PlateCurie is a software for estimating the Curie depth from the inversion of the power spectrum of magnetic anomaly data calculated from a wavelet transform.

Licence

Copyright 2019 Pascal Audet

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Installation

Dependencies

  • A fortran compiler

  • pymc

  • seaborn

  • scikit-image

  • plateflex

See below for full installation details.

Conda environment

We recommend creating a custom conda environment where platecurie can be installed along with its dependencies. This will ensure that all packages are compatible.

Note

In theory, you could use your own fortran compiler. However, to ensure a proper installation, it is recommended to install fortran-compiler in the pflex environment.

conda create -n pcurie -c conda-forge python=3.12 fortran-compiler pymc seaborn scikit-image

Activate the newly created environment:

conda activate pcurie

Install plateflex from the development on GitHub

pip install plateflex@git+https://github.com/paudetseis/plateflex

Installing development branch from GitHub

Install the latest version of platecurie from the GitHub repository with the following command:

pip install platecurie@git+https://github.com/paudetseis/platecurie

Jupyter Notebooks

Included in this package is a set of Jupyter Notebooks (see Table of Content) with accompanying data, which give examples on how to call the various routines The Notebooks describe how to reproduce published examples from Gaudreau et al. (2019).

These data and notebooks can be locally installed (i.e., in a local folder Examples) from the package by typing in a python window:

from platecurie.doc import install_doc
install_doc(path='Examples')

To view and run the notebooks you will have to further install jupyter. From the terminal, type:

conda install jupyter

Followed by:

jupyter notebook

You can then save the notebooks as python scripts, check out the model files and set up your own examples.

Global Variables

platecurie.get_conf_cpwt()

Print global variable that controls the spatio-spectral resolution of the wavelet transform

Example

>>> import platecurie
>>> platecurie.get_conf_cpwt()
Wavelet parameter used in platecurie.cpwt:
------------------------------------------
[Internal wavenumber]      k0 (float):     5.336