Pseudo-3D cubes from densely spaced subbottom profiles via Projection Onto Convex Sets (POCS) interpolation#
This repository contains the source code for the generation of pseudo-3D cubes from densely spaced 2D subbottom profiles by utilizing the Projection Onto Convex Sets (POCS) method.
The source code accompanies a journal article published in GEOPHYSICS:
Warnke, F., Pecher, I. A., Hillman, J. I. T., Davy, B., Woelz, S., Gorman, A. R., & Strachan, L. J. (2023).
Pseudo-3D cubes from densely spaced subbottom profiles via projection onto convex sets interpolation:
An open-source workflow applied to a pockmark field. GEOPHYSICS, F51–F69.
Usage information
When using this workflow please refer to the citation information and, in case of feedback or questions, the contact information.
Installation#
Preparations#
The workflow can be installed locally after downloading and unzipping the source code from GitHub.
Navigate into the unzipped directory:
[Optional] Install dependencies using conda/mamba#
Use the provided conda/mamba environment file to install dependencies:
>>> conda install -f {environment.yml} # install dependencies
>>> conda activate pseudo_3d # activate new env (default name: "pseudo_3d")
The repository includes three different environment YAML files:
-
environment.yml: Minimal dependencies required to run the core workflow. -
environment_optional.yml: Minimal and optional dependencies required to run the full workflow:-
tpxo-tide-predictionfor tide compensation. -
for different sparse transforms
-
wavelet:
pywavelets -
shearlet:
PyShearlets -
curvelet: see note below
-
-
geopandas: for QC -
numba: for optimization
-
-
environment_dev.yml: Developer dependencies (not for common user).
[Optional] Install dependencies using pip#
Use the provided pip requirements file to install dependencies:
The repository includes three different requirement files:
-
requirements.txt: Minimal dependencies required to run the core workflow. -
requirements_optional.txt: Minimal and optional dependencies required to run the full workflow.-
includes
tpxo-tide-predictionfor tide compensation. -
for different sparse transforms
-
wavelet:
pywavelets -
shearlet:
PyShearlets -
curvelet: see note below
-
-
geopandas: for QC -
numba: for optimization
-
-
requirements_dev.txt: Developer dependencies (not for common user).
Install from source#
Install the workflow package in your active environment (with optional dependencies):
>>> pip install [-e] . # -e: setuptools "develop mode"
>>> pip install ".[tide]" # install optional "tpxo-tide-prediction" dependency
>>> pip install ".[transforms]" # install optional transform dependencies
>>> pip install ".[extra]" # install optional dependencies (geopandas, numba)
>>> pip install ".[tide,transforms,extra]" # install all optional dependencies (RECOMMENDED!)
>>> pip install ".[dev]" # developer installation
Dependencies
The required dependencies will be installed automatically if they are not already available.
Warning
The Curvelet transform is only available on Unix systems via the curvelops package!
Please refer to the README of the project and additional installation instructions if you plan to use this transform.
Funding#
This workflow was developed as part of my PhD research at the School of Environment, University of Auckland, New Zealand.
The funding was provided by the Royal Society of New Zealand Marsden Fund grant Geologic champagne: What controls sudden release of CO2 at glacial terminations on the Chatham Rise? (19-UOA-339) with additional support by the University of Auckland Doctoral Scholarship. Ship time was supported by the Ministry of Business, Innovation and Employment (MBIE) and additional funding from GNS Science.
License#
This project is licensed under GNU GPLv3. Please refer to the project license when considering using this workflow for your own research or project.