Simple One-Shot Seafloor Age Computation¶

This example demonstrates the simplest way to compute seafloor ages using gtrack. The compute_ages() class method provides a functional interface that handles all setup internally.

Use this approach when you need ages at a single target geological age and don't need to access intermediate states.

In [1]:

from pathlib import Path
import matplotlib.pyplot as plt
import cartopy.crs as ccrs

from gtrack import SeafloorAgeTracker, TracerConfig

from pathlib import Path import matplotlib.pyplot as plt import cartopy.crs as ccrs from gtrack import SeafloorAgeTracker, TracerConfig

Data File Paths¶

Run make data in the examples directory to download and extract the data.

In [2]:

data_dir = Path("./Matthews_et_al_410_0")

rotation_files = [
    data_dir / "Global_EB_250-0Ma_GK07_Matthews++.rot",
    data_dir / "Global_EB_410-250Ma_GK07_Matthews++.rot"
]

topology_files = [
    data_dir / "Mesozoic-Cenozoic_plate_boundaries_Matthews++.gpml",
    data_dir / "Paleozoic_plate_boundaries_Matthews++.gpml",
    data_dir / "TopologyBuildingBlocks_Matthews++.gpml",
]

# Continental polygons are optional - if not provided, tracers are not
# removed when entering continental regions
continental_polygons = data_dir / \
    "ContPolys/PresentDay_ContinentalPolygons_Matthews++.shp"

data_dir = Path("./Matthews_et_al_410_0") rotation_files = [ data_dir / "Global_EB_250-0Ma_GK07_Matthews++.rot", data_dir / "Global_EB_410-250Ma_GK07_Matthews++.rot" ] topology_files = [ data_dir / "Mesozoic-Cenozoic_plate_boundaries_Matthews++.gpml", data_dir / "Paleozoic_plate_boundaries_Matthews++.gpml", data_dir / "TopologyBuildingBlocks_Matthews++.gpml", ] # Continental polygons are optional - if not provided, tracers are not # removed when entering continental regions continental_polygons = data_dir / \ "ContPolys/PresentDay_ContinentalPolygons_Matthews++.shp"

Configuration¶

TracerConfig controls all tracer parameters. The new API uses pygplates' C++ backend for efficient collision detection and point advection, matching GPlately's approach.

In [3]:

config = TracerConfig(
    # Time stepping
    time_step=1.0,  # Time step size (Myr)

    # Mesh initialization - icosahedral mesh refinement level
    # Level 5 = ~10,242 points, Level 6 = ~40,962 points
    default_refinement_levels=5,

    # Initial age calculation
    initial_ocean_mean_spreading_rate=75.0,  # mm/yr (GPlately default)

    # MOR seed generation
    ridge_sampling_degrees=0.5,    # Ridge tessellation (~50 km at equator)
    spreading_offset_degrees=0.01,  # Offset from ridge (~1 km)

    # Collision detection (C++ backend - GPlately compatible)
    velocity_delta_threshold=7.0,      # km/Myr (converted to 0.7 cm/yr)
    distance_threshold_per_myr=10.0,   # km/Myr
)

config = TracerConfig( # Time stepping time_step=1.0, # Time step size (Myr) # Mesh initialization - icosahedral mesh refinement level # Level 5 = ~10,242 points, Level 6 = ~40,962 points default_refinement_levels=5, # Initial age calculation initial_ocean_mean_spreading_rate=75.0, # mm/yr (GPlately default) # MOR seed generation ridge_sampling_degrees=0.5, # Ridge tessellation (~50 km at equator) spreading_offset_degrees=0.01, # Offset from ridge (~1 km) # Collision detection (C++ backend - GPlately compatible) velocity_delta_threshold=7.0, # km/Myr (converted to 0.7 cm/yr) distance_threshold_per_myr=10.0, # km/Myr )

Compute Ages in One Call¶

The compute_ages() class method creates a tracker, initialises tracers at the starting age, and evolves them to the target age - all in a single call. This is the simplest way to get seafloor ages.

Here we compute present-day (0 Ma) seafloor ages, starting the simulation at 200 Ma.

In [4]:

cloud = SeafloorAgeTracker.compute_ages(
    target_age=0,
    starting_age=200,
    rotation_files=rotation_files,
    topology_files=topology_files,
    continental_polygons=continental_polygons,
    config=config,
)

cloud = SeafloorAgeTracker.compute_ages( target_age=0, starting_age=200, rotation_files=rotation_files, topology_files=topology_files, continental_polygons=continental_polygons, config=config, )

INFO: Initializing SeafloorAgeTracker...

INFO:   Initialization complete.

INFO: Initializing tracers at 200 Ma (method='icosahedral')...

INFO:   Initialized with 13460 tracers at 200 Ma

INFO: Evolving: 200 Ma -> 0 Ma

INFO:   Current tracer count: 286438

Access Results¶

The result is a PointCloud with xyz coordinates and an 'age' property containing the material age of each tracer.

In [5]:

# Get coordinates and ages
# (N, 2) array with [lon, lat] in degrees
xyz = cloud.xyz
lonlat = cloud.lonlat  # (N, 2) array with [lon, lat] in degrees
tracer_ages = cloud.get_property('age')   # (N,) material ages in Myr

# Get coordinates and ages # (N, 2) array with [lon, lat] in degrees xyz = cloud.xyz lonlat = cloud.lonlat # (N, 2) array with [lon, lat] in degrees tracer_ages = cloud.get_property('age') # (N,) material ages in Myr

Plotting the Results¶

Plot the tracers as a scatter plot on a Mollweide projection, coloured by their material age.

In [6]:

fig = plt.figure(figsize=(12, 6))
ax = plt.axes(projection=ccrs.Mollweide())

scatter = ax.scatter(
    lonlat[:, 0], lonlat[:, 1],
    c=tracer_ages,
    s=1,
    cmap='viridis_r',
    vmin=0, vmax=200,
    transform=ccrs.PlateCarree()
)

ax.coastlines(resolution='110m', linewidth=0.5)
ax.set_global()

cbar = plt.colorbar(scatter, ax=ax, orientation='horizontal',
                    pad=0.05, aspect=40, shrink=0.8)
cbar.set_label('Seafloor Age (Myr)')

ax.set_title('Present-Day Seafloor Ages (computed from 200 Ma)')
plt.show()

# Print summary statistics
print(f"Number of tracers: {len(tracer_ages)}")
print(f"Age range: {tracer_ages.min():.1f} - {tracer_ages.max():.1f} Myr")
print(f"Mean age: {tracer_ages.mean():.1f} Myr")

fig = plt.figure(figsize=(12, 6)) ax = plt.axes(projection=ccrs.Mollweide()) scatter = ax.scatter( lonlat[:, 0], lonlat[:, 1], c=tracer_ages, s=1, cmap='viridis_r', vmin=0, vmax=200, transform=ccrs.PlateCarree() ) ax.coastlines(resolution='110m', linewidth=0.5) ax.set_global() cbar = plt.colorbar(scatter, ax=ax, orientation='horizontal', pad=0.05, aspect=40, shrink=0.8) cbar.set_label('Seafloor Age (Myr)') ax.set_title('Present-Day Seafloor Ages (computed from 200 Ma)') plt.show() # Print summary statistics print(f"Number of tracers: {len(tracer_ages)}") print(f"Age range: {tracer_ages.min():.1f} - {tracer_ages.max():.1f} Myr") print(f"Mean age: {tracer_ages.mean():.1f} Myr")

/opt/hostedtoolcache/Python/3.12.12/x64/lib/python3.12/site-packages/cartopy/io/__init__.py:242: DownloadWarning: Downloading: https://naturalearth.s3.amazonaws.com/110m_physical/ne_110m_coastline.zip
  warnings.warn(f'Downloading: {url}', DownloadWarning)

Number of tracers: 286438
Age range: 0.0 - 443.6 Myr
Mean age: 57.3 Myr