示例#1
0
period = 0.00048828125  #s

#Put the data into a TimeSeriesRegion datatype
white_matter = connectivity.Connectivity()
tsr = TimeSeriesRegion(connectivity=white_matter,
                       data=data,
                       sample_period=period)
tsr.configure()

#Create and run the analyser
pca_analyser = pca.PCA(time_series=tsr)
pca_data = pca_analyser.evaluate()

#Generate derived data, such as, compnent time series, etc.
pca_data.configure()

#Put the data into a TimeSeriesSurface datatype
component_tsr = TimeSeriesRegion(connectivity=white_matter,
                                 data=pca_data.component_time_series,
                                 sample_period=period)
component_tsr.configure()

#Prutty puctures...
tsi = timeseries_interactive.TimeSeriesInteractive(time_series=component_tsr)
tsi.configure()
tsi.show()

if IMPORTED_MAYAVI:
    xmas_balls(tsr.connectivity, pca_data.weights[:, 0, 0, 0], edge_data=True)
##----------------------------------------------------------------------------##
##-               Plot pretty pictures of what we just did                   -##
##----------------------------------------------------------------------------##

#Make the lists numpy.arrays for easier use.
LOG.info("Converting result to array...")
TAVG_TIME = numpy.array(tavg_time)
BOLD_TIME = numpy.array(bold_time)
BOLD = numpy.array(bold_data)
TAVG = numpy.array(tavg_data)

#Create TimeSeries instance
tsr = TimeSeriesRegion(data=TAVG, time=TAVG_TIME, sample_period=2.)
tsr.configure()

#Create and run the monitor/analyser
bold_model = bold.BalloonModel(time_series=tsr)
bold_data = bold_model.evaluate()

bold_tsr = TimeSeriesRegion(connectivity=white_matter,
                            data=bold_data.data,
                            time=bold_data.time)

#Prutty puctures...
tsi = timeseries_interactive.TimeSeriesInteractive(time_series=bold_tsr)
tsi.configure()
tsi.show()

###EoF###
示例#3
0
文件: fusion.py 项目: govtmirror/lsnm
    imshow(ss[timesteps,:,:], vmin=0, vmax=1, cmap='hot')
    
    subplot(3,4,7)
    imshow(fs[timesteps,:,:], vmin=0, vmax=1, cmap='hot')
    
    subplot(3,4,11)
    imshow(fd1[timesteps,:,:], vmin=0, vmax=1, cmap='hot')
    
    subplot(3,4,4)
    imshow(fd2[timesteps,:,:], vmin=0, vmax=1, cmap='hot')
    
    subplot(3,4,8)
    imshow(fr[timesteps,:,:], vmin=0, vmax=1, cmap='hot')
    
stimesteps.on_changed(update)


########## NOW DISPLAY TVB SIMULATED NEURAL ACTIVITY ##################
plot_connectivity(white_matter)

white_matter.display_name = 'default'
tsr = tvb.datatypes.time_series.TimeSeriesRegion(data = RAW,
                                                 connectivity=white_matter)
tsr.configure()

tsi = ts_int.TimeSeriesInteractive(time_series=tsr)

tsi.configure()

tsi.show()