def eprime2dm(eprime,pppi):
import os
import re
import scipy.io as sp
import glob as gl
import numpy
import nipype.interfaces.matlab as mlab
from nipype.interfaces.base import Bunch
# convert numpy data array
def convert_numpy(ar,toString = False):
lst = []
for a in ar.tolist():
if toString:
lst.append(str(a))
elif type(a) == numpy.ndarray:
if a.size > 1:
lst.append(a.tolist())
else:
lst.append([a.tolist()])
else:
lst.append([a])
return lst
m = re.search("eprime_([a-z]+)\.txt",eprime)
sequence = m.group(1)
# get nDM. mat files
mat = os.path.join(os.path.dirname(eprime),"nDM*"+sequence+".mat")
mat = gl.glob(mat)
if len(mat) > 0:
mat = mat[0]
else:
# execute matlab script to generate nDM file
m = mlab.MatlabCommand()
m.inputs.mfile = False
m.inputs.script = sequence+"_eprime2dm_embarcs(\'"+eprime+"\');"
m.run();
# get nDM file (again)
mat = os.path.join(os.path.dirname(eprime),'nDM*.mat')
mat = gl.glob(mat)
if len(mat) > 0:
mat = mat[0]
dm = sp.loadmat(mat,squeeze_me=True)
names = convert_numpy(dm.get('names'),True)
onsets = convert_numpy(dm.get('onsets'))
durations = convert_numpy(dm.get('durations'))
# load up values and convert them
# for PPPI remove last column for reward PPI; for ert last 3 columns
# error, posterror, misc
if pppi:
trim = 3
if sequence == "reward":
trim = 1
names = names[0:(len(names)-trim)]
durations = durations[0:(len(durations)-trim)]
onsets = onsets[0:(len(onsets)-trim)]
# create bunch to return
bunch = Bunch(conditions=names,onsets=onsets,durations=durations)
if 'pmod' in dm:
pmod = []
for i in range(0,len(dm.get('pmod'))):
if dm['pmod']['name'][i].size == 0:
pmod.append(None)
else:
name = str(dm['pmod']['name'][i])
param = dm['pmod']['param'][i].tolist()
poly = dm['pmod']['poly'][i]
pmod.append(Bunch(name=[name],param=[param],poly=[poly]))
bunch.pmod = pmod
return bunch
def load_design_matrix(mat_file,trim=0):
import os
import re
import scipy.io as sp
import glob as gl
import numpy
import nipype.interfaces.matlab as mlab
from nipype.interfaces.base import Bunch
# convert numpy data array
def convert_numpy(ar,toString = False):
lst = []
for a in ar.tolist():
if toString:
lst.append(str(a))
elif type(a) == numpy.ndarray:
if a.size > 1:
lst.append(a.tolist())
else:
lst.append([a.tolist()])
else:
lst.append([a])
return lst
# if list of mat_files, then do a list
mat_files = []
if isinstance(mat_file,list):
mat_files = mat_file
else:
mat_files = [mat_file]
bunches = []
# go over mat files
for mat_file in mat_files:
# load design matrix
dm = sp.loadmat(mat_file,squeeze_me=True)
names = convert_numpy(dm.get('names'),True)
onsets = convert_numpy(dm.get('onsets'))
durations = convert_numpy(dm.get('durations'))
# load up values and convert them
# for PPPI remove last column for reward PPI; for ert last 3 columns
# error, posterror, misc
if trim > 0:
names = names[0:(len(names)-trim)]
durations = durations[0:(len(durations)-trim)]
onsets = onsets[0:(len(onsets)-trim)]
# create bunch to return
bunch = Bunch(conditions=names,onsets=onsets,durations=durations)
if 'pmod' in dm:
pmod = []
for i in range(0,len(dm.get('pmod'))):
if isinstance(dm['pmod']['name'][i],unicode) or dm['pmod']['name'][i].size == 1:
name = str(dm['pmod']['name'][i])
param = dm['pmod']['param'][i].tolist()
poly = dm['pmod']['poly'][i]
pmod.append(Bunch(name=[name],param=[param],poly=[poly]))
elif dm['pmod']['name'][i].size > 1:
names = []
params = []
polys = []
for j in range(0,dm['pmod']['name'][i].size):
names.append(str(dm['pmod']['name'][i][j]))
params.append(dm['pmod']['param'][i][j].tolist())
polys.append(dm['pmod']['poly'][i][j])
pmod.append(Bunch(name=names,param=params,poly=polys))
else:
pmod.append(None)
bunch.pmod = pmod
bunches.append(bunch)
return bunches
