def main(overide={}):
# get command line args and config
sc = 'make_reference'
# search the current directory for *.ini files if not present in cxi directory
config_dirs = [os.path.split(os.path.abspath(__file__))[0]]
# extract the first paragraph from the doc string
des = st.make_object_map.__doc__.split('\n\n')[0]
# now load the necessary data
args, params = cmdline_config_cxi_reader.get_all(sc,
des,
config_dirs=config_dirs,
roi=True)
params = params['make_reference']
# overide with input params (if any)
params.update(overide)
O, n0, m0 = st.make_object_map(
params['data'].astype(params['whitefield'].dtype), params['mask'],
params['whitefield'], params['pixel_translations'],
params['pixel_map'], params['ls'])
out = {'reference_image': O, 'n0': n0, 'm0': m0}
cmdline_config_cxi_reader.write_all(params,
args.filename,
out,
apply_roi=True)
# output display for gui
with open('.log', 'w') as f:
print('display: ' + params['h5_group'] + '/reference_image', file=f)
def defocus_sweep(z1_min, z1_max, N, z, data, mask, whitefield, basis,
x_pixel_size, y_pixel_size, translations, ls):
"""
Sweep over possible defocus values
"""
z1s = np.linspace(z1_min, z1_max, N)
Os = []
it = tqdm.trange(z1s.shape[0], desc='sweeping defocus')
for i in it:
z1 = z1s[i]
# generate pixel mapping
pixel_map, pixel_translations, res = st.generate_pixel_map(
mask.shape,
translations,
basis,
x_pixel_size,
y_pixel_size,
z,
z1,
None,
None,
None,
verbose=False)
# generate reference image
I0 = st.make_object_map(data.astype(whitefield.dtype), mask,
whitefield, pixel_translations, pixel_map,
ls)[0]
Os.append(np.mean(gaussian_gradient_magnitude(I0, sigma=ls)**2))
z1 = z1s[np.argmax(Os)]
return np.array(Os), z1
def defocus_sweep(z1_min, z1_max, N, z, roi, data, mask, whitefield, basis,
x_pixel_size, y_pixel_size, translations):
"""
Sweep over possible defocus values
"""
z1s = np.linspace(z1_min, z1_max, N)
Os = []
it = tqdm.trange(z1s.shape[0], desc='sweeping defocus')
for i in it:
z1 = z1s[i]
# generate pixel mapping
pixel_map, pixel_translations, res = st.generate_pixel_map(
mask.shape,
translations,
basis,
x_pixel_size,
y_pixel_size,
z,
z1,
None,
None,
None,
verbose=False)
# generate reference image
Iref, m0, n0 = st.make_object_map(data,
mask,
whitefield,
pixel_translations,
pixel_map,
roi=None,
subpixel=False,
verbose=False,
minimum_overlap=None,
sig=None)
Os.append(np.squeeze(Iref).copy()[:10000])
# make an array with all Os
s = max([o.shape[0] for o in Os])
Os_ar = np.zeros((len(z1s), s), dtype=np.float)
for i, o in enumerate(Os):
Os_ar[i, :o.shape[0]] = o
# find the z1 value with the greatest variance
vs = []
for o in Os_ar:
vs.append(np.var(o[o > 0]))
i = np.argmax(vs)
z1 = z1s[i]
print('i, optimum', i, z1)
return np.squeeze(Os_ar), z1
def main(overide={}):
# get command line args and config
sc = 'make_pixel_map_poly'
# search the current directory for *.ini files if not present in cxi directory
config_dirs = [os.path.split(os.path.abspath(__file__))[0]]
# extract the first paragraph from the doc string
#des = st.generate_pixel_map.__doc__.split('\n\n')[0]
des = ""
# now load the necessary data
args, params = cmdline_config_cxi_reader.get_all(sc,
des,
config_dirs=config_dirs,
roi=True)
params = params[sc]
# overide with input params (if any)
params.update(overide)
# evaluate the polynomial expreesion for the pixel map
y, x = np.indices(params['whitefield'].shape)
ufs = eval(params['pixel_map_fs'])
uss = eval(params['pixel_map_ss'])
u = np.array([uss, ufs])
u = np.clip(u, -1000, 1000)
# generate the pixel translations
M = params['z'] / params['defocus']
dfs = params['x_pixel_size'] / M
dss = params['y_pixel_size'] / M
pixel_translations = st.make_pixel_translations(params['translations'],
params['basis'], dss, dfs)
O, n0, m0 = st.make_object_map(
params['data'].astype(params['whitefield'].dtype), params['mask'],
params['whitefield'], pixel_translations,
u.astype(params['whitefield'].dtype), params['ls'])
u0 = np.array(np.indices(params['mask'].shape))
du = u - u0
out = {
'reference_image': O,
'n0': n0,
'm0': m0,
'pixel_map': u,
'pixel_map_residual': du,
'pixel_translations': pixel_translations,
'dfs': dfs,
'dss': dss
}
cmdline_config_cxi_reader.write_all(params,
args.filename,
out,
apply_roi=True)
# output display for gui
with open('.log', 'w') as f:
print('display: ' + params['h5_group'] + '/reference_image', file=f)
def test_st_update(defocus, length_scale, path, roi):
with h5py.File(path, 'r') as cxi_file:
I_n = cxi_file['/entry_1/data_1/data'][:, roi[0]:roi[1],
roi[2]:roi[3]].sum(axis=1)[:,
None]
basis = cxi_file['/entry_1/instrument_1/detector_1/basis_vectors'][...]
z = cxi_file['/entry_1/instrument_1/detector_1/distance'][...]
x_ps = cxi_file['/entry_1/instrument_1/detector_1/x_pixel_size'][...]
y_ps = cxi_file['/entry_1/instrument_1/detector_1/y_pixel_size'][...]
wl = cxi_file['/entry_1/instrument_1/source_1/wavelength'][...]
dij = cxi_file['/entry_1/sample_1/geometry/translation'][...]
M = np.ones((I_n.shape[1], I_n.shape[2]), dtype=bool)
W = st.make_whitefield(I_n, M, verbose=True).astype(I_n.dtype)
u, dij_pix, res = st.generate_pixel_map(W.shape,
dij,
basis,
x_ps,
y_ps,
z,
defocus,
verbose=True)
I0, n0, m0 = st.make_object_map(data=I_n,
mask=M,
W=W,
dij_n=dij_pix,
pixel_map=u,
ls=length_scale)
es = []
for i in range(5):
# calculate errors
error_total = st.calc_error(data=I_n,
mask=M,
W=W,
dij_n=dij_pix,
O=I0,
pixel_map=u,
n0=n0,
m0=m0,
ls=length_scale,
verbose=True)[0]
# store total error
es.append(error_total)
# update pixel map
u = st.update_pixel_map(data=I_n,
mask=M,
W=W,
O=I0,
pixel_map=u,
n0=n0,
m0=m0,
dij_n=dij_pix,
sw_ss=0,
sw_fs=10,
ls=length_scale)
# make reference image
I0, n0, m0 = st.make_object_map(data=I_n,
mask=M,
W=W,
dij_n=dij_pix,
pixel_map=u,
ls=length_scale)