fad458b2a7
- UIUX 文档:填充 19 个缺口(多主体画像/健康度/AI+看板/增长域/洞察域/创始人端/OODA/助推/商密) - UIUX 文档:插入 6 个新章节(十四~十九),旧章节重编号为二十~三十一,更新目录和交叉引用 - 作业指导书 x5:导航改为 6 域分组,新增 Context Bar/工作模式/Insight Rail/决策线程/多工作区等 UI 概念 - 新建 docs/2-task-uiux.md:50 个代码落地开发任务,按 P0-P6 分优先级 + 8 Sprint 规划 - 后端/前端:大量新增模型、路由、组件(来自之前 Phase 开发)
94 lines
3.4 KiB
Python
94 lines
3.4 KiB
Python
"""T4.10 智能预警 + 预测分析测试。"""
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import pytest
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from fastapi.testclient import TestClient
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from app.services.predictor import predict_trend, detect_anomalies
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class TestPredictTrend:
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"""趋势预测函数测试。"""
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def test_predict_with_sufficient_data(self):
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"""有足够历史数据时应返回预测。"""
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result = predict_trend([60, 62, 65, 68, 70], months_ahead=3)
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assert "predicted" in result
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assert len(result["predicted"]) == 3
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assert all(0 <= p <= 100 for p in result["predicted"])
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assert result["confidence"] > 0
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def test_predict_with_insufficient_data(self):
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"""数据不足时应返回空预测。"""
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result = predict_trend([50], months_ahead=3)
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assert result["predicted"] == []
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assert result["confidence"] == 0.0
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def test_predict_stable_trend(self):
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"""稳定趋势斜率应接近 0。"""
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result = predict_trend([70, 70, 70, 70], months_ahead=2)
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assert abs(result["slope"]) < 0.1
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def test_predict_upward_trend(self):
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"""上升趋势斜率应为正。"""
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result = predict_trend([50, 55, 60, 65, 70], months_ahead=2)
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assert result["slope"] > 0
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def test_predict_downward_trend(self):
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"""下降趋势斜率应为负。"""
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result = predict_trend([80, 75, 70, 65, 60], months_ahead=2)
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assert result["slope"] < 0
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class TestDetectAnomalies:
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"""异常检测函数测试。"""
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def test_detect_with_normal_data(self):
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"""正常数据不应检测到异常。"""
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result = detect_anomalies([70, 71, 69, 70, 71])
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assert result == []
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def test_detect_with_anomaly(self):
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"""包含异常值时应检测到。"""
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result = detect_anomalies([70, 71, 69, 70, 500], threshold=1.5)
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assert len(result) > 0
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assert 4 in result
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def test_detect_with_insufficient_data(self):
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"""数据不足时应返回空。"""
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assert detect_anomalies([50, 60]) == []
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def test_detect_with_constant_data(self):
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"""恒定数据不应检测到异常。"""
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assert detect_anomalies([70, 70, 70, 70]) == []
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class TestForecastEndpoint:
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"""预测接口测试。"""
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def test_forecast_empty(self, client: TestClient, auth_headers: dict):
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"""无历史数据时应正常返回。"""
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resp = client.get("/api/v1/dashboard/forecasts", headers=auth_headers)
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assert resp.status_code == 200
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data = resp.json()["data"]
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assert "predictions" in data
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assert "trend_direction" in data
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assert "anomalies" in data
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def test_forecast_with_company_id(self, client: TestClient, auth_headers: dict, company_id: str):
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"""指定企业 ID 应正常返回。"""
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resp = client.get(
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f"/api/v1/dashboard/forecasts?company_id={company_id}&months_ahead=3",
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headers=auth_headers,
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)
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assert resp.status_code == 200
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def test_forecast_invalid_months(self, client: TestClient, auth_headers: dict):
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"""无效 months_ahead 应返回 422。"""
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resp = client.get("/api/v1/dashboard/forecasts?months_ahead=0", headers=auth_headers)
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assert resp.status_code == 422
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def test_forecast_no_auth(self, client: TestClient):
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"""未认证应返回 401。"""
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resp = client.get("/api/v1/dashboard/forecasts")
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assert resp.status_code == 401
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