sedipack 0.0.1

A Sedimentology package for Grain Statistics and Plots.

Sedipack

This is a simple package that is created to provide support to earth scientist and earth engineers (students in particuar).

This package seeks to help create an open-source solution to grain-size statistical analysis, and the production of grain plots.

Sedi pack is born out of the problems faced during the earlier days of the my Senior year project.

The Problem I faced was: Software and Activation Keys which is or was expensive to get.

After Which I then thought to my self why was there no existing way to do it in python. Then I went to work.

Available Functions.

The Package comprises of 4 Houses of serveral functions.

1. GrainPreprocess.
2. GrainViz.
3. GrainStasDes.
4. GrainDataTables.

Functions and Methods Available.

There are about 14 functions/method that vcan be called and returns various data points.

1. GrainPreprocess: has four calls that can be made. which are

• MM_to_Phi()

• Bed_To_100()

• CummulateBed()

• Percentiles()

2. GrainViz: houses serveral calls which are

• DataFrame()

• DataFrame_PhiPercentiles()

• DataPlot()

3. GrainStatsDes: houses several calls which are

• GraphicMean()

• GraphicStandard_Dev()

• GraphicSkewness()

• GraphicKurtosis()

4. GrainDataTables: houses several call which are

• BedData()

• CompleteBeds()

• SaveBeds()

Which call contains a docstring which contains information on how to use it.

How to use this package.

To use the function present in this package, the package has to be installed and that can be done with pip install sedipack.

Then importing the functionalities needed,

`from sedipack.grainpreprocess import GrainPreprocess

from sedipack.grainviz import GrainViz

from sedipack.grainstats import GrainStatsDes

from sedipack.grainstatsdata import GrainDataTables`

Once this has been done then you can initialize the import, viz = GrainViz() Then all other functionality can be gotten with a dot call. viz.DataPlot().

Using viz.infohelp() provides info about the type of functionality present and each method contains docstrings showing both inputs and outputs.

Acknowledgements

I will like to also acknowledge the input of mentors and friends in this project.

1. Olawale Ibrahim (Machine Learning Engineer & The Author of Petroeval) & Emmanuel Jolaiya ( Machine Learning Engineer & The Author of rsgis and the Famous GISBOT on Twitter)

2. You for using and reading this, Thank you.

Thank you all.

Philip Ireoluwa Okiokio