# samples, comp_cfg = dt.open_sampled('2017-08-04_14:46:29.npy', mode='simulation')
# pc = PlatformCoordinates()
task = 'acquire'
if task is 'acquire':
image_dict = dict()
save_yaml_metadata(out_file, cfg)
for index, theta, shift, acqpars in iterator:
image_dict[(theta, phi)] = client.acquire(theta, phi, power)
np.save(out_file, image_dict)
elif task is 'reconstruct':
start_time = time.time()
rec, phase = fpm_reconstruct(samples=samples, backgrounds=None, it=iterator,
init_point=[0, 0], cfg=comp_cfg, debug=True)
print('--- %s seconds ---' % (time.time() - start_time))
plt.imshow(rec), plt.gray()
plt.show()
if task is 'test_and_measure':
image_dict = np.load(out_file)
for index, theta, phi, power in iterator:
if phi == 20 or phi == 40:
im_array = image_dict[()][(theta, phi)]
intensity = np.mean(im_array)
print('int: %f, theta: %d, phi: %d' % (intensity, theta, phi))
ax = plt.gca() or plt
ax.imshow(im_array, cmap=plt.get_cmap('gray'))
ax.get_figure().canvas.draw()
plt.show(block=False)
from pyfpm import web
from pyfpm.reconstruct import fpm_reconstruct
from pyfpm.fpmmath import set_iterator
from pyfpm.data import save_yaml_metadata
import pyfpm.data as dt
from pyfpm.coordinates import PlatformCoordinates
# Simulation parameters
cfg = dt.load_config()
samples, comp_cfg = dt.open_sampled('2017-05-26_152307.npy')
background, comp_cfg = dt.open_sampled('2017-05-26_145449_blank.npy')
# Connect to a web client running serve_microscope.py
pc = PlatformCoordinates(theta=0, phi=0, height=cfg.sample_height, cfg=cfg)
pc.generate_model(cfg.plat_model)
iterator = set_iterator(cfg)
# reconstruction
dx = cfg.patch_size[0]
x_range = range(0, cfg.video_size[1], dx)[:-1]
y_range = range(0, cfg.video_size[0], dx)[:-1]
# for i, point in enumerate(it.product(x_range, y_range)):
# init_point = [point[0], point[1]]
# rec, phase = fpm_reconstruct(samples, background, iterator, init_point,
# cfg=cfg, debug=False)
# misc.imsave('./misc/ph'+str(i)+'.png', phase)
# misc.imsave('./misc/im'+str(i)+'.png', rec)
rec, phase = fpm_reconstruct(samples, background, iterator, [90, 80],
cfg=comp_cfg, debug=True)
plt.show()
img = client.acquire(theta_plat, phi_plat, shift, power)
im_array = misc.imread(StringIO(img.read()), 'RGB')
image_dict[(theta, phi)] = im_array
ax = plt.gca() or plt
ax.imshow(im_array)
ax.get_figure().canvas.draw()
plt.show(block=False)
print(out_file)
np.save(out_file, image_dict)
client.acquire(0, cfg.servo_init, 0)
elif task is 'reconstruct':
print("here", cfg.video_size)
start_time = time.time()
rec = fpm_reconstruct(in_file, iterator, cfg=cfg, debug=True)
print('--- %s seconds ---' % (time.time() - start_time))
plt.imshow(rec), plt.gray()
plt.show()
if task is 'complete_scan':
print(task)
json_savemeta(json_file, image_size, pupil_radius, theta_max, phi_max)
client.complete_scan(color)
if task is 'test_and_measure':
fig, ax = plt.subplots(1, 1, figsize=(25, 15))
im1 = ax.imshow(np.ones((480, 640)), cmap=plt.get_cmap('hot'))
fig.show()
while 1:
img = client.get_camera_picture()