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<h1 id="statistics">Statistics<a class="headerlink" href="#statistics" title="Permanent link">¶</a></h1>
|
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<p>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 <code>HealthAnalyticsService</code> to generate insights, identify patterns, detect correlations, and predict trends.</p>
|
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<h2 id="architecture">Architecture<a class="headerlink" href="#architecture" title="Permanent link">¶</a></h2>
|
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<div class="language-text highlight"><pre><span></span><code>lib/src/features/stats/
|
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├── charts/ # Chart widgets for data visualization
|
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├── models/ # Data models for statistical analysis
|
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├── providers/ # Riverpod providers for state management
|
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├── screens/ # UI screens for displaying analytics
|
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├── tabs/ # Tab components for the main stats screen
|
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├── utils/ # Utility functions for analysis and formatting
|
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└── widgets/ # Reusable UI components
|
|
</code></pre></div>
|
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<h2 id="components">Components<a class="headerlink" href="#components" title="Permanent link">¶</a></h2>
|
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<h3 id="models">Models<a class="headerlink" href="#models" title="Permanent link">¶</a></h3>
|
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<p>The analytics feature uses a large set of models to represent different types of statistical insights:</p>
|
|
<ul>
|
|
<li><code>ComprehensiveAnalysis</code>: Container for all types of analytics data</li>
|
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<li><code>StatisticalInsight</code>: Basic statistical findings</li>
|
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<li><code>FactorRelationship</code>: Relationships between different health factors</li>
|
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<li><code>HealthPattern</code>: Detected patterns in health data</li>
|
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<li><code>HealthPrediction</code>: Forecasts of future health metrics</li>
|
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<li><code>HealthAnomaly</code>: Unusual data points</li>
|
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<li><code>FactorImpactRanking</code>: Impacts of factors on a target variable</li>
|
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<li><code>WeekdayAnalysis</code>: Metrics across days of the week</li>
|
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<li><code>HealthStreak</code>: Consistent periods for health metrics</li>
|
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<li><code>HormoneAnalysis</code>: Hormone level analysis</li>
|
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<li><code>MedicationImpact</code>: Effects of medications on health metrics</li>
|
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</ul>
|
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<h3 id="providers">Providers<a class="headerlink" href="#providers" title="Permanent link">¶</a></h3>
|
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<div class="language-dart highlight"><pre><span></span><code><span class="c1">// Basic statistical insights</span>
|
|
<span class="kd">final</span><span class="w"> </span><span class="n">statisticsInsightsProvider</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">FutureProvider</span><span class="p">.</span><span class="n">autoDispose</span>
|
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<span class="w"> </span><span class="p">.</span><span class="n">family</span><span class="o"><</span><span class="n">List</span><span class="o"><</span><span class="n">StatisticalInsight</span><span class="o">></span><span class="p">,</span><span class="w"> </span><span class="kt">String</span><span class="o">></span><span class="p">((</span><span class="n">ref</span><span class="p">,</span><span class="w"> </span><span class="n">timeframe</span><span class="p">)</span><span class="w"> </span><span class="kd">async</span><span class="w"> </span><span class="p">{</span><span class="w"> </span><span class="p">...</span><span class="w"> </span><span class="p">});</span>
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<span class="c1">// Comprehensive analysis (More detailed/resource extensive)</span>
|
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<span class="kd">final</span><span class="w"> </span><span class="n">comprehensiveAnalysisProvider</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">FutureProvider</span><span class="p">.</span><span class="n">autoDispose</span>
|
|
<span class="w"> </span><span class="p">.</span><span class="n">family</span><span class="o"><</span><span class="n">ComprehensiveAnalysis</span><span class="p">,</span><span class="w"> </span><span class="kt">String</span><span class="o">></span><span class="p">((</span><span class="n">ref</span><span class="p">,</span><span class="w"> </span><span class="n">timeframe</span><span class="p">)</span><span class="w"> </span><span class="kd">async</span><span class="w"> </span><span class="p">{</span><span class="w"> </span><span class="p">...</span><span class="w"> </span><span class="p">});</span>
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|
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<span class="c1">// Factor-specific analysis</span>
|
|
<span class="kd">final</span><span class="w"> </span><span class="n">factorAnalysisProvider</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">FutureProvider</span><span class="p">.</span><span class="n">autoDispose</span>
|
|
<span class="w"> </span><span class="p">.</span><span class="n">family</span><span class="o"><</span><span class="n">Map</span><span class="o"><</span><span class="kt">String</span><span class="p">,</span><span class="w"> </span><span class="kt">dynamic</span><span class="o">></span><span class="p">,</span><span class="w"> </span><span class="n">FactorAnalysisParams</span><span class="o">></span><span class="p">((</span><span class="n">ref</span><span class="p">,</span><span class="w"> </span><span class="n">params</span><span class="p">)</span><span class="w"> </span><span class="kd">async</span><span class="w"> </span><span class="p">{</span><span class="w"> </span><span class="p">...</span><span class="w"> </span><span class="p">});</span>
|
|
</code></pre></div>
|
|
<h3 id="services">Services<a class="headerlink" href="#services" title="Permanent link">¶</a></h3>
|
|
<p>The analytics functionality relies on the <code>HealthAnalyticsService</code></p>
|
|
<h3 id="charts">Charts<a class="headerlink" href="#charts" title="Permanent link">¶</a></h3>
|
|
<ul>
|
|
<li><code>CorrelationsChart</code>: Displays relationships between factors</li>
|
|
<li><code>ImpactChart</code>: Shows impact ranking of factors</li>
|
|
<li><code>WeekdayChart</code>: Visualizes metrics by day of week</li>
|
|
<li>And other specialized charts</li>
|
|
</ul>
|
|
<h2 id="ui-organization">UI Organization<a class="headerlink" href="#ui-organization" title="Permanent link">¶</a></h2>
|
|
<p>The main Stats screen is organized into tabs:
|
|
- <code>Overview</code>: Summary of health insights and key metrics
|
|
- <code>Correlations</code>: Relationships between different health factors
|
|
- <code>Patterns</code>: Detected trends and cyclical patterns
|
|
- <code>Factors</code>: Analysis of what factors affect health metrics
|
|
- <code>Predictions</code>: Forecasts of future health values</p>
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<h2 id="factor-analysis">Factor Analysis<a class="headerlink" href="#factor-analysis" title="Permanent link">¶</a></h2>
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<p>The feature supports detailed analysis of specific factors with the <code>FactorAnalysisScreen</code>, which provides:</p>
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<ul>
|
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<li>Basic statistics (mean, median, min, max)</li>
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<li>Related factors and correlations</li>
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<li>Detected patterns</li>
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<li>Historical timeline</li>
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<li>Health impacts</li>
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</ul>
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<h2 id="data-sources">Data Sources<a class="headerlink" href="#data-sources" title="Permanent link">¶</a></h2>
|
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<p>The Health Analytics feature consumes data from multiple sources:
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|
- <strong>Mood Tracker</strong>: Emotional state, energy levels, sleep quality, etc.
|
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- <strong>Medication Tracker</strong>: Medication adherence and effects
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- <strong>Bloodwork Tracker</strong>: Lab results and hormone levels</p>
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<h2 id="usage-examples">Usage Examples<a class="headerlink" href="#usage-examples" title="Permanent link">¶</a></h2>
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<p>To access the comprehensive analysis:
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<div class="language-dart highlight"><pre><span></span><code><span class="c1">// Watch for analysis data with a specific timeframe</span>
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<span class="kd">final</span><span class="w"> </span><span class="n">analysisAsync</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">ref</span><span class="p">.</span><span class="n">watch</span><span class="p">(</span><span class="n">comprehensiveAnalysisProvider</span><span class="p">(</span><span class="s1">'Last Month'</span><span class="p">));</span>
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<span class="c1">// Use the data when available</span>
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<span class="n">analysisAsync</span><span class="p">.</span><span class="n">when</span><span class="p">(</span>
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<span class="w"> </span><span class="nl">data:</span><span class="w"> </span><span class="p">(</span><span class="n">analysis</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
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<span class="w"> </span><span class="c1">// Access insights, relationships, patterns, etc.</span>
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|
<span class="w"> </span><span class="kd">final</span><span class="w"> </span><span class="n">relationships</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">analysis</span><span class="p">.</span><span class="n">relationships</span><span class="p">;</span>
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<span class="w"> </span><span class="kd">final</span><span class="w"> </span><span class="n">patterns</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">analysis</span><span class="p">.</span><span class="n">patterns</span><span class="p">;</span>
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<span class="w"> </span><span class="kd">final</span><span class="w"> </span><span class="n">predictions</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">analysis</span><span class="p">.</span><span class="n">predictions</span><span class="p">;</span>
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<span class="w"> </span><span class="c1">// Build UI with the data</span>
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|
<span class="w"> </span><span class="k">return</span><span class="w"> </span><span class="n">ListView</span><span class="p">(</span>
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<span class="w"> </span><span class="nl">children:</span><span class="w"> </span><span class="p">[</span>
|
|
<span class="w"> </span><span class="c1">// Display insights</span>
|
|
<span class="w"> </span><span class="p">],</span>
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<span class="w"> </span><span class="p">);</span>
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<span class="w"> </span><span class="p">},</span>
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<span class="w"> </span><span class="nl">loading:</span><span class="w"> </span><span class="p">()</span><span class="w"> </span><span class="o">=></span><span class="w"> </span><span class="k">const</span><span class="w"> </span><span class="n">LoadingView</span><span class="p">(),</span>
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<span class="w"> </span><span class="nl">error:</span><span class="w"> </span><span class="p">(</span><span class="n">error</span><span class="p">,</span><span class="w"> </span><span class="n">stack</span><span class="p">)</span><span class="w"> </span><span class="o">=></span><span class="w"> </span><span class="n">ErrorView</span><span class="p">(</span><span class="nl">error:</span><span class="w"> </span><span class="n">error</span><span class="p">),</span>
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<span class="p">);</span>
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|
</code></pre></div></p>
|
|
<p>To analyze a specific factor:
|
|
<div class="language-dart highlight"><pre><span></span><code><span class="c1">// Watch for factor-specific analysis</span>
|
|
<span class="kd">final</span><span class="w"> </span><span class="n">factorAsync</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">ref</span><span class="p">.</span><span class="n">watch</span><span class="p">(</span>
|
|
<span class="w"> </span><span class="n">factorAnalysisProvider</span><span class="p">(</span>
|
|
<span class="w"> </span><span class="n">FactorAnalysisParams</span><span class="p">(</span>
|
|
<span class="w"> </span><span class="nl">factorName:</span><span class="w"> </span><span class="s1">'Mood'</span><span class="p">,</span>
|
|
<span class="w"> </span><span class="nl">timeframe:</span><span class="w"> </span><span class="s1">'All Time'</span><span class="p">,</span>
|
|
<span class="w"> </span><span class="p">),</span>
|
|
<span class="w"> </span><span class="p">),</span>
|
|
<span class="p">);</span>
|
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|
|
<span class="c1">// Use the data when available</span>
|
|
<span class="n">factorAsync</span><span class="p">.</span><span class="n">when</span><span class="p">(</span>
|
|
<span class="w"> </span><span class="nl">data:</span><span class="w"> </span><span class="p">(</span><span class="n">factorAnalysis</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
|
|
<span class="w"> </span><span class="c1">// Access factor-specific data</span>
|
|
<span class="w"> </span><span class="kd">final</span><span class="w"> </span><span class="n">relationships</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">factorAnalysis</span><span class="p">[</span><span class="s1">'relationships'</span><span class="p">];</span>
|
|
<span class="w"> </span><span class="kd">final</span><span class="w"> </span><span class="n">patterns</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">factorAnalysis</span><span class="p">[</span><span class="s1">'patterns'</span><span class="p">];</span>
|
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|
|
<span class="w"> </span><span class="c1">// Build UI with the data</span>
|
|
<span class="w"> </span><span class="p">},</span>
|
|
<span class="w"> </span><span class="nl">loading:</span><span class="w"> </span><span class="p">()</span><span class="w"> </span><span class="o">=></span><span class="w"> </span><span class="k">const</span><span class="w"> </span><span class="n">LoadingView</span><span class="p">(),</span>
|
|
<span class="w"> </span><span class="nl">error:</span><span class="w"> </span><span class="p">(</span><span class="n">error</span><span class="p">,</span><span class="w"> </span><span class="n">stack</span><span class="p">)</span><span class="w"> </span><span class="o">=></span><span class="w"> </span><span class="n">ErrorView</span><span class="p">(</span><span class="nl">error:</span><span class="w"> </span><span class="n">error</span><span class="p">),</span>
|
|
<span class="p">);</span>
|
|
</code></pre></div></p>
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<h2 id="implementation-details">Implementation Details<a class="headerlink" href="#implementation-details" title="Permanent link">¶</a></h2>
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<h3 id="correlation-analysis">Correlation Analysis<a class="headerlink" href="#correlation-analysis" title="Permanent link">¶</a></h3>
|
|
<p>The service calculates Pearson correlation coefficients between different health factors to identify relationships. For example, it can detect correlations between:</p>
|
|
<ul>
|
|
<li>Sleep quality and mood</li>
|
|
<li>Energy levels and exercise</li>
|
|
<li>Hormone levels and emotions</li>
|
|
</ul>
|
|
<h3 id="pattern-detection">Pattern Detection<a class="headerlink" href="#pattern-detection" title="Permanent link">¶</a></h3>
|
|
<p>Patterns are identified through statistical analysis of time series data, including:</p>
|
|
<ul>
|
|
<li><strong>Trends</strong>: Directional changes over time</li>
|
|
<li><strong>Cyclical Patterns</strong>: Repeating patterns (e.g., weekly sleep cycles)</li>
|
|
<li><strong>Clusters</strong>: Groupings of related factors</li>
|
|
<li><strong>Thresholds</strong>: Significant crossover points</li>
|
|
</ul>
|
|
<h3 id="anomaly-detection">Anomaly Detection<a class="headerlink" href="#anomaly-detection" title="Permanent link">¶</a></h3>
|
|
<p>The service identifies unusual data points using z-score analysis, which detects values that deviate significantly from normal patterns.</p>
|
|
<h3 id="prediction-algorithm">Prediction Algorithm<a class="headerlink" href="#prediction-algorithm" title="Permanent link">¶</a></h3>
|
|
<p>Predictions are generated using a combination of:</p>
|
|
<ul>
|
|
<li>Linear trend extrapolation</li>
|
|
<li>Moving averages</li>
|
|
<li>Pattern-based forecasting</li>
|
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</ul>
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