provides modules to read and perform analysis of a time series data
Project description
This package provides some subpackages containing classes and functions to analyze time series data.
“time_series_analysis” package contains four main classes
1) data_reader.py: Contains DataReader class that reads in a time series data from a flat file Data should be in multiple rows per time step data could contain 1 or more columns that evolves in time
2) data_analysis.py: Contains DataAnalysis class that inherits reader from DataReader Contains functions to compute mean, standard deviation, Contains function to plot time tracy along any dimension
3) convergence_analysis.py: Contains function to test convergence using samples along time to test if mean vary Can test convergence along one or all dimensions
4) auto_correlation.py: Contains AutoCorrelation class that inherits DataReader Computes autocorrelation along one or several dimension and reports correlation along time
“test” package Contains unit test of the above classes
For example these tests could be run as follows: python -m unittest test.test_data_reader.py
“example” package: contains worked out examples
“example.py” demonstrates how to perform autocorrelation using this tool on a n*m time series data where, “n” are samples observed in time and “m” is the dimension of the data the code handles 1 to “n” higher dimensional data
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