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‎_posts/creative_writing/2025-12-04-comicbookgeneration-20251204162502.md‎

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@@ -79,6 +79,32 @@ is_gateway: true
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is_synthesis: true
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---
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![Page 1 Row 1](../../assets/images/dates/page_1_row_1.png)
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![Page 1 Row 2](../../assets/images/dates/page_1_row_2.png)
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![Page 1 Row 3](../../assets/images/dates/page_1_row_3.png)
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![Page 2 Row 1](../../assets/images/dates/page_2_row_1.png)
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![Page 2 Row 2](../../assets/images/dates/page_2_row_2.png)
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![Page 2 Row 3](../../assets/images/dates/page_2_row_3.png)
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![Page 3 Row 1](../../assets/images/dates/page_3_row_1.png)
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![Page 3 Row 2](../../assets/images/dates/page_3_row_2.png)
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![Page 3 Row 3](../../assets/images/dates/page_3_row_3.png)
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![Page 4 Row 1](../../assets/images/dates/page_4_row_1.png)
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![Page 4 Row 2](../../assets/images/dates/page_4_row_2.png)
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![Page 4 Row 3](../../assets/images/dates/page_4_row_3.png)
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![Page 4 Row 4](../../assets/images/dates/page_4_row_4.png)
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# Comic Book Generation Task
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@@ -188,30 +214,3 @@ is_synthesis: true
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![CHLOE](../../assets/images/dates/char_CHLOE.png)
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*The Date. Curated casual personality who speaks exclusively in therapy-speak and TikTok trends.*
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![Page 1 Row 1](../../assets/images/dates/page_1_row_1.png)
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![Page 1 Row 2](../../assets/images/dates/page_1_row_2.png)
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![Page 1 Row 3](../../assets/images/dates/page_1_row_3.png)
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![Page 2 Row 1](../../assets/images/dates/page_2_row_1.png)
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![Page 2 Row 2](../../assets/images/dates/page_2_row_2.png)
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![Page 2 Row 3](../../assets/images/dates/page_2_row_3.png)
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![Page 3 Row 1](../../assets/images/dates/page_3_row_1.png)
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![Page 3 Row 2](../../assets/images/dates/page_3_row_2.png)
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![Page 3 Row 3](../../assets/images/dates/page_3_row_3.png)
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![Page 4 Row 1](../../assets/images/dates/page_4_row_1.png)
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![Page 4 Row 2](../../assets/images/dates/page_4_row_2.png)
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![Page 4 Row 3](../../assets/images/dates/page_4_row_3.png)
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![Page 4 Row 4](../../assets/images/dates/page_4_row_4.png)
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‎assets/2025-06-30-knots-lab.html‎

Lines changed: 42 additions & 9 deletions
Original file line numberDiff line numberDiff line change
@@ -519,6 +519,14 @@ <h1>
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<div class="panel-header">Optimization</div>
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<div class="control-group">
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<label>Optimizer</label>
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<select id="opt-optimizer">
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<option value="adam">Adam</option>
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<option value="qqn">QQN</option>
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<option value="lbfgs">L-BFGS</option>
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</select>
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</div>
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<div class="control-group">
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<label>Learning Rate <input type="number" class="value-input" id="val-lr" value="0.01" step="0.001"></label>
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<input type="range" id="param-lr" min="0.001" max="0.1" step="0.001" value="0.01">
@@ -616,7 +624,11 @@ <h1>
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</div>
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</main>
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<script>
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<script type="module">
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import {OptimizerLbfgs} from './js/optimizer-lbfgs.js';
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import {OptimizerAdam} from './js/optimizer-adam.js';
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import {OptimizerQQN} from './js/optimizer-qqn.js';
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/**
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* Knot Topology Lab
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*
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lr: 0.01,
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c: 1.0,
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knotType: 'random',
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metricMode: 'euclidean'
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metricMode: 'euclidean',
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optimizerType: 'adam'
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},
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metrics: {
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totalLoss: 0,
@@ -669,6 +682,7 @@ <h1>
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matrixCanvas: document.getElementById('matrix-canvas'),
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loading: document.getElementById('loading'),
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knotSelect: document.getElementById('knot-select'),
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optimizerSelect: document.getElementById('opt-optimizer'),
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metricSelect: document.getElementById('metric-select'),
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grpC: document.getElementById('grp-c'),
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cInput: document.getElementById('param-c'),
@@ -713,6 +727,15 @@ <h1>
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const knotCtx = els.knotCanvas.getContext('2d');
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const matrixCtx = els.matrixCanvas.getContext('2d');
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function createOptimizer() {
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if (state.params.optimizerType === 'adam') {
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return new OptimizerAdam(state.params.lr);
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} else if (state.params.optimizerType === 'qqn') {
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return new OptimizerQQN(state.params.lr);
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}
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return new OptimizerLbfgs(state.params.lr);
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}
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// --- Spline Generation ---
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state.points.dispose();
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state.points = tf.variable(tf.tensor2d(newPoints));
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// Reset optimizer to clear history
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state.optimizer = tf.train.adam(state.params.lr);
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state.optimizer = createOptimizer();
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updateDistanceMatrix();
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}
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/**
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state.points = tf.variable(tf.tensor2d(pointsArray));
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// Reset optimizer
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state.optimizer = tf.train.adam(state.params.lr);
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state.optimizer = createOptimizer();
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state.step = 0;
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}
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if (!state.points) return;
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const lossInfo = tf.tidy(() => {
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const {value, grads} = tf.variableGrads(() => {
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const lossFunction = () => {
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const edgeLoss = computeEdgeLoss(
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state.points,
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state.params.targetEdgeLength,
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state.params.repulsionCutoff
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);
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return tf.add(edgeLoss, repulsionLoss);
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});
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};
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state.optimizer.applyGradients(grads);
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const {value, grads} = state.optimizer.computeGradients(lossFunction);
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state.optimizer.applyGradients(grads, lossFunction);
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// Compute individual losses for display
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const edgeLoss = computeEdgeLoss(
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updateDistanceMatrix();
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}
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});
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els.optimizerSelect.addEventListener('change', (e) => {
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state.params.optimizerType = e.target.value;
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state.optimizer = createOptimizer();
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});
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els.lrInput.addEventListener('input', () => {
1727-
state.optimizer = tf.train.adam(state.params.lr);
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if (state.optimizer && typeof state.optimizer.setLearningRate === 'function') {
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state.optimizer.setLearningRate(state.params.lr);
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} else {
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state.optimizer = createOptimizer();
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}
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});
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els.chkAutoRotate.addEventListener('change', (e) => {
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state.params.n = data.length;
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els.valN.value = data.length;
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els.nInput.value = data.length;
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state.optimizer = tf.train.adam(state.params.lr);
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state.optimizer = createOptimizer();
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state.step = 0;
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updateDistanceMatrix();
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const original = els.btnPaste.textContent;

‎assets/2025-11-27-geometric-entropy.html‎

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@@ -479,6 +479,7 @@ <h1>
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<label>Optimizer</label>
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<select id="opt-optimizer">
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<option value="adam">Adam</option>
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<option value="qqn">QQN</option>
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<option value="lbfgs">L-BFGS</option>
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</div>
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<script type="module">
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import {OptimizerLbfgs} from './js/optimizer-lbfgs.js';
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import {OptimizerAdam} from './js/optimizer-adam.js';
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import {OptimizerQQN} from './js/optimizer-qqn.js';
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/**
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* Spherical Gram Entropy - Interactive Demo
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function createOptimizer() {
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if (state.params.optimizerType === 'adam') {
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return new OptimizerAdam(state.params.lr);
1413+
} else if (state.params.optimizerType === 'qqn') {
1414+
return new OptimizerQQN(state.params.lr);
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}
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return new OptimizerLbfgs(state.params.lr);
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}

‎assets/2025-11-27-measures.html‎

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@@ -832,6 +832,7 @@ <h1>
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</label>
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<select id="opt-optimizer">
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<option value="lbfgs">L-BFGS</option>
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<option value="qqn">QQN</option>
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<option value="adam">Adam</option>
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</select>
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</div>
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<script type="module">
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import {OptimizerAdam} from './js/optimizer-adam.js';
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import {OptimizerQQN} from './js/optimizer-qqn.js';
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/**
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* Interpolated Density Entropy - Interactive Demo
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return;
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}
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1084-
state.optimizer.applyGradients(grads);
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state.optimizer.applyGradients(grads, lossFunction);
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// Update metrics for UI (syncing small scalars is cheap)
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const stats = getDensityStats(effectivePoints, state.params.tau);
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const sortedPoints = Float32Array.from(pointsArr).sort();
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11241126
// Determine scale
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// We want to keep the view somewhat centered but dynamic
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const minVal = Math.min(...sortedPoints);
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const maxVal = Math.max(...sortedPoints);
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const spread = Math.max(maxVal - minVal, 4.0); // Minimum spread of 4
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const padding = spread * 0.1;
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const viewMin = minVal - padding;
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const viewMax = maxVal + padding;
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let viewMin, viewMax;
1128+
if (state.params.fixBoundaries) {
1129+
viewMin = -0.1;
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viewMax = 1.1;
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} else {
1132+
// We want to keep the view somewhat centered but dynamic
1133+
const minVal = Math.min(...sortedPoints);
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const maxVal = Math.max(...sortedPoints);
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const spread = Math.max(maxVal - minVal, 4.0); // Minimum spread of 4
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const padding = spread * 0.1;
1137+
viewMin = minVal - padding;
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viewMax = maxVal + padding;
1139+
}
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11331141
const mapX = (val) => {
11341142
return ((val - viewMin) / (viewMax - viewMin)) * (width - 40) + 20;
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function createOptimizer() {
12331241
if (state.params.optimizerType === 'adam') {
12341242
return new OptimizerAdam(state.params.lr);
1243+
} else if (state.params.optimizerType === 'qqn') {
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return new OptimizerQQN(state.params.lr);
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}
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return new OptimizerLbfgs(state.params.lr);
12371247
}

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