Matcard's starred repositories
pyPDFtoDXF
Quick and dirty script to pull vector graphics from a PDF and export to DXF drawing files.
svg_to_dxf
Utility to convert SVG files to DXF 14 files. This code is extracted from Inkscape's extensions, and is needed by TPMS Studio for stencil generation (for converting the SVG files that TPMS Studio generates, into a format the laser cutters can use).
gempy
GemPy is an open-source, Python-based 3-D structural geological modeling software, which allows the implicit (i.e. automatic) creation of complex geological models from interface and orientation data. It also offers support for stochastic modeling to address parameter and model uncertainties.
LoopStructural
LoopStructural is an open-source 3D structural geological modelling library.
seismicmodelcompression
Model based seismic data compression
ERT-XBH-sensitivity
Matlab scripts for computing 2D and 3D sensitivity distributions for electric resistivity tomography (ERT) surface and cross-borehole (XBH) electrode configurations.
PyOctoMesh3D
3D quad mesh algorithm written in Python; uses tomographic images
RESINVM3D-mod
http://software.seg.org/2007/0001 <- playing with this
seismic-inversion
Seismic inversion
SeismicWaves
Programme de simulation de propagation d'ondes à partir de sources ponctuelles ou linéaires
Seismic_Wave_Directivity
Based on previous research, ground motion can be amplified in certain direction and show with significant anisotropy. The causes still remain unclear, and different researchers have attributed this phenomenon to several factors, including topographic effect, local geological heterogeneities, wave polarization, wave trapped in fault zone and etc. This phenomenon might have severe impacts on buildings that cause damages, especially in the near-fault area. However, the current seismic design code focus on the perpendicular direction of fault strike only, which is not suitable enough for real situation. The objective of this study will focus on seismic wave directivity in near-fault zone. A total of 104 earthquake events with basic geological data were collected. Causative factors were selected based on previous research. There are three main causes considered of free field stations, included wave polarization, anisotropic stiffness and forward directivity. Data of influence factors were collected accordingly, and Arias Intensity is used to describe the directivity of seismic wave. The deep learning technique was applied to predict Arias Intensity distribution with the given parameters. This research used TensorFlow as the main deep learning tool.
AnisotroPy
Toolkit for the study of seismic anisotropy.
RESinvANFIS-v-1.0
Geolectrical sounding inversion using Neuro Fuzzy technique