def test_decon_wrapper_with_variable_shapes(self):
"""
test that the
"""
images = [
self.deskewed, self.deskewed[:, 4:-4, 4:-4],
self.deskewed[2:-2, 16:-16, 16:-16]
]
decon(images, self.otf, **self.config)
def test_decon_wrapper_with_psf_array(self):
"""
test that we can deconvolve an image
"""
psf = imread(self.psf)
decon_result = decon(self.deskewed, psf, **self.config)
self.assertTrue(np.allclose(decon_result, self.stored_decon))
def test_decon_wrapper_save_deskewed(self):
"""
test that the
"""
config = dict(self.config)
config['deskew'] = 31.5
decon_result = decon(self.raw, self.otf, save_deskewed=True, **config)
self.assertTrue(len(decon_result) == 2)
def test_decon_wrapper_with_many_inputs(self):
"""
test that the
"""
images = [self.deskewed, self.deskewed, self.deskewed]
decon_results = decon(images, self.otf, **self.config)
self.assertTrue(
all([np.allclose(d, self.stored_decon) for d in decon_results]))
def proc_channel(pos):
for chan in channels:
data = dir+experiment+pos+channels[chan]
psf = dir+"\\"+kernels[chan]
if not os.path.isfile(data):
print("bad file path: "+data)
if not os.path.isfile(psf):
print('bad file path: '+psf)
result = decon(data, psf, cleanup_otf=True, wavelength=wavelengths[chan], na=1.47, nimm=1.515)
# to output full zstack
# tifffile.imsave(outdir+pos+"\\testthing%s.tif" % chan, result.astype(dtype=np.uint16))
# to output individual z-planes in the format generated by micromanager
for zIdx in range(0, len(result)):
out_filename = '\\img_000000000_Zyla_%s_Widefield_%03d.tif' % (chan, zIdx)
tifffile.imsave(outdir+pos+out_filename, result[zIdx].astype(dtype=np.uint16))
wavelengths = {'405': 430,
'488': 515,
'561': 585,
'637': 655}
# set range on position if want a subset
for pos in positions[:]:
if not os.path.exists(outdir+pos):
os.mkdir(outdir+pos)
for chan in channels:
data = dir+experiment+pos+channels[chan]
psf = dir+"\\"+kernels[chan]
if not os.path.isfile(data):
print("bad file path: "+data)
if not os.path.isfile(psf):
print('bad file path: '+psf)
result = decon(data, psf, cleanup_otf=True, wavelength=wavelengths[chan], na=1.47, nimm=1.515)
# to output full zstack
# tifffile.imsave(outdir+pos+"\\testthing%s.tif" % chan, result.astype(dtype=np.uint16))
# to output individual z-planes in the format generated by micromanager
for zIdx in range(0, len(result)):
out_filename = '\\img_000000000_Zyla_%s_Widefield_%03d.tif' % (chan, zIdx)
tifffile.imsave(outdir+pos+out_filename, result[zIdx].astype(dtype=np.uint16))
requires installation of python and other python packlages,
which are included in the anaconda python release.
pyCUDAdecon and instructions to install and use are at
https://github.com/tlambert03/pycudadecon
"""
#import required packages
from pycudadecon import decon, make_otf
from skimage.external.tifffile import imsave
# set input a and output file paths
image_path = 'C1-YeastTNA1_1516_conv_RG_26oC_003.tif'
psf_path = 'gpsf_3D_1514_a3_001_WF-sub105.tif'
otfOutPath = 'otf.tif'
# do the deconvolution on GPU
numIters = 30
result = decon(image_path, psf_path, n_iters=numIters)
print("result data type is " + str(result.dtype))
print('results numpy array shape is ')
print(result.shape)
# save the result,
print('Saving result image TIFF file')
# using skimage.external.tifffile.imsave
imsave(('result' + str(numIters) + 'iterations.tif'), result) #, imagej)
# save otf tiff file from PSF image tiff.
print('making otf')
make_otf(psf_path, otfOutPath, dzpsf=0.15, dxpsf=0.05, wavelength=510, na=1.3, nimm=1.333, otf_bgrd=None, krmax=0, fixorigin=10, cleanup_otf=True, max_otf_size=60000)
def test_decon_wrapper_save_deskewed(raw_image, config):
"""test that save_deskewed includes deskewed when passing raw image"""
config["deskew"] = 31.5
decon_result = decon(raw_image, OTF_PATH, save_deskewed=True, **config)
assert len(decon_result) == 2
def test_decon_wrapper_with_variable_shapes(deskewed_image, config):
"""test passing a list of variabel shape images to decon"""
im = deskewed_image
images = [im, im[:, 4:-4, 4:-4], im[2:-2, 16:-16, 16:-16]]
decon(images, OTF_PATH, **config)
def test_decon_wrapper_with_many_inputs(deskewed_image, decon_image, config):
"""test passing a list of images to decon"""
images = [deskewed_image, deskewed_image, deskewed_image]
for d in decon(images, OTF_PATH, **config):
npt.assert_allclose(d, decon_image, atol=ATOL)
def test_decon_wrapper_with_psf_array(deskewed_image, decon_image, config):
"""test that we can deconvolve an image with psf as array"""
decon_result = decon(deskewed_image, imread(PSF_PATH), **config)
npt.assert_allclose(decon_result, decon_image, atol=ATOL)
def test_decon_wrapper_with_psf(deskewed_image, decon_image, config):
"""test that we can deconvolve an image with psf as string"""
decon_result = decon(deskewed_image, PSF_PATH, **config)
npt.assert_allclose(decon_result, decon_image, atol=ATOL)
def test_decon_wrapper_with_otf(deskewed_image, decon_image, config):
"""test that we can deconvolve when provided OTF directly"""
decon_result = decon(deskewed_image, OTF_PATH, **config)
npt.assert_allclose(decon_result, decon_image, atol=ATOL)
def test_decon_wrapper_with_otf(self):
"""
test that the
"""
decon_result = decon(self.deskewed, self.otf, **self.config)
self.assertTrue(np.allclose(decon_result, self.stored_decon))