Reconstruct flowline features

This example shows a couple of different scenarios involving the reconstruction of flowline features to geological times.

Exported reconstructed flowlines to a file 

In this example we reconstruct flowline features and export the results to a Shapefile.

Sample code 

import pygplates


# Load one or more rotation files into a rotation model.
rotation_model = pygplates.RotationModel('rotations.rot')

# Load some flowline features.
flowline_features = pygplates.FeatureCollection('flowline_features.gpml')

# Reconstruct features to this geological time.
reconstruction_time = 50

# The filename of the exported reconstructed flowlines.
# It's a shapefile called 'flowline_output_50Ma.shp'.
export_filename = 'flowline_output_{0}Ma.shp'.format(reconstruction_time)

# Reconstruct the flowlines to the reconstruction time and export them to a shapefile.
pygplates.reconstruct(flowline_features, rotation_model, export_filename, reconstruction_time,
    reconstruct_type=pygplates.ReconstructType.flowline)

Details 

The rotations are loaded from a rotation file into a pygplates.RotationModel.

rotation_model = pygplates.RotationModel('rotations.rot')

The flowline features are loaded into a pygplates.FeatureCollection.

flowline_features = pygplates.FeatureCollection('flowline_features.gpml')

The flowline features will be reconstructed to their 50Ma positions.

reconstruction_time = 50

All flowline features are reconstructed to 50Ma using pygplates.reconstruct().
We specify we only want to reconstruct flowline features by specifying
pygplates.ReconstructType.flowline for the reconstruct_type argument.
We specify a filename to export the reconstructed geometries to.

pygplates.reconstruct(flowline_features, rotation_model, export_filename, reconstruction_time,
    reconstruct_type=pygplates.ReconstructType.flowline)

Output 

We should now have a file called flowline_output_50Ma.shp containing the flowlines reconstructed to their 50Ma positions.

Query a reconstructed flowline 

In this example we print out the point locations in a reconstructed flowline.

Sample code 

import pygplates


# Specify two (lat/lon) seed points on a present-day mid-ocean ridge between plates 201 and 701.
seed_points = pygplates.MultiPointOnSphere(
    [
        (-35.547600, -17.873000),
        (-46.208000, -13.623000)
    ])

# A list of times to sample flowline - from 0 to 90Ma in 5My intervals.
times = range(0, 91, 5)

# Create a flowline feature.
flowline_feature = pygplates.Feature.create_flowline(
        seed_points,
        times,
        valid_time=(max(times), min(times)),
        left_plate=201,
        right_plate=701)

# Load one or more rotation files into a rotation model.
rotation_model = pygplates.RotationModel('rotations.rot')

# Reconstruct features to this geological time.
reconstruction_time = 50

# Reconstruct the flowline feature to the reconstruction time.
reconstructed_flowlines = []
pygplates.reconstruct(flowline_feature, rotation_model, reconstructed_flowlines, reconstruction_time,
    reconstruct_type=pygplates.ReconstructType.flowline)

# Iterate over all reconstructed flowlines.
# There will be two (one for each seed point).
for reconstructed_flowline in reconstructed_flowlines:

    # Print the flowline left/right plate IDs.
    print 'flowline: left %d, right %d at %fMa' % (
        reconstructed_flowline.get_feature().get_left_plate(),
        reconstructed_flowline.get_feature().get_right_plate(),
        reconstruction_time)

    # Print the reconstructed seed point location.
    print '  reconstructed seed point: lat: %f, lon: %f' % reconstructed_flowline.get_reconstructed_seed_point().to_lat_lon()

    flowline_times = reconstructed_flowline.get_feature().get_times()

    print '  left flowline:'

    # Iterate over the left points in the flowline.
    # The first point in the path is the youngest and the last point is the oldest.
    # So we reverse the order to start with the oldest.
    for point_index, left_point in enumerate(reversed(reconstructed_flowline.get_left_flowline())):

        lat, lon = left_point.to_lat_lon()

        # The first point in the path is the oldest and the last point is the reconstructed seed point.
        # So we need to start at the last time and work our way backwards.
        time = flowline_times[-1-point_index]

        # Print the point location and the time associated with it.
        print '    time: %f, lat: %f, lon: %f' % (time, lat, lon)

    print '  right flowline:'

    # Iterate over the right points in the flowline.
    # The first point in the path is the youngest and the last point is the oldest.
    # So we reverse the order to start with the oldest.
    for point_index, right_point in enumerate(reversed(reconstructed_flowline.get_right_flowline())):

        lat, lon = right_point.to_lat_lon()

        # The first point in the path is the oldest and the last point is the reconstructed seed point.
        # So we need to start at the last time and work our way backwards.
        time = flowline_times[-1-point_index]

        # Print the point location and the time associated with it.
        print '    time: %f, lat: %f, lon: %f' % (time, lat, lon)

Details 

The first part of this example comes from Create a flowline feature.

It creates a flowline feature specifying the seed point locations that each flowline spreads from as well as a list of times to plot points in the left/right paths.

seed_points = pygplates.MultiPointOnSphere([(-35.547600, -17.873000), (-46.208000, -13.623000)])
times = range(0, 91, 1)
flowline_feature = pygplates.Feature.create_flowline(
        seed_points,
        times,
        valid_time=(max(times), min(times)),
        left_plate=201,
        right_plate=701)

The rotations are loaded from a rotation file into a pygplates.RotationModel.

rotation_model = pygplates.RotationModel('rotations.rot')

The features will be reconstructed to their 50Ma positions.

reconstruction_time = 50

The flowline feature is reconstructed to 50Ma using pygplates.reconstruct().
We specify a list for reconstructed_flowlines instead of a filename so that we
can query the reconstructed flowlines easily.
We also specify we only want to reconstruct flowline features by specifying
pygplates.ReconstructType.flowline for the reconstruct_type argument.

reconstructed_flowlines = []
pygplates.reconstruct(flowline_feature, rotation_model, reconstructed_flowlines, reconstruction_time,
    reconstruct_type=pygplates.ReconstructType.flowline)

We iterate over the points in the reconstructed left flowline and print each point location and its associated time.

The first point in a flowline path is the youngest and the last point is the oldest. We reverse that order so that we start with the oldest point first since there is always a point in the path corresponding to the oldest time, but there is not always a point corresponding to the youngest time (present day). However when we index into the flowline times we again need to reverse our indexing order (since the times array goes from youngest to oldest). So we need to start at the last (oldest) time and work our way backwards. The last sample is at index -1 and point_index starts at zero. So our time indices are -1, -2, etc, which means last sample, then second last sample, etc.

for point_index, left_point in enumerate(reversed(reconstructed_flowline.get_left_flowline())):
    lat, lon = left_point.to_lat_lon()
    time = flowline_times[-1-point_index]
    print '    time: %f, lat: %f, lon: %f' % (time, lat, lon)

Then we do the same thing for the reconstructed right flowline.

Output 

Our time range is 90Ma to 0Ma, but since the reconstruction time is 50Ma the output is only from 90Ma to 50Ma.

flowline: left 201, right 701 at 50.000000Ma
  reconstructed seed point: lat: -39.850694, lon: -16.014821
  left flowline:
    time: 90.000000, lat: -40.901733, lon: -27.101972
    time: 85.000000, lat: -40.656544, lon: -25.013022
    time: 80.000000, lat: -40.483824, lon: -23.206460
    time: 75.000000, lat: -40.334783, lon: -21.521684
    time: 70.000000, lat: -40.162941, lon: -19.844649
    time: 65.000000, lat: -40.040648, lon: -18.640309
    time: 60.000000, lat: -39.971463, lon: -17.834474
    time: 55.000000, lat: -39.903776, lon: -16.997535
    time: 50.000000, lat: -39.850694, lon: -16.014821
  right flowline:
    time: 90.000000, lat: -38.122807, lon: -5.288718
    time: 85.000000, lat: -38.647048, lon: -7.218192
    time: 80.000000, lat: -38.993610, lon: -8.936790
    time: 75.000000, lat: -39.256681, lon: -10.566648
    time: 70.000000, lat: -39.498386, lon: -12.207892
    time: 65.000000, lat: -39.646000, lon: -13.398159
    time: 60.000000, lat: -39.723847, lon: -14.198892
    time: 55.000000, lat: -39.796142, lon: -15.033014
    time: 50.000000, lat: -39.850694, lon: -16.014821
flowline: left 201, right 701 at 50.000000Ma
  reconstructed seed point: lat: -50.546458, lon: -11.620705
  left flowline:
    time: 90.000000, lat: -51.886602, lon: -24.489162
    time: 85.000000, lat: -51.571835, lon: -21.855842
    time: 80.000000, lat: -51.343265, lon: -19.679682
    time: 75.000000, lat: -51.144581, lon: -17.701380
    time: 70.000000, lat: -50.919599, lon: -15.739301
    time: 65.000000, lat: -50.765425, lon: -14.377055
    time: 60.000000, lat: -50.684497, lon: -13.516892
    time: 55.000000, lat: -50.605968, lon: -12.631013
    time: 50.000000, lat: -50.546458, lon: -11.620705
  right flowline:
    time: 90.000000, lat: -48.420517, lon: 0.540404
    time: 85.000000, lat: -49.070539, lon: -1.777819
    time: 80.000000, lat: -49.499811, lon: -3.780529
    time: 75.000000, lat: -49.827249, lon: -5.651092
    time: 70.000000, lat: -50.130910, lon: -7.543508
    time: 65.000000, lat: -50.312577, lon: -8.879531
    time: 60.000000, lat: -50.402339, lon: -9.730844
    time: 55.000000, lat: -50.485515, lon: -10.611898
    time: 50.000000, lat: -50.546458, lon: -11.620705

Note

The reconstructed seed point is the same position as the last point in the left and right flowlines.