fix: 🚨 fix linter errors

src/force/Force.ts

@@ -1,6 +1,5 @@
 /**
  * @author @thkruz Theodore Kruczek
- *
  * @license AGPL-3.0-or-later
  * @copyright (c) 2020-2024 Theodore Kruczek
  *
@@ -25,6 +24,8 @@ export abstract class Force {
   /**
    * Calculate the acceleration due to the perturbing force on a given
    * state vector.
+   * @param state The state vector.
+   * @throws If the force cannot be calculated.
    */
   acceleration(state: J2000): Vector3D {
     throw Error('Not implemented');

src/force/Gravity.ts

@@ -1,6 +1,5 @@
 /**
  * @author @thkruz Theodore Kruczek
- *
  * @license AGPL-3.0-or-later
  * @copyright (c) 2020-2024 Theodore Kruczek
  *
@@ -34,7 +33,6 @@ export class Gravity implements Force {
 
   /**
    * Calculates the gravitational force in spherical coordinates.
-   *
    * @param state The J2000 state containing the position and velocity vectors.
    * @returns The gravitational force vector in spherical coordinates.
    */
@@ -46,7 +44,6 @@ export class Gravity implements Force {
 
   /**
    * Calculates the acceleration due to gravity at a given state.
-   *
    * @param state The J2000 state at which to calculate the acceleration.
    * @returns The acceleration vector.
    */

src/force/SolarRadiationPressure.ts

@@ -1,6 +1,5 @@
 /**
  * @author @thkruz Theodore Kruczek
- *
  * @license AGPL-3.0-or-later
  * @copyright (c) 2020-2024 Theodore Kruczek
  *

src/force/ThirdBodyGravity.ts

@@ -1,6 +1,5 @@
 /**
  * @author @thkruz Theodore Kruczek
- *
  * @license AGPL-3.0-or-later
  * @copyright (c) 2020-2024 Theodore Kruczek
  *

src/interpolator/StateInterpolator.ts

@@ -1,6 +1,5 @@
 /**
  * @author @thkruz Theodore Kruczek
- *
  * @license AGPL-3.0-or-later
  * @copyright (c) 2020-2024 Theodore Kruczek
  *
@@ -26,9 +25,8 @@ import { Interpolator } from './Interpolator';
 export abstract class StateInterpolator extends Interpolator {
   /**
    * Interpolates the state at the given epoch.
-   *
    * @param epoch The epoch in UTC format.
-   * @returns The interpolated state at the given epoch, or null if interpolation is not possible.
+   * @throws If the interpolator has not been initialized.
    */
   interpolate(epoch: EpochUTC): J2000 | null {
     throw new Error('Not implemented.');

src/objects/DetailedSensor.ts

@@ -1,6 +1,5 @@
 /**
  * @author @thkruz Theodore Kruczek
- *
  * @license AGPL-3.0-or-later
  * @copyright (c) 2020-2024 Theodore Kruczek
  *

src/objects/Marker.ts

@@ -1,6 +1,5 @@
 /**
  * @author @thkruz Theodore Kruczek
- *
  * @license AGPL-3.0-or-later
  * @copyright (c) 2020-2024 Theodore Kruczek
  *

src/observation/ObservationUtils.ts

@@ -1,6 +1,5 @@
 /**
  * @author @thkruz Theodore Kruczek
- *
  * @license AGPL-3.0-or-later
  * @copyright (c) 2020-2024 Theodore Kruczek
  *

src/observation/PropagatorPairs.ts

@@ -1,6 +1,5 @@
 /**
  * @author @thkruz Theodore Kruczek
- *
  * @license AGPL-3.0-or-later
  * @copyright (c) 2020-2024 Theodore Kruczek
  *
@@ -37,6 +36,8 @@ export class PropagatorPairs {
 
   /**
    * Get the step size at the provided index.
+   * @param index The index.
+   * @returns The step size.
    */
   step(index: number): number {
     return index < 3 ? this._posStep : this._velStep;

src/operations/BoxMuller.ts

@@ -1,6 +1,5 @@
 /**
  * @author @thkruz Theodore Kruczek
- *
  * @license AGPL-3.0-or-later
  * @copyright (c) 2020-2024 Theodore Kruczek
  *
@@ -32,6 +31,9 @@ export class BoxMuller {
   /**
    * Create a new [BoxMuller] object with mean [mu], standard deviation
    * [sigma], and [seed] number.
+   * @param mu Mean value.
+   * @param sigma Standard deviation.
+   * @param seed Random seed.
    */
   constructor(mu: number, sigma: number, seed = 0) {
     this.mu = mu;
@@ -54,6 +56,7 @@ export class BoxMuller {
   /**
    * Generate a gaussian number, with mean [mu] and standard
    * deviation [sigma].
+   * @returns A gaussian number.
    */
   nextGauss(): number {
     if (this._index > 1) {
@@ -69,6 +72,8 @@ export class BoxMuller {
   /**
    * Generate a [Vector] of gaussian numbers, with mean [mu] and standard
    * deviation [sigma].
+   * @param n Number of gaussian numbers to generate.
+   * @returns A [Vector] of gaussian numbers.
    */
   gaussVector(n: number): Vector {
     const result = new Float64Array(n);

src/optimize/DownhillSimplex.ts

@@ -1,6 +1,5 @@
 /**
  * @author @thkruz Theodore Kruczek
- *
  * @license AGPL-3.0-or-later
  * @copyright (c) 2020-2024 Theodore Kruczek
  *
@@ -27,6 +26,9 @@ export class DownhillSimplex {
   /**
    * Compute the centroid from a list of [SimplexEntry] objects, using cost
    * function [f].
+   * @param f Cost function
+   * @param xss Simplex entries
+   * @returns The centroid.
    */
   private static _centroid(f: CostFunction, xss: SimplexEntry[]): SimplexEntry {
     const n = xss[0].points.length;
@@ -58,6 +60,9 @@ export class DownhillSimplex {
   /**
    * Generate a new simplex from initial guess [x0], and an optional
    * simplex [step] value.
+   * @param x0 Initial guess
+   * @param step Simplex step
+   * @returns The simplex.
    */
   static generateSimplex(x0: Float64Array, step = 0.01): Float64Array[] {
     const output: Float64Array[] = [x0.slice(0)];
@@ -82,6 +87,15 @@ export class DownhillSimplex {
    * - `maxIter`: maximum number of optimization iterations
    * - `adaptive`: use adaptive coefficients if possible
    * - `printIter`: print a debug statement after each iteration
+   * @param f Cost function
+   * @param xs Initial simplex
+   * @param root0 Root0
+   * @param root0.xTolerance Root0.xTolerance
+   * @param root0.fTolerance Root0.fTolerance
+   * @param root0.maxIter Root0.maxIter
+   * @param root0.adaptive Root0.adaptive
+   * @param root0.printIter Root0.printIter
+   * @returns The optimal input value.
    */
   static solveSimplex(
     f: CostFunction,

src/optimize/PolynomialRegression.ts

@@ -1,6 +1,5 @@
 /**
  * @author @thkruz Theodore Kruczek
- *
  * @license AGPL-3.0-or-later
  * @copyright (c) 2020-2024 Theodore Kruczek
  *
@@ -34,6 +33,12 @@ export class PolynomialRegression {
   /**
    * Optimize polynomial coefficients to fit data series [xs] and [ys] for the
    * provided polynomial [order].
+   * @param xs x values
+   * @param ys y values
+   * @param order Polynomial order
+   * @param root0 Root0
+   * @param root0.printIter Root0.printIter
+   * @returns The optimal input value.
    */
   static solve(
     xs: Float64Array,
@@ -43,6 +48,11 @@ export class PolynomialRegression {
   ): PolynomicalRegressionResult {
     const simplex = DownhillSimplex.generateSimplex(Float64Array.from(Array(order + 1).fill(1.0)));
 
+    /**
+     * Sum of squared errors.
+     * @param coeffs Polynomial coefficients
+     * @returns Sum of squared errors
+     */
     function f(coeffs: Float64Array): number {
       let sse = 0.0;
 
@@ -72,6 +82,13 @@ export class PolynomialRegression {
    * Optimize polynomial coefficients to fit data series [xs] and [ys], and
    * attempt to find an optimal order within the [minOrder] and
    * [maxOrder] bounds.
+   * @param xs x values
+   * @param ys y values
+   * @param minOrder Minimum polynomial order
+   * @param maxOrder Maximum polynomial order
+   * @param root0 Root0
+   * @param root0.printIter Root0.printIter
+   * @returns The optimal input value.
    */
   static solveOrder(
     xs: Float64Array,

src/optimize/PolynomicalRegressionResult.ts

@@ -1,6 +1,5 @@
 /**
  * @author @thkruz Theodore Kruczek
- *
  * @license AGPL-3.0-or-later
  * @copyright (c) 2020-2024 Theodore Kruczek
  *
@@ -22,6 +21,10 @@ export class PolynomicalRegressionResult {
    * Create a new [PolynomicalRegressionResult] object, containing the
    * polynomial [coefficients], root-sum-squared error [rss], and Bayes
    * information criterea [bic].
+   * @param coefficients  The polynomial coefficients.
+   * @param rss The root-sum-squared error.
+   * @param bic The Bayes information criterea.
+   * @returns The optimal input value.
    */
   constructor(public coefficients: Float64Array, public rss: number, public bic: number) {
     // Nothing to do here.

src/optimize/SimpleLinearRegression.ts

@@ -1,6 +1,5 @@
 /**
  * @author @thkruz Theodore Kruczek
- *
  * @license AGPL-3.0-or-later
  * @copyright (c) 2020-2024 Theodore Kruczek
  *
@@ -21,6 +20,8 @@ export class SimpleLinearRegression {
   /**
    * Create a new [SimpleLinearRegression] object from lists of x and y
    * values.
+   * @param xs x values
+   * @param ys y values
    */
   constructor(public xs: number[], public ys: number[]) {
     this.update();
@@ -106,6 +107,8 @@ export class SimpleLinearRegression {
   /**
    * Create a new [SimpleLinearRegression] object with outliers above the
    * provided standard deviation [sigma] value removed.
+   * @param sigma standard deviation
+   * @returns new [SimpleLinearRegression] object
    */
   filterOutliers(sigma = 1.0): SimpleLinearRegression {
     const limit = this.error * sigma;

src/optimize/SimplexEntry.ts

@@ -1,6 +1,5 @@
 /**
  * @author @thkruz Theodore Kruczek
- *
  * @license AGPL-3.0-or-later
  * @copyright (c) 2020-2024 Theodore Kruczek
  *

src/orbit_determination/BatchLeastSquaresResult.ts

@@ -1,6 +1,5 @@
 /**
  * @author @thkruz Theodore Kruczek
- *
  * @license AGPL-3.0-or-later
  * @copyright (c) 2020-2024 Theodore Kruczek
  *
@@ -24,6 +23,9 @@ export class BatchLeastSquaresResult {
   /**
    * Create a new [BatchLeastSquaresResult] object, containing the solved
    * [state], [covariance], and root-mean-squared error [rms].
+   * @param state The solved state.
+   * @param covariance The solved covariance.
+   * @param rms The root-mean-squared error.
    */
   constructor(public state: J2000, public covariance: StateCovariance, public rms: number) {
     // Nothing to do here.

src/propagator/DormandPrince54Propagator.ts

@@ -1,6 +1,5 @@
 /**
  * @author @thkruz Theodore Kruczek
- *
  * @license AGPL-3.0-or-later
  * @copyright (c) 2020-2024 Theodore Kruczek
  *

src/propagator/RkCheckpoint.ts

@@ -1,6 +1,5 @@
 /**
  * @author @thkruz Theodore Kruczek
- *
  * @license AGPL-3.0-or-later
  * @copyright (c) 2020-2024 Theodore Kruczek
  *

src/propagator/RkResult.ts

@@ -1,6 +1,5 @@
 /**
  * @author @thkruz Theodore Kruczek
- *
  * @license AGPL-3.0-or-later
  * @copyright (c) 2020-2024 Theodore Kruczek
  *

src/propagator/RungeKutta89Propagator.ts

@@ -1,6 +1,5 @@
 /**
  * @author @thkruz Theodore Kruczek
- *
  * @license AGPL-3.0-or-later
  * @copyright (c) 2020-2024 Theodore Kruczek
  *

src/propagator/Sgp4Propagator.ts

@@ -1,6 +1,5 @@
 /**
  * @author @thkruz Theodore Kruczek
- *
  * @license AGPL-3.0-or-later
  * @copyright (c) 2020-2024 Theodore Kruczek
  *

src/smoothing/ExponentialSmoothing.ts

@@ -1,6 +1,5 @@
 /**
  * @author @thkruz Theodore Kruczek
- *
  * @license AGPL-3.0-or-later
  * @copyright (c) 2020-2024 Theodore Kruczek
  *