Application software for applying the Second-order tensor statistical proposal of Jelínek (1978).
Application software in Python 3 to apply the statistical proposal of Jelínek (1978) for a sample of several second-order tensors in order to obtain the mean tensor of the sample, its principal values with their confidence intervals, and the principal directions with their confidence regions.
This application program is able to plot the summary of the statistical model described above in a stereographic projection for a better understanding of the outcomes. Provided that, the next picture represents the aim of jelinekstat.
Open source and free software: BSD-2-Clause.
The code was written in Python 3. The packages numpy, scipy, matplotlib and mplstereonet are required for using jelinekstat. All of them are downloadable from the PyPI repository by opening a terminal and typing the following code lines:
pip install numpy pip install scipy pip install matplotlib pip install mplstereonet
To install jelinekstat open a terminal and type:
pip install jelinekstat
To produce the plot shown above execute the following script
from jelinekstat.jelinekstat import tensorStat # Input data sample = [[1.02327, 1.02946, 0.94727, -0.01495, -0.03599, -0.05574], [1.02315, 1.01803, 0.95882, -0.00924, -0.02058, -0.03151], [1.02801, 1.03572, 0.93627, -0.03029, -0.03491, -0.06088], [1.02775, 1.00633, 0.96591, -0.01635, -0.04148, -0.02006], [1.02143, 1.01775, 0.96082, -0.02798, -0.04727, -0.02384], [1.01823, 1.01203, 0.96975, -0.01126, -0.02833, -0.03649], [1.01486, 1.02067, 0.96446, -0.01046, -0.01913, -0.03864], [1.04596, 1.01133, 0.94271, -0.01660, -0.04711, -0.03636]] confLevel = 0.95 # Performing the calculation all in one function. jelinekStatsSummary, stereonetPlot = tensorStat( sample, confLevel=0.95, want2plot=True, plotName='tes', ext='pdf') stereonetPlot.show()
Jelínek, V (1978). Statistical processing of anisotropy of magnetic susceptibility measured on group of specimens. Studia Geophysica et Geodaetica, 22 (1), pp. 50-62.
First release on PyPI.
Documentation and the examples directory were completely adjusted.
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