Package 'SUSY'

susy to data.frame conversion method

Description

Turns susy class object into a data.frame.

Usage

## S3 method for class 'susy'
as.data.frame(x, row.names=NULL, optional=FALSE, corr.no.abs=TRUE, ...)

Arguments

x	A susy object.
row.names	Ignored, only for consistency to generic as.data.frame method.
optional	Ignored, only for consistency to generic as.data.frame method.
corr.no.abs	Logical, defaults to TRUE display correlation without the absolute value.
...	Ignored.

Value

Returns data.frame.

See Also

susy

Examples

n = 1000
data = data.frame(
  var1 = runif(n, 300, 330),
  var2 = runif(n, 300, 330)
)
res = susy(data, segment=30L, Hz=15L)
as.data.frame(res)

---

susy plot method

Description

Generate plot(s) for a susy object.

Usage

## S3 method for class 'susy'
plot(x, type=c(4, 5), ...)

Arguments

x	A susy object.
type	Numeric, specifies the types of plot, defaults to c(4, 5). GMcrosscorrs synchrony by segments GM-Z time series plot Z not abs
...	Ignored.

Details

Method can generate multiple types of plots by providing numeric vector to type argument. Note it will generate plots for each pair (cross computation) in x, so the final number of plots is length(x) * length(type).

Value

Returns NULL invisibly. Generate plot(s) as a side effect.

See Also

susy

Examples

n = 1000
data = data.frame(
  var1 = runif(n, 300, 330),
  var2 = runif(n, 300, 330),
  var3 = runif(n, 300, 330)
)
res = susy(data, segment=30L, Hz=15L, permutation=TRUE)
plot(res, type=c(3,5))

---

susy print method

Description

Prints information about an susy object.

Usage

## S3 method for class 'susy'
print(x, corr.no.abs=TRUE, legacy=FALSE, ...)

Arguments

x	A susy object.
corr.no.abs	Logical, defaults to TRUE display correlation without the absolute value.
legacy	Logical, defaults to FALSE, when TRUE print will produce an output that matches the output of legacy SUSY implementation.
...	Extra arguments passed to print.data.frame method.

Value

Returns x invisibly. Display output to console as a side effect.

See Also

susy

Examples

n = 1000
data = data.frame(
  var1 = runif(n, 300, 330),
  var2 = runif(n, 300, 330)
)
res = susy(data, segment=30L, Hz=15L)
res
print(res, corr.no.abs=FALSE)
print(res, digits=4)
print(res, legacy=TRUE)

---

Surrogate Synchrony

Description

Cross-correlations of two time series are computed up to a specific lag in seconds maxlag. Cross-correlation is done within segment of the time series. The size of segments segment can be chosen in seconds. Aggregation is then performed by transforming correlations to Fisher's Z, computing mean Z in each segment, then across all segments of the time series. Segment shuffling is used to create surrogate time series, on which the same computations are run. This provides effect sizes ES. SUSY provides these different synchrony measures for each twin time series: mean Z and ES of mean Z; mean absolute_Z and ES of mean absolute_Z.

Usage

susy(x, segment, Hz, maxlag=3L, permutation=FALSE,
  restrict.surrogates=FALSE, surrogates.total=500)

Arguments

x	A data.frame of numeric columns.
segment	Integer, size in seconds. Must not be smaller than 2 * maxlag, must not be larger than half the the time series (nrow(x)/2).
Hz	Integer, frames per second (sampling rate).
maxlag	Integer, maximum lag for ccf in seconds. Default 3 seconds.
permutation	Logical, default FALSE requires x to have even number of columns which are processed in pairs (1-2, 3-4, etc.). When permutation is TRUE then function computes all pairs combinations between columns provided in x (n*(n-1)/2 pairs).
restrict.surrogates	Logical, default FALSE. Restrict the number of surrogates or not.
surrogates.total	Numeric, the number of generated surrogates, default 500. Ignored when restrict.surrogates is FALSE (default).

Details

Segments are non-overlapping, and the number of segments that fit into the time series may have a remainder (usually a few seconds at the end of the time series), which is not considered.

Value

Object of class susy is returned. Each cross correlation pair is an element in resulting object.

See Also

plot.susy, as.data.frame.susy, print.susy

Examples

n = 1000
data = data.frame(
  var1 = runif(n, 300, 330),
  var2 = runif(n, 300, 330),
  var3 = runif(n, 300, 330)
)

## use only first two columns
res = susy(data[, 1:2], segment=30L, Hz=15L)
length(res)
names(res)

## use all columns and permutation
res = susy(data, segment=30L, Hz=15L, permutation=TRUE)
length(res)
names(res)

## print susy
res
print(res, legacy=TRUE)

## plot susy
plot(res)
plot(res, type=1:2)

---