def plot_mriscan_weak(fu, mriscan, netname):
print(mriscan)
net = fu.nets.load(mriscan, netname)
netfilepath = fu.nets.loadfilepath(mriscan, netname)
netfiledir = os.path.dirname(netfilepath)
atlasobj = fu.atlasobj
attrdata = np.mean(net.data, axis=0)
attr = netattr.Attr(attrdata, atlasobj)
outfilepath = os.path.join(netfiledir, netname + '_circos_weak')
title = '{}\n{}\n'.format(mriscan, netname)
if netname == 'bold_net':
p = WeakBOLDNetCircosPlot(atlasobj, title, outfilepath)
p.add_circosvalue(braincircos.CircosValue(attr, (-1, 1)))
p.add_circoslink(WeakCircosLink(net, 0.5, (-1, 1)))
elif netname == 'dwi_net':
p = WeakDWINetCircosPlot(atlasobj, title, outfilepath)
p.add_circosvalue(braincircos.CircosValue(attr, (-100, 100)))
p.add_circosvalue(
braincircos.CircosValue(fu.attrs.load(mriscan, 'dwi_MD'),
(-0.003, 0.003)))
p.add_circosvalue(
braincircos.CircosValue(fu.attrs.load(mriscan, 'dwi_FA'), (-1, 1)))
p.add_circoslink(WeakCircosLink(net, 2, (-6, 6)))
else:
return
p.plot()
def trans_netattr(self,subject_scan, atlas_name, feature_name, value): if value.ndim == 1: # 这里要改一下 arr = netattr.Attr(value, atlas.get(atlas_name),subject_scan, feature_name) return arr else: net = netattr.Net(value, atlas.get(atlas_name), subject_scan, feature_name) return net
def loadSingle(self, mriscan, attrname, csvfilename = None): """ Load the attribute object, with atlasobj. - mriscan: specify which scan to load from - attrname: the name of the attr to load - csvfilename: the name of the attr file name. Specify this parameter to override filename """ if csvfilename is not None: attrdata = self.loaddata(mriscan, attrname, csvfilename) else: attrdata = self.loaddata(mriscan, attrname) attr = netattr.Attr(attrdata, self.atlasobj, mriscan, attrname) return attr
def plot_mriscan(fu, mriscan):
netname = 'bold_net'
print(mriscan)
net = fu.nets.load(mriscan, netname)
netfilepath = fu.nets.loadfilepath(mriscan, netname)
netfiledir = os.path.dirname(netfilepath)
atlasobj = fu.atlasobj
#attr = netattr.Attr(0.5*np.ones(atlasobj.count), atlasobj)
mean = np.mean(net.data, axis=0)
attr = netattr.Attr(mean, atlasobj)
outfilepath = os.path.join(netfiledir, netname + '_circos')
title = '{}\n{}'.format(mriscan, netname)
p = braincircos.CircosPlot(net, attr, title, outfilepath)
p.plot()
def get_static_attr(self, scan, atlas_name, feature, comment={}):
""" Return to an attr object directly """
query = dict(scan=scan, comment=comment)
col = self.getcol(atlas_name, feature)
count = self.sadb[col].count_documents(query)
if count == 0:
raise NoRecordFoundException(scan + atlas_name + feature)
elif count > 1:
raise MultipleRecordException(scan + atlas_name + feature)
else:
AttrData = pickle.loads(self.sadb[col].find_one(query)['value'])
atlasobj = atlas.get(atlas_name)
attr = netattr.Attr(AttrData, atlasobj, scan, feature)
return attr
def get_attr(self, scan, atlas_name, feature, comment_dict={}):
#return to an attr object directly
if self.exist_static(scan, atlas_name, feature, comment_dict):
binary_data = self.query_static(scan, atlas_name, feature,
comment_dict)[0]['value']
attrdata = pickle.loads(binary_data)
atlasobj = atlas.get(atlas_name)
attr = netattr.Attr(attrdata, atlasobj, scan, feature)
return attr
else:
print(
"can't find the document you look for. scan: %s, atlas: %s, feature: %s."
% (scan, atlas_name, feature))
raise NoRecordFoundException(scan)
return None
ChanggungPatientNets = io_utils.loadSpecificNets(
mmdps_locale.ChanggungAllFullPath,
atlasobj,
subjectList=os.path.join(mmdps_locale.ChanggungRootPath,
'CS_subjects.txt'))
ChanggungHealthyNets = io_utils.loadSpecificNets(
mmdps_locale.ChanggungAllFullPath,
atlasobj,
subjectList=os.path.join(mmdps_locale.ChanggungRootPath,
'normal_subjects.txt'))
sig_connections = stats_utils.filter_sigdiff_connections_Bonferroni(
ChanggungPatientNets, ChanggungHealthyNets)
sigDiffNet = netattr.Net(np.zeros((atlasobj.count, atlasobj.count)), atlasobj)
for conn in sig_connections:
sigDiffNet.data[conn[0], conn[1]] = 1
title = 'CS_signet'
outfilepath = 'E:/Results/CS_signet/test.png'
builder = braincircos.CircosPlotBuilder(atlasobj, title, outfilepath)
builder.add_circoslink(braincircos.CircosLink(sigDiffNet))
builder.add_circosvalue(
braincircos.CircosValue(
netattr.Attr(np.random.uniform(size=atlasobj.count), atlasobj)))
builder.customizeSize('0.80', '10p')
builder.plot()
atlasobj = atlas.get('brodmann_lrce')
# subject_list = ['tanenci_20170601', 'tanenci_20170706', 'tanenci_20170814', 'tanenci_20170922', 'tanenci_20171117']
subject_list = [
'wangwei_20171107', 'wangwei_20171221', 'wangwei_20180124',
'wangwei_20180211', 'wangwei_20180520'
]
# subject_list = ['xiezhihao_20180416', 'xiezhihao_20180524']
# load in the given subject's net
net1 = netattr.Net(
loadsave.load_csvmat('Y:/BOLD/%s/brodmann_lrce/bold_net/corrcoef.csv' %
subject_list[0]), atlasobj)
wd1 = netattr.Attr(
loadsave.load_csvmat(
'Y:/BOLD/%s/brodmann_lrce/bold_net_attr/inter-region_wd.csv' %
subject_list[0]), atlasobj)
# net1.data = abs(net1.data)
net2 = netattr.Net(
loadsave.load_csvmat('Y:/BOLD/%s/brodmann_lrce/bold_net/corrcoef.csv' %
subject_list[-1]), atlasobj)
wd2 = netattr.Attr(
loadsave.load_csvmat(
'Y:/BOLD/%s/brodmann_lrce/bold_net_attr/inter-region_wd.csv' %
subject_list[-1]), atlasobj)
# net2.data = abs(net2.data)
net1, net2, ratio = all_neg(net1, net2)
net2.data -= net1.data
# net2.data = abs(net2.data) - abs(net1.data)
def run_feature(self, feature_name, feature_config):
"""
Override super run_feature.
Stores csv files to MongoDB directly
"""
if feature_config['file_type'] != '.csv':
# only supports csv features
return
in_file_list, out_file_list = self.get_feature_file_path(feature_config)
if self.is_dynamic and feature_config['modal'] == 'BOLD':
if len(in_file_list) < 1:
print('==Not Exist:', self.mriscan, self.atlasname, feature_name)
return
if feature_name.find('net') != -1:
feature = netattr.DynamicNet(None, self.atlasname, self.dataconfig['dynamic']['window_length'], self.dataconfig['dynamic']['step_size'], scan = self.mriscan, feature_name = feature_name)
for file in in_file_list:
feature.append_one_slice(load_csvmat(file))
try:
self.mdb.save_dynamic_network(feature)
except mongodb_database.MultipleRecordException:
if self.force:
# delete and overwrite
self.mdb.remove_dynamic_network(self.mriscan, self.dataconfig['dynamic']['window_length'], self.dataconfig['dynamic']['step_size'], self.atlasname)
self.mdb.save_dynamic_network(feature)
else:
print('!!!Already Exist: %s %s %s. Skipped' % (self.mriscan, self.atlasname, feature_name))
else:
feature = netattr.DynamicAttr(None, self.atlasname, self.dataconfig['dynamic']['window_length'], self.dataconfig['dynamic']['step_size'], scan = self.mriscan, feature_name = feature_name)
for file in in_file_list:
feature.append_one_slice(load_csvmat(file))
try:
self.mdb.save_dynamic_attr(feature)
except mongodb_database.MultipleRecordException:
if self.force:
# delete and overwrite
self.mdb.remove_dynamic_attr(self.mriscan, feature_name, self.dataconfig['dynamic']['window_length'], self.dataconfig['dynamic']['step_size'], self.atlasname)
self.mdb.save_dynamic_attr(feature)
else:
print('!!!Already Exist: %s %s %s. Skipped' % (self.mriscan, self.atlasname, feature_name))
elif self.is_dynamic:
# dynamic but not BOLD feature
return
else:
# not dynamic
for file in in_file_list:
if not os.path.isfile(file):
print('==Not Exist:', self.mriscan, self.atlasname, feature_name)
continue
if feature_name.find('net') != -1:
feature = netattr.Net(load_csvmat(file), self.atlasname, self.mriscan, feature_name)
else:
feature = netattr.Attr(load_csvmat(file), self.atlasname, self.mriscan, feature_name)
try:
self.mdb.save_static_feature(feature)
except mongodb_database.MultipleRecordException:
if self.force:
# delete and overwrite
self.mdb.remove_static_feature(self.mriscan, self.atlasname, feature_name)
self.mdb.save_static_feature(feature)
else:
print('!!!Already Exist: %s %s %s. Skipped' % (self.mriscan, self.atlasname, feature_name))
from mmdps.util import loadsave
from mmdps.vis.bnv import gen_matlab, get_mesh
import numpy as np
# load in the given subject's attributes
atlasobj = atlas.get('brodmann_lrce')
subject_list = [
'tanenci_20170601', 'tanenci_20170706', 'tanenci_20170814',
'tanenci_20170922', 'tanenci_20171117'
]
# subject_list = ['wangwei_20171107', 'wangwei_20171221', 'wangwei_20180124', 'wangwei_20180211', 'wangwei_20180520']
# subject_list = ['xiezhihao_20180416', 'xiezhihao_20180524']
for i in range(0, len(subject_list)):
attr1 = netattr.Attr(
loadsave.load_csvmat(
'Y:/BOLD/%s/brodmann_lrce/bold_net_attr/inter-region_wd.csv' %
subject_list[i - 1]), atlasobj)
# prepare BNV node file
atlasobj.bnvnode.change_value(attr1.data)
atlasobj.bnvnode.change_modular([int(d) for d in (attr1.data > 0)])
atlasobj.bnvnode.write(
'E:/Changgung works/jixieshou_20180703/%s/%s %d node.node' %
(subject_list[i].split('_')[0], subject_list[i].replace('_',
' '), i + 1))
mstr = gen_matlab(
'E:/Changgung works/jixieshou_20180703/%s/%s %d node.node' %
(subject_list[i].split('_')[0], subject_list[i].replace(
'_', ' '), i + 1), '', 'abc',
'E:/Changgung works/jixieshou_20180703/%s/%s %d node.png' %
(subject_list[i].split('_')[0], subject_list[i].replace('_',
import csv
from mmdps.proc import netattr, atlas, job
from mmdps.util import loadsave
from mmdps.vis.bnv import gen_matlab, get_mesh
import numpy as np
# load in the given subject's attributes
atlasobj = atlas.get('brodmann_lrce')
subject_list = [
'tanenci_20170601', 'tanenci_20170706', 'tanenci_20170814',
'tanenci_20170922', 'tanenci_20171117'
]
# subject_list = ['wangwei_20171107', 'wangwei_20171221', 'wangwei_20180124', 'wangwei_20180211', 'wangwei_20180520']
attr1 = netattr.Attr(
loadsave.load_csvmat(
'Y:/BOLD/xiezhihao_20180416/brodmann_lrce/bold_net_attr/inter-region_wd.csv'
), atlasobj)
attr2 = netattr.Attr(
loadsave.load_csvmat(
'Y:/BOLD/xiezhihao_20180524/brodmann_lrce/bold_net_attr/inter-region_wd.csv'
), atlasobj)
attr2.data -= attr1.data
# prepare BNV node file
atlasobj.bnvnode.change_value(attr2.data)
atlasobj.bnvnode.change_modular([int(d) for d in (attr2.data > 0)])
atlasobj.bnvnode.write(
'E:/Changgung works/jixieshou_20180703/xiezhihao/xiezhihao 21 node.node')
mstr = gen_matlab(
'E:/Changgung works/jixieshou_20180703/xiezhihao/xiezhihao 21 node.node',
