smart_arrays_lmfit 2.0.4

Smart Arrays LM (Levenberg-Marquart) Fit #

What the package can do for you #

The purpose of this package is to fit "experimental data" to a "fit function" representing a model for the experimental data. These must be specified as an array of x values and an an array of the respective y values.

This curve fitter is using the Levenberg-Marquardt algorithm. The Dart implementation here was derived from https://github.com/reptillicus/jsfit.

The major API functionalities #

  • Available in the class LMfit.
  • Usage:
    1. call constructor
    2. call fit() or lmfit() ( = async version of fit())

Detailed API #

Please view the detailed API documentation in the API reference of this package (sidebar at the right of this page).

smart_arrays_base: Basic functions for 1D and 2D arrays

smart_arrays_numerics: Numerics with 1D and 2D arrays

smart_arrays_compress: Compress 1D and 2D arrays to a smaller size.

smart_arrays_dbstore: Store 1D and 2D arrays along with metadata on the local device.

smart_arrays_peaks: Detect peaks in 1D and 2D arrays.

smart_lorentz-gauss: Compute Lorentz-Gauss (pseudo-Voigt) line shapes.

smart_signal_processing: Fourier transform and more.

smart_dialogs: Easy-to-use dialogs in Web applications

Smart Arrays LM fit #

Version history #

2.0.0 - 2019-04-02 First version available on pub site

2.0.1 - 2019-04-04 Doc updates.

2.0.2 - 2019-04-13 Doc updates.

2.0.4 - 2019-05-06 Doc updates.

example/example.dart

// Copyright (c) 2019, Dr. Bruno Guigas. All rights reserved. Use of this source
// code is governed by a BSD-style license that can be found in the LICENSE file.
import 'package:smart_arrays_lmfit/smart_arrays_lmfit.dart';
import 'dart:math' as math;

/// Demonstrates fitting data to a Gaussian.
main() async {
  // Define the "fit model" to which a data array should be fitted: a Gaussian
  double fitFunctionGAUSS(double x, List<double> params) {
    // amplitude, center, width, y offset:
    double a = params[0], c = params[1], w = params[2], y0 = params[3];
    final FGAUSS = 4 * math.log(2); // normalization constant
    return y0 + a * math.exp(-FGAUSS * ((x - c) / w) * ((x - c) / w));
  }

  // Compute "experimental data" to be fitted to a Gaussian:
  // We compute an exact Gaussian, then add some random noise to it.
  final int NPOINTS = 50;
  double a = 100, c = 25, w = 10, y0 = 20;
  final List<double> GAUSS_PARS = [a, c, w, y0];
  List<double> xvals = List(NPOINTS), yvals = List(NPOINTS);
  math.Random rand = math.Random();
  for (int i = 0; i < NPOINTS; i++) {
    double x = i.toDouble();
    xvals[i] = x;
    yvals[i] = fitFunctionGAUSS(x, GAUSS_PARS);
    double noise = (2 * rand.nextDouble() - 1.0) * yvals[i] * 0.005;
    yvals[i] += noise;
  }

  // initial parameters for the fit, derived from the exact parameters
  final List<double> INITIAL_PARS = [a * 0.8, c * 0.9, w * 1.2, y0];

  // use these fitting options
  Map<String, List<String>> fitOptions = {
    LMfit.FIT_OPT_TOLERANCE: ["1e-10"],
    LMfit.PARAM_DELTA_CONVERGE: ["0.0001"],
    LMfit.MAX_ITERATIONS: ["200"],
    LMfit.PAR_INFO: [null, null, null, "y0 fixed null null"]
  };

  // start fitting the "experimental data" to a Gaussian
  LMfit lm = LMfit();
  Map<String, List<String>> fitResult =
      await lm.lmfit(fitFunctionGAUSS, xvals, yvals, INITIAL_PARS, fitOptions);

  // print the fitting result
  print("exact Gaussian params=${GAUSS_PARS}");
  print("inital params=${fitResult[LMfit.INITIAL_PARAMS]}");
  print("fitted params=${fitResult[LMfit.PARAMS]}");
  print("iterations=${fitResult[LMfit.ITERATIONS][0]}");
  print("stop reason=${fitResult[LMfit.STOP_REASON][0]}");
  print("time [milliseconds]=${fitResult[LMfit.TIME][0]}");
  print("chi squared=${fitResult[LMfit.CHI2][0]}");
}

Use this package as a library

1. Depend on it

Add this to your package's pubspec.yaml file:


dependencies:
  smart_arrays_lmfit: ^2.0.4

2. Install it

You can install packages from the command line:

with pub:


$ pub get

with Flutter:


$ flutter pub get

Alternatively, your editor might support pub get or flutter pub get. Check the docs for your editor to learn more.

3. Import it

Now in your Dart code, you can use:


import 'package:smart_arrays_lmfit/smart_arrays_lmfit.dart';
  
Popularity:
Describes how popular the package is relative to other packages. [more]
0
Health:
Code health derived from static analysis. [more]
99
Maintenance:
Reflects how tidy and up-to-date the package is. [more]
90
Overall:
Weighted score of the above. [more]
48
Learn more about scoring.

We analyzed this package on Jul 22, 2019, and provided a score, details, and suggestions below. Analysis was completed with status completed using:

  • Dart: 2.4.0
  • pana: 0.12.19

Platforms

Detected platforms: Flutter, web, other

No platform restriction found in primary library package:smart_arrays_lmfit/smart_arrays_lmfit.dart.

Health suggestions

Fix lib/src/lmfit.dart. (-1.49 points)

Analysis of lib/src/lmfit.dart reported 3 hints:

line 604 col 9: DO use curly braces for all flow control structures.

line 608 col 9: DO use curly braces for all flow control structures.

line 620 col 9: DO use curly braces for all flow control structures.

Maintenance issues and suggestions

Support latest dependencies. (-10 points)

The version constraint in pubspec.yaml does not support the latest published versions for 1 dependency (build_web_compilers).

Dependencies

Package Constraint Resolved Available
Direct dependencies
Dart SDK >=2.1.0 <3.0.0
build_runner ^1.1.2 1.6.1
build_web_compilers ^1.0.0 1.2.2 2.1.4
pedantic ^1.5.0 1.8.0+1
smart_arrays_numerics ^2.0.0 2.0.3
Transitive dependencies
analyzer 0.35.4 0.37.0
archive 2.0.10
args 1.5.2
async 2.3.0
bazel_worker 0.1.21
build 1.1.5
build_config 0.4.0 0.4.1
build_daemon 1.1.0 2.0.0
build_modules 1.0.11 2.3.1
build_resolvers 1.0.6
build_runner_core 3.0.6
built_collection 4.2.2
built_value 6.7.0
charcode 1.1.2
code_builder 3.2.0
collection 1.14.11
convert 2.1.1
crypto 2.0.6
dart_style 1.2.4 1.2.9
fixnum 0.10.9
front_end 0.1.14 0.1.20
glob 1.1.7
graphs 0.2.0
http 0.12.0+2
http_multi_server 2.1.0
http_parser 3.1.3
io 0.3.3
js 0.6.1+1
json_annotation 2.4.0
kernel 0.3.14 0.3.20
logging 0.11.3+2
matcher 0.12.5
meta 1.1.7
mime 0.9.6+3
package_config 1.0.5
package_resolver 1.0.10
path 1.6.2
pool 1.4.0
protobuf 0.13.15
pub_semver 1.4.2
pubspec_parse 0.1.4
quiver 2.0.3
scratch_space 0.0.3+2
shelf 0.7.5
shelf_web_socket 0.2.3
source_maps 0.10.8
source_span 1.5.5
stack_trace 1.9.3
stream_channel 2.0.0
stream_transform 0.0.19
string_scanner 1.0.4
term_glyph 1.1.0
timing 0.1.1+1
typed_data 1.1.6
watcher 0.9.7+12
web_socket_channel 1.0.14
yaml 2.1.16

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