
|
||||
<span>{locale === "en-US" ? "Upside" : "上修"} · {intradayMeteorology.upside_bucket || "--"}</span>
|
||||
<span>{locale === "en-US" ? "Invalidates at" : "失效观察"} · {nextObservationTime}</span>
|
||||
</div>
|
||||
</section>
|
||||
|
||||
<div className="future-v2-meteorology-grid">
|
||||
<section className="future-modal-section future-v2-evidence-panel">
|
||||
<div className="modal-section-heading">
|
||||
<div className="modal-section-kicker">
|
||||
{locale === "en-US" ? "Evidence chain" : "气象证据链"}
|
||||
</div>
|
||||
<h3>{locale === "en-US" ? "Signal Contributions" : "信号贡献"}</h3>
|
||||
</div>
|
||||
<div className="future-v2-evidence-list">
|
||||
{meteorologySignals.length > 0 ? (
|
||||
meteorologySignals.map((signal, index) => (
|
||||
<div
|
||||
key={`${signal.label || "signal"}-${index}`}
|
||||
className={clsx(
|
||||
"future-v2-evidence-row",
|
||||
signalTone(signal),
|
||||
)}
|
||||
>
|
||||
<div className="future-v2-evidence-head">
|
||||
<strong>{signal.label || "--"}</strong>
|
||||
<span>
|
||||
{formatSignalDirection(signal.direction, locale)} ·{" "}
|
||||
{formatSignalStrength(signal.strength, locale)}
|
||||
</span>
|
||||
</div>
|
||||
<p>{signal.summary || "--"}</p>
|
||||
</div>
|
||||
))
|
||||
) : (
|
||||
<div className="future-text-block">
|
||||
{locale === "en-US"
|
||||
? "Meteorology signals are still loading."
|
||||
: "气象信号仍在加载。"}
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
</section>
|
||||
|
||||
<section className="future-modal-section future-v2-rule-panel">
|
||||
<div className="modal-section-heading">
|
||||
<div className="modal-section-kicker">
|
||||
{locale === "en-US" ? "Failure modes" : "失效条件"}
|
||||
</div>
|
||||
<h3>{locale === "en-US" ? "What Downgrades the Read" : "什么会让判断降级"}</h3>
|
||||
</div>
|
||||
<ul className="future-v2-rule-list">
|
||||
{(invalidationRules.length > 0
|
||||
? invalidationRules
|
||||
: [
|
||||
locale === "en-US"
|
||||
? "If observations stop tracking the expected curve, wait for the next refresh."
|
||||
: "若实测不再贴近预期曲线，等待下一次刷新确认。",
|
||||
]
|
||||
).map((rule, index) => (
|
||||
<li key={`${rule}-${index}`}>{rule}</li>
|
||||
))}
|
||||
</ul>
|
||||
</section>
|
||||
|
||||
<section className="future-modal-section future-v2-rule-panel">
|
||||
<div className="modal-section-heading">
|
||||
<div className="modal-section-kicker">
|
||||
{locale === "en-US" ? "Confirmation" : "确认条件"}
|
||||
</div>
|
||||
<h3>{locale === "en-US" ? "What Confirms the Path" : "什么会确认主路径"}</h3>
|
||||
</div>
|
||||
<ul className="future-v2-rule-list">
|
||||
{(confirmationRules.length > 0
|
||||
? confirmationRules
|
||||
: [
|
||||
locale === "en-US"
|
||||
? "Keep watching the next settlement-source observation."
|
||||
: "继续观察下一次结算源报文。",
|
||||
]
|
||||
).map((rule, index) => (
|
||||
<li key={`${rule}-${index}`}>{rule}</li>
|
||||
))}
|
||||
</ul>
|
||||
<div className="future-v2-model-note">{modelSummary}</div>
|
||||
</section>
|
||||
</div>
|
||||
|
||||
<div className="future-modal-grid">
|
||||
<section className="future-modal-section">
|
||||
<div className="modal-section-heading">
|
||||
<div className="modal-section-kicker">
|
||||
{locale === "en-US" ? "Probability layer" : "概率层"}
|
||||
{locale === "en-US" ? "Auxiliary probability" : "辅助概率"}
|
||||
</div>
|
||||
<h3>
|
||||
{locale === "en-US" ? "Current Hit Odds" : "当前命中胜率"}
|
||||
{locale === "en-US" ? "Model & Market Reference" : "模型与市场参考"}
|
||||
</h3>
|
||||
</div>
|
||||
<div className="future-text-block" style={{ marginBottom: "12px" }}>
|
||||
@@ -1503,6 +1730,7 @@ export function FutureForecastModal() {
|
||||
<ProbabilityDistribution
|
||||
detail={detail}
|
||||
targetDate={dateStr}
|
||||
marketScan={detail.market_scan}
|
||||
hideTitle
|
||||
/>
|
||||
</div>
|
||||
|
||||
@@ -485,12 +485,12 @@ export function ProbabilityDistribution({
|
||||
const buyNoText = toPriceCents(bucket.no_buy);
|
||||
const marketTag = buyYesText
|
||||
? locale === "en-US"
|
||||
? `Buy Yes: ${buyYesText}`
|
||||
: `买 Yes: ${buyYesText}`
|
||||
? `Market ref: ${buyYesText}`
|
||||
: `市场参考: ${buyYesText}`
|
||||
: buyNoText
|
||||
? locale === "en-US"
|
||||
? `Buy No: ${buyNoText}`
|
||||
: `买 No: ${buyNoText}`
|
||||
? `Market hedge: ${buyNoText}`
|
||||
: `市场反向: ${buyNoText}`
|
||||
: null;
|
||||
|
||||
return (
|
||||
@@ -530,23 +530,23 @@ export function ProbabilityDistribution({
|
||||
Math.abs(bucketTemp - marketBucketTemp) < 0.26;
|
||||
const marketTag = isMarketBucket
|
||||
? locale === "en-US"
|
||||
? `Buy Yes: ${marketYesText || "--"}`
|
||||
: `买 Yes: ${marketYesText || "--"}`
|
||||
? `Market ref: ${marketYesText || "--"}`
|
||||
: `市场参考: ${marketYesText || "--"}`
|
||||
: marketNoText
|
||||
? locale === "en-US"
|
||||
? `Buy No: ${marketNoText}`
|
||||
: `买 No: ${marketNoText}`
|
||||
? `Market hedge: ${marketNoText}`
|
||||
: `市场反向: ${marketNoText}`
|
||||
: null;
|
||||
const yesPriceText = toPriceCents(marketYesPrice);
|
||||
const noPriceText = toPriceCents(marketNoPrice);
|
||||
const marketTagFinal = isMarketBucket
|
||||
? locale === "en-US"
|
||||
? `Buy Yes: ${yesPriceText || "--"}`
|
||||
: `买 Yes: ${yesPriceText || "--"}`
|
||||
? `Market ref: ${yesPriceText || "--"}`
|
||||
: `市场参考: ${yesPriceText || "--"}`
|
||||
: noPriceText
|
||||
? locale === "en-US"
|
||||
? `Buy No: ${noPriceText}`
|
||||
: `买 No: ${noPriceText}`
|
||||
? `Market hedge: ${noPriceText}`
|
||||
: `市场反向: ${noPriceText}`
|
||||
: marketTag;
|
||||
let bucketLabel =
|
||||
bucket.label || `${bucket.value}${detail.temp_symbol}`;
|
||||
|
||||
@@ -14,6 +14,10 @@ import {
|
||||
toCitySummary,
|
||||
} from "@/lib/dashboard-client";
|
||||
import { markAnalyticsOnce, trackAppEvent } from "@/lib/app-analytics";
|
||||
import {
|
||||
getSupabaseBrowserClient,
|
||||
hasSupabasePublicEnv,
|
||||
} from "@/lib/supabase/client";
|
||||
import {
|
||||
CityDetail,
|
||||
CityListItem,
|
||||
@@ -95,6 +99,36 @@ const SELECTED_CITY_STORAGE_KEY = "polyWeather_selected_city_v1";
|
||||
const BACKGROUND_SUMMARY_REFRESH_MS = 30_000;
|
||||
type CityDetailDepth = "panel" | "market" | "nearby" | "full";
|
||||
|
||||
async function buildAuthMeHeaders(): Promise<HeadersInit> {
|
||||
const headers: Record<string, string> = {
|
||||
Accept: "application/json",
|
||||
};
|
||||
if (!hasSupabasePublicEnv()) {
|
||||
return headers;
|
||||
}
|
||||
|
||||
try {
|
||||
const {
|
||||
data: { session: cachedSession },
|
||||
} = await getSupabaseBrowserClient().auth.getSession();
|
||||
let accessToken = String(cachedSession?.access_token || "").trim();
|
||||
const expiresAtSec = Number(cachedSession?.expires_at || 0);
|
||||
const nowSec = Math.floor(Date.now() / 1000);
|
||||
if (!accessToken || (Number.isFinite(expiresAtSec) && expiresAtSec <= nowSec + 60)) {
|
||||
const {
|
||||
data: { session: refreshedSession },
|
||||
} = await getSupabaseBrowserClient().auth.refreshSession();
|
||||
accessToken = String(refreshedSession?.access_token || accessToken || "").trim();
|
||||
}
|
||||
if (accessToken) {
|
||||
headers.Authorization = `Bearer ${accessToken}`;
|
||||
}
|
||||
} catch {
|
||||
// The same-origin route can still fall back to cookie-backed auth.
|
||||
}
|
||||
return headers;
|
||||
}
|
||||
|
||||
function countAvailableModels(
|
||||
detail?: CityDetail | null,
|
||||
targetDate?: string | null,
|
||||
@@ -563,11 +597,10 @@ export function DashboardStoreProvider({
|
||||
error: null,
|
||||
}));
|
||||
try {
|
||||
const headers = await buildAuthMeHeaders();
|
||||
const response = await fetch("/api/auth/me", {
|
||||
cache: "no-store",
|
||||
headers: {
|
||||
Accept: "application/json",
|
||||
},
|
||||
headers,
|
||||
});
|
||||
if (!response.ok) {
|
||||
throw new Error(`HTTP ${response.status}`);
|
||||
|
||||
@@ -316,6 +316,26 @@ export interface MarketScan {
|
||||
websocket?: Record<string, unknown>;
|
||||
}
|
||||
|
||||
export interface IntradayMeteorologySignal {
|
||||
label?: string | null;
|
||||
direction?: "support" | "suppress" | "neutral" | string | null;
|
||||
strength?: "weak" | "medium" | "strong" | string | null;
|
||||
summary?: string | null;
|
||||
}
|
||||
|
||||
export interface IntradayMeteorology {
|
||||
headline?: string | null;
|
||||
confidence?: "low" | "medium" | "high" | string | null;
|
||||
base_case_bucket?: string | null;
|
||||
upside_bucket?: string | null;
|
||||
downside_bucket?: string | null;
|
||||
next_observation_time?: string | null;
|
||||
peak_window?: string | null;
|
||||
invalidation_rules?: string[] | null;
|
||||
confirmation_rules?: string[] | null;
|
||||
signal_contributions?: IntradayMeteorologySignal[] | null;
|
||||
}
|
||||
|
||||
export interface AiAnalysisStructured {
|
||||
summary?: string | null;
|
||||
text?: string | null;
|
||||
@@ -473,6 +493,7 @@ export interface CityDetail {
|
||||
multi_model_daily?: Record<string, DailyModelForecast>;
|
||||
source_forecasts?: SourceForecasts;
|
||||
market_scan?: MarketScan;
|
||||
intraday_meteorology?: IntradayMeteorology;
|
||||
}
|
||||
|
||||
export interface HistoryPoint {
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
from src.data_collection.country_networks import build_country_network_snapshot
|
||||
from src.data_collection.city_registry import ALIASES, CITY_REGISTRY
|
||||
from web.analysis_service import _build_city_detail_payload
|
||||
from web.analysis_service import _build_city_detail_payload, _build_intraday_meteorology
|
||||
|
||||
|
||||
def test_new_south_asia_city_registry_entries_are_wired():
|
||||
@@ -198,3 +198,84 @@ def test_city_detail_payload_exposes_airport_and_official_network_layers():
|
||||
assert payload["official"]["airport_primary"]["source_code"] == "metar"
|
||||
assert payload["official"]["official_nearby"][0]["source_code"] == "mgm"
|
||||
assert payload["settlement_station"]["settlement_station_code"] == "LTAC"
|
||||
|
||||
|
||||
def test_intraday_meteorology_supportive_heating_case():
|
||||
payload = _build_intraday_meteorology(
|
||||
{
|
||||
"local_time": "12:04",
|
||||
"temp_symbol": "°C",
|
||||
"current": {"temp": 38.2, "max_so_far": 38.2},
|
||||
"deb": {"prediction": 40.4},
|
||||
"probabilities": {"distribution": [{"value": 40, "probability": 0.42}]},
|
||||
"peak": {"first_h": 14, "last_h": 15, "status": "before"},
|
||||
"deviation_monitor": {"direction": "hot", "severity": "strong", "current_delta": 1.9},
|
||||
"vertical_profile_signal": {
|
||||
"heating_setup": "supportive",
|
||||
"summary_zh": "混合层偏深，仍支持午后继续升温。",
|
||||
},
|
||||
"taf": {"signal": {"available": True, "suppression_level": "low", "summary_zh": "TAF 暂未提示强云雨压温。"}},
|
||||
}
|
||||
)
|
||||
|
||||
assert "上修空间" in payload["headline"]
|
||||
assert payload["confidence"] == "high"
|
||||
assert payload["base_case_bucket"] == "40°C"
|
||||
assert payload["next_observation_time"] == "12:30"
|
||||
assert any(item["direction"] == "support" for item in payload["signal_contributions"])
|
||||
|
||||
|
||||
def test_intraday_meteorology_suppressed_cloud_rain_case():
|
||||
payload = _build_intraday_meteorology(
|
||||
{
|
||||
"local_time": "13:10",
|
||||
"temp_symbol": "°C",
|
||||
"current": {"temp": 36.0, "max_so_far": 36.5},
|
||||
"deb": {"prediction": 40.2},
|
||||
"probabilities": {"distribution": [{"value": 40, "probability": 0.35}]},
|
||||
"peak": {"first_h": 14, "last_h": 15, "status": "before"},
|
||||
"deviation_monitor": {"direction": "cold", "severity": "strong", "current_delta": -2.0},
|
||||
"vertical_profile_signal": {"heating_setup": "suppressed", "suppression_risk": "high"},
|
||||
"taf": {"signal": {"available": True, "suppression_level": "high", "disruption_level": "high"}},
|
||||
}
|
||||
)
|
||||
|
||||
assert "压制" in payload["headline"]
|
||||
assert payload["confidence"] == "high"
|
||||
assert any("云雨" in rule for rule in payload["invalidation_rules"])
|
||||
assert any(item["direction"] == "suppress" for item in payload["signal_contributions"])
|
||||
|
||||
|
||||
def test_intraday_meteorology_handles_sparse_observations():
|
||||
payload = _build_intraday_meteorology(
|
||||
{
|
||||
"local_time": "08:00",
|
||||
"temp_symbol": "°C",
|
||||
"current": {},
|
||||
"probabilities": {"distribution": []},
|
||||
"peak": {},
|
||||
"taf": {},
|
||||
"vertical_profile_signal": {},
|
||||
}
|
||||
)
|
||||
|
||||
assert payload["confidence"] == "low"
|
||||
assert payload["next_observation_time"] == "08:30"
|
||||
assert payload["signal_contributions"][0]["label"] == "数据完整性"
|
||||
|
||||
|
||||
def test_intraday_meteorology_past_peak_case():
|
||||
payload = _build_intraday_meteorology(
|
||||
{
|
||||
"local_time": "17:20",
|
||||
"temp_symbol": "°C",
|
||||
"current": {"temp": 33.0, "max_so_far": 39.0},
|
||||
"probabilities": {"distribution": [{"value": 39, "probability": 0.5}]},
|
||||
"peak": {"first_h": 13, "last_h": 15, "status": "past"},
|
||||
"deviation_monitor": {"direction": "normal", "severity": "normal", "current_delta": 0.1},
|
||||
}
|
||||
)
|
||||
|
||||
assert "峰值窗口已过" in payload["headline"]
|
||||
assert payload["base_case_bucket"] == "39°C"
|
||||
assert any("最终高点" in rule for rule in payload["invalidation_rules"])
|
||||
|
||||
@@ -1118,6 +1118,296 @@ def _build_taf_signal(
|
||||
}
|
||||
|
||||
|
||||
def _clock_minutes(value: Any) -> Optional[int]:
|
||||
text = str(value or "").strip()
|
||||
match = re.search(r"\b(\d{1,2}):(\d{2})\b", text)
|
||||
if not match:
|
||||
return None
|
||||
hour = int(match.group(1))
|
||||
minute = int(match.group(2))
|
||||
if hour < 0 or hour > 23 or minute < 0 or minute > 59:
|
||||
return None
|
||||
return hour * 60 + minute
|
||||
|
||||
|
||||
def _format_clock_minutes(value: int) -> str:
|
||||
value = max(0, min(23 * 60 + 59, int(value)))
|
||||
return f"{value // 60:02d}:{value % 60:02d}"
|
||||
|
||||
|
||||
def _next_observation_clock(local_time: Any) -> str:
|
||||
minutes = _clock_minutes(local_time)
|
||||
if minutes is None:
|
||||
return "--"
|
||||
next_slot = ((minutes // 30) + 1) * 30
|
||||
if next_slot > 23 * 60 + 59:
|
||||
return "23:59"
|
||||
return _format_clock_minutes(next_slot)
|
||||
|
||||
|
||||
def _bucket_label_from_value(value: Optional[float], unit: str) -> Optional[str]:
|
||||
if value is None:
|
||||
return None
|
||||
try:
|
||||
return f"{int(round(float(value)))}{unit or '°C'}"
|
||||
except Exception:
|
||||
return None
|
||||
|
||||
|
||||
def _top_probability_bucket(distribution: Any) -> Optional[Dict[str, Any]]:
|
||||
if not isinstance(distribution, list):
|
||||
return None
|
||||
candidates = [row for row in distribution if isinstance(row, dict)]
|
||||
if not candidates:
|
||||
return None
|
||||
return max(candidates, key=lambda row: _sf(row.get("probability")) or -1.0)
|
||||
|
||||
|
||||
def _bucket_label(row: Optional[Dict[str, Any]], unit: str) -> Optional[str]:
|
||||
if not isinstance(row, dict):
|
||||
return None
|
||||
for key in ("label", "bucket", "range"):
|
||||
raw = str(row.get(key) or "").strip()
|
||||
if raw:
|
||||
return raw
|
||||
return _bucket_label_from_value(_sf(row.get("value")), unit)
|
||||
|
||||
|
||||
def _add_signal(
|
||||
signals: list,
|
||||
*,
|
||||
label: str,
|
||||
direction: str,
|
||||
strength: str,
|
||||
summary: str,
|
||||
) -> None:
|
||||
signals.append(
|
||||
{
|
||||
"label": label,
|
||||
"direction": direction,
|
||||
"strength": strength,
|
||||
"summary": summary,
|
||||
}
|
||||
)
|
||||
|
||||
|
||||
def _build_intraday_meteorology(data: Dict[str, Any]) -> Dict[str, Any]:
|
||||
"""Build a paid-product intraday meteorology read from existing layers."""
|
||||
current = data.get("current") or {}
|
||||
probabilities = data.get("probabilities") or {}
|
||||
distribution = probabilities.get("distribution") or []
|
||||
top_bucket = _top_probability_bucket(distribution)
|
||||
unit = str(data.get("temp_symbol") or "°C")
|
||||
deb = data.get("deb") or {}
|
||||
peak = data.get("peak") or {}
|
||||
deviation = data.get("deviation_monitor") or {}
|
||||
taf_signal = (
|
||||
((data.get("taf") or {}).get("signal") or {})
|
||||
if isinstance(data.get("taf"), dict)
|
||||
else {}
|
||||
)
|
||||
vertical = data.get("vertical_profile_signal") or {}
|
||||
|
||||
current_temp = _sf(current.get("temp"))
|
||||
max_so_far = _sf(current.get("max_so_far"))
|
||||
deb_prediction = _sf(deb.get("prediction"))
|
||||
base_value = _sf(top_bucket.get("value")) if isinstance(top_bucket, dict) else None
|
||||
if base_value is None:
|
||||
base_value = deb_prediction
|
||||
if base_value is None:
|
||||
base_value = max_so_far if max_so_far is not None else current_temp
|
||||
|
||||
base_case_bucket = _bucket_label(top_bucket, unit) or _bucket_label_from_value(base_value, unit)
|
||||
upside_bucket = _bucket_label_from_value(base_value + 1.0, unit) if base_value is not None else None
|
||||
downside_bucket = _bucket_label_from_value(base_value - 1.0, unit) if base_value is not None else None
|
||||
|
||||
signals: list = []
|
||||
support_score = 0
|
||||
suppress_score = 0
|
||||
available_layers = 0
|
||||
|
||||
direction = str(deviation.get("direction") or "").lower()
|
||||
severity = str(deviation.get("severity") or "normal").lower()
|
||||
delta = _sf(deviation.get("current_delta"))
|
||||
if direction:
|
||||
available_layers += 1
|
||||
strength = "strong" if severity == "strong" else ("medium" if severity == "light" else "weak")
|
||||
if direction == "hot":
|
||||
support_score += 2 if strength == "strong" else 1
|
||||
_add_signal(
|
||||
signals,
|
||||
label="日内节奏",
|
||||
direction="support",
|
||||
strength=strength,
|
||||
summary=f"实测较预期路径偏高 {abs(delta or 0):.1f}{unit}，峰值仍有上修空间。",
|
||||
)
|
||||
elif direction == "cold":
|
||||
suppress_score += 2 if strength == "strong" else 1
|
||||
_add_signal(
|
||||
signals,
|
||||
label="日内节奏",
|
||||
direction="suppress",
|
||||
strength=strength,
|
||||
summary=f"实测较预期路径偏低 {abs(delta or 0):.1f}{unit}，追更高温档需要等待后续观测确认。",
|
||||
)
|
||||
else:
|
||||
_add_signal(
|
||||
signals,
|
||||
label="日内节奏",
|
||||
direction="neutral",
|
||||
strength="weak",
|
||||
summary="实测大体贴近当前预期路径，下一步主要看峰值窗口内是否继续抬升。",
|
||||
)
|
||||
|
||||
heating_setup = str(vertical.get("heating_setup") or "").lower()
|
||||
suppression_risk = str(vertical.get("suppression_risk") or "").lower()
|
||||
if heating_setup or suppression_risk:
|
||||
available_layers += 1
|
||||
if heating_setup == "supportive":
|
||||
support_score += 2
|
||||
_add_signal(
|
||||
signals,
|
||||
label="边界层结构",
|
||||
direction="support",
|
||||
strength="strong",
|
||||
summary=str(vertical.get("summary_zh") or "边界层结构支持白天继续混合升温。"),
|
||||
)
|
||||
elif heating_setup == "suppressed" or suppression_risk == "high":
|
||||
suppress_score += 2
|
||||
_add_signal(
|
||||
signals,
|
||||
label="边界层结构",
|
||||
direction="suppress",
|
||||
strength="strong",
|
||||
summary=str(vertical.get("summary_zh") or "边界层或云雨结构对午后峰值形成压制。"),
|
||||
)
|
||||
else:
|
||||
_add_signal(
|
||||
signals,
|
||||
label="边界层结构",
|
||||
direction="neutral",
|
||||
strength="medium",
|
||||
summary=str(vertical.get("summary_zh") or "边界层结构暂未给出单边信号。"),
|
||||
)
|
||||
|
||||
taf_suppression = str(taf_signal.get("suppression_level") or "").lower()
|
||||
taf_disruption = str(taf_signal.get("disruption_level") or "").lower()
|
||||
if taf_signal.get("available") or taf_suppression:
|
||||
available_layers += 1
|
||||
if taf_suppression == "high" or taf_disruption == "high":
|
||||
suppress_score += 2
|
||||
direction_value = "suppress"
|
||||
strength = "strong"
|
||||
elif taf_suppression == "medium" or taf_disruption == "medium":
|
||||
suppress_score += 1
|
||||
direction_value = "suppress"
|
||||
strength = "medium"
|
||||
else:
|
||||
support_score += 1
|
||||
direction_value = "support"
|
||||
strength = "weak"
|
||||
_add_signal(
|
||||
signals,
|
||||
label="TAF 云雨扰动",
|
||||
direction=direction_value,
|
||||
strength=strength,
|
||||
summary=str(taf_signal.get("summary_zh") or "TAF 暂未提示强云雨压温信号。"),
|
||||
)
|
||||
|
||||
airport_delta = _sf(data.get("airport_vs_network_delta"))
|
||||
lead_signal = data.get("network_lead_signal") or {}
|
||||
if airport_delta is not None:
|
||||
available_layers += 1
|
||||
leader = str(lead_signal.get("leader_station_label") or lead_signal.get("leader_station_code") or "").strip()
|
||||
if airport_delta <= -0.4:
|
||||
support_score += 1
|
||||
_add_signal(
|
||||
signals,
|
||||
label="站网对比",
|
||||
direction="support",
|
||||
strength="medium",
|
||||
summary=f"周边站网较机场锚点偏热 {abs(airport_delta):.1f}{unit}{f'，领先点位 {leader}' if leader else ''}。",
|
||||
)
|
||||
elif airport_delta >= 0.4:
|
||||
suppress_score += 1
|
||||
_add_signal(
|
||||
signals,
|
||||
label="站网对比",
|
||||
direction="suppress",
|
||||
strength="medium",
|
||||
summary=f"机场锚点较周边站网偏热 {abs(airport_delta):.1f}{unit}，继续上修需要机场自身后续报文确认。",
|
||||
)
|
||||
else:
|
||||
_add_signal(
|
||||
signals,
|
||||
label="站网对比",
|
||||
direction="neutral",
|
||||
strength="weak",
|
||||
summary="机场锚点与周边站网基本同步，暂不构成单独上修或下修理由。",
|
||||
)
|
||||
|
||||
peak_status = str(peak.get("status") or "").lower()
|
||||
first_h = _sf(peak.get("first_h"))
|
||||
last_h = _sf(peak.get("last_h"))
|
||||
peak_window = (
|
||||
f"{int(first_h):02d}:00-{int(last_h):02d}:59"
|
||||
if first_h is not None and last_h is not None
|
||||
else "--"
|
||||
)
|
||||
if peak_status == "past":
|
||||
headline = "峰值窗口已过，后续更偏向确认最终高点而非继续上修。"
|
||||
confidence = "high" if available_layers >= 2 else "medium"
|
||||
elif suppress_score >= support_score + 2:
|
||||
headline = "峰值存在云雨或结构压制，当前更偏防守高温上修。"
|
||||
confidence = "high" if available_layers >= 3 else "medium"
|
||||
elif support_score >= suppress_score + 2:
|
||||
headline = "峰值仍有上修空间，后续重点看峰值窗口内报文能否继续抬升。"
|
||||
confidence = "high" if available_layers >= 3 else "medium"
|
||||
elif available_layers == 0:
|
||||
headline = "关键日内层仍在补齐，先以观测锚点和下一次报文为主。"
|
||||
confidence = "low"
|
||||
else:
|
||||
headline = "当前处于分歧判断区，峰值窗口内的下一组观测将决定方向。"
|
||||
confidence = "medium" if available_layers >= 2 else "low"
|
||||
|
||||
next_observation = _next_observation_clock(data.get("local_time") or current.get("obs_time"))
|
||||
threshold = base_value
|
||||
invalidation_rules = []
|
||||
confirmation_rules = []
|
||||
if peak_status == "past":
|
||||
invalidation_rules.append("若后续官方结算源补录更高值，以结算源最终高点为准。")
|
||||
confirmation_rules.append("若峰值窗口后连续两次观测不再创新高，当前高点基本确认。")
|
||||
else:
|
||||
watch_clock = _format_clock_minutes(int(first_h or 13) * 60 + 30)
|
||||
if threshold is not None:
|
||||
invalidation_rules.append(f"{watch_clock} 前若仍未接近 {threshold:.0f}{unit}，上修路径降级。")
|
||||
confirmation_rules.append(f"峰值窗口内任一结算源观测触达或超过 {threshold:.0f}{unit}，基准路径确认度上升。")
|
||||
invalidation_rules.append("若 TAF 或实况报文出现阵雨、雷暴或低云/云雨压制，高温上沿需要下调。")
|
||||
confirmation_rules.append("若实测继续贴近 DEB 曲线且云雨信号不增强，维持当前主路径。")
|
||||
|
||||
if not signals:
|
||||
_add_signal(
|
||||
signals,
|
||||
label="数据完整性",
|
||||
direction="neutral",
|
||||
strength="weak",
|
||||
summary="当前缺少足够的日内结构层，等待下一次观测刷新后再提高判断权重。",
|
||||
)
|
||||
|
||||
return {
|
||||
"headline": headline,
|
||||
"confidence": confidence,
|
||||
"base_case_bucket": base_case_bucket,
|
||||
"upside_bucket": upside_bucket,
|
||||
"downside_bucket": downside_bucket,
|
||||
"next_observation_time": next_observation,
|
||||
"peak_window": peak_window,
|
||||
"invalidation_rules": invalidation_rules[:4],
|
||||
"confirmation_rules": confirmation_rules[:3],
|
||||
"signal_contributions": signals[:5],
|
||||
}
|
||||
|
||||
|
||||
def _analyze(
|
||||
city: str,
|
||||
force_refresh: bool = False,
|
||||
@@ -1983,6 +2273,7 @@ def _analyze(
|
||||
"ai_analysis": "",
|
||||
"updated_at": datetime.now(timezone.utc).isoformat(),
|
||||
}
|
||||
result["intraday_meteorology"] = _build_intraday_meteorology(result)
|
||||
|
||||
if include_llm_commentary:
|
||||
result["dynamic_commentary"] = _maybe_enrich_dynamic_commentary_with_groq(
|
||||
@@ -2483,6 +2774,8 @@ def _build_city_detail_payload(
|
||||
},
|
||||
"probabilities": data.get("probabilities") or {"mu": None, "distribution": []},
|
||||
"dynamic_commentary": data.get("dynamic_commentary") or {"summary": "", "notes": []},
|
||||
"intraday_meteorology": data.get("intraday_meteorology")
|
||||
or _build_intraday_meteorology(data),
|
||||
"vertical_profile_signal": data.get("vertical_profile_signal") or {},
|
||||
"taf": data.get("taf") or {},
|
||||
"market_scan": market_scan,
|
||||
|
||||
Reference in New Issue
Block a user