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]: