platerecipy 2.0.1

PLATE RECognition In PYthon

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

Releases are made available on PyPI so that platerecipy can be installed using pip on the shell as follows:

python -m 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)

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Developed by Pejvak Javaheri, [e-mail].