PLATE RECognition In PYthon
Project description
platerecipy: a package for PLATE RECognition In PYthon
platerecipy is a tool for detecting candidate plates on global geophysical
datasets. It analyzes the surface to identify diffuse and non-conforming regions,
as well as regions with low confidence in plate assignment.
Supported platforms
Though platerecipy is fundamentally a Python package, it also relies on
backend functionalities that are implemented in C. Linux is the main operating
system for platerecipy. However, expect for a number of optimizations (e.g., multithreaded C functions),
platerecipy is now available via pip on Windows systems.
Installation
Version releases are made available on PyPI so that platerecipy can be installed using
pip on the shell as follows:
pip install platerecipy
User guide
platerecipy's documentation is moved to platerecipy.readthedocs.io!
For a detailed explanation and illustration of platerecipy's core functionalities,
please refer to:
Javaheri, P., & Lowman, J. P. (2026). A random walker algorithm for plate boundary detection in spherical mantle convection models and global geophysical data sets: Application to Euler vector determination. Journal of Geophysical Research: Solid Earth, 131, e2025JB032259. https://doi.org/10.1029/2025JB032259
As a demonstration, assuming a given input_xs, input_ys, input_zs, and
input_field (all numpy arrays), using platerecipy is as simple as follows:
from platerecipy.model import PlateModel
from platerecipy.grid import SphericalGrid
input_xs = # to be specified ...
input_ys = # to be specified ...
input_zs = # to be specified ...
input_field = # to be specified ...
# generating a consistent grid for interpolation
grid = SphericalGrid(input_xs, input_ys, input_zs)
# interpolating an input field
field = grid.interpolate_field(input_field)
# initializing a plate model
m = PlateModel(grid)
# stacking the interpolated field
m.stack_field(field, take_log=True)
# finding plates on the stacked field
m.find_plates(
boundary_quantile = 0.9, # threshold for the boundaries
separation_tolerance = 4*3.1416/180., # 4 degrees for separation tolerance
RW_beta = 200, # RW beta (for feature sharpness)
min_marker_size = 100 # to filter out micro plates
)
# outputting as a ParaView readable .vtk file
from platerecipy import io
io.save_as_vtk(m)
Citing platerecipy
If this package has been useful to your research, please cite the original paper:
Javaheri, P., & Lowman, J. P. (2026). A random walker algorithm for plate boundary detection in spherical mantle convection models and global geophysical data sets: Application to Euler vector determination. Journal of Geophysical Research: Solid Earth, 131, e2025JB032259. https://doi.org/10.1029/2025JB032259
@article{platerecipy,
author = {Javaheri, P. and Lowman, J. P.},
title = {{A random walker algorithm for plate boundary detection in spherical mantle convection models and global geophysical data sets: Application to Euler vector determination}},
journal = {Journal of Geophysical Research: Solid Earth},
volume = {131},
number = {3},
pages = {e2025JB032259},
keywords = {plate tectonics, plate modeling, Euler vector, diffuse zones, mantle convection, strain-rate},
doi = {https://doi.org/10.1029/2025JB032259},
url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2025JB032259},
eprint = {https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2025JB032259},
note = {e2025JB032259 2025JB032259},
year = {2026}
}
as well as the software version:
P. Javaheri. (2025). pjavaheri/platerecipy: Release of version 1.0.0 (v1.0.0). Zenodo. https://doi.org/10.5281/zenodo.15625716
@software{p_javaheri_2025_15625716,
author = {P. Javaheri},
title = {pjavaheri/platerecipy: Release of version 1.0.0},
month = jun,
year = 2025,
publisher = {Zenodo},
version = {v1.0.0},
doi = {10.5281/zenodo.15625716},
url = {https://doi.org/10.5281/zenodo.15625716},
}
Please note that platerecipy is a platform under development. Depending on your installed
version, the software version citation should point to the most recent prior
release on Zenodo.
Developed by Pejvak Javaheri, pejvak.javaheri@mail.utoronto.ca.
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