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# Architecture
Nøkken follows a feature-first architecture with clear separation of concerns.
## Project Structure
```
lib/
├── main.dart # Application entry point
├── src/
├── app.dart # App configuration and theme setup
├── core/ # Core functionality shared across features
│ ├── constants/ # App-wide constants
│ ├── screens/ # Core screens (main container)
│ ├── services/ # Shared services (database, navigation, etc.)
│ ├── theme/ # Theming system
│ └── utils/ # Utility functions
├── features/ # Feature modules
├── medication_tracker/ # Medication tracking feature
├── bloodwork_tracker/ # Bloodwork tracking feature
├── mood_tracker/ # Mood tracking feature
├── stats/ # Statistics / Analysis
├── scheduler/ # Daily tracker and calendar
└── settings/ # Settings and preferences
```
## Dependency Flow
- Features may depend on core services, but never on other features
- Core services are designed to be independent and modular
- Data flows from the database through state providers to UI components
## State Management
Nokken uses [Riverpod](https://riverpod.dev/docs/introduction/why_riverpod) for state management.

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# Database Service
The DatabaseService is the heart of Nokken's data persistence layer, providing a structured interface to the SQLite database.
## Key Responsibilities
- Managing the SQLite database schema and versioning
- Providing CRUD operations for all entity types
- Abstracting database operations from the rest of the application
- Handling error management through a custom `DatabaseException` class
## Interactions with Other Services
- Feature modules: All feature modules interact with the database service to store and retrieve data
- State providers: Riverpod state providers use the database service to fetch data
- `ValidationService`: Database operations use validation to ensure data integrity
## Database Schema
The database consists of several tables:
- `medications`: Stores medication information
- `taken_medications`: Records which medications have been taken
- `bloodwork`: Stores lab results and appointment information
- `mood_entries`: Stores daily mood and wellness metrics

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# Health Analytics Service
The Health Analytics Service provides advanced statistical analysis capabilities for health-related data. It's designed to identify patterns, correlations, and insights in health metrics through a high-performance native C++ implementation with a Dart interface.
This service leverages Foreign Function Interface (FFI) to bridge Dart applications with the C++ analytics engine, enabling complex health data analysis with minimal computational overhead in Flutter applications.
Key capabilities include statistical computations, correlation identification, time series analysis, anomaly detection, clustering, and health-specific analyses like medication impact and hormone level monitoring.
## Table of Contents
- [Core Features](#core-features)
- [API Reference](#api-reference)
- [Basic Statistics](#basic-statistics)
- [Trend Analysis](#trend-analysis)
- [Correlation Analysis](#correlation-analysis)
- [Multivariate Analysis](#multivariate-analysis)
- [Cluster Analysis](#cluster-analysis)
- [Time Series Forecasting](#time-series-forecasting)
- [Anomaly Detection](#anomaly-detection)
- [Factor Impact Analysis](#factor-impact-analysis)
- [Date Pattern Analysis](#date-pattern-analysis)
- [Cycle Analysis](#cycle-analysis)
- [Medication Impact Analysis](#medication-impact-analysis)
- [Hormone Analysis](#hormone-analysis)
- [Comprehensive Analysis](#comprehensive-analysis)
- [Data Models](#data-models)
- [Example Usage](#example-usage)
- [Performance Considerations](#performance-considerations)
- [Troubleshooting](#troubleshooting)
## Core Features
The Health Analytics Service provides the following core functionalities:
- **Statistical Analysis**: Calculate mean, median, variance, standard deviation, quartiles, skewness, and kurtosis for health metrics.
- **Trend Detection**: Identify increasing, decreasing, cyclic, or variable trends in time series data.
- **Correlation Analysis**: Find relationships between various health factors and determine their significance.
- **Multivariate Analysis**: Explore complex relationships between multiple health variables.
- **Clustering**: Group similar health patterns together to identify natural categories.
- **Time Series Forecasting**: Predict future values of health metrics based on historical data.
- **Anomaly Detection**: Identify unusual patterns or outliers in health data.
- **Factor Impact Analysis**: Determine which factors have the strongest influence on target health metrics.
- **Temporal Pattern Analysis**: Discover cyclical patterns and date-related trends (e.g., weekly patterns).
- **Medication Impact Analysis**: Assess how medications affect various health metrics.
- **Hormone Analysis**: Evaluate hormone levels and their impact on health factors.
- **Comprehensive Analysis**: Integrate multiple analysis techniques for holistic health insights.
## API Reference
### Basic Statistics
Calculate fundamental statistics for a health metric:
```dart
HealthStatistics stats = analyticsService.calculateStatistics(values);
```
The `HealthStatistics` object provides:
- mean
- median
- min/max values
- standard deviation
- variance
- skewness
- kurtosis
- quartiles (Q1, Q3)
- interquartile range (IQR)
### Trend Analysis
Detect trends in time series data:
```dart
TrendAnalysis trend = analyticsService.detectTrend(values);
```
This returns a `TrendAnalysis` with:
- trend type (increasing, decreasing, cyclic, variable, or none)
- strength (0-1 scale)
- description of the detected trend
### Correlation Analysis
Find correlations between a target variable and multiple factors:
```dart
List<FactorCorrelation> correlations = analyticsService.findCorrelations(
targetValues,
factorData,
);
```
Where:
- `targetValues` is a list of double values for the target metric
- `factorData` is a map of factor names to lists of double values
Returns a list of `FactorCorrelation` objects with:
- factor name
- correlation coefficient (-1 to 1)
- p-value
- confidence level
### Multivariate Analysis
Find complex relationships between multiple factors:
```dart
List<MultivariateRelationship> relationships = analyticsService.findMultivariateCorrelations(
factorData,
);
```
This identifies various relationship types (direct correlation, mediation, network effects) between three or more factors.
### Cluster Analysis
Group similar data points based on multiple factors:
```dart
List<ClusterPattern> clusters = analyticsService.performClusterAnalysis(
factorData,
maxClusters,
);
```
This identifies natural groupings in the data, returning:
- cluster ID and name
- number of points in each cluster
- significance score
- key factors defining each cluster
- detailed description
### Time Series Forecasting
Predict future values of a health metric:
```dart
TimeSeriesPrediction forecast = analyticsService.predictTimeSeries(
factorName,
timeSeriesData,
stepsAhead,
);
```
Returns predictions with confidence intervals and seasonality information.
### Anomaly Detection
Identify unusual patterns or outliers in health data:
```dart
List<AnomalyResult> anomalies = analyticsService.detectAnomalies(
factorName,
timeSeriesData,
dates,
threshold,
);
```
Detects statistical outliers, contextual anomalies, and trend changes.
### Factor Impact Analysis
Determine which factors have the strongest influence on a target metric:
```dart
List<FactorImpact> impacts = analyticsService.rankFactorImpacts(
factorData,
targetData,
);
```
This analyzes both direct and indirect effects of factors, returning:
- impact score
- direct effect
- indirect effect (through other factors)
- confidence level
- mechanism description
### Date Pattern Analysis
Discover patterns related to specific times (day of week, month, etc.):
```dart
List<DatePattern> patterns = analyticsService.analyzeDatePatterns(
factorName,
values,
dates,
);
```
Identifies weekly, monthly, or custom periodicity patterns.
### Cycle Analysis
Analyze cyclical patterns in health data:
```dart
CycleAnalysis cycles = analyticsService.analyzeCycles(
factorName,
values,
dates,
);
```
Returns information about:
- cycle length
- amplitude
- phase shift
- confidence level
- variance in cycle length
### Medication Impact Analysis
Assess how medications affect health metrics:
```dart
MedicationImpactResult impact = analyticsService.analyzeMedicationImpact(
medicationName,
factorName,
beforeData,
afterData,
);
```
Compares health metrics before and after medication, providing:
- mean values before and after
- magnitude and significance of changes
- overall impact score
- estimated days to effect
### Hormone Analysis
Evaluate hormone levels and their impact on health factors:
```dart
HormoneImpactResult hormoneImpact = analyticsService.analyzeHormoneImpact(
hormoneName,
hormoneLevels,
factorData,
minOptimalLevel,
maxOptimalLevel,
);
```
Provides information about:
- current vs. optimal hormone levels
- deviation from optimal range
- impact on mood and energy
- correlations with other health factors
### Comprehensive Analysis
Generate a holistic analysis combining multiple techniques:
```dart
ComprehensiveHealthAnalysis analysis = await analyticsService.generateComprehensiveAnalysis(
moodEntries: moodEntries,
medications: medications,
takenMedications: takenMedications,
bloodworkEntries: bloodworkEntries,
timeframe: "3 months",
);
```
This integrates all analysis methods to provide a complete health overview.
## Data Models
The service uses the following core data models:
### Health Statistics
```dart
class HealthStatistics {
final double mean;
final double median;
final double min;
final double max;
final double stdDev;
final double variance;
final double skewness;
final double kurtosis;
final double q1;
final double q3;
final double iqr;
}
```
### Trend Analysis
```dart
class TrendAnalysis {
final TrendType type; // enum: none, increasing, decreasing, cyclic, variable
final double strength;
final String description;
}
```
### Factor Correlation
```dart
class FactorCorrelation {
final String factorName;
final double correlation;
final double pValue;
final double confidence;
}
```
### Multivariate Relationship
```dart
class MultivariateRelationship {
final List<String> factorNames;
final double correlationStrength;
final String description;
final double confidence;
final List<double> factorWeights;
final RelationshipType relationshipType;
}
```
### Cluster Pattern
```dart
class ClusterPattern {
final int id;
final String name;
final String description;
final int pointCount;
final double significance;
final List<String> keyFactors;
final List<double> factorImportance;
}
```
### Time Series Prediction
```dart
class TimeSeriesPrediction {
final String factorName;
final List<double> predictions;
final List<List<double>> confidenceIntervals;
final double confidence;
final int seasonalityPeriod;
final TimeUnit timeUnit;
}
```
### Anomaly Result
```dart
class AnomalyResult {
final String factorName;
final int dataPointIndex;
final double anomalyScore;
final String description;
final double originalValue;
final double expectedValue;
final DateTime? date;
final double confidence;
final AnomalyType anomalyType;
}
```
### Factor Impact
```dart
class FactorImpact {
final String factorName;
final double impactScore;
final double directEffect;
final double indirectEffect;
final double confidence;
final String mechanism;
}
```
### Date Pattern
```dart
class DatePattern {
final PatternType type;
final int periodicity;
final double strength;
final String description;
final List<double> peakValues;
final int peakDayOfWeek;
final int peakDayOfMonth;
final int peakMonth;
}
```
### Cycle Analysis
```dart
class CycleAnalysis {
final double cycleLength;
final double cycleLengthVariance;
final double amplitude;
final double phaseShift;
final double confidence;
final String description;
}
```
### Medication Impact Result
```dart
class MedicationImpactResult {
final String medicationName;
final String factorName;
final double beforeMean;
final double afterMean;
final double changeMagnitude;
final double changeSignificance;
final double overallImpact;
final int daysToEffect;
final String description;
}
```
### Hormone Impact Result
```dart
class HormoneImpactResult {
final String hormoneName;
final double currentLevel;
final double optimalLevel;
final double optimalRangeLower;
final double optimalRangeUpper;
final double deviation;
final double impactOnMood;
final double impactOnEnergy;
final Map<String, double> factorImpacts;
final String description;
}
```
### Comprehensive Health Analysis
```dart
class ComprehensiveHealthAnalysis {
final TrendAnalysis moodTrend;
final List<MultivariateRelationship> factorCorrelations;
final List<ClusterPattern> clusters;
final List<AnomalyResult> anomalies;
final List<FactorImpact> factorImpacts;
final List<TimeSeriesPrediction> predictions;
final List<DatePattern> datePatterns;
final List<CycleAnalysis> cycleAnalyses;
final List<HormoneImpactResult> hormoneImpacts;
final List<MedicationImpactResult> medicationImpacts;
final DateTime analysisDate;
final String timeframe;
}
```
## Example Usage
```dart
import 'package:nokken/src/features/health_analytics/health_analytics_service.dart';
import 'package:nokken/src/features/mood_tracker/models/mood_entry.dart';
import 'package:nokken/src/features/medication_tracker/models/medication.dart';
import 'package:nokken/src/features/bloodwork_tracker/models/bloodwork.dart';
Future<void> generateHealthInsights(
List<MoodEntry> moodEntries,
List<Medication> medications,
List<Bloodwork> bloodworkEntries,
) async {
final analyticsService = HealthAnalyticsService();
await analyticsService.initialize();
if (!analyticsService.isInitialized) {
print('Failed to initialize analytics service');
return;
}
// Determine which medications the user is currently taking
final takenMedications = medications
.where((med) => med.isActive)
.map((med) => med.id)
.toSet();
// Generate comprehensive analysis
final analysis = await analyticsService.generateComprehensiveAnalysis(
moodEntries: moodEntries,
medications: medications,
takenMedications: takenMedications,
bloodworkEntries: bloodworkEntries,
timeframe: '3 months',
);
// Present key insights
print('=== HEALTH INSIGHTS ===');
print('Analysis date: ${analysis.analysisDate}');
print('Timeframe: ${analysis.timeframe}');
// Mood trend
print('\n== Mood Trend ==');
print(analysis.moodTrend.description);
// Key correlations
print('\n== Key Correlations ==');
for (final correlation in analysis.factorCorrelations.take(3)) {
print(correlation.description);
}
// Anomalies
print('\n== Anomalies Detected ==');
for (final anomaly in analysis.anomalies.take(5)) {
print('${anomaly.factorName}: ${anomaly.description}');
if (anomaly.date != null) {
print('Date: ${anomaly.date}');
}
}
// Medication impacts
print('\n== Medication Impacts ==');
for (final impact in analysis.medicationImpacts) {
print('${impact.medicationName} → ${impact.factorName}: ${impact.description}');
}
// Predictions
print('\n== Predictions ==');
for (final prediction in analysis.predictions.take(3)) {
print('${prediction.factorName} next week: ${prediction.predictions.first.toStringAsFixed(1)} (confidence: ${(prediction.confidence * 100).toStringAsFixed(1)}%)');
}
}
```
## Performance Considerations
The Health Analytics Service uses a high-performance C++ implementation for computation-intensive operations, but there are still important considerations for optimal usage:
1. **Data Volume**: The service performs well with typical health tracking data volumes (hundreds to thousands of data points), but very large datasets may require batching or sampling.
2. **Memory Management**: The service handles memory allocation and deallocation for native resources, but be mindful of large data structures in Dart code.
3. **Initialization Cost**: The first call to `initialize()` has a one-time overhead for loading the native library.
4. **Operation Complexity**: Operations like cluster analysis and multivariate correlation have higher computational complexity.
5. **Platform Differences**: Performance may vary across platforms. iOS and Android have different native code optimization levels.
## Troubleshooting
### Common Issues
#### Native Library Loading Failures
If you encounter issues loading the native library:
1. Verify the native libraries are correctly placed in platform-specific directories
2. Check that library names match expected platform conventions:
|Platform|Library|
|-------|------|
|Android|`libhealth_analytics.so`|
|iOS|Framework or dynamic library|
|Linux|`libhealth_analytics.so`|
3. For Android, ensure the correct ABIs are supported in your `build.gradle`:
```gradle
android {
defaultConfig {
ndk {
abiFilters 'armeabi-v7a', 'arm64-v8a', 'x86', 'x86_64'
}
}
}
```
#### Insufficient Data Errors
Many analysis methods require minimum data points:
- Basic statistics: at least 1 data point
- Trend analysis: at least 3 data points
- Correlation analysis: at least 3 matched pairs
- Cycle analysis: at least 20 data points
- Cluster analysis: at least 5 data points
Always check data volumes before calling analysis methods and provide appropriate fallbacks or messages when data is insufficient.

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# Core Services
Nokken's architecture is built around several core services that provide foundational functionality to the application. These services follow a singleton pattern for efficient resource usage and are designed with clear separation of concerns.
## Structure
```
lib/src/
├── app.dart # App configuration and theme setup
├── core/ # Core functionality shared across features
│ ├── constants/ # App-wide constants
│ ├── screens/ # Core screens (main container)
│ ├── services/ # Shared services
│ ├── theme/ # Theming system
│ └── utils/ # Utility functions
├── features/ # Feature modules (medication, bloodwork, etc.)
```

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# Navigation Service
Nokken uses a centralized navigation system to handle screen transitions.
## Key Components
- `NavigationService`: Provides methods for navigating between screens
- `AppRouter`: Generates routes based on route names and arguments
- `RouteNames`: Constants for all route paths
- `RouteArguments`: Type-safe argument passing between screens
## Interactions with Other Services
- Feature modules: All screens use the navigation service to navigate between screens
- Core screens: The main container screen uses navigation to switch between feature tabs
- `DialogService`: Uses the navigation service for dialog-related navigation

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# Notification Service
The `NotificationService` handles push notifications for medication reminders and refill alerts using the `flutter_local_notifications` package.
## Key Features
- Platform-aware implementation (only initializes on mobile platforms)
- Scheduling of medication reminders based on time of day
- Support for refill reminders
- Permission handling
## Interactions with Other Services
- Medication Tracker: Uses the service to schedule medication reminders
- Time-based features: Interacts with any feature that requires time-based notifications

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# UI Components
Nokken includes several shared UI components for consistency:
## Theming System
### Key Components
- `AppTheme`: Base theme definitions and spacing/padding constants
- `AppColors`: Theme-aware color values
- `AppTextStyles`: Theme-aware text styles
- `AppIcons`: Centralized icon management
### Theme Management
- Theme state is managed through Riverpod with the `themeProvider`
- `ThemeUtils` provides utility functions for theme management
- Settings Screen: User preferences for theme are stored and managed by the settings feature
```dart
// Provider for the theme mode
final themeProvider = StateProvider<ThemeMode>((ref) => ThemeMode.dark);
// Utility functions for theme management
class ThemeUtils {
static void toggleTheme(WidgetRef ref) {...}
static void setTheme(WidgetRef ref, ThemeMode mode) {...}
}
```
## Widgets
### SharedWidgets
The `SharedWidgets` class provides reusable UI components throughout the app
### Dialog Service
The `DialogService` provides centralized management of dialogs and alerts.
#### Features
- Standard save/discard changes dialog
- Delete confirmation dialog
- Generic back button handler with unsaved changes check

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# Utilities
Nokken includes several utility classes that provide shared functionality:
## DateTimeFormatter
Provides methods for consistent date and time formatting throughout the app.
### Features
- Date formatting with special handling for today/yesterday/tomorrow
- Time formatting and parsing between different formats
- Day of week formatting
- Medication-specific time-related formatting
- Time icon selection based on time of day
## GetIconsColors
Functions for returning appropriate Icon/Color for medication/appointment types.
### Features
- Icon selection based on medication type
- Color selection based on medication type
- Combined icon and color selection for consistent UI
- Icon selection for appointment types
## GetLabels
Functions for returning appropriate text labels for medication/appointment types.
### Features
- Text descriptions for medication types and subtypes
- Text for injection subtypes
- Formatted dosage text based on medication type
- Text for medication status (taken/not taken)
- Text for appointment types
## List Extensions
Additional functionality for lists, currently only the `firstWhereOrNull` method.

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# Validation Service
The `ValidationService` provides centralized validation logic for form inputs, ensuring consistent validation throughout the app.
## Key Features
- Returns `ValidationResult` objects with success status and error messages
- Provides validators for all data types in the application
- Integration with Flutter's form validation system
- Composition of validation rules for complex validations
## Interactions with Other Services
- `DatabaseService`: Validates data before persistence
- Feature modules: Form screens use validation for user input
- Model classes: Constructors validate data during object creation

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# Bloodwork Tracker
The bloodwork tracker feature helps users manage their lab results, medical appointments, and visualize trends in hormone levels over time.
## Models
- `Bloodwork`: Primary model for lab tests and medical appointments.
```dart
class Bloodwork {
final String id;
final DateTime date;
final AppointmentType appointmentType;
final List<HormoneReading> hormoneReadings;
final String? location;
final String? doctor;
final String? notes;
}
```
- `HormoneReading`: Represents an individual hormone measurement with value and unit.
```dart
class HormoneReading {
final String name;
final double value;
final String unit;
// Serialization methods
Map<String, dynamic> toJson() {...}
factory HormoneReading.fromJson(Map<String, dynamic> json) {...}
}
```
- `AppointmentType`: Enumeration for different types of medical appointments (bloodwork, appointment, surgery).
- `HormoneTypes`: Contains predefined hormone types with their default units.
## Providers
- `bloodworkStateProvider`: Manages bloodwork CRUD operations
- Various derived providers:
```dart
// Main state providers
final bloodworkStateProvider = StateNotifierProvider<BloodworkNotifier, BloodworkState>
// Derived providers
final bloodworkRecordsProvider = Provider<List<Bloodwork>>
final bloodworkLoadingProvider = Provider<bool>
final bloodworkErrorProvider = Provider<String?>
final sortedBloodworkProvider = Provider<List<Bloodwork>>
final bloodworkTypeRecordsProvider = Provider<List<Bloodwork>>
final bloodworkDatesProvider = Provider<Set<DateTime>>
final groupedBloodworkProvider = Provider<Map<String, List<Bloodwork>>>
final hormoneTypesProvider = Provider<List<String>>
final hormoneRecordsProvider = Provider.family<List<MapEntry<DateTime, double>>, String>
final latestHormoneValueProvider = Provider.family<double?, String>
```
### State Notifier
```dart
class BloodworkNotifier extends StateNotifier<BloodworkState> {
// Notifier methods
Future<void> loadBloodwork() async {...}
Future<void> addBloodwork(Bloodwork bloodwork) async {...}
Future<void> updateBloodwork(Bloodwork bloodwork) async {...}
Future<void> deleteBloodwork(String id) async {...}
}
```
## Screens
- `BloodworkListScreen`: List of all appointments organized by upcoming/past/today.
- `AddEditBloodworkScreen`: Form for adding and editing appointments and lab results.
- `BloodLevelListScreen`: Overview display of all tracked hormone levels with mini graphs.
- `BloodworkGraphScreen`: Visualizations of hormone levels over time with reference ranges.
## Interactions
- Uses `DatabaseService` for persistent storage of bloodwork data
- Interacts with Scheduler feature to display appointments on calendar and daily views
- Uses `ValidationService` for data validation

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# Feature Modules
Nokken features multiple modules for tracking different aspects of health management. The application follows a feature-first architecture with clear separation of concerns.
- [Medication Tracker](medication-tracker/index.md): Track medications, schedules, and adherence
- [Bloodwork Tracker](bloodwork-tracker/index.md): Manage lab results, medical appointments, and visualize hormone data
- [Mood Tracker](mood-tracker/index.md): Track daily mood and wellness metrics
- [Scheduler](scheduler/index.md): Integrated calendar and daily tracker for all medical events
- [Statistics](statistics/index.md): Analytics dashboards for mood and health trends
- [Settings](settings/index.md): Application preferences and configuration

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# Medication Tracker
The medication tracker feature allows users to manage their medications, track adherence, and receive refill alerts.
## Models
- `Medication`: Core model representing a medication with properties for name, dosage, schedule, inventory, and type-specific details.
- `MedicationDose`: Represents a specific instance of a medication taken at a particular date and time slot.
```dart
class MedicationDose {
final String medicationId;
final DateTime date;
final String timeSlot;
// Methods for generating unique keys
String toKey() {...}
static MedicationDose fromKey(String key) {...}
}
```
- `InjectionDetails`: Extends medication information with injection-specific details like needle types, site rotation, and supplies tracking.
- `InjectionSite`: Manages individual injection locations on the body.
- `InjectionSiteRotation`: Handles the automatic rotation of injection sites.
## Providers
- `medicationStateProvider`: Manages medication CRUD operations with the database.
- `medicationTakenProvider`: Tracks which medications have been taken on specific dates.
- Various derived providers:
```dart
// Main state providers
final medicationStateProvider = StateNotifierProvider<MedicationNotifier, MedicationState>
final medicationTakenProvider = StateNotifierProvider<MedicationTakenNotifier, Set<String>>
// Derived providers
final medicationsProvider = Provider<List<Medication>>
final medicationsLoadingProvider = Provider<bool>
final medicationsErrorProvider = Provider<String?>
final medicationsByNeedRefillProvider = Provider<List<Medication>>
final sortedMedicationsProvider = Provider<List<Medication>>
final groupedMedicationTypeProvider = Provider<Map<String, List<Medication>>>
```
### State Notifiers
```dart
class MedicationNotifier extends StateNotifier<MedicationState> {
// Notifier methods
Future<void> loadMedications() async {...}
Future<void> addMedication(Medication medication) async {...}
Future<void> updateMedication(Medication medication) async {...}
Future<void> updateMedicationQuantity(Medication medication, bool taken) async {...}
Future<void> deleteMedication(String id) async {...}
}
```
```dart
class MedicationTakenNotifier extends StateNotifier<Set<String>> {
// Notifier methods
Future<void> loadTakenMedicationsForDate(DateTime date) async {...}
Future<void> setMedicationTaken(MedicationDose dose, bool taken, {String? customKey}) async {...}
Future<void> clearOldData(int olderThanDays) async {...}
}
```
## Screens
- `MedicationListScreen`: Displays all medications with grouping by type and refill alerts.
- `MedicationDetailScreen`: Detailed view of medication information with adherence tracking.
- `AddEditMedicationScreen`: Form for adding and editing medications with type-specific fields.
- `InjectionSiteTrackerScreen`: Interface for managing and visualizing injection site rotation.
- `InjectionSiteViewerScreen`: Visualization of the current injection site on a body diagram.
## Interactions
- Uses `DatabaseService` for persistent storage of medication data
- Uses `NotificationService` for medication reminders
- Interacts with Scheduler feature to display medications on calendar and daily views
- Uses `ValidationService` to ensure data integrity

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# Mood Tracker
The mood tracker feature allows users to record their daily moods and track various wellness metrics over time, helping users identify patterns and correlations in their wellbeing.
## Models
- `MoodEntry`: Primary model for daily mood records with emotional and health metrics.
- `MoodRating`: Enumeration of mood levels (great, good, okay, meh, bad) with display names, emojis, and descriptions.
- `Emotion`: Various emotional states that can be selected (excited, relaxed, happy, etc.) with display names and emojis.
- **Health Categories**: Multiple enums tracking various wellness metrics: `SleepQuality`, `EnergyLevel`, `LibidoLevel`, `AppetiteLevel`, `FocusLevel`, `DysphoriaLevel`, `ExerciseLevel`
## Providers
- `moodStateProvider`: Manages mood entry CRUD operations
- `moodEntryForDateProvider`: Retrieves mood entries for specific dates
- `moodColorsProvider`: Defines the color scheme for different mood ratings
- `moodEntriesProvider`: Provides access to the full list of mood entries
- `moodEntriesLoadingProvider`: Indicates when mood entries are loading
- `moodEntriesErrorProvider`: Provides access to any error messages
## Screens
- `MoodTrackerScreen`: Form for recording detailed mood and wellness data
- `MoodQuickSelector`: Compact widget for quickly selecting mood from the daily tracker.
## Widgets
- `MoodFieldChips`: Displays mood and wellness data as visual indicator chips.
## Utilities
- `MoodUtils`: Helper functions for mood-related UI elements:
- Color mapping for all mood ratings and health categories
- Emoji and display name access
- Collections of enum values for UI rendering
## Interactions
- Uses `DatabaseService` for persistent storage of mood data
- Uses `NavigationService` for screen transitions
- Interacts with `Scheduler` to display mood indicators on calendar
- Provides data to `Stats` module for analytics and visualizations

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# Scheduler
The scheduler module provides calendar-based visualization and management of health events, including medications, medical appointments, and mood tracking. It offers multiple time-scale views (day/month/year).
## Screens
- `DailyTrackerScreen`: Daily view combining medications, appointments, and mood tracking
- `CalendarScreen`: Monthly calendar view with visual indicators for all health events
- `YearScreen`: An annual overview showing all 365 days simultaneously with color-coded days indicating medical events or mood entries
## View Modes
- `Medical Mode`: Shows medication schedules and medical appointments
- `Mood Mode`: Displays mood tracking data with emotion-based color coding
## Providers
### Core Providers
```dart
// Tracks the currently selected date (used in DailyTrackerScreen)
final selectedDateProvider = StateProvider<DateTime>((ref) => DateTime.now());
// Controls animation direction for day changes
final slideDirectionProvider = StateProvider<bool>((ref) => true);
// Tracks the calendar view mode (medical or mood)
final calendarViewModeProvider = StateProvider<CalendarViewMode>((ref) => CalendarViewMode.medical);
```
### Derived Data Providers
```dart
// Gets bloodwork records for a specific date
final bloodworkForSelectedDateProvider = Provider.family<List<Bloodwork>, DateTime>((ref, date) { ... });
// Processes medication doses with indexes for uniqueness
final uniqueMedicationDosesProvider = Provider.family<List<(MedicationDose, int, Medication)>, DateTime>((ref, date) { ... });
// Checks if a specific medication dose is marked as taken
final isUniqueDoseTakenProvider = Provider.family<bool, (MedicationDose, int)>((ref, params) { ... });
// Checks if there's a mood entry for a specific date
final moodEntryExistsProvider = Provider.family<bool, DateTime>((ref, date) { ... });
```
## Integration
The scheduler module integrates data from:
- `MedicationTracker` for medication schedules
- `BloodworkTracker` for appointments
- `MoodTracker` for mood entries

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# Settings
The settings feature allows users to customize application preferences.
## Screens
- `SettingsScreen`: Interface for changing application settings:
- Theme mode toggle (dark/light)
- Version information
## Providers
- `themeProvider`: Controls dark/light mode settings
## Interactions
- Uses `ThemeUtils` for theme management

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# Statistics
The statistics feature provides statistical analysis and visualization of user health data. It processes information from multiple sources (mood entries, medications, bloodwork, etc.) and uses the `HealthAnalyticsService` to generate insights, identify patterns, detect correlations, and predict trends.
## Architecture
```
lib/src/features/stats/
├── charts/ # Chart widgets for data visualization
├── models/ # Data models for statistical analysis
├── providers/ # Riverpod providers for state management
├── screens/ # UI screens for displaying analytics
├── tabs/ # Tab components for the main stats screen
├── utils/ # Utility functions for analysis and formatting
└── widgets/ # Reusable UI components
```
## Components
### Models
The analytics feature uses a large set of models to represent different types of statistical insights:
- `ComprehensiveAnalysis`: Container for all types of analytics data
- `StatisticalInsight`: Basic statistical findings
- `FactorRelationship`: Relationships between different health factors
- `HealthPattern`: Detected patterns in health data
- `HealthPrediction`: Forecasts of future health metrics
- `HealthAnomaly`: Unusual data points
- `FactorImpactRanking`: Impacts of factors on a target variable
- `WeekdayAnalysis`: Metrics across days of the week
- `HealthStreak`: Consistent periods for health metrics
- `HormoneAnalysis`: Hormone level analysis
- `MedicationImpact`: Effects of medications on health metrics
### Providers
```dart
// Basic statistical insights
final statisticsInsightsProvider = FutureProvider.autoDispose
.family<List<StatisticalInsight>, String>((ref, timeframe) async { ... });
// Comprehensive analysis (More detailed/resource extensive)
final comprehensiveAnalysisProvider = FutureProvider.autoDispose
.family<ComprehensiveAnalysis, String>((ref, timeframe) async { ... });
// Factor-specific analysis
final factorAnalysisProvider = FutureProvider.autoDispose
.family<Map<String, dynamic>, FactorAnalysisParams>((ref, params) async { ... });
```
### Services
The analytics functionality relies on the `HealthAnalyticsService`
### Charts
- `CorrelationsChart`: Displays relationships between factors
- `ImpactChart`: Shows impact ranking of factors
- `WeekdayChart`: Visualizes metrics by day of week
- And other specialized charts
## UI Organization
The main Stats screen is organized into tabs:
- `Overview`: Summary of health insights and key metrics
- `Correlations`: Relationships between different health factors
- `Patterns`: Detected trends and cyclical patterns
- `Factors`: Analysis of what factors affect health metrics
- `Predictions`: Forecasts of future health values
## Factor Analysis
The feature supports detailed analysis of specific factors with the `FactorAnalysisScreen`, which provides:
- Basic statistics (mean, median, min, max)
- Related factors and correlations
- Detected patterns
- Historical timeline
- Health impacts
## Data Sources
The Health Analytics feature consumes data from multiple sources:
- **Mood Tracker**: Emotional state, energy levels, sleep quality, etc.
- **Medication Tracker**: Medication adherence and effects
- **Bloodwork Tracker**: Lab results and hormone levels
## Usage Examples
To access the comprehensive analysis:
```dart
// Watch for analysis data with a specific timeframe
final analysisAsync = ref.watch(comprehensiveAnalysisProvider('Last Month'));
// Use the data when available
analysisAsync.when(
data: (analysis) {
// Access insights, relationships, patterns, etc.
final relationships = analysis.relationships;
final patterns = analysis.patterns;
final predictions = analysis.predictions;
// Build UI with the data
return ListView(
children: [
// Display insights
],
);
},
loading: () => const LoadingView(),
error: (error, stack) => ErrorView(error: error),
);
```
To analyze a specific factor:
```dart
// Watch for factor-specific analysis
final factorAsync = ref.watch(
factorAnalysisProvider(
FactorAnalysisParams(
factorName: 'Mood',
timeframe: 'All Time',
),
),
);
// Use the data when available
factorAsync.when(
data: (factorAnalysis) {
// Access factor-specific data
final relationships = factorAnalysis['relationships'];
final patterns = factorAnalysis['patterns'];
// Build UI with the data
},
loading: () => const LoadingView(),
error: (error, stack) => ErrorView(error: error),
);
```
## Implementation Details
### Correlation Analysis
The service calculates Pearson correlation coefficients between different health factors to identify relationships. For example, it can detect correlations between:
- Sleep quality and mood
- Energy levels and exercise
- Hormone levels and emotions
### Pattern Detection
Patterns are identified through statistical analysis of time series data, including:
- **Trends**: Directional changes over time
- **Cyclical Patterns**: Repeating patterns (e.g., weekly sleep cycles)
- **Clusters**: Groupings of related factors
- **Thresholds**: Significant crossover points
### Anomaly Detection
The service identifies unusual data points using z-score analysis, which detects values that deviate significantly from normal patterns.
### Prediction Algorithm
Predictions are generated using a combination of:
- Linear trend extrapolation
- Moving averages
- Pattern-based forecasting

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# Getting Started
## Prerequisites
- Flutter (2.10.0 or higher)
- Dart (2.16.0 or higher)
- Android Studio / VS Code
- iOS simulator / Android emulator
## Installation
```bash
# Clone the repository
git clone https://github.com/nokken-io/nokkenapp.git
# Navigate to project directory
cd nokken
# Install dependencies
flutter pub get
# Run the app
flutter run
```

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Nøkken (or Nokken) is a medical tracking application built with Flutter. It is designed to work on mobile platforms (iOS / Android) with a strong focus on user privacy.
## Open Source Transparency
Nøkken is fully open source, providing transparency into how your sensitive health data is handled. This approach ensures:
- Full visibility into all application code
- Community verification of privacy and security practices
- The ability to modify, extend, or replace components as needed
- Long-term sustainability independent of any single developer or organization
## Uncompromising Privacy
Nøkken embraces a strict privacy-first approach:
- No data collection: Your health information never leaves your device
- No cloud storage: All data is stored locally on your device
- No tracking: No analytics, telemetry, or usage statistics are collected
- No network requirements: Functions fully offline with no dependency on external services
- No account creation or registration required

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site_name: Nokken Documentation
site_description: Documentation for the Nokken medical tracking application
site_author: Charlotte Croce
repo_url: https://codeberg.org/charlottecroce/nokken
theme:
name: material
features:
- navigation.sections # Groups sidebar items
- navigation.expand # Expands menu by default
- navigation.indexes # Makes section index pages
- toc.integrate # Integrates table of contents into sidebar
- search.highlight # Highlights search results
- search.share # Adds shareable search queries
- content.code.annotate # Enables code annotations
- content.code.copy # Adds copy button to code blocks
palette:
- scheme: slate
primary: black
accent: pink
- scheme: default
primary: blue
accent: pink
highlightjs: true
markdown_extensions:
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guess_lang: false
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use_pygments: true
pygments_lang_class: true
- pymdownx.superfences
- pymdownx.inlinehilite
- tables
- toc:
permalink: true
nav:
- Home:
- Overview: index.md
- Getting Started:
- Overview: getting-started/index.md
- Architecture:
- Overview: architecture/index.md
- Core Services:
- Overview: core/index.md
- Database: core/database.md
- Navigation: core/navigation.md
- Notifications: core/notifications.md
- Health Analytics: core/health_analytics.md
- UI Componenets: core/ui.md
- Utilities: core/utilities.md
- Validation: core/validation.md
- Features:
- Overview: features/index.md
- Medication Tracker: features/medication-tracker/index.md
- Bloodwork Tracker: features/bloodwork-tracker/index.md
- Mood Tracker: features/mood-tracker/index.md
- Scheduler: features/scheduler/index.md
- Statistics: features/statistics/index.md
- Settings: features/settings/index.md

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<h1 id="architecture">Architecture<a class="headerlink" href="#architecture" title="Permanent link">&para;</a></h1>
<p>Nøkken follows a feature-first architecture with clear separation of concerns.</p>
<h2 id="project-structure">Project Structure<a class="headerlink" href="#project-structure" title="Permanent link">&para;</a></h2>
<div class="language-text highlight"><pre><span></span><code>lib/
├── main.dart # Application entry point
├── src/
├── app.dart # App configuration and theme setup
├── core/ # Core functionality shared across features
│ ├── constants/ # App-wide constants
│ ├── screens/ # Core screens (main container)
│ ├── services/ # Shared services (database, navigation, etc.)
│ ├── theme/ # Theming system
│ └── utils/ # Utility functions
├── features/ # Feature modules
├── medication_tracker/ # Medication tracking feature
├── bloodwork_tracker/ # Bloodwork tracking feature
├── mood_tracker/ # Mood tracking feature
├── stats/ # Statistics / Analysis
├── scheduler/ # Daily tracker and calendar
└── settings/ # Settings and preferences
</code></pre></div>
<h2 id="dependency-flow">Dependency Flow<a class="headerlink" href="#dependency-flow" title="Permanent link">&para;</a></h2>
<ul>
<li>Features may depend on core services, but never on other features</li>
<li>Core services are designed to be independent and modular</li>
<li>Data flows from the database through state providers to UI components</li>
</ul>
<h2 id="state-management">State Management<a class="headerlink" href="#state-management" title="Permanent link">&para;</a></h2>
<p>Nokken uses <a href="https://riverpod.dev/docs/introduction/why_riverpod">Riverpod</a> for state management.</p>
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/*!
* Lunr languages, `Danish` language
* https://github.com/MihaiValentin/lunr-languages
*
* Copyright 2014, Mihai Valentin
* http://www.mozilla.org/MPL/
*/
/*!
* based on
* Snowball JavaScript Library v0.3
* http://code.google.com/p/urim/
* http://snowball.tartarus.org/
*
* Copyright 2010, Oleg Mazko
* http://www.mozilla.org/MPL/
*/
!function(e,r){"function"==typeof define&&define.amd?define(r):"object"==typeof exports?module.exports=r():r()(e.lunr)}(this,function(){return function(e){if(void 0===e)throw new Error("Lunr is not present. Please include / require Lunr before this script.");if(void 0===e.stemmerSupport)throw new Error("Lunr stemmer support is not present. Please include / require Lunr stemmer support before this script.");e.da=function(){this.pipeline.reset(),this.pipeline.add(e.da.trimmer,e.da.stopWordFilter,e.da.stemmer),this.searchPipeline&&(this.searchPipeline.reset(),this.searchPipeline.add(e.da.stemmer))},e.da.wordCharacters="A-Za-zªºÀ-ÖØ-öø-ʸˠ-ˤᴀ-ᴥᴬ-ᵜᵢ-ᵥᵫ-ᵷᵹ-ᶾḀ-ỿⁱⁿₐ-ₜKÅℲⅎⅠ-ↈⱠ-ⱿꜢ-ꞇꞋ-ꞭꞰ-ꞷꟷ-ꟿꬰ-ꭚꭜ-ꭤff-stA--",e.da.trimmer=e.trimmerSupport.generateTrimmer(e.da.wordCharacters),e.Pipeline.registerFunction(e.da.trimmer,"trimmer-da"),e.da.stemmer=function(){var r=e.stemmerSupport.Among,i=e.stemmerSupport.SnowballProgram,n=new function(){function e(){var e,r=f.cursor+3;if(d=f.limit,0<=r&&r<=f.limit){for(a=r;;){if(e=f.cursor,f.in_grouping(w,97,248)){f.cursor=e;break}if(f.cursor=e,e>=f.limit)return;f.cursor++}for(;!f.out_grouping(w,97,248);){if(f.cursor>=f.limit)return;f.cursor++}d=f.cursor,d<a&&(d=a)}}function n(){var e,r;if(f.cursor>=d&&(r=f.limit_backward,f.limit_backward=d,f.ket=f.cursor,e=f.find_among_b(c,32),f.limit_backward=r,e))switch(f.bra=f.cursor,e){case 1:f.slice_del();break;case 2:f.in_grouping_b(p,97,229)&&f.slice_del()}}function t(){var e,r=f.limit-f.cursor;f.cursor>=d&&(e=f.limit_backward,f.limit_backward=d,f.ket=f.cursor,f.find_among_b(l,4)?(f.bra=f.cursor,f.limit_backward=e,f.cursor=f.limit-r,f.cursor>f.limit_backward&&(f.cursor--,f.bra=f.cursor,f.slice_del())):f.limit_backward=e)}function s(){var e,r,i,n=f.limit-f.cursor;if(f.ket=f.cursor,f.eq_s_b(2,"st")&&(f.bra=f.cursor,f.eq_s_b(2,"ig")&&f.slice_del()),f.cursor=f.limit-n,f.cursor>=d&&(r=f.limit_backward,f.limit_backward=d,f.ket=f.cursor,e=f.find_among_b(m,5),f.limit_backward=r,e))switch(f.bra=f.cursor,e){case 1:f.slice_del(),i=f.limit-f.cursor,t(),f.cursor=f.limit-i;break;case 2:f.slice_from("løs")}}function o(){var e;f.cursor>=d&&(e=f.limit_backward,f.limit_backward=d,f.ket=f.cursor,f.out_grouping_b(w,97,248)?(f.bra=f.cursor,u=f.slice_to(u),f.limit_backward=e,f.eq_v_b(u)&&f.slice_del()):f.limit_backward=e)}var a,d,u,c=[new r("hed",-1,1),new r("ethed",0,1),new r("ered",-1,1),new r("e",-1,1),new r("erede",3,1),new r("ende",3,1),new r("erende",5,1),new r("ene",3,1),new r("erne",3,1),new r("ere",3,1),new r("en",-1,1),new r("heden",10,1),new r("eren",10,1),new r("er",-1,1),new r("heder",13,1),new r("erer",13,1),new r("s",-1,2),new r("heds",16,1),new r("es",16,1),new r("endes",18,1),new r("erendes",19,1),new r("enes",18,1),new r("ernes",18,1),new r("eres",18,1),new r("ens",16,1),new r("hedens",24,1),new r("erens",24,1),new r("ers",16,1),new r("ets",16,1),new r("erets",28,1),new r("et",-1,1),new r("eret",30,1)],l=[new r("gd",-1,-1),new r("dt",-1,-1),new r("gt",-1,-1),new r("kt",-1,-1)],m=[new r("ig",-1,1),new r("lig",0,1),new r("elig",1,1),new r("els",-1,1),new r("løst",-1,2)],w=[17,65,16,1,0,0,0,0,0,0,0,0,0,0,0,0,48,0,128],p=[239,254,42,3,0,0,0,0,0,0,0,0,0,0,0,0,16],f=new i;this.setCurrent=function(e){f.setCurrent(e)},this.getCurrent=function(){return f.getCurrent()},this.stem=function(){var r=f.cursor;return e(),f.limit_backward=r,f.cursor=f.limit,n(),f.cursor=f.limit,t(),f.cursor=f.limit,s(),f.cursor=f.limit,o(),!0}};return function(e){return"function"==typeof e.update?e.update(function(e){return n.setCurrent(e),n.stem(),n.getCurrent()}):(n.setCurrent(e),n.stem(),n.getCurrent())}}(),e.Pipeline.registerFunction(e.da.stemmer,"stemmer-da"),e.da.stopWordFilter=e.generateStopWordFilter("ad af alle alt anden at blev blive bliver da de dem den denne der deres det dette dig din disse dog du efter eller en end er et for fra ham han hans har havde have hende hendes her hos hun hvad hvis hvor i ikke ind jeg jer jo kunne man mange med meget men mig min mine mit mod ned noget nogle nu når og også om op os over på selv sig sin sine sit skal skulle som sådan thi til ud under var vi vil ville vor være været".split(" ")),e.Pipeline.registerFunction(e.da.stopWordFilter,"stopWordFilter-da")}});

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!function(e,r){"function"==typeof define&&define.amd?define(r):"object"==typeof exports?module.exports=r():r()(e.lunr)}(this,function(){return function(e){if(void 0===e)throw new Error("Lunr is not present. Please include / require Lunr before this script.");if(void 0===e.stemmerSupport)throw new Error("Lunr stemmer support is not present. Please include / require Lunr stemmer support before this script.");e.hi=function(){this.pipeline.reset(),this.pipeline.add(e.hi.trimmer,e.hi.stopWordFilter,e.hi.stemmer),this.searchPipeline&&(this.searchPipeline.reset(),this.searchPipeline.add(e.hi.stemmer))},e.hi.wordCharacters="ऀ-ःऄ-एऐ-टठ-यर-िी-ॏॐ-य़ॠ-९॰-ॿa-zA-Z--0-9-",e.hi.trimmer=e.trimmerSupport.generateTrimmer(e.hi.wordCharacters),e.Pipeline.registerFunction(e.hi.trimmer,"trimmer-hi"),e.hi.stopWordFilter=e.generateStopWordFilter("अत अपना अपनी अपने अभी अंदर आदि आप इत्यादि इन इनका इन्हीं इन्हें इन्हों इस इसका इसकी इसके इसमें इसी इसे उन उनका उनकी उनके उनको उन्हीं उन्हें उन्हों उस उसके उसी उसे एक एवं एस ऐसे और कई कर करता करते करना करने करें कहते कहा का काफ़ी कि कितना किन्हें किन्हों किया किर किस किसी किसे की कुछ कुल के को कोई कौन कौनसा गया घर जब जहाँ जा जितना जिन जिन्हें जिन्हों जिस जिसे जीधर जैसा जैसे जो तक तब तरह तिन तिन्हें तिन्हों तिस तिसे तो था थी थे दबारा दिया दुसरा दूसरे दो द्वारा न नके नहीं ना निहायत नीचे ने पर पहले पूरा पे फिर बनी बही बहुत बाद बाला बिलकुल भी भीतर मगर मानो मे में यदि यह यहाँ यही या यिह ये रखें रहा रहे ऱ्वासा लिए लिये लेकिन व वग़ैरह वर्ग वह वहाँ वहीं वाले वुह वे वो सकता सकते सबसे सभी साथ साबुत साभ सारा से सो संग ही हुआ हुई हुए है हैं हो होता होती होते होना होने".split(" ")),e.hi.stemmer=function(){return function(e){return"function"==typeof e.update?e.update(function(e){return e}):e}}();var r=e.wordcut;r.init(),e.hi.tokenizer=function(i){if(!arguments.length||null==i||void 0==i)return[];if(Array.isArray(i))return i.map(function(r){return isLunr2?new e.Token(r.toLowerCase()):r.toLowerCase()});var t=i.toString().toLowerCase().replace(/^\s+/,"");return r.cut(t).split("|")},e.Pipeline.registerFunction(e.hi.stemmer,"stemmer-hi"),e.Pipeline.registerFunction(e.hi.stopWordFilter,"stopWordFilter-hi")}});

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!function(e,r){"function"==typeof define&&define.amd?define(r):"object"==typeof exports?module.exports=r():r()(e.lunr)}(this,function(){return function(e){if(void 0===e)throw new Error("Lunr is not present. Please include / require Lunr before this script.");if(void 0===e.stemmerSupport)throw new Error("Lunr stemmer support is not present. Please include / require Lunr stemmer support before this script.");e.hy=function(){this.pipeline.reset(),this.pipeline.add(e.hy.trimmer,e.hy.stopWordFilter)},e.hy.wordCharacters="[A-Za-z԰-֏ff-ﭏ]",e.hy.trimmer=e.trimmerSupport.generateTrimmer(e.hy.wordCharacters),e.Pipeline.registerFunction(e.hy.trimmer,"trimmer-hy"),e.hy.stopWordFilter=e.generateStopWordFilter("դու և եք էիր էիք հետո նաև նրանք որը վրա է որ պիտի են այս մեջ ն իր ու ի այդ որոնք այն կամ էր մի ես համար այլ իսկ էին ենք հետ ին թ էինք մենք նրա նա դուք եմ էի ըստ որպես ում".split(" ")),e.Pipeline.registerFunction(e.hy.stopWordFilter,"stopWordFilter-hy"),e.hy.stemmer=function(){return function(e){return"function"==typeof e.update?e.update(function(e){return e}):e}}(),e.Pipeline.registerFunction(e.hy.stemmer,"stemmer-hy")}});

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!function(e,r){"function"==typeof define&&define.amd?define(r):"object"==typeof exports?module.exports=r():r()(e.lunr)}(this,function(){return function(e){if(void 0===e)throw new Error("Lunr is not present. Please include / require Lunr before this script.");if(void 0===e.stemmerSupport)throw new Error("Lunr stemmer support is not present. Please include / require Lunr stemmer support before this script.");var r="2"==e.version[0];e.ja=function(){this.pipeline.reset(),this.pipeline.add(e.ja.trimmer,e.ja.stopWordFilter,e.ja.stemmer),r?this.tokenizer=e.ja.tokenizer:(e.tokenizer&&(e.tokenizer=e.ja.tokenizer),this.tokenizerFn&&(this.tokenizerFn=e.ja.tokenizer))};var t=new e.TinySegmenter;e.ja.tokenizer=function(i){var n,o,s,p,a,u,m,l,c,f;if(!arguments.length||null==i||void 0==i)return[];if(Array.isArray(i))return i.map(function(t){return r?new e.Token(t.toLowerCase()):t.toLowerCase()});for(o=i.toString().toLowerCase().replace(/^\s+/,""),n=o.length-1;n>=0;n--)if(/\S/.test(o.charAt(n))){o=o.substring(0,n+1);break}for(a=[],s=o.length,c=0,l=0;c<=s;c++)if(u=o.charAt(c),m=c-l,u.match(/\s/)||c==s){if(m>0)for(p=t.segment(o.slice(l,c)).filter(function(e){return!!e}),f=l,n=0;n<p.length;n++)r?a.push(new e.Token(p[n],{position:[f,p[n].length],index:a.length})):a.push(p[n]),f+=p[n].length;l=c+1}return a},e.ja.stemmer=function(){return function(e){return e}}(),e.Pipeline.registerFunction(e.ja.stemmer,"stemmer-ja"),e.ja.wordCharacters="一二三四五六七八九十百千万億兆一-龠々〆ヵヶぁ-んァ-ヴーア-ン゙a-zA-Z--0-9-",e.ja.trimmer=e.trimmerSupport.generateTrimmer(e.ja.wordCharacters),e.Pipeline.registerFunction(e.ja.trimmer,"trimmer-ja"),e.ja.stopWordFilter=e.generateStopWordFilter("これ それ あれ この その あの ここ そこ あそこ こちら どこ だれ なに なん 何 私 貴方 貴方方 我々 私達 あの人 あのかた 彼女 彼 です あります おります います は が の に を で え から まで より も どの と し それで しかし".split(" ")),e.Pipeline.registerFunction(e.ja.stopWordFilter,"stopWordFilter-ja"),e.jp=e.ja,e.Pipeline.registerFunction(e.jp.stemmer,"stemmer-jp"),e.Pipeline.registerFunction(e.jp.trimmer,"trimmer-jp"),e.Pipeline.registerFunction(e.jp.stopWordFilter,"stopWordFilter-jp")}});

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module.exports=require("./lunr.ja");

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!function(e,r){"function"==typeof define&&define.amd?define(r):"object"==typeof exports?module.exports=r():r()(e.lunr)}(this,function(){return function(e){if(void 0===e)throw new Error("Lunr is not present. Please include / require Lunr before this script.");if(void 0===e.stemmerSupport)throw new Error("Lunr stemmer support is not present. Please include / require Lunr stemmer support before this script.");e.kn=function(){this.pipeline.reset(),this.pipeline.add(e.kn.trimmer,e.kn.stopWordFilter,e.kn.stemmer),this.searchPipeline&&(this.searchPipeline.reset(),this.searchPipeline.add(e.kn.stemmer))},e.kn.wordCharacters="ಀ-಄ಅ-ಔಕ-ಹಾ-ೌ಼-ಽೕ-ೖೝ-ೞೠ-ೡೢ-ೣ೤೥೦-೯ೱ-ೳ",e.kn.trimmer=e.trimmerSupport.generateTrimmer(e.kn.wordCharacters),e.Pipeline.registerFunction(e.kn.trimmer,"trimmer-kn"),e.kn.stopWordFilter=e.generateStopWordFilter("ಮತ್ತು ಈ ಒಂದು ರಲ್ಲಿ ಹಾಗೂ ಎಂದು ಅಥವಾ ಇದು ರ ಅವರು ಎಂಬ ಮೇಲೆ ಅವರ ತನ್ನ ಆದರೆ ತಮ್ಮ ನಂತರ ಮೂಲಕ ಹೆಚ್ಚು ನ ಆ ಕೆಲವು ಅನೇಕ ಎರಡು ಹಾಗು ಪ್ರಮುಖ ಇದನ್ನು ಇದರ ಸುಮಾರು ಅದರ ಅದು ಮೊದಲ ಬಗ್ಗೆ ನಲ್ಲಿ ರಂದು ಇತರ ಅತ್ಯಂತ ಹೆಚ್ಚಿನ ಸಹ ಸಾಮಾನ್ಯವಾಗಿ ನೇ ಹಲವಾರು ಹೊಸ ದಿ ಕಡಿಮೆ ಯಾವುದೇ ಹೊಂದಿದೆ ದೊಡ್ಡ ಅನ್ನು ಇವರು ಪ್ರಕಾರ ಇದೆ ಮಾತ್ರ ಕೂಡ ಇಲ್ಲಿ ಎಲ್ಲಾ ವಿವಿಧ ಅದನ್ನು ಹಲವು ರಿಂದ ಕೇವಲ ದ ದಕ್ಷಿಣ ಗೆ ಅವನ ಅತಿ ನೆಯ ಬಹಳ ಕೆಲಸ ಎಲ್ಲ ಪ್ರತಿ ಇತ್ಯಾದಿ ಇವು ಬೇರೆ ಹೀಗೆ ನಡುವೆ ಇದಕ್ಕೆ ಎಸ್ ಇವರ ಮೊದಲು ಶ್ರೀ ಮಾಡುವ ಇದರಲ್ಲಿ ರೀತಿಯ ಮಾಡಿದ ಕಾಲ ಅಲ್ಲಿ ಮಾಡಲು ಅದೇ ಈಗ ಅವು ಗಳು ಎ ಎಂಬುದು ಅವನು ಅಂದರೆ ಅವರಿಗೆ ಇರುವ ವಿಶೇಷ ಮುಂದೆ ಅವುಗಳ ಮುಂತಾದ ಮೂಲ ಬಿ ಮೀ ಒಂದೇ ಇನ್ನೂ ಹೆಚ್ಚಾಗಿ ಮಾಡಿ ಅವರನ್ನು ಇದೇ ಯ ರೀತಿಯಲ್ಲಿ ಜೊತೆ ಅದರಲ್ಲಿ ಮಾಡಿದರು ನಡೆದ ಆಗ ಮತ್ತೆ ಪೂರ್ವ ಆತ ಬಂದ ಯಾವ ಒಟ್ಟು ಇತರೆ ಹಿಂದೆ ಪ್ರಮಾಣದ ಗಳನ್ನು ಕುರಿತು ಯು ಆದ್ದರಿಂದ ಅಲ್ಲದೆ ನಗರದ ಮೇಲಿನ ಏಕೆಂದರೆ ರಷ್ಟು ಎಂಬುದನ್ನು ಬಾರಿ ಎಂದರೆ ಹಿಂದಿನ ಆದರೂ ಆದ ಸಂಬಂಧಿಸಿದ ಮತ್ತೊಂದು ಸಿ ಆತನ ".split(" ")),e.kn.stemmer=function(){return function(e){return"function"==typeof e.update?e.update(function(e){return e}):e}}();var r=e.wordcut;r.init(),e.kn.tokenizer=function(t){if(!arguments.length||null==t||void 0==t)return[];if(Array.isArray(t))return t.map(function(r){return isLunr2?new e.Token(r.toLowerCase()):r.toLowerCase()});var n=t.toString().toLowerCase().replace(/^\s+/,"");return r.cut(n).split("|")},e.Pipeline.registerFunction(e.kn.stemmer,"stemmer-kn"),e.Pipeline.registerFunction(e.kn.stopWordFilter,"stopWordFilter-kn")}});

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!function(e,t){"function"==typeof define&&define.amd?define(t):"object"==typeof exports?module.exports=t():t()(e.lunr)}(this,function(){return function(e){e.multiLanguage=function(){for(var t=Array.prototype.slice.call(arguments),i=t.join("-"),r="",n=[],s=[],p=0;p<t.length;++p)"en"==t[p]?(r+="\\w",n.unshift(e.stopWordFilter),n.push(e.stemmer),s.push(e.stemmer)):(r+=e[t[p]].wordCharacters,e[t[p]].stopWordFilter&&n.unshift(e[t[p]].stopWordFilter),e[t[p]].stemmer&&(n.push(e[t[p]].stemmer),s.push(e[t[p]].stemmer)));var o=e.trimmerSupport.generateTrimmer(r);return e.Pipeline.registerFunction(o,"lunr-multi-trimmer-"+i),n.unshift(o),function(){this.pipeline.reset(),this.pipeline.add.apply(this.pipeline,n),this.searchPipeline&&(this.searchPipeline.reset(),this.searchPipeline.add.apply(this.searchPipeline,s))}}}});

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/*!
* Lunr languages, `Norwegian` language
* https://github.com/MihaiValentin/lunr-languages
*
* Copyright 2014, Mihai Valentin
* http://www.mozilla.org/MPL/
*/
/*!
* based on
* Snowball JavaScript Library v0.3
* http://code.google.com/p/urim/
* http://snowball.tartarus.org/
*
* Copyright 2010, Oleg Mazko
* http://www.mozilla.org/MPL/
*/
!function(e,r){"function"==typeof define&&define.amd?define(r):"object"==typeof exports?module.exports=r():r()(e.lunr)}(this,function(){return function(e){if(void 0===e)throw new Error("Lunr is not present. Please include / require Lunr before this script.");if(void 0===e.stemmerSupport)throw new Error("Lunr stemmer support is not present. Please include / require Lunr stemmer support before this script.");e.no=function(){this.pipeline.reset(),this.pipeline.add(e.no.trimmer,e.no.stopWordFilter,e.no.stemmer),this.searchPipeline&&(this.searchPipeline.reset(),this.searchPipeline.add(e.no.stemmer))},e.no.wordCharacters="A-Za-zªºÀ-ÖØ-öø-ʸˠ-ˤᴀ-ᴥᴬ-ᵜᵢ-ᵥᵫ-ᵷᵹ-ᶾḀ-ỿⁱⁿₐ-ₜKÅℲⅎⅠ-ↈⱠ-ⱿꜢ-ꞇꞋ-ꞭꞰ-ꞷꟷ-ꟿꬰ-ꭚꭜ-ꭤff-stA--",e.no.trimmer=e.trimmerSupport.generateTrimmer(e.no.wordCharacters),e.Pipeline.registerFunction(e.no.trimmer,"trimmer-no"),e.no.stemmer=function(){var r=e.stemmerSupport.Among,n=e.stemmerSupport.SnowballProgram,i=new function(){function e(){var e,r=w.cursor+3;if(a=w.limit,0<=r||r<=w.limit){for(s=r;;){if(e=w.cursor,w.in_grouping(d,97,248)){w.cursor=e;break}if(e>=w.limit)return;w.cursor=e+1}for(;!w.out_grouping(d,97,248);){if(w.cursor>=w.limit)return;w.cursor++}a=w.cursor,a<s&&(a=s)}}function i(){var e,r,n;if(w.cursor>=a&&(r=w.limit_backward,w.limit_backward=a,w.ket=w.cursor,e=w.find_among_b(m,29),w.limit_backward=r,e))switch(w.bra=w.cursor,e){case 1:w.slice_del();break;case 2:n=w.limit-w.cursor,w.in_grouping_b(c,98,122)?w.slice_del():(w.cursor=w.limit-n,w.eq_s_b(1,"k")&&w.out_grouping_b(d,97,248)&&w.slice_del());break;case 3:w.slice_from("er")}}function t(){var e,r=w.limit-w.cursor;w.cursor>=a&&(e=w.limit_backward,w.limit_backward=a,w.ket=w.cursor,w.find_among_b(u,2)?(w.bra=w.cursor,w.limit_backward=e,w.cursor=w.limit-r,w.cursor>w.limit_backward&&(w.cursor--,w.bra=w.cursor,w.slice_del())):w.limit_backward=e)}function o(){var e,r;w.cursor>=a&&(r=w.limit_backward,w.limit_backward=a,w.ket=w.cursor,e=w.find_among_b(l,11),e?(w.bra=w.cursor,w.limit_backward=r,1==e&&w.slice_del()):w.limit_backward=r)}var s,a,m=[new r("a",-1,1),new r("e",-1,1),new r("ede",1,1),new r("ande",1,1),new r("ende",1,1),new r("ane",1,1),new r("ene",1,1),new r("hetene",6,1),new r("erte",1,3),new r("en",-1,1),new r("heten",9,1),new r("ar",-1,1),new r("er",-1,1),new r("heter",12,1),new r("s",-1,2),new r("as",14,1),new r("es",14,1),new r("edes",16,1),new r("endes",16,1),new r("enes",16,1),new r("hetenes",19,1),new r("ens",14,1),new r("hetens",21,1),new r("ers",14,1),new r("ets",14,1),new r("et",-1,1),new r("het",25,1),new r("ert",-1,3),new r("ast",-1,1)],u=[new r("dt",-1,-1),new r("vt",-1,-1)],l=[new r("leg",-1,1),new r("eleg",0,1),new r("ig",-1,1),new r("eig",2,1),new r("lig",2,1),new r("elig",4,1),new r("els",-1,1),new r("lov",-1,1),new r("elov",7,1),new r("slov",7,1),new r("hetslov",9,1)],d=[17,65,16,1,0,0,0,0,0,0,0,0,0,0,0,0,48,0,128],c=[119,125,149,1],w=new n;this.setCurrent=function(e){w.setCurrent(e)},this.getCurrent=function(){return w.getCurrent()},this.stem=function(){var r=w.cursor;return e(),w.limit_backward=r,w.cursor=w.limit,i(),w.cursor=w.limit,t(),w.cursor=w.limit,o(),!0}};return function(e){return"function"==typeof e.update?e.update(function(e){return i.setCurrent(e),i.stem(),i.getCurrent()}):(i.setCurrent(e),i.stem(),i.getCurrent())}}(),e.Pipeline.registerFunction(e.no.stemmer,"stemmer-no"),e.no.stopWordFilter=e.generateStopWordFilter("alle at av bare begge ble blei bli blir blitt både båe da de deg dei deim deira deires dem den denne der dere deres det dette di din disse ditt du dykk dykkar då eg ein eit eitt eller elles en enn er et ett etter for fordi fra før ha hadde han hans har hennar henne hennes her hjå ho hoe honom hoss hossen hun hva hvem hver hvilke hvilken hvis hvor hvordan hvorfor i ikke ikkje ikkje ingen ingi inkje inn inni ja jeg kan kom korleis korso kun kunne kva kvar kvarhelst kven kvi kvifor man mange me med medan meg meget mellom men mi min mine mitt mot mykje ned no noe noen noka noko nokon nokor nokre nå når og også om opp oss over på samme seg selv si si sia sidan siden sin sine sitt sjøl skal skulle slik so som som somme somt så sånn til um upp ut uten var vart varte ved vere verte vi vil ville vore vors vort vår være være vært å".split(" ")),e.Pipeline.registerFunction(e.no.stopWordFilter,"stopWordFilter-no")}});

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!function(e,r){"function"==typeof define&&define.amd?define(r):"object"==typeof exports?module.exports=r():r()(e.lunr)}(this,function(){return function(e){if(void 0===e)throw new Error("Lunr is not present. Please include / require Lunr before this script.");if(void 0===e.stemmerSupport)throw new Error("Lunr stemmer support is not present. Please include / require Lunr stemmer support before this script.");e.sa=function(){this.pipeline.reset(),this.pipeline.add(e.sa.trimmer,e.sa.stopWordFilter,e.sa.stemmer),this.searchPipeline&&(this.searchPipeline.reset(),this.searchPipeline.add(e.sa.stemmer))},e.sa.wordCharacters="ऀ-ःऄ-एऐ-टठ-यर-िी-ॏॐ-य़ॠ-९॰-ॿ꣠-꣱ꣲ-ꣷ꣸-ꣻ꣼-ꣽꣾ-ꣿᆰ0-ᆰ9",e.sa.trimmer=e.trimmerSupport.generateTrimmer(e.sa.wordCharacters),e.Pipeline.registerFunction(e.sa.trimmer,"trimmer-sa"),e.sa.stopWordFilter=e.generateStopWordFilter('तथा अयम्‌ एकम्‌ इत्यस्मिन्‌ तथा तत्‌ वा अयम्‌ इत्यस्य ते आहूत उपरि तेषाम्‌ किन्तु तेषाम्‌ तदा इत्यनेन अधिकः इत्यस्य तत्‌ केचन बहवः द्वि तथा महत्वपूर्णः अयम्‌ अस्य विषये अयं अस्ति तत्‌ प्रथमः विषये इत्युपरि इत्युपरि इतर अधिकतमः अधिकः अपि सामान्यतया ठ इतरेतर नूतनम्‌ द न्यूनम्‌ कश्चित्‌ वा विशालः द सः अस्ति तदनुसारम् तत्र अस्ति केवलम्‌ अपि अत्र सर्वे विविधाः तत्‌ बहवः यतः इदानीम्‌ द दक्षिण इत्यस्मै तस्य उपरि नथ अतीव कार्यम्‌ सर्वे एकैकम्‌ इत्यादि। एते सन्ति उत इत्थम्‌ मध्ये एतदर्थं . स कस्य प्रथमः श्री. करोति अस्मिन् प्रकारः निर्मिता कालः तत्र कर्तुं समान अधुना ते सन्ति स एकः अस्ति सः अर्थात् तेषां कृते . स्थितम् विशेषः अग्रिम तेषाम्‌ समान स्रोतः ख म समान इदानीमपि अधिकतया करोतु ते समान इत्यस्य वीथी सह यस्मिन् कृतवान्‌ धृतः तदा पुनः पूर्वं सः आगतः किम्‌ कुल इतर पुरा मात्रा स विषये उ अतएव अपि नगरस्य उपरि यतः प्रतिशतं कतरः कालः साधनानि भूत तथापि जात सम्बन्धि अन्यत्‌ ग अतः अस्माकं स्वकीयाः अस्माकं इदानीं अन्तः इत्यादयः भवन्तः इत्यादयः एते एताः तस्य अस्य इदम् एते तेषां तेषां तेषां तान् तेषां तेषां तेषां समानः सः एकः च तादृशाः बहवः अन्ये च वदन्ति यत् कियत् कस्मै कस्मै यस्मै यस्मै यस्मै यस्मै न अतिनीचः किन्तु प्रथमं सम्पूर्णतया ततः चिरकालानन्तरं पुस्तकं सम्पूर्णतया अन्तः किन्तु अत्र वा इह इव श्रद्धाय अवशिष्यते परन्तु अन्ये वर्गाः सन्ति ते सन्ति शक्नुवन्ति सर्वे मिलित्वा सर्वे एकत्र"'.split(" ")),e.sa.stemmer=function(){return function(e){return"function"==typeof e.update?e.update(function(e){return e}):e}}();var r=e.wordcut;r.init(),e.sa.tokenizer=function(t){if(!arguments.length||null==t||void 0==t)return[];if(Array.isArray(t))return t.map(function(r){return isLunr2?new e.Token(r.toLowerCase()):r.toLowerCase()});var i=t.toString().toLowerCase().replace(/^\s+/,"");return r.cut(i).split("|")},e.Pipeline.registerFunction(e.sa.stemmer,"stemmer-sa"),e.Pipeline.registerFunction(e.sa.stopWordFilter,"stopWordFilter-sa")}});

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!function(r,t){"function"==typeof define&&define.amd?define(t):"object"==typeof exports?module.exports=t():t()(r.lunr)}(this,function(){return function(r){r.stemmerSupport={Among:function(r,t,i,s){if(this.toCharArray=function(r){for(var t=r.length,i=new Array(t),s=0;s<t;s++)i[s]=r.charCodeAt(s);return i},!r&&""!=r||!t&&0!=t||!i)throw"Bad Among initialisation: s:"+r+", substring_i: "+t+", result: "+i;this.s_size=r.length,this.s=this.toCharArray(r),this.substring_i=t,this.result=i,this.method=s},SnowballProgram:function(){var r;return{bra:0,ket:0,limit:0,cursor:0,limit_backward:0,setCurrent:function(t){r=t,this.cursor=0,this.limit=t.length,this.limit_backward=0,this.bra=this.cursor,this.ket=this.limit},getCurrent:function(){var t=r;return r=null,t},in_grouping:function(t,i,s){if(this.cursor<this.limit){var e=r.charCodeAt(this.cursor);if(e<=s&&e>=i&&(e-=i,t[e>>3]&1<<(7&e)))return this.cursor++,!0}return!1},in_grouping_b:function(t,i,s){if(this.cursor>this.limit_backward){var e=r.charCodeAt(this.cursor-1);if(e<=s&&e>=i&&(e-=i,t[e>>3]&1<<(7&e)))return this.cursor--,!0}return!1},out_grouping:function(t,i,s){if(this.cursor<this.limit){var e=r.charCodeAt(this.cursor);if(e>s||e<i)return this.cursor++,!0;if(e-=i,!(t[e>>3]&1<<(7&e)))return this.cursor++,!0}return!1},out_grouping_b:function(t,i,s){if(this.cursor>this.limit_backward){var e=r.charCodeAt(this.cursor-1);if(e>s||e<i)return this.cursor--,!0;if(e-=i,!(t[e>>3]&1<<(7&e)))return this.cursor--,!0}return!1},eq_s:function(t,i){if(this.limit-this.cursor<t)return!1;for(var s=0;s<t;s++)if(r.charCodeAt(this.cursor+s)!=i.charCodeAt(s))return!1;return this.cursor+=t,!0},eq_s_b:function(t,i){if(this.cursor-this.limit_backward<t)return!1;for(var s=0;s<t;s++)if(r.charCodeAt(this.cursor-t+s)!=i.charCodeAt(s))return!1;return this.cursor-=t,!0},find_among:function(t,i){for(var s=0,e=i,n=this.cursor,u=this.limit,o=0,h=0,c=!1;;){for(var a=s+(e-s>>1),f=0,l=o<h?o:h,_=t[a],m=l;m<_.s_size;m++){if(n+l==u){f=-1;break}if(f=r.charCodeAt(n+l)-_.s[m])break;l++}if(f<0?(e=a,h=l):(s=a,o=l),e-s<=1){if(s>0||e==s||c)break;c=!0}}for(;;){var _=t[s];if(o>=_.s_size){if(this.cursor=n+_.s_size,!_.method)return _.result;var b=_.method();if(this.cursor=n+_.s_size,b)return _.result}if((s=_.substring_i)<0)return 0}},find_among_b:function(t,i){for(var s=0,e=i,n=this.cursor,u=this.limit_backward,o=0,h=0,c=!1;;){for(var a=s+(e-s>>1),f=0,l=o<h?o:h,_=t[a],m=_.s_size-1-l;m>=0;m--){if(n-l==u){f=-1;break}if(f=r.charCodeAt(n-1-l)-_.s[m])break;l++}if(f<0?(e=a,h=l):(s=a,o=l),e-s<=1){if(s>0||e==s||c)break;c=!0}}for(;;){var _=t[s];if(o>=_.s_size){if(this.cursor=n-_.s_size,!_.method)return _.result;var b=_.method();if(this.cursor=n-_.s_size,b)return _.result}if((s=_.substring_i)<0)return 0}},replace_s:function(t,i,s){var e=s.length-(i-t),n=r.substring(0,t),u=r.substring(i);return r=n+s+u,this.limit+=e,this.cursor>=i?this.cursor+=e:this.cursor>t&&(this.cursor=t),e},slice_check:function(){if(this.bra<0||this.bra>this.ket||this.ket>this.limit||this.limit>r.length)throw"faulty slice operation"},slice_from:function(r){this.slice_check(),this.replace_s(this.bra,this.ket,r)},slice_del:function(){this.slice_from("")},insert:function(r,t,i){var s=this.replace_s(r,t,i);r<=this.bra&&(this.bra+=s),r<=this.ket&&(this.ket+=s)},slice_to:function(){return this.slice_check(),r.substring(this.bra,this.ket)},eq_v_b:function(r){return this.eq_s_b(r.length,r)}}}},r.trimmerSupport={generateTrimmer:function(r){var t=new RegExp("^[^"+r+"]+"),i=new RegExp("[^"+r+"]+$");return function(r){return"function"==typeof r.update?r.update(function(r){return r.replace(t,"").replace(i,"")}):r.replace(t,"").replace(i,"")}}}}});

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/*!
* Lunr languages, `Swedish` language
* https://github.com/MihaiValentin/lunr-languages
*
* Copyright 2014, Mihai Valentin
* http://www.mozilla.org/MPL/
*/
/*!
* based on
* Snowball JavaScript Library v0.3
* http://code.google.com/p/urim/
* http://snowball.tartarus.org/
*
* Copyright 2010, Oleg Mazko
* http://www.mozilla.org/MPL/
*/
!function(e,r){"function"==typeof define&&define.amd?define(r):"object"==typeof exports?module.exports=r():r()(e.lunr)}(this,function(){return function(e){if(void 0===e)throw new Error("Lunr is not present. Please include / require Lunr before this script.");if(void 0===e.stemmerSupport)throw new Error("Lunr stemmer support is not present. Please include / require Lunr stemmer support before this script.");e.sv=function(){this.pipeline.reset(),this.pipeline.add(e.sv.trimmer,e.sv.stopWordFilter,e.sv.stemmer),this.searchPipeline&&(this.searchPipeline.reset(),this.searchPipeline.add(e.sv.stemmer))},e.sv.wordCharacters="A-Za-zªºÀ-ÖØ-öø-ʸˠ-ˤᴀ-ᴥᴬ-ᵜᵢ-ᵥᵫ-ᵷᵹ-ᶾḀ-ỿⁱⁿₐ-ₜKÅℲⅎⅠ-ↈⱠ-ⱿꜢ-ꞇꞋ-ꞭꞰ-ꞷꟷ-ꟿꬰ-ꭚꭜ-ꭤff-stA--",e.sv.trimmer=e.trimmerSupport.generateTrimmer(e.sv.wordCharacters),e.Pipeline.registerFunction(e.sv.trimmer,"trimmer-sv"),e.sv.stemmer=function(){var r=e.stemmerSupport.Among,n=e.stemmerSupport.SnowballProgram,t=new function(){function e(){var e,r=w.cursor+3;if(o=w.limit,0<=r||r<=w.limit){for(a=r;;){if(e=w.cursor,w.in_grouping(l,97,246)){w.cursor=e;break}if(w.cursor=e,w.cursor>=w.limit)return;w.cursor++}for(;!w.out_grouping(l,97,246);){if(w.cursor>=w.limit)return;w.cursor++}o=w.cursor,o<a&&(o=a)}}function t(){var e,r=w.limit_backward;if(w.cursor>=o&&(w.limit_backward=o,w.cursor=w.limit,w.ket=w.cursor,e=w.find_among_b(u,37),w.limit_backward=r,e))switch(w.bra=w.cursor,e){case 1:w.slice_del();break;case 2:w.in_grouping_b(d,98,121)&&w.slice_del()}}function i(){var e=w.limit_backward;w.cursor>=o&&(w.limit_backward=o,w.cursor=w.limit,w.find_among_b(c,7)&&(w.cursor=w.limit,w.ket=w.cursor,w.cursor>w.limit_backward&&(w.bra=--w.cursor,w.slice_del())),w.limit_backward=e)}function s(){var e,r;if(w.cursor>=o){if(r=w.limit_backward,w.limit_backward=o,w.cursor=w.limit,w.ket=w.cursor,e=w.find_among_b(m,5))switch(w.bra=w.cursor,e){case 1:w.slice_del();break;case 2:w.slice_from("lös");break;case 3:w.slice_from("full")}w.limit_backward=r}}var a,o,u=[new r("a",-1,1),new r("arna",0,1),new r("erna",0,1),new r("heterna",2,1),new r("orna",0,1),new r("ad",-1,1),new r("e",-1,1),new r("ade",6,1),new r("ande",6,1),new r("arne",6,1),new r("are",6,1),new r("aste",6,1),new r("en",-1,1),new r("anden",12,1),new r("aren",12,1),new r("heten",12,1),new r("ern",-1,1),new r("ar",-1,1),new r("er",-1,1),new r("heter",18,1),new r("or",-1,1),new r("s",-1,2),new r("as",21,1),new r("arnas",22,1),new r("ernas",22,1),new r("ornas",22,1),new r("es",21,1),new r("ades",26,1),new r("andes",26,1),new r("ens",21,1),new r("arens",29,1),new r("hetens",29,1),new r("erns",21,1),new r("at",-1,1),new r("andet",-1,1),new r("het",-1,1),new r("ast",-1,1)],c=[new r("dd",-1,-1),new r("gd",-1,-1),new r("nn",-1,-1),new r("dt",-1,-1),new r("gt",-1,-1),new r("kt",-1,-1),new r("tt",-1,-1)],m=[new r("ig",-1,1),new r("lig",0,1),new r("els",-1,1),new r("fullt",-1,3),new r("löst",-1,2)],l=[17,65,16,1,0,0,0,0,0,0,0,0,0,0,0,0,24,0,32],d=[119,127,149],w=new n;this.setCurrent=function(e){w.setCurrent(e)},this.getCurrent=function(){return w.getCurrent()},this.stem=function(){var r=w.cursor;return e(),w.limit_backward=r,w.cursor=w.limit,t(),w.cursor=w.limit,i(),w.cursor=w.limit,s(),!0}};return function(e){return"function"==typeof e.update?e.update(function(e){return t.setCurrent(e),t.stem(),t.getCurrent()}):(t.setCurrent(e),t.stem(),t.getCurrent())}}(),e.Pipeline.registerFunction(e.sv.stemmer,"stemmer-sv"),e.sv.stopWordFilter=e.generateStopWordFilter("alla allt att av blev bli blir blivit de dem den denna deras dess dessa det detta dig din dina ditt du där då efter ej eller en er era ert ett från för ha hade han hans har henne hennes hon honom hur här i icke ingen inom inte jag ju kan kunde man med mellan men mig min mina mitt mot mycket ni nu när någon något några och om oss på samma sedan sig sin sina sitta själv skulle som så sådan sådana sådant till under upp ut utan vad var vara varför varit varje vars vart vem vi vid vilka vilkas vilken vilket vår våra vårt än är åt över".split(" ")),e.Pipeline.registerFunction(e.sv.stopWordFilter,"stopWordFilter-sv")}});

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!function(e,r){"function"==typeof define&&define.amd?define(r):"object"==typeof exports?module.exports=r():r()(e.lunr)}(this,function(){return function(e){if(void 0===e)throw new Error("Lunr is not present. Please include / require Lunr before this script.");if(void 0===e.stemmerSupport)throw new Error("Lunr stemmer support is not present. Please include / require Lunr stemmer support before this script.");e.vi=function(){this.pipeline.reset(),this.pipeline.add(e.vi.stopWordFilter,e.vi.trimmer)},e.vi.wordCharacters="[A-Za-ẓ̀͐́͑̉̃̓ÂâÊêÔôĂ-ăĐ-đƠ-ơƯ-ư]",e.vi.trimmer=e.trimmerSupport.generateTrimmer(e.vi.wordCharacters),e.Pipeline.registerFunction(e.vi.trimmer,"trimmer-vi"),e.vi.stopWordFilter=e.generateStopWordFilter("là cái nhưng mà".split(" "))}});

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/**
* export the module via AMD, CommonJS or as a browser global
* Export code from https://github.com/umdjs/umd/blob/master/returnExports.js
*/
;(function (root, factory) {
if (typeof define === 'function' && define.amd) {
// AMD. Register as an anonymous module.
define(factory)
} else if (typeof exports === 'object') {
/**
* Node. Does not work with strict CommonJS, but
* only CommonJS-like environments that support module.exports,
* like Node.
*/
module.exports = factory()
} else {
// Browser globals (root is window)
factory()(root.lunr);
}
}(this, function () {
/**
* Just return a value to define the module export.
* This example returns an object, but the module
* can return a function as the exported value.
*/
return function(lunr) {
// TinySegmenter 0.1 -- Super compact Japanese tokenizer in Javascript
// (c) 2008 Taku Kudo <taku@chasen.org>
// TinySegmenter is freely distributable under the terms of a new BSD licence.
// For details, see http://chasen.org/~taku/software/TinySegmenter/LICENCE.txt
function TinySegmenter() {
var patterns = {
"[一二三四五六七八九十百千万億兆]":"M",
"[一-龠々〆ヵヶ]":"H",
"[ぁ-ん]":"I",
"[ァ-ヴーア-ン゙ー]":"K",
"[a-zA-Z--]":"A",
"[0-9-]":"N"
}
this.chartype_ = [];
for (var i in patterns) {
var regexp = new RegExp(i);
this.chartype_.push([regexp, patterns[i]]);
}
this.BIAS__ = -332
this.BC1__ = {"HH":6,"II":2461,"KH":406,"OH":-1378};
this.BC2__ = {"AA":-3267,"AI":2744,"AN":-878,"HH":-4070,"HM":-1711,"HN":4012,"HO":3761,"IA":1327,"IH":-1184,"II":-1332,"IK":1721,"IO":5492,"KI":3831,"KK":-8741,"MH":-3132,"MK":3334,"OO":-2920};
this.BC3__ = {"HH":996,"HI":626,"HK":-721,"HN":-1307,"HO":-836,"IH":-301,"KK":2762,"MK":1079,"MM":4034,"OA":-1652,"OH":266};
this.BP1__ = {"BB":295,"OB":304,"OO":-125,"UB":352};
this.BP2__ = {"BO":60,"OO":-1762};
this.BQ1__ = {"BHH":1150,"BHM":1521,"BII":-1158,"BIM":886,"BMH":1208,"BNH":449,"BOH":-91,"BOO":-2597,"OHI":451,"OIH":-296,"OKA":1851,"OKH":-1020,"OKK":904,"OOO":2965};
this.BQ2__ = {"BHH":118,"BHI":-1159,"BHM":466,"BIH":-919,"BKK":-1720,"BKO":864,"OHH":-1139,"OHM":-181,"OIH":153,"UHI":-1146};
this.BQ3__ = {"BHH":-792,"BHI":2664,"BII":-299,"BKI":419,"BMH":937,"BMM":8335,"BNN":998,"BOH":775,"OHH":2174,"OHM":439,"OII":280,"OKH":1798,"OKI":-793,"OKO":-2242,"OMH":-2402,"OOO":11699};
this.BQ4__ = {"BHH":-3895,"BIH":3761,"BII":-4654,"BIK":1348,"BKK":-1806,"BMI":-3385,"BOO":-12396,"OAH":926,"OHH":266,"OHK":-2036,"ONN":-973};
this.BW1__ = {",と":660,",同":727,"B1あ":1404,"B1同":542,"、と":660,"、同":727,"」と":1682,"あっ":1505,"いう":1743,"いっ":-2055,"いる":672,"うし":-4817,"うん":665,"から":3472,"がら":600,"こう":-790,"こと":2083,"こん":-1262,"さら":-4143,"さん":4573,"した":2641,"して":1104,"すで":-3399,"そこ":1977,"それ":-871,"たち":1122,"ため":601,"った":3463,"つい":-802,"てい":805,"てき":1249,"でき":1127,"です":3445,"では":844,"とい":-4915,"とみ":1922,"どこ":3887,"ない":5713,"なっ":3015,"など":7379,"なん":-1113,"にし":2468,"には":1498,"にも":1671,"に対":-912,"の一":-501,"の中":741,"ませ":2448,"まで":1711,"まま":2600,"まる":-2155,"やむ":-1947,"よっ":-2565,"れた":2369,"れで":-913,"をし":1860,"を見":731,"亡く":-1886,"京都":2558,"取り":-2784,"大き":-2604,"大阪":1497,"平方":-2314,"引き":-1336,"日本":-195,"本当":-2423,"毎日":-2113,"目指":-724,"B1あ":1404,"B1同":542,"」と":1682};
this.BW2__ = {"..":-11822,"11":-669,"――":-5730,"":-13175,"いう":-1609,"うか":2490,"かし":-1350,"かも":-602,"から":-7194,"かれ":4612,"がい":853,"がら":-3198,"きた":1941,"くな":-1597,"こと":-8392,"この":-4193,"させ":4533,"され":13168,"さん":-3977,"しい":-1819,"しか":-545,"した":5078,"して":972,"しな":939,"その":-3744,"たい":-1253,"たた":-662,"ただ":-3857,"たち":-786,"たと":1224,"たは":-939,"った":4589,"って":1647,"っと":-2094,"てい":6144,"てき":3640,"てく":2551,"ては":-3110,"ても":-3065,"でい":2666,"でき":-1528,"でし":-3828,"です":-4761,"でも":-4203,"とい":1890,"とこ":-1746,"とと":-2279,"との":720,"とみ":5168,"とも":-3941,"ない":-2488,"なが":-1313,"など":-6509,"なの":2614,"なん":3099,"にお":-1615,"にし":2748,"にな":2454,"によ":-7236,"に対":-14943,"に従":-4688,"に関":-11388,"のか":2093,"ので":-7059,"のに":-6041,"のの":-6125,"はい":1073,"はが":-1033,"はず":-2532,"ばれ":1813,"まし":-1316,"まで":-6621,"まれ":5409,"めて":-3153,"もい":2230,"もの":-10713,"らか":-944,"らし":-1611,"らに":-1897,"りし":651,"りま":1620,"れた":4270,"れて":849,"れば":4114,"ろう":6067,"われ":7901,"を通":-11877,"んだ":728,"んな":-4115,"一人":602,"一方":-1375,"一日":970,"一部":-1051,"上が":-4479,"会社":-1116,"出て":2163,"分の":-7758,"同党":970,"同日":-913,"大阪":-2471,"委員":-1250,"少な":-1050,"年度":-8669,"年間":-1626,"府県":-2363,"手権":-1982,"新聞":-4066,"日新":-722,"日本":-7068,"日米":3372,"曜日":-601,"朝鮮":-2355,"本人":-2697,"東京":-1543,"然と":-1384,"社会":-1276,"立て":-990,"第に":-1612,"米国":-4268,"":-669};
this.BW3__ = {"あた":-2194,"あり":719,"ある":3846,"い.":-1185,"い。":-1185,"いい":5308,"いえ":2079,"いく":3029,"いた":2056,"いっ":1883,"いる":5600,"いわ":1527,"うち":1117,"うと":4798,"えと":1454,"か.":2857,"か。":2857,"かけ":-743,"かっ":-4098,"かに":-669,"から":6520,"かり":-2670,"が,":1816,"が、":1816,"がき":-4855,"がけ":-1127,"がっ":-913,"がら":-4977,"がり":-2064,"きた":1645,"けど":1374,"こと":7397,"この":1542,"ころ":-2757,"さい":-714,"さを":976,"し,":1557,"し、":1557,"しい":-3714,"した":3562,"して":1449,"しな":2608,"しま":1200,"す.":-1310,"す。":-1310,"する":6521,"ず,":3426,"ず、":3426,"ずに":841,"そう":428,"た.":8875,"た。":8875,"たい":-594,"たの":812,"たり":-1183,"たる":-853,"だ.":4098,"だ。":4098,"だっ":1004,"った":-4748,"って":300,"てい":6240,"てお":855,"ても":302,"です":1437,"でに":-1482,"では":2295,"とう":-1387,"とし":2266,"との":541,"とも":-3543,"どう":4664,"ない":1796,"なく":-903,"など":2135,"に,":-1021,"に、":-1021,"にし":1771,"にな":1906,"には":2644,"の,":-724,"の、":-724,"の子":-1000,"は,":1337,"は、":1337,"べき":2181,"まし":1113,"ます":6943,"まっ":-1549,"まで":6154,"まれ":-793,"らし":1479,"られ":6820,"るる":3818,"れ,":854,"れ、":854,"れた":1850,"れて":1375,"れば":-3246,"れる":1091,"われ":-605,"んだ":606,"んで":798,"カ月":990,"会議":860,"入り":1232,"大会":2217,"始め":1681,"市":965,"新聞":-5055,"日,":974,"日、":974,"社会":2024,"カ月":990};
this.TC1__ = {"AAA":1093,"HHH":1029,"HHM":580,"HII":998,"HOH":-390,"HOM":-331,"IHI":1169,"IOH":-142,"IOI":-1015,"IOM":467,"MMH":187,"OOI":-1832};
this.TC2__ = {"HHO":2088,"HII":-1023,"HMM":-1154,"IHI":-1965,"KKH":703,"OII":-2649};
this.TC3__ = {"AAA":-294,"HHH":346,"HHI":-341,"HII":-1088,"HIK":731,"HOH":-1486,"IHH":128,"IHI":-3041,"IHO":-1935,"IIH":-825,"IIM":-1035,"IOI":-542,"KHH":-1216,"KKA":491,"KKH":-1217,"KOK":-1009,"MHH":-2694,"MHM":-457,"MHO":123,"MMH":-471,"NNH":-1689,"NNO":662,"OHO":-3393};
this.TC4__ = {"HHH":-203,"HHI":1344,"HHK":365,"HHM":-122,"HHN":182,"HHO":669,"HIH":804,"HII":679,"HOH":446,"IHH":695,"IHO":-2324,"IIH":321,"III":1497,"IIO":656,"IOO":54,"KAK":4845,"KKA":3386,"KKK":3065,"MHH":-405,"MHI":201,"MMH":-241,"MMM":661,"MOM":841};
this.TQ1__ = {"BHHH":-227,"BHHI":316,"BHIH":-132,"BIHH":60,"BIII":1595,"BNHH":-744,"BOHH":225,"BOOO":-908,"OAKK":482,"OHHH":281,"OHIH":249,"OIHI":200,"OIIH":-68};
this.TQ2__ = {"BIHH":-1401,"BIII":-1033,"BKAK":-543,"BOOO":-5591};
this.TQ3__ = {"BHHH":478,"BHHM":-1073,"BHIH":222,"BHII":-504,"BIIH":-116,"BIII":-105,"BMHI":-863,"BMHM":-464,"BOMH":620,"OHHH":346,"OHHI":1729,"OHII":997,"OHMH":481,"OIHH":623,"OIIH":1344,"OKAK":2792,"OKHH":587,"OKKA":679,"OOHH":110,"OOII":-685};
this.TQ4__ = {"BHHH":-721,"BHHM":-3604,"BHII":-966,"BIIH":-607,"BIII":-2181,"OAAA":-2763,"OAKK":180,"OHHH":-294,"OHHI":2446,"OHHO":480,"OHIH":-1573,"OIHH":1935,"OIHI":-493,"OIIH":626,"OIII":-4007,"OKAK":-8156};
this.TW1__ = {"につい":-4681,"東京都":2026};
this.TW2__ = {"ある程":-2049,"いった":-1256,"ころが":-2434,"しょう":3873,"その後":-4430,"だって":-1049,"ていた":1833,"として":-4657,"ともに":-4517,"もので":1882,"一気に":-792,"初めて":-1512,"同時に":-8097,"大きな":-1255,"対して":-2721,"社会党":-3216};
this.TW3__ = {"いただ":-1734,"してい":1314,"として":-4314,"につい":-5483,"にとっ":-5989,"に当た":-6247,"ので,":-727,"ので、":-727,"のもの":-600,"れから":-3752,"十二月":-2287};
this.TW4__ = {"いう.":8576,"いう。":8576,"からな":-2348,"してい":2958,"たが,":1516,"たが、":1516,"ている":1538,"という":1349,"ました":5543,"ません":1097,"ようと":-4258,"よると":5865};
this.UC1__ = {"A":484,"K":93,"M":645,"O":-505};
this.UC2__ = {"A":819,"H":1059,"I":409,"M":3987,"N":5775,"O":646};
this.UC3__ = {"A":-1370,"I":2311};
this.UC4__ = {"A":-2643,"H":1809,"I":-1032,"K":-3450,"M":3565,"N":3876,"O":6646};
this.UC5__ = {"H":313,"I":-1238,"K":-799,"M":539,"O":-831};
this.UC6__ = {"H":-506,"I":-253,"K":87,"M":247,"O":-387};
this.UP1__ = {"O":-214};
this.UP2__ = {"B":69,"O":935};
this.UP3__ = {"B":189};
this.UQ1__ = {"BH":21,"BI":-12,"BK":-99,"BN":142,"BO":-56,"OH":-95,"OI":477,"OK":410,"OO":-2422};
this.UQ2__ = {"BH":216,"BI":113,"OK":1759};
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this.UW6__ = {",":227,".":808,"1":-270,"E1":306,"、":227,"。":808,"あ":-307,"う":189,"か":241,"が":-73,"く":-121,"こ":-200,"じ":1782,"す":383,"た":-428,"っ":573,"て":-1014,"で":101,"と":-105,"な":-253,"に":-149,"の":-417,"は":-236,"も":-206,"り":187,"る":-135,"を":195,"ル":-673,"ン":-496,"一":-277,"中":201,"件":-800,"会":624,"前":302,"区":1792,"員":-1212,"委":798,"学":-960,"市":887,"広":-695,"後":535,"業":-697,"相":753,"社":-507,"福":974,"空":-822,"者":1811,"連":463,"郎":1082,"":-270,"":306,"ル":-673,"ン":-496};
return this;
}
TinySegmenter.prototype.ctype_ = function(str) {
for (var i in this.chartype_) {
if (str.match(this.chartype_[i][0])) {
return this.chartype_[i][1];
}
}
return "O";
}
TinySegmenter.prototype.ts_ = function(v) {
if (v) { return v; }
return 0;
}
TinySegmenter.prototype.segment = function(input) {
if (input == null || input == undefined || input == "") {
return [];
}
var result = [];
var seg = ["B3","B2","B1"];
var ctype = ["O","O","O"];
var o = input.split("");
for (i = 0; i < o.length; ++i) {
seg.push(o[i]);
ctype.push(this.ctype_(o[i]))
}
seg.push("E1");
seg.push("E2");
seg.push("E3");
ctype.push("O");
ctype.push("O");
ctype.push("O");
var word = seg[3];
var p1 = "U";
var p2 = "U";
var p3 = "U";
for (var i = 4; i < seg.length - 3; ++i) {
var score = this.BIAS__;
var w1 = seg[i-3];
var w2 = seg[i-2];
var w3 = seg[i-1];
var w4 = seg[i];
var w5 = seg[i+1];
var w6 = seg[i+2];
var c1 = ctype[i-3];
var c2 = ctype[i-2];
var c3 = ctype[i-1];
var c4 = ctype[i];
var c5 = ctype[i+1];
var c6 = ctype[i+2];
score += this.ts_(this.UP1__[p1]);
score += this.ts_(this.UP2__[p2]);
score += this.ts_(this.UP3__[p3]);
score += this.ts_(this.BP1__[p1 + p2]);
score += this.ts_(this.BP2__[p2 + p3]);
score += this.ts_(this.UW1__[w1]);
score += this.ts_(this.UW2__[w2]);
score += this.ts_(this.UW3__[w3]);
score += this.ts_(this.UW4__[w4]);
score += this.ts_(this.UW5__[w5]);
score += this.ts_(this.UW6__[w6]);
score += this.ts_(this.BW1__[w2 + w3]);
score += this.ts_(this.BW2__[w3 + w4]);
score += this.ts_(this.BW3__[w4 + w5]);
score += this.ts_(this.TW1__[w1 + w2 + w3]);
score += this.ts_(this.TW2__[w2 + w3 + w4]);
score += this.ts_(this.TW3__[w3 + w4 + w5]);
score += this.ts_(this.TW4__[w4 + w5 + w6]);
score += this.ts_(this.UC1__[c1]);
score += this.ts_(this.UC2__[c2]);
score += this.ts_(this.UC3__[c3]);
score += this.ts_(this.UC4__[c4]);
score += this.ts_(this.UC5__[c5]);
score += this.ts_(this.UC6__[c6]);
score += this.ts_(this.BC1__[c2 + c3]);
score += this.ts_(this.BC2__[c3 + c4]);
score += this.ts_(this.BC3__[c4 + c5]);
score += this.ts_(this.TC1__[c1 + c2 + c3]);
score += this.ts_(this.TC2__[c2 + c3 + c4]);
score += this.ts_(this.TC3__[c3 + c4 + c5]);
score += this.ts_(this.TC4__[c4 + c5 + c6]);
// score += this.ts_(this.TC5__[c4 + c5 + c6]);
score += this.ts_(this.UQ1__[p1 + c1]);
score += this.ts_(this.UQ2__[p2 + c2]);
score += this.ts_(this.UQ3__[p3 + c3]);
score += this.ts_(this.BQ1__[p2 + c2 + c3]);
score += this.ts_(this.BQ2__[p2 + c3 + c4]);
score += this.ts_(this.BQ3__[p3 + c2 + c3]);
score += this.ts_(this.BQ4__[p3 + c3 + c4]);
score += this.ts_(this.TQ1__[p2 + c1 + c2 + c3]);
score += this.ts_(this.TQ2__[p2 + c2 + c3 + c4]);
score += this.ts_(this.TQ3__[p3 + c1 + c2 + c3]);
score += this.ts_(this.TQ4__[p3 + c2 + c3 + c4]);
var p = "O";
if (score > 0) {
result.push(word);
word = "";
p = "B";
}
p1 = p2;
p2 = p3;
p3 = p;
word += seg[i];
}
result.push(word);
return result;
}
lunr.TinySegmenter = TinySegmenter;
};
}));

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<!doctype html>
<html lang="en" class="no-js">
<head>
<meta charset="utf-8">
<meta name="viewport" content="width=device-width,initial-scale=1">
<meta name="description" content="Documentation for the Nokken medical tracking application">
<meta name="author" content="Charlotte Croce">
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<h1 id="core-services">Core Services<a class="headerlink" href="#core-services" title="Permanent link">&para;</a></h1>
<p>Nokken's architecture is built around several core services that provide foundational functionality to the application. These services follow a singleton pattern for efficient resource usage and are designed with clear separation of concerns.</p>
<h2 id="structure">Structure<a class="headerlink" href="#structure" title="Permanent link">&para;</a></h2>
<div class="language-text highlight"><pre><span></span><code>lib/src/
├── app.dart # App configuration and theme setup
├── core/ # Core functionality shared across features
│ ├── constants/ # App-wide constants
│ ├── screens/ # Core screens (main container)
│ ├── services/ # Shared services
│ ├── theme/ # Theming system
│ └── utils/ # Utility functions
├── features/ # Feature modules (medication, bloodwork, etc.)
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<h1 id="feature-modules">Feature Modules<a class="headerlink" href="#feature-modules" title="Permanent link">&para;</a></h1>
<p>Nokken features multiple modules for tracking different aspects of health management. The application follows a feature-first architecture with clear separation of concerns.</p>
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<li><a href="medication-tracker/">Medication Tracker</a>: Track medications, schedules, and adherence</li>
<li><a href="bloodwork-tracker/">Bloodwork Tracker</a>: Manage lab results, medical appointments, and visualize hormone data</li>
<li><a href="mood-tracker/">Mood Tracker</a>: Track daily mood and wellness metrics</li>
<li><a href="scheduler/">Scheduler</a>: Integrated calendar and daily tracker for all medical events</li>
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<li><a href="settings/">Settings</a>: Application preferences and configuration</li>
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<div class="language-bash highlight"><pre><span></span><code><span class="c1"># Clone the repository</span>
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<h1>Overview</h1>
<p>Nøkken (or Nokken) is a medical tracking application built with Flutter. It is designed to work on mobile platforms (iOS / Android) with a strong focus on user privacy.</p>
<h2 id="open-source-transparency">Open Source Transparency<a class="headerlink" href="#open-source-transparency" title="Permanent link">&para;</a></h2>
<p>Nøkken is fully open source, providing transparency into how your sensitive health data is handled. This approach ensures:</p>
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<li>Full visibility into all application code</li>
<li>Community verification of privacy and security practices</li>
<li>The ability to modify, extend, or replace components as needed</li>
<li>Long-term sustainability independent of any single developer or organization</li>
</ul>
<h2 id="uncompromising-privacy">Uncompromising Privacy<a class="headerlink" href="#uncompromising-privacy" title="Permanent link">&para;</a></h2>
<p>Nøkken embraces a strict privacy-first approach:</p>
<ul>
<li>No data collection: Your health information never leaves your device</li>
<li>No cloud storage: All data is stored locally on your device</li>
<li>No tracking: No analytics, telemetry, or usage statistics are collected</li>
<li>No network requirements: Functions fully offline with no dependency on external services</li>
<li>No account creation or registration required</li>
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