The Ezyfit toolbox for Matlab enables you to perform simple curve fitting of one-dimensional data using arbitrary (non linear) fitting functions.
EzyFit adds a new menu to your figure windows, which allows you to easily fit your data with predefined or user-defined fit equations, including selection of your data (outliers removing) using the ``Data Brushing'' tool (available since Matlab 7.6).
This toolbox also provides a set of command-line functions to perform curve fitting 'programmatically': you just have to type something like showfit('c+a/x^n') and EzyFit gives you the values for c, a and n and shows you the curve!
Visit http://www.fast.u-psud.fr/ezyfit/ for additional info.
Installation and system requirements
EzyFit needs Matlab 7.0 or higher. It has been tested under 7.0 to 7.14 (R2012a), but mainly under Windows. The command-line functions (e.g. ezfit, showfit...) work equally well on all systems. However graphical operations (e.g. showslope, getslope...) may not be fully stable, especially on non-Windows systems.
1. Download and unzip the EzyFit Toolbox in a directory somewhere in your system. For instance, in a Windows installation, the directory Documents/MATLAB/toolbox/ezyfit may be a good location. Do NOT install the toolbox in the Matlab directory itself (Program Files/Matlab directory in Windows). If you upgrade from an older version, first empty the previous directory.
2. From the menu 'File > Set Path', click on 'Add Folder' (NOT 'with subfolders') and select the ezyfit directory. Click on 'Save' and 'Close'.
3. Restart Matlab. From the Start button, select Toolboxes > EzyFit to check that the toolbox is correctly recognized by your system.
4. If you want to always have the Ezyfit menu in your figures, type efmenu install. This will create or update your 'startup.m' file in the main user directory of your Matlab installation.
Note: If you upgrade Matlab and you want to use your previous Ezyfit installation, you just have to follow the steps 2-4.
plotsample power % a power law
plotsample hist % an histogram
f = ezfit('gauss'); % fits with a Gaussian
f % displays the values of the coefficients