/usr/lib/python2.7/dist-packages/cfflib/util.py is in python-cfflib 2.0.5-2.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
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from glob import glob
import os.path as op
import os
import json
import pickle
# NumPy
try:
import numpy as np
except ImportError:
raise ImportError("Failed to import numpy from any known place")
# Nibabel
try:
import nibabel as ni
except ImportError:
raise ImportError("Failed to import nibabel from any known place")
# NetworkX
try:
import networkx as nx
except ImportError:
pass
#raise ImportError("Failed to import networkx from any known place")
# PyTables
try:
import tables
except ImportError:
pass
#raise ImportError("Failed to import pytables from any known place")
# setting up xnat interface as global variable
has_pyxnat = True
try:
import pyxnat
except:
has_pyxnat = False
DEBUG_msg = True
import cfflib2 as cf
xnat_interface = None
def set_xnat_connection(connection_interface = None):
""" Setup XNAT to push and pull
Parameters
----------
connection_interface : { pxnat.Interface, dict }
Set the PyXNAT interface or a dictionary
with keys server, user, password, cachedir (optional)
"""
global xnat_interface
if not has_pyxnat:
raise Exception('You need to install PyXNAT to use this functionality')
if isinstance(connection_interface, dict):
xnat_interface = pyxnat.Interface(**connection_interface)
elif isinstance(connection_interface, pyxnat.Interface):
xnat_interface = connection_interface
else:
xnat_interface = None
if DEBUG_msg:
print("Connected to XNAT Server")
def xnat_push(connectome_obj, projectid, subjectid, experimentid, overwrite = False):
""" Push all the connectome objects to the remote XNAT server.
Parameters
----------
connectome_obj : connectome object
The connectome object you want to push
projectid : string
The id of the project, has to be unique across an XNAT server
subjectid : string
The id of the subject
experimentid : string
The id of the experiment
overwrite : boolean
Overwrite remote version of the connectome object with
the connectome object contained in the local connectome container
"""
def _push_metacml(experiment_uri):
_, fname = tempfile.mkstemp()
f=open(fname, 'wb')
f.write(connectome_obj.to_xml())
f.close()
# finally update remote meta.cml
meta_uri = '%s/resources/meta/files/meta.cml' % experiment_uri
xnat_interface.select(meta_uri).insert(fname, experiments = 'xnat:imageSessionData', \
use_label=True)
if xnat_interface is None:
raise Exception('You need to setup the XNAT connection first with set_xnat_connection')
# we define the unique experimental id based on the user input
# user do not expect this composed identifiers, so we directly use
# the given parameters to construct the path
# originally, we thought that this is required because there have to be
# unique subject identifiers across the whole XNAT instance
# we seems not to be required anymore
# subj_id = '%s_%s' % (projectid, subjectid)
# exp_id = '%s_%s' % (subj_id, experimentid)
subj_id = '%s' % subjectid
exp_id = '%s_%s' % (projectid, experimentid)
experiment_uri = '/projects/%s/subjects/%s/experiments/%s' % (projectid, subj_id, exp_id)
metacml_uri = '%s/resources/meta/files/meta.cml' % experiment_uri
# does the experiment exists
if xnat_interface.select(metacml_uri).exists():
# it exists
# compare it to the local object
remote_metacml = open(xnat_interface.select(metacml_uri).get(), 'rb')
remote_connectome = cf.parseString(remote_metacml.read())
# loop over local connectome objects and check if the exists remotely
all_local_cobj = connectome_obj.get_all()
# connectome objects we need to add to the remote metacml
push_objects = []
for ele in all_local_cobj:
if DEBUG_msg:
print "Working on element %s" % ele.name
if (ele in remote_connectome.get_all() and overwrite) or \
not ele in remote_connectome.get_all():
if DEBUG_msg:
print "We push element %s" % ele.name
print "Element in remote? " + str(ele in remote_connectome.get_all())
# push connectome object to remote
cobj_uri = '%s/assessors/%s/out/resources/data/files/%s' % (
experiment_uri,
'%s_%s' % (exp_id, ele.__class__.__name__),
quote_for_xnat(ele.name) + ele.get_file_ending()
)
if DEBUG_msg:
print "uri", cobj_uri
# insert data file to xnat
xnat_interface.select(cobj_uri).insert(ele.get_abs_path(), experiments = 'xnat:imageSessionData', \
assessors = 'xnat:imageAssessorData', use_label=True)
# add element for updating metacml later on the remote
push_objects.append(ele)
else:
# we do not push
if DEBUG_msg:
print "We do nothing with element %s (already on remote and no overwrite)" % ele.name
# synchronize meta_cml
# we need to retrieve the remote connectome objects and add it to the
# local if they no not yet exists
for el in remote_connectome.get_all():
if not el in connectome_obj.get_all():
connectome_obj.add_connectome_object(el)
#for el in push_objects:
# add all push_objects to remote meta_cml
# remote_connectome.add_connectome_object(el)
# update cmetadata (overwriting remote with local)
remote_connectome.connectome_meta = connectome_obj.connectome_meta
_push_metacml(experiment_uri)
if DEBUG_msg:
print "Current local connectome container", connectome_obj.to_xml()
print "Current remote connectome container", remote_connectome.to_xml()
print "Current push objects", push_objects
else:
# create meta.cml
# loop over local connectome objects and check if the exists remotely
all_local_cobj = connectome_obj.get_all()
for ele in all_local_cobj:
print "We push element %s" % ele.name
# push connectome object to remote
cobj_uri = '%s/assessors/%s/out/resources/data/files/%s' % (
experiment_uri,
'%s_%s' % (exp_id, ele.__class__.__name__),
quote_for_xnat(ele.name)
)
# insert data file to xnat
xnat_interface.select(cobj_uri).insert(ele.get_abs_path(), experiments = 'xnat:imageSessionData', \
assessors = 'xnat:imageAssessorData', use_label=True)
# push the current connectome object to remote
_push_metacml(experiment_uri)
def xnat_pull( projectid, subjectid, experimentid, storagepath):
""" Pull the complete set of files from a XNAT project, subject and experiment id """
absstoragepath = op.abspath(storagepath)
# we define the unique experimental id based on the user input
# see push for more comments
# subj_id = '%s_%s' % (projectid, subjectid)
# exp_id = '%s_%s' % (subj_id, experimentid)
subj_id = '%s' % subjectid
exp_id = '%s_%s' % (projectid, experimentid)
experiment_uri = '/projects/%s/subjects/%s/experiments/%s' % (projectid, subj_id, exp_id)
metacml_uri = '%s/resources/meta/files/meta.cml' % experiment_uri
# download meta.cml
metacmlpath = op.join(absstoragepath, 'meta.cml')
meta_uri = '%s/resources/meta/files/meta.cml' % experiment_uri
xnat_interface.select(meta_uri).get(metacmlpath)
# parse meta.cml
f = open(metacmlpath, 'rb')
remote_connectome = cf.parseString(f.read())
f.close()
if DEBUG_msg:
print "Remote connectome", remote_connectome.to_xml()
# loop over objects and download them to pyxnat cache / or path
for ele in remote_connectome.get_all():
if DEBUG_msg:
print("Downloading connectome object")
ele.print_summary()
cobj_uri = '%s/assessors/%s/out/resources/data/files/%s' % (
experiment_uri,
'%s_%s' % (exp_id, ele.__class__.__name__),
quote_for_xnat(ele.name) + ele.get_file_ending()
)
# download file
# does file folder exist?
eleobjfolderfname = op.join(absstoragepath, ele.get_unique_relpath())
if not op.exists(op.split(eleobjfolderfname)[0]):
os.makedirs( op.split(eleobjfolderfname)[0] )
xnat_interface.select(cobj_uri).get(eleobjfolderfname)
# update current connectome container
print("=============")
print("You can load the pulled connectome file with:")
print("import cfflib as cf; mycon = cf.load('%s')" % op.join(absstoragepath, 'meta.cml'))
print("=============")
return True
def quote_for_xnat(name):
""" Quote mapping from connectome object name to a valid XNAT filename
that can be used for PyXNAT queries """
n = name.lower()
# XXX: might need update
remove_characters = [' ', '/', '\\', '[', ']', '*', '"', '?', '\'', '%', '(', ')']
for c in remove_characters:
n = n.replace(c, '_')
return n
def validate_fileformat_type(src, location, fileformat):
""" Try to evaluate whether the given file has the correct fileformat is given """
pass
def validate_filedata_type(src, location, fileformat, dtype):
""" Try to evalute whether the given file is of dtype type """
pass
def remove_file(fpath):
""" Closes and removes the fpath file from the temporary folder """
import os
os.remove(fpath)
class NotSupportedFormat(Exception):
def __init__(self, fileformat, objtype):
self.fileformat = fileformat
self.objtype = objtype
def __str__(self):
return "Loading %s:\nFile format '%s' not supported by cfflib. Use your custom loader." % (self.objtype, self.fileformat)
def save_data(obj):
objrep = str(type(obj))
if hasattr(obj, 'data'):
# it appears that there is no remove function for zip archives implemented to date
# http://bugs.python.org/issue6818
# the file was loaded, thus it exists a .tmpsrc pointing to
# its absolute path. Use this path to overwrite the file by the
# current .data data
if hasattr(obj, 'tmpsrc'):
tmpfname = obj.tmpsrc
else:
# if it has no .tmpsrc, i.e. it is not loaded from a file path
# but it has a .data set
raise Exception('Element %s cannot be saved. (It was never loaded)' % str(obj))
dname = op.dirname(tmpfname)
if not op.exists(dname):
os.makedirs()
if 'CVolume' in objrep:
print "Saving CVolume ..."
ni.save(obj.data, tmpfname)
print "Done."
elif 'CNetwork' in objrep:
print "Saving CNetwork"
if obj.fileformat == "GraphML":
# write graph to temporary file
nx.write_graphml(obj.data, tmpfname)
elif obj.fileformat == "GEXF":
nx.write_gexf(obj.data, tmpfname)
elif obj.fileformat == "NXGPickle":
nx.write_gpickle(obj.data, tmpfname)
else:
raise NotSupportedFormat("Other", str(obj))
print "Done."
elif 'CSurface' in objrep:
if obj.fileformat == "Gifti":
import nibabel.gifti as nig
nig.write(obj.data, tmpfname)
else:
raise NotSupportedFormat("Other", str(obj))
elif 'CTrack' in objrep:
if obj.fileformat == "TrackVis":
ni.trackvis.write(tmpfname, obj.data[0], obj.data[1])
else:
raise NotSupportedFormat("Other", str(obj))
elif 'CTimeserie' in objrep:
if obj.fileformat == "HDF5":
# flush the data of the buffers
obj.data.flush()
# close the file
obj.data.close()
elif obj.fileformat == "NumPy":
load = np.save(tmpfname, obj.data)
else:
raise NotSupportedFormat("Other", str(obj))
elif 'CData' in objrep:
if obj.fileformat == "NumPy":
load = np.save(tmpfname, obj.data)
elif obj.fileformat == "HDF5":
# flush the data of the buffers
obj.data.flush()
# close the file
obj.data.close()
elif obj.fileformat == "XML":
f = open(tmpfname, 'w')
f.write(obj.data)
f.close()
elif obj.fileformat == "JSON":
f = open(tmpfname, 'w')
json.dump(obj.data, f)
f.close()
elif obj.fileformat == "Pickle":
f = open(tmpfname, 'w')
pickle.dump(obj.data, f)
f.close()
elif obj.fileformat == "CSV" or obj.fileformat == "TXT":
# write as text
f = open(tmpfname, 'w')
f.write(obj.data)
f.close()
else:
raise NotSupportedFormat("Other", str(obj))
elif 'CScript' in objrep:
f = open(tmpfname, 'w')
f.write(obj.data)
f.close()
return tmpfname
else:
# assumes the .src paths are given relative to the meta.cml
# valid for iszip = True and iszip = False
# either path to the .cff or to the meta.cml
# return op.join(op.dirname(obj.parent_cfile.fname), obj.src)
print "Connectome Object is not loaded. Nothing to save."
return ''
def load_data(obj):
objrep = str(type(obj))
if 'CVolume' in objrep:
load = ni.load
elif 'CNetwork' in objrep:
if obj.fileformat == "GraphML":
load = nx.read_graphml
elif obj.fileformat == "GEXF":
# works with networkx 1.4
load = nx.read_gexf
elif obj.fileformat == "NXGPickle":
load = nx.read_gpickle
else:
raise NotSupportedFormat("Other", str(obj))
elif 'CSurface' in objrep:
if obj.fileformat == "Gifti":
import nibabel.gifti as nig
load = nig.read
else:
raise NotSupportedFormat("Other", str(obj))
elif 'CTrack' in objrep:
if obj.fileformat == "TrackVis":
load = ni.trackvis.read
else:
raise NotSupportedFormat("Other", str(obj))
elif 'CTimeserie' in objrep:
if obj.fileformat == "HDF5":
load = tables.openFile
elif obj.fileformat == "NumPy":
load = np.load
else:
raise NotSupportedFormat("Other", str(obj))
elif 'CData' in objrep:
if obj.fileformat == "NumPy":
load = np.load
elif obj.fileformat == "HDF5":
load = tables.openFile
elif obj.fileformat == "XML":
load = open
elif obj.fileformat == "JSON":
load = json.load
elif obj.fileformat == "Pickle":
load = pickle.load
elif obj.fileformat == "CSV" or obj.fileformat == "TXT":
# can use import csv on the returned object
load = open
else:
raise NotSupportedFormat("Other", str(obj))
elif 'CScript' in objrep:
load = open
elif 'CImagestack' in objrep:
if obj.parent_cfile.iszip:
_zipfile = ZipFile(obj.parent_cfile.src, 'r', ZIP_DEFLATED)
try:
namelist = _zipfile.namelist()
except: # XXX: what is the correct exception for read error?
raise RuntimeError('Can not extract %s from connectome file.' % str(obj.src) )
finally:
_zipfile.close()
import fnmatch
ret = []
for ele in namelist:
if fnmatch.fnmatch(ele, op.join(obj.src, obj.pattern)):
ret.append(ele)
return ret
else:
# returned list should be absolute path
if op.isabs(obj.src):
return sorted(glob(op.join(obj.src, obj.pattern)))
else:
path2files = op.join(op.dirname(obj.parent_cfile.fname), obj.src, obj.pattern)
return sorted(glob(path2files))
######
if obj.parent_cfile.iszip:
from tempfile import gettempdir
# create a meaningful and unique temporary path to extract data files
tmpdir = op.join(gettempdir(), obj.parent_cfile.get_unique_cff_name())
# extract src from zipfile to temp
_zipfile = ZipFile(obj.parent_cfile.src, 'r', ZIP_DEFLATED)
try:
exfile = _zipfile.extract(obj.src, tmpdir)
print "Loading file. Created temporary file: %s" % exfile
obj.tmpsrc = exfile
_zipfile.close()
retload = load(exfile)
print "Succeed."
return retload
except: # XXX: what is the correct exception for read error?
raise RuntimeError('Can not extract "%s" from connectome file using path %s. Please extract .cff and load meta.cml directly.' % (str(obj.name), str(obj.src)) )
return None
else:
if hasattr(obj, 'tmpsrc'):
# we have an absolute path
print "Load object: %s" % obj.tmpsrc
obj.tmpsrc = obj.tmpsrc
retload = load(obj.tmpsrc)
print "Succeed."
return retload
else:
# otherwise, we need to join the meta.cml path with the current relative path
path2file = op.join(op.dirname(obj.parent_cfile.fname), obj.src)
print "Load object: %s" % path2file
obj.tmpsrc = path2file
retload = load(path2file)
print "Succeed."
return retload
def unify(t, n):
""" Unify type and name """
n = n.lower()
n = n.replace(' ', '_')
return '%s/%s' % (t, n)
import urllib2
def download(url, fileName=None):
def getFileName(url,openUrl):
if 'Content-Disposition' in openUrl.info():
# If the response has Content-Disposition, try to get filename from it
cd = dict(map(
lambda x: x.strip().split('=') if '=' in x else (x.strip(),''),
openUrl.info().split(';')))
if 'filename' in cd:
filename = cd['filename'].strip("\"'")
if filename: return filename
# if no filename was found above, parse it out of the final URL.
return basename(urlsplit(openUrl.url)[2])
r = urllib2.urlopen(urllib2.Request(url))
try:
fileName = fileName or getFileName(url,r)
with open(fileName, 'wb') as f:
shutil.copyfileobj(r,f)
finally:
r.close()
def group_by_tagkey(cobj_list, tagkey, cobj_type = None, exclude_values = None):
""" Specifying the connectome object type and metadata key, a
dictionary is returned keyed by the values of the given metadata
key.
Parameter
---------
cobj_list : list of connectome objects
This list is filtered by the tagging key
tagkey : string
The metadata tag key you want to use for grouping
cobj_type : string
If you want to confine your result to a particular connectome
object type such as 'CNetwork', 'CVolume' etc.
exclude_values : list of string
If you want to discard particular metadata values
in the returned dictionary.
Notes
-----
This function is helpful to retrieve groups of connectome
objects for further analysis, e.g. statistical comparison.
The metadata works as a kind of "intersubject" grouping
criteria. For example you can have a metadata key "sex" with
values M, F and unknown. You can exclude the unknown value
by setting exclude_values = ['unknown'].
If the metadata key does not exists for the connectome
object, just skip this object.
"""
rdict = {}
for cob in cobj_list:
if cobj_type is None or cobj_type in cob.__class__:
mdi = cob.get_metadata_as_dict()
if not mdi is None and tagkey in mdi.keys():
if rdict.has_key(mdi[tagkey]):
rdict[mdi[tagkey]].append(cob)
else:
rdict[mdi[tagkey]] = [cob]
# eventually, remove not desired values
if not exclude_values is None:
for k in exclude_values:
if rdict.has_key(k):
del rdict[k]
return rdict
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