def create_ctf_list(current_ctf, def_search_range, def_step_size):
"""
Creates a set of CTFs with different defoci based on a defocus search range arround the
defocus of the current ctf estimate.
:param current_ctf: Current ctf
:param def_search_range: Defocus search range
:param def_step_size: Defocus step size
:return: Set of CTFs
"""
current_defocus = current_ctf.defocus
ctfs = []
lower_defocus = current_defocus - def_search_range
if lower_defocus < 0:
lower_defocus = 0
upper_defocus = current_defocus + def_search_range + def_step_size
for defocus in numpy.arange(lower_defocus, upper_defocus, def_step_size):
ctf_parameter = EMAN2.EMAN2Ctf()
removed_dict = dict([(key, value) for key , value in current_ctf.to_dict().items() if key not in ('background', 'snr')])
ctf_parameter.from_dict(removed_dict)
# ctf_parameter.from_dict(current_ctf.to_dict())
ctf_parameter.defocus = defocus
ctfs.append(ctf_parameter)
return ctfs
def create_ctf_list(current_ctf, def_search_range, def_step_size): """ Creates a set of CTFs with different defoci based on a defocus search range arround the defocus of the current ctf estimate. :param current_ctf: Current ctf :param def_search_range: Defocus search range :param def_step_size: Defocus step size :return: Set of CTFs """ current_defocus = current_ctf.defocus ctfs = [] lower_defocus = current_defocus - def_search_range if lower_defocus < 0: lower_defocus = 0 upper_defocus = current_defocus + def_search_range + def_step_size for defocus in np.arange(lower_defocus, upper_defocus, def_step_size): ctf_parameter = EMAN2.EMAN2Ctf() ctf_parameter.from_dict(current_ctf.to_dict()) ctf_parameter.defocus = defocus ctfs.append(ctf_parameter) return ctfs
def writeParticles():
line = sys.stdin.readline()
fnHdf = ""
while line:
objDict = json.loads(line)
index = int(objDict['_index'])
filename = str(objDict['_filename'])
imageData = eman.EMData()
imageData.read_image(filename, index)
if '_ctfModel._defocusU' in objDict:
ctf = eman.EMAN2Ctf()
defU = objDict['_ctfModel._defocusU']
defV = objDict['_ctfModel._defocusV']
ctf.from_dict({"defocus": (defU + defV) / 20000.0,
"dfang": objDict['_ctfModel._defocusAngle'],
"dfdiff": (defU - defV) / 10000.0,
"voltage": objDict['_acquisition._voltage'],
"cs": max(objDict['_acquisition._sphericalAberration'], 0.0001),
"ampcont": objDict['_acquisition._amplitudeContrast'] * 100.0,
"apix": objDict['_samplingRate']})
imageData.set_attr('ctf', ctf)
imageData.set_attr('apix_x', objDict['_samplingRate'])
imageData.set_attr('apix_y', objDict['_samplingRate'])
transformation = None
if '_angles' in objDict:
# TODO: convert to vector not matrix
angles = objDict['_angles']
shifts = objDict['_shifts']
transformation = eman.Transform({"type": "spider",
"phi": angles[0],
"theta": angles[1],
"psi": angles[2],
"tx": -shifts[0],
"ty": -shifts[1],
"tz": -shifts[2],
"mirror": 0, # TODO: test flip
"scale": 1.0})
if transformation is not None:
imageData.set_attr('xform.projection', transformation)
outputFile = str(objDict['hdfFn'])
if outputFile != fnHdf:
i = 0
fnHdf = outputFile
imageData.write_image(outputFile, i,
eman.EMUtil.ImageType.IMAGE_HDF, False)
i += 1
print("OK") # it is necessary to add newline
sys.stdout.flush()
line = sys.stdin.readline()
def writeParticles():
line = sys.stdin.readline()
fnHdf = ""
while line:
#for line in sys.stdin:
objDict=json.loads(line)
###imgId, index, filename = line.split()
if '_index' in objDict.keys():
index = int(objDict['_index'])
if '_filename' in objDict.keys():
filename = str(objDict['_filename'])
else:
raise Exception('ERROR (e2converter): Cannot process a particle without filename')
imageData = eman.EMData()
imageData.read_image(filename, index)
ctf = None
if '_ctfModel._defocusU' in objDict.keys():
ctf = eman.EMAN2Ctf()
defU = objDict['_ctfModel._defocusU']
defV = objDict['_ctfModel._defocusV']
ctf.from_dict({"defocus": (defU + defV)/20000.0,
"dfang": objDict['_ctfModel._defocusAngle'],
"dfdiff": (defU - defV)/10000.0,
"voltage": objDict['_acquisition._voltage'],
"cs": objDict['_acquisition._sphericalAberration'],
"ampcont": objDict['_acquisition._amplitudeContrast'] * 100.0,
"apix": objDict['_samplingRate']})
imageData.set_attr('ctf', ctf)
transformation = None
if '_angles' in objDict.keys():
#TODO: convert to vector not matrix
angles = objDict['_angles']
shifts = objDict['_shifts']
transformation = eman.Transform({"type": "spider",
"phi": angles[0],
"theta": angles[1],
"psi": angles[2],
"tx": shifts[0],
"ty": shifts[1],
"tz": shifts[2],
"mirror": 0, ####TODO: test flip
"scale": 1.0})
if transformation is not None:
imageData.set_attr('xform.projection', transformation)
outputFile = str(objDict['hdfFn'])
if outputFile != fnHdf:
i = 0
fnHdf = outputFile
imageData.write_image(outputFile, i, eman.EMUtil.ImageType.IMAGE_HDF, False)
i += 1
print "OK"
sys.stdout.flush()
line = sys.stdin.readline()
print "DONE"
