Merge remote-tracking branch 'origin/tills-branch' into tills-branch

static/neural-network-background.js

@@ -49,35 +49,37 @@ class NeuralNetworkBackground {
     this.animationFrameId = null;
     this.isDarkMode = true; // Always use dark mode for the background
     
-    // Colors - Updated to be more subtle
+    // Colors - Updated for intense visibility and neural effect
     this.darkModeColors = {
-      background: '#050a14', // Darker blue-black background
-      nodeColor: '#4a5568',  // Darker nodes for subtlety
-      nodePulse: '#718096',  // Subtle blue pulse
-      connectionColor: '#2d3748', // Darker connections
-      flowColor: '#4a88ff80'   // Semi-transparent flow highlight
+      background: '#030610', // Noch dunklerer Hintergrund für besseren Kontrast
+      nodeColor: '#88a5ff',  // Hellere, leuchtende Knoten
+      nodePulse: '#c0d5ff',  // Strahlend helles Pulsieren
+      connectionColor: '#5a6ca8', // Hellere, sichtbarere Verbindungen
+      flowColor: '#90c8ffee'   // Sehr leuchtende, fast undurchsichtige Flüsse
     };
     
     this.lightModeColors = {
       background: '#f9fafb',
-      nodeColor: '#7c3aed',
-      nodePulse: '#8b5cf6',
-      connectionColor: '#a78bfa',
-      flowColor: '#c4b5fd'
+      nodeColor: '#8c4aff',
+      nodePulse: '#ab7cff',
+      connectionColor: '#b798ff',
+      flowColor: '#d4c5ff'
     };
     
-    // Config - Updated to be more subtle, efficient, and elegant
+    // Config - Drastisch verstärkt für strahlende Animationen und neuronale Vernetzung
     this.config = {
-      nodeCount: 70,             // Reduced node count for better performance
-      nodeSize: 0.6,             // Smaller nodes for subtlety
-      nodeVariation: 0.3,        // Less variation for uniformity
-      connectionDistance: 150,   // Shorter connections for cleaner look
-      connectionOpacity: 0.15,   // More subtle connections
-      animationSpeed: 0.04,      // Slower, more elegant movement
-      pulseSpeed: 0.002,         // Very slow pulse for subtlety
-      flowSpeed: 0.4,            // Slower flow animations
-      flowDensity: 0.0008,       // Less frequent flow animations
-      flowLength: 0.15           // Shorter flow animations
+      nodeCount: 120,             // Viel mehr Knoten für ein dichtes Netzwerk
+      nodeSize: 1.4,              // Größere Knoten für mehr Sichtbarkeit
+      nodeVariation: 0.6,         // Mehr Variation für organisches Aussehen
+      connectionDistance: 220,    // Deutlich längere Verbindungen für mehr Vernetzung
+      connectionOpacity: 0.4,     // Wesentlich stärkere Verbindungen
+      animationSpeed: 0.08,       // Schnellere Bewegung
+      pulseSpeed: 0.006,          // Schnelleres Pulsieren für lebendiges Aussehen
+      flowSpeed: 0.8,             // Schnellere Flussanimationen
+      flowDensity: 0.005,         // Viel mehr Flussanimationen
+      flowLength: 0.25,           // Längere Flussanimationen
+      maxConnections: 6,          // NEW: Neue Eigenschaft für mehr neuronale Verbindungen pro Knoten
+      clusteringFactor: 0.3       // NEW: Erzeugt Cluster wie in einem neuronalen Netzwerk
     };
     
     // Initialize
@@ -221,18 +223,60 @@ class NeuralNetworkBackground {
     const width = this.canvas.width / (window.devicePixelRatio || 1);
     const height = this.canvas.height / (window.devicePixelRatio || 1);
     
-    // Create nodes with random positions and properties
-    for (let i = 0; i < this.config.nodeCount; i++) {
-      const node = {
+    // Erstelle Cluster-Zentren für neuronale Netzwerkmuster
+    const clusterCount = Math.floor(5 + Math.random() * 4); // 5-8 Cluster
+    const clusters = [];
+    
+    for (let i = 0; i < clusterCount; i++) {
+      clusters.push({
         x: Math.random() * width,
         y: Math.random() * height,
-        size: this.config.nodeSize + Math.random() * this.config.nodeVariation,
+        radius: 100 + Math.random() * 150
+      });
+    }
+    
+    // Create nodes with random positions and properties
+    for (let i = 0; i < this.config.nodeCount; i++) {
+      // Entscheide, ob dieser Knoten zu einem Cluster gehört oder nicht
+      const useCluster = Math.random() < this.config.clusteringFactor;
+      let x, y;
+      
+      if (useCluster && clusters.length > 0) {
+        // Wähle ein zufälliges Cluster
+        const cluster = clusters[Math.floor(Math.random() * clusters.length)];
+        const angle = Math.random() * Math.PI * 2;
+        const distance = Math.random() * cluster.radius;
+        
+        // Platziere in der Nähe des Clusters mit einiger Streuung
+        x = cluster.x + Math.cos(angle) * distance;
+        y = cluster.y + Math.sin(angle) * distance;
+        
+        // Stelle sicher, dass es innerhalb des Bildschirms bleibt
+        x = Math.max(0, Math.min(width, x));
+        y = Math.max(0, Math.min(height, y));
+      } else {
+        // Zufällige Position außerhalb von Clustern
+        x = Math.random() * width;
+        y = Math.random() * height;
+      }
+      
+      // Bestimme die Knotengröße - wichtigere Knoten (in Clustern) sind größer
+      const nodeImportance = useCluster ? 1.2 : 0.8;
+      const size = this.config.nodeSize * nodeImportance + Math.random() * this.config.nodeVariation;
+      
+      const node = {
+        x: x,
+        y: y,
+        size: size,
         speed: {
           x: (Math.random() - 0.5) * this.config.animationSpeed,
           y: (Math.random() - 0.5) * this.config.animationSpeed
         },
         pulsePhase: Math.random() * Math.PI * 2, // Random starting phase
-        connections: []
+        connections: [],
+        isActive: Math.random() < 0.3, // Some nodes start active for neural firing effect
+        lastFired: 0,                  // For neural firing animation
+        firingRate: 1000 + Math.random() * 4000 // Random firing rate in ms
       };
       
       this.nodes.push(node);
@@ -248,23 +292,60 @@ class NeuralNetworkBackground {
       const nodeA = this.nodes[i];
       nodeA.connections = [];
       
-      for (let j = i + 1; j < this.nodes.length; j++) {
+      // Sortiere andere Knoten nach Entfernung für bevorzugte nahe Verbindungen
+      const potentialConnections = [];
+      
+      for (let j = 0; j < this.nodes.length; j++) {
+        if (i === j) continue;
+        
         const nodeB = this.nodes[j];
         const dx = nodeB.x - nodeA.x;
         const dy = nodeB.y - nodeA.y;
         const distance = Math.sqrt(dx * dx + dy * dy);
         
         if (distance < this.config.connectionDistance) {
+          potentialConnections.push({
+            index: j,
+            distance: distance
+          });
+        }
+      }
+      
+      // Sortiere nach Entfernung
+      potentialConnections.sort((a, b) => a.distance - b.distance);
+      
+      // Wähle die nächsten N Verbindungen, maximal maxConnections
+      const maxConn = Math.min(
+        this.config.maxConnections, 
+        potentialConnections.length, 
+        1 + Math.floor(Math.random() * this.config.maxConnections)
+      );
+      
+      for (let c = 0; c < maxConn; c++) {
+        const connection = potentialConnections[c];
+        const j = connection.index;
+        const nodeB = this.nodes[j];
+        const distance = connection.distance;
+        
+        // Create weighted connection (closer = stronger)
+        const connectionStrength = Math.max(0, 1 - distance / this.config.connectionDistance);
+        const connOpacity = connectionStrength * this.config.connectionOpacity;
+        
+        // Check if connection already exists
+        if (!this.connections.some(conn => 
+          (conn.from === i && conn.to === j) || (conn.from === j && conn.to === i)
+        )) {
           // Create connection
-          const connection = {
+          this.connections.push({
             from: i,
             to: j,
             distance: distance,
-            opacity: Math.max(0, 1 - distance / this.config.connectionDistance) * this.config.connectionOpacity,
-            hasFlow: false // Each connection can have a flow
-          };
+            opacity: connOpacity,
+            strength: connectionStrength,
+            hasFlow: false, // Each connection can have a flow
+            lastActivated: 0 // For neural firing animation
+          });
           
-          this.connections.push(connection);
           nodeA.connections.push(j);
           nodeB.connections.push(i);
         }
@@ -280,42 +361,48 @@ class NeuralNetworkBackground {
     // Update nodes
     const width = this.canvas.width / (window.devicePixelRatio || 1);
     const height = this.canvas.height / (window.devicePixelRatio || 1);
+    const now = Date.now();
     
-    // Update node positions - slower, more flowing movement
+    // Simulate neural firing
     for (let i = 0; i < this.nodes.length; i++) {
       const node = this.nodes[i];
       
-      // Move node with slight randomness for organic feel
-      node.speed.x += (Math.random() - 0.5) * 0.001;
-      node.speed.y += (Math.random() - 0.5) * 0.001;
+      // Check if node should fire based on its firing rate
+      if (now - node.lastFired > node.firingRate) {
+        node.isActive = true;
+        node.lastFired = now;
         
-      // Dampen speeds for stability
-      node.speed.x *= 0.99;
-      node.speed.y *= 0.99;
+        // Activate connected nodes with probability based on connection strength
+        for (const connIndex of node.connections) {
+          // Find the connection
+          const conn = this.connections.find(c => 
+            (c.from === i && c.to === connIndex) || (c.from === connIndex && c.to === i)
+          );
           
-      // Apply speed limits
-      node.speed.x = Math.max(-this.config.animationSpeed, Math.min(this.config.animationSpeed, node.speed.x));
-      node.speed.y = Math.max(-this.config.animationSpeed, Math.min(this.config.animationSpeed, node.speed.y));
+          if (conn) {
+            // Mark connection as recently activated
+            conn.lastActivated = now;
             
-      // Move node
-      node.x += node.speed.x;
-      node.y += node.speed.y;
-      
-      // Boundary check with smooth bounce
-      if (node.x < 0 || node.x > width) {
-        node.speed.x *= -0.8; // Softer bounce
-        node.x = Math.max(0, Math.min(node.x, width));
+            // Create a flow along this connection
+            if (Math.random() < conn.strength * 0.8) {
+              this.flows.push({
+                connection: conn,
+                progress: 0,
+                direction: conn.from === i, // Flow from activated node
+                length: this.config.flowLength + Math.random() * 0.1,
+                intensity: 0.7 + Math.random() * 0.3 // Random intensity for variation
+              });
             }
             
-      if (node.y < 0 || node.y > height) {
-        node.speed.y *= -0.8; // Softer bounce
-        node.y = Math.max(0, Math.min(node.y, height));
+            // Probability for connected node to activate
+            if (Math.random() < conn.strength * 0.5) {
+              this.nodes[connIndex].isActive = true;
+              this.nodes[connIndex].lastFired = now - Math.random() * 500; // Slight variation
             }
-      
-      // Update pulse phase
-      node.pulsePhase += this.config.pulseSpeed;
-      if (node.pulsePhase > Math.PI * 2) {
-        node.pulsePhase -= Math.PI * 2;
+          }
+        }
+      } else if (now - node.lastFired > 300) { // Deactivate after short period
+        node.isActive = false;
       }
     }
     
@@ -355,6 +442,11 @@ class NeuralNetworkBackground {
         this.flows.splice(i, 1);
       }
     }
+    
+    // Generate more flows for enhanced visibility
+    if (Math.random() < this.config.flowDensity * 2) {
+      this.createNewFlow();
+    }
   }
   
   // New method to create flow animations
@@ -416,14 +508,30 @@ class NeuralNetworkBackground {
     const positions = new Float32Array(this.nodes.length * 2);
     const sizes = new Float32Array(this.nodes.length);
     
+    const now = Date.now();
+    
     for (let i = 0; i < this.nodes.length; i++) {
       const node = this.nodes[i];
       positions[i * 2] = node.x;
       positions[i * 2 + 1] = node.y;
       
-      // Size with subtle pulse effect
-      const pulse = Math.sin(node.pulsePhase) * 0.2 + 1;
-      sizes[i] = node.size * pulse * (node.connections.length > 3 ? 1.3 : 1);
+      // Enhanced pulse effect with additional boost for active nodes
+      let pulse = Math.sin(node.pulsePhase) * 0.4 + 1;
+      
+      // Make active nodes pulse more intensely (neural firing effect)
+      if (node.isActive) {
+        const timeSinceFired = now - node.lastFired;
+        if (timeSinceFired < 300) {
+          // Quick expand then contract effect
+          const normalizedTime = timeSinceFired / 300;
+          const fireBoost = 1.5 * (1 - normalizedTime);
+          pulse += fireBoost;
+        }
+      }
+      
+      // Nodes with more connections are larger (hub neurons)
+      const connectivityFactor = 1 + (node.connections.length / this.config.maxConnections) * 0.8;
+      sizes[i] = node.size * pulse * connectivityFactor;
     }
     
     // Bind position buffer
@@ -452,24 +560,45 @@ class NeuralNetworkBackground {
     );
     this.gl.enableVertexAttribArray(this.programInfo.attribLocations.pointSize);
     
-    // Set node color - more subtle
-    const colorObj = this.isDarkMode ? this.darkModeColors : this.lightModeColors;
-    const nodeColor = this.hexToRgb(colorObj.nodeColor);
-    this.gl.uniform4f(
-      this.programInfo.uniformLocations.color,
-      nodeColor.r / 255,
-      nodeColor.g / 255,
-      nodeColor.b / 255,
-      0.7  // Lower opacity for subtlety
-    );
-    
-    // Draw nodes
+    // Enable blending for all nodes
     this.gl.enable(this.gl.BLEND);
     this.gl.blendFunc(this.gl.SRC_ALPHA, this.gl.ONE);  // Additive blending for glow
-    this.gl.drawArrays(this.gl.POINTS, 0, this.nodes.length);
+    
+    // Draw each node individually with its own color
+    for (let i = 0; i < this.nodes.length; i++) {
+      const node = this.nodes[i];
+      
+      // Set node color - more visible with active highlighting
+      const colorObj = this.isDarkMode ? this.darkModeColors : this.lightModeColors;
+      const nodeColor = this.hexToRgb(colorObj.nodeColor);
+      const nodePulseColor = this.hexToRgb(colorObj.nodePulse);
+      
+      // Use pulse color for active nodes
+      let r = nodeColor.r / 255;
+      let g = nodeColor.g / 255;
+      let b = nodeColor.b / 255;
+      
+      // Active nodes get brighter color
+      if (node.isActive) {
+        r = (r + nodePulseColor.r / 255) / 2;
+        g = (g + nodePulseColor.g / 255) / 2;
+        b = (b + nodePulseColor.b / 255) / 2;
+      }
+      
+      this.gl.uniform4f(
+        this.programInfo.uniformLocations.color,
+        r, g, b,
+        0.95  // Higher opacity for maximum visibility
+      );
+      
+      // Draw each node individually for better control
+      this.gl.drawArrays(this.gl.POINTS, i, 1);
+    }
   }
   
   renderConnectionsWebGL() {
+    const now = Date.now();
+    
     // For each connection, draw a line
     for (const connection of this.connections) {
       const fromNode = this.nodes[connection.from];
@@ -497,15 +626,28 @@ class NeuralNetworkBackground {
       // Disable point size attribute for lines
       this.gl.disableVertexAttribArray(this.programInfo.attribLocations.pointSize);
       
-      // Set line color with connection opacity - darker, more subtle
+      // Set line color with connection opacity
       const colorObj = this.isDarkMode ? this.darkModeColors : this.lightModeColors;
-      const lineColor = this.hexToRgb(colorObj.connectionColor);
+      let lineColor = this.hexToRgb(colorObj.connectionColor);
+      
+      // Highlight recently activated connections for neural pathway effect
+      let opacity = connection.opacity * 1.4; // Base increased visibility
+      
+      if (now - connection.lastActivated < 800) {
+        // Make recently activated connections brighter
+        lineColor = this.hexToRgb(colorObj.flowColor);
+        
+        // Fade out effect
+        const timeFactor = 1 - ((now - connection.lastActivated) / 800);
+        opacity = Math.max(opacity, timeFactor * 0.9);
+      }
+      
       this.gl.uniform4f(
         this.programInfo.uniformLocations.color,
         lineColor.r / 255,
         lineColor.g / 255,
         lineColor.b / 255,
-        connection.opacity * 0.8  // Reduced for subtlety
+        opacity
       );
       
       // Draw the line
@@ -585,7 +727,7 @@ class NeuralNetworkBackground {
         1
       );
       
-      // Flow color - subtle glow
+      // Flow color - much stronger glow
       const colorObj = this.isDarkMode ? this.darkModeColors : this.lightModeColors;
       const flowColor = this.hexToRgb(colorObj.flowColor);
       this.gl.uniform4f(
@@ -593,13 +735,13 @@ class NeuralNetworkBackground {
         flowColor.r / 255,
         flowColor.g / 255,
         flowColor.b / 255,
-        0.4 * fadeOpacity // Subtle flow opacity
+        0.9 * fadeOpacity * flow.intensity // Much stronger flow opacity with intensity variation
       );
       
       // Draw the flow line
       this.gl.enable(this.gl.BLEND);
       this.gl.blendFunc(this.gl.SRC_ALPHA, this.gl.ONE);
-      this.gl.lineWidth(1.5); // Slightly thicker for visibility
+      this.gl.lineWidth(2.5); // Even thicker for dramatic visibility
       this.gl.drawArrays(this.gl.LINES, 0, 2);
     }
   }