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Computing FWHM of PSF using 2D Gaussian fit
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| # Compute FWHM(x,y) using 2D Gaussian fit, min-square optimization | |
| # Optimization fits 2D gaussian: center, sigmas, baseline and amplitude | |
| # works best if there is only one blob and it is close to the image center. | |
| # author: Nikita Vladimirov @nvladimus (2018). | |
| # based on code example: https://stackoverflow.com/questions/21566379/fitting-a-2d-gaussian-function-using-scipy-optimize-curve-fit-valueerror-and-m | |
| import numpy as np | |
| import scipy.optimize as opt | |
| def twoD_GaussianScaledAmp((x, y), xo, yo, sigma_x, sigma_y, amplitude, offset): | |
| """Function to fit, returns 2D gaussian function as 1D array""" | |
| xo = float(xo) | |
| yo = float(yo) | |
| g = offset + amplitude*np.exp( - (((x-xo)**2)/(2*sigma_x**2) + ((y-yo)**2)/(2*sigma_y**2))) | |
| return g.ravel() | |
| def getFWHM_GaussianFitScaledAmp(img): | |
| """Get FWHM(x,y) of a blob by 2D gaussian fitting | |
| Parameter: | |
| img - image as numpy array | |
| Returns: | |
| FWHMs in pixels, along x and y axes. | |
| """ | |
| x = np.linspace(0, img.shape[1], img.shape[1]) | |
| y = np.linspace(0, img.shape[0], img.shape[0]) | |
| x, y = np.meshgrid(x, y) | |
| #Parameters: xpos, ypos, sigmaX, sigmaY, amp, baseline | |
| initial_guess = (img.shape[1]/2,img.shape[0]/2,10,10,1,0) | |
| # subtract background and rescale image into [0,1], with floor clipping | |
| bg = np.percentile(img,5) | |
| img_scaled = np.clip((img - bg) / (img.max() - bg),0,1) | |
| popt, pcov = opt.curve_fit(twoD_GaussianScaledAmp, (x, y), | |
| img_scaled.ravel(), p0=initial_guess, | |
| bounds = ((img.shape[1]*0.4, img.shape[0]*0.4, 1, 1, 0.5, -0.1), | |
| (img.shape[1]*0.6, img.shape[0]*0.6, img.shape[1]/2, img.shape[0]/2, 1.5, 0.5))) | |
| xcenter, ycenter, sigmaX, sigmaY, amp, offset = popt[0], popt[1], popt[2], popt[3], popt[4], popt[5] | |
| FWHM_x = np.abs(4*sigmaX*np.sqrt(-0.5*np.log(0.5))) | |
| FWHM_y = np.abs(4*sigmaY*np.sqrt(-0.5*np.log(0.5))) | |
| return (FWHM_x, FWHM_y) | |
| #calling example: img is your image | |
| (FWHM_x, FWHM_y) = getFWHM_GaussianFitScaledAmp(img) |
what is opt?
That's the alias of the scipy.optimize module!
There will be ValueError if the image has nan
Worked perfectly for me. Thanks.
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what is opt?