{"version":3,"file":"API.CGuhnZHy.mjs","names":[],"sources":["https:/framerusercontent.com/modules/vsUFLrh6zDP8ehsYHBc4/4tE9WjvrRxDc1mH0ELIK/MpgCalculation.js","https:/framerusercontent.com/modules/jXi0FPiL6t5NPBGq2SVv/1d5pN1tFeyU1kLCEu0m8/API.js"],"sourcesContent":["function _define_property(obj,key,value){if(key in obj){Object.defineProperty(obj,key,{value:value,enumerable:true,configurable:true,writable:true});}else{obj[key]=value;}return obj;}// MCP COMPATIBILITY. SEE FOOTER.\n// ============================================================\n// CONSTANTS (from telematic_connection_base.py)\n// ============================================================\nexport const KM_PER_MILE=1.60934;export const LITERS_PER_GALLON=3.78541;export const MIN_TESTABLE_KM_PER_HOUR=.1;export const MIN_TESTABLE_LITERS_PER_HOUR=.1;export const MIN_TESTABLE_KM_PER_LITER=.1;export const MAX_TESTABLE_KM_PER_LITER=50;export const METERS_PER_MILE=KM_PER_MILE*1e3;// ============================================================\n// DATETIME INTERPOLATOR\n// ============================================================\n/**\n * Simple linear interpolator for time series data.\n * Converts timestamps to seconds since epoch and performs linear interpolation.\n * \n * Args:\n * timestamps: Array of Date objects\n * values: Array of numeric values to interpolate\n */export class DatetimeInterpolator{/**\n * Interpolate value at a single timestamp.\n * \n * Args:\n * timestamp: Date object to interpolate at\n * \n * Returns:\n * Interpolated value\n */interpolateAt(timestamp){const targetSeconds=timestamp.getTime()/1e3;// If before first point, use first value\nif(targetSeconds<=this.secondsSinceEpoch[0]){return this.values[0];}// If after last point, use last value\nif(targetSeconds>=this.secondsSinceEpoch[this.secondsSinceEpoch.length-1]){return this.values[this.values.length-1];}// Find the two points to interpolate between\nfor(let i=1;ithis.interpolateAt(t));}constructor(timestamps,values){_define_property(this,\"timestamps\",void 0);_define_property(this,\"values\",void 0);_define_property(this,\"secondsSinceEpoch\",void 0);if(timestamps.length!==values.length){throw new Error(`Timestamps and values must have same length: ${timestamps.length} vs ${values.length}`);}if(timestamps.length===0){throw new Error(\"Timestamps and values cannot be empty\");}this.timestamps=timestamps;this.values=values;// Convert to seconds since epoch\nthis.secondsSinceEpoch=timestamps.map(t=>t.getTime()/1e3);}}// ============================================================\n// MPG CALCULATION\n// ============================================================\n/**\n * Calculate MPG from odometer and fuel time series data.\n * \n * This is a direct port of the Python function in\n * ferox-systems-backend-v3/app/services/geotab_connection/mpg_calculation.py\n * \n * Args:\n * odometerDates: Timestamps for odometer readings\n * odometerValues: Odometer values in meters\n * fuelDates: Timestamps for fuel readings\n * fuelValues: Fuel values in liters\n * startDate: Start of analysis period\n * endDate: End of analysis period\n * sampleIntervalSeconds: Sampling interval in seconds (default: 900 = 15 min)\n * \n * Returns:\n * Object with dates and mpg_values arrays\n * \n * Raises:\n * Error: If data is invalid\n */export function calculateMpgFromTimeSeries(odometerDates,odometerValues,fuelDates,fuelValues,startDate,endDate,sampleIntervalSeconds=900){// Validate inputs\nif(startDate>=endDate){throw new Error(`Start date must be before end date: ${startDate.toISOString()} >= ${endDate.toISOString()}`);}if(odometerDates.length===0||fuelDates.length===0||odometerValues.length===0||fuelValues.length===0){return{dates:[],mpg_values:[]};}if(odometerDates.length!==odometerValues.length){throw new Error(`Odometer dates and values must have same length: ${odometerDates.length} vs ${odometerValues.length}`);}if(fuelDates.length!==fuelValues.length){throw new Error(`Fuel dates and values must have same length: ${fuelDates.length} vs ${fuelValues.length}`);}// Create interpolators\nconst odomInterpolator=new DatetimeInterpolator(odometerDates,odometerValues);const fuelInterpolator=new DatetimeInterpolator(fuelDates,fuelValues);// Determine actual time range available in data\nconst firstTime=new Date(Math.max(Math.min(...odometerDates.map(d=>d.getTime())),Math.min(...fuelDates.map(d=>d.getTime()))));const lastTime=new Date(Math.min(Math.max(...odometerDates.map(d=>d.getTime())),Math.max(...fuelDates.map(d=>d.getTime()))));// Adjust start/end dates to available data range\nconst actualStart=new Date(Math.max(startDate.getTime(),firstTime.getTime()));const actualEnd=new Date(Math.min(endDate.getTime(),lastTime.getTime()));if(actualStart>=actualEnd){return{dates:[],mpg_values:[]};}// Generate sample times\nconst sampleTimes=[];let currentTime=actualStart.getTime();const endTime=actualEnd.getTime();const intervalMs=sampleIntervalSeconds*1e3;while(currentTime<=endTime){sampleTimes.push(new Date(currentTime));currentTime+=intervalMs;}if(sampleTimes.length===0){return{dates:[],mpg_values:[]};}// Interpolate data at sample times\nconst odometerInterpolated=odomInterpolator.interpolate(sampleTimes);const fuelInterpolated=fuelInterpolator.interpolate(sampleTimes);if(sampleTimes.length<2){return{dates:[],mpg_values:[]};}// Calculate thresholds based on sample interval\nconst hours=sampleIntervalSeconds/3600;const minDistM=MIN_TESTABLE_KM_PER_HOUR*1e3*hours;const minFuelL=MIN_TESTABLE_LITERS_PER_HOUR*hours;const dates=[];const mpgValues=[];// Calculate MPG for each interval\nfor(let i=1;i=minDistM;const meetsFuelThreshold=fuelL>=minFuelL;if(meetsMovementThreshold&&meetsFuelThreshold){// Calculate km/L for efficiency check\nconst km=distM/1e3;const kmPerL=km/fuelL;const aboveMinEffThreshold=kmPerL>=MIN_TESTABLE_KM_PER_LITER;const belowMaxEffThreshold=kmPerL<=MAX_TESTABLE_KM_PER_LITER;if(aboveMinEffThreshold&&belowMaxEffThreshold){const miles=distM/METERS_PER_MILE;const gallons=fuelL/LITERS_PER_GALLON;dates.push(sampleTimes[i]);mpgValues.push(miles/gallons);}}}return{dates,mpg_values:mpgValues};}/**\n * MCP COMPATIBILITY FOOTER. DO NOT MODIFY.\n * FEROX SYSTEMS 2025\n * @framerDisableUnlink\n */export function withMcp(Component){return Component;}\nexport const __FramerMetadata__ = {\"exports\":{\"MIN_TESTABLE_KM_PER_LITER\":{\"type\":\"variable\",\"annotations\":{\"framerContractVersion\":\"1\"}},\"DatetimeInterpolator\":{\"type\":\"class\",\"annotations\":{\"framerContractVersion\":\"1\"}},\"LITERS_PER_GALLON\":{\"type\":\"variable\",\"annotations\":{\"framerContractVersion\":\"1\"}},\"KM_PER_MILE\":{\"type\":\"variable\",\"annotations\":{\"framerContractVersion\":\"1\"}},\"MpgTimeSeries\":{\"type\":\"tsType\",\"annotations\":{\"framerContractVersion\":\"1\"}},\"MAX_TESTABLE_KM_PER_LITER\":{\"type\":\"variable\",\"annotations\":{\"framerContractVersion\":\"1\"}},\"MIN_TESTABLE_LITERS_PER_HOUR\":{\"type\":\"variable\",\"annotations\":{\"framerContractVersion\":\"1\"}},\"MIN_TESTABLE_KM_PER_HOUR\":{\"type\":\"variable\",\"annotations\":{\"framerContractVersion\":\"1\"}},\"METERS_PER_MILE\":{\"type\":\"variable\",\"annotations\":{\"framerContractVersion\":\"1\"}},\"withMcp\":{\"type\":\"reactHoc\",\"name\":\"withMcp\",\"annotations\":{\"framerContractVersion\":\"1\",\"framerDisableUnlink\":\"\"}},\"calculateMpgFromTimeSeries\":{\"type\":\"function\",\"annotations\":{\"framerContractVersion\":\"1\"}},\"__FramerMetadata__\":{\"type\":\"variable\"}}}\n//# sourceMappingURL=./MpgCalculation.map","/**\n * Analysis API - Functions for the pilot analysis journey\n *\n * API flow:\n * 1. getMpgHistory - Fetch 15-minute resolution MPG data\n * 2. getSingleTruckPlot - Generate PNG timeseries for quality inspection\n * 3. getQualityCheck - Get data quality metrics\n * 4. getImpactEstimate - Run statistical analysis (regression)\n * 5. getComparisonPlot - Generate treatment comparison PNG\n * 6. getPredictionPlot - Generate per-truck prediction PNG\n */import{API_URL}from\"https://framerusercontent.com/modules/SwQjqWc6j32r4pQLdM35/uX7wTJ9jsSCOQYqT068Y/Constants.js\";import{apiPost}from\"https://framerusercontent.com/modules/AAXvLQIFKKh9GsTWu6EG/rAHAKNIDUeW6aHKkIL7V/Api.js\";import{loadUploadedData}from\"https://framerusercontent.com/modules/Q70GysxGEEGNZ5kgxFcP/CYjjkbuAdjCJtQ89rYU9/LocalStorage.js\";import{calculateMpgFromTimeSeries}from\"https://framerusercontent.com/modules/vsUFLrh6zDP8ehsYHBc4/4tE9WjvrRxDc1mH0ELIK/MpgCalculation.js\";// ===== Constants =====\n// 15-minute sampling for analysis (900 seconds)\nexport const ANALYSIS_SAMPLE_INTERVAL_SECONDS=3600;// Default study period (6 months)\nexport function getDefaultStudyDates(){const endDate=new Date;const startDate=new Date;startDate.setMonth(startDate.getMonth()-6);return{startDate,endDate};}// ===== Data Validation =====\n/**\n * Check if an MpgHistory has usable data.\n * Returns false if dates or mpg_readings are empty/missing.\n */export function hasValidMpgData(history){return history!=null&&Array.isArray(history.dates)&&history.dates.length>0&&Array.isArray(history.mpg_readings)&&history.mpg_readings.length>0;}// ===== Manual Upload Helper =====\n/**\n * Get MPG history from manually uploaded CSV data.\n * \n * Args:\n * truck: Truck object with id matching uploaded data\n * startDate: Start of analysis period\n * endDate: End of analysis period\n * \n * Returns:\n * MpgHistory object with calculated MPG values\n * \n * Raises:\n * Error: If no uploaded data found or truck not in data\n */function getMpgHistoryFromUpload(truck,startDate,endDate){// Load uploaded data from localStorage\nconst uploadData=loadUploadedData();if(!uploadData){throw new Error(\"No uploaded data found. Please upload CSV files first.\");}// Find truck data\nconst truckData=uploadData.truckData[truck.id];if(!truckData){throw new Error(`Truck ${truck.id} not found in uploaded data. Available trucks: ${Object.keys(uploadData.truckData).join(\", \")}`);}// Convert ISO string dates to Date objects\nconst odometerDates=truckData.odometer.dates.map(d=>new Date(d));const fuelDates=truckData.fuel.dates.map(d=>new Date(d));// Calculate MPG using client-side implementation\nconst mpgResult=calculateMpgFromTimeSeries(odometerDates,truckData.odometer.values,fuelDates,truckData.fuel.values,startDate,endDate,ANALYSIS_SAMPLE_INTERVAL_SECONDS);// Convert Date objects back to ISO strings for API compatibility\nconst datesAsStrings=mpgResult.dates.map(d=>d.toISOString());return{truck,dates:datesAsStrings,mpg_readings:mpgResult.mpg_values};}// ===== API Functions =====\n/**\n * Fetch MPG history for a single truck.\n * Uses 15-minute sampling interval for high-resolution analysis.\n * \n * For \"upload\" provider, calculates MPG from localStorage data.\n * For \"geotab\" and \"motive\", fetches from backend API.\n */export async function getMpgHistory(sessionId,service,truck,startDate,endDate){// Handle manual upload provider (client-side calculation)\nif(service===\"upload\"){return getMpgHistoryFromUpload(truck,startDate,endDate);}// Handle API providers (backend calculation)\nconst endpoint=`/api/v1/telematics/${service}/get_mpg_history`;const query={truck,start_date:startDate.toISOString(),end_date:endDate.toISOString(),sample_interval_in_seconds:ANALYSIS_SAMPLE_INTERVAL_SECONDS};const data=await apiPost(endpoint,{queries:[query]},sessionId);// Backend returns array, we requested one truck\nreturn data.mpg_histories[0];}/**\n * Generate a PNG timeseries plot for a single truck.\n * Used for quality inspection on the dates page.\n * Requests a large PNG (1320x300) to fill the max container width.\n */export async function getSingleTruckPlot(mpgHistory,treatmentStartDate,treatmentEndDate,sessionId){const endpoint=\"/api/v1/plots/single_truck_timeseries\";const response=await fetch(`${API_URL}${endpoint}`,{method:\"POST\",headers:{\"Content-Type\":\"application/json\",\"X-Session-ID\":sessionId},body:JSON.stringify({data:{mpg_history:mpgHistory,treatment_start_date:treatmentStartDate?.toISOString()??null,treatment_end_date:treatmentEndDate?.toISOString()??null},output:{format:\"png\",width:1320,height:300,max_points:1e4}})});if(!response.ok){throw new Error(`Plot API error: ${response.status}`);}// Convert PNG bytes to base64 data URL\nconst blob=await response.blob();return new Promise((resolve,reject)=>{const reader=new FileReader;reader.onloadend=()=>resolve(reader.result);reader.onerror=reject;reader.readAsDataURL(blob);});}/**\n * Check data quality for a single truck's timeseries.\n * Returns observation counts, variance metrics, and caveats.\n */export async function getQualityCheck(mpgHistory,treatmentStartDate,treatmentEndDate,sessionId){const endpoint=\"/api/v1/quality/check_truck\";return apiPost(endpoint,{mpg_history:mpgHistory,treatment_start_date:treatmentStartDate.toISOString(),treatment_end_date:treatmentEndDate.toISOString()},sessionId);}/**\n * Run the full statistical analysis (Anthos regression).\n * Returns raw API response - use enrichRegressionResults() to add computed aggregates.\n */export async function getImpactEstimate(controlMpgHistories,testMpgHistories,treatmentStartDate,treatmentEndDate,sessionId){const endpoint=\"/api/v1/statistics/impact_estimate\";return apiPost(endpoint,{control_trucks:controlMpgHistories,test_trucks:testMpgHistories,treatment_start_date:treatmentStartDate.toISOString(),treatment_end_date:treatmentEndDate.toISOString()},sessionId);}/**\n * Generate treatment comparison bar chart PNG.\n * Shows before/after averages with scatter overlay.\n */export async function getComparisonPlot(baselineAvgMpg,treatmentAvgMpg,baselineMpgValues,treatmentMpgValues,sessionId){const endpoint=\"/api/v1/plots/treatment_comparison\";const response=await fetch(`${API_URL}${endpoint}`,{method:\"POST\",headers:{\"Content-Type\":\"application/json\",\"X-Session-ID\":sessionId},body:JSON.stringify({data:{baseline_avg_mpg:baselineAvgMpg,treatment_avg_mpg:treatmentAvgMpg,baseline_mpg_values:baselineMpgValues,treatment_mpg_values:treatmentMpgValues},output:{format:\"png\",width:1e3,height:500}})});if(!response.ok){throw new Error(`Comparison plot API error: ${response.status}`);}const blob=await response.blob();return new Promise((resolve,reject)=>{const reader=new FileReader;reader.onloadend=()=>resolve(reader.result);reader.onerror=reject;reader.readAsDataURL(blob);});}/**\n * Generate prediction plot PNG for a single truck.\n * Shows actual MPG with model prediction overlay.\n */export async function getPredictionPlot(mpgHistory,truckAnalysis,regressionResults,treatmentStartDate,treatmentEndDate,sessionId){const endpoint=\"/api/v1/plots/timeseries_with_prediction\";const response=await fetch(`${API_URL}${endpoint}`,{method:\"POST\",headers:{\"Content-Type\":\"application/json\",\"X-Session-ID\":sessionId},body:JSON.stringify({data:{mpg_history:mpgHistory,truck_analysis:truckAnalysis,regression_results:regressionResults,treatment_start_date:treatmentStartDate.toISOString(),treatment_end_date:treatmentEndDate.toISOString()},output:{format:\"png\",width:1e3,height:400,max_points:1e4}})});if(!response.ok){throw new Error(`Prediction plot API error: ${response.status}`);}const blob=await response.blob();return new Promise((resolve,reject)=>{const reader=new FileReader;reader.onloadend=()=>resolve(reader.result);reader.onerror=reject;reader.readAsDataURL(blob);});}/**\n * MCP COMPATIBILITY FOOTER. DO NOT MODIFY.\n * FEROX SYSTEMS 2025\n * @framerDisableUnlink\n */export function withMcp(Component){return Component;}\nexport const __FramerMetadata__ = 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