def processAndPlotEnergyCalibrationData(energyCalibrationData): x = energyCalibrationData['Peak'] x_err = energyCalibrationData['PeakErr'] y = energyCalibrationData['Energy'] y_err = energyCalibrationData['EnergyErr'] (fig, axes) = createEmptyPlottingArea(config.energy_x_axis_label, config.energy_y_axis_label, fontsize = config.fontsize, figWidth=config.plotwidth, figHeight=config.plotheight) axes.set_title(config.energytitle) addDataWithErrorBarsToPlot(axes, x, y, x_err=x_err, y_err=y_err, fmt=config.energyplotformat, label=config.energyplotlabel) axes.legend() fig.show() #find fit for energy calibration output = fitFunctionOdr(x, y, x_err, y_err, fitFunction=lineOdr, startingParameters=[0.2,10.0]) params = output.beta param_std_dev = output.sd_beta #seems to calculated this for us already print (params, param_std_dev) energyCalibrationFit = FitData(TestData(['Param','Value','Std Dev'], ['a','b'], params, param_std_dev), output.cov_beta, energyCalibrationData, 'Peak', residualVariance=output.res_var, inverseConditionNumber=output.inv_condnum, relativeError=output.rel_error, haltingReasons='\n'.join(output.stopreason)) (a,b) = params #fits for line fittedLine = fittedOdrFunction(lineOdr, params) addFunctionToPlot(axes, x, fittedLine, config.energyfitplotformat, label=config.energyfitplotlabel) axes.legend() fig.show() return energyCalibrationFit
def fitGaussianAndAddToPlotOdr(interval, xfield, x, y, x_err, y_err, startingGaussianParameters, max_iterations, fig, axes, nb_of_fits, config, label):
countSum = numpy.sum(y)
output = fitFunctionOdr(x, y, x_err, y_err, fitFunction=gaussianOdr, startingParameters=startingGaussianParameters)
params = output.beta
param_std_dev = output.sd_beta #seems to calculated this for us already
print 'Params: ', params, '\nParam Std Dev: ', param_std_dev
# (a,b,c) = params
# (err_a, err_b, err_c) = fit_errors
gaussParams = FitData(TestData(['Param','Value','Std Dev'], ['a','b','c'], params, param_std_dev), output.cov_beta, interval, xfield, residualVariance=output.res_var, inverseConditionNumber=output.inv_condnum, relativeError=output.rel_error, haltingReasons='\n'.join(output.stopreason))
# gaussParams = ({'a':a, 'b':b, 'c':c},variance_matrix,{'a':err_a, 'b':err_b, 'c':err_c},countSum)
fittedGaussian = fittedOdrFunction(gaussianOdr, params)
addFunctionToPlot(axes, x, fittedGaussian, fmt=config.gaussianfitformats[nb_of_fits%len(config.gaussianfitformats)], label=label)
axes.legend()
fig.show()
return (gaussParams, countSum)