Miscellaneous Plugins

Bin

The bin plugin group elements of a single data vector into bins of a specified size. The value of each bin is the mean of the elements belonging to the bin. For example, if the bin size is 3, and the input vector is [9,2,7,3,4,74,5,322,444,2,1], then the outputted bins would be [6,27,257]. Note that any elements remaining at the end of the input vector that do not form a complete bin (in this case, elements 2 and 1), are simply discarded.

Inputs

Input Vector (vector): The vector to bin.
Bin Size (scalar): The size (# of elements) to have in each bin.

Outputs

Bins (vector): The array of means for each bin.

Binned Map

The binned map can generate a surface count or plot of a two-variable function.

Settings

X,Y,Z (vector): X/Y vectors are used to specify values of the two independent variables in a function, and Z vector specifies the values of the dependent variable.
X/Y Binning: From/To (scalar): Specify the range of X/Y values.
Num X/Y bins (scalar): Specify the number of resolution grid for the output binned map.

Outputs

Binned Map (matrix): Binned Map is a matrix whose entries can be used to generate the surface contour plot of the Z vector.
Hits Map (matrix): Hits Map is a matrix whose values are specified by the number of points in each X/Y bin, and the image of Hits Map indicates the positions where Z values have been located in the X/Y plane.

Chop

The chop plugin takes an input vector and divides it into two vectors. Every second element in the input vector is placed in one output vector, while all other elements from the input vector are placed in another output vector.

Inputs

Array (vector): The array of values to perform the chop on.

Outputs

Odd Array (vector): The array containing the odd part of the input array (i.e. it contains the first element of the input array).
Even Array (vector): The array containing the even part of the input array (i.e. it does not contain the first element of the input array).
Difference Array (vector): The array containing the elements of the odd array minus the respective elements of the even array.
Index Array (vector): An index array has the same length as the other three output arrays.

Convert time

The Convert time plugin converts a vector from one time format to another:

Inputs

Input vector

The vector holding the time values to be converted.

Input time format (scalar)

The time format of the values in the input vector. The formats are:
0: standard C time
1: TAI
2: JD
3: MJD
4: RJD
5: JY
6: TAI (ns)
7: TAI (2^-16 sec)

Output time format (scalar)

The time format for the values in the output vector. The formats are the same as for the input time format.

Outputs

Output vector: The vector holding the converted time values, which will be the same size as the input vector.

Noise Addition

The Noise addition plugin adds a Gaussian random variable to each element of the input vector. The Gaussian distribution used has a mean of 0 and the specified standard deviation. The probability density function of a Gaussian random variable is:

Inputs

Array (vector): The array of elements to which random noise is to be added.
Sigma (scalar): The standard deviation to use for the Gaussian distribution.

Outputs

Output Array (vector): The array of elements with Gaussian noise added.

Normalization (Standard score)

This plugin subtracts the mean from the input vector and divides by the standard deviation.

Inputs

Vector In: The vector to normalize

Outputs

Vector Out: Output the original vector after normalizing.

Phase

This plugin calculates the phase value for each data point of an input time array.

Inputs

Time Array (vector): An array of time values
Data In Array (vector): Input data array corresponding to the time array
Period (scalar): Set the period of the input time array.
Zero Phase (scalar): Set the time for the zero phase.

Outputs

Phase Array (vector): An array of phase values corresponding to the input data values.
Data Out Array (vector): Output the original data set with values sorted by the phase array.

Reverse

This plugin reverses the input vector.

Inputs

InputVector: The vector to reverse.

Outputs

Output Vector: The reversed vector.

Shift

This plugin shifts the plot of an input vector forwards or backwards on the X axis.

Inputs

InputVector: The vector to shift.
Shift value(#points, negative allowed) (scalar): Specify the units to be shifted. Positive shifted value results right or forward shift. Negative shifted value results left or backwards shift.

Outputs

ShiftedVector: Output the original vector after shifting by the units indicated above.

Statistics

The statistics plugin calculates statistics for a given data set beyond those automatically calculated by Kst. Most of the output scalars are named such that the values they represent should be apparent. Standard formulae are used to calculate the statistical values.

Inputs

Data Array (vector): The array of data whose statistic values needed to be calculated.

Outputs

Mean (scalar): The mean of the data values.
Minimum (scalar): The minimum value found in the data array.
Maximum (scalar): The maximum value found in the data array.
Variance (scalar): The variance of the data set.
Standard deviation (scalar): The standard deviation of the data set.
Median (scalar): The median of the data set.
Absolute deviation (scalar): The absolute deviation of the data set.
Skewness (scalar): The skewness of the data set.
Kurtosis (scalar): The kurtosis of the data set.

Syncbin

This plugin groups y values of a data set into bins defined by x values.

Inputs

X in (vector): The X values of a set of data points
Y in (vector): The Y values of a set of data points
Number of Bins (scalar): Specify the number of bins used to group the data points
X min/X max (scalar): Specify min/max X values of a data set to indicate the range of data points needed to be grouped.

Outputs

X out (vector): The X values after binning. The X out vector is composed of the median values of the X elements in each bin
Y out (vector): The Y values after binning. The Y out vector is composed of the mean values of the Y elements in each bin
Y error (vector): This vector is composed of the standard deviations of the Y values in each bin.
N (vector): The N vector is composed of the number of data points in each bin.