Remez Algorithm - Source Code

This page displays the source code of key functions and methods used in the Remez algorithm implementation.
initializeCFRemezNodesRational(targetFunc, a, b, numNodes, numerDeg, denomDeg) {
		try {
			if (!Number.isFinite(a) || !Number.isFinite(b) || a >= b || numNodes < 2) {
				throw new Error(`Invalid inputs: a=${a}, b=${b}, numNodes=${numNodes}`);
			}
			if (numerDeg < 0 || denomDeg < 0) {
				throw new Error(`Invalid degrees: n=${numerDeg}, d=${denomDeg}`);
			}
			const n = numerDeg;
			const d = denomDeg;
			const totalDeg = n + d;
			if (!Number.isFinite(totalDeg) || totalDeg < 0 || totalDeg > 1000) {
				throw new Error(`Invalid total degree: ${totalDeg} (n=${n}, d=${d})`);
			}
			const numChebCoeffs = Math.min(2 * totalDeg + 200, 1500);
			const numSamples = Math.max(40 * (totalDeg + 1), 5000);
			console.log(`CF Rational: n=${n}, d=${d}, chebCoeffs=${numChebCoeffs}, samples=${numSamples}`);
			const chebCoeffs = new Array(numChebCoeffs).fill(0);
			for (let k = 0; k < numSamples; k++) {
				const t = Math.cos(Math.PI * k / (numSamples - 1));
				const x = (b - a) * (t + 1) / 2 + a;
				const y = targetFunc(x);
				if (!Number.isFinite(y)) {
					console.warn(`Non-finite function value at x=${x}`);
					continue;
				}
				for (let j = 0; j < numChebCoeffs && j < numSamples; j++) {
					const Tj = this.chebyshevPolynomial(j, t);
					chebCoeffs[j] += y * Tj;
				}
			}
			for (let j = 0; j < chebCoeffs.length; j++) {
				chebCoeffs[j] *= (j === 0) ? 1.0 / numSamples : 2.0 / numSamples;
				if (Math.abs(chebCoeffs[j]) < 1e-14) chebCoeffs[j] = 0;
			}
			console.log('Chebyshev coefficients:', chebCoeffs.slice(0, Math.min(10, chebCoeffs.length)));
			const cfResult = this.solveRationalCFSystem(chebCoeffs, n, d);
			if (!cfResult.success) {
				throw new Error('CF rational system solver failed');
			}
			const { numerCoeffs, denomCoeffs } = cfResult;
			const cfRationalApprox = (x) => {
				const t = 2 * (x - a) / (b - a) - 1;
				let numer = 0;
				for (let k = 0; k <= n && k < numerCoeffs.length; k++) {
					numer += numerCoeffs[k] * this.chebyshevPolynomial(k, t);
				}
				let denom = 0;
				for (let k = 0; k <= d && k < denomCoeffs.length; k++) {
					denom += denomCoeffs[k] * this.chebyshevPolynomial(k, t);
				}
				if (Math.abs(denom) < 1e-12) {
					console.warn(`Near-zero denominator at x=${x}, t=${t}`);
					return numer / (Math.sign(denom) * 1e-12 || 1e-12);
				}
				return numer / denom;
			};
			console.log('CF rational - numerator coeffs:', numerCoeffs);
			console.log('CF rational - denominator coeffs:', denomCoeffs);
			const testError = Math.abs(targetFunc((a+b)/2) - cfRationalApprox((a+b)/2));
			console.log(`CF test error at midpoint: ${testError.toExponential(3)}`);
			const denseSamples = Math.max(1000, 100 * numNodes);
			const extrema = this.findAlternatingExtremaDetailed(
				targetFunc, 
				cfRationalApprox, 
				a, b, 
				numNodes, 
				denseSamples
			);
			const nodes = extrema.map(e => e.x);
			const maxError = Math.max(...extrema.map(e => Math.abs(e.y)));
			console.log(`CF rational: found ${nodes.length} extrema, maxError=${maxError}`);
			if (nodes.length < numNodes) {
				console.warn(`CF found only ${nodes.length} extrema, need ${numNodes}`);
				return { nodes: nodes, success: true, error: 'Insufficient extrema' };
			}
			return {
				numerCoeffs: numerCoeffs,
				denomCoeffs: denomCoeffs,
				nodes: nodes,
				cfApprox: cfRationalApprox,
				maxError: maxError,
				success: true,
				isRational: true,
				degrees: { n, d }
			};
		} catch (error) {
			console.error('CF rational approximation failed:', error);
			return { nodes: [], success: false, error: error.message };
		}
	}
initializeL2RemezNodes(targetFunc, a, b, numNodes) {
        try {
            const l2A = remMath.polynomialL2Approximation(targetFunc, numNodes-2, a, b, { silent: this.autoMode });
            if (!l2A || !l2A.lsApprox) {
                throw new Error('L2 approximation returned invalid result');
            }
            const lsApprox = l2A.lsApprox;
            let extrema = this.findAlternatingExtrema(targetFunc, l2A.lsApprox, a, b, numNodes);
            const nodes = extrema.map(e => e.x);
            return {
                coeffs: l2A.coeffs, 
                nodes: nodes, 
                lsApprox: l2A.lsApprox,
                success: true
            };
        } catch (error) {
            console.warn('L2 approximation failed:', error.message);
            return { nodes: [], success: false, error: error.message };
        }
    }
initializeDiscreteRemezNodes(targetFunc, a, b, numNodes, gridDensity = 100) {
        const degree = numNodes - 2;
        const numGridPoints = Math.max(1000, gridDensity * numNodes);
        const gridPoints = Array.from({ length: numGridPoints }, (_, i) => 
            a + i * (b - a) / (numGridPoints - 1)
        );
        const targetValues = gridPoints.map(x => targetFunc(x));
        const discreteResult = this.solveDiscreteRemez(gridPoints, targetValues, degree);
        if (!discreteResult.success) {
            console.warn('Discrete Remez failed:', discreteResult.error);
            return { nodes: [], success: false, error: discreteResult.error };
        }
        const extrema = this.findDiscreteExtremaFromSolution(
            gridPoints, 
            targetValues, 
            discreteResult.approxValues, 
            numNodes
        );
        const nodes = extrema.map(e => e.x);
        return {
            coeffs: discreteResult.coeffs,
            nodes: nodes,
            discreteApprox: discreteResult.approxFunc,
            maxError: Math.max(...extrema.map(e => Math.abs(e.error))),
            success: true
        };
    }
findReferenceSimple(errorFunction, coefficients, currentReference) {
    const coarseSteps = parseInt(document.getElementById('bruteSteps').value);
    const refinementSteps = 10;
    const refinementIterations = 5;
    const eps = 0.000001/n;
    let newReference = [];
    for (let k = 0; k < currentReference.length; k++) {
        const isFirst = k == 0;
        const isLast = k == currentReference.length - 1;
        // If first/last point lies on the boundary, re-evaluate it there without searching
        if (isFirst && currentReference[k].x <= aP.intervalStart + eps) {
            const x = aP.intervalStart;
            newReference.push({x, y: errorFunction(coefficients, x), originalIndex: k});
            continue;
        }
        if (isLast && currentReference[k].x >= aP.intervalEnd - eps) {
            const x = aP.intervalEnd;
            newReference.push({x, y: errorFunction(coefficients, x), originalIndex: k});
            continue;
        }
        // Free points: search within the interval between neighbors
        const left = isFirst ? aP.intervalStart + eps : currentReference[k-1].x + eps;
        const right = isLast ? aP.intervalEnd - eps : currentReference[k+1].x - eps;
        if (left >= right || !isFinite(left) || !isFinite(right)) {
            console.warn('Current reference: ', currentReference);
            console.warn(`Invalid interval at k=${k}: [${left}, ${right}]`);
            newReference.push({...currentReference[k], originalIndex: k});
            continue;
        }
        let extremum = currentReference[k];
        let delta = (right - left) / coarseSteps;
        for (let step = 0; step <= coarseSteps; step++) {
            const currentX = left + step * delta;
            if (currentX > right) break;
            const currentY = errorFunction(coefficients, currentX);
            if (!isFinite(currentY)) continue;
            if ((currentReference[k].y > 0 && currentY > extremum.y) ||
                (currentReference[k].y < 0 && currentY < extremum.y)) {
                extremum = {x: currentX, y: currentY};
            }
        }
        for (let i = 0; i < refinementIterations; i++) {
            const refinementLeft = Math.max(left, extremum.x - delta);
            const refinementRight = Math.min(right, extremum.x + delta);
            delta = (refinementRight - refinementLeft) / refinementSteps;
            if (delta <= 0 || !isFinite(delta)) break;
            for (let step = 0; step <= refinementSteps; step++) {
                const currentX = refinementLeft + step * delta;
                if (currentX > refinementRight) break;
                const currentY = errorFunction(coefficients, currentX);
                if (!isFinite(currentY)) continue;
                if ((currentReference[k].y > 0 && currentY > extremum.y) ||
                    (currentReference[k].y < 0 && currentY < extremum.y)) {
                    extremum = {x: currentX, y: currentY};
                }
            }
        }
        newReference.push({...extremum, originalIndex: k});
    }
    return newReference;
}
findReferenceParabolic(calculateError, optimizationCoefficients, currentReferencePoints) {
    const maxInterpolationIterations = parseInt(document.getElementById('parabolicSteps').value);
    const minimumPointSeparation = 0.01;
    const convergenceThreshold = 1e-10;
    const epsilon = 1e-12;
    const goldenRatio = 0.618033988749;
    // Enhanced parabolic interpolation with better numerical stability
    function interpolateParabola(x0, x1, x2, y0, y1, y2) {
        // Use more numerically stable form
        const h1 = x1 - x0;
        const h2 = x2 - x1;
        const d1 = (y1 - y0) / h1;
        const d2 = (y2 - y1) / h2;
        const denominator = h1 + h2;
        if (Math.abs(denominator) < epsilon || Math.abs(d2 - d1) < epsilon) {
            return (x0 + x2) / 2; // Fallback to midpoint
        }
        const a = (d2 - d1) / denominator;
        if (Math.abs(a) < epsilon) {
            return (x0 + x2) / 2; // Nearly linear, use midpoint
        }
        // Compute vertex of parabola
        const vertex = x1 - d1 / (2 * a) - h1 / 2;
        return vertex;
    }
    // Adaptive bracket width calculation
    function calculateInitialBracket(pointIndex, currentPoints) {
        const baseWidth = 0.1; // Default bracket width
        let adaptiveWidth = baseWidth;
        if (pointIndex > 0) {
            const leftSpacing = currentPoints[pointIndex].x - currentPoints[pointIndex - 1].x;
            adaptiveWidth = Math.min(adaptiveWidth, leftSpacing * 0.3);
        }
        if (pointIndex < currentPoints.length - 1) {
            const rightSpacing = currentPoints[pointIndex + 1].x - currentPoints[pointIndex].x;
            adaptiveWidth = Math.min(adaptiveWidth, rightSpacing * 0.3);
        }
        return Math.max(adaptiveWidth, minimumPointSeparation * 2);
    }
    // Enhanced caching with LRU eviction
    class ErrorCache {
        constructor(maxSize = 1000) {
            this.cache = new Map();
            this.maxSize = maxSize;
        }
        get(x) {
            const key = x.toFixed(12); // Round to avoid floating point issues
            if (this.cache.has(key)) {
                const value = this.cache.get(key);
                this.cache.delete(key);
                this.cache.set(key, value); // Move to end (most recent)
                return value;
            }
            const value = calculateError(optimizationCoefficients, x);
            if (this.cache.size >= this.maxSize) {
                const firstKey = this.cache.keys().next().value;
                this.cache.delete(firstKey);
            }
            this.cache.set(key, value);
            return value;
        }
    }
    const errorCache = new ErrorCache();
    // Main optimization loop
    let optimizedReferencePoints = [];
    for (let pointIndex = 0; pointIndex < currentReferencePoints.length; pointIndex++) {
        const currentPoint = currentReferencePoints[pointIndex];
        // Calculate boundaries
        const minAllowedX = (pointIndex === 0) ? 
            aP.intervalStart : 
            optimizedReferencePoints[pointIndex - 1].x + minimumPointSeparation;
        const maxAllowedX = (pointIndex === currentReferencePoints.length - 1) ? 
            aP.intervalEnd : 
            currentReferencePoints[pointIndex + 1].x - minimumPointSeparation;
        // Initialize with adaptive bracket
        const bracketWidth = calculateInitialBracket(pointIndex, currentReferencePoints);
        let leftX = Math.max(minAllowedX, currentPoint.x - bracketWidth);
        let midX = currentPoint.x;
        let rightX = Math.min(maxAllowedX, currentPoint.x + bracketWidth);
        // Ensure proper ordering and spacing
        if (rightX - leftX < 2 * minimumPointSeparation) {
            const center = (leftX + rightX) / 2;
            leftX = Math.max(minAllowedX, center - minimumPointSeparation);
            rightX = Math.min(maxAllowedX, center + minimumPointSeparation);
            midX = center;
        }
        let bestX = midX;
        let bestY = errorCache.get(midX);
        let iterationCount = 0;
        let consecutiveSmallSteps = 0;
        let lastStepSize = Infinity;
        // Target direction: maximize absolute error
        const targetSign = Math.sign(currentPoint.y);
        while (iterationCount < maxInterpolationIterations) {
            const leftY = errorCache.get(leftX);
            const midY = errorCache.get(midX);
            const rightY = errorCache.get(rightX);
            // Try parabolic interpolation
            let newX = interpolateParabola(leftX, midX, rightX, 
                                         leftY * targetSign, midY * targetSign, rightY * targetSign);
            // Clamp to valid range
            newX = Math.max(minAllowedX, Math.min(maxAllowedX, newX));
            // Avoid getting stuck at boundaries
            if (newX === minAllowedX || newX === maxAllowedX) {
                newX = (leftX + rightX) / 2;
            }
            const stepSize = Math.abs(newX - bestX);
            // Check convergence
            if (stepSize < convergenceThreshold) {
                consecutiveSmallSteps++;
                if (consecutiveSmallSteps >= 3) break;
            } else {
                consecutiveSmallSteps = 0;
            }
            // Detect oscillation or stagnation
            if (stepSize > lastStepSize * 0.9 && iterationCount > 3) {
                // Switch to golden section if parabolic isn't converging
                const range = rightX - leftX;
                if (newX > midX) {
                    newX = midX + goldenRatio * (rightX - midX);
                } else {
                    newX = midX - goldenRatio * (midX - leftX);
                }
                newX = Math.max(minAllowedX, Math.min(maxAllowedX, newX));
            }
            const newY = errorCache.get(newX);
            // Update best point if we found improvement
            if (Math.abs(newY) > Math.abs(bestY)) {
                bestX = newX;
                bestY = newY;
            }
            // Update bracket based on function behavior
            if (newX < midX) {
                if (Math.abs(newY) > Math.abs(midY)) {
                    rightX = midX;
                    midX = newX;
                } else {
                    leftX = newX;
                }
            } else if (newX > midX) {
                if (Math.abs(newY) > Math.abs(midY)) {
                    leftX = midX;
                    midX = newX;
                } else {
                    rightX = newX;
                }
            }
            // Ensure bracket doesn't collapse
            if (rightX - leftX < 2 * convergenceThreshold) {
                const expansion = Math.max(convergenceThreshold * 10, (maxAllowedX - minAllowedX) * 0.01);
                const center = (leftX + rightX) / 2;
                leftX = Math.max(minAllowedX, center - expansion);
                rightX = Math.min(maxAllowedX, center + expansion);
                midX = center;
            }
            lastStepSize = stepSize;
            iterationCount++;
        }
        // Final adjustment for minimum separation
        if (optimizedReferencePoints.length > 0) {
            const minRequiredX = optimizedReferencePoints[optimizedReferencePoints.length - 1].x + minimumPointSeparation;
            if (bestX < minRequiredX) {
                bestX = minRequiredX;
                bestY = errorCache.get(bestX);
            }
        }
        optimizedReferencePoints.push({
            x: bestX, 
            y: bestY,
            iterations: iterationCount,
            converged: consecutiveSmallSteps >= 3 || iterationCount < maxInterpolationIterations
        });
    }
    console.log("Optimized Reference Points:", optimizedReferencePoints);
    return optimizedReferencePoints;
}