analysis.correlation¶
Classes¶
CorrelationAnalyzer
¶

class
nitime.analysis.correlation.
CorrelationAnalyzer
(input=None)¶ Bases:
nitime.analysis.base.BaseAnalyzer
Analyzer object for correlation analysis. Has the same API as the CoherenceAnalyzer
Attributes
Methods

__init__
(input=None)¶ Parameters: input : TimeSeries object
Containing the data to analyze.
Examples
>>> np.set_printoptions(precision=4) # for doctesting >>> t1 = ts.TimeSeries(data = np.sin(np.arange(0, ... 10*np.pi,10*np.pi/100)).reshape(2,50), ... sampling_rate=np.pi) >>> c1 = CorrelationAnalyzer(t1) >>> c1 = CorrelationAnalyzer(t1) >>> c1.corrcoef array([[ 1., 1.], [1., 1.]]) >>> c1.xcorr.sampling_rate 3.141592653... Hz >>> c1.xcorr.t0 15.91549430915... s

corrcoef
()¶ The correlation coefficient between every pairwise combination of timeseries contained in the object

xcorr
()¶ The crosscorrelation between every pairwise combination timeseries in the object. Uses np.correlation(‘full’).
Returns: TimeSeries : the timedependent crosscorrelation, with zerolag
at time=0

xcorr_norm
()¶ The crosscorrelation between every pairwise combination timeseries in the object, where the zero lag correlation is normalized to be equal to the correlation coefficient between the timeseries
Returns: TimeSeries : A TimeSeries object
the timedependent crosscorrelation, with zerolag at time=0

SeedCorrelationAnalyzer
¶

class
nitime.analysis.correlation.
SeedCorrelationAnalyzer
(seed_time_series=None, target_time_series=None)¶ Bases:
object
This analyzer takes two timeseries. The first is designated as a timeseries of seeds. The other is designated as a timeseries of targets. The analyzer performs a correlation analysis between each of the channels in the seed timeseries and all of the channels in the target timeseries.
Methods

__init__
(seed_time_series=None, target_time_series=None)¶ Parameters: seed_time_series : a TimeSeries object
target_time_series : a TimeSeries object

corrcoef
()¶
