Non-Linear CURVE FITTING using PYTHON

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  • čas přidán 18. 08. 2019
  • A tutorial on how to perform a non-linear curve fitting of data-points to any arbitrary function with multiple fitting parameters.
    I use the script package and the script.optimize.curve_fit function to perform an exponential fitting of data-points.
    Documentation:
    docs.scipy.org/doc/scipy/refe...
    Code shown in the video:
    www.bragitoff.com/2019/08/non...
    Hope you find it useful!
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Komentáře • 64

  • @msm932
    @msm932 Před 3 lety +14

    I saw at least five tutorials by now, asked three questions on stack-overflow cause that stuff never worked with my function. And finally I found a fellow scientist who gives this marvellous tutorial on curve fitting. Thank you a thousand times, it works!

  • @diegolovato5832
    @diegolovato5832 Před 4 lety +5

    Bless your soul, this was excellent. I was able to find non-linear relationships between temperature and electrical load of a city, for electricity load forecasting. THANK YOU!

    • @PhysWhiz
      @PhysWhiz  Před 4 lety +1

      I'm glad you found it useful 😊

    • @kamleshrathor1866
      @kamleshrathor1866 Před rokem

      How do you decide the best initial guess I also want to find a relationship between droplet diameter and height, but the r2 value is around 0.48 so how can I improve thank you

  • @cryfier
    @cryfier Před 2 lety +1

    Dude your a god that was so well explained! Love you!

  • @candelariohg
    @candelariohg Před rokem

    Thank you very much, friend, I've been suffering for two days what you can't imagine to achieve something like this.

  • @Magnuomoliticus
    @Magnuomoliticus Před 3 lety +7

    Thank you very much! I hope I can help any viewer with this other tips.
    # In this example, if you want to know the errors of the fitting parameters "a" and "b" you can add this line to your code:
    a, b = np.sqrt(np.diag(pcov))
    # If you want to know the r^2 score of the fit, use this lines in your code:
    from sklearn.metrics import r2_score
    r2 = r2_score(yData, func(xData, *popt))
    I wish you the best of lucks!

  • @mohammadkazemi8854
    @mohammadkazemi8854 Před 4 lety +3

    Thanks for this nice tutorial. I have a question. How can I calculate the r2 (r-squared) of the curve fit? Is there any way to convert the pcov to r2? THANKS!

  • @fernandozeledonmunoz6525
    @fernandozeledonmunoz6525 Před 4 lety +2

    Is it possible to choose the size of the y-axis? I mean, my experimental y values are very little and i want the graph only to show them in comparision with the curve fitting ...

  • @mandarbopardikar9135
    @mandarbopardikar9135 Před 3 lety

    Awesome!! This helped me a lot.

  • @Gustavo_0107
    @Gustavo_0107 Před 2 lety

    Thank you for the video! I have one question, how do I determine the uncertainty of the coefficients generated by the curvefit?

  • @Alex-oh1wt
    @Alex-oh1wt Před 2 lety

    what an absolute legend

  • @WizToma
    @WizToma Před 2 lety

    absolute hero so much better than online forums/documentation explenations

  • @asherjablon9598
    @asherjablon9598 Před 4 lety +2

    How do you find the R squared value?

  • @sunday-thequant8477
    @sunday-thequant8477 Před 3 lety

    Thanks man! Very simple code.

  • @aaronlopes5256
    @aaronlopes5256 Před 3 lety

    Thank you...simple and effective

  • @ahmedroumi2512
    @ahmedroumi2512 Před 3 lety

    How can we compute the area under curve ( for exemple for an asymetric gaussian )

  • @addons01
    @addons01 Před 3 lety

    I have a question, how can you predict using the curve_fitted function for a specific value but no array, which isn't part of the dataframe? Let's say the x value is 6 and a prediction for this number is needed.

  • @idirhouari3878
    @idirhouari3878 Před 4 lety +1

    Thanks for the help :))

  • @NovaWarrior77
    @NovaWarrior77 Před 3 lety

    THANK YOU SO MUCH!!

  • @sksahil4374
    @sksahil4374 Před 5 lety +2

    how to get error ...??

  • @MrGreen_N
    @MrGreen_N Před 3 lety

    Well done, thank you

  • @Alpharabius99
    @Alpharabius99 Před 3 lety

    How can we get the equation for curve?

  • @Samphysicsguy
    @Samphysicsguy Před 2 lety

    U saved my life

  • @ahmedhass146
    @ahmedhass146 Před rokem

    thx sir
    that was helpful :)

  • @MM-vw1ck
    @MM-vw1ck Před 3 lety

    I have this problem, where the data I'm trying to fit is not of polynomial/exponential form.

  • @Anuraag-oh5eb
    @Anuraag-oh5eb Před 3 lety +5

    lovely content! thank you. but your plot .. talk about overfitting the data :D :D :D

  • @UddhikaIshara
    @UddhikaIshara Před 2 lety

    i got error saying " ImportError: cannot import name 'read_arguments' from partially initialized module 'popt' " could you please help?

  • @sheetanshudeepak8779
    @sheetanshudeepak8779 Před 3 lety +1

    sir kindly make video on improve the goodness(reduce SSE) of fitting curve, thank you

  • @oxydol3456
    @oxydol3456 Před 3 lety

    interesting topic. thanks.

  • @grenliquid6513
    @grenliquid6513 Před 2 lety

    Can u do a curve fit with more than one curve, example u have 2 function/model with same parameter and u want to fit those curves with 2datas u have of that function respectively, maybe u can weight the residual of the curves?

  • @JpmestraoPSN
    @JpmestraoPSN Před 4 lety

    thanks

  • @juandiegobohorquez8238

    Do you know if it is possible to use scipy functions instead of defining the fitting function yourself? That is, for example, if I want to make a fit my data with lognormal or power law equation, do I have to write it explicitly and change the parameters for each?

    • @PhysWhiz
      @PhysWhiz  Před 3 lety +2

      This is the most automatic it can get if you want to do meaningful science. We only need to define a fitting function here which we do so by considering the type of problem we are considering.

  • @sheetanshudeepak8779
    @sheetanshudeepak8779 Před 3 lety

    thanks sir

  • @HS-ii9dj
    @HS-ii9dj Před 4 lety

    can I still use curve_fit if I have errors in x but not in y?

    • @PhysWhiz
      @PhysWhiz  Před 4 lety

      Good question. curve_fit may not be the best choice in such a case. You may wanna try odr from scipy.

  • @shahinsharafi5062
    @shahinsharafi5062 Před 3 lety

    I tried to do same code, however python did not sketch the curve for me !

  • @guerreirodaluzgmailcom
    @guerreirodaluzgmailcom Před 4 lety +2

    hi Mr., How do I know which initial values to consider for the initial conjecture of the parameters?
    I will be grateful for the answer

    • @PhysWhiz
      @PhysWhiz  Před 4 lety +2

      Just an educated guess is usually enough. If you're modelling something you might have an idea about what to expect. In some cases even bad initial guesses may converge. If not then just try another one randomly if you have no odea about what to expect.

    • @IvCastilla
      @IvCastilla Před 2 lety

      Each problem has a method to get initial values. In Process Simulation you must know where do you com from and what do you espect. There no exists a general method o mathematics for the initial value. Cheers

  • @HS-ii9dj
    @HS-ii9dj Před 4 lety +1

    Hi, would you be able to help me I'm trying to fit a curve_fit through my data but it's not working?

    • @PhysWhiz
      @PhysWhiz  Před 4 lety

      Is the code running? Since the curve_fit method requires an initial guess, so that may be the reason if the optimization doesn't converge. You can try different values for initial guess.

    • @HS-ii9dj
      @HS-ii9dj Před 4 lety

      The code does run and give a straight line , I have guessed the slope and intercept do I also need a start_slope and start_intercept?

    • @PhysWhiz
      @PhysWhiz  Před 4 lety

      You want to do a linear fit?

    • @HS-ii9dj
      @HS-ii9dj Před 4 lety

      yeah a linear one , shall i send you my code?

    • @PhysWhiz
      @PhysWhiz  Před 4 lety

      Although the video is for non-linear fitting, you can still do linear fitting by modifying the func as:
      def func(x,m,c):
      return m*x+c

  • @BlueSkyGoldSun
    @BlueSkyGoldSun Před 2 lety

    Can we do this on real dataset?

    • @PhysWhiz
      @PhysWhiz  Před 2 lety

      It depends on the amount of noise that your data might have. Also, if you have an idea about the what mathematical relationship should it follow.

  • @tawhidpranto3862
    @tawhidpranto3862 Před 3 lety +1

    Thank you so much for explaining in details. Can you explain why you wrote a=%5.3f, b=%5.3f in line 28 of your code?

    • @PhysWhiz
      @PhysWhiz  Před 3 lety

      It means it will print a floating point number with 5 characters, with 3 digits after the decimal point. It is just for formatting the output.

  • @arslan809
    @arslan809 Před 4 lety

    bhai tu gora nhe hy pr koshish poori kr rha hy k wsa boly mgr nhee
    You know, You know kam bola kr

  • @kartikanand6348
    @kartikanand6348 Před 4 lety

    I would prefer you to speak in your original accent, please