Basic Statistics¶
Introduction¶
Blah.
API¶
-
hsltools.Basics.basic_all_features(signal, name) Returns signal_statistics of the signal in the form of a labeled data frame.
- Parameters
signal (array-like) – Array containing numbers whose basic statistics are desired.
- Returns
Returns a data frame of basic statistics with column headings [mean, std, skewness, kurtosis, maximum, minimum, iqr, variation, entropy, corrtime] (see signal_statistics).
- Return type
DataFrame
-
hsltools.Basics.scaled_correlation_time(signal1, signal2) Returns the scaled correlation time of the signal.
- Parameters
signal1 (array-like) – Array containing numbers whose correlation time is desired.
signal2 (array-like) – Array containing numbers whose correlation time is desired.
- Returns
Returns the scaled correlation time of the signals.
- Return type
ndarray of ints
-
hsltools.Basics.signal_statistics(signal) Returns an array containing basic statistics of the signal (mean, standard deviation, skewness, kurtosis, maximum, minimum, interquartile range, variation, entropy, scaled correlation time).
- Parameters
signal (array-like) – Array containing numbers whose basic statistics are desired.
- Returns
Returns array of basic statistics [mean, std, skewness, kurtosis, maximum, minimum, iqr, variation, entropy, corrtime].
mean - mean of the signal std - standard deviation of the signal skewness - imbalance and asymmetry from the mean computed as the Fisher-Pearson coefficient of skewness kurtosis - sharpness of the peak of a frequency-distribution curve maximum - maximum value of the signal minimum - minimum value of the signal iqr - interquartile range, statistical dispersion as the diffrence betwen the upper and lower quartiles variation - ratio of the biased standard deviation to the mean entropy - measure of uncertainty using Shannon entropy corrtime - see scaled_correlation_time
- Return type
ndarray