def fitwin(x,y):
    def fit(x, params):
        a, b, c, d = params
        O1 = 0.9295 #principal lunar
        M2 = 1.9324 #principal lunar
        return a * (numpy.cos(2*pi*O1*x + b)) + c * (numpy.cos(2*pi*M2*x + d))

    a = FitParam("O1 Amp", 0., -10., 10.)
    b = FitParam("O1 Shift", 0., -10., 10.,logscale="True")
    c = FitParam("M2 Amp", 0., -10., 10.)
    d = FitParam("M2 Shift", 0., -10., 10.,logscale="True")
    params = [a, b, c, d]
    values = guifit(x, y, fit, params, xlabel="Time (s)", ylabel="amplitude (ft)")
    return values
예제 #2
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파일: fit.py 프로젝트: zgpglee/guiqwt
def test():
    x = np.linspace(-10, 10, 1000)
    y = np.cos(1.5*x)+np.random.rand(x.shape[0])*.2
    
    def fit(x, params):
        a, b = params
        return np.cos(b*x)+a
    
    a = FitParam("Offset", 1., 0., 2.)
    b = FitParam("Frequency", 2., 1., 10., logscale=True)
    params = [a, b]
    values = guifit(x, y, fit, params, xlabel="Time (s)", ylabel="Power (a.u.)")
    
    print(values)
    print([param.value for param in params])
예제 #3
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def gaussfit(x,y):
    if not isinstance(x,np.ndarray):
        x=np.array(x)
        y=np.array(y)
    from guiqwt.widgets.fit import FitParam, guifit
    def fit(x, params):
        A, mu, FWHM,b = params
        return A*np.exp(-4*math.log(2)*np.power((x-mu),2)/math.pow(FWHM,2))+b
        
    
    A = FitParam("Amplitude", y.max(), 0., y.max())
    mu = FitParam("mu", x[len(x)/2], x[0], x[-1])
    FWHM = FitParam("FWHM", (x.max()-x.min())/4, 0., x.max()-x.min())
    b = FitParam("Offset", 0, 0., y.max())
    params = [A, mu, FWHM,b]
    values = guifit(x, y, fit, params, xlabel="Time (s)", ylabel="Power (a.u.)",auto_fit=True)    
    return(values)
def fitwin(x, y):
    def fit(x, params):
        a, b, c, d = params
        O1 = 0.9295  #principal lunar
        M2 = 1.9324  #principal lunar
        return a * (numpy.cos(2 * pi * O1 * x +
                              b)) + c * (numpy.cos(2 * pi * M2 * x + d))

    a = FitParam("O1 Amp", 0., -10., 10.)
    b = FitParam("O1 Shift", 0., -10., 10., logscale="True")
    c = FitParam("M2 Amp", 0., -10., 10.)
    d = FitParam("M2 Shift", 0., -10., 10., logscale="True")
    params = [a, b, c, d]
    values = guifit(x,
                    y,
                    fit,
                    params,
                    xlabel="Time (s)",
                    ylabel="amplitude (ft)")
    return values
예제 #5
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def gaussfit(x, y):
    if not isinstance(x, np.ndarray):
        x = np.array(x)
        y = np.array(y)
    from guiqwt.widgets.fit import FitParam, guifit

    def fit(x, params):
        A, mu, FWHM, b = params
        return A * np.exp(-4 * math.log(2) * np.power(
            (x - mu), 2) / math.pow(FWHM, 2)) + b

    A = FitParam("Amplitude", y.max(), 0., y.max())
    mu = FitParam("mu", x[len(x) / 2], x[0], x[-1])
    FWHM = FitParam("FWHM", (x.max() - x.min()) / 4, 0., x.max() - x.min())
    b = FitParam("Offset", 0, 0., y.max())
    params = [A, mu, FWHM, b]
    values = guifit(x,
                    y,
                    fit,
                    params,
                    xlabel="Time (s)",
                    ylabel="Power (a.u.)",
                    auto_fit=True)
    return (values)
예제 #6
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 def graphicalfit(self):
     #SHOW = True # Show test in GUI-based test launcher
     x=self.x()
     y=self.y()
     
     def fitfn(x, params):
         #ignore the x
         for index, key in enumerate(self.fit_params):
             self.fit_params[key] = float(params[index])
             res = self.fn(**self.getparams())  
             if len(x)!=len(self.x()):
                 s = pandas.Series(res, index=self.x())
                 res = s[x].values   
         return res
     
     self.graphical_params=list()
     for index, key in enumerate(self.fit_params):
             fp=FitParam(key, self.fit_params[key],0.001*abs(self.fit_params[key]),10.0*abs(self.fit_params[key]),logscale=False,steps=2000,format='%.8f')
             self.graphical_params.append(fp)
     values = guifit(x, y, fitfn, self.graphical_params, xlabel="x-axis", ylabel="y-axis")
     if values is None:
         self.gfit_concluded = False
     else:
         self.gfit_concluded = True
         
     self.comment("Graphical fit finished with the following values: ")        
     self.comment(values)
     self.comment([param.value for param in self.graphical_params])
     self.sqerror = self.getsqerror() 
     self.comment("Fit completed with sqerror = " + str(self.sqerror))
     self.comment("Obtained parameter values: ")
     self.comment(dict(self.getparams()))
     # evaluate the performed fit in fitdata
     self.fitdata = pandas.Series(data = self.fn(**self.getparams()), index = self.x(), \
                         name = 'fitfunction: '+ self.func)    
     return values
예제 #7
0
파일: guifit.py 프로젝트: mivade/guifit
    interactive = InteractiveFitSettings()
    if not interactive.edit(size=(640, 1)):
        sys.exit(0)
    else:
        config['file'] = interactive.filename
        config['function'] = interactive.funcname
        config['xcol'] = interactive.xcol
        config['ycol'] = interactive.ycol
        config['skiprows'] = interactive.skiprows
        with open(config_file, 'w') as f:
            pickle.dump(config, f)

    # Open data file
    name, extension = os.path.splitext(interactive.filename)
    if extension == 'csv':
        delimiter = ','
    else:
        delimiter = None
    xdata, ydata = np.loadtxt(
        interactive.filename, delimiter=delimiter,
        usecols=(interactive.xcol, interactive.ycol),
        unpack=True, skiprows=interactive.skiprows
    )

    # Fit
    #x = np.linspace(-10, 10, 1000)
    #y = np.cos(1.5*x) + np.random.rand(x.shape[0])*.2
    #func = Sine(x, y)
    func = getattr(sys.modules[__name__], interactive.funcname)(xdata, ydata)
    values = guifit(func.xdata, func.ydata, func.func, func.params)