frontend/__tests__/test-data-mocking.ts

/**
 * Test Data Mocking
 * Provides consistent mock data for frontend tests that matches backend API responses.
 */

import { NormEntry } from '../lib/norm-utils';

// Mock Sale Order Details Response
export const mockSaleOrderResponse = {
    sale_order: "81S_81S-25000172",
    dna: {
        Article: "18006BA",
        "Grey Code": "18006BA",
        "Grey Code DB": "18006BA",
        Count: "80",
        Product: "Cotton Normal",
        Route: "Continouse",
        Finish: "Soft",
        "Shade Type": "Dyed",
        "Material Type": "Cotton",
        Customer: "N/A",
        Segment: "N/A",
        "Sub-Segment": "N/A",
        OCDKE1: "18006",
        OCDKE2: "BA",
        OCDKE3: "CT-SF",
        OCDKE4: "5000082944",
        "Dispo Date": "2025-01-10",
        "Pack Date": "2025-01-15",
        "PO Series": "F0U...",
        "Total POs": 1,
        "Input POs": 1,
        "Output POs": 1
    },
    metrics: {
        "Order Qty": 425,
        "PO Qty": 425,
        "Reserved Qty": 495,
        "Actual Issued": 545,
        "Total Packing": 508,
        "Pack Fresh": 510,
        "Shortfall": -85,
        "Status": "Fulfilled",
        "Fresh Yield %": 93.58,
        "Reprocess Count": 0,
        "Reprocess Qty": 0,
        "Rejection Rate %": 0,
        "Extra Gr Reserved %": 16.47,
        "Actual Gr Issue %": 28.24,
        "Shrinkage %": 6.79,
        "Fresh Pkg %": 100.39,
        "Fresh to Order %": 120.00
    },
    calculations: {
        extra_gr_reserved: {
            label: "Extra Gr %age Reserved",
            formula: "(Reserved - PO_Qty) / PO_Qty × 100",
            steps: [
                "= (495 - 425) / 425 × 100",
                "= 70 / 425 × 100",
                "= 16.47%"
            ],
            value: 16.47,
            interpretation: "Greige reserved above PO demand"
        },
        actual_gr_issue: {
            label: "Actual Gr Issue %age",
            formula: "(Issued - PO_Qty) / PO_Qty × 100",
            steps: [
                "= (545 - 425) / 425 × 100",
                "= 28.24%"
            ],
            value: 28.24,
            interpretation: "Total greige issued above PO demand"
        },
        shrinkage: {
            label: "Shrinkage %age (Process Loss)",
            formula: "(Issued - Total Packing) / Issued × 100",
            steps: [
                "= (545 - 508) / 545 × 100",
                "= 6.79%"
            ],
            value: 6.79,
            interpretation: "Material lost during processing"
        },
        fresh_pkg: {
            label: "Fresh Pkg %age",
            formula: "Pack Fresh / Total Packing × 100",
            steps: [
                "= 510 / 508 × 100",
                "= 100.39%"
            ],
            value: 100.39,
            interpretation: "Proportion of packing that is fresh"
        },
        fresh_yield: {
            label: "Fresh Process Yield",
            formula: "Pack Fresh / Fresh Issued × 100",
            steps: [
                "= 510 / 545 × 100",
                "= 93.58%"
            ],
            value: 93.58,
            interpretation: "Efficiency of the first run"
        }
    },
    intelligence: {
        waterfall: [
            { label: "Demand", value: 425, type: "base" },
            { label: "Policy Gap", value: 70, type: "variance", desc: "Norm Buffer" },
            { label: "Execution Adj", value: 50, type: "variance", desc: "Planner Adj" },
            { label: "Process Loss", value: -35, type: "variance", desc: "Net Loss" },
            { label: "Delivered", value: 510, type: "final" }
        ],
        norm_adequacy: 120.0,
        intervention_roi: "High",
        break_even_tolerance: 22.0,
        yield_rate: 93.6,
        blame_breakdown: {
            policy_impact: 70,
            execution_impact: 50,
            process_impact: -35,
            policy_pct: 45.2,
            execution_pct: 32.3,
            process_pct: 22.5
        },
        elasticity: {
            classification: "HIGH",
            value: 0.89
        },
        false_yield_warning: false,
        safety_recommendation: {
            value: 5.5,
            confidence_low: 5.0,
            confidence_high: 6.0
        },
        po_imbalance: {
            detected: false,
            stddev: 0,
            details: []
        },
        min_charge_distortion: false,
        risk_fingerprint: {
            norm_reliability: 0.95,
            policy_sensitivity: "HIGH",
            reprocessing_dependence: 0,
            risk_level: "MEDIUM"
        }
    },
    rows: [
        {
            PO_NO: "F0U0000996",
            "PO Type": "Fresh Input",
            DORQT1: 425,
            RES_QTY: 495,
            ISS_QTY: 545,
            pack_fresh: 510,
            is_input: true,
            is_output: true
        }
    ],
    po_breakdown: [
        {
            po_no: "F0U0000996",
            po_code: "F0U",
            type: "Fresh",
            issued_qty: 545,
            pack_fresh: 510,
            reserved_qty: 495,
            line_no: "1"
        }
    ]
};

// Mock Global Analytics Response
export const mockGlobalAnalyticsResponse = {
    kpis: {
        total_orders: 970,
        total_volume_m: 2500000,
        global_yield_pct: 94.5,
        shortfall_risk_pct: 15.2
    },
    distributions: {
        route: [
            { Route: "Continouse", yield: 94.8, count: 4100 },
            { Route: "Jigger", yield: 92.3, count: 306 },
            { Route: "Jet", yield: 93.1, count: 189 }
        ],
        finish: [
            { Finish: "Soft", yield: 94.2, count: 2500 },
            { Finish: "Peach", yield: 93.8, count: 2100 }
        ],
        shade: [
            { "Shade Type": "Dyed", yield: 94.1, count: 3725 },
            { "Shade Type": "FB", yield: 95.2, count: 659 },
            { "Shade Type": "RFD", yield: 94.5, count: 181 }
        ],
        segment: [],
        customer: []
    },
    trends: [
        { month: "2024-10", yield: 93.5 },
        { month: "2024-11", yield: 94.2 },
        { month: "2024-12", yield: 94.8 }
    ],
    global_waterfall: [
        { label: "Total Demand", value: 2500000, type: "base" },
        { label: "Policy Gap", value: 175000, type: "variance", desc: "Norm vs Demand" },
        { label: "Execution Adj", value: 50000, type: "variance", desc: "Issued vs Norm" },
        { label: "Process Loss", value: -362500, type: "variance", desc: "Defects & Shrinkage" },
        { label: "Delivered", value: 2362500, type: "final" }
    ],
    global_blame: {
        policy_pct: 46.7,
        execution_pct: 13.3,
        process_pct: 40.0
    }
};

// Mock Article Prediction Response
export const mockArticlePredictionResponse = {
    article_id: "18006BA",
    details: {
        product: "Cotton Normal",
        count: "80",
        finish: "Soft",
        route: "Continouse"
    },
    norm_params: {
        division_factor: "Dyed",
        sub_type: "Normal",
        composition: "Cotton",
        count_range: "40s and above"
    },
    stats: {
        total_volume: 150000,
        avg_yield: 93.5,
        total_orders: 25,
        total_input: 165000,
        total_output: 154275
    },
    ai_prediction: {
        historical_orders: 25,
        yield_stats: {
            avg: 93.5,
            min: 88.2,
            max: 98.1,
            std_dev: 2.3
        },
        norm_analysis: {
            applicable_rule_upto_3000: "7% or 100m",
            applicable_rule_above_3000: "5% or 100m",
            base_norm_pct: 7.0,
            min_charge_m: 100
        },
        historical_analysis: {
            avg_actual_reservation_pct: 8.2,
            avg_fulfillment_pct: 102.8,
            success_rate_pct: 92.0,
            shortfall_rate_pct: 8.0,
            fulfilled_orders: 23,
            median_successful_reservation_pct: 7.5,
            performance_gap_pct: 1.2
        },
        recommendation: {
            suggested_reservation_pct: 8.0,
            ai_adjustment_pct: 1.0,
            explanation: "Norms appear adequate based on historical success"
        },
        avg_process_loss_pct: 6.5,
        recommended_multiplier: 1.08,
        confidence: "high"
    },
    orders: [
        {
            id: "81S_81S-25000172",
            volume: 425,
            input: 545,
            output: 510,
            yield: 93.58,
            dates: { dispo: "2025-01-10" }
        }
    ]
};

// Mock Full Data Response
export const mockFullDataResponse = [
    {
        PO_NO: "F0U0000866",
        Article: "18006BA",
        "Order Qty": 153,
        "Reserver Qty as per Std Norms": 223,
        "Actual Gr Opening": 278,
        Deviation: 55,
        Finish: "Soft",
        Route: "Continouse",
        Product: "Cotton Normal"
    },
    {
        PO_NO: "FQT0001479",
        Article: "A240B236HMF",
        "Order Qty": 200,
        "Reserver Qty as per Std Norms": 300,
        "Actual Gr Opening": 313,
        Deviation: 13,
        Finish: "Peach",
        Route: "Continouse",
        Product: "Stretch Cotton"
    }
];

// Mock Trends Response
export const mockTrendsResponse = {
    articles: [
        {
            id: "18006BA",
            name: "18006BA",
            rank: 1,
            count: 25,
            volume: 150000,
            yield: 93.5,
            trend: "up",
            shortfall: -5000,
            shortfall_pct: -3.3,
            success_rate: 92.0,
            deviation: { avg: 5.2, std: 2.1, min: 1.5, max: 12.3 },
            efficiency_score: 89.5,
            risk_level: "low",
            greige_issued: 165000,
            greige_reserved: 160500,
            norm_deviation: { absolute: 4500, percent: 2.8, over_allocated_pct: 65.0, under_allocated_pct: 35.0 },
            waterfall: { demand: 150000, policy_gap: 10500, execution_adj: 4500, process_loss: -10650, delivered: 154350 },
            blame: { policy_pct: 40.5, execution_pct: 17.3, process_pct: 42.2 },
            compliance: { norm_compliance: 85.0, norm_reliability: 92.0 }
        }
    ],
    sale_orders: [],
    po_numbers: [],
    shades: [],
    routes: [],
    finishes: [],
    customers: [],
    segments: [],
    counts: [],
    products: [],
    summary: {
        total_articles: 496,
        total_sale_orders: 970,
        total_pos: 4613,
        avg_yield: 94.2
    }
};

// Mock Norm Entries
export const mockNormEntries: NormEntry[] = [
    {
        id: 1,
        division_factor: "Dyed",
        sub_type: "Peach",
        composition: "Cotton",
        count_range: "Below 40s",
        route: "Continouse",
        rules: {
            upto_3000m: "7% or 100m",
            above_3000m: "5% or 100m"
        },
        tolerance_adjustments: {
            tolerance_3_percent: "1% Extra",
            tolerance_5_7_percent: "2% Extra",
            tolerance_10_percent: "5% Extra",
            tolerance_plus0_minus3_5: "-1% Less",
            tolerance_1_2_percent: "As per Std Norms"
        }
    },
    {
        id: 2,
        division_factor: "Dyed",
        sub_type: "Normal",
        composition: "Cotton",
        count_range: "40s and above",
        route: "Continouse",
        rules: {
            upto_3000m: "5% or 100m",
            above_3000m: "4% or 100m"
        },
        tolerance_adjustments: {
            tolerance_3_percent: "1% Extra",
            tolerance_5_7_percent: "2% Extra",
            tolerance_10_percent: "5% Extra",
            tolerance_plus0_minus3_5: "-1% Less",
            tolerance_1_2_percent: "As per Std Norms"
        }
    },
    {
        id: 3,
        division_factor: "RFD",
        sub_type: "Peach/ Soft",
        composition: "Cotton",
        count_range: "Below 40s",
        route: "Continouse",
        rules: {
            upto_3000m: "5% or 100m",
            above_3000m: "3% or 100m"
        },
        tolerance_adjustments: {
            tolerance_3_percent: "1% Extra",
            tolerance_5_7_percent: "2% Extra",
            tolerance_10_percent: "5% Extra",
            tolerance_plus0_minus3_5: "-1% Less",
            tolerance_1_2_percent: "As per Std Norms"
        }
    }
];

// Helper to create mock fetch response
export function createMockFetchResponse(data: any, ok = true) {
    return {
        ok,
        json: async () => data,
        status: ok ? 200 : 404
    };
}

// Helper formulas matching backend
export const ManualCalculator = {
    extra_gr_reserved_pct: (reserved: number, po_qty: number) => 
        po_qty > 0 ? ((reserved - po_qty) / po_qty) * 100 : 0,
    
    actual_gr_issue_pct: (issued: number, po_qty: number) => 
        po_qty > 0 ? ((issued - po_qty) / po_qty) * 100 : 0,
    
    shrinkage_pct: (issued: number, packing: number) => 
        issued > 0 ? ((issued - packing) / issued) * 100 : 0,
    
    fresh_pkg_pct: (pack_fresh: number, total_packing: number) => 
        total_packing > 0 ? (pack_fresh / total_packing) * 100 : 0,
    
    fresh_yield_pct: (pack_fresh: number, fresh_issued: number) => 
        fresh_issued > 0 ? (pack_fresh / fresh_issued) * 100 : 0,
    
    shortfall: (order_qty: number, pack_fresh: number) => 
        order_qty - pack_fresh,
    
    policy_impact: (reserved: number, demand: number) => 
        reserved - demand,
    
    execution_impact: (issued: number, reserved: number) => 
        issued - reserved,
    
    process_impact: (pack_fresh: number, issued: number) => 
        pack_fresh - issued,
    
    yield_rate: (pack_fresh: number, issued: number) => 
        issued > 0 ? (pack_fresh / issued) * 100 : 0,
    
    norm_score: (pack_fresh: number, demand: number) => 
        demand > 0 ? (pack_fresh / demand) * 100 : 0
};