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app-template

Common conventions for building applications on the GeoDeepDive infrastructure

awesome-open-geoscience

Curated from repositories that make our lives as geoscientists, hackers and data wranglers easier or just more awesome

badlands

Basin and Landscape Dynamics model

corebreakout

Segmentation and depth-alignment of geological core sample image columns via Mask-RCNN

crudeaudacitymaps

"Geospatial mapping in python" webinar for Crude Audacity podcast

cs61a

Assignments/labs/projects for cs61a done by me

cs61a-1

This is my repository for labs, homework or projects when going through the course, CS 61A, from U.C. Berkeley.

cs61a_sp20

CS61A - Structure and Interpretation of Computer Programs, Spring 2020

earthsurface

Landscape evolution, deltaic systems, stratigraphy

lobyte3db

mines-erds

"Data Science: Earth Resources" graduate certificate at Colorado School of Mines

nolineartimeseriesanalysis

The codes in the toolbox can be used to perform nonlinear time series analysis on single(or multi) channel data. This is done by mapping the single channel data to phase space representation using Taken's embedding theorem (compute_psv.m). The parameters - optimal delay and dimension are estimated using first minimum of MI (compute_tau.m) and FNN method (compute_dim) respectively. The recurrence network can be constructed from the phase space vector using ComputeRecurrenceNetwork_ANN.m or ComputeRecurrenceNetwork_fixedRR.m. The topology of the RN can be further analysed using graph theoreticl quantifiers (you need BCT toolbox for this). One can also compute the complexity-entrropy plane using get_mpr_complexity.m for which the ordinal patterns are computed using get_ordinal_pattern_dist.m (see the function descp for more details). Also, the tool box contains python codes to generate variety of uni(or multi) variate surrogate data.

nolitsa

A Python module implementing some standard algorithms used in nonlinear time series analysis

stratstat

A R-based digitizer that is used to discretize hand-drawn stratigraphic sections/core logs into a numerical format for use in statistical analysis, visualization, or prediction of sedimentary strata.

trilium

Build your personal knowledge base with Trilium Notes

twitanalysis

Twitter analysis