Method computeLayerPositions

assets/main.js:2511–2558

(layerIndex, neuronCount, layerX)

  }

  computeLayerPositions(layerIndex, neuronCount, layerX) {
    const positions = [];
    const isOutputLayer = layerIndex === this.mlp.architecture.length - 1;
    if (layerIndex === 0) {
      const spacing = this.options.inputSpacing;
      let rows;
      let cols;
      if (neuronCount === 28 * 28) {
        rows = 28;
        cols = 28;
      } else {
        cols = Math.ceil(Math.sqrt(neuronCount));
        rows = Math.ceil(neuronCount / cols);
      }
      const height = (rows - 1) * spacing;
      const width = (cols - 1) * spacing;
      let filled = 0;
      for (let row = 0; row < rows && filled < neuronCount; row += 1) {
        for (let col = 0; col < cols && filled < neuronCount; col += 1) {
          const y = height / 2 - row * spacing;
          const z = -width / 2 + col * spacing;
          positions.push(new THREE.Vector3(layerX, y, z));
          filled += 1;
        }
      }
    } else if (isOutputLayer) {
      const spacing = this.options.outputSpacing ?? this.options.hiddenSpacing;
      const height = (neuronCount - 1) * spacing;
      for (let index = 0; index < neuronCount; index += 1) {
        const y = height / 2 - index * spacing;
        positions.push(new THREE.Vector3(layerX, y, 0));
      }
    } else {
      const spacing = this.options.hiddenSpacing;
      const cols = Math.max(1, Math.ceil(Math.sqrt(neuronCount)));
      const rows = Math.ceil(neuronCount / cols);
      const height = (rows - 1) * spacing;
      const width = (cols - 1) * spacing;
      for (let index = 0; index < neuronCount; index += 1) {
        const row = Math.floor(index / cols);
        const col = index % cols;
        const y = height / 2 - row * spacing;
        const z = -width / 2 + col * spacing;
        positions.push(new THREE.Vector3(layerX, y, z));
      }
    }
    return positions;
  }

  clearOutputLabels() {
    if (!this.outputLabels.length || !this.labelGroup) return;