from fiber_properties import gaussian_fit, gaussian_array, FiberImage, plot_overlaid_cross_sections import numpy as np import matplotlib.pyplot as plt # image = np.meshgrid(np.arange(100), np.arange(100)) # coeffs = np.random.normal(size=5) * 15 + 50 # print coeffs # image = gaussian_array(image, *coeffs).reshape(100,100).astype('float64') # image += np.random.normal(size=image.shape) # im_obj = FiberImage('../data/modal_noise/Kris_data/rectangular_100x300um/coupled_agitation/ff_corrected.fit') im_obj = FiberImage('../data/stability/2017-03-19 Stability Test/circular_200um/in_100.fit', camera='in') image = im_obj.get_image() center = im_obj.get_fiber_center() plt.figure(1) plt.imshow(image) # fit, output = gaussian_fit(image, full_output=True) # print output fit = im_obj.get_gaussian_fit() plt.figure(2) plt.imshow(fit) plot_overlaid_cross_sections(image, fit, center) plt.show()
ff_ambient = image_list(ambient_folder + 'ff_ambient_') nf_agitated = FiberImage(image_list(agitated_folder + 'nf_agitated_'), nf_dark, nf_ambient) nf_unagitated = FiberImage( image_list(unagitated_folder + 'nf_unagitated_'), nf_dark, nf_ambient) nf_baseline = FiberImage(nf_agitated.get_tophat_fit(), pixel_size=nf_agitated.get_pixel_size(), threshold=0.1, camera='nf') ff_agitated = FiberImage(image_list(agitated_folder + 'ff_agitated_'), ff_dark, ff_ambient) ff_unagitated = FiberImage( image_list(unagitated_folder + 'ff_unagitated_'), ff_dark, ff_ambient) ff_baseline = FiberImage(ff_agitated.get_gaussian_fit(), pixel_size=ff_agitated.get_pixel_size(), magnification=1, camera='ff') print modal_noise = [] for test in [nf_agitated, nf_unagitated, nf_baseline]: modal_noise.append( modal_noise(test, method='fft', output='array', radius_factor=1.0)) plot_fft([modal_noise[i][1] for i in xrange(3)], [modal_noise[i][0] for i in xrange(3)], labels=['Agitated laser', 'Unagitated laser', 'Baseline'], title='NF Modal Noise Comparison (600um Fiber)')
from fiber_properties import gaussian_fit, gaussian_array, FiberImage, plot_overlaid_cross_sections import numpy as np import matplotlib.pyplot as plt # image = np.meshgrid(np.arange(100), np.arange(100)) # coeffs = np.random.normal(size=5) * 15 + 50 # print coeffs # image = gaussian_array(image, *coeffs).reshape(100,100).astype('float64') # image += np.random.normal(size=image.shape) # im_obj = FiberImage('../data/modal_noise/Kris_data/rectangular_100x300um/coupled_agitation/ff_corrected.fit') im_obj = FiberImage( '../data/stability/2017-03-19 Stability Test/circular_200um/in_100.fit', camera='in') image = im_obj.get_image() center = im_obj.get_fiber_center() plt.figure(1) plt.imshow(image) # fit, output = gaussian_fit(image, full_output=True) # print output fit = im_obj.get_gaussian_fit() plt.figure(2) plt.imshow(fit) plot_overlaid_cross_sections(image, fit, center) plt.show()
ff_dark = image_list(dark_folder + 'ff_dark_') ff_ambient = image_list(ambient_folder + 'ff_ambient_') nf_agitated = FiberImage(image_list(agitated_folder + 'nf_agitated_'), nf_dark, nf_ambient) nf_unagitated = FiberImage(image_list(unagitated_folder + 'nf_unagitated_'), nf_dark, nf_ambient) nf_baseline = FiberImage(nf_agitated.get_tophat_fit(), pixel_size=nf_agitated.get_pixel_size(), threshold=0.1, camera='nf') ff_agitated = FiberImage(image_list(agitated_folder + 'ff_agitated_'), ff_dark, ff_ambient) ff_unagitated = FiberImage(image_list(unagitated_folder + 'ff_unagitated_'), ff_dark, ff_ambient) ff_baseline = FiberImage(ff_agitated.get_gaussian_fit(), pixel_size=ff_agitated.get_pixel_size(), magnification=1, camera='ff') print() modal_noise = [] for test in [nf_agitated, nf_unagitated, nf_baseline]: modal_noise.append(modal_noise(test, method='fft', output='array', radius_factor=1.0)) plot_fft([modal_noise[i][1] for i in xrange(3)], [modal_noise[i][0] for i in xrange(3)], labels=['Agitated laser', 'Unagitated laser', 'Baseline'], title='NF Modal Noise Comparison (600um Fiber)') modal_noise = [] for test in [ff_agitated, ff_unagitated, ff_baseline]: