|
@@ -0,0 +1,78 @@
|
|
|
+const rawMetrics = (() => {
|
|
|
+ const RMS = {
|
|
|
+ name: "RMS Deviation (σ)",
|
|
|
+ display: p => String.raw`
|
|
|
+ \sigma\left(${p}\right) = \sqrt{I\left(${p}\right) - 2\vec{q}\cdot\vec{\mu}\left(${p}\right) + \left|\left|\vec{q}\right|\right|^2}
|
|
|
+ `,
|
|
|
+ evaluate: (data, target) => math.sqrt(data.inertia - 2 * vectorDot(data.mu.vector, target.vector) + target.sqMag),
|
|
|
+ };
|
|
|
+
|
|
|
+ const meanOfAngle = {
|
|
|
+ name: "Mean of Angular Difference (Θ)",
|
|
|
+ display: p => String.raw`
|
|
|
+ \Theta\left(${p}\right) = \cos^{-1}\left( \hat{q}\cdot\vec{\nu}\left(${p}\right) \right)
|
|
|
+ `,
|
|
|
+ evaluate: (data, target) => rad2deg * Math.acos(vectorDot(data.nu.vector, target.unit)),
|
|
|
+ };
|
|
|
+
|
|
|
+ const angleOfMean = {
|
|
|
+ name: "Angular Difference of Mean (θ)",
|
|
|
+ display: p => String.raw`
|
|
|
+ \theta\left(${p}\right) = \cos^{-1}\left( \hat{q}\cdot\hat{\mu}\left(${p}\right) \right)
|
|
|
+ `,
|
|
|
+ evaluate: (data, target) => rad2deg * Math.acos(vectorDot(data.mu.unit, target.unit)),
|
|
|
+ };
|
|
|
+
|
|
|
+ const hue = {
|
|
|
+ name: "Hue Difference of Mean (ϕ)",
|
|
|
+ display: p => String.raw`
|
|
|
+ \phi\left(${p}\right) = \angle \left(\vec{q}_{\perp}, \vec{\mu}\left(${p}\right)_{\perp} \right)
|
|
|
+ `,
|
|
|
+ evaluate: (data, target) => angleDiff(data.mu.hue, target.hue),
|
|
|
+ }
|
|
|
+
|
|
|
+ const euclidean = {
|
|
|
+ name: "Euclidean Distance to Mean (δ)",
|
|
|
+ display: p => String.raw`
|
|
|
+ \delta\left(${p}\right) = \left|\left| \vec{q} - \vec{\mu}\left(${p}\right) \right|\right|
|
|
|
+ `,
|
|
|
+ evaluate: (data, target) => vectorDist(data.mu.vector, target.vector),
|
|
|
+ };
|
|
|
+
|
|
|
+ const chebyshev = {
|
|
|
+ name: "Chebyshev Distance to Mean (Ч)",
|
|
|
+ display: p => String.raw`
|
|
|
+ Ч\left(${p}\right) = \max_{i} \left| \vec{\mu}\left(${p}\right)_i - \vec{q}_i \right|
|
|
|
+ `,
|
|
|
+ evaluate: (data, target) => Math.max(...data.mu.vector.map((x, i) => Math.abs(x - target.vector[i]))),
|
|
|
+ };
|
|
|
+
|
|
|
+ const inertia = {
|
|
|
+ name: "Inertia (I)",
|
|
|
+ display: p => String.raw`
|
|
|
+ I\left(${p}\right) = \frac{1}{\left|${p}\right|} \sum_{p\in ${p}}{\left|\left|\vec{p}\right|\right|^2}
|
|
|
+ `,
|
|
|
+ evaluate: data => data.inertia,
|
|
|
+ };
|
|
|
+
|
|
|
+ const size = {
|
|
|
+ name: "Size (N)",
|
|
|
+ display: p => String.raw`
|
|
|
+ N\left(${p}\right) = \left|${p}\right|
|
|
|
+ `,
|
|
|
+ evaluate: data => data.size,
|
|
|
+ };
|
|
|
+
|
|
|
+ return [RMS, meanOfAngle, angleOfMean, hue, euclidean, chebyshev, inertia, size];
|
|
|
+})();
|
|
|
+
|
|
|
+const applyMetrics = (data, target) => ({
|
|
|
+ sigma: rawMetrics[0].evaluate(data, target),
|
|
|
+ bigTheta: rawMetrics[1].evaluate(data, target),
|
|
|
+ theta: rawMetrics[2].evaluate(data, target),
|
|
|
+ phi: rawMetrics[3].evaluate(data, target),
|
|
|
+ delta: rawMetrics[4].evaluate(data, target),
|
|
|
+ ch: rawMetrics[5].evaluate(data, target),
|
|
|
+ inertia: rawMetrics[6].evaluate(data),
|
|
|
+ size: rawMetrics[7].evaluate(data),
|
|
|
+});
|