interactive-curve-fit 0.0.1

interactive_curve_fit: A Python project enables you to do curve fitting on spectrum data interactively on GUI. You can visualize your spectrum and fit the optional number of peaks on GUI using Scipy.optimize.curve_fit method.

interactive_curve_fit

A Python project enables you to do curve fitting on spectrum data interactively on GUI. You can visualize your spectrum and fit the optional number of peaks on GUI using Scipy.optimize.curve_fit method.

How to use?

Try tutorial.py with your spectrum data!

Spectrum data format must be like the table below

x	y
0	1
1	13
2	30
3	43
4	31
5	11
...	...

Steps to curve-fit

1. Teach your initial guess of the positions of each peaks roughly to Fitter.

   from interactive_curve_fit import read_data, Guessor, Fitter
   
   data = read_data(data, headers=2, sep=',')
   guessor = Guessor(data, background=10, method='drag')
   guess = guessor.guess()
   

   Initial Guess method

   • mouse-dragging (wrap up peak area by mouse-dragging)
   • click (click the top and the both edges of each peaks)

   Screenshot

   

2. Give your spectrum data and your guess to Fitter.

   fitter = Fitter(data, guess)
   fitter.run(method='gaussian')
   

   Supported fitting functions

   • gaussian function
   • polynomial function

   Output information includes

   • position (x, y) of each peaks
   • baseline height of the spectrum
   • bandwidth of each peaks with its CI (confidential interval)

3. Save the fitting results

   fitter.save_data('out/fitting_result.csv')
   

4. Other features

   bmp_to_csv converts bmp file to csv file.

   from interactive_curve_fit import bmg_to_csv
   bmp_to_csv('data/line_spectrum.bmp')
   data = read_data('data/line_spectrum.csv')
   

   Fitter can visualize fitting results

   fitter.plot_fit()
   

   Fitter can also display fitting results on terminal

   fitter.display_results_terminal(ci=2)
   

Supported supectrum file format

• ascii file(.asc .csv .txt etc..)

• bmp image(.bmp .jpg .png .jpeg etc..)

  excel sheet files, table of html are planed to be suported in the near future.

Features that are planned to be supported!

• baseline correlation
• other fitting functions (e.g. binomical distribution function)
• automated guessor method using wavelet transform and CNN