METRIC Metric space analysis
Y = METRIC(X,OPTS) performs a metric space method to find the amount
of information conveyed by the spike trains in X about their
category membership. The results are stored in the structure
Y. If OPTS.shift_cost is a vector (see below), then Y will be a
vector of output structures.
The members of Y are:
Y.categories: A vector of the spike train category
indices. See METRICOPEN for details.
Y.d: The matrix of the distances between all possible spike
train pairs. See METRICDIST for details.
Y.cm: The confusion matrix resulting from clustering of the
distances. See METRICCLUST for details.
Y.table: A HIST2D structure version of the confusion
matrix. See MATRIX2HIST2D and INFO2D for details.
The options and parameters for this function are:
OPTS.start_time: The start time of the analysis window. The
default is the maximum of all of the start times in X.
OPTS.end_time: The end time of the analysis window. The
default is the minimum of all of the end times in X.
OPTS.shift_cost: The cost of shifting a spike per unit time
relative to inserting or deleting a spike. This option may
be a vector of such values. The default is
1/(end_time-start_time).
OPTS.label_cost: This applies only to data sets with
simultaneously recorded spike trains. It is the cost of
altering a spike's label, and may range from 0 to 2. This
option may be a vector of such values whose length is equal
to OPTS.shift_cost. The default is 0.
OPTS.metric_family: Selects the metric to be used.
OPTS.metric_family=0: Uses D^spike metric.
OPTS.metric_family=1: Uses D^interval metric. This is
only applicable to single-site data.
The default value is 0.
OPTS.parallel: Selects which algorithm version to
use.
OPTS.parallel=0: Computes distances for a single shift_cost,
label_cost pairs at a time.
OPTS.parallel=1: Uses an algorithm that computes the
distances for all shift_cost,label_cost pairs
concurrently. When many parameters sets are being
analyzed, this method can provide considerable
computational savings.
The default value is 0 if OPTS.shift_cost has one element
and 1 if OPTS.shift_cost has multiple elements.
OPTS.clustering_exponent: A constant that controls the
clustering. Negative values emphasize smaller distances
and positive values emphasize larger distances. The
default is -2.
Y = METRIC(X) uses the default options and parameters.
[Y,OPTS_USED] = METRIC(X) or [Y,OPTS_USED] = METRIC(X,OPTS)
additionally return the options used.
See also METRICDIST, METRICCLUST, MATRIX2HIST2D, INFO2D, METRIC_SHUF,
METRIC_JACK.
This function calls: