def TBV_value_extractor(TBVip,voi,ctr,outdir,basename):
"""
This function extracts the tvalues from data loaded in TBV and save them
as binary files.
Up to this date there is no possibility to extract the beta values.
Parameters
----------
TBVip : string
IP index to access the TBV processed data. When TBV is running on the
same machine please use 'localhost'
voi : integer
A value ranging from 0 to infinite. It indicates the index of the ROI
used in analysis.
ctr : integer
A value ranging from 0 to infinite. It indicates the index of the
contrast of interest. The contrast can be defined manually using a .ctr
file or it can be defined automatically by TBV. Usually the contrast
'0' corresponds to the map 'first predictors vs. baseline'.
outdir : string
The directory for the output files.
basename : string
Basename for the outputs.
Returns
-------
None.
"""
TBV = tbvnetworkinterface.TbvNetworkInterface(TBVip,55555)
if TBV.get_current_time_point()[0] == TBV.get_expected_nr_of_time_points()[0]:
print('Extracting t-values...')
#coordinates of voxels of the roi
coord_roi_voxels = np.array(TBV.get_all_coords_of_voxels_of_roi(voi)[0])
tvals = np.array([TBV.get_map_value_of_voxel(voi,coord)[0]
for coord in coord_roi_voxels]).reshape(-1,1)
output_tval = np.concatenate((coord_roi_voxels,tvals),axis=1)
print('Saving t-vals data...')
with open(os.path.join(outdir,basename+'_voi'+str(voi)+'.tvals'), 'w') as outfile:
np.savetxt(outfile, output_tval)
print('Everything have been estimated! Goodbye!')
#load properties in the just created rtRSAObj
#the config.json file can be created by using one of the class method
#the file si wirtten after the estimation of the RS
rtRSAObj.load(sub_json_file)
print('rtRSA ready!\n')
print('Nr of voxels: ', +len(rtRSAObj.func_coords))
print('Base stimuli name:')
print(rtRSAObj.conditions)
#%%############################################################################
# TBV interface settings #
###############################################################################
#create an instance to access TBV via network plugin
TBV = tbvnetworkinterface.TbvNetworkInterface('localhost', 55555)
win = visual.Window(fullscr=False,
color='gray',
screen=0,
size=(1024, 768),
colorSpace='rgb255')
#creation of the cue for the image
image = visual.ImageStim(win,
image=None,
mask=None,
units='pix',
pos=(0.0, 0.0),
size=600,
ori=0.0,