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geostatistics
Here are 83 public repositories matching this topic...
Kriging Toolkit for Python
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Jun 25, 2021 - Python
Datseris
commented
Jun 2, 2021
At the moment, looking at the doc page of Variograms, it seems like the only way to analyze Variograms is via the Plots.jl package. But I would much rather obtain the actual values that are plotted. How do I obtain:
- Values of h axis
- Values of γ(h)
- Bin values b(h)
? I don't use Plots.jl and I see no mention in the documentation page on how to obtain these values. The display method
GeostatsPy Python package for spatial data analytics and geostatistics. Mostly a reimplementation of GSLIB, Geostatistical Library (Deutsch and Journel, 1992) in Python. Geostatistics in a Python package. I hope this resources is helpful, Prof. Michael Pyrcz
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May 12, 2021 - Jupyter Notebook
GSTools - A geostatistical toolbox: random fields, variogram estimation, covariance models, kriging and much more
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Jul 5, 2021 - Python
Geostatistical variogram estimation expansion in the scipy style
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Jul 5, 2021 - Python
Fast, memory-efficient 3D spline interpolation and global kriging, via RBF (radial basis function) interpolation.
cpp
interpolation
regression
approximation
surface-reconstruction
smoothing
splines
spline
geostatistics
kriging
function-approximation
radial-basis-function
rbf
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Oct 23, 2020 - C++
Geostatistics in Python
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Jul 26, 2020 - Python
Fast image quilting simulation solver for the GeoStats.jl framework
computer-vision
image-processing
graph-theory
texture-synthesis
geostatistics
multiple-point-statistics
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May 26, 2021 - Julia
Tutorials in the form of Jupyter notebooks for the GeoStats.jl framework
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May 16, 2021 - Julia
These are python notebooks accompanying Lessons available at GeostatisticsLessons.com
statistics
notebook
mining
petroleum
geostatistics
python-notebook
applied-statistics
geostatistics-lessons
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Jun 24, 2020 - Jupyter Notebook
Repository of the GammaRay geomodeling software. New in April, 12th: export GeoGrid as Eclipse grid.
simulation
random-forest
regression
estimation
classification
fft
cart
svd
gabor
markov-chain-monte-carlo
geostatistics
gslib
earthsciences
kriging
variogram
emd
markov-random-field
discrete-wavelet-transformation
stratigraphic-grid
vertical-proportion-curve
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Jun 11, 2021 - C++
A flexible MPS framework
stochastic
simulations
nds
mps
texture-synthesis
geostatistics
qs
multiple-point-statistics
quantile-sampling
narrow-distribution-selection
training-images
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Jun 16, 2021 - C++
A High Performance Unified Framework for Geostatistics on Manycore Systems.
machine-learning
prediction
climate-model
geostatistics
statistical-models
maximum-likelihood-estimation
manycore
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Jun 7, 2021 - C
Implicit 3D geological modeling and geostatistics
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Mar 15, 2019 - R
The STK is a (not so) Small Toolbox for Kriging. Its primary focus is on the interpolation/regression technique known as kriging, which is very closely related to Splines and Radial Basis Functions, and can be interpreted as a non-parametric Bayesian method using a Gaussian Process (GP) prior.
machine-learning
gaussian-processes
geostatistics
kriging
gaussian-process-regression
gaussian-process-optimisation
computer-experiment-design
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Jun 14, 2021 - MATLAB
Set of tools to manipulate Digital Elevation Models (DEMs)
digital
model
geoscience
comparison
elevation
dem
geostatistics
variogram
dems
coregistration
glaciers
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Jul 5, 2021 - Python
Use SGeMS (Stanford Geostatistical Modeling Software) within Python.
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Jul 5, 2021 - Python
Spatial interpolation of groundwater level for realistic flow dynamics
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Aug 29, 2018 - R
An R implementation of the DSMART algorithm
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Feb 16, 2019 - R
Sequential Gaussian Simulation for generating Gaussian fields.
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Jul 3, 2019 - HTML
Geological Reservoir Virtualization
visualization
knowledge-discovery
data-management
visual-analytics
geostatistics
multivariate-analysis
reservoir-characterization
subsurface
geological-models
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Jun 6, 2021 - C#
Gaussian process regression
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Apr 21, 2021 - Julia
Generate stocastic Gaussian realization constrained to a coarse scale image.
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Sep 9, 2019 - HTML
juifa-tsai
commented
Feb 26, 2019
The format of module is not completely compatible to sklearn. The reason for adopting to sklearn is because of the parameter optimization. Sklearn provides well-defined tool for tuning parameter and validation. Thus, making the module to adopt sklearn is kind of way to simplify future work.
- Change get_params() to output the default parameter sets with {'name':value} instead.
- Add relevant f
An R package that implements the methods of geostatistics for functional data
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Mar 18, 2019 - R
Training images for geostastical simulation
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Mar 1, 2021 - Julia
Mandatory work for Introduction to Geostatistics course on University of Buenos Aires (UBA)
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Dec 12, 2016 - R
Local anisotropies and nonstationary spatial processes for the GeoStats.jl framework
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Jun 4, 2021 - Julia
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Proposing to add Webviz to the list, along with Webviz-subsurface.
Project name:
Webviz+Webviz-subsurface
Project website/repository:
https://github.com/equinor/webviz-subsurface/
License:
MIT for webviz-config, GPLv3 for webviz-subsurface
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