def test_dpc_end_to_end():
"""
Integrated test for DPC based on dpc_runner.
"""
start_point = [1, 0]
pixel_size = (55, 55)
focus_to_det = 1.46e6
scan_rows = 2
scan_cols = 2
scan_xstep = 0.1
scan_ystep = 0.1
energy = 19.5
roi = None
padding = 0
weighting = 1
bad_pixels = None
solver = 'Nelder-Mead'
img_size = (40, 40)
scale = True
negate = True
ref_image = np.ones(img_size)
image_sequence = np.ones((scan_rows * scan_cols, img_size[0], img_size[1]))
phi, a = dpc.dpc_runner(ref_image, image_sequence, start_point, pixel_size,
focus_to_det, scan_rows, scan_cols, scan_xstep,
scan_ystep, energy, padding, weighting, solver,
roi, bad_pixels, negate, scale)
assert_array_almost_equal(phi, np.zeros((scan_rows, scan_cols)))
assert_array_almost_equal(a, np.ones((scan_rows, scan_cols)))
def run():
# download to this folder
current_folder = os.sep.join(__file__.split(os.sep)[:-1])
dpc_demo_data_path = os.path.join(current_folder, 'SOFC')
if not os.path.exists(dpc_demo_data_path):
sofc_file = os.path.join(current_folder, 'SOFC.zip')
print('The required test data directory was not found.'
'\nDownloading the test data to %s' % dpc_demo_data_path)
# todo make this not print every fraction of a second
call(('wget https://www.dropbox.com/s/963c4ymfmbjg5dm/SOFC.zip -P %s' %
current_folder),
shell=True)
# unzip it into this directory
unzip(sofc_file)
# 1. Set parameters
start_point = [1, 0]
first_image = 1
pixel_size = (55, 55)
focus_to_det = 1.46e6
scan_xstep = 0.1
scan_ystep = 0.1
scan_rows = 121
scan_cols = 121
energy = 19.5
roi = None
padding = 0
weighting = 1.
bad_pixels = None
solver = 'Nelder-Mead'
images = ImageSequence(dpc_demo_data_path + "/*.tif")
img_size = images[0].shape
ref_image = np.ones(img_size)
scale = True
negate = True
print('running dpc')
# 2. Use dpc.dpc_runner
phase, amplitude = dpc.dpc_runner(
ref_image, images, start_point, pixel_size, focus_to_det, scan_rows,
scan_cols, scan_xstep, scan_ystep, energy, padding, weighting, solver,
roi, bad_pixels, negate, scale)
# 3. Save intermediate and final results
scipy.misc.imsave(os.path.join(current_folder, 'phase.jpg'), phase)
np.savetxt(os.path.join(current_folder, 'phase.txt'), phase)
scipy.misc.imsave(os.path.join(current_folder, 'amplitude.jpg'), amplitude)
np.savetxt(os.path.join(current_folder, 'amplitude.txt'), amplitude)
def run():
# download to this folder
current_folder = os.sep.join(__file__.split(os.sep)[:-1])
dpc_demo_data_path = os.path.join(current_folder, 'SOFC')
if not os.path.exists(dpc_demo_data_path):
sofc_file = os.path.join(current_folder, 'SOFC.zip')
print('The required test data directory was not found.'
'\nDownloading the test data to %s' % dpc_demo_data_path)
# todo make this not print every fraction of a second
call(('wget https://www.dropbox.com/s/963c4ymfmbjg5dm/SOFC.zip -P %s' %
current_folder),
shell=True)
# unzip it into this directory
unzip(sofc_file)
# 1. Set parameters
start_point = [1, 0]
first_image = 1
pixel_size = (55, 55)
focus_to_det = 1.46e6
scan_xstep = 0.1
scan_ystep = 0.1
scan_rows = 121
scan_cols = 121
energy = 19.5
roi = None
padding = 0
weighting = 1.
bad_pixels = None
solver = 'Nelder-Mead'
images = ImageSequence(dpc_demo_data_path + "/*.tif")
img_size = images[0].shape
ref_image = np.ones(img_size)
scale = True
negate = True
print('running dpc')
# 2. Use dpc.dpc_runner
phase, amplitude = dpc.dpc_runner(ref_image, images, start_point,
pixel_size, focus_to_det, scan_rows,
scan_cols, scan_xstep, scan_ystep,
energy, padding, weighting, solver, roi,
bad_pixels, negate, scale)
# 3. Save intermediate and final results
scipy.misc.imsave(os.path.join(current_folder, 'phase.jpg'), phase)
np.savetxt(os.path.join(current_folder, 'phase.txt'), phase)
scipy.misc.imsave(os.path.join(current_folder, 'amplitude.jpg'), amplitude)
np.savetxt(os.path.join(current_folder, 'amplitude.txt'), amplitude)
def run():
# download to this folder
current_folder = os.sep.join(__file__.split(os.sep)[:-1])
dpc_demo_data_path = os.path.join(current_folder, 'SOFC')
if not os.path.exists(dpc_demo_data_path):
zip_file_url = 'https://www.dropbox.com/s/963c4ymfmbjg5dm/SOFC.zip?dl=1'
import download
download.run()
# download_zip(zip_file_url, current_folder)
# 1. Set parameters
start_point = [1, 0]
first_image = 1
pixel_size = (55, 55)
focus_to_det = 1.46e6
scan_xstep = 0.1
scan_ystep = 0.1
scan_rows = 121
scan_cols = 121
energy = 19.5
roi = None
padding = 0
weighting = 1.
bad_pixels = None
solver = 'Nelder-Mead'
images = ImageSequence(dpc_demo_data_path + "/*.tif")
img_size = images[0].shape
ref_image = np.ones(img_size)
scale = True
negate = True
print('running dpc')
# 2. Use dpc.dpc_runner
phase, amplitude = dpc.dpc_runner(ref_image, images, start_point,
pixel_size, focus_to_det, scan_rows,
scan_cols, scan_xstep, scan_ystep,
energy, padding, weighting, solver, roi,
bad_pixels, negate, scale)
# 3. Save intermediate and final results
print('saving dpc output to disk in --> %s' % current_folder)
scipy.misc.imsave(os.path.join(current_folder, 'phase.jpg'), phase)
np.savetxt(os.path.join(current_folder, 'phase.txt'), phase)
scipy.misc.imsave(os.path.join(current_folder, 'amplitude.jpg'), amplitude)
np.savetxt(os.path.join(current_folder, 'amplitude.txt'), amplitude)
def run():
# download to this folder
current_folder = os.sep.join(__file__.split(os.sep)[:-1])
dpc_demo_data_path = os.path.join(current_folder, 'SOFC')
if not os.path.exists(dpc_demo_data_path):
zip_file_url = 'https://www.dropbox.com/s/963c4ymfmbjg5dm/SOFC.zip?dl=1'
import download
download.run()
# download_zip(zip_file_url, current_folder)
# 1. Set parameters
start_point = [1, 0]
first_image = 1
pixel_size = (55, 55)
focus_to_det = 1.46e6
scan_xstep = 0.1
scan_ystep = 0.1
scan_rows = 121
scan_cols = 121
energy = 19.5
roi = None
padding = 0
weighting = 1.
bad_pixels = None
solver = 'Nelder-Mead'
images = ImageSequence(dpc_demo_data_path + "/*.tif")
img_size = images[0].shape
ref_image = np.ones(img_size)
scale = True
negate = True
print('running dpc')
# 2. Use dpc.dpc_runner
phase, amplitude = dpc.dpc_runner(
ref_image, images, start_point, pixel_size, focus_to_det, scan_rows,
scan_cols, scan_xstep, scan_ystep, energy, padding, weighting, solver,
roi, bad_pixels, negate, scale)
# 3. Save intermediate and final results
print('saving dpc output to disk in --> %s' % current_folder)
scipy.misc.imsave(os.path.join(current_folder, 'phase.jpg'), phase)
np.savetxt(os.path.join(current_folder, 'phase.txt'), phase)
scipy.misc.imsave(os.path.join(current_folder, 'amplitude.jpg'), amplitude)
np.savetxt(os.path.join(current_folder, 'amplitude.txt'), amplitude)
