def runAceCorrect(imgdict,params):
imgname = imgdict['filename']
imgpath = os.path.join(imgdict['session']['image path'], imgname+'.mrc')
voltage = (imgdict['scope']['high tension'])
apix = apDatabase.getPixelSize(imgdict)
ctfvalues = ctfdb.getBestCtfByResolution(imgdata)
conf = ctfdb.calculateConfidenceScore(bestctfvalue)
ctdimname = imgname
ctdimpath = os.path.join(params['rundir'],ctdimname)
print "Corrected Image written to " + ctdimpath
#pdb.set_trace()
acecorrectcommand=("ctfcorrect1('%s', '%s', '%.32f', '%.32f', '%f', '%f', '%f');" % \
(imgpath, ctdimpath, ctfvalues['defocus1'], ctfvalues['defocus2'], -ctfvalues['angle_astigmatism'], voltage, apix))
print acecorrectcommand
try:
matlab = pymat.open("matlab -nosplash")
except:
apDisplay.environmentError()
raise
pymat.eval(matlab, acecorrectcommand)
pymat.close(matlab)
return
def processImage(self, imgdata):
self.ctfvalues = {}
# RESTART MATLAB EVERY 500 IMAGES OR IT RUNS OUT OF MEMORY
if self.stats['count'] % 500 == 0:
apDisplay.printWarning("processed 500 images. restarting matlab...")
pymat.close(self.matlab)
time.sleep(5)
self.matlab = pymat.open()
scopeparams = {
'kv': imgdata['scope']['high tension']/1000,
'apix': apDatabase.getPixelSize(imgdata),
'cs': self.params['cs'],
'tempdir': self.params['tempdir'],
}
### Scott's hack for FSU CM
### For CM high tension is given in kv instead of v
if imgdata['scope']['tem']['name'] == "CM":
scopeparams['kv'] = imgdata['scope']['high tension']
apMatlab.setScopeParams(self.matlab, scopeparams)
### RUN ACE
self.ctfvalues = {}
acevalues = apMatlab.runAce(self.matlab, imgdata, self.params)
#check if ACE was successful
if acevalues[0] == -1:
self.badprocess = True
return False
acevaluelist = ('defocus1','defocus2','defocusinit','amplitude_contrast','angle_astigmatism',
'noise1','noise2','noise3','noise4','envelope1','envelope2','envelope3','envelope4',
'lowercutoff','uppercutoff','snr','confidence','confidence_d')
for i in range(len(acevaluelist)):
self.ctfvalues[ acevaluelist[i] ] = acevalues[i]
### override the astig angle to be in degrees
self.ctfvalues['angle_astigmatism'] = - math.degrees(self.ctfvalues['angle_astigmatism'])
self.ctfvalues['mat_file'] = imgdata['filename']+".mrc.mat"
self.ctfvalues['cs'] = scopeparams['cs']
self.ctfvalues['volts'] = scopeparams['kv']*1000.0
### RENAME/MOVE OUTPUT FILES
imfile1 = os.path.join(self.params['tempdir'], "im1.png")
imfile2 = os.path.join(self.params['tempdir'], "im2.png")
opimfile1 = imgdata['filename']+".mrc1.png"
opimfile2 = imgdata['filename']+".mrc2.png"
opimfilepath1 = os.path.join(self.powerspecdir, opimfile1)
opimfilepath2 = os.path.join(self.powerspecdir, opimfile2)
if os.path.isfile(imfile1):
shutil.copyfile(imfile1, opimfilepath1)
else:
apDisplay.printWarning("imfile1 is missing, %s"%(imfile1))
if os.path.isfile(imfile2):
shutil.copyfile(imfile2, opimfilepath2)
else:
apDisplay.printWarning("imfile2 is missing, %s"%(imfile2))
self.ctfvalues['graph1'] = opimfilepath1
self.ctfvalues['graph2'] = opimfilepath2
def close(self):
if not self._closed:
self._closed = True
try:
mlabraw.close(self._session)
except AssertionError:
pass
def runAceCorrect(imgdict,params):
imgname = imgdict['filename']
imgpath = os.path.join(imgdict['session']['image path'], imgname+'.mrc')
voltage = (imgdict['scope']['high tension'])
apix = apDatabase.getPixelSize(imgdict)
ctfvalues, conf = ctfdb.getBestCtfValueForImage(imgdict)
ctdimname = imgname
ctdimpath = os.path.join(params['rundir'],ctdimname)
print "Corrected Image written to " + ctdimpath
#pdb.set_trace()
acecorrectcommand=("ctfcorrect1('%s', '%s', '%.32f', '%.32f', '%f', '%f', '%f');" % \
(imgpath, ctdimpath, ctfvalues['defocus1'], ctfvalues['defocus2'], -ctfvalues['angle_astigmatism'], voltage, apix))
print acecorrectcommand
try:
matlab = pymat.open("matlab -nosplash")
except:
apDisplay.environmentError()
raise
pymat.eval(matlab, acecorrectcommand)
pymat.close(matlab)
return
def __init__(self):
"""Create a new matlab(tm) wrapper object.
"""
self._array_cast = None
"""specifies a cast for arrays. If the result of an
operation is a numpy array, ``return_type(res)`` will be returned
instead."""
self._autosync_dirs = True
"""`autosync_dirs` specifies whether the working directory of the
matlab session should be kept in sync with that of python."""
self._flatten_row_vecs = False
"""Automatically return 1xn matrices as flat numeric arrays."""
self._flatten_col_vecs = False
"""Automatically return nx1 matrices as flat numeric arrays."""
self._clear_call_args = True
"""Remove the function args from matlab workspace after each function
call. Otherwise they are left to be (partly) overwritten by the next
function call. This saves a function call in matlab but means that the
memory used up by the arguments will remain unreclaimed till
overwritten."""
self._session = mlabraw.open()
atexit.register(lambda handle=self._session: mlabraw.close(handle))
self._proxies = weakref.WeakValueDictionary()
"""Use ``mlab._proxies.values()`` for a list of matlab object's that
are currently proxied."""
self._proxy_count = 0
self._mlabraw_can_convert = ('double', 'char')
"""The matlab(tm) types that mlabraw will automatically convert for us."""
self._dont_proxy = {'cell': False}
"""The matlab(tm) types we can handle ourselves with a bit of
def __init__(self):
"""Create a new matlab(tm) wrapper object.
"""
self._array_cast = None
"""specifies a cast for arrays. If the result of an
operation is a numpy array, ``return_type(res)`` will be returned
instead."""
self._autosync_dirs=True
"""`autosync_dirs` specifies whether the working directory of the
matlab session should be kept in sync with that of python."""
self._flatten_row_vecs = False
"""Automatically return 1xn matrices as flat numeric arrays."""
self._flatten_col_vecs = False
"""Automatically return nx1 matrices as flat numeric arrays."""
self._clear_call_args = True
"""Remove the function args from matlab workspace after each function
call. Otherwise they are left to be (partly) overwritten by the next
function call. This saves a function call in matlab but means that the
memory used up by the arguments will remain unreclaimed till
overwritten."""
self._session = mlabraw.open(os.getenv("MLABRAW_CMD_STR", ""))
atexit.register(lambda handle=self._session: mlabraw.close(handle))
self._proxies = weakref.WeakValueDictionary()
"""Use ``mlab._proxies.values()`` for a list of matlab object's that
are currently proxied."""
self._proxy_count = 0
self._mlabraw_can_convert = ('double', 'char')
"""The matlab(tm) types that mlabraw will automatically convert for us."""
self._dont_proxy = {'cell' : False}
"""The matlab(tm) types we can handle ourselves with a bit of
def __init__(self):
"""Create a new matlab(tm) wrapper object.
"""
self._array_cast = None
"""specifies a cast for arrays. If the result of an
operation is a numpy array, ``return_type(res)`` will be returned
instead."""
self._autosync_dirs=True
"""`autosync_dirs` specifies whether the working directory of the
matlab session should be kept in sync with that of python."""
self._flatten_row_vecs = True
"""Automatically return 1xn matrices as flat numeric arrays."""
self._flatten_col_vecs = True
"""Automatically return nx1 matrices as flat numeric arrays."""
self._clear_call_args = True
"""Remove the function args from matlab workspace after each function
call. Otherwise they are left to be (partly) overwritten by the next
function call. This saves a function call in matlab but means that the
memory used up by the arguments will remain unreclaimed till
overwritten."""
self._session = mlabraw.open(os.getenv("MLABRAW_CMD_STR", ""))
atexit.register(lambda handle=self._session: mlabraw.close(handle))
self._proxies = weakref.WeakValueDictionary()
"""Use ``mlab._proxies.values()`` for a list of matlab object's that
are currently proxied."""
self._proxy_count = 0
self._mlabraw_can_convert = ('double', 'char','single','int')
"""The matlab(tm) types that mlabraw will automatically convert for us."""
self._dont_proxy = {'cell' : True, 'struct' : True, 'logical' : True}
"""The matlab(tm) types we can handle ourselves with a bit of
effort. To turn on autoconversion for e.g. cell arrays do:
``mlab._dont_proxy["cell"] = True``."""
if 'matlab' in self._session.matlab_process_path:
# addpath to iFit location if using Matlab and distribution is not standalone
self._eval('isd=double(isdeployed);')
isdeployed = self._get('isd')
# when not deployed, call 'addpath'
if isdeployed == 0:
print "Installing iFit"
location = os.path.abspath(
os.path.realpath(os.path.dirname(__file__))+os.sep+'..'+os.sep+'..' )
self._eval("addpath(genpath('"+location+"'));", print_expression=True)
print self._eval('disp(version(iData));')
print "To learn how to use Python iFit, type: mlab.doc(mlab.iData())\n";
def __init__(self, matlab_binary_path=None, matlab_version=None):
"""Create a new matlab(tm) wrapper object.
:param matlab_binary_path: This is the full path to the main Matlab
executable script on Linux and OSX, e.g.
``/opt/MATLAB/R2010a/matlab``. Not required on Windows. If set to
None, mlabwrap will try to find matlab in your path.
:param matlab_version: The version string, for example ``2010b``, or
None if you want me to deduce it from the matlab path.
"""
self._array_cast = None
"""specifies a cast for arrays. If the result of an
operation is a numpy array, ``return_type(res)`` will be returned
instead."""
self._autosync_dirs=True
"""`autosync_dirs` specifies whether the working directory of the
matlab session should be kept in sync with that of python."""
self._flatten_row_vecs = False
"""Automatically return 1xn matrices as flat numeric arrays."""
self._flatten_col_vecs = False
"""Automatically return nx1 matrices as flat numeric arrays."""
self._clear_call_args = True
"""Remove the function args from matlab workspace after each function
call. Otherwise they are left to be (partly) overwritten by the next
function call. This saves a function call in matlab but means that the
memory used up by the arguments will remain unreclaimed till
overwritten."""
#self._session = mlabraw.open(os.getenv("MLABRAW_CMD_STR", ""))
self._session = mlabraw.open(matlab_binary_path)
atexit.register(lambda handle=self._session: mlabraw.close(handle))
self._proxies = weakref.WeakValueDictionary()
"""Use ``mlab._proxies.values()`` for a list of matlab object's that
are currently proxied."""
self._proxy_count = 0
# due to save stdio defaulting to matlab v4 files, we can unfortunately
# only handle these types. sucks!
self._mlabraw_can_convert = ('double', 'char')
"""The matlab(tm) types that mlabraw will automatically convert for us."""
self._dont_proxy = {'cell' : False}
"""The matlab(tm) types we can handle ourselves with a bit of
def __init__(self, matlab_binary_path=None, matlab_version=None):
"""Create a new matlab(tm) wrapper object.
:param matlab_binary_path: This is the full path to the main Matlab
executable script on Linux and OSX, e.g.
``/opt/MATLAB/R2010a/matlab``. Not required on Windows. If set to
None, mlabwrap will try to find matlab in your path.
:param matlab_version: The version string, for example ``2010b``, or
None if you want me to deduce it from the matlab path.
"""
self._array_cast = None
"""specifies a cast for arrays. If the result of an
operation is a numpy array, ``return_type(res)`` will be returned
instead."""
self._autosync_dirs=True
"""`autosync_dirs` specifies whether the working directory of the
matlab session should be kept in sync with that of python."""
self._flatten_row_vecs = False
"""Automatically return 1xn matrices as flat numeric arrays."""
self._flatten_col_vecs = False
"""Automatically return nx1 matrices as flat numeric arrays."""
self._clear_call_args = True
"""Remove the function args from matlab workspace after each function
call. Otherwise they are left to be (partly) overwritten by the next
function call. This saves a function call in matlab but means that the
memory used up by the arguments will remain unreclaimed till
overwritten."""
#self._session = mlabraw.open(os.getenv("MLABRAW_CMD_STR", ""))
self._session = mlabraw.open(matlab_binary_path)
atexit.register(lambda handle=self._session: mlabraw.close(handle))
self._proxies = weakref.WeakValueDictionary()
"""Use ``mlab._proxies.values()`` for a list of matlab object's that
are currently proxied."""
self._proxy_count = 0
# due to save stdio defaulting to matlab v4 files, we can unfortunately
# only handle these types. sucks!
self._mlabraw_can_convert = ('double', 'char')
"""The matlab(tm) types that mlabraw will automatically convert for us."""
self._dont_proxy = {'cell' : False}
"""The matlab(tm) types we can handle ourselves with a bit of
def __del__(self):
mlabraw.close(self.session)
def postLoopFunctions(self):
pymat.close(self.matlab)
ctfdb.printCtfSummary(self.params, self.imgtree)
def _close_session(self):
if self._session is not None:
mlabraw.close(self._session)
self._session = None
def __del__(self):
mlabraw.close(self.session)
def postLoopFunctions(self): pymat.close(self.matlab) ctfdb.printCtfSummary(self.params, self.imgtree)
def close(self):
try: mlabraw.close(self._engine)
except: pass
def close(self):
if not self._closed:
self._closed = True
mlabraw.close(self._session)
def __del__(self):
try:
mlabraw.close(self._session)
except:
pass
def processImage(self, imgdata):
self.ctfvalues = {}
# RESTART MATLAB EVERY 500 IMAGES OR IT RUNS OUT OF MEMORY
if self.stats["count"] % 500 == 0:
apDisplay.printWarning("processed 500 images. restarting matlab...")
pymat.close(self.matlab)
time.sleep(5)
self.matlab = pymat.open()
scopeparams = {
"kv": imgdata["scope"]["high tension"] / 1000,
"apix": apDatabase.getPixelSize(imgdata),
"cs": self.params["cs"],
"tempdir": self.params["tempdir"],
}
### Scott's hack for FSU CM
### For CM high tension is given in kv instead of v
if imgdata["scope"]["tem"]["name"] == "CM":
scopeparams["kv"] = imgdata["scope"]["high tension"]
apMatlab.setScopeParams(self.matlab, scopeparams)
### RUN ACE
self.ctfvalues = {}
acevalues = apMatlab.runAce(self.matlab, imgdata, self.params)
# check if ACE was successful
if acevalues[0] == -1:
self.badprocess = True
return False
acevaluelist = (
"defocus1",
"defocus2",
"defocusinit",
"amplitude_contrast",
"angle_astigmatism",
"confidence",
"confidence_d",
)
for i in range(len(acevaluelist)):
self.ctfvalues[acevaluelist[i]] = acevalues[i]
### override the astig angle to be in degrees
self.ctfvalues["angle_astigmatism"] = -math.degrees(self.ctfvalues["angle_astigmatism"])
self.ctfvalues["mat_file"] = imgdata["filename"] + ".mrc.mat"
self.ctfvalues["cs"] = scopeparams["cs"]
self.ctfvalues["volts"] = scopeparams["kv"] * 1000.0
### RENAME/MOVE OUTPUT FILES
imfile1 = os.path.join(self.params["tempdir"], "im1.png")
imfile2 = os.path.join(self.params["tempdir"], "im2.png")
opimfile1 = imgdata["filename"] + ".mrc1.png"
opimfile2 = imgdata["filename"] + ".mrc2.png"
opimfilepath1 = os.path.join(self.powerspecdir, opimfile1)
opimfilepath2 = os.path.join(self.powerspecdir, opimfile2)
if os.path.isfile(imfile1):
shutil.copyfile(imfile1, opimfilepath1)
else:
apDisplay.printWarning("imfile1 is missing, %s" % (imfile1))
if os.path.isfile(imfile2):
shutil.copyfile(imfile2, opimfilepath2)
else:
apDisplay.printWarning("imfile2 is missing, %s" % (imfile2))
self.ctfvalues["graph1"] = opimfilepath1
self.ctfvalues["graph2"] = opimfilepath2