Huge News!Announcing our $40M Series B led by Abstract Ventures.Learn More →
ml-curve-fitting
Advanced tools
ml-curve-fitting - npm Package Compare versions
Comparing version 0.0.5 to 0.0.6
| { | ||
| "name": "ml-curve-fitting", | ||
| "version": "0.0.5", | ||
| "version": "0.0.6", | ||
| "description": "Levenberg Marquardt curve-fitting: minimize sum of weighted squared residuals", | ||
@@ -5,0 +5,0 @@ "keywords": [ |
| { | ||
| "name": "ml-curve-fitting", | ||
| "version": "0.0.5", | ||
| "version": "0.0.6", | ||
| "description": "Levenberg Marquardt curve-fitting: minimize sum of weighted squared residuals", | ||
@@ -5,0 +5,0 @@ "main": "src/index.js", |
105
README.md
@@ -1,93 +0,26 @@ | ||
| # Levenberg Marquardt curve-fitting | ||
| # ml-curve-fitting | ||
| [![NPM version][npm-image]][npm-url] | ||
| [![build status][travis-image]][travis-url] | ||
| [![npm download][download-image]][download-url] | ||
| Levenberg Marquardt curve-fitting | ||
| minimize sum of weighted squared residuals. Javascript version of matlab library from Henri Gavin. | ||
| See example for usage | ||
| ## Installation | ||
| ## --------- INPUT VARIABLES ----------- | ||
| func = function of n independent variables, 't', and m parameters, 'p', | ||
| returning the simulated model: y_hat = func(t,p,c) | ||
| p = n-vector of initial guess of parameter values | ||
| t = m-vectors or matrix of independent variables (used as arg to func) | ||
| y_dat = m-vectors or matrix of data to be fit by func(t,p) | ||
| weight = weighting vector for least squares fit ( weight >= 0 ) ... | ||
| inverse of the standard measurement errors | ||
| Default: sqrt(d.o.f. / ( y_dat' * y_dat )) | ||
| dp = fractional increment of 'p' for numerical derivatives | ||
| dp(j)>0 central differences calculated | ||
| dp(j)<0 one sided 'backwards' differences calculated | ||
| dp(j)=0 sets corresponding partials to zero; i.e. holds p(j) fixed | ||
| Default: 0.001; | ||
| p_min = n-vector of lower bounds for parameter values | ||
| p_max = n-vector of upper bounds for parameter values | ||
| c = an optional matrix of values passed to func(t,p,c) | ||
| opts = vector of algorithmic parameters | ||
| parameter defaults meaning | ||
| opts(1) = prnt 3 >1 intermediate results; >2 plots | ||
| opts(2) = MaxIter 10*Npar maximum number of iterations | ||
| opts(3) = epsilon_1 1e-3 convergence tolerance for gradient | ||
| opts(4) = epsilon_2 1e-3 convergence tolerance for parameters | ||
| opts(5) = epsilon_3 1e-3 convergence tolerance for Chi-square | ||
| opts(6) = epsilon_4 1e-2 determines acceptance of a L-M step | ||
| opts(7) = lambda_0 1e-2 initial value of L-M paramter | ||
| opts(8) = lambda_UP_fac 11 factor for increasing lambda | ||
| opts(9) = lambda_DN_fac 9 factor for decreasing lambda | ||
| opts(10) = Update_Type 1 1: Levenberg-Marquardt lambda update | ||
| 2: Quadratic update | ||
| 3: Nielsen's lambda update equations | ||
| `$ npm install ml-curve-fitting` | ||
| ##---------- OUTPUT VARIABLES ----------- | ||
| ## [Documentation](./Documentation.md) | ||
| p = least-squares optimal estimate of the parameter values | ||
| X2 = Chi squared criteria | ||
| ## License | ||
| Henri Gavin, Dept. Civil & Environ. Engineering, Duke Univ. 22 Sep 2013 | ||
| modified from: [http://octave.sourceforge.net/optim/function/leasqr.html] | ||
| using references by | ||
| Press, et al., Numerical Recipes, Cambridge Univ. Press, 1992, Chapter 15. | ||
| Sam Roweis [http://www.cs.toronto.edu/~roweis/notes/lm.pdf] | ||
| Manolis Lourakis [http://www.ics.forth.gr/~lourakis/levmar/levmar.pdf] | ||
| Hans Nielson [http://www2.imm.dtu.dk/~hbn/publ/TR9905.ps] | ||
| Mathworks optimization toolbox reference manual | ||
| K. Madsen, H.B., Nielsen, and O. Tingleff | ||
| [http://www2.imm.dtu.dk/pubdb/views/edoc_download.php/3215/pdf/imm3215.pdf] | ||
| [MIT](./LICENSE) | ||
| [npm-image]: https://img.shields.io/npm/v/ml-curve-fitting.svg?style=flat-square | ||
| [npm-url]: https://npmjs.org/package/ml-curve-fitting | ||
| [travis-image]: https://img.shields.io/travis/mljs/curve-fitting/master.svg?style=flat-square | ||
| [travis-url]: https://travis-ci.org/mljs/curve-fitting | ||
| [download-image]: https://img.shields.io/npm/dm/ml-curve-fitting.svg?style=flat-square | ||
| [download-url]: https://npmjs.org/package/ml-curve-fitting |
@@ -86,7 +86,4 @@ /** | ||
| var J = Matrix.zeros(Npnt,Npar); | ||
| /*var J = new Array(Npnt);//zeros(Npnt,Npar); // Jacobian matrix | ||
| for(var i=0;i<Npnt;i++){ | ||
| J[i] = new Array(Npar); | ||
| }*/ | ||
| if (t.length != y_dat.length) { | ||
@@ -127,6 +124,3 @@ console.log('lm.m error: the length of t must equal the length of y_dat'); | ||
| //plotcmd='figure(11); plot(t(:,1),y_dat,''og'',t(:,1),y_hat,''-b''); axis tight; drawnow '; | ||
| //p_min=p_min(:); p_max=p_max(:); // make column vectors | ||
| if(!dp.length || dp.length == 1){ | ||
@@ -133,0 +127,0 @@ var dp_array = new Array(Npar); |
New alerts
License Policy Violation
LicenseThis package is not allowed per your license policy. Review the package's license to ensure compliance.
Found 1 instance in 1 package
Fixed alerts
License Policy Violation
LicenseThis package is not allowed per your license policy. Review the package's license to ensure compliance.
Found 1 instance in 1 package
Improved metrics
- Total package byte prevSize
- increased by0.97%
53889
- Number of package files
- increased by9.09%
12
Worsened metrics
- Lines of code
- decreased by-0.65%
923
- Number of lines in readme file
- decreased by-71.28%
27
No dependency changes