This is the class and function reference of catch22. Please refer to the user guide for further details as the class and function specifications may not be sufficient to give full context.
catch22_all
Automatically run every time series feature calculation included in the catch22/24 set.
[featureValues, featureNamesLong, featureNamesShort] = catch22_all(data, doCatch24) returns a 24x1 array of feature outputs, a 24x1 array of long feature names and 24x1 array of short feature names for the input time series, data.
Examples
Compute catch22 features
Compute catch22 features on a Gaussian i.i.d. random number sequence.
tsData = rand(100, 1) % data as a column vector% compute catch22 features[featureValues, featureNamesLong, featureNameShort] = catch22_all(data, false)% compute cactch24 features[featureValues, featureNamesLong, featureNameShort] = catch22_all(data)
Input Arguments
data - time series as column vector
Input univariate time series, specified as a column vector.
Data Types: double
doCatch24 - Include Mean and Std. Deviation
Whether to include mean and standard deviation (a total of 24 features). Default is true.
Data Types: logical
Output Arguments
featureValues
Computed feature values for the input data.
Data Type: cell array
featureNamesLong
Long feature names corresponding to the feature values.
Data Type: cell array
featureNamesShort
Short feature names corresponding to the feature values.
Data Type: cell array
GetAllFeatureNames
Get all feature names for the catch22/24 feature set.
[featureNamesLong, featureNamesShort] = GetAllFeatureNames(doCatch24) retrieves all feature names for the catch22 (or catch24) feature set.
Examples
Retrieve catch22/24 feature names
% get catch24 feature names[featureNamesLong24,featureNamesShort24] = GetAllFeatureNames(true)% get catch22 feature names[featureNamesLong22,featureNamesShort22] = GetAllFeatureNames(false)
Input Arguments
doCatch24
Whether to include mean and standard deviation as features. Default is true.
Data Types: logical
Output Arguments
featureNamesLong
Long feature names corresponding to the feature values.
Data Type: cell array
featureNamesShort
Short feature names corresponding to the feature values.
Data Type: cell array
catch22_DN_HistogramMode_5
Measures the mode of the data vector using histogram with 5 bins.
Note: This is a typical example of how an individual feature method is called. All features are called in this way and accept the same data types as inputs while returning the same data types as outputs. You can call each feature individually using its corresponding long name as per the table of features, e.g., catch22_CO_f1ecac.
Syntax
% individual feature method of interest, e.g., DN_HistogramMode_5featureVal = catch22_DN_HistogramMode_5(data)
Description
featureVal = catch22_DN_HistogramMode_5(data) computes the mode of the data vector using a histogram with 5 bins.
Examples
Compute DN_HistogramMode_5 for time series
tsData = rand(1, 100) % time series as a row vectorfeatureVal = catch22_DN_HisogramMode_5(tsData)
Input Arguments
data - time series row vector
Input univariate time series, specified as a row vector.
Data Types: double
Output Arguments
featureVal - feature output
Output corresponding to the feature method.
Data Type: double
Note: All catch22/24 feature methods expect the same input arguments (and data types) and return the same output arguments (and data types).
