Module gplately.plot
Tools for reconstructing and plotting geological features and feature data through time.
Methods in plot.py reconstruct geological features using
pyGPlates' reconstruct function,
turns them into plottable Shapely geometries, and plots them onto
Cartopy GeoAxes using Shapely and GeoPandas.
Classes
PlotTopologies
Expand source code
"""Tools for reconstructing and plotting geological features and feature data through time.
Methods in `plot.py` reconstruct geological features using
[pyGPlates' `reconstruct` function](https://www.gplates.org/docs/pygplates/generated/pygplates.reconstruct.html),
turns them into plottable Shapely geometries, and plots them onto
Cartopy GeoAxes using Shapely and GeoPandas.
Classes
-------
PlotTopologies
"""
import re
import warnings
import pygplates
import cartopy.crs as ccrs
import matplotlib.pyplot as plt
import numpy as np
import ptt
from shapely.geometry import Point, Polygon
from shapely.geometry.base import BaseGeometry, BaseMultipartGeometry
from shapely.ops import linemerge
from .pygplates import FeatureCollection as _FeatureCollection
from .pygplates import _is_string
from .reconstruction import PlateReconstruction as _PlateReconstruction
from .geometry import pygplates_to_shapely
import geopandas as gpd
from .io import (
get_valid_geometries, # included for backwards compatibility
get_geometries as _get_geometries,
)
from .tools import EARTH_RADIUS
from .gpml import _load_FeatureCollection
def plot_subduction_teeth(
geometries,
width,
polarity=None,
height=None,
spacing=None,
projection="auto",
transform=None,
ax=None,
**kwargs
):
"""Add subduction teeth to a plot.
The subduction polarity used for subduction teeth can be specified
manually or detected automatically if `geometries` is a
`geopandas.GeoDataFrame` object with a `polarity` column.
Parameters
----------
geometries : geopandas.GeoDataFrame, sequence of shapely geometries, or str
If a `geopandas.GeoDataFrame` is given, its geometry attribute
will be used. If `geometries` is a string, it must be the path to
a file, which will be loaded with `geopandas.read_file`. Otherwise,
`geometries` must be a sequence of shapely geometry objects (instances
of the `shapely.geometry.base.BaseGeometry` class).
width : float
The (approximate) width of the subduction teeth. If a projection is
used, this value will be in projected units.
polarity : {"left", "l", "right", "r", None}, default None
The subduction polarity of the geometries. If no polarity is provided,
and `geometries` is a `geopandas.GeoDataFrame`, this function will
attempt to find a `polarity` column in the data frame and use the
values given there. If `polarity` is not manually specified and no
appropriate column can be found, an error will be raised.
height : float, default None
If provided, the height of the subduction teeth. As with `width`,
this value should be given in projected units. If no value is given,
the height of the teeth will be equal to 0.6 * `width`.
spacing : float, default None
If provided, the spacing between the subduction teeth. As with
`width` and `height`, this value should be given in projected units.
If no value is given, `spacing` will default to `width`, producing
tightly packed subduction teeth.
projection : cartopy.crs.Transform, "auto", or None, default "auto"
The projection of the plot. If the plot has no projection, this value
can be explicitly given as `None`. The default value is "auto", which
will acquire the projection automatically from the plot axes.
transform : cartopy.crs.Transform, or None, default None
If the plot is projected, a `transform` value is usually needed.
Frequently, the appropriate value is an instance of
`cartopy.crs.PlateCarree`.
ax : matplotlib.axes.Axes, or None, default None
The axes on which the subduction teeth will be drawn. By default,
the current axes will be acquired using `matplotlib.pyplot.gca`.
**kwargs
Any further keyword arguments will be passed to
`matplotlib.patches.Polygon`.
Raises
------
ValueError
If `width` <= 0, or if `polarity` is an invalid value or could not
be determined.
"""
if ax is None:
ax = plt.gca()
if projection == "auto":
try:
projection = ax.projection
except AttributeError:
projection = None
elif isinstance(projection, str):
raise ValueError("Invalid projection: {}".format(projection))
if polarity is None:
polarity_column = _find_polarity_column(geometries.columns.values)
if polarity_column is None:
raise ValueError(
"Could not automatically determine polarity; "
+ "it must be defined manually instead."
)
triangles = []
for p in geometries[polarity_column].unique():
if p.lower() not in {"left", "l", "right", "r"}:
continue
gdf_polarity = geometries[geometries[polarity_column] == p]
triangles.extend(
_tessellate_triangles(
gdf_polarity,
width,
p,
height,
spacing,
projection,
transform,
)
)
else:
triangles = _tessellate_triangles(
geometries,
width,
polarity,
height,
spacing,
projection,
transform,
)
if projection is not None:
domain = projection.domain
triangles = [domain.intersection(i) for i in triangles]
if hasattr(ax, "add_geometries") and projection is not None:
ax.add_geometries(triangles, crs=projection, **kwargs)
else:
for triangle in triangles:
ax.fill(*triangle.exterior.xy, **kwargs)
def _tessellate_triangles(
geometries,
width,
polarity="left",
height=None,
spacing=None,
projection=None,
transform=None,
):
"""Generate subduction teeth triangles for plotting.
Forms continuous trench geometries and identifies their subduction polarities.
Subduction teeth triangles can be customised with a given spacing and width.
Their apexes point in the identified polarity directions.
Parameters
----------
geometries : geopandas.GeoDataFrame, sequence of shapely geometries, or str
If a `geopandas.GeoDataFrame` is given, its geometry attribute
will be used. If `geometries` is a string, it must be the path to
a file, which will be loaded with `geopandas.read_file`. Otherwise,
`geometries` must be a sequence of shapely geometry objects (instances
of the `shapely.geometry.base.BaseGeometry` class).
width : float
The (approximate) width of the subduction teeth. If a projection is
used, this value will be in projected units.
polarity : {"left", "l", "right", "r", None}, default "left"
The subduction polarity of the geometries. If no polarity is provided,
and `geometries` is a `geopandas.GeoDataFrame`, this function will
attempt to find a `polarity` column in the data frame and use the
values given there. If `polarity` is not manually specified and no
appropriate column can be found, an error will be raised.
height : float, default None
If provided, the height of the subduction teeth. As with `width`,
this value should be given in projected units. If no value is given,
the height of the teeth will be equal to 0.6 * `width`.
spacing : float, default None
If provided, the spacing between the subduction teeth. As with
`width` and `height`, this value should be given in projected units.
If no value is given, `spacing` will default to `width`, producing
tightly packed subduction teeth.
projection : cartopy.crs.Transform, "auto", or None, default None
The projection of the plot. If the plot has no projection, this value
can be explicitly given as `None`. The default value is "auto", which
will acquire the projection automatically from the plot axes.
transform : cartopy.crs.Transform, or None, default None
If the plot is projected, a `transform` value is usually needed.
Frequently, the appropriate value is an instance of
`cartopy.crs.PlateCarree`.
Returns
-------
results : list of shapely Polygon objects
Subduction teeth generated for the given geometries.
"""
if width <= 0.0:
raise ValueError("Invalid `width` argument: {}".format(width))
polarity = _parse_polarity(polarity)
geometries = _parse_geometries(geometries)
if height is None:
height = width * 2.0/3.0
if spacing is None:
spacing = width
if projection is not None:
geometries_new = []
for i in geometries:
geometries_new.extend(
_project_geometry(i, projection, transform)
)
geometries = geometries_new
del geometries_new
geometries = linemerge(geometries)
if isinstance(geometries, BaseMultipartGeometry):
geometries = list(geometries.geoms)
elif isinstance(geometries, BaseGeometry):
geometries = [geometries]
results = _calculate_triangle_vertices(
geometries,
width,
spacing,
height,
polarity,
)
return results
def _project_geometry(geometry, projection, transform=None):
"""Project shapely geometries onto a certain Cartopy CRS map projection.
Uses a coordinate system ("transform"), if given.
Parameters
----------
geometry : shapely.geometry.base.BaseGeometry
An instance of a shapely geometry.
projection : cartopy.crs.Transform,
The projection of the plot.
transform : cartopy.crs.Transform or None, default None
If the plot is projected, a `transform` value is usually needed.
Frequently, the appropriate value is an instance of
`cartopy.crs.PlateCarree`.
Returns
-------
projected : list
The provided shapely geometries projected onto a Cartopy CRS map projection.
"""
if transform is None:
transform = ccrs.PlateCarree()
result = [projection.project_geometry(geometry, transform)]
projected = []
for i in result:
if isinstance(i, BaseMultipartGeometry):
projected.extend(list(i.geoms))
else:
projected.append(i)
return projected
def _calculate_triangle_vertices(
geometries,
width,
spacing,
height,
polarity,
):
"""Generate vertices of subduction teeth triangles.
Triangle bases are set on shapely BaseGeometry trench instances with their apexes
pointing in directions of subduction polarity. Triangle dimensions are set by a
specified width, spacing and height (either provided by the user or set as default
values from _tessellate_triangles). The teeth are returned as shapely polygons.
Parameters
----------
geometries : list of shapely geometries (instances of the
shapely.geometry.base.BaseGeometry or shapely.geometry.base.BaseMultipartGeometry
class)
Trench geometries projected onto a certain map projection (using a
coordinate system if specified), each with identified subduction polarities.
Teeth triangles will be generated only on the BaseGeometry instances.
width : float
The (approximate) width of the subduction teeth. If a projection is
used, this value will be in projected units.
spacing : float,
The spacing between the subduction teeth. As with
`width` and `height`, this value should be given in projected units.
height : float, default None
The height of the subduction teeth. This value should also be given in projected
units.
polarity : {"left", "right"}
The subduction polarity of the shapely geometries.
Returns
-------
triangles : list of shapely polygons
The subduction teeth generated along the supplied trench geometries.
"""
if isinstance(geometries, BaseGeometry):
geometries = [geometries]
triangles = []
for geometry in geometries:
if not isinstance(geometry, BaseGeometry):
continue
length = geometry.length
tessellated_x = []
tessellated_y = []
for distance in np.arange(spacing, length, spacing):
point = Point(geometry.interpolate(distance))
tessellated_x.append(point.x)
tessellated_y.append(point.y)
tessellated_x = np.array(tessellated_x)
tessellated_y = np.array(tessellated_y)
for i in range(len(tessellated_x) - 1):
normal_x = tessellated_y[i] - tessellated_y[i + 1]
normal_y = tessellated_x[i + 1] - tessellated_x[i]
normal = np.array((normal_x, normal_y))
normal_mag = np.sqrt((normal ** 2).sum())
if normal_mag == 0:
continue
normal *= height / normal_mag
midpoint = np.array((tessellated_x[i], tessellated_y[i]))
if polarity == "right":
normal *= -1.0
apex = midpoint + normal
next_midpoint = np.array((tessellated_x[i + 1], tessellated_y[i + 1]))
line_vector = np.array(next_midpoint - midpoint)
line_vector_mag = np.sqrt((line_vector ** 2).sum())
line_vector /= line_vector_mag
triangle_point_a = midpoint + width * 0.5 * line_vector
triangle_point_b = midpoint - width * 0.5 * line_vector
triangle_points = np.array(
(
triangle_point_a,
triangle_point_b,
apex,
)
)
triangles.append(Polygon(triangle_points))
return triangles
def _parse_polarity(polarity):
"""Ensure subduction polarities have valid strings as labels - either "left", "l", "right" or "r".
The geometries' subduction polarities are either provided by the user in plot_subduction_teeth
or found automatically in a geopandas.GeoDataFrame column by _find_polarity_column, if such a
column exists.
Parameters
----------
polarity : {"left", "l", "right", "r"}
The subduction polarity of the geometries (either set by the user or found automatically
from the geometries' data frame).
Returns
-------
polarity : {"left", "right"}
Returned if the provided polarity string is one of {"left", "l", "right", "r"}. "l" and "r"
are classified and returned as "left" and "right" respectively.
Raises
------
TypeError
If the provided polarity is not a string type.
ValueError
If the provided polarity is not valid ("left", "l", "right" or "r").
"""
if not isinstance(polarity, str):
raise TypeError(
"Invalid `polarity` argument type: {}".format(type(polarity))
)
if polarity.lower() in {"left", "l"}:
polarity = "left"
elif polarity.lower() in {"right", "r"}:
polarity = "right"
else:
valid_args = {"left", "l", "right", "r"}
err_msg = "Invalid `polarity` argument: {}".format(
polarity
) + "\n(must be one of: {})".format(valid_args)
raise ValueError(err_msg)
return polarity
def _find_polarity_column(columns):
"""Search for a 'polarity' column in a geopandas.GeoDataFrame to extract subduction
polarity values.
Subduction polarities can be used for tessellating subduction teeth.
Parameters
----------
columns : geopandas.GeoDataFrame.columns.values instance
A list of geopandas.GeoDataFrame column header strings.
Returns
-------
column : list
If found, returns a list of all subduction polarities ascribed to the supplied
geometry data frame.
None
if a 'polarity' column was not found in the data frame. In this case, subduction
polarities will have to be manually provided to plot_subduction_teeth.
"""
pattern = "polarity"
for column in columns:
if re.fullmatch(pattern, column) is not None:
return column
return None
def _parse_geometries(geometries):
"""Resolve a geopandas.GeoSeries object into shapely BaseGeometry and/or
BaseMutipartGeometry instances.
Parameters
----------
geometries : geopandas.GeoDataFrame, sequence of shapely geometries, or str
If a `geopandas.GeoDataFrame` is given, its geometry attribute
will be used. If `geometries` is a string, it must be the path to
a file, which will be loaded with `geopandas.read_file`. Otherwise,
`geometries` must be a sequence of shapely geometry objects (instances
of the `shapely.geometry.base.BaseGeometry` class).
Returns
-------
out : list
Resolved shapely BaseMutipartGeometry and/or BaseGeometry instances.
"""
geometries = _get_geometries(geometries)
if isinstance(geometries, gpd.GeoSeries):
geometries = list(geometries)
# Explode multi-part geometries
# Weirdly the following seems to be faster than
# the equivalent explode() method from GeoPandas:
out = []
for i in geometries:
if isinstance(i, BaseMultipartGeometry):
out.extend(list(i.geoms))
else:
out.append(i)
return out
def shapelify_features(features, central_meridian=0.0, tessellate_degrees=None):
"""Generate Shapely `MultiPolygon` or `MultiLineString` geometries
from reconstructed feature polygons.
Notes
-----
Some Shapely polygons generated by `shapelify_features` cut longitudes of 180
or -180 degrees. These features may appear unclosed at the dateline, so Shapely
"closes" these polygons by connecting any of their open ends with lines. These
lines may manifest on GeoAxes plots as horizontal lines that span the entire
global extent. To prevent this, `shapelify_features` uses pyGPlates'
[DateLineWrapper](https://www.gplates.org/docs/pygplates/generated/pygplates.datelinewrapper)
to split a feature polygon into multiple closed polygons if it happens to cut the
antimeridian.
Another measure taken to ensure features are valid is to order exterior coordinates
of Shapely polygons anti-clockwise.
Parameters
----------
features : iterable of <pygplates.Feature>, <ReconstructedFeatureGeometry> or <GeometryOnSphere>
Iterable containing reconstructed polygon features.
central_meridian : float
Central meridian around which to perform wrapping; default: 0.0.
tessellate_degrees : float or None
If provided, geometries will be tessellated to this resolution prior
to wrapping.
Returns
-------
all_geometries : list of `shapely.geometry.BaseGeometry`
Shapely geometries converted from the given reconstructed features. Any
geometries at the dateline are split.
See Also
--------
geometry.pygplates_to_shapely : convert PyGPlates geometry objects to
Shapely geometries.
"""
if isinstance(
features,
(
pygplates.Feature,
pygplates.ReconstructedFeatureGeometry,
pygplates.GeometryOnSphere,
),
):
features = [features]
geometries = []
for feature in features:
if isinstance(feature, pygplates.Feature):
geometries.extend(feature.get_all_geometries())
elif isinstance(feature, pygplates.ReconstructedFeatureGeometry):
geometries.append(feature.get_reconstructed_geometry())
elif isinstance(feature, (pygplates.GeometryOnSphere, pygplates.LatLonPoint)):
geometries.append(feature)
elif isinstance(feature, pygplates.DateLineWrapper.LatLonMultiPoint):
geometries.append(
pygplates.MultiPointOnSphere(
[i.to_lat_lon() for i in feature.get_points()]
)
)
elif isinstance(feature, pygplates.DateLineWrapper.LatLonPolyline):
geometries.append(pygplates.PolylineOnSphere(feature.get_points()))
elif isinstance(feature, pygplates.DateLineWrapper.LatLonPolygon):
geometries.append(
pygplates.PolygonOnSphere(
[i.to_lat_lon() for i in feature.get_exterior_points()]
)
)
return [
pygplates_to_shapely(
i,
force_ccw=True,
validate=True,
central_meridian=central_meridian,
tessellate_degrees=tessellate_degrees,
explode=False,
)
for i in geometries
]
shapelify_feature_lines = shapelify_features
shapelify_feature_polygons = shapelify_features
class PlotTopologies(object):
"""A class with tools to read, reconstruct and plot topology features at specific
reconstruction times.
`PlotTopologies` is a shorthand for PyGPlates and Shapely functionalities that:
* Read features held in GPlates GPML (GPlates Markup Language) files and
ESRI shapefiles;
* Reconstruct the locations of these features as they migrate through
geological time;
* Turn these reconstructed features into Shapely geometries for plotting
on `cartopy.mpl.geoaxes.GeoAxes` or `cartopy.mpl.geoaxes.GeoAxesSubplot` map
Projections.
To call the `PlotTopologies` object, supply:
* an instance of the GPlately `plate_reconstruction` object
and optionally,
* a `coastline_filename`
* a `continent_filename`
* a `COB_filename`
* a reconstruction `time`
* an `anchor_plate_id`
For example:
# Calling the PlotTopologies object
gplot = gplately.plot.PlotTopologies(plate_reconstruction,
coastline_filename=None,
continent_filename=None,
COB_filename=None,
time=None,
anchor_plate_id=0,
)
# Setting a new reconstruction time
gplot.time = 20 # Ma
The `coastline_filename`, `continent_filename` and `COB_filename` can be single
strings to GPML and/or shapefiles, as well as instances of `pygplates.FeatureCollection`.
If using GPlately's `DataServer` object to source these files, they will be passed as
`pygplates.FeatureCollection` items.
Some features for plotting (like plate boundaries) are taken from the `PlateReconstruction`
object's`topology_features` attribute. They have already been reconstructed to the given
`time` using [Plate Tectonic Tools](https://github.com/EarthByte/PlateTectonicTools).
Simply provide a new reconstruction time by changing the `time` attribute, e.g.
gplot.time = 20 # Ma
which will automatically reconstruct all topologies to the specified time.
You __MUST__ set `gplot.time` before plotting anything.
A variety of geological features can be plotted on GeoAxes/GeoAxesSubplot maps
as Shapely `MultiLineString` or `MultiPolygon` geometries, including:
* subduction boundaries & subduction polarity teeth
* mid-ocean ridge boundaries
* transform boundaries
* miscellaneous boundaries
* coastline polylines
* continental polygons and
* continent-ocean boundary polylines
* topological plate velocity vector fields
* netCDF4 MaskedArray or ndarray raster data:
- seafloor age grids
- paleo-age grids
- global relief (topography and bathymetry)
* assorted reconstructable feature data, for example:
- seafloor fabric
- large igneous provinces
- volcanic provinces
Attributes
----------
plate_reconstruction : instance of <gplately.reconstruction.PlateReconstruction>
The GPlately `PlateReconstruction` object will be used to access a plate
`rotation_model` and a set of `topology_features` which contains plate boundary
features like trenches, ridges and transforms.
anchor_plate_id : int, default 0
The anchor plate ID used for reconstruction.
base_projection : instance of <cartopy.crs.{transform}>, default <cartopy.crs.PlateCarree> object
where {transform} is the map Projection to use on the Cartopy GeoAxes.
By default, the base projection is set to cartopy.crs.PlateCarree. See the
[Cartopy projection list](https://scitools.org.uk/cartopy/docs/v0.15/crs/projections.html)
for all supported Projection types.
coastlines : str, or instance of <pygplates.FeatureCollection>
The full string path to a coastline feature file. Coastline features can also
be passed as instances of the `pygplates.FeatureCollection` object (this is
the case if these features are sourced from the `DataServer` object).
continents : str, or instance of <pygplates.FeatureCollection>
The full string path to a continent feature file. Continent features can also
be passed as instances of the `pygplates.FeatureCollection` object (this is
the case if these features are sourced from the `DataServer` object).
COBs : str, or instance of <pygplates.FeatureCollection>
The full string path to a COB feature file. COB features can also be passed
as instances of the `pygplates.FeatureCollection` object (this is the case
if these features are sourced from the `DataServer` object).
coastlines : iterable/list of <pygplates.ReconstructedFeatureGeometry>
A list containing coastline features reconstructed to the specified `time` attribute.
continents : iterable/list of <pygplates.ReconstructedFeatureGeometry>
A list containing continent features reconstructed to the specified `time` attribute.
COBs : iterable/list of <pygplates.ReconstructedFeatureGeometry>
A list containing COB features reconstructed to the specified `time` attribute.
time : float
The time (Ma) to reconstruct and plot geological features to.
topologies : iterable/list of <pygplates.Feature>
A list containing assorted topologies like:
- pygplates.FeatureType.gpml_topological_network
- pygplates.FeatureType.gpml_oceanic_crust
- pygplates.FeatureType.gpml_topological_slab_boundary
- pygplates.FeatureType.gpml_topological_closed_plate_boundary
ridge_transforms : iterable/list of <pygplates.Feature>
A list containing ridge and transform boundary sections of type
pygplates.FeatureType.gpml_mid_ocean_ridge
ridges : iterable/list of <pygplates.Feature>
A list containing ridge boundary sections of type pygplates.FeatureType.gpml_mid_ocean_ridge
transforms : iterable/list of <pygplates.Feature>
A list containing transform boundary sections of type pygplates.FeatureType.gpml_mid_ocean_ridge
trenches : iterable/list of <pygplates.Feature>
A list containing trench boundary sections of type pygplates.FeatureType.gpml_subduction_zone
trench_left : iterable/list of <pygplates.Feature>
A list containing left subduction boundary sections of type pygplates.FeatureType.gpml_subduction_zone
trench_right : iterable/list of <pygplates.Feature>
A list containing right subduction boundary sections of type pygplates.FeatureType.gpml_subduction_zone
other : iterable/list of <pygplates.Feature>
A list containing other geological features like unclassified features, extended continental crusts,
continental rifts, faults, orogenic belts, fracture zones, inferred paleo boundaries, terrane
boundaries and passive continental boundaries.
"""
def __init__(
self,
plate_reconstruction,
coastlines=None,
continents=None,
COBs=None,
time=None,
anchor_plate_id=0,
):
self.plate_reconstruction = plate_reconstruction
if self.plate_reconstruction.topology_features is None:
raise ValueError("Plate model must have topology features.")
self.base_projection = ccrs.PlateCarree()
# store these for when time is updated
# make sure these are initialised as FeatureCollection objects
self._coastlines = _load_FeatureCollection(coastlines)
self._continents = _load_FeatureCollection(continents)
self._COBs = _load_FeatureCollection(COBs)
self.coastlines = None
self.continents = None
self.COBs = None
self._anchor_plate_id = self._check_anchor_plate_id(anchor_plate_id)
# store topologies for easy access
# setting time runs the update_time routine
if time is not None:
self.time = time
else:
self._time = None
def __getstate__(self):
filenames = self.plate_reconstruction.__getstate__()
# add important variables from Points object
if self._coastlines:
filenames["coastlines"] = self._coastlines.filenames
if self._continents:
filenames["continents"] = self._continents.filenames
if self._COBs:
filenames["COBs"] = self._COBs.filenames
filenames['time'] = self.time
filenames['plate_id'] = self._anchor_plate_id
return filenames
def __setstate__(self, state):
self.plate_reconstruction = _PlateReconstruction(state['rotation_model'], state['topology_features'], state['static_polygons'])
self._coastlines = None
self._continents = None
self._COBs = None
self.coastlines = None
self.continents = None
self.COBs = None
# reinstate unpicklable items
if 'coastlines' in state:
self._coastlines = _FeatureCollection()
for feature in state['coastlines']:
self._coastlines.add( _FeatureCollection(feature) )
if 'continents' in state:
self._continents = _FeatureCollection()
for feature in state['continents']:
self._continents.add( _FeatureCollection(feature) )
if 'COBs' in state:
self._COBs = _FeatureCollection()
for feature in state['COBs']:
self._COBs.add( _FeatureCollection(feature) )
self._anchor_plate_id = state["plate_id"]
self.base_projection = ccrs.PlateCarree()
self._time = None
@property
def time(self):
""" The reconstruction time."""
return self._time
@time.setter
def time(self, var):
"""Allows the time attribute to be changed. Updates all instances of the time attribute in the object (e.g.
reconstructions and resolving topologies will use this new time).
Raises
------
ValueError
If the chosen reconstruction time is <0 Ma.
"""
if var >= 0:
self.update_time(var)
else:
raise ValueError("Enter a valid time >= 0")
@property
def anchor_plate_id(self):
"""Anchor plate ID for reconstruction. Must be an integer >= 0."""
return self._anchor_plate_id
@anchor_plate_id.setter
def anchor_plate_id(self, anchor_plate):
self._anchor_plate_id = self._check_anchor_plate_id(anchor_plate)
self.update_time(self.time)
@staticmethod
def _check_anchor_plate_id(id):
id = int(id)
if id < 0:
raise ValueError(
"Invalid anchor plate ID: {}".format(id)
)
return id
def update_time(self, time):
"""Re-reconstruct features and topologies to the time specified by the `PlotTopologies` `time` attribute
whenever it or the anchor plate is updated.
Notes
-----
The following `PlotTopologies` attributes are updated whenever a reconstruction `time` attribute is set:
- resolved topology features (topological plates and networks)
- ridge and transform boundary sections (resolved features)
- ridge boundary sections (resolved features)
- transform boundary sections (resolved features)
- subduction boundary sections (resolved features)
- left subduction boundary sections (resolved features)
- right subduction boundary sections (resolved features)
- other boundary sections (resolved features) that are not subduction zones or mid-ocean ridges
(ridge/transform)
Moreover, coastlines, continents and COBs are reconstructed to the new specified `time`.
"""
self._time = float(time)
resolved_topologies = ptt.resolve_topologies.resolve_topologies_into_features(
self.plate_reconstruction.rotation_model,
self.plate_reconstruction.topology_features,
self.time)
self.topologies, self.ridge_transforms, self.ridges, self.transforms, self.trenches, self.trench_left, self.trench_right, self.other = resolved_topologies
# miscellaneous boundaries
self.continental_rifts = []
self.faults = []
self.fracture_zones = []
self.inferred_paleo_boundaries = []
self.terrane_boundaries = []
self.transitional_crusts = []
self.orogenic_belts = []
self.sutures = []
self.continental_crusts = []
self.extended_continental_crusts = []
self.passive_continental_boundaries = []
self.slab_edges = []
self.misc_transforms = []
self.unclassified_features = []
for topol in self.other:
if topol.get_feature_type() == pygplates.FeatureType.gpml_continental_rift:
self.continental_rifts.append(topol)
elif topol.get_feature_type() == pygplates.FeatureType.gpml_fault:
self.faults.append(topol)
elif topol.get_feature_type() == pygplates.FeatureType.gpml_fracture_zone:
self.fracture_zones.append(topol)
elif topol.get_feature_type() == pygplates.FeatureType.gpml_inferred_paleo_boundary:
self.inferred_paleo_boundaries.append(topol)
elif topol.get_feature_type() == pygplates.FeatureType.gpml_terrane_boundary:
self.terrane_boundaries.append(topol)
elif topol.get_feature_type() == pygplates.FeatureType.gpml_transitional_crust:
self.transitional_crusts.append(topol)
elif topol.get_feature_type() == pygplates.FeatureType.gpml_orogenic_belt:
self.orogenic_belts.append(topol)
elif topol.get_feature_type() == pygplates.FeatureType.gpml_suture:
self.sutures.append(topol)
elif topol.get_feature_type() == pygplates.FeatureType.gpml_continental_crust:
self.continental_crusts.append(topol)
elif topol.get_feature_type() == pygplates.FeatureType.gpml_extended_continental_crust:
self.extended_continental_crusts.append(topol)
elif topol.get_feature_type() == pygplates.FeatureType.gpml_passive_continental_boundary:
self.passive_continental_boundaries.append(topol)
elif topol.get_feature_type() == pygplates.FeatureType.gpml_slab_edge:
self.slab_edges.append(topol)
elif topol.get_feature_type() == pygplates.FeatureType.gpml_transform:
self.misc_transforms.append(topol)
elif topol.get_feature_type() == pygplates.FeatureType.gpml_unclassified_feature:
self.unclassified_features.append(topol)
# reconstruct other important polygons and lines
if self._coastlines:
self.coastlines = self.plate_reconstruction.reconstruct(
self._coastlines, self.time, from_time=0, anchor_plate_id=self.anchor_plate_id)
if self._continents:
self.continents = self.plate_reconstruction.reconstruct(
self._continents, self.time, from_time=0, anchor_plate_id=self.anchor_plate_id)
if self._COBs:
self.COBs = self.plate_reconstruction.reconstruct(
self._COBs, self.time, from_time=0, anchor_plate_id=self.anchor_plate_id)
# subduction teeth
def _tessellate_triangles(self, features, tesselation_radians, triangle_base_length, triangle_aspect=1.0):
"""Places subduction teeth along subduction boundary line segments within a MultiLineString shapefile.
Parameters
----------
shapefilename : str
Path to shapefile containing the subduction boundary features
tesselation_radians : float
Parametrises subduction teeth density. Triangles are generated only along line segments with distances
that exceed the given threshold tessellation_radians.
triangle_base_length : float
Length of teeth triangle base
triangle_aspect : float, default=1.0
Aspect ratio of teeth triangles. Ratio is 1.0 by default.
Returns
-------
X_points : (n,3) array
X points that define the teeth triangles
Y_points : (n,3) array
Y points that define the teeth triangles
"""
tesselation_degrees = np.degrees(tesselation_radians)
triangle_pointsX = []
triangle_pointsY = []
date_line_wrapper = pygplates.DateLineWrapper()
for feature in features:
cum_distance = 0.0
for geometry in feature.get_geometries():
wrapped_lines = date_line_wrapper.wrap(geometry)
for line in wrapped_lines:
pts = np.array([(p.get_longitude(), p.get_latitude()) for p in line.get_points()])
for p in range(0, len(pts) - 1):
A = pts[p]
B = pts[p+1]
AB_dist = B - A
AB_norm = AB_dist / np.hypot(*AB_dist)
cum_distance += np.hypot(*AB_dist)
# create a new triangle if cumulative distance is exceeded.
if cum_distance >= tesselation_degrees:
C = A + triangle_base_length*AB_norm
# find normal vector
AD_dist = np.array([AB_norm[1], -AB_norm[0]])
AD_norm = AD_dist / np.linalg.norm(AD_dist)
C0 = A + 0.5*triangle_base_length*AB_norm
# project point along normal vector
D = C0 + triangle_base_length*triangle_aspect*AD_norm
triangle_pointsX.append( [A[0], C[0], D[0]] )
triangle_pointsY.append( [A[1], C[1], D[1]] )
cum_distance = 0.0
return np.array(triangle_pointsX), np.array(triangle_pointsY)
def get_feature(self, feature):
"""Create a geopandas.GeoDataFrame object containing geometries of reconstructed features.
Notes
-----
The feature needed to produce the GeoDataFrame should already be constructed to a `time`.
This function converts the feature into a set of Shapely geometries whose coordinates are
passed to a geopandas GeoDataFrame.
Parameters
----------
feature : instance of <pygplates.Feature>
A feature reconstructed to `time`.
Returns
-------
gdf : instance of <geopandas.GeoDataFrame>
A pandas.DataFrame that has a column with `feature` geometries.
"""
shp = shapelify_features(feature)
gdf = gpd.GeoDataFrame({'geometry': shp}, geometry='geometry')
return gdf
def plot_feature(self, ax, feature, **kwargs):
""" Plot pygplates.FeatureCollection or pygplates.Feature onto a map.
Parameters
----------
ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot>
A subclass of `matplotlib.axes.Axes` which represents a map Projection.
The map should be set at a particular Cartopy projection.
**kwargs :
Keyword arguments for parameters such as `facecolor`, `alpha`,
etc. for plotting coastline geometries.
See `Matplotlib` keyword arguments
[here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html).
Returns
-------
ax : instance of <geopandas.GeoDataFrame.plot>
A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map
with coastline features plotted onto the chosen map projection.
"""
gdf = self.get_feature(feature)
return gdf.plot(ax=ax, transform=self.base_projection, **kwargs)
def get_coastlines(self):
"""Create a geopandas.GeoDataFrame object containing geometries of reconstructed coastline polygons.
Notes
-----
The `coastlines` needed to produce the GeoDataFrame are automatically constructed if the optional `time`
parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed
either when `PlotTopologies` is first called...
gplot = gplately.PlotTopologies(..., time=100,...)
or anytime afterwards, by setting:
time = 100 #Ma
gplot.time = time
...after which this function can be re-run. Once the `coastlines` are reconstructed, they are
converted into Shapely polygons whose coordinates are passed to a geopandas GeoDataFrame.
Returns
-------
gdf : instance of <geopandas.GeoDataFrame>
A pandas.DataFrame that has a column with `coastlines` geometry.
Raises
------
ValueError
If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct
`coastlines` to the requested `time` and thus populate the GeoDataFrame.
"""
if self._time is None:
raise ValueError("No coastlines have been resolved. Set `PlotTopologies.time` to construct coastlines.")
if self.coastlines is None:
raise ValueError("Supply coastlines to PlotTopologies object")
coastline_polygons = shapelify_feature_polygons(self.coastlines)
gdf = gpd.GeoDataFrame({"geometry": coastline_polygons}, geometry="geometry")
return gdf
def plot_coastlines(self, ax, **kwargs):
"""Plot reconstructed coastline polygons onto a standard map Projection.
Notes
-----
The `coastlines` for plotting are accessed from the `PlotTopologies` object's
`coastlines` attribute. These `coastlines` are reconstructed to the `time`
passed to the `PlotTopologies` object and converted into Shapely polylines. The
reconstructed `coastlines` are added onto the GeoAxes or GeoAxesSubplot map `ax` using
GeoPandas.
Map resentation details (e.g. facecolor, edgecolor, alpha…) are permitted as keyword
arguments.
Parameters
----------
ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot>
A subclass of `matplotlib.axes.Axes` which represents a map Projection.
The map should be set at a particular Cartopy projection.
**kwargs :
Keyword arguments for parameters such as `facecolor`, `alpha`,
etc. for plotting coastline geometries.
See `Matplotlib` keyword arguments
[here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html).
Returns
-------
ax : instance of <geopandas.GeoDataFrame.plot>
A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map
with coastline features plotted onto the chosen map projection.
"""
gdf = self.get_coastlines()
return gdf.plot(ax=ax, transform=self.base_projection, **kwargs)
def get_continents(self):
"""Create a geopandas.GeoDataFrame object containing geometries of reconstructed continental polygons.
Notes
-----
The `continents` needed to produce the GeoDataFrame are automatically constructed if the optional `time`
parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed
either when `PlotTopologies` is first called...
gplot = gplately.PlotTopologies(..., time=100,...)
or anytime afterwards, by setting:
time = 100 #Ma
gplot.time = time
...after which this function can be re-run. Once the `continents` are reconstructed, they are
converted into Shapely polygons whose coordinates are passed to a geopandas GeoDataFrame.
Returns
-------
gdf : instance of <geopandas.GeoDataFrame>
A pandas.DataFrame that has a column with `continents` geometry.
Raises
------
ValueError
If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct
`continents` to the requested `time` and thus populate the GeoDataFrame.
"""
if self._time is None:
raise ValueError("No continents have been resolved. Set `PlotTopologies.time` to construct continents.")
if self.continents is None:
raise ValueError("Supply continents to PlotTopologies object")
continent_polygons = shapelify_feature_polygons(self.continents)
gdf = gpd.GeoDataFrame({"geometry": continent_polygons}, geometry="geometry")
return gdf
def plot_continents(self, ax, **kwargs):
"""Plot reconstructed continental polygons onto a standard map Projection.
Notes
-----
The `continents` for plotting are accessed from the `PlotTopologies` object's
`continents` attribute. These `continents` are reconstructed to the `time`
passed to the `PlotTopologies` object and converted into Shapely polygons.
The reconstructed `coastlines` are plotted onto the GeoAxes or GeoAxesSubplot map `ax` using
GeoPandas.
Map presentation details (e.g. facecolor, edgecolor, alpha…) are permitted as
keyword arguments.
Parameters
----------
ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot>
A subclass of `matplotlib.axes.Axes` which represents a map Projection.
The map should be set at a particular Cartopy projection.
**kwargs :
Keyword arguments for parameters such as `facecolor`, `alpha`,
etc. for plotting continental geometries.
See `Matplotlib` keyword arguments
[here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html).
Returns
-------
ax : instance of <geopandas.GeoDataFrame.plot>
A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map
with continent features plotted onto the chosen map projection.
"""
gdf = self.get_continents()
return gdf.plot(ax=ax, transform=self.base_projection, **kwargs)
def get_continent_ocean_boundaries(self):
"""Create a geopandas.GeoDataFrame object containing geometries of reconstructed continent-ocean
boundary lines.
Notes
-----
The `COBs` needed to produce the GeoDataFrame are automatically constructed if the optional `time`
parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed
either when `PlotTopologies` is first called...
gplot = gplately.PlotTopologies(..., time=100,...)
or anytime afterwards, by setting:
time = 100 #Ma
gplot.time = time
...after which this function can be re-run. Once the `COBs` are reconstructed, they are
converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame.
Returns
-------
gdf : instance of <geopandas.GeoDataFrame>
A pandas.DataFrame that has a column with `COBs` geometry.
Raises
------
ValueError
If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct
`COBs` to the requested `time` and thus populate the GeoDataFrame.
"""
if self._time is None:
raise ValueError("No geometries have been resolved. Set `PlotTopologies.time` to construct topologies.")
if self.COBs is None:
raise ValueError("Supply COBs to PlotTopologies object")
COB_lines = shapelify_feature_lines(self.COBs)
gdf = gpd.GeoDataFrame({"geometry": COB_lines}, geometry="geometry")
return gdf
def plot_continent_ocean_boundaries(self, ax, **kwargs):
"""Plot reconstructed continent-ocean boundary (COB) polygons onto a standard
map Projection.
Notes
-----
The `COBs` for plotting are accessed from the `PlotTopologies` object's
`COBs` attribute. These `COBs` are reconstructed to the `time`
passed to the `PlotTopologies` object and converted into Shapely polylines.
The reconstructed `COBs` are plotted onto the GeoAxes or GeoAxesSubplot map
`ax` using GeoPandas. Map presentation details (e.g. `facecolor`, `edgecolor`, `alpha`…)
are permitted as keyword arguments.
These COBs are transformed into shapely
geometries and added onto the chosen map for a specific geological time (supplied to the
PlotTopologies object). Map presentation details (e.g. facecolor, edgecolor, alpha…)
are permitted.
Parameters
----------
ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot>
A subclass of `matplotlib.axes.Axes` which represents a map Projection.
The map should be set at a particular Cartopy projection.
**kwargs :
Keyword arguments for parameters such as `facecolor`, `alpha`,
etc. for plotting COB geometries.
See `Matplotlib` keyword arguments
[here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html).
Returns
-------
ax : instance of <geopandas.GeoDataFrame.plot>
A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map
with COB features plotted onto the chosen map projection.
"""
gdf = self.get_continent_ocean_boundaries()
return gdf.plot(ax=ax, transform=self.base_projection, **kwargs)
def get_ridges(self):
"""Create a geopandas.GeoDataFrame object containing geometries of reconstructed ridge lines.
Notes
-----
The `ridges` needed to produce the GeoDataFrame are automatically constructed if the optional `time`
parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed
either when `PlotTopologies` is first called...
gplot = gplately.PlotTopologies(..., time=100,...)
or anytime afterwards, by setting:
time = 100 #Ma
gplot.time = time
...after which this function can be re-run. Once the `ridges` are reconstructed, they are
converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame.
Returns
-------
gdf : instance of <geopandas.GeoDataFrame>
A pandas.DataFrame that has a column with `ridges` geometry.
Raises
------
ValueError
If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct
`ridges` to the requested `time` and thus populate the GeoDataFrame.
"""
if self._time is None:
raise ValueError("No ridges have been resolved. Set `PlotTopologies.time` to construct ridges.")
if self.ridges is None:
raise ValueError("No ridge topologies passed to PlotTopologies.")
ridge_lines = shapelify_feature_lines(self.ridges)
gdf = gpd.GeoDataFrame({"geometry": ridge_lines}, geometry="geometry")
return gdf
def plot_ridges(self, ax, color='black', **kwargs):
"""Plot reconstructed ridge polylines onto a standard map Projection.
Notes
-----
The `ridges` for plotting are accessed from the `PlotTopologies` object's
`ridges` attribute. These `ridges` are reconstructed to the `time`
passed to the `PlotTopologies` object and converted into Shapely polylines.
The reconstructed `ridges` are plotted onto the GeoAxes or GeoAxesSubplot map
`ax` using GeoPandas. Map presentation details (e.g. `facecolor`, `edgecolor`, `alpha`…)
are permitted as keyword arguments.
Ridge geometries are wrapped to the dateline using
pyGPlates' [DateLineWrapper](https://www.gplates.org/docs/pygplates/generated/pygplates.datelinewrapper)
by splitting a polyline into multiple polylines at the dateline. This is to avoid
horizontal lines being formed between polylines at longitudes of -180 and 180 degrees.
Point features near the poles (-89 & 89 degree latitude) are also clipped to ensure
compatibility with Cartopy.
Parameters
----------
ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot>
A subclass of `matplotlib.axes.Axes` which represents a map Projection.
The map should be set at a particular Cartopy projection.
color : str, default=’black’
The colour of the ridge lines. By default, it is set to black.
**kwargs :
Keyword arguments for parameters such as `alpha`, etc. for
plotting ridge geometries.
See `Matplotlib` keyword arguments
[here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html).
Returns
-------
ax : instance of <geopandas.GeoDataFrame.plot>
A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map
with ridge features plotted onto the chosen map projection.
"""
gdf = self.get_ridges()
return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs)
def get_ridges_and_transforms(self):
"""Create a geopandas.GeoDataFrame object containing geometries of reconstructed ridge and transform lines.
Notes
-----
The `ridge_transforms` needed to produce the GeoDataFrame are automatically constructed if the optional `time`
parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed
either when `PlotTopologies` is first called...
gplot = gplately.PlotTopologies(..., time=100,...)
or anytime afterwards, by setting:
time = 100 #Ma
gplot.time = time
...after which this function can be re-run. Once the `ridge_transforms` are reconstructed, they are
converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame.
Returns
-------
gdf : instance of <geopandas.GeoDataFrame>
A pandas.DataFrame that has a column with `ridges` geometry.
Raises
------
ValueError
If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct
`ridge_transforms` to the requested `time` and thus populate the GeoDataFrame.
"""
if self._time is None:
raise ValueError("No ridges and transforms have been resolved. Set `PlotTopologies.time` to construct ridges and transforms.")
if self.ridge_transforms is None:
raise ValueError("No ridge and transform topologies passed to PlotTopologies.")
ridge_transform_lines = shapelify_feature_lines(self.ridge_transforms)
gdf = gpd.GeoDataFrame({"geometry": ridge_transform_lines}, geometry="geometry")
return gdf
def plot_ridges_and_transforms(self, ax, color='black', **kwargs):
"""Plot reconstructed ridge & transform boundary polylines onto a standard map
Projection.
Notes
-----
The ridge & transform sections for plotting are accessed from the
`PlotTopologies` object's `ridge_transforms` attribute. These `ridge_transforms`
are reconstructed to the `time` passed to the `PlotTopologies` object and converted
into Shapely polylines. The reconstructed `ridge_transforms` are plotted onto the
GeoAxes or GeoAxesSubplot map `ax` using GeoPandas. Map presentation details
(e.g. `facecolor`, `edgecolor`, `alpha`…) are permitted as keyword arguments.
Note: Ridge & transform geometries are wrapped to the dateline using
pyGPlates' [DateLineWrapper](https://www.gplates.org/docs/pygplates/generated/pygplates.datelinewrapper)
by splitting a polyline into multiple polylines at the dateline. This is to avoid
horizontal lines being formed between polylines at longitudes of -180 and 180 degrees.
Point features near the poles (-89 & 89 degree latitude) are also clipped to ensure
compatibility with Cartopy.
Parameters
----------
ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot>
A subclass of `matplotlib.axes.Axes` which represents a map Projection.
The map should be set at a particular Cartopy projection.
color : str, default=’black’
The colour of the ridge & transform lines. By default, it is set to black.
**kwargs :
Keyword arguments for parameters such as ‘alpha’, etc. for
plotting ridge & transform geometries.
See `Matplotlib` keyword arguments
[here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html).
Returns
-------
ax : instance of <geopandas.GeoDataFrame.plot>
A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map
with ridge & transform features plotted onto the chosen map projection.
"""
gdf = self.get_ridges_and_transforms()
return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs)
def get_transforms(self):
"""Create a geopandas.GeoDataFrame object containing geometries of reconstructed transform lines.
Notes
-----
The `transforms` needed to produce the GeoDataFrame are automatically constructed if the optional `time`
parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed
either when `PlotTopologies` is first called...
gplot = gplately.PlotTopologies(..., time=100,...)
or anytime afterwards, by setting:
time = 100 #Ma
gplot.time = time
...after which this function can be re-run. Once the `transforms` are reconstructed, they are
converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame.
Returns
-------
gdf : instance of <geopandas.GeoDataFrame>
A pandas.DataFrame that has a column with `transforms` geometry.
Raises
------
ValueError
If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct
`transforms` to the requested `time` and thus populate the GeoDataFrame.
"""
if self._time is None:
raise ValueError("No transforms have been resolved. Set `PlotTopologies.time` to construct transforms.")
if self.transforms is None:
raise ValueError("No transform topologies passed to PlotTopologies.")
transform_lines = shapelify_feature_lines(self.transforms)
gdf = gpd.GeoDataFrame({"geometry": transform_lines}, geometry="geometry")
return gdf
def plot_transforms(self, ax, color='black', **kwargs):
"""Plot reconstructed transform boundary polylines onto a standard map.
Notes
-----
The transform sections for plotting are accessed from the
`PlotTopologies` object's `transforms` attribute. These `transforms`
are reconstructed to the `time` passed to the `PlotTopologies` object and converted
into Shapely polylines. The reconstructed `transforms` are plotted onto the
GeoAxes or GeoAxesSubplot map `ax` using GeoPandas. Map presentation details
(e.g. `facecolor`, `edgecolor`, `alpha`…) are permitted as keyword arguments.
Transform geometries are wrapped to the dateline using
pyGPlates' [DateLineWrapper](https://www.gplates.org/docs/pygplates/generated/pygplates.datelinewrapper)
by splitting a polyline into multiple polylines at the dateline. This is to avoid
horizontal lines being formed between polylines at longitudes of -180 and 180 degrees.
Point features near the poles (-89 & 89 degree latitude) are also clipped to ensure
compatibility with Cartopy.
Parameters
----------
ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot>
A subclass of `matplotlib.axes.Axes` which represents a map Projection.
The map should be set at a particular Cartopy projection.
color : str, default=’black’
The colour of the transform lines. By default, it is set to black.
**kwargs :
Keyword arguments for parameters such as `alpha`, etc.
for plotting transform geometries.
See `Matplotlib` keyword arguments
[here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html).
Returns
-------
ax : instance of <geopandas.GeoDataFrame.plot>
A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map
with transform features plotted onto the chosen map projection.
"""
gdf = self.get_transforms()
return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs)
def get_trenches(self):
"""Create a geopandas.GeoDataFrame object containing geometries of reconstructed trench lines.
Notes
-----
The `trenches` needed to produce the GeoDataFrame are automatically constructed if the optional `time`
parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed
either when `PlotTopologies` is first called...
gplot = gplately.PlotTopologies(..., time=100,...)
or anytime afterwards, by setting:
time = 100 #Ma
gplot.time = time
...after which this function can be re-run. Once the `trenches` are reconstructed, they are
converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame.
Returns
-------
gdf : instance of <geopandas.GeoDataFrame>
A pandas.DataFrame that has a column with `trenches` geometry.
Raises
------
ValueError
If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct
`trenches` to the requested `time` and thus populate the GeoDataFrame.
"""
if self._time is None:
raise ValueError("No trenches have been resolved. Set `PlotTopologies.time` to construct trenches.")
if self.trenches is None:
raise ValueError("No trenches passed to PlotTopologies.")
trench_lines = shapelify_feature_lines(self.trenches)
gdf = gpd.GeoDataFrame({"geometry": trench_lines}, geometry="geometry")
return gdf
def plot_trenches(self, ax, color='black', **kwargs):
"""Plot reconstructed subduction trench polylines onto a standard map
Projection.
Notes
-----
The trench sections for plotting are accessed from the
`PlotTopologies` object's `trenches` attribute. These `trenches`
are reconstructed to the `time` passed to the `PlotTopologies` object and converted
into Shapely polylines. The reconstructed `trenches` are plotted onto the
GeoAxes or GeoAxesSubplot map `ax` using GeoPandas. Map presentation details
(e.g. `facecolor`, `edgecolor`, `alpha`…) are permitted as keyword arguments.
Trench geometries are wrapped to the dateline using
pyGPlates' [DateLineWrapper](https://www.gplates.org/docs/pygplates/generated/pygplates.datelinewrapper)
by splitting a polyline into multiple polylines at the dateline. This is to avoid
horizontal lines being formed between polylines at longitudes of -180 and 180 degrees.
Point features near the poles (-89 & 89 degree latitude) are also clipped to ensure
compatibility with Cartopy.
Parameters
----------
ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot>
A subclass of `matplotlib.axes.Axes` which represents a map Projection.
The map should be set at a particular Cartopy projection.
color : str, default=’black’
The colour of the trench lines. By default, it is set to black.
**kwargs :
Keyword arguments for parameters such as `alpha`, etc.
for plotting trench geometries.
See `Matplotlib` keyword arguments
[here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html).
Returns
-------
ax : instance of <geopandas.GeoDataFrame.plot>
A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map
with transform features plotted onto the chosen map projection.
"""
gdf = self.get_trenches()
return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs)
def get_misc_boundaries(self):
"""Create a geopandas.GeoDataFrame object containing geometries of other reconstructed lines.
Notes
-----
The `other` geometries needed to produce the GeoDataFrame are automatically constructed if the optional `time`
parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed
either when `PlotTopologies` is first called...
gplot = gplately.PlotTopologies(..., time=100,...)
or anytime afterwards, by setting:
time = 100 #Ma
gplot.time = time
...after which this function can be re-run. Once the `other` geometries are reconstructed, they are
converted into Shapely features whose coordinates are passed to a geopandas GeoDataFrame.
Returns
-------
gdf : instance of <geopandas.GeoDataFrame>
A pandas.DataFrame that has a column with `other` geometry.
Raises
------
ValueError
If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct
`other` geometries to the requested `time` and thus populate the GeoDataFrame.
"""
if self._time is None:
raise ValueError("No miscellaneous topologies have been resolved. Set `PlotTopologies.time` to construct them.")
if self.other is None:
raise ValueError("No miscellaneous topologies passed to PlotTopologies.")
lines = shapelify_features(self.other)
gdf = gpd.GeoDataFrame({"geometry": lines}, geometry="geometry")
return gdf
def plot_misc_boundaries(self, ax, color="black", **kwargs):
"""Plot reconstructed miscellaneous plate boundary polylines onto a standard
map Projection.
Notes
-----
The miscellaneous boundary sections for plotting are accessed from the
`PlotTopologies` object's `other` attribute. These `other` boundaries
are reconstructed to the `time` passed to the `PlotTopologies` object and converted
into Shapely polylines. The reconstructed `other` boundaries are plotted onto the
GeoAxes or GeoAxesSubplot map `ax` using GeoPandas. Map presentation details
(e.g. `facecolor`, `edgecolor`, `alpha`…) are permitted as keyword arguments.
Miscellaneous boundary geometries are wrapped to the dateline using
pyGPlates' [DateLineWrapper](https://www.gplates.org/docs/pygplates/generated/pygplates.datelinewrapper)
by splitting a polyline into multiple polylines at the dateline. This is to avoid
horizontal lines being formed between polylines at longitudes of -180 and 180 degrees.
Point features near the poles (-89 & 89 degree latitude) are also clipped to ensure
compatibility with Cartopy.
Parameters
----------
ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot>
A subclass of `matplotlib.axes.Axes` which represents a map Projection.
The map should be set at a particular Cartopy projection.
color : str, default=’black’
The colour of the boundary lines. By default, it is set to black.
**kwargs :
Keyword arguments for parameters such as ‘alpha’, etc. for
plotting miscellaneous boundary geometries.
See `Matplotlib` keyword arguments
[here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html).
Returns
-------
ax : instance of <geopandas.GeoDataFrame.plot>
A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map
with miscellaneous boundary features plotted onto the chosen map projection.
"""
gdf = self.get_misc_boundaries()
return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs)
def plot_subduction_teeth_deprecated(self, ax, spacing=0.1, size=2.0, aspect=1, color='black', **kwargs):
"""Plot subduction teeth onto a standard map Projection.
Notes
-----
Subduction teeth are tessellated from `PlotTopologies` object attributes `trench_left` and
`trench_right`, and transformed into Shapely polygons for plotting.
Parameters
----------
ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot>
A subclass of `matplotlib.axes.Axes` which represents a map Projection.
The map should be set at a particular Cartopy projection.
spacing : float, default=0.1
The tessellation threshold (in radians). Parametrises subduction tooth density.
Triangles are generated only along line segments with distances that exceed
the given threshold ‘spacing’.
size : float, default=2.0
Length of teeth triangle base.
aspect : float, default=1
Aspect ratio of teeth triangles. Ratio is 1.0 by default.
color : str, default=’black’
The colour of the teeth. By default, it is set to black.
**kwargs :
Keyword arguments for parameters such as ‘alpha’, etc. for
plotting subduction tooth polygons.
See `Matplotlib` keyword arguments
[here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html).
Returns
-------
ax : instance of <geopandas.GeoDataFrame.plot>
A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map
with subduction teeth plotted onto the chosen map projection.
"""
import shapely
# add Subduction Teeth
subd_xL, subd_yL = self._tessellate_triangles(
self.trench_left,
tesselation_radians=spacing,
triangle_base_length=size,
triangle_aspect=-aspect)
subd_xR, subd_yR = self._tessellate_triangles(
self.trench_right,
tesselation_radians=spacing,
triangle_base_length=size,
triangle_aspect=aspect)
teeth = []
for tX, tY in zip(subd_xL, subd_yL):
triangle_xy_points = np.c_[tX, tY]
shp = shapely.geometry.Polygon(triangle_xy_points)
teeth.append(shp)
for tX, tY in zip(subd_xR, subd_yR):
triangle_xy_points = np.c_[tX, tY]
shp = shapely.geometry.Polygon(triangle_xy_points)
teeth.append(shp)
return ax.add_geometries(teeth, crs=self.base_projection, color=color, **kwargs)
def get_subduction_direction(self):
"""Create a geopandas.GeoDataFrame object containing geometries of trench directions.
Notes
-----
The `trench_left` and `trench_right` geometries needed to produce the GeoDataFrame are automatically
constructed if the optional `time` parameter is passed to the `PlotTopologies` object before calling
this function. `time` can be passed either when `PlotTopologies` is first called...
gplot = gplately.PlotTopologies(..., time=100,...)
or anytime afterwards, by setting:
time = 100 #Ma
gplot.time = time
...after which this function can be re-run. Once the `other` geometries are reconstructed, they are
converted into Shapely features whose coordinates are passed to a geopandas GeoDataFrame.
Returns
-------
gdf_left : instance of <geopandas.GeoDataFrame>
A pandas.DataFrame that has a column with `trench_left` geometry.
gdf_right : instance of <geopandas.GeoDataFrame>
A pandas.DataFrame that has a column with `trench_right` geometry.
Raises
------
ValueError
If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct
`trench_left` or `trench_right` geometries to the requested `time` and thus populate the GeoDataFrame.
"""
if self._time is None:
raise ValueError("No miscellaneous topologies have been resolved. Set `PlotTopologies.time` to construct them.")
if self.trench_left is None or self.trench_right is None:
raise ValueError("No trench_left or trench_right topologies passed to PlotTopologies.")
trench_left_features = shapelify_feature_lines(self.trench_left)
trench_right_features = shapelify_feature_lines(self.trench_right)
gdf_left = gpd.GeoDataFrame({"geometry": trench_left_features}, geometry="geometry")
gdf_right = gpd.GeoDataFrame({"geometry": trench_right_features}, geometry="geometry")
return gdf_left, gdf_right
def plot_subduction_teeth(self, ax, spacing=0.07, size=None, aspect=None, color='black', **kwargs):
"""Plot subduction teeth onto a standard map Projection.
Notes
-----
Subduction teeth are tessellated from `PlotTopologies` object attributes `trench_left` and
`trench_right`, and transformed into Shapely polygons for plotting.
Parameters
----------
ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot>
A subclass of `matplotlib.axes.Axes` which represents a map Projection.
The map should be set at a particular Cartopy projection.
spacing : float, default=0.1
The tessellation threshold (in radians). Parametrises subduction tooth density.
Triangles are generated only along line segments with distances that exceed
the given threshold ‘spacing’.
size : float, default=None
Length of teeth triangle base (in radians). If kept at `None`, then
`size = 0.5*spacing`.
aspect : float, default=None
Aspect ratio of teeth triangles. If kept at `None`, then `aspect = 2/3*size`.
color : str, default=’black’
The colour of the teeth. By default, it is set to black.
**kwargs :
Keyword arguments parameters such as ‘alpha’, etc.
for plotting subduction tooth polygons.
See `Matplotlib` keyword arguments
[here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html).
Returns
-------
ax : instance of <geopandas.GeoDataFrame.plot>
A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map
with subduction teeth plotted onto the chosen map projection.
"""
if self._time is None:
raise ValueError("No miscellaneous topologies have been resolved. Set `PlotTopologies.time` to construct them.")
spacing = spacing * EARTH_RADIUS * 1e3
if aspect is None:
aspect = 2.0/3.0
if size is None:
size = spacing*0.5
height = size*aspect
trench_left_features = shapelify_feature_lines(self.trench_left)
trench_right_features = shapelify_feature_lines(self.trench_right)
return(
plot_subduction_teeth(trench_left_features, size, 'l', height, spacing, ax=ax, color=color, **kwargs),
plot_subduction_teeth(trench_right_features, size, 'r', height, spacing, ax=ax, color=color, **kwargs)
)
def plot_plate_id(self, ax, plate_id, **kwargs):
"""Plot a plate polygon with an associated `plate_id` onto a standard map Projection.
Parameters
----------
ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot>
A subclass of `matplotlib.axes.Axes` which represents a map Projection.
The map should be set at a particular Cartopy projection.
plate_id : int
A plate ID that identifies the continental polygon to plot. See the
[Global EarthByte plate IDs list](https://www.earthbyte.org/webdav/ftp/earthbyte/GPlates/SampleData/FeatureCollections/Rotations/Global_EarthByte_PlateIDs_20071218.pdf)
for a full list of plate IDs to plot.
**kwargs :
Keyword arguments for map presentation parameters such as
`alpha`, etc. for plotting the grid.
See `Matplotlib`'s `imshow` keyword arguments
[here](https://matplotlib.org/3.5.1/api/_as_gen/matplotlib.axes.Axes.imshow.html).
"""
for feature in self.topologies:
if feature.get_reconstruction_plate_id() == plate_id:
ft_plate = shapelify_feature_polygons([feature])
return ax.add_geometries(ft_plate, crs=self.base_projection, **kwargs)
def plot_grid(self, ax, grid, extent=[-180,180,-90,90], **kwargs):
"""Plot a `MaskedArray` raster or grid onto a standard map Projection.
Notes
-----
Uses Matplotlib's `imshow`
[function](https://matplotlib.org/3.5.1/api/_as_gen/matplotlib.axes.Axes.imshow.html).
Parameters
----------
ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot>
A subclass of `matplotlib.axes.Axes` which represents a map Projection.
The map should be set at a particular Cartopy projection.
grid : MaskedArray or `gplately.grids.Raster`
A `MaskedArray` with elements that define a grid. The number of rows in the raster
corresponds to the number of latitudinal coordinates, while the number of raster
columns corresponds to the number of longitudinal coordinates.
extent : 1d array, default=[-180,180,-90,90]
A four-element array to specify the [min lon, max lon, min lat, max lat] with
which to constrain the grid image. If no extents are supplied, full global
extent is assumed.
**kwargs :
Keyword arguments for map presentation parameters such as
`alpha`, etc. for plotting the grid.
See `Matplotlib`'s `imshow` keyword arguments
[here](https://matplotlib.org/3.5.1/api/_as_gen/matplotlib.axes.Axes.imshow.html).
Returns
-------
ax : instance of <geopandas.GeoDataFrame.plot>
A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map
with the grid plotted onto the chosen map projection.
"""
# Override matplotlib default origin ('upper')
origin = kwargs.pop("origin", "lower")
from .grids import Raster
if isinstance(grid, Raster):
# extract extent and origin
extent = grid.extent
origin = grid.origin
data = grid.data
else:
data = grid
return ax.imshow(
data,
extent=extent,
transform=self.base_projection,
origin=origin,
**kwargs,
)
def plot_grid_from_netCDF(self, ax, filename, **kwargs):
"""Read a raster from a netCDF file, convert it to a `MaskedArray` and plot it
onto a standard map Projection.
Notes
-----
`plot_grid_from_netCDF` uses Matplotlib's `imshow`
[function](https://matplotlib.org/3.5.1/api/_as_gen/matplotlib.axes.Axes.imshow.html).
Parameters
----------
ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot>
A subclass of `matplotlib.axes.Axes` which represents a map Projection.
The map should be set at a particular Cartopy projection.
filename : str
Full path to a netCDF filename.
**kwargs :
Keyword arguments for map presentation parameters for
plotting the grid. See `Matplotlib`'s `imshow` keyword arguments
[here](https://matplotlib.org/3.5.1/api/_as_gen/matplotlib.axes.Axes.imshow.html).
Returns
-------
ax : instance of <geopandas.GeoDataFrame.plot>
A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map
with the netCDF grid plotted onto the chosen map projection.
"""
# Override matplotlib default origin ('upper')
origin = kwargs.pop("origin", "lower")
from .grids import read_netcdf_grid
raster, lon_coords, lat_coords = read_netcdf_grid(filename, return_grids=True)
extent = [lon_coords[0], lon_coords[-1], lat_coords[0], lat_coords[-1]]
if lon_coords[0] < lat_coords[-1]:
origin = "lower"
else:
origin = "upper"
return self.plot_grid(ax, raster, extent=extent, origin=origin, **kwargs)
def plot_plate_motion_vectors(self, ax, spacingX=10, spacingY=10, normalise=False, **kwargs):
"""Calculate plate motion velocity vector fields at a particular geological time
and plot them onto a standard map Projection.
Notes
-----
`plot_plate_motion_vectors` generates a MeshNode domain of point features using
given spacings in the X and Y directions (`spacingX` and `spacingY`). Each point in
the domain is assigned a plate ID, and these IDs are used to obtain equivalent stage
rotations of identified tectonic plates over a 5 Ma time interval. Each point and
its stage rotation are used to calculate plate velocities at a particular geological
time. Velocities for each domain point are represented in the north-east-down
coordinate system and plotted on a GeoAxes.
Vector fields can be optionally normalised by setting `normalise` to `True`. This
makes vector arrow lengths uniform.
Parameters
----------
ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot>
A subclass of `matplotlib.axes.Axes` which represents a map Projection.
The map should be set at a particular Cartopy projection.
spacingX : int, default=10
The spacing in the X direction used to make the velocity domain point feature mesh.
spacingY : int, default=10
The spacing in the Y direction used to make the velocity domain point feature mesh.
normalise : bool, default=False
Choose whether to normalise the velocity magnitudes so that vector lengths are
all equal.
**kwargs :
Keyword arguments for quiver presentation parameters for plotting
the velocity vector field. See `Matplotlib` quiver keyword arguments
[here](https://matplotlib.org/3.5.1/api/_as_gen/matplotlib.axes.Axes.quiver.html).
Returns
-------
ax : instance of <geopandas.GeoDataFrame.plot>
A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map
with the velocity vector field plotted onto the chosen map projection.
"""
lons = np.arange(-180, 180+spacingX, spacingX)
lats = np.arange(-90, 90+spacingY, spacingY)
lonq, latq = np.meshgrid(lons, lats)
# create a feature from all the points
velocity_domain_features = ptt.velocity_tools.make_GPML_velocity_feature(lonq.ravel(), latq.ravel())
rotation_model = self.plate_reconstruction.rotation_model
topology_features = self.plate_reconstruction.topology_features
delta_time = 5.0
all_velocities = ptt.velocity_tools.get_plate_velocities(
velocity_domain_features,
topology_features,
rotation_model,
self.time,
delta_time,
'vector_comp')
X, Y, U, V = ptt.velocity_tools.get_x_y_u_v(lons, lats, all_velocities)
if normalise:
mag = np.hypot(U, V)
mag[mag == 0] = 1
U /= mag
V /= mag
with warnings.catch_warnings():
warnings.simplefilter("ignore", UserWarning)
quiver = ax.quiver(
X, Y,
U, V,
transform=self.base_projection,
**kwargs
)
return quiver
def get_continental_rifts(self):
"""Create a geopandas.GeoDataFrame object containing geometries of reconstructed contiental rift lines.
Notes
-----
The `continental_rifts` needed to produce the GeoDataFrame are automatically constructed if the optional `time`
parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed
either when `PlotTopologies` is first called...
gplot = gplately.PlotTopologies(..., time=100,...)
or anytime afterwards, by setting:
time = 100 #Ma
gplot.time = time
...after which this function can be re-run. Once the `continental_rifts` are reconstructed, they are
converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame.
Returns
-------
gdf : instance of <geopandas.GeoDataFrame>
A pandas.DataFrame that has a column with `continental_rifts` geometry.
Raises
------
ValueError
If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct
`continental_rifts` to the requested `time` and thus populate the GeoDataFrame.
"""
if self._time is None:
raise ValueError("No continental rifts have been resolved. Set `PlotTopologies.time` to construct them.")
if self.continental_rifts is None:
raise ValueError("No continental rifts passed to PlotTopologies.")
continental_rift_lines = shapelify_feature_lines(self.continental_rifts)
gdf = gpd.GeoDataFrame({"geometry": continental_rift_lines}, geometry="geometry")
return gdf
def plot_continental_rifts(self, ax, color='black', **kwargs):
"""Plot continental rifts on a standard map projection.
Parameters
----------
ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot>
A subclass of `matplotlib.axes.Axes` which represents a map Projection.
The map should be set at a particular Cartopy projection.
color : str, default=’black’
The colour of the trench lines. By default, it is set to black.
**kwargs :
Keyword arguments for parameters such as `alpha`, etc.
for plotting trench geometries.
See `Matplotlib` keyword arguments
[here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html).
Returns
-------
ax : instance of <geopandas.GeoDataFrame.plot>
A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map
with continental rifts plotted onto the chosen map projection.
"""
gdf = self.get_continental_rifts()
return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs)
def get_faults(self):
"""Create a geopandas.GeoDataFrame object containing geometries of reconstructed fault lines.
Notes
-----
The `faults` needed to produce the GeoDataFrame are automatically constructed if the optional `time`
parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed
either when `PlotTopologies` is first called...
gplot = gplately.PlotTopologies(..., time=100,...)
or anytime afterwards, by setting:
time = 100 #Ma
gplot.time = time
...after which this function can be re-run. Once the `faults` are reconstructed, they are
converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame.
Returns
-------
gdf : instance of <geopandas.GeoDataFrame>
A pandas.DataFrame that has a column with `faults` geometry.
Raises
------
ValueError
If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct
`faults` to the requested `time` and thus populate the GeoDataFrame.
"""
if self._time is None:
raise ValueError("No faults have been resolved. Set `PlotTopologies.time` to construct them.")
if self.faults is None:
raise ValueError("No faults passed to PlotTopologies.")
fault_lines = shapelify_feature_lines(self.faults)
gdf = gpd.GeoDataFrame({"geometry": fault_lines}, geometry="geometry")
return gdf
def plot_faults(self, ax, color='black', **kwargs):
"""Plot faults on a standard map projection.
Parameters
----------
ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot>
A subclass of `matplotlib.axes.Axes` which represents a map Projection.
The map should be set at a particular Cartopy projection.
color : str, default=’black’
The colour of the trench lines. By default, it is set to black.
**kwargs :
Keyword arguments for parameters such as `alpha`, etc.
for plotting trench geometries.
See `Matplotlib` keyword arguments
[here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html).
Returns
-------
ax : instance of <geopandas.GeoDataFrame.plot>
A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map
with faults plotted onto the chosen map projection.
"""
gdf = self.get_faults()
return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs)
def get_fracture_zones(self):
"""Create a geopandas.GeoDataFrame object containing geometries of reconstructed fracture zone lines.
Notes
-----
The `fracture_zones` needed to produce the GeoDataFrame are automatically constructed if the optional `time`
parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed
either when `PlotTopologies` is first called...
gplot = gplately.PlotTopologies(..., time=100,...)
or anytime afterwards, by setting:
time = 100 #Ma
gplot.time = time
...after which this function can be re-run. Once the `fracture_zones` are reconstructed, they are
converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame.
Returns
-------
gdf : instance of <geopandas.GeoDataFrame>
A pandas.DataFrame that has a column with `fracture_zones` geometry.
Raises
------
ValueError
If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct
`fracture_zones` to the requested `time` and thus populate the GeoDataFrame.
"""
if self._time is None:
raise ValueError("No fracture zones have been resolved. Set `PlotTopologies.time` to construct them.")
if self.fracture_zones is None:
raise ValueError("No fracture zones passed to PlotTopologies.")
fracture_zone_lines = shapelify_feature_lines(self.fracture_zones)
gdf = gpd.GeoDataFrame({"geometry": fracture_zone_lines}, geometry="geometry")
return gdf
def plot_fracture_zones(self, ax, color='black', **kwargs):
"""Plot fracture zones on a standard map projection.
Parameters
----------
ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot>
A subclass of `matplotlib.axes.Axes` which represents a map Projection.
The map should be set at a particular Cartopy projection.
color : str, default=’black’
The colour of the trench lines. By default, it is set to black.
**kwargs :
Keyword arguments for parameters such as `alpha`, etc.
for plotting trench geometries.
See `Matplotlib` keyword arguments
[here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html).
Returns
-------
ax : instance of <geopandas.GeoDataFrame.plot>
A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map
with fracture zones plotted onto the chosen map projection.
"""
gdf = self.get_fracture_zones()
return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs)
def get_inferred_paleo_boundaries(self):
"""Create a geopandas.GeoDataFrame object containing geometries of reconstructed inferred paleo boundary lines.
Notes
-----
The `inferred_paleo_boundaries` needed to produce the GeoDataFrame are automatically constructed if the optional `time`
parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed
either when `PlotTopologies` is first called...
gplot = gplately.PlotTopologies(..., time=100,...)
or anytime afterwards, by setting:
time = 100 #Ma
gplot.time = time
...after which this function can be re-run. Once the `inferred_paleo_boundaries` are reconstructed, they are
converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame.
Returns
-------
gdf : instance of <geopandas.GeoDataFrame>
A pandas.DataFrame that has a column with `inferred_paleo_boundaries` geometry.
Raises
------
ValueError
If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct
`inferred_paleo_boundaries` to the requested `time` and thus populate the GeoDataFrame.
"""
if self._time is None:
raise ValueError("No inferred paleo boundaries have been resolved. Set `PlotTopologies.time` to construct them.")
if self.inferred_paleo_boundaries is None:
raise ValueError("No inferred paleo boundaries passed to PlotTopologies.")
inferred_paleo_boundary_lines = shapelify_feature_lines(self.inferred_paleo_boundaries)
gdf = gpd.GeoDataFrame({"geometry": inferred_paleo_boundary_lines}, geometry="geometry")
return gdf
def plot_inferred_paleo_boundaries(self, ax, color='black', **kwargs):
"""Plot inferred paleo boundaries on a standard map projection.
Parameters
----------
ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot>
A subclass of `matplotlib.axes.Axes` which represents a map Projection.
The map should be set at a particular Cartopy projection.
color : str, default=’black’
The colour of the trench lines. By default, it is set to black.
**kwargs :
Keyword arguments for parameters such as `alpha`, etc.
for plotting trench geometries.
See `Matplotlib` keyword arguments
[here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html).
Returns
-------
ax : instance of <geopandas.GeoDataFrame.plot>
A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map
with inferred paleo boundaries plotted onto the chosen map projection.
"""
gdf = get_inferred_paleo_boundaries()
return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs)
def get_terrane_boundaries(self):
"""Create a geopandas.GeoDataFrame object containing geometries of reconstructed terrane boundary lines.
Notes
-----
The `terrane_boundaries` needed to produce the GeoDataFrame are automatically constructed if the optional `time`
parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed
either when `PlotTopologies` is first called...
gplot = gplately.PlotTopologies(..., time=100,...)
or anytime afterwards, by setting:
time = 100 #Ma
gplot.time = time
...after which this function can be re-run. Once the `terrane_boundaries` are reconstructed, they are
converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame.
Returns
-------
gdf : instance of <geopandas.GeoDataFrame>
A pandas.DataFrame that has a column with `terrane_boundaries` geometry.
Raises
------
ValueError
If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct
`terrane_boundaries` to the requested `time` and thus populate the GeoDataFrame.
"""
if self._time is None:
raise ValueError("No terrane boundaries have been resolved. Set `PlotTopologies.time` to construct them.")
if self.terrane_boundaries is None:
raise ValueError("No terrane boundaries passed to PlotTopologies.")
terrane_boundary_lines = shapelify_feature_lines(self.terrane_boundaries)
gdf = gpd.GeoDataFrame({"geometry": terrane_boundary_lines}, geometry="geometry")
return gdf
def plot_terrane_boundaries(self, ax, color='black', **kwargs):
"""Plot terrane boundaries on a standard map projection.
Parameters
----------
ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot>
A subclass of `matplotlib.axes.Axes` which represents a map Projection.
The map should be set at a particular Cartopy projection.
color : str, default=’black’
The colour of the trench lines. By default, it is set to black.
**kwargs :
Keyword arguments for parameters such as `alpha`, etc.
for plotting trench geometries.
See `Matplotlib` keyword arguments
[here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html).
Returns
-------
ax : instance of <geopandas.GeoDataFrame.plot>
A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map
with terrane boundaries plotted onto the chosen map projection.
"""
gdf = self.get_terrane_boundaries()
return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs)
def get_transitional_crusts(self):
"""Create a geopandas.GeoDataFrame object containing geometries of reconstructed transitional crust lines.
Notes
-----
The `transitional_crusts` needed to produce the GeoDataFrame are automatically constructed if the optional `time`
parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed
either when `PlotTopologies` is first called...
gplot = gplately.PlotTopologies(..., time=100,...)
or anytime afterwards, by setting:
time = 100 #Ma
gplot.time = time
...after which this function can be re-run. Once the `transitional_crusts` are reconstructed, they are
converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame.
Returns
-------
gdf : instance of <geopandas.GeoDataFrame>
A pandas.DataFrame that has a column with `transitional_crusts` geometry.
Raises
------
ValueError
If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct
`transitional_crusts` to the requested `time` and thus populate the GeoDataFrame.
"""
if self._time is None:
raise ValueError("No transitional crusts have been resolved. Set `PlotTopologies.time` to construct them.")
if self.transitional_crusts is None:
raise ValueError("No transitional crusts passed to PlotTopologies.")
transitional_crust_lines = shapelify_feature_lines(self.transitional_crusts)
gdf = gpd.GeoDataFrame({"geometry": transitional_crust_lines}, geometry="geometry")
return gdf
def plot_transitional_crusts(self, ax, color='black', **kwargs):
"""Plot transitional crust on a standard map projection.
Parameters
----------
ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot>
A subclass of `matplotlib.axes.Axes` which represents a map Projection.
The map should be set at a particular Cartopy projection.
color : str, default=’black’
The colour of the trench lines. By default, it is set to black.
**kwargs :
Keyword arguments for parameters such as `alpha`, etc.
for plotting trench geometries.
See `Matplotlib` keyword arguments
[here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html).
Returns
-------
ax : instance of <geopandas.GeoDataFrame.plot>
A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map
with transitional crust plotted onto the chosen map projection.
"""
gdf = self.get_transitional_crusts()
return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs)
def get_orogenic_belts(self):
"""Create a geopandas.GeoDataFrame object containing geometries of reconstructed orogenic belt lines.
Notes
-----
The `orogenic_belts` needed to produce the GeoDataFrame are automatically constructed if the optional `time`
parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed
either when `PlotTopologies` is first called...
gplot = gplately.PlotTopologies(..., time=100,...)
or anytime afterwards, by setting:
time = 100 #Ma
gplot.time = time
...after which this function can be re-run. Once the `orogenic_belts` are reconstructed, they are
converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame.
Returns
-------
gdf : instance of <geopandas.GeoDataFrame>
A pandas.DataFrame that has a column with `orogenic_belts` geometry.
Raises
------
ValueError
If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct
`orogenic_belts` to the requested `time` and thus populate the GeoDataFrame.
"""
if self._time is None:
raise ValueError("No orogenic belts have been resolved. Set `PlotTopologies.time` to construct them.")
if self.orogenic_belts is None:
raise ValueError("No orogenic belts passed to PlotTopologies.")
orogenic_belt_lines = shapelify_feature_lines(self.orogenic_belts)
gdf = gpd.GeoDataFrame({"geometry": orogenic_belt_lines}, geometry="geometry")
return gdf
def plot_orogenic_belts(self, ax, color='black', **kwargs):
"""Plot orogenic belts on a standard map projection.
Parameters
----------
ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot>
A subclass of `matplotlib.axes.Axes` which represents a map Projection.
The map should be set at a particular Cartopy projection.
color : str, default=’black’
The colour of the trench lines. By default, it is set to black.
**kwargs :
Keyword arguments for parameters such as `alpha`, etc.
for plotting trench geometries.
See `Matplotlib` keyword arguments
[here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html).
Returns
-------
ax : instance of <geopandas.GeoDataFrame.plot>
A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map
with orogenic belts plotted onto the chosen map projection.
"""
gdf = self.get_orogenic_belts()
return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs)
def get_sutures(self):
"""Create a geopandas.GeoDataFrame object containing geometries of reconstructed suture lines.
Notes
-----
The `sutures` needed to produce the GeoDataFrame are automatically constructed if the optional `time`
parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed
either when `PlotTopologies` is first called...
gplot = gplately.PlotTopologies(..., time=100,...)
or anytime afterwards, by setting:
time = 100 #Ma
gplot.time = time
...after which this function can be re-run. Once the `sutures` are reconstructed, they are
converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame.
Returns
-------
gdf : instance of <geopandas.GeoDataFrame>
A pandas.DataFrame that has a column with `sutures` geometry.
Raises
------
ValueError
If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct
`sutures` to the requested `time` and thus populate the GeoDataFrame.
"""
if self._time is None:
raise ValueError("No sutures have been resolved. Set `PlotTopologies.time` to construct them.")
if self.sutures is None:
raise ValueError("No sutures passed to PlotTopologies.")
suture_lines = shapelify_feature_lines(self.sutures)
gdf = gpd.GeoDataFrame({"geometry": suture_lines}, geometry="geometry")
return gdf
def plot_sutures(self, ax, color='black', **kwargs):
"""Plot sutures on a standard map projection.
Parameters
----------
ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot>
A subclass of `matplotlib.axes.Axes` which represents a map Projection.
The map should be set at a particular Cartopy projection.
color : str, default=’black’
The colour of the trench lines. By default, it is set to black.
**kwargs :
Keyword arguments for parameters such as `alpha`, etc.
for plotting trench geometries.
See `Matplotlib` keyword arguments
[here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html).
Returns
-------
ax : instance of <geopandas.GeoDataFrame.plot>
A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map
with sutures plotted onto the chosen map projection.
"""
gdf = self.get_sutures()
return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs)
def get_continental_crusts(self):
"""Create a geopandas.GeoDataFrame object containing geometries of reconstructed continental crust lines.
Notes
-----
The `continental_crusts` needed to produce the GeoDataFrame are automatically constructed if the optional `time`
parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed
either when `PlotTopologies` is first called...
gplot = gplately.PlotTopologies(..., time=100,...)
or anytime afterwards, by setting:
time = 100 #Ma
gplot.time = time
...after which this function can be re-run. Once the `continental_crusts` are reconstructed, they are
converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame.
Returns
-------
gdf : instance of <geopandas.GeoDataFrame>
A pandas.DataFrame that has a column with `continental_crusts` geometry.
Raises
------
ValueError
If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct
`continental_crusts` to the requested `time` and thus populate the GeoDataFrame.
"""
if self._time is None:
raise ValueError("No continental crust topologies have been resolved. Set `PlotTopologies.time` to construct them.")
if self.continental_crusts is None:
raise ValueError("No continental crust topologies passed to PlotTopologies.")
continental_crust_lines = shapelify_feature_lines(self.continental_crusts)
gdf = gpd.GeoDataFrame({"geometry": continental_crust_lines}, geometry="geometry")
return gdf
def plot_continental_crusts(self, ax, color='black', **kwargs):
"""Plot continental crust lines on a standard map projection.
Parameters
----------
ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot>
A subclass of `matplotlib.axes.Axes` which represents a map Projection.
The map should be set at a particular Cartopy projection.
color : str, default=’black’
The colour of the trench lines. By default, it is set to black.
**kwargs :
Keyword arguments for parameters such as `alpha`, etc.
for plotting trench geometries.
See `Matplotlib` keyword arguments
[here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html).
Returns
-------
ax : instance of <geopandas.GeoDataFrame.plot>
A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map
with continental crust lines plotted onto the chosen map projection.
"""
gdf = self.get_continental_crusts()
return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs)
def get_extended_continental_crusts(self):
"""Create a geopandas.GeoDataFrame object containing geometries of reconstructed extended continental crust lines.
Notes
-----
The `extended_continental_crusts` needed to produce the GeoDataFrame are automatically constructed if the optional `time`
parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed
either when `PlotTopologies` is first called...
gplot = gplately.PlotTopologies(..., time=100,...)
or anytime afterwards, by setting:
time = 100 #Ma
gplot.time = time
...after which this function can be re-run. Once the `extended_continental_crusts` are reconstructed, they are
converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame.
Returns
-------
gdf : instance of <geopandas.GeoDataFrame>
A pandas.DataFrame that has a column with `extended_continental_crusts` geometry.
Raises
------
ValueError
If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct
`extended_continental_crusts` to the requested `time` and thus populate the GeoDataFrame.
"""
if self._time is None:
raise ValueError("No extended continental crust topologies have been resolved. Set `PlotTopologies.time` to construct them.")
if self.extended_continental_crusts is None:
raise ValueError("No extended continental crust topologies passed to PlotTopologies.")
extended_continental_crust_lines = shapelify_feature_lines(self.extended_continental_crusts)
gdf = gpd.GeoDataFrame({"geometry": extended_continental_crust_lines}, geometry="geometry")
return gdf
def plot_extended_continental_crusts(self, ax, color='black', **kwargs):
"""Plot extended continental crust lines on a standard map projection.
Parameters
----------
ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot>
A subclass of `matplotlib.axes.Axes` which represents a map Projection.
The map should be set at a particular Cartopy projection.
color : str, default=’black’
The colour of the trench lines. By default, it is set to black.
**kwargs :
Keyword arguments for parameters such as `alpha`, etc.
for plotting trench geometries.
See `Matplotlib` keyword arguments
[here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html).
Returns
-------
ax : instance of <geopandas.GeoDataFrame.plot>
A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map
with extended continental crust lines plotted onto the chosen map projection.
"""
gdf = self.get_extended_continental_crusts()
return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs)
def get_passive_continental_boundaries(self):
"""Create a geopandas.GeoDataFrame object containing geometries of reconstructed passive continental boundary lines.
Notes
-----
The `passive_continental_boundaries` needed to produce the GeoDataFrame are automatically constructed if the optional `time`
parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed
either when `PlotTopologies` is first called...
gplot = gplately.PlotTopologies(..., time=100,...)
or anytime afterwards, by setting:
time = 100 #Ma
gplot.time = time
...after which this function can be re-run. Once the `passive_continental_boundaries` are reconstructed, they are
converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame.
Returns
-------
gdf : instance of <geopandas.GeoDataFrame>
A pandas.DataFrame that has a column with `passive_continental_boundaries` geometry.
Raises
------
ValueError
If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct
`passive_continental_boundaries` to the requested `time` and thus populate the GeoDataFrame.
"""
if self._time is None:
raise ValueError("No passive continental boundaries have been resolved. Set `PlotTopologies.time` to construct them.")
if self.passive_continental_boundaries is None:
raise ValueError("No passive continental boundaries passed to PlotTopologies.")
passive_continental_boundary_lines = shapelify_feature_lines(self.passive_continental_boundaries)
gdf = gpd.GeoDataFrame({"geometry": passive_continental_boundary_lines}, geometry="geometry")
return gdf
def plot_passive_continental_boundaries(self, ax, color='black', **kwargs):
"""Plot passive continental boundaries on a standard map projection.
Parameters
----------
ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot>
A subclass of `matplotlib.axes.Axes` which represents a map Projection.
The map should be set at a particular Cartopy projection.
color : str, default=’black’
The colour of the trench lines. By default, it is set to black.
**kwargs :
Keyword arguments for parameters such as `alpha`, etc.
for plotting trench geometries.
See `Matplotlib` keyword arguments
[here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html).
Returns
-------
ax : instance of <geopandas.GeoDataFrame.plot>
A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map
with passive continental boundaries plotted onto the chosen map projection.
"""
gdf = self.get_passive_continental_boundaries()
return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs)
def get_slab_edges(self):
"""Create a geopandas.GeoDataFrame object containing geometries of reconstructed slab edge lines.
Notes
-----
The `slab_edges` needed to produce the GeoDataFrame are automatically constructed if the optional `time`
parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed
either when `PlotTopologies` is first called...
gplot = gplately.PlotTopologies(..., time=100,...)
or anytime afterwards, by setting:
time = 100 #Ma
gplot.time = time
...after which this function can be re-run. Once the `slab_edges` are reconstructed, they are
converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame.
Returns
-------
gdf : instance of <geopandas.GeoDataFrame>
A pandas.DataFrame that has a column with `slab_edges` geometry.
Raises
------
ValueError
If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct
`slab_edges` to the requested `time` and thus populate the GeoDataFrame.
"""
if self._time is None:
raise ValueError("No slab edges have been resolved. Set `PlotTopologies.time` to construct them.")
if self.slab_edges is None:
raise ValueError("No slab edges passed to PlotTopologies.")
slab_edge_lines = shapelify_feature_lines(self.slab_edges)
gdf = gpd.GeoDataFrame({"geometry": slab_edge_lines}, geometry="geometry")
return gdf
def plot_slab_edges(self, ax, color='black', **kwargs):
"""Plot slab edges on a standard map projection.
Parameters
----------
ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot>
A subclass of `matplotlib.axes.Axes` which represents a map Projection.
The map should be set at a particular Cartopy projection.
color : str, default=’black’
The colour of the trench lines. By default, it is set to black.
**kwargs :
Keyword arguments for parameters such as `alpha`, etc.
for plotting trench geometries.
See `Matplotlib` keyword arguments
[here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html).
Returns
-------
ax : instance of <geopandas.GeoDataFrame.plot>
A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map
with slab edges plotted onto the chosen map projection.
"""
gdf = self.get_slab_edges()
return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs)
def get_misc_transforms(self):
"""Create a geopandas.GeoDataFrame object containing geometries of reconstructed misc transform lines.
Notes
-----
The `misc_transforms` needed to produce the GeoDataFrame are automatically constructed if the optional `time`
parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed
either when `PlotTopologies` is first called...
gplot = gplately.PlotTopologies(..., time=100,...)
or anytime afterwards, by setting:
time = 100 #Ma
gplot.time = time
...after which this function can be re-run. Once the `misc_transforms` are reconstructed, they are
converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame.
Returns
-------
gdf : instance of <geopandas.GeoDataFrame>
A pandas.DataFrame that has a column with `misc_transforms` geometry.
Raises
------
ValueError
If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct
`misc_transforms` to the requested `time` and thus populate the GeoDataFrame.
"""
if self._time is None:
raise ValueError("No miscellaneous transforms have been resolved. Set `PlotTopologies.time` to construct them.")
if self.misc_transforms is None:
raise ValueError("No miscellaneous transforms passed to PlotTopologies.")
misc_transform_lines = shapelify_feature_lines(self.misc_transforms)
gdf = gpd.GeoDataFrame({"geometry": misc_transform_lines}, geometry="geometry")
return gdf
def plot_misc_transforms(self, ax, color='black', **kwargs):
"""Plot miscellaneous transform boundaries on a standard map projection.
Parameters
----------
ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot>
A subclass of `matplotlib.axes.Axes` which represents a map Projection.
The map should be set at a particular Cartopy projection.
color : str, default=’black’
The colour of the trench lines. By default, it is set to black.
**kwargs :
Keyword arguments for parameters such as `alpha`, etc.
for plotting trench geometries.
See `Matplotlib` keyword arguments
[here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html).
Returns
-------
ax : instance of <geopandas.GeoDataFrame.plot>
A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map
with miscellaneous transform boundaries plotted onto the chosen map projection.
"""
gdf = self.get_misc_transforms()
return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs)
def get_unclassified_features(self):
"""Create a geopandas.GeoDataFrame object containing geometries of reconstructed unclassified feature lines.
Notes
-----
The `unclassified_features` needed to produce the GeoDataFrame are automatically constructed if the optional `time`
parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed
either when `PlotTopologies` is first called...
gplot = gplately.PlotTopologies(..., time=100,...)
or anytime afterwards, by setting:
time = 100 #Ma
gplot.time = time
...after which this function can be re-run. Once the `unclassified_features` are reconstructed, they are
converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame.
Returns
-------
gdf : instance of <geopandas.GeoDataFrame>
A pandas.DataFrame that has a column with `unclassified_features` geometry.
Raises
------
ValueError
If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct
`unclassified_features` to the requested `time` and thus populate the GeoDataFrame.
"""
if self._time is None:
raise ValueError("No unclassified features have been resolved. Set `PlotTopologies.time` to construct them.")
if self.unclassified_features is None:
raise ValueError("No unclassified features passed to PlotTopologies.")
unclassified_feature_lines = shapelify_feature_lines(self.unclassified_features)
gdf = gpd.GeoDataFrame({"geometry": unclassified_feature_lines}, geometry="geometry")
return gdf
def plot_unclassified_features(self, ax, color='black', **kwargs):
"""Plot GPML unclassified features on a standard map projection.
Parameters
----------
ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot>
A subclass of `matplotlib.axes.Axes` which represents a map Projection.
The map should be set at a particular Cartopy projection.
color : str, default=’black’
The colour of the trench lines. By default, it is set to black.
**kwargs :
Keyword arguments for parameters such as `alpha`, etc.
for plotting trench geometries.
See `Matplotlib` keyword arguments
[here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html).
Returns
-------
ax : instance of <geopandas.GeoDataFrame.plot>
A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map
with unclassified features plotted onto the chosen map projection.
"""
gdf = self.get_unclassified_features()
return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs)
def get_all_topologies(self):
"""Create a geopandas.GeoDataFrame object containing geometries of reconstructed unclassified feature lines.
Notes
-----
The `topologies` needed to produce the GeoDataFrame are automatically constructed if the optional `time`
parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed
either when `PlotTopologies` is first called...
gplot = gplately.PlotTopologies(..., time=100,...)
or anytime afterwards, by setting:
time = 100 #Ma
gplot.time = time
...after which this function can be re-run. Once the `topologies` are reconstructed, they are
converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame.
Returns
-------
gdf : instance of <geopandas.GeoDataFrame>
A pandas.DataFrame that has a column with `topologies` geometry.
Raises
------
ValueError
If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct
`topologies` to the requested `time` and thus populate the GeoDataFrame.
"""
if self._time is None:
raise ValueError("No topologies have been resolved. Set `PlotTopologies.time` to construct them.")
if self.topologies is None:
raise ValueError("No topologies passed to PlotTopologies.")
all_topologies = shapelify_features(self.topologies)
# get plate IDs and feature types to add to geodataframe
plate_IDs = []
feature_types = []
feature_names = []
for topo in self.topologies:
ft_type = topo.get_feature_type()
plate_IDs.append(topo.get_reconstruction_plate_id())
feature_types.append(ft_type)
feature_names.append(ft_type.get_name())
gdf = gpd.GeoDataFrame({"geometry": all_topologies,
"reconstruction_plate_ID": plate_IDs,
"feature_type": feature_types,
"feature_name": feature_names},
geometry="geometry")
return gdf
def plot_all_topologies(self, ax, color='black', **kwargs):
"""Plot all topologies on a standard map projection.
Parameters
----------
ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot>
A subclass of `matplotlib.axes.Axes` which represents a map Projection.
The map should be set at a particular Cartopy projection.
color : str, default=’black’
The colour of the trench lines. By default, it is set to black.
**kwargs :
Keyword arguments for parameters such as `alpha`, etc.
for plotting trench geometries.
See `Matplotlib` keyword arguments
[here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html).
Returns
-------
ax : instance of <geopandas.GeoDataFrame.plot>
A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map
with unclassified features plotted onto the chosen map projection.
"""
gdf = self.get_all_topologies()
return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs)Functions
def plot_subduction_teeth(geometries, width, polarity=None, height=None, spacing=None, projection='auto', transform=None, ax=None, **kwargs)-
Add subduction teeth to a plot.
The subduction polarity used for subduction teeth can be specified manually or detected automatically if
geometriesis ageopandas.GeoDataFrameobject with apolaritycolumn.Parameters
geometries:geopandas.GeoDataFrame, sequenceofshapely geometries,orstr- If a
geopandas.GeoDataFrameis given, its geometry attribute will be used. Ifgeometriesis a string, it must be the path to a file, which will be loaded withgeopandas.read_file. Otherwise,geometriesmust be a sequence of shapely geometry objects (instances of theshapely.geometry.base.BaseGeometryclass). width:float- The (approximate) width of the subduction teeth. If a projection is used, this value will be in projected units.
polarity:{"left", "l", "right", "r", None}, defaultNone- The subduction polarity of the geometries. If no polarity is provided,
and
geometriesis ageopandas.GeoDataFrame, this function will attempt to find apolaritycolumn in the data frame and use the values given there. Ifpolarityis not manually specified and no appropriate column can be found, an error will be raised. height:float, defaultNone- If provided, the height of the subduction teeth. As with
width, this value should be given in projected units. If no value is given, the height of the teeth will be equal to 0.6 *width. spacing:float, defaultNone- If provided, the spacing between the subduction teeth. As with
widthandheight, this value should be given in projected units. If no value is given,spacingwill default towidth, producing tightly packed subduction teeth. projection:cartopy.crs.Transform, "auto",orNone, default"auto"- The projection of the plot. If the plot has no projection, this value
can be explicitly given as
None. The default value is "auto", which will acquire the projection automatically from the plot axes. transform:cartopy.crs.Transform,orNone, defaultNone- If the plot is projected, a
transformvalue is usually needed. Frequently, the appropriate value is an instance ofcartopy.crs.PlateCarree. ax:matplotlib.axes.Axes,orNone, defaultNone- The axes on which the subduction teeth will be drawn. By default,
the current axes will be acquired using
matplotlib.pyplot.gca. **kwargs- Any further keyword arguments will be passed to
matplotlib.patches.Polygon.
Raises
ValueError- If
width<= 0, or ifpolarityis an invalid value or could not be determined.
Expand source code
def plot_subduction_teeth( geometries, width, polarity=None, height=None, spacing=None, projection="auto", transform=None, ax=None, **kwargs ): """Add subduction teeth to a plot. The subduction polarity used for subduction teeth can be specified manually or detected automatically if `geometries` is a `geopandas.GeoDataFrame` object with a `polarity` column. Parameters ---------- geometries : geopandas.GeoDataFrame, sequence of shapely geometries, or str If a `geopandas.GeoDataFrame` is given, its geometry attribute will be used. If `geometries` is a string, it must be the path to a file, which will be loaded with `geopandas.read_file`. Otherwise, `geometries` must be a sequence of shapely geometry objects (instances of the `shapely.geometry.base.BaseGeometry` class). width : float The (approximate) width of the subduction teeth. If a projection is used, this value will be in projected units. polarity : {"left", "l", "right", "r", None}, default None The subduction polarity of the geometries. If no polarity is provided, and `geometries` is a `geopandas.GeoDataFrame`, this function will attempt to find a `polarity` column in the data frame and use the values given there. If `polarity` is not manually specified and no appropriate column can be found, an error will be raised. height : float, default None If provided, the height of the subduction teeth. As with `width`, this value should be given in projected units. If no value is given, the height of the teeth will be equal to 0.6 * `width`. spacing : float, default None If provided, the spacing between the subduction teeth. As with `width` and `height`, this value should be given in projected units. If no value is given, `spacing` will default to `width`, producing tightly packed subduction teeth. projection : cartopy.crs.Transform, "auto", or None, default "auto" The projection of the plot. If the plot has no projection, this value can be explicitly given as `None`. The default value is "auto", which will acquire the projection automatically from the plot axes. transform : cartopy.crs.Transform, or None, default None If the plot is projected, a `transform` value is usually needed. Frequently, the appropriate value is an instance of `cartopy.crs.PlateCarree`. ax : matplotlib.axes.Axes, or None, default None The axes on which the subduction teeth will be drawn. By default, the current axes will be acquired using `matplotlib.pyplot.gca`. **kwargs Any further keyword arguments will be passed to `matplotlib.patches.Polygon`. Raises ------ ValueError If `width` <= 0, or if `polarity` is an invalid value or could not be determined. """ if ax is None: ax = plt.gca() if projection == "auto": try: projection = ax.projection except AttributeError: projection = None elif isinstance(projection, str): raise ValueError("Invalid projection: {}".format(projection)) if polarity is None: polarity_column = _find_polarity_column(geometries.columns.values) if polarity_column is None: raise ValueError( "Could not automatically determine polarity; " + "it must be defined manually instead." ) triangles = [] for p in geometries[polarity_column].unique(): if p.lower() not in {"left", "l", "right", "r"}: continue gdf_polarity = geometries[geometries[polarity_column] == p] triangles.extend( _tessellate_triangles( gdf_polarity, width, p, height, spacing, projection, transform, ) ) else: triangles = _tessellate_triangles( geometries, width, polarity, height, spacing, projection, transform, ) if projection is not None: domain = projection.domain triangles = [domain.intersection(i) for i in triangles] if hasattr(ax, "add_geometries") and projection is not None: ax.add_geometries(triangles, crs=projection, **kwargs) else: for triangle in triangles: ax.fill(*triangle.exterior.xy, **kwargs) def shapelify_feature_lines(features, central_meridian=0.0, tessellate_degrees=None)-
Generate Shapely
MultiPolygonorMultiLineStringgeometries from reconstructed feature polygons.Notes
Some Shapely polygons generated by
shapelify_features()cut longitudes of 180 or -180 degrees. These features may appear unclosed at the dateline, so Shapely "closes" these polygons by connecting any of their open ends with lines. These lines may manifest on GeoAxes plots as horizontal lines that span the entire global extent. To prevent this,shapelify_features()uses pyGPlates' DateLineWrapper to split a feature polygon into multiple closed polygons if it happens to cut the antimeridian. Another measure taken to ensure features are valid is to order exterior coordinates of Shapely polygons anti-clockwise.Parameters
features:iterableof<pygplates.Feature>, <ReconstructedFeatureGeometry>or<GeometryOnSphere>- Iterable containing reconstructed polygon features.
central_meridian:float- Central meridian around which to perform wrapping; default: 0.0.
tessellate_degrees:floatorNone- If provided, geometries will be tessellated to this resolution prior to wrapping.
Returns
all_geometries:listofshapely.geometry.BaseGeometry- Shapely geometries converted from the given reconstructed features. Any geometries at the dateline are split.
See Also
geometry.pygplates_to_shapely- convert PyGPlates geometry objects to
Shapely geometries.
Expand source code
def shapelify_features(features, central_meridian=0.0, tessellate_degrees=None): """Generate Shapely `MultiPolygon` or `MultiLineString` geometries from reconstructed feature polygons. Notes ----- Some Shapely polygons generated by `shapelify_features` cut longitudes of 180 or -180 degrees. These features may appear unclosed at the dateline, so Shapely "closes" these polygons by connecting any of their open ends with lines. These lines may manifest on GeoAxes plots as horizontal lines that span the entire global extent. To prevent this, `shapelify_features` uses pyGPlates' [DateLineWrapper](https://www.gplates.org/docs/pygplates/generated/pygplates.datelinewrapper) to split a feature polygon into multiple closed polygons if it happens to cut the antimeridian. Another measure taken to ensure features are valid is to order exterior coordinates of Shapely polygons anti-clockwise. Parameters ---------- features : iterable of <pygplates.Feature>, <ReconstructedFeatureGeometry> or <GeometryOnSphere> Iterable containing reconstructed polygon features. central_meridian : float Central meridian around which to perform wrapping; default: 0.0. tessellate_degrees : float or None If provided, geometries will be tessellated to this resolution prior to wrapping. Returns ------- all_geometries : list of `shapely.geometry.BaseGeometry` Shapely geometries converted from the given reconstructed features. Any geometries at the dateline are split. See Also -------- geometry.pygplates_to_shapely : convert PyGPlates geometry objects to Shapely geometries. """ if isinstance( features, ( pygplates.Feature, pygplates.ReconstructedFeatureGeometry, pygplates.GeometryOnSphere, ), ): features = [features] geometries = [] for feature in features: if isinstance(feature, pygplates.Feature): geometries.extend(feature.get_all_geometries()) elif isinstance(feature, pygplates.ReconstructedFeatureGeometry): geometries.append(feature.get_reconstructed_geometry()) elif isinstance(feature, (pygplates.GeometryOnSphere, pygplates.LatLonPoint)): geometries.append(feature) elif isinstance(feature, pygplates.DateLineWrapper.LatLonMultiPoint): geometries.append( pygplates.MultiPointOnSphere( [i.to_lat_lon() for i in feature.get_points()] ) ) elif isinstance(feature, pygplates.DateLineWrapper.LatLonPolyline): geometries.append(pygplates.PolylineOnSphere(feature.get_points())) elif isinstance(feature, pygplates.DateLineWrapper.LatLonPolygon): geometries.append( pygplates.PolygonOnSphere( [i.to_lat_lon() for i in feature.get_exterior_points()] ) ) return [ pygplates_to_shapely( i, force_ccw=True, validate=True, central_meridian=central_meridian, tessellate_degrees=tessellate_degrees, explode=False, ) for i in geometries ] def shapelify_feature_polygons(features, central_meridian=0.0, tessellate_degrees=None)-
Generate Shapely
MultiPolygonorMultiLineStringgeometries from reconstructed feature polygons.Notes
Some Shapely polygons generated by
shapelify_features()cut longitudes of 180 or -180 degrees. These features may appear unclosed at the dateline, so Shapely "closes" these polygons by connecting any of their open ends with lines. These lines may manifest on GeoAxes plots as horizontal lines that span the entire global extent. To prevent this,shapelify_features()uses pyGPlates' DateLineWrapper to split a feature polygon into multiple closed polygons if it happens to cut the antimeridian. Another measure taken to ensure features are valid is to order exterior coordinates of Shapely polygons anti-clockwise.Parameters
features:iterableof<pygplates.Feature>, <ReconstructedFeatureGeometry>or<GeometryOnSphere>- Iterable containing reconstructed polygon features.
central_meridian:float- Central meridian around which to perform wrapping; default: 0.0.
tessellate_degrees:floatorNone- If provided, geometries will be tessellated to this resolution prior to wrapping.
Returns
all_geometries:listofshapely.geometry.BaseGeometry- Shapely geometries converted from the given reconstructed features. Any geometries at the dateline are split.
See Also
geometry.pygplates_to_shapely- convert PyGPlates geometry objects to
Shapely geometries.
Expand source code
def shapelify_features(features, central_meridian=0.0, tessellate_degrees=None): """Generate Shapely `MultiPolygon` or `MultiLineString` geometries from reconstructed feature polygons. Notes ----- Some Shapely polygons generated by `shapelify_features` cut longitudes of 180 or -180 degrees. These features may appear unclosed at the dateline, so Shapely "closes" these polygons by connecting any of their open ends with lines. These lines may manifest on GeoAxes plots as horizontal lines that span the entire global extent. To prevent this, `shapelify_features` uses pyGPlates' [DateLineWrapper](https://www.gplates.org/docs/pygplates/generated/pygplates.datelinewrapper) to split a feature polygon into multiple closed polygons if it happens to cut the antimeridian. Another measure taken to ensure features are valid is to order exterior coordinates of Shapely polygons anti-clockwise. Parameters ---------- features : iterable of <pygplates.Feature>, <ReconstructedFeatureGeometry> or <GeometryOnSphere> Iterable containing reconstructed polygon features. central_meridian : float Central meridian around which to perform wrapping; default: 0.0. tessellate_degrees : float or None If provided, geometries will be tessellated to this resolution prior to wrapping. Returns ------- all_geometries : list of `shapely.geometry.BaseGeometry` Shapely geometries converted from the given reconstructed features. Any geometries at the dateline are split. See Also -------- geometry.pygplates_to_shapely : convert PyGPlates geometry objects to Shapely geometries. """ if isinstance( features, ( pygplates.Feature, pygplates.ReconstructedFeatureGeometry, pygplates.GeometryOnSphere, ), ): features = [features] geometries = [] for feature in features: if isinstance(feature, pygplates.Feature): geometries.extend(feature.get_all_geometries()) elif isinstance(feature, pygplates.ReconstructedFeatureGeometry): geometries.append(feature.get_reconstructed_geometry()) elif isinstance(feature, (pygplates.GeometryOnSphere, pygplates.LatLonPoint)): geometries.append(feature) elif isinstance(feature, pygplates.DateLineWrapper.LatLonMultiPoint): geometries.append( pygplates.MultiPointOnSphere( [i.to_lat_lon() for i in feature.get_points()] ) ) elif isinstance(feature, pygplates.DateLineWrapper.LatLonPolyline): geometries.append(pygplates.PolylineOnSphere(feature.get_points())) elif isinstance(feature, pygplates.DateLineWrapper.LatLonPolygon): geometries.append( pygplates.PolygonOnSphere( [i.to_lat_lon() for i in feature.get_exterior_points()] ) ) return [ pygplates_to_shapely( i, force_ccw=True, validate=True, central_meridian=central_meridian, tessellate_degrees=tessellate_degrees, explode=False, ) for i in geometries ] def shapelify_features(features, central_meridian=0.0, tessellate_degrees=None)-
Generate Shapely
MultiPolygonorMultiLineStringgeometries from reconstructed feature polygons.Notes
Some Shapely polygons generated by
shapelify_features()cut longitudes of 180 or -180 degrees. These features may appear unclosed at the dateline, so Shapely "closes" these polygons by connecting any of their open ends with lines. These lines may manifest on GeoAxes plots as horizontal lines that span the entire global extent. To prevent this,shapelify_features()uses pyGPlates' DateLineWrapper to split a feature polygon into multiple closed polygons if it happens to cut the antimeridian. Another measure taken to ensure features are valid is to order exterior coordinates of Shapely polygons anti-clockwise.Parameters
features:iterableof<pygplates.Feature>, <ReconstructedFeatureGeometry>or<GeometryOnSphere>- Iterable containing reconstructed polygon features.
central_meridian:float- Central meridian around which to perform wrapping; default: 0.0.
tessellate_degrees:floatorNone- If provided, geometries will be tessellated to this resolution prior to wrapping.
Returns
all_geometries:listofshapely.geometry.BaseGeometry- Shapely geometries converted from the given reconstructed features. Any geometries at the dateline are split.
See Also
geometry.pygplates_to_shapely- convert PyGPlates geometry objects to
Shapely geometries.
Expand source code
def shapelify_features(features, central_meridian=0.0, tessellate_degrees=None): """Generate Shapely `MultiPolygon` or `MultiLineString` geometries from reconstructed feature polygons. Notes ----- Some Shapely polygons generated by `shapelify_features` cut longitudes of 180 or -180 degrees. These features may appear unclosed at the dateline, so Shapely "closes" these polygons by connecting any of their open ends with lines. These lines may manifest on GeoAxes plots as horizontal lines that span the entire global extent. To prevent this, `shapelify_features` uses pyGPlates' [DateLineWrapper](https://www.gplates.org/docs/pygplates/generated/pygplates.datelinewrapper) to split a feature polygon into multiple closed polygons if it happens to cut the antimeridian. Another measure taken to ensure features are valid is to order exterior coordinates of Shapely polygons anti-clockwise. Parameters ---------- features : iterable of <pygplates.Feature>, <ReconstructedFeatureGeometry> or <GeometryOnSphere> Iterable containing reconstructed polygon features. central_meridian : float Central meridian around which to perform wrapping; default: 0.0. tessellate_degrees : float or None If provided, geometries will be tessellated to this resolution prior to wrapping. Returns ------- all_geometries : list of `shapely.geometry.BaseGeometry` Shapely geometries converted from the given reconstructed features. Any geometries at the dateline are split. See Also -------- geometry.pygplates_to_shapely : convert PyGPlates geometry objects to Shapely geometries. """ if isinstance( features, ( pygplates.Feature, pygplates.ReconstructedFeatureGeometry, pygplates.GeometryOnSphere, ), ): features = [features] geometries = [] for feature in features: if isinstance(feature, pygplates.Feature): geometries.extend(feature.get_all_geometries()) elif isinstance(feature, pygplates.ReconstructedFeatureGeometry): geometries.append(feature.get_reconstructed_geometry()) elif isinstance(feature, (pygplates.GeometryOnSphere, pygplates.LatLonPoint)): geometries.append(feature) elif isinstance(feature, pygplates.DateLineWrapper.LatLonMultiPoint): geometries.append( pygplates.MultiPointOnSphere( [i.to_lat_lon() for i in feature.get_points()] ) ) elif isinstance(feature, pygplates.DateLineWrapper.LatLonPolyline): geometries.append(pygplates.PolylineOnSphere(feature.get_points())) elif isinstance(feature, pygplates.DateLineWrapper.LatLonPolygon): geometries.append( pygplates.PolygonOnSphere( [i.to_lat_lon() for i in feature.get_exterior_points()] ) ) return [ pygplates_to_shapely( i, force_ccw=True, validate=True, central_meridian=central_meridian, tessellate_degrees=tessellate_degrees, explode=False, ) for i in geometries ]
Classes
class PlotTopologies (plate_reconstruction, coastlines=None, continents=None, COBs=None, time=None, anchor_plate_id=0)-
A class with tools to read, reconstruct and plot topology features at specific reconstruction times.
PlotTopologiesis a shorthand for PyGPlates and Shapely functionalities that:- Read features held in GPlates GPML (GPlates Markup Language) files and ESRI shapefiles;
- Reconstruct the locations of these features as they migrate through geological time;
- Turn these reconstructed features into Shapely geometries for plotting
on
cartopy.mpl.geoaxes.GeoAxesorcartopy.mpl.geoaxes.GeoAxesSubplotmap Projections.
To call the
PlotTopologiesobject, supply:- an instance of the GPlately
plate_reconstructionobject
and optionally,
- a
coastline_filename - a
continent_filename - a
COB_filename - a reconstruction
time - an
anchor_plate_id
For example:
# Calling the PlotTopologies object gplot = gplately.plot.PlotTopologies(plate_reconstruction, coastline_filename=None, continent_filename=None, COB_filename=None, time=None, anchor_plate_id=0, ) # Setting a new reconstruction time gplot.time = 20 # MaThe
coastline_filename,continent_filenameandCOB_filenamecan be single strings to GPML and/or shapefiles, as well as instances ofpygplates.FeatureCollection. If using GPlately'sDataServerobject to source these files, they will be passed aspygplates.FeatureCollectionitems.Some features for plotting (like plate boundaries) are taken from the
PlateReconstructionobject'stopology_featuresattribute. They have already been reconstructed to the giventimeusing Plate Tectonic Tools. Simply provide a new reconstruction time by changing thetimeattribute, e.g.gplot.time = 20 # Mawhich will automatically reconstruct all topologies to the specified time. You MUST set
gplot.timebefore plotting anything.A variety of geological features can be plotted on GeoAxes/GeoAxesSubplot maps as Shapely
MultiLineStringorMultiPolygongeometries, including:- subduction boundaries & subduction polarity teeth
- mid-ocean ridge boundaries
- transform boundaries
- miscellaneous boundaries
- coastline polylines
- continental polygons and
- continent-ocean boundary polylines
- topological plate velocity vector fields
- netCDF4 MaskedArray or ndarray raster data:
- seafloor age grids
- paleo-age grids
- global relief (topography and bathymetry)
- assorted reconstructable feature data, for example:
- seafloor fabric
- large igneous provinces
- volcanic provinces
Attributes
plate_reconstruction:instanceof<gplately.reconstruction.PlateReconstruction>- The GPlately
PlateReconstructionobject will be used to access a platerotation_modeland a set oftopology_featureswhich contains plate boundary features like trenches, ridges and transforms. anchor_plate_id:int, default0- The anchor plate ID used for reconstruction.
base_projection:instanceof<cartopy.crs.{transform}>, default<cartopy.crs.PlateCarree> object- where {transform} is the map Projection to use on the Cartopy GeoAxes. By default, the base projection is set to cartopy.crs.PlateCarree. See the Cartopy projection list for all supported Projection types.
coastlines:str,orinstanceof<pygplates.FeatureCollection>- The full string path to a coastline feature file. Coastline features can also
be passed as instances of the
pygplates.FeatureCollectionobject (this is the case if these features are sourced from theDataServerobject). continents:str,orinstanceof<pygplates.FeatureCollection>- The full string path to a continent feature file. Continent features can also
be passed as instances of the
pygplates.FeatureCollectionobject (this is the case if these features are sourced from theDataServerobject). COBs:str,orinstanceof<pygplates.FeatureCollection>- The full string path to a COB feature file. COB features can also be passed
as instances of the
pygplates.FeatureCollectionobject (this is the case if these features are sourced from theDataServerobject). coastlines:iterable/listof<pygplates.ReconstructedFeatureGeometry>- A list containing coastline features reconstructed to the specified
timeattribute. continents:iterable/listof<pygplates.ReconstructedFeatureGeometry>- A list containing continent features reconstructed to the specified
timeattribute. COBs:iterable/listof<pygplates.ReconstructedFeatureGeometry>- A list containing COB features reconstructed to the specified
timeattribute. time:float- The time (Ma) to reconstruct and plot geological features to.
topologies:iterable/listof<pygplates.Feature>-
A list containing assorted topologies like:
- pygplates.FeatureType.gpml_topological_network
- pygplates.FeatureType.gpml_oceanic_crust
- pygplates.FeatureType.gpml_topological_slab_boundary
- pygplates.FeatureType.gpml_topological_closed_plate_boundary
ridge_transforms:iterable/listof<pygplates.Feature>- A list containing ridge and transform boundary sections of type pygplates.FeatureType.gpml_mid_ocean_ridge
ridges:iterable/listof<pygplates.Feature>- A list containing ridge boundary sections of type pygplates.FeatureType.gpml_mid_ocean_ridge
transforms:iterable/listof<pygplates.Feature>- A list containing transform boundary sections of type pygplates.FeatureType.gpml_mid_ocean_ridge
trenches:iterable/listof<pygplates.Feature>- A list containing trench boundary sections of type pygplates.FeatureType.gpml_subduction_zone
trench_left:iterable/listof<pygplates.Feature>- A list containing left subduction boundary sections of type pygplates.FeatureType.gpml_subduction_zone
trench_right:iterable/listof<pygplates.Feature>- A list containing right subduction boundary sections of type pygplates.FeatureType.gpml_subduction_zone
other:iterable/listof<pygplates.Feature>- A list containing other geological features like unclassified features, extended continental crusts, continental rifts, faults, orogenic belts, fracture zones, inferred paleo boundaries, terrane boundaries and passive continental boundaries.
Expand source code
class PlotTopologies(object): """A class with tools to read, reconstruct and plot topology features at specific reconstruction times. `PlotTopologies` is a shorthand for PyGPlates and Shapely functionalities that: * Read features held in GPlates GPML (GPlates Markup Language) files and ESRI shapefiles; * Reconstruct the locations of these features as they migrate through geological time; * Turn these reconstructed features into Shapely geometries for plotting on `cartopy.mpl.geoaxes.GeoAxes` or `cartopy.mpl.geoaxes.GeoAxesSubplot` map Projections. To call the `PlotTopologies` object, supply: * an instance of the GPlately `plate_reconstruction` object and optionally, * a `coastline_filename` * a `continent_filename` * a `COB_filename` * a reconstruction `time` * an `anchor_plate_id` For example: # Calling the PlotTopologies object gplot = gplately.plot.PlotTopologies(plate_reconstruction, coastline_filename=None, continent_filename=None, COB_filename=None, time=None, anchor_plate_id=0, ) # Setting a new reconstruction time gplot.time = 20 # Ma The `coastline_filename`, `continent_filename` and `COB_filename` can be single strings to GPML and/or shapefiles, as well as instances of `pygplates.FeatureCollection`. If using GPlately's `DataServer` object to source these files, they will be passed as `pygplates.FeatureCollection` items. Some features for plotting (like plate boundaries) are taken from the `PlateReconstruction` object's`topology_features` attribute. They have already been reconstructed to the given `time` using [Plate Tectonic Tools](https://github.com/EarthByte/PlateTectonicTools). Simply provide a new reconstruction time by changing the `time` attribute, e.g. gplot.time = 20 # Ma which will automatically reconstruct all topologies to the specified time. You __MUST__ set `gplot.time` before plotting anything. A variety of geological features can be plotted on GeoAxes/GeoAxesSubplot maps as Shapely `MultiLineString` or `MultiPolygon` geometries, including: * subduction boundaries & subduction polarity teeth * mid-ocean ridge boundaries * transform boundaries * miscellaneous boundaries * coastline polylines * continental polygons and * continent-ocean boundary polylines * topological plate velocity vector fields * netCDF4 MaskedArray or ndarray raster data: - seafloor age grids - paleo-age grids - global relief (topography and bathymetry) * assorted reconstructable feature data, for example: - seafloor fabric - large igneous provinces - volcanic provinces Attributes ---------- plate_reconstruction : instance of <gplately.reconstruction.PlateReconstruction> The GPlately `PlateReconstruction` object will be used to access a plate `rotation_model` and a set of `topology_features` which contains plate boundary features like trenches, ridges and transforms. anchor_plate_id : int, default 0 The anchor plate ID used for reconstruction. base_projection : instance of <cartopy.crs.{transform}>, default <cartopy.crs.PlateCarree> object where {transform} is the map Projection to use on the Cartopy GeoAxes. By default, the base projection is set to cartopy.crs.PlateCarree. See the [Cartopy projection list](https://scitools.org.uk/cartopy/docs/v0.15/crs/projections.html) for all supported Projection types. coastlines : str, or instance of <pygplates.FeatureCollection> The full string path to a coastline feature file. Coastline features can also be passed as instances of the `pygplates.FeatureCollection` object (this is the case if these features are sourced from the `DataServer` object). continents : str, or instance of <pygplates.FeatureCollection> The full string path to a continent feature file. Continent features can also be passed as instances of the `pygplates.FeatureCollection` object (this is the case if these features are sourced from the `DataServer` object). COBs : str, or instance of <pygplates.FeatureCollection> The full string path to a COB feature file. COB features can also be passed as instances of the `pygplates.FeatureCollection` object (this is the case if these features are sourced from the `DataServer` object). coastlines : iterable/list of <pygplates.ReconstructedFeatureGeometry> A list containing coastline features reconstructed to the specified `time` attribute. continents : iterable/list of <pygplates.ReconstructedFeatureGeometry> A list containing continent features reconstructed to the specified `time` attribute. COBs : iterable/list of <pygplates.ReconstructedFeatureGeometry> A list containing COB features reconstructed to the specified `time` attribute. time : float The time (Ma) to reconstruct and plot geological features to. topologies : iterable/list of <pygplates.Feature> A list containing assorted topologies like: - pygplates.FeatureType.gpml_topological_network - pygplates.FeatureType.gpml_oceanic_crust - pygplates.FeatureType.gpml_topological_slab_boundary - pygplates.FeatureType.gpml_topological_closed_plate_boundary ridge_transforms : iterable/list of <pygplates.Feature> A list containing ridge and transform boundary sections of type pygplates.FeatureType.gpml_mid_ocean_ridge ridges : iterable/list of <pygplates.Feature> A list containing ridge boundary sections of type pygplates.FeatureType.gpml_mid_ocean_ridge transforms : iterable/list of <pygplates.Feature> A list containing transform boundary sections of type pygplates.FeatureType.gpml_mid_ocean_ridge trenches : iterable/list of <pygplates.Feature> A list containing trench boundary sections of type pygplates.FeatureType.gpml_subduction_zone trench_left : iterable/list of <pygplates.Feature> A list containing left subduction boundary sections of type pygplates.FeatureType.gpml_subduction_zone trench_right : iterable/list of <pygplates.Feature> A list containing right subduction boundary sections of type pygplates.FeatureType.gpml_subduction_zone other : iterable/list of <pygplates.Feature> A list containing other geological features like unclassified features, extended continental crusts, continental rifts, faults, orogenic belts, fracture zones, inferred paleo boundaries, terrane boundaries and passive continental boundaries. """ def __init__( self, plate_reconstruction, coastlines=None, continents=None, COBs=None, time=None, anchor_plate_id=0, ): self.plate_reconstruction = plate_reconstruction if self.plate_reconstruction.topology_features is None: raise ValueError("Plate model must have topology features.") self.base_projection = ccrs.PlateCarree() # store these for when time is updated # make sure these are initialised as FeatureCollection objects self._coastlines = _load_FeatureCollection(coastlines) self._continents = _load_FeatureCollection(continents) self._COBs = _load_FeatureCollection(COBs) self.coastlines = None self.continents = None self.COBs = None self._anchor_plate_id = self._check_anchor_plate_id(anchor_plate_id) # store topologies for easy access # setting time runs the update_time routine if time is not None: self.time = time else: self._time = None def __getstate__(self): filenames = self.plate_reconstruction.__getstate__() # add important variables from Points object if self._coastlines: filenames["coastlines"] = self._coastlines.filenames if self._continents: filenames["continents"] = self._continents.filenames if self._COBs: filenames["COBs"] = self._COBs.filenames filenames['time'] = self.time filenames['plate_id'] = self._anchor_plate_id return filenames def __setstate__(self, state): self.plate_reconstruction = _PlateReconstruction(state['rotation_model'], state['topology_features'], state['static_polygons']) self._coastlines = None self._continents = None self._COBs = None self.coastlines = None self.continents = None self.COBs = None # reinstate unpicklable items if 'coastlines' in state: self._coastlines = _FeatureCollection() for feature in state['coastlines']: self._coastlines.add( _FeatureCollection(feature) ) if 'continents' in state: self._continents = _FeatureCollection() for feature in state['continents']: self._continents.add( _FeatureCollection(feature) ) if 'COBs' in state: self._COBs = _FeatureCollection() for feature in state['COBs']: self._COBs.add( _FeatureCollection(feature) ) self._anchor_plate_id = state["plate_id"] self.base_projection = ccrs.PlateCarree() self._time = None @property def time(self): """ The reconstruction time.""" return self._time @time.setter def time(self, var): """Allows the time attribute to be changed. Updates all instances of the time attribute in the object (e.g. reconstructions and resolving topologies will use this new time). Raises ------ ValueError If the chosen reconstruction time is <0 Ma. """ if var >= 0: self.update_time(var) else: raise ValueError("Enter a valid time >= 0") @property def anchor_plate_id(self): """Anchor plate ID for reconstruction. Must be an integer >= 0.""" return self._anchor_plate_id @anchor_plate_id.setter def anchor_plate_id(self, anchor_plate): self._anchor_plate_id = self._check_anchor_plate_id(anchor_plate) self.update_time(self.time) @staticmethod def _check_anchor_plate_id(id): id = int(id) if id < 0: raise ValueError( "Invalid anchor plate ID: {}".format(id) ) return id def update_time(self, time): """Re-reconstruct features and topologies to the time specified by the `PlotTopologies` `time` attribute whenever it or the anchor plate is updated. Notes ----- The following `PlotTopologies` attributes are updated whenever a reconstruction `time` attribute is set: - resolved topology features (topological plates and networks) - ridge and transform boundary sections (resolved features) - ridge boundary sections (resolved features) - transform boundary sections (resolved features) - subduction boundary sections (resolved features) - left subduction boundary sections (resolved features) - right subduction boundary sections (resolved features) - other boundary sections (resolved features) that are not subduction zones or mid-ocean ridges (ridge/transform) Moreover, coastlines, continents and COBs are reconstructed to the new specified `time`. """ self._time = float(time) resolved_topologies = ptt.resolve_topologies.resolve_topologies_into_features( self.plate_reconstruction.rotation_model, self.plate_reconstruction.topology_features, self.time) self.topologies, self.ridge_transforms, self.ridges, self.transforms, self.trenches, self.trench_left, self.trench_right, self.other = resolved_topologies # miscellaneous boundaries self.continental_rifts = [] self.faults = [] self.fracture_zones = [] self.inferred_paleo_boundaries = [] self.terrane_boundaries = [] self.transitional_crusts = [] self.orogenic_belts = [] self.sutures = [] self.continental_crusts = [] self.extended_continental_crusts = [] self.passive_continental_boundaries = [] self.slab_edges = [] self.misc_transforms = [] self.unclassified_features = [] for topol in self.other: if topol.get_feature_type() == pygplates.FeatureType.gpml_continental_rift: self.continental_rifts.append(topol) elif topol.get_feature_type() == pygplates.FeatureType.gpml_fault: self.faults.append(topol) elif topol.get_feature_type() == pygplates.FeatureType.gpml_fracture_zone: self.fracture_zones.append(topol) elif topol.get_feature_type() == pygplates.FeatureType.gpml_inferred_paleo_boundary: self.inferred_paleo_boundaries.append(topol) elif topol.get_feature_type() == pygplates.FeatureType.gpml_terrane_boundary: self.terrane_boundaries.append(topol) elif topol.get_feature_type() == pygplates.FeatureType.gpml_transitional_crust: self.transitional_crusts.append(topol) elif topol.get_feature_type() == pygplates.FeatureType.gpml_orogenic_belt: self.orogenic_belts.append(topol) elif topol.get_feature_type() == pygplates.FeatureType.gpml_suture: self.sutures.append(topol) elif topol.get_feature_type() == pygplates.FeatureType.gpml_continental_crust: self.continental_crusts.append(topol) elif topol.get_feature_type() == pygplates.FeatureType.gpml_extended_continental_crust: self.extended_continental_crusts.append(topol) elif topol.get_feature_type() == pygplates.FeatureType.gpml_passive_continental_boundary: self.passive_continental_boundaries.append(topol) elif topol.get_feature_type() == pygplates.FeatureType.gpml_slab_edge: self.slab_edges.append(topol) elif topol.get_feature_type() == pygplates.FeatureType.gpml_transform: self.misc_transforms.append(topol) elif topol.get_feature_type() == pygplates.FeatureType.gpml_unclassified_feature: self.unclassified_features.append(topol) # reconstruct other important polygons and lines if self._coastlines: self.coastlines = self.plate_reconstruction.reconstruct( self._coastlines, self.time, from_time=0, anchor_plate_id=self.anchor_plate_id) if self._continents: self.continents = self.plate_reconstruction.reconstruct( self._continents, self.time, from_time=0, anchor_plate_id=self.anchor_plate_id) if self._COBs: self.COBs = self.plate_reconstruction.reconstruct( self._COBs, self.time, from_time=0, anchor_plate_id=self.anchor_plate_id) # subduction teeth def _tessellate_triangles(self, features, tesselation_radians, triangle_base_length, triangle_aspect=1.0): """Places subduction teeth along subduction boundary line segments within a MultiLineString shapefile. Parameters ---------- shapefilename : str Path to shapefile containing the subduction boundary features tesselation_radians : float Parametrises subduction teeth density. Triangles are generated only along line segments with distances that exceed the given threshold tessellation_radians. triangle_base_length : float Length of teeth triangle base triangle_aspect : float, default=1.0 Aspect ratio of teeth triangles. Ratio is 1.0 by default. Returns ------- X_points : (n,3) array X points that define the teeth triangles Y_points : (n,3) array Y points that define the teeth triangles """ tesselation_degrees = np.degrees(tesselation_radians) triangle_pointsX = [] triangle_pointsY = [] date_line_wrapper = pygplates.DateLineWrapper() for feature in features: cum_distance = 0.0 for geometry in feature.get_geometries(): wrapped_lines = date_line_wrapper.wrap(geometry) for line in wrapped_lines: pts = np.array([(p.get_longitude(), p.get_latitude()) for p in line.get_points()]) for p in range(0, len(pts) - 1): A = pts[p] B = pts[p+1] AB_dist = B - A AB_norm = AB_dist / np.hypot(*AB_dist) cum_distance += np.hypot(*AB_dist) # create a new triangle if cumulative distance is exceeded. if cum_distance >= tesselation_degrees: C = A + triangle_base_length*AB_norm # find normal vector AD_dist = np.array([AB_norm[1], -AB_norm[0]]) AD_norm = AD_dist / np.linalg.norm(AD_dist) C0 = A + 0.5*triangle_base_length*AB_norm # project point along normal vector D = C0 + triangle_base_length*triangle_aspect*AD_norm triangle_pointsX.append( [A[0], C[0], D[0]] ) triangle_pointsY.append( [A[1], C[1], D[1]] ) cum_distance = 0.0 return np.array(triangle_pointsX), np.array(triangle_pointsY) def get_feature(self, feature): """Create a geopandas.GeoDataFrame object containing geometries of reconstructed features. Notes ----- The feature needed to produce the GeoDataFrame should already be constructed to a `time`. This function converts the feature into a set of Shapely geometries whose coordinates are passed to a geopandas GeoDataFrame. Parameters ---------- feature : instance of <pygplates.Feature> A feature reconstructed to `time`. Returns ------- gdf : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `feature` geometries. """ shp = shapelify_features(feature) gdf = gpd.GeoDataFrame({'geometry': shp}, geometry='geometry') return gdf def plot_feature(self, ax, feature, **kwargs): """ Plot pygplates.FeatureCollection or pygplates.Feature onto a map. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. **kwargs : Keyword arguments for parameters such as `facecolor`, `alpha`, etc. for plotting coastline geometries. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with coastline features plotted onto the chosen map projection. """ gdf = self.get_feature(feature) return gdf.plot(ax=ax, transform=self.base_projection, **kwargs) def get_coastlines(self): """Create a geopandas.GeoDataFrame object containing geometries of reconstructed coastline polygons. Notes ----- The `coastlines` needed to produce the GeoDataFrame are automatically constructed if the optional `time` parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed either when `PlotTopologies` is first called... gplot = gplately.PlotTopologies(..., time=100,...) or anytime afterwards, by setting: time = 100 #Ma gplot.time = time ...after which this function can be re-run. Once the `coastlines` are reconstructed, they are converted into Shapely polygons whose coordinates are passed to a geopandas GeoDataFrame. Returns ------- gdf : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `coastlines` geometry. Raises ------ ValueError If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct `coastlines` to the requested `time` and thus populate the GeoDataFrame. """ if self._time is None: raise ValueError("No coastlines have been resolved. Set `PlotTopologies.time` to construct coastlines.") if self.coastlines is None: raise ValueError("Supply coastlines to PlotTopologies object") coastline_polygons = shapelify_feature_polygons(self.coastlines) gdf = gpd.GeoDataFrame({"geometry": coastline_polygons}, geometry="geometry") return gdf def plot_coastlines(self, ax, **kwargs): """Plot reconstructed coastline polygons onto a standard map Projection. Notes ----- The `coastlines` for plotting are accessed from the `PlotTopologies` object's `coastlines` attribute. These `coastlines` are reconstructed to the `time` passed to the `PlotTopologies` object and converted into Shapely polylines. The reconstructed `coastlines` are added onto the GeoAxes or GeoAxesSubplot map `ax` using GeoPandas. Map resentation details (e.g. facecolor, edgecolor, alpha…) are permitted as keyword arguments. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. **kwargs : Keyword arguments for parameters such as `facecolor`, `alpha`, etc. for plotting coastline geometries. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with coastline features plotted onto the chosen map projection. """ gdf = self.get_coastlines() return gdf.plot(ax=ax, transform=self.base_projection, **kwargs) def get_continents(self): """Create a geopandas.GeoDataFrame object containing geometries of reconstructed continental polygons. Notes ----- The `continents` needed to produce the GeoDataFrame are automatically constructed if the optional `time` parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed either when `PlotTopologies` is first called... gplot = gplately.PlotTopologies(..., time=100,...) or anytime afterwards, by setting: time = 100 #Ma gplot.time = time ...after which this function can be re-run. Once the `continents` are reconstructed, they are converted into Shapely polygons whose coordinates are passed to a geopandas GeoDataFrame. Returns ------- gdf : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `continents` geometry. Raises ------ ValueError If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct `continents` to the requested `time` and thus populate the GeoDataFrame. """ if self._time is None: raise ValueError("No continents have been resolved. Set `PlotTopologies.time` to construct continents.") if self.continents is None: raise ValueError("Supply continents to PlotTopologies object") continent_polygons = shapelify_feature_polygons(self.continents) gdf = gpd.GeoDataFrame({"geometry": continent_polygons}, geometry="geometry") return gdf def plot_continents(self, ax, **kwargs): """Plot reconstructed continental polygons onto a standard map Projection. Notes ----- The `continents` for plotting are accessed from the `PlotTopologies` object's `continents` attribute. These `continents` are reconstructed to the `time` passed to the `PlotTopologies` object and converted into Shapely polygons. The reconstructed `coastlines` are plotted onto the GeoAxes or GeoAxesSubplot map `ax` using GeoPandas. Map presentation details (e.g. facecolor, edgecolor, alpha…) are permitted as keyword arguments. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. **kwargs : Keyword arguments for parameters such as `facecolor`, `alpha`, etc. for plotting continental geometries. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with continent features plotted onto the chosen map projection. """ gdf = self.get_continents() return gdf.plot(ax=ax, transform=self.base_projection, **kwargs) def get_continent_ocean_boundaries(self): """Create a geopandas.GeoDataFrame object containing geometries of reconstructed continent-ocean boundary lines. Notes ----- The `COBs` needed to produce the GeoDataFrame are automatically constructed if the optional `time` parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed either when `PlotTopologies` is first called... gplot = gplately.PlotTopologies(..., time=100,...) or anytime afterwards, by setting: time = 100 #Ma gplot.time = time ...after which this function can be re-run. Once the `COBs` are reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame. Returns ------- gdf : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `COBs` geometry. Raises ------ ValueError If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct `COBs` to the requested `time` and thus populate the GeoDataFrame. """ if self._time is None: raise ValueError("No geometries have been resolved. Set `PlotTopologies.time` to construct topologies.") if self.COBs is None: raise ValueError("Supply COBs to PlotTopologies object") COB_lines = shapelify_feature_lines(self.COBs) gdf = gpd.GeoDataFrame({"geometry": COB_lines}, geometry="geometry") return gdf def plot_continent_ocean_boundaries(self, ax, **kwargs): """Plot reconstructed continent-ocean boundary (COB) polygons onto a standard map Projection. Notes ----- The `COBs` for plotting are accessed from the `PlotTopologies` object's `COBs` attribute. These `COBs` are reconstructed to the `time` passed to the `PlotTopologies` object and converted into Shapely polylines. The reconstructed `COBs` are plotted onto the GeoAxes or GeoAxesSubplot map `ax` using GeoPandas. Map presentation details (e.g. `facecolor`, `edgecolor`, `alpha`…) are permitted as keyword arguments. These COBs are transformed into shapely geometries and added onto the chosen map for a specific geological time (supplied to the PlotTopologies object). Map presentation details (e.g. facecolor, edgecolor, alpha…) are permitted. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. **kwargs : Keyword arguments for parameters such as `facecolor`, `alpha`, etc. for plotting COB geometries. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with COB features plotted onto the chosen map projection. """ gdf = self.get_continent_ocean_boundaries() return gdf.plot(ax=ax, transform=self.base_projection, **kwargs) def get_ridges(self): """Create a geopandas.GeoDataFrame object containing geometries of reconstructed ridge lines. Notes ----- The `ridges` needed to produce the GeoDataFrame are automatically constructed if the optional `time` parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed either when `PlotTopologies` is first called... gplot = gplately.PlotTopologies(..., time=100,...) or anytime afterwards, by setting: time = 100 #Ma gplot.time = time ...after which this function can be re-run. Once the `ridges` are reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame. Returns ------- gdf : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `ridges` geometry. Raises ------ ValueError If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct `ridges` to the requested `time` and thus populate the GeoDataFrame. """ if self._time is None: raise ValueError("No ridges have been resolved. Set `PlotTopologies.time` to construct ridges.") if self.ridges is None: raise ValueError("No ridge topologies passed to PlotTopologies.") ridge_lines = shapelify_feature_lines(self.ridges) gdf = gpd.GeoDataFrame({"geometry": ridge_lines}, geometry="geometry") return gdf def plot_ridges(self, ax, color='black', **kwargs): """Plot reconstructed ridge polylines onto a standard map Projection. Notes ----- The `ridges` for plotting are accessed from the `PlotTopologies` object's `ridges` attribute. These `ridges` are reconstructed to the `time` passed to the `PlotTopologies` object and converted into Shapely polylines. The reconstructed `ridges` are plotted onto the GeoAxes or GeoAxesSubplot map `ax` using GeoPandas. Map presentation details (e.g. `facecolor`, `edgecolor`, `alpha`…) are permitted as keyword arguments. Ridge geometries are wrapped to the dateline using pyGPlates' [DateLineWrapper](https://www.gplates.org/docs/pygplates/generated/pygplates.datelinewrapper) by splitting a polyline into multiple polylines at the dateline. This is to avoid horizontal lines being formed between polylines at longitudes of -180 and 180 degrees. Point features near the poles (-89 & 89 degree latitude) are also clipped to ensure compatibility with Cartopy. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. color : str, default=’black’ The colour of the ridge lines. By default, it is set to black. **kwargs : Keyword arguments for parameters such as `alpha`, etc. for plotting ridge geometries. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with ridge features plotted onto the chosen map projection. """ gdf = self.get_ridges() return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs) def get_ridges_and_transforms(self): """Create a geopandas.GeoDataFrame object containing geometries of reconstructed ridge and transform lines. Notes ----- The `ridge_transforms` needed to produce the GeoDataFrame are automatically constructed if the optional `time` parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed either when `PlotTopologies` is first called... gplot = gplately.PlotTopologies(..., time=100,...) or anytime afterwards, by setting: time = 100 #Ma gplot.time = time ...after which this function can be re-run. Once the `ridge_transforms` are reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame. Returns ------- gdf : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `ridges` geometry. Raises ------ ValueError If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct `ridge_transforms` to the requested `time` and thus populate the GeoDataFrame. """ if self._time is None: raise ValueError("No ridges and transforms have been resolved. Set `PlotTopologies.time` to construct ridges and transforms.") if self.ridge_transforms is None: raise ValueError("No ridge and transform topologies passed to PlotTopologies.") ridge_transform_lines = shapelify_feature_lines(self.ridge_transforms) gdf = gpd.GeoDataFrame({"geometry": ridge_transform_lines}, geometry="geometry") return gdf def plot_ridges_and_transforms(self, ax, color='black', **kwargs): """Plot reconstructed ridge & transform boundary polylines onto a standard map Projection. Notes ----- The ridge & transform sections for plotting are accessed from the `PlotTopologies` object's `ridge_transforms` attribute. These `ridge_transforms` are reconstructed to the `time` passed to the `PlotTopologies` object and converted into Shapely polylines. The reconstructed `ridge_transforms` are plotted onto the GeoAxes or GeoAxesSubplot map `ax` using GeoPandas. Map presentation details (e.g. `facecolor`, `edgecolor`, `alpha`…) are permitted as keyword arguments. Note: Ridge & transform geometries are wrapped to the dateline using pyGPlates' [DateLineWrapper](https://www.gplates.org/docs/pygplates/generated/pygplates.datelinewrapper) by splitting a polyline into multiple polylines at the dateline. This is to avoid horizontal lines being formed between polylines at longitudes of -180 and 180 degrees. Point features near the poles (-89 & 89 degree latitude) are also clipped to ensure compatibility with Cartopy. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. color : str, default=’black’ The colour of the ridge & transform lines. By default, it is set to black. **kwargs : Keyword arguments for parameters such as ‘alpha’, etc. for plotting ridge & transform geometries. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with ridge & transform features plotted onto the chosen map projection. """ gdf = self.get_ridges_and_transforms() return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs) def get_transforms(self): """Create a geopandas.GeoDataFrame object containing geometries of reconstructed transform lines. Notes ----- The `transforms` needed to produce the GeoDataFrame are automatically constructed if the optional `time` parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed either when `PlotTopologies` is first called... gplot = gplately.PlotTopologies(..., time=100,...) or anytime afterwards, by setting: time = 100 #Ma gplot.time = time ...after which this function can be re-run. Once the `transforms` are reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame. Returns ------- gdf : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `transforms` geometry. Raises ------ ValueError If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct `transforms` to the requested `time` and thus populate the GeoDataFrame. """ if self._time is None: raise ValueError("No transforms have been resolved. Set `PlotTopologies.time` to construct transforms.") if self.transforms is None: raise ValueError("No transform topologies passed to PlotTopologies.") transform_lines = shapelify_feature_lines(self.transforms) gdf = gpd.GeoDataFrame({"geometry": transform_lines}, geometry="geometry") return gdf def plot_transforms(self, ax, color='black', **kwargs): """Plot reconstructed transform boundary polylines onto a standard map. Notes ----- The transform sections for plotting are accessed from the `PlotTopologies` object's `transforms` attribute. These `transforms` are reconstructed to the `time` passed to the `PlotTopologies` object and converted into Shapely polylines. The reconstructed `transforms` are plotted onto the GeoAxes or GeoAxesSubplot map `ax` using GeoPandas. Map presentation details (e.g. `facecolor`, `edgecolor`, `alpha`…) are permitted as keyword arguments. Transform geometries are wrapped to the dateline using pyGPlates' [DateLineWrapper](https://www.gplates.org/docs/pygplates/generated/pygplates.datelinewrapper) by splitting a polyline into multiple polylines at the dateline. This is to avoid horizontal lines being formed between polylines at longitudes of -180 and 180 degrees. Point features near the poles (-89 & 89 degree latitude) are also clipped to ensure compatibility with Cartopy. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. color : str, default=’black’ The colour of the transform lines. By default, it is set to black. **kwargs : Keyword arguments for parameters such as `alpha`, etc. for plotting transform geometries. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with transform features plotted onto the chosen map projection. """ gdf = self.get_transforms() return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs) def get_trenches(self): """Create a geopandas.GeoDataFrame object containing geometries of reconstructed trench lines. Notes ----- The `trenches` needed to produce the GeoDataFrame are automatically constructed if the optional `time` parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed either when `PlotTopologies` is first called... gplot = gplately.PlotTopologies(..., time=100,...) or anytime afterwards, by setting: time = 100 #Ma gplot.time = time ...after which this function can be re-run. Once the `trenches` are reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame. Returns ------- gdf : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `trenches` geometry. Raises ------ ValueError If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct `trenches` to the requested `time` and thus populate the GeoDataFrame. """ if self._time is None: raise ValueError("No trenches have been resolved. Set `PlotTopologies.time` to construct trenches.") if self.trenches is None: raise ValueError("No trenches passed to PlotTopologies.") trench_lines = shapelify_feature_lines(self.trenches) gdf = gpd.GeoDataFrame({"geometry": trench_lines}, geometry="geometry") return gdf def plot_trenches(self, ax, color='black', **kwargs): """Plot reconstructed subduction trench polylines onto a standard map Projection. Notes ----- The trench sections for plotting are accessed from the `PlotTopologies` object's `trenches` attribute. These `trenches` are reconstructed to the `time` passed to the `PlotTopologies` object and converted into Shapely polylines. The reconstructed `trenches` are plotted onto the GeoAxes or GeoAxesSubplot map `ax` using GeoPandas. Map presentation details (e.g. `facecolor`, `edgecolor`, `alpha`…) are permitted as keyword arguments. Trench geometries are wrapped to the dateline using pyGPlates' [DateLineWrapper](https://www.gplates.org/docs/pygplates/generated/pygplates.datelinewrapper) by splitting a polyline into multiple polylines at the dateline. This is to avoid horizontal lines being formed between polylines at longitudes of -180 and 180 degrees. Point features near the poles (-89 & 89 degree latitude) are also clipped to ensure compatibility with Cartopy. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. color : str, default=’black’ The colour of the trench lines. By default, it is set to black. **kwargs : Keyword arguments for parameters such as `alpha`, etc. for plotting trench geometries. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with transform features plotted onto the chosen map projection. """ gdf = self.get_trenches() return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs) def get_misc_boundaries(self): """Create a geopandas.GeoDataFrame object containing geometries of other reconstructed lines. Notes ----- The `other` geometries needed to produce the GeoDataFrame are automatically constructed if the optional `time` parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed either when `PlotTopologies` is first called... gplot = gplately.PlotTopologies(..., time=100,...) or anytime afterwards, by setting: time = 100 #Ma gplot.time = time ...after which this function can be re-run. Once the `other` geometries are reconstructed, they are converted into Shapely features whose coordinates are passed to a geopandas GeoDataFrame. Returns ------- gdf : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `other` geometry. Raises ------ ValueError If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct `other` geometries to the requested `time` and thus populate the GeoDataFrame. """ if self._time is None: raise ValueError("No miscellaneous topologies have been resolved. Set `PlotTopologies.time` to construct them.") if self.other is None: raise ValueError("No miscellaneous topologies passed to PlotTopologies.") lines = shapelify_features(self.other) gdf = gpd.GeoDataFrame({"geometry": lines}, geometry="geometry") return gdf def plot_misc_boundaries(self, ax, color="black", **kwargs): """Plot reconstructed miscellaneous plate boundary polylines onto a standard map Projection. Notes ----- The miscellaneous boundary sections for plotting are accessed from the `PlotTopologies` object's `other` attribute. These `other` boundaries are reconstructed to the `time` passed to the `PlotTopologies` object and converted into Shapely polylines. The reconstructed `other` boundaries are plotted onto the GeoAxes or GeoAxesSubplot map `ax` using GeoPandas. Map presentation details (e.g. `facecolor`, `edgecolor`, `alpha`…) are permitted as keyword arguments. Miscellaneous boundary geometries are wrapped to the dateline using pyGPlates' [DateLineWrapper](https://www.gplates.org/docs/pygplates/generated/pygplates.datelinewrapper) by splitting a polyline into multiple polylines at the dateline. This is to avoid horizontal lines being formed between polylines at longitudes of -180 and 180 degrees. Point features near the poles (-89 & 89 degree latitude) are also clipped to ensure compatibility with Cartopy. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. color : str, default=’black’ The colour of the boundary lines. By default, it is set to black. **kwargs : Keyword arguments for parameters such as ‘alpha’, etc. for plotting miscellaneous boundary geometries. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with miscellaneous boundary features plotted onto the chosen map projection. """ gdf = self.get_misc_boundaries() return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs) def plot_subduction_teeth_deprecated(self, ax, spacing=0.1, size=2.0, aspect=1, color='black', **kwargs): """Plot subduction teeth onto a standard map Projection. Notes ----- Subduction teeth are tessellated from `PlotTopologies` object attributes `trench_left` and `trench_right`, and transformed into Shapely polygons for plotting. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. spacing : float, default=0.1 The tessellation threshold (in radians). Parametrises subduction tooth density. Triangles are generated only along line segments with distances that exceed the given threshold ‘spacing’. size : float, default=2.0 Length of teeth triangle base. aspect : float, default=1 Aspect ratio of teeth triangles. Ratio is 1.0 by default. color : str, default=’black’ The colour of the teeth. By default, it is set to black. **kwargs : Keyword arguments for parameters such as ‘alpha’, etc. for plotting subduction tooth polygons. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with subduction teeth plotted onto the chosen map projection. """ import shapely # add Subduction Teeth subd_xL, subd_yL = self._tessellate_triangles( self.trench_left, tesselation_radians=spacing, triangle_base_length=size, triangle_aspect=-aspect) subd_xR, subd_yR = self._tessellate_triangles( self.trench_right, tesselation_radians=spacing, triangle_base_length=size, triangle_aspect=aspect) teeth = [] for tX, tY in zip(subd_xL, subd_yL): triangle_xy_points = np.c_[tX, tY] shp = shapely.geometry.Polygon(triangle_xy_points) teeth.append(shp) for tX, tY in zip(subd_xR, subd_yR): triangle_xy_points = np.c_[tX, tY] shp = shapely.geometry.Polygon(triangle_xy_points) teeth.append(shp) return ax.add_geometries(teeth, crs=self.base_projection, color=color, **kwargs) def get_subduction_direction(self): """Create a geopandas.GeoDataFrame object containing geometries of trench directions. Notes ----- The `trench_left` and `trench_right` geometries needed to produce the GeoDataFrame are automatically constructed if the optional `time` parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed either when `PlotTopologies` is first called... gplot = gplately.PlotTopologies(..., time=100,...) or anytime afterwards, by setting: time = 100 #Ma gplot.time = time ...after which this function can be re-run. Once the `other` geometries are reconstructed, they are converted into Shapely features whose coordinates are passed to a geopandas GeoDataFrame. Returns ------- gdf_left : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `trench_left` geometry. gdf_right : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `trench_right` geometry. Raises ------ ValueError If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct `trench_left` or `trench_right` geometries to the requested `time` and thus populate the GeoDataFrame. """ if self._time is None: raise ValueError("No miscellaneous topologies have been resolved. Set `PlotTopologies.time` to construct them.") if self.trench_left is None or self.trench_right is None: raise ValueError("No trench_left or trench_right topologies passed to PlotTopologies.") trench_left_features = shapelify_feature_lines(self.trench_left) trench_right_features = shapelify_feature_lines(self.trench_right) gdf_left = gpd.GeoDataFrame({"geometry": trench_left_features}, geometry="geometry") gdf_right = gpd.GeoDataFrame({"geometry": trench_right_features}, geometry="geometry") return gdf_left, gdf_right def plot_subduction_teeth(self, ax, spacing=0.07, size=None, aspect=None, color='black', **kwargs): """Plot subduction teeth onto a standard map Projection. Notes ----- Subduction teeth are tessellated from `PlotTopologies` object attributes `trench_left` and `trench_right`, and transformed into Shapely polygons for plotting. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. spacing : float, default=0.1 The tessellation threshold (in radians). Parametrises subduction tooth density. Triangles are generated only along line segments with distances that exceed the given threshold ‘spacing’. size : float, default=None Length of teeth triangle base (in radians). If kept at `None`, then `size = 0.5*spacing`. aspect : float, default=None Aspect ratio of teeth triangles. If kept at `None`, then `aspect = 2/3*size`. color : str, default=’black’ The colour of the teeth. By default, it is set to black. **kwargs : Keyword arguments parameters such as ‘alpha’, etc. for plotting subduction tooth polygons. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with subduction teeth plotted onto the chosen map projection. """ if self._time is None: raise ValueError("No miscellaneous topologies have been resolved. Set `PlotTopologies.time` to construct them.") spacing = spacing * EARTH_RADIUS * 1e3 if aspect is None: aspect = 2.0/3.0 if size is None: size = spacing*0.5 height = size*aspect trench_left_features = shapelify_feature_lines(self.trench_left) trench_right_features = shapelify_feature_lines(self.trench_right) return( plot_subduction_teeth(trench_left_features, size, 'l', height, spacing, ax=ax, color=color, **kwargs), plot_subduction_teeth(trench_right_features, size, 'r', height, spacing, ax=ax, color=color, **kwargs) ) def plot_plate_id(self, ax, plate_id, **kwargs): """Plot a plate polygon with an associated `plate_id` onto a standard map Projection. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. plate_id : int A plate ID that identifies the continental polygon to plot. See the [Global EarthByte plate IDs list](https://www.earthbyte.org/webdav/ftp/earthbyte/GPlates/SampleData/FeatureCollections/Rotations/Global_EarthByte_PlateIDs_20071218.pdf) for a full list of plate IDs to plot. **kwargs : Keyword arguments for map presentation parameters such as `alpha`, etc. for plotting the grid. See `Matplotlib`'s `imshow` keyword arguments [here](https://matplotlib.org/3.5.1/api/_as_gen/matplotlib.axes.Axes.imshow.html). """ for feature in self.topologies: if feature.get_reconstruction_plate_id() == plate_id: ft_plate = shapelify_feature_polygons([feature]) return ax.add_geometries(ft_plate, crs=self.base_projection, **kwargs) def plot_grid(self, ax, grid, extent=[-180,180,-90,90], **kwargs): """Plot a `MaskedArray` raster or grid onto a standard map Projection. Notes ----- Uses Matplotlib's `imshow` [function](https://matplotlib.org/3.5.1/api/_as_gen/matplotlib.axes.Axes.imshow.html). Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. grid : MaskedArray or `gplately.grids.Raster` A `MaskedArray` with elements that define a grid. The number of rows in the raster corresponds to the number of latitudinal coordinates, while the number of raster columns corresponds to the number of longitudinal coordinates. extent : 1d array, default=[-180,180,-90,90] A four-element array to specify the [min lon, max lon, min lat, max lat] with which to constrain the grid image. If no extents are supplied, full global extent is assumed. **kwargs : Keyword arguments for map presentation parameters such as `alpha`, etc. for plotting the grid. See `Matplotlib`'s `imshow` keyword arguments [here](https://matplotlib.org/3.5.1/api/_as_gen/matplotlib.axes.Axes.imshow.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with the grid plotted onto the chosen map projection. """ # Override matplotlib default origin ('upper') origin = kwargs.pop("origin", "lower") from .grids import Raster if isinstance(grid, Raster): # extract extent and origin extent = grid.extent origin = grid.origin data = grid.data else: data = grid return ax.imshow( data, extent=extent, transform=self.base_projection, origin=origin, **kwargs, ) def plot_grid_from_netCDF(self, ax, filename, **kwargs): """Read a raster from a netCDF file, convert it to a `MaskedArray` and plot it onto a standard map Projection. Notes ----- `plot_grid_from_netCDF` uses Matplotlib's `imshow` [function](https://matplotlib.org/3.5.1/api/_as_gen/matplotlib.axes.Axes.imshow.html). Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. filename : str Full path to a netCDF filename. **kwargs : Keyword arguments for map presentation parameters for plotting the grid. See `Matplotlib`'s `imshow` keyword arguments [here](https://matplotlib.org/3.5.1/api/_as_gen/matplotlib.axes.Axes.imshow.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with the netCDF grid plotted onto the chosen map projection. """ # Override matplotlib default origin ('upper') origin = kwargs.pop("origin", "lower") from .grids import read_netcdf_grid raster, lon_coords, lat_coords = read_netcdf_grid(filename, return_grids=True) extent = [lon_coords[0], lon_coords[-1], lat_coords[0], lat_coords[-1]] if lon_coords[0] < lat_coords[-1]: origin = "lower" else: origin = "upper" return self.plot_grid(ax, raster, extent=extent, origin=origin, **kwargs) def plot_plate_motion_vectors(self, ax, spacingX=10, spacingY=10, normalise=False, **kwargs): """Calculate plate motion velocity vector fields at a particular geological time and plot them onto a standard map Projection. Notes ----- `plot_plate_motion_vectors` generates a MeshNode domain of point features using given spacings in the X and Y directions (`spacingX` and `spacingY`). Each point in the domain is assigned a plate ID, and these IDs are used to obtain equivalent stage rotations of identified tectonic plates over a 5 Ma time interval. Each point and its stage rotation are used to calculate plate velocities at a particular geological time. Velocities for each domain point are represented in the north-east-down coordinate system and plotted on a GeoAxes. Vector fields can be optionally normalised by setting `normalise` to `True`. This makes vector arrow lengths uniform. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. spacingX : int, default=10 The spacing in the X direction used to make the velocity domain point feature mesh. spacingY : int, default=10 The spacing in the Y direction used to make the velocity domain point feature mesh. normalise : bool, default=False Choose whether to normalise the velocity magnitudes so that vector lengths are all equal. **kwargs : Keyword arguments for quiver presentation parameters for plotting the velocity vector field. See `Matplotlib` quiver keyword arguments [here](https://matplotlib.org/3.5.1/api/_as_gen/matplotlib.axes.Axes.quiver.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with the velocity vector field plotted onto the chosen map projection. """ lons = np.arange(-180, 180+spacingX, spacingX) lats = np.arange(-90, 90+spacingY, spacingY) lonq, latq = np.meshgrid(lons, lats) # create a feature from all the points velocity_domain_features = ptt.velocity_tools.make_GPML_velocity_feature(lonq.ravel(), latq.ravel()) rotation_model = self.plate_reconstruction.rotation_model topology_features = self.plate_reconstruction.topology_features delta_time = 5.0 all_velocities = ptt.velocity_tools.get_plate_velocities( velocity_domain_features, topology_features, rotation_model, self.time, delta_time, 'vector_comp') X, Y, U, V = ptt.velocity_tools.get_x_y_u_v(lons, lats, all_velocities) if normalise: mag = np.hypot(U, V) mag[mag == 0] = 1 U /= mag V /= mag with warnings.catch_warnings(): warnings.simplefilter("ignore", UserWarning) quiver = ax.quiver( X, Y, U, V, transform=self.base_projection, **kwargs ) return quiver def get_continental_rifts(self): """Create a geopandas.GeoDataFrame object containing geometries of reconstructed contiental rift lines. Notes ----- The `continental_rifts` needed to produce the GeoDataFrame are automatically constructed if the optional `time` parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed either when `PlotTopologies` is first called... gplot = gplately.PlotTopologies(..., time=100,...) or anytime afterwards, by setting: time = 100 #Ma gplot.time = time ...after which this function can be re-run. Once the `continental_rifts` are reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame. Returns ------- gdf : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `continental_rifts` geometry. Raises ------ ValueError If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct `continental_rifts` to the requested `time` and thus populate the GeoDataFrame. """ if self._time is None: raise ValueError("No continental rifts have been resolved. Set `PlotTopologies.time` to construct them.") if self.continental_rifts is None: raise ValueError("No continental rifts passed to PlotTopologies.") continental_rift_lines = shapelify_feature_lines(self.continental_rifts) gdf = gpd.GeoDataFrame({"geometry": continental_rift_lines}, geometry="geometry") return gdf def plot_continental_rifts(self, ax, color='black', **kwargs): """Plot continental rifts on a standard map projection. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. color : str, default=’black’ The colour of the trench lines. By default, it is set to black. **kwargs : Keyword arguments for parameters such as `alpha`, etc. for plotting trench geometries. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with continental rifts plotted onto the chosen map projection. """ gdf = self.get_continental_rifts() return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs) def get_faults(self): """Create a geopandas.GeoDataFrame object containing geometries of reconstructed fault lines. Notes ----- The `faults` needed to produce the GeoDataFrame are automatically constructed if the optional `time` parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed either when `PlotTopologies` is first called... gplot = gplately.PlotTopologies(..., time=100,...) or anytime afterwards, by setting: time = 100 #Ma gplot.time = time ...after which this function can be re-run. Once the `faults` are reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame. Returns ------- gdf : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `faults` geometry. Raises ------ ValueError If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct `faults` to the requested `time` and thus populate the GeoDataFrame. """ if self._time is None: raise ValueError("No faults have been resolved. Set `PlotTopologies.time` to construct them.") if self.faults is None: raise ValueError("No faults passed to PlotTopologies.") fault_lines = shapelify_feature_lines(self.faults) gdf = gpd.GeoDataFrame({"geometry": fault_lines}, geometry="geometry") return gdf def plot_faults(self, ax, color='black', **kwargs): """Plot faults on a standard map projection. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. color : str, default=’black’ The colour of the trench lines. By default, it is set to black. **kwargs : Keyword arguments for parameters such as `alpha`, etc. for plotting trench geometries. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with faults plotted onto the chosen map projection. """ gdf = self.get_faults() return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs) def get_fracture_zones(self): """Create a geopandas.GeoDataFrame object containing geometries of reconstructed fracture zone lines. Notes ----- The `fracture_zones` needed to produce the GeoDataFrame are automatically constructed if the optional `time` parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed either when `PlotTopologies` is first called... gplot = gplately.PlotTopologies(..., time=100,...) or anytime afterwards, by setting: time = 100 #Ma gplot.time = time ...after which this function can be re-run. Once the `fracture_zones` are reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame. Returns ------- gdf : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `fracture_zones` geometry. Raises ------ ValueError If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct `fracture_zones` to the requested `time` and thus populate the GeoDataFrame. """ if self._time is None: raise ValueError("No fracture zones have been resolved. Set `PlotTopologies.time` to construct them.") if self.fracture_zones is None: raise ValueError("No fracture zones passed to PlotTopologies.") fracture_zone_lines = shapelify_feature_lines(self.fracture_zones) gdf = gpd.GeoDataFrame({"geometry": fracture_zone_lines}, geometry="geometry") return gdf def plot_fracture_zones(self, ax, color='black', **kwargs): """Plot fracture zones on a standard map projection. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. color : str, default=’black’ The colour of the trench lines. By default, it is set to black. **kwargs : Keyword arguments for parameters such as `alpha`, etc. for plotting trench geometries. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with fracture zones plotted onto the chosen map projection. """ gdf = self.get_fracture_zones() return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs) def get_inferred_paleo_boundaries(self): """Create a geopandas.GeoDataFrame object containing geometries of reconstructed inferred paleo boundary lines. Notes ----- The `inferred_paleo_boundaries` needed to produce the GeoDataFrame are automatically constructed if the optional `time` parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed either when `PlotTopologies` is first called... gplot = gplately.PlotTopologies(..., time=100,...) or anytime afterwards, by setting: time = 100 #Ma gplot.time = time ...after which this function can be re-run. Once the `inferred_paleo_boundaries` are reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame. Returns ------- gdf : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `inferred_paleo_boundaries` geometry. Raises ------ ValueError If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct `inferred_paleo_boundaries` to the requested `time` and thus populate the GeoDataFrame. """ if self._time is None: raise ValueError("No inferred paleo boundaries have been resolved. Set `PlotTopologies.time` to construct them.") if self.inferred_paleo_boundaries is None: raise ValueError("No inferred paleo boundaries passed to PlotTopologies.") inferred_paleo_boundary_lines = shapelify_feature_lines(self.inferred_paleo_boundaries) gdf = gpd.GeoDataFrame({"geometry": inferred_paleo_boundary_lines}, geometry="geometry") return gdf def plot_inferred_paleo_boundaries(self, ax, color='black', **kwargs): """Plot inferred paleo boundaries on a standard map projection. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. color : str, default=’black’ The colour of the trench lines. By default, it is set to black. **kwargs : Keyword arguments for parameters such as `alpha`, etc. for plotting trench geometries. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with inferred paleo boundaries plotted onto the chosen map projection. """ gdf = get_inferred_paleo_boundaries() return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs) def get_terrane_boundaries(self): """Create a geopandas.GeoDataFrame object containing geometries of reconstructed terrane boundary lines. Notes ----- The `terrane_boundaries` needed to produce the GeoDataFrame are automatically constructed if the optional `time` parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed either when `PlotTopologies` is first called... gplot = gplately.PlotTopologies(..., time=100,...) or anytime afterwards, by setting: time = 100 #Ma gplot.time = time ...after which this function can be re-run. Once the `terrane_boundaries` are reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame. Returns ------- gdf : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `terrane_boundaries` geometry. Raises ------ ValueError If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct `terrane_boundaries` to the requested `time` and thus populate the GeoDataFrame. """ if self._time is None: raise ValueError("No terrane boundaries have been resolved. Set `PlotTopologies.time` to construct them.") if self.terrane_boundaries is None: raise ValueError("No terrane boundaries passed to PlotTopologies.") terrane_boundary_lines = shapelify_feature_lines(self.terrane_boundaries) gdf = gpd.GeoDataFrame({"geometry": terrane_boundary_lines}, geometry="geometry") return gdf def plot_terrane_boundaries(self, ax, color='black', **kwargs): """Plot terrane boundaries on a standard map projection. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. color : str, default=’black’ The colour of the trench lines. By default, it is set to black. **kwargs : Keyword arguments for parameters such as `alpha`, etc. for plotting trench geometries. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with terrane boundaries plotted onto the chosen map projection. """ gdf = self.get_terrane_boundaries() return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs) def get_transitional_crusts(self): """Create a geopandas.GeoDataFrame object containing geometries of reconstructed transitional crust lines. Notes ----- The `transitional_crusts` needed to produce the GeoDataFrame are automatically constructed if the optional `time` parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed either when `PlotTopologies` is first called... gplot = gplately.PlotTopologies(..., time=100,...) or anytime afterwards, by setting: time = 100 #Ma gplot.time = time ...after which this function can be re-run. Once the `transitional_crusts` are reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame. Returns ------- gdf : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `transitional_crusts` geometry. Raises ------ ValueError If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct `transitional_crusts` to the requested `time` and thus populate the GeoDataFrame. """ if self._time is None: raise ValueError("No transitional crusts have been resolved. Set `PlotTopologies.time` to construct them.") if self.transitional_crusts is None: raise ValueError("No transitional crusts passed to PlotTopologies.") transitional_crust_lines = shapelify_feature_lines(self.transitional_crusts) gdf = gpd.GeoDataFrame({"geometry": transitional_crust_lines}, geometry="geometry") return gdf def plot_transitional_crusts(self, ax, color='black', **kwargs): """Plot transitional crust on a standard map projection. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. color : str, default=’black’ The colour of the trench lines. By default, it is set to black. **kwargs : Keyword arguments for parameters such as `alpha`, etc. for plotting trench geometries. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with transitional crust plotted onto the chosen map projection. """ gdf = self.get_transitional_crusts() return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs) def get_orogenic_belts(self): """Create a geopandas.GeoDataFrame object containing geometries of reconstructed orogenic belt lines. Notes ----- The `orogenic_belts` needed to produce the GeoDataFrame are automatically constructed if the optional `time` parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed either when `PlotTopologies` is first called... gplot = gplately.PlotTopologies(..., time=100,...) or anytime afterwards, by setting: time = 100 #Ma gplot.time = time ...after which this function can be re-run. Once the `orogenic_belts` are reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame. Returns ------- gdf : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `orogenic_belts` geometry. Raises ------ ValueError If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct `orogenic_belts` to the requested `time` and thus populate the GeoDataFrame. """ if self._time is None: raise ValueError("No orogenic belts have been resolved. Set `PlotTopologies.time` to construct them.") if self.orogenic_belts is None: raise ValueError("No orogenic belts passed to PlotTopologies.") orogenic_belt_lines = shapelify_feature_lines(self.orogenic_belts) gdf = gpd.GeoDataFrame({"geometry": orogenic_belt_lines}, geometry="geometry") return gdf def plot_orogenic_belts(self, ax, color='black', **kwargs): """Plot orogenic belts on a standard map projection. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. color : str, default=’black’ The colour of the trench lines. By default, it is set to black. **kwargs : Keyword arguments for parameters such as `alpha`, etc. for plotting trench geometries. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with orogenic belts plotted onto the chosen map projection. """ gdf = self.get_orogenic_belts() return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs) def get_sutures(self): """Create a geopandas.GeoDataFrame object containing geometries of reconstructed suture lines. Notes ----- The `sutures` needed to produce the GeoDataFrame are automatically constructed if the optional `time` parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed either when `PlotTopologies` is first called... gplot = gplately.PlotTopologies(..., time=100,...) or anytime afterwards, by setting: time = 100 #Ma gplot.time = time ...after which this function can be re-run. Once the `sutures` are reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame. Returns ------- gdf : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `sutures` geometry. Raises ------ ValueError If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct `sutures` to the requested `time` and thus populate the GeoDataFrame. """ if self._time is None: raise ValueError("No sutures have been resolved. Set `PlotTopologies.time` to construct them.") if self.sutures is None: raise ValueError("No sutures passed to PlotTopologies.") suture_lines = shapelify_feature_lines(self.sutures) gdf = gpd.GeoDataFrame({"geometry": suture_lines}, geometry="geometry") return gdf def plot_sutures(self, ax, color='black', **kwargs): """Plot sutures on a standard map projection. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. color : str, default=’black’ The colour of the trench lines. By default, it is set to black. **kwargs : Keyword arguments for parameters such as `alpha`, etc. for plotting trench geometries. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with sutures plotted onto the chosen map projection. """ gdf = self.get_sutures() return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs) def get_continental_crusts(self): """Create a geopandas.GeoDataFrame object containing geometries of reconstructed continental crust lines. Notes ----- The `continental_crusts` needed to produce the GeoDataFrame are automatically constructed if the optional `time` parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed either when `PlotTopologies` is first called... gplot = gplately.PlotTopologies(..., time=100,...) or anytime afterwards, by setting: time = 100 #Ma gplot.time = time ...after which this function can be re-run. Once the `continental_crusts` are reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame. Returns ------- gdf : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `continental_crusts` geometry. Raises ------ ValueError If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct `continental_crusts` to the requested `time` and thus populate the GeoDataFrame. """ if self._time is None: raise ValueError("No continental crust topologies have been resolved. Set `PlotTopologies.time` to construct them.") if self.continental_crusts is None: raise ValueError("No continental crust topologies passed to PlotTopologies.") continental_crust_lines = shapelify_feature_lines(self.continental_crusts) gdf = gpd.GeoDataFrame({"geometry": continental_crust_lines}, geometry="geometry") return gdf def plot_continental_crusts(self, ax, color='black', **kwargs): """Plot continental crust lines on a standard map projection. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. color : str, default=’black’ The colour of the trench lines. By default, it is set to black. **kwargs : Keyword arguments for parameters such as `alpha`, etc. for plotting trench geometries. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with continental crust lines plotted onto the chosen map projection. """ gdf = self.get_continental_crusts() return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs) def get_extended_continental_crusts(self): """Create a geopandas.GeoDataFrame object containing geometries of reconstructed extended continental crust lines. Notes ----- The `extended_continental_crusts` needed to produce the GeoDataFrame are automatically constructed if the optional `time` parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed either when `PlotTopologies` is first called... gplot = gplately.PlotTopologies(..., time=100,...) or anytime afterwards, by setting: time = 100 #Ma gplot.time = time ...after which this function can be re-run. Once the `extended_continental_crusts` are reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame. Returns ------- gdf : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `extended_continental_crusts` geometry. Raises ------ ValueError If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct `extended_continental_crusts` to the requested `time` and thus populate the GeoDataFrame. """ if self._time is None: raise ValueError("No extended continental crust topologies have been resolved. Set `PlotTopologies.time` to construct them.") if self.extended_continental_crusts is None: raise ValueError("No extended continental crust topologies passed to PlotTopologies.") extended_continental_crust_lines = shapelify_feature_lines(self.extended_continental_crusts) gdf = gpd.GeoDataFrame({"geometry": extended_continental_crust_lines}, geometry="geometry") return gdf def plot_extended_continental_crusts(self, ax, color='black', **kwargs): """Plot extended continental crust lines on a standard map projection. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. color : str, default=’black’ The colour of the trench lines. By default, it is set to black. **kwargs : Keyword arguments for parameters such as `alpha`, etc. for plotting trench geometries. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with extended continental crust lines plotted onto the chosen map projection. """ gdf = self.get_extended_continental_crusts() return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs) def get_passive_continental_boundaries(self): """Create a geopandas.GeoDataFrame object containing geometries of reconstructed passive continental boundary lines. Notes ----- The `passive_continental_boundaries` needed to produce the GeoDataFrame are automatically constructed if the optional `time` parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed either when `PlotTopologies` is first called... gplot = gplately.PlotTopologies(..., time=100,...) or anytime afterwards, by setting: time = 100 #Ma gplot.time = time ...after which this function can be re-run. Once the `passive_continental_boundaries` are reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame. Returns ------- gdf : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `passive_continental_boundaries` geometry. Raises ------ ValueError If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct `passive_continental_boundaries` to the requested `time` and thus populate the GeoDataFrame. """ if self._time is None: raise ValueError("No passive continental boundaries have been resolved. Set `PlotTopologies.time` to construct them.") if self.passive_continental_boundaries is None: raise ValueError("No passive continental boundaries passed to PlotTopologies.") passive_continental_boundary_lines = shapelify_feature_lines(self.passive_continental_boundaries) gdf = gpd.GeoDataFrame({"geometry": passive_continental_boundary_lines}, geometry="geometry") return gdf def plot_passive_continental_boundaries(self, ax, color='black', **kwargs): """Plot passive continental boundaries on a standard map projection. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. color : str, default=’black’ The colour of the trench lines. By default, it is set to black. **kwargs : Keyword arguments for parameters such as `alpha`, etc. for plotting trench geometries. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with passive continental boundaries plotted onto the chosen map projection. """ gdf = self.get_passive_continental_boundaries() return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs) def get_slab_edges(self): """Create a geopandas.GeoDataFrame object containing geometries of reconstructed slab edge lines. Notes ----- The `slab_edges` needed to produce the GeoDataFrame are automatically constructed if the optional `time` parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed either when `PlotTopologies` is first called... gplot = gplately.PlotTopologies(..., time=100,...) or anytime afterwards, by setting: time = 100 #Ma gplot.time = time ...after which this function can be re-run. Once the `slab_edges` are reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame. Returns ------- gdf : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `slab_edges` geometry. Raises ------ ValueError If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct `slab_edges` to the requested `time` and thus populate the GeoDataFrame. """ if self._time is None: raise ValueError("No slab edges have been resolved. Set `PlotTopologies.time` to construct them.") if self.slab_edges is None: raise ValueError("No slab edges passed to PlotTopologies.") slab_edge_lines = shapelify_feature_lines(self.slab_edges) gdf = gpd.GeoDataFrame({"geometry": slab_edge_lines}, geometry="geometry") return gdf def plot_slab_edges(self, ax, color='black', **kwargs): """Plot slab edges on a standard map projection. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. color : str, default=’black’ The colour of the trench lines. By default, it is set to black. **kwargs : Keyword arguments for parameters such as `alpha`, etc. for plotting trench geometries. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with slab edges plotted onto the chosen map projection. """ gdf = self.get_slab_edges() return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs) def get_misc_transforms(self): """Create a geopandas.GeoDataFrame object containing geometries of reconstructed misc transform lines. Notes ----- The `misc_transforms` needed to produce the GeoDataFrame are automatically constructed if the optional `time` parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed either when `PlotTopologies` is first called... gplot = gplately.PlotTopologies(..., time=100,...) or anytime afterwards, by setting: time = 100 #Ma gplot.time = time ...after which this function can be re-run. Once the `misc_transforms` are reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame. Returns ------- gdf : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `misc_transforms` geometry. Raises ------ ValueError If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct `misc_transforms` to the requested `time` and thus populate the GeoDataFrame. """ if self._time is None: raise ValueError("No miscellaneous transforms have been resolved. Set `PlotTopologies.time` to construct them.") if self.misc_transforms is None: raise ValueError("No miscellaneous transforms passed to PlotTopologies.") misc_transform_lines = shapelify_feature_lines(self.misc_transforms) gdf = gpd.GeoDataFrame({"geometry": misc_transform_lines}, geometry="geometry") return gdf def plot_misc_transforms(self, ax, color='black', **kwargs): """Plot miscellaneous transform boundaries on a standard map projection. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. color : str, default=’black’ The colour of the trench lines. By default, it is set to black. **kwargs : Keyword arguments for parameters such as `alpha`, etc. for plotting trench geometries. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with miscellaneous transform boundaries plotted onto the chosen map projection. """ gdf = self.get_misc_transforms() return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs) def get_unclassified_features(self): """Create a geopandas.GeoDataFrame object containing geometries of reconstructed unclassified feature lines. Notes ----- The `unclassified_features` needed to produce the GeoDataFrame are automatically constructed if the optional `time` parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed either when `PlotTopologies` is first called... gplot = gplately.PlotTopologies(..., time=100,...) or anytime afterwards, by setting: time = 100 #Ma gplot.time = time ...after which this function can be re-run. Once the `unclassified_features` are reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame. Returns ------- gdf : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `unclassified_features` geometry. Raises ------ ValueError If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct `unclassified_features` to the requested `time` and thus populate the GeoDataFrame. """ if self._time is None: raise ValueError("No unclassified features have been resolved. Set `PlotTopologies.time` to construct them.") if self.unclassified_features is None: raise ValueError("No unclassified features passed to PlotTopologies.") unclassified_feature_lines = shapelify_feature_lines(self.unclassified_features) gdf = gpd.GeoDataFrame({"geometry": unclassified_feature_lines}, geometry="geometry") return gdf def plot_unclassified_features(self, ax, color='black', **kwargs): """Plot GPML unclassified features on a standard map projection. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. color : str, default=’black’ The colour of the trench lines. By default, it is set to black. **kwargs : Keyword arguments for parameters such as `alpha`, etc. for plotting trench geometries. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with unclassified features plotted onto the chosen map projection. """ gdf = self.get_unclassified_features() return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs) def get_all_topologies(self): """Create a geopandas.GeoDataFrame object containing geometries of reconstructed unclassified feature lines. Notes ----- The `topologies` needed to produce the GeoDataFrame are automatically constructed if the optional `time` parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed either when `PlotTopologies` is first called... gplot = gplately.PlotTopologies(..., time=100,...) or anytime afterwards, by setting: time = 100 #Ma gplot.time = time ...after which this function can be re-run. Once the `topologies` are reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame. Returns ------- gdf : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `topologies` geometry. Raises ------ ValueError If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct `topologies` to the requested `time` and thus populate the GeoDataFrame. """ if self._time is None: raise ValueError("No topologies have been resolved. Set `PlotTopologies.time` to construct them.") if self.topologies is None: raise ValueError("No topologies passed to PlotTopologies.") all_topologies = shapelify_features(self.topologies) # get plate IDs and feature types to add to geodataframe plate_IDs = [] feature_types = [] feature_names = [] for topo in self.topologies: ft_type = topo.get_feature_type() plate_IDs.append(topo.get_reconstruction_plate_id()) feature_types.append(ft_type) feature_names.append(ft_type.get_name()) gdf = gpd.GeoDataFrame({"geometry": all_topologies, "reconstruction_plate_ID": plate_IDs, "feature_type": feature_types, "feature_name": feature_names}, geometry="geometry") return gdf def plot_all_topologies(self, ax, color='black', **kwargs): """Plot all topologies on a standard map projection. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. color : str, default=’black’ The colour of the trench lines. By default, it is set to black. **kwargs : Keyword arguments for parameters such as `alpha`, etc. for plotting trench geometries. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with unclassified features plotted onto the chosen map projection. """ gdf = self.get_all_topologies() return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs)Instance variables
var anchor_plate_id-
Anchor plate ID for reconstruction. Must be an integer >= 0.
Expand source code
@property def anchor_plate_id(self): """Anchor plate ID for reconstruction. Must be an integer >= 0.""" return self._anchor_plate_id var time-
The reconstruction time.
Expand source code
@property def time(self): """ The reconstruction time.""" return self._time
Methods
def get_all_topologies(self)-
Create a geopandas.GeoDataFrame object containing geometries of reconstructed unclassified feature lines.
Notes
The
topologiesneeded to produce the GeoDataFrame are automatically constructed if the optionaltimeparameter is passed to thePlotTopologiesobject before calling this function.timecan be passed either whenPlotTopologiesis first called…gplot = gplately.PlotTopologies(..., time=100,...)or anytime afterwards, by setting:
time = 100 #Ma gplot.time = time…after which this function can be re-run. Once the
topologiesare reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame.Returns
gdf:instanceof<geopandas.GeoDataFrame>- A pandas.DataFrame that has a column with
topologiesgeometry.
Raises
ValueError If the optional
timeparameter has not been passed toPlotTopologies. This is needed to constructtopologiesto the requestedtimeand thus populate the GeoDataFrame.Expand source code
def get_all_topologies(self): """Create a geopandas.GeoDataFrame object containing geometries of reconstructed unclassified feature lines. Notes ----- The `topologies` needed to produce the GeoDataFrame are automatically constructed if the optional `time` parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed either when `PlotTopologies` is first called... gplot = gplately.PlotTopologies(..., time=100,...) or anytime afterwards, by setting: time = 100 #Ma gplot.time = time ...after which this function can be re-run. Once the `topologies` are reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame. Returns ------- gdf : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `topologies` geometry. Raises ------ ValueError If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct `topologies` to the requested `time` and thus populate the GeoDataFrame. """ if self._time is None: raise ValueError("No topologies have been resolved. Set `PlotTopologies.time` to construct them.") if self.topologies is None: raise ValueError("No topologies passed to PlotTopologies.") all_topologies = shapelify_features(self.topologies) # get plate IDs and feature types to add to geodataframe plate_IDs = [] feature_types = [] feature_names = [] for topo in self.topologies: ft_type = topo.get_feature_type() plate_IDs.append(topo.get_reconstruction_plate_id()) feature_types.append(ft_type) feature_names.append(ft_type.get_name()) gdf = gpd.GeoDataFrame({"geometry": all_topologies, "reconstruction_plate_ID": plate_IDs, "feature_type": feature_types, "feature_name": feature_names}, geometry="geometry") return gdf def get_coastlines(self)-
Create a geopandas.GeoDataFrame object containing geometries of reconstructed coastline polygons.
Notes
The
coastlinesneeded to produce the GeoDataFrame are automatically constructed if the optionaltimeparameter is passed to thePlotTopologiesobject before calling this function.timecan be passed either whenPlotTopologiesis first called…gplot = gplately.PlotTopologies(..., time=100,...)or anytime afterwards, by setting:
time = 100 #Ma gplot.time = time…after which this function can be re-run. Once the
coastlinesare reconstructed, they are converted into Shapely polygons whose coordinates are passed to a geopandas GeoDataFrame.Returns
gdf:instanceof<geopandas.GeoDataFrame>- A pandas.DataFrame that has a column with
coastlinesgeometry.
Raises
ValueError If the optional
timeparameter has not been passed toPlotTopologies. This is needed to constructcoastlinesto the requestedtimeand thus populate the GeoDataFrame.Expand source code
def get_coastlines(self): """Create a geopandas.GeoDataFrame object containing geometries of reconstructed coastline polygons. Notes ----- The `coastlines` needed to produce the GeoDataFrame are automatically constructed if the optional `time` parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed either when `PlotTopologies` is first called... gplot = gplately.PlotTopologies(..., time=100,...) or anytime afterwards, by setting: time = 100 #Ma gplot.time = time ...after which this function can be re-run. Once the `coastlines` are reconstructed, they are converted into Shapely polygons whose coordinates are passed to a geopandas GeoDataFrame. Returns ------- gdf : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `coastlines` geometry. Raises ------ ValueError If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct `coastlines` to the requested `time` and thus populate the GeoDataFrame. """ if self._time is None: raise ValueError("No coastlines have been resolved. Set `PlotTopologies.time` to construct coastlines.") if self.coastlines is None: raise ValueError("Supply coastlines to PlotTopologies object") coastline_polygons = shapelify_feature_polygons(self.coastlines) gdf = gpd.GeoDataFrame({"geometry": coastline_polygons}, geometry="geometry") return gdf def get_continent_ocean_boundaries(self)-
Create a geopandas.GeoDataFrame object containing geometries of reconstructed continent-ocean boundary lines.
Notes
The
COBsneeded to produce the GeoDataFrame are automatically constructed if the optionaltimeparameter is passed to thePlotTopologiesobject before calling this function.timecan be passed either whenPlotTopologiesis first called…gplot = gplately.PlotTopologies(..., time=100,...)or anytime afterwards, by setting:
time = 100 #Ma gplot.time = time…after which this function can be re-run. Once the
COBsare reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame.Returns
gdf:instanceof<geopandas.GeoDataFrame>- A pandas.DataFrame that has a column with
COBsgeometry.
Raises
ValueError If the optional
timeparameter has not been passed toPlotTopologies. This is needed to constructCOBsto the requestedtimeand thus populate the GeoDataFrame.Expand source code
def get_continent_ocean_boundaries(self): """Create a geopandas.GeoDataFrame object containing geometries of reconstructed continent-ocean boundary lines. Notes ----- The `COBs` needed to produce the GeoDataFrame are automatically constructed if the optional `time` parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed either when `PlotTopologies` is first called... gplot = gplately.PlotTopologies(..., time=100,...) or anytime afterwards, by setting: time = 100 #Ma gplot.time = time ...after which this function can be re-run. Once the `COBs` are reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame. Returns ------- gdf : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `COBs` geometry. Raises ------ ValueError If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct `COBs` to the requested `time` and thus populate the GeoDataFrame. """ if self._time is None: raise ValueError("No geometries have been resolved. Set `PlotTopologies.time` to construct topologies.") if self.COBs is None: raise ValueError("Supply COBs to PlotTopologies object") COB_lines = shapelify_feature_lines(self.COBs) gdf = gpd.GeoDataFrame({"geometry": COB_lines}, geometry="geometry") return gdf def get_continental_crusts(self)-
Create a geopandas.GeoDataFrame object containing geometries of reconstructed continental crust lines.
Notes
The
continental_crustsneeded to produce the GeoDataFrame are automatically constructed if the optionaltimeparameter is passed to thePlotTopologiesobject before calling this function.timecan be passed either whenPlotTopologiesis first called…gplot = gplately.PlotTopologies(..., time=100,...)or anytime afterwards, by setting:
time = 100 #Ma gplot.time = time…after which this function can be re-run. Once the
continental_crustsare reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame.Returns
gdf:instanceof<geopandas.GeoDataFrame>- A pandas.DataFrame that has a column with
continental_crustsgeometry.
Raises
ValueError If the optional
timeparameter has not been passed toPlotTopologies. This is needed to constructcontinental_cruststo the requestedtimeand thus populate the GeoDataFrame.Expand source code
def get_continental_crusts(self): """Create a geopandas.GeoDataFrame object containing geometries of reconstructed continental crust lines. Notes ----- The `continental_crusts` needed to produce the GeoDataFrame are automatically constructed if the optional `time` parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed either when `PlotTopologies` is first called... gplot = gplately.PlotTopologies(..., time=100,...) or anytime afterwards, by setting: time = 100 #Ma gplot.time = time ...after which this function can be re-run. Once the `continental_crusts` are reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame. Returns ------- gdf : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `continental_crusts` geometry. Raises ------ ValueError If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct `continental_crusts` to the requested `time` and thus populate the GeoDataFrame. """ if self._time is None: raise ValueError("No continental crust topologies have been resolved. Set `PlotTopologies.time` to construct them.") if self.continental_crusts is None: raise ValueError("No continental crust topologies passed to PlotTopologies.") continental_crust_lines = shapelify_feature_lines(self.continental_crusts) gdf = gpd.GeoDataFrame({"geometry": continental_crust_lines}, geometry="geometry") return gdf def get_continental_rifts(self)-
Create a geopandas.GeoDataFrame object containing geometries of reconstructed contiental rift lines.
Notes
The
continental_riftsneeded to produce the GeoDataFrame are automatically constructed if the optionaltimeparameter is passed to thePlotTopologiesobject before calling this function.timecan be passed either whenPlotTopologiesis first called…gplot = gplately.PlotTopologies(..., time=100,...)or anytime afterwards, by setting:
time = 100 #Ma gplot.time = time…after which this function can be re-run. Once the
continental_riftsare reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame.Returns
gdf:instanceof<geopandas.GeoDataFrame>- A pandas.DataFrame that has a column with
continental_riftsgeometry.
Raises
ValueError If the optional
timeparameter has not been passed toPlotTopologies. This is needed to constructcontinental_riftsto the requestedtimeand thus populate the GeoDataFrame.Expand source code
def get_continental_rifts(self): """Create a geopandas.GeoDataFrame object containing geometries of reconstructed contiental rift lines. Notes ----- The `continental_rifts` needed to produce the GeoDataFrame are automatically constructed if the optional `time` parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed either when `PlotTopologies` is first called... gplot = gplately.PlotTopologies(..., time=100,...) or anytime afterwards, by setting: time = 100 #Ma gplot.time = time ...after which this function can be re-run. Once the `continental_rifts` are reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame. Returns ------- gdf : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `continental_rifts` geometry. Raises ------ ValueError If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct `continental_rifts` to the requested `time` and thus populate the GeoDataFrame. """ if self._time is None: raise ValueError("No continental rifts have been resolved. Set `PlotTopologies.time` to construct them.") if self.continental_rifts is None: raise ValueError("No continental rifts passed to PlotTopologies.") continental_rift_lines = shapelify_feature_lines(self.continental_rifts) gdf = gpd.GeoDataFrame({"geometry": continental_rift_lines}, geometry="geometry") return gdf def get_continents(self)-
Create a geopandas.GeoDataFrame object containing geometries of reconstructed continental polygons.
Notes
The
continentsneeded to produce the GeoDataFrame are automatically constructed if the optionaltimeparameter is passed to thePlotTopologiesobject before calling this function.timecan be passed either whenPlotTopologiesis first called…gplot = gplately.PlotTopologies(..., time=100,...)or anytime afterwards, by setting:
time = 100 #Ma gplot.time = time…after which this function can be re-run. Once the
continentsare reconstructed, they are converted into Shapely polygons whose coordinates are passed to a geopandas GeoDataFrame.Returns
gdf:instanceof<geopandas.GeoDataFrame>- A pandas.DataFrame that has a column with
continentsgeometry.
Raises
ValueError If the optional
timeparameter has not been passed toPlotTopologies. This is needed to constructcontinentsto the requestedtimeand thus populate the GeoDataFrame.Expand source code
def get_continents(self): """Create a geopandas.GeoDataFrame object containing geometries of reconstructed continental polygons. Notes ----- The `continents` needed to produce the GeoDataFrame are automatically constructed if the optional `time` parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed either when `PlotTopologies` is first called... gplot = gplately.PlotTopologies(..., time=100,...) or anytime afterwards, by setting: time = 100 #Ma gplot.time = time ...after which this function can be re-run. Once the `continents` are reconstructed, they are converted into Shapely polygons whose coordinates are passed to a geopandas GeoDataFrame. Returns ------- gdf : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `continents` geometry. Raises ------ ValueError If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct `continents` to the requested `time` and thus populate the GeoDataFrame. """ if self._time is None: raise ValueError("No continents have been resolved. Set `PlotTopologies.time` to construct continents.") if self.continents is None: raise ValueError("Supply continents to PlotTopologies object") continent_polygons = shapelify_feature_polygons(self.continents) gdf = gpd.GeoDataFrame({"geometry": continent_polygons}, geometry="geometry") return gdf def get_extended_continental_crusts(self)-
Create a geopandas.GeoDataFrame object containing geometries of reconstructed extended continental crust lines.
Notes
The
extended_continental_crustsneeded to produce the GeoDataFrame are automatically constructed if the optionaltimeparameter is passed to thePlotTopologiesobject before calling this function.timecan be passed either whenPlotTopologiesis first called…gplot = gplately.PlotTopologies(..., time=100,...)or anytime afterwards, by setting:
time = 100 #Ma gplot.time = time…after which this function can be re-run. Once the
extended_continental_crustsare reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame.Returns
gdf:instanceof<geopandas.GeoDataFrame>- A pandas.DataFrame that has a column with
extended_continental_crustsgeometry.
Raises
ValueError If the optional
timeparameter has not been passed toPlotTopologies. This is needed to constructextended_continental_cruststo the requestedtimeand thus populate the GeoDataFrame.Expand source code
def get_extended_continental_crusts(self): """Create a geopandas.GeoDataFrame object containing geometries of reconstructed extended continental crust lines. Notes ----- The `extended_continental_crusts` needed to produce the GeoDataFrame are automatically constructed if the optional `time` parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed either when `PlotTopologies` is first called... gplot = gplately.PlotTopologies(..., time=100,...) or anytime afterwards, by setting: time = 100 #Ma gplot.time = time ...after which this function can be re-run. Once the `extended_continental_crusts` are reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame. Returns ------- gdf : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `extended_continental_crusts` geometry. Raises ------ ValueError If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct `extended_continental_crusts` to the requested `time` and thus populate the GeoDataFrame. """ if self._time is None: raise ValueError("No extended continental crust topologies have been resolved. Set `PlotTopologies.time` to construct them.") if self.extended_continental_crusts is None: raise ValueError("No extended continental crust topologies passed to PlotTopologies.") extended_continental_crust_lines = shapelify_feature_lines(self.extended_continental_crusts) gdf = gpd.GeoDataFrame({"geometry": extended_continental_crust_lines}, geometry="geometry") return gdf def get_faults(self)-
Create a geopandas.GeoDataFrame object containing geometries of reconstructed fault lines.
Notes
The
faultsneeded to produce the GeoDataFrame are automatically constructed if the optionaltimeparameter is passed to thePlotTopologiesobject before calling this function.timecan be passed either whenPlotTopologiesis first called…gplot = gplately.PlotTopologies(..., time=100,...)or anytime afterwards, by setting:
time = 100 #Ma gplot.time = time…after which this function can be re-run. Once the
faultsare reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame.Returns
gdf:instanceof<geopandas.GeoDataFrame>- A pandas.DataFrame that has a column with
faultsgeometry.
Raises
ValueError If the optional
timeparameter has not been passed toPlotTopologies. This is needed to constructfaultsto the requestedtimeand thus populate the GeoDataFrame.Expand source code
def get_faults(self): """Create a geopandas.GeoDataFrame object containing geometries of reconstructed fault lines. Notes ----- The `faults` needed to produce the GeoDataFrame are automatically constructed if the optional `time` parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed either when `PlotTopologies` is first called... gplot = gplately.PlotTopologies(..., time=100,...) or anytime afterwards, by setting: time = 100 #Ma gplot.time = time ...after which this function can be re-run. Once the `faults` are reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame. Returns ------- gdf : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `faults` geometry. Raises ------ ValueError If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct `faults` to the requested `time` and thus populate the GeoDataFrame. """ if self._time is None: raise ValueError("No faults have been resolved. Set `PlotTopologies.time` to construct them.") if self.faults is None: raise ValueError("No faults passed to PlotTopologies.") fault_lines = shapelify_feature_lines(self.faults) gdf = gpd.GeoDataFrame({"geometry": fault_lines}, geometry="geometry") return gdf def get_feature(self, feature)-
Create a geopandas.GeoDataFrame object containing geometries of reconstructed features.
Notes
The feature needed to produce the GeoDataFrame should already be constructed to a
time. This function converts the feature into a set of Shapely geometries whose coordinates are passed to a geopandas GeoDataFrame.Parameters
feature:instanceof<pygplates.Feature>- A feature reconstructed to
time.
Returns
gdf:instanceof<geopandas.GeoDataFrame>- A pandas.DataFrame that has a column with
featuregeometries.
Expand source code
def get_feature(self, feature): """Create a geopandas.GeoDataFrame object containing geometries of reconstructed features. Notes ----- The feature needed to produce the GeoDataFrame should already be constructed to a `time`. This function converts the feature into a set of Shapely geometries whose coordinates are passed to a geopandas GeoDataFrame. Parameters ---------- feature : instance of <pygplates.Feature> A feature reconstructed to `time`. Returns ------- gdf : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `feature` geometries. """ shp = shapelify_features(feature) gdf = gpd.GeoDataFrame({'geometry': shp}, geometry='geometry') return gdf def get_fracture_zones(self)-
Create a geopandas.GeoDataFrame object containing geometries of reconstructed fracture zone lines.
Notes
The
fracture_zonesneeded to produce the GeoDataFrame are automatically constructed if the optionaltimeparameter is passed to thePlotTopologiesobject before calling this function.timecan be passed either whenPlotTopologiesis first called…gplot = gplately.PlotTopologies(..., time=100,...)or anytime afterwards, by setting:
time = 100 #Ma gplot.time = time…after which this function can be re-run. Once the
fracture_zonesare reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame.Returns
gdf:instanceof<geopandas.GeoDataFrame>- A pandas.DataFrame that has a column with
fracture_zonesgeometry.
Raises
ValueError If the optional
timeparameter has not been passed toPlotTopologies. This is needed to constructfracture_zonesto the requestedtimeand thus populate the GeoDataFrame.Expand source code
def get_fracture_zones(self): """Create a geopandas.GeoDataFrame object containing geometries of reconstructed fracture zone lines. Notes ----- The `fracture_zones` needed to produce the GeoDataFrame are automatically constructed if the optional `time` parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed either when `PlotTopologies` is first called... gplot = gplately.PlotTopologies(..., time=100,...) or anytime afterwards, by setting: time = 100 #Ma gplot.time = time ...after which this function can be re-run. Once the `fracture_zones` are reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame. Returns ------- gdf : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `fracture_zones` geometry. Raises ------ ValueError If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct `fracture_zones` to the requested `time` and thus populate the GeoDataFrame. """ if self._time is None: raise ValueError("No fracture zones have been resolved. Set `PlotTopologies.time` to construct them.") if self.fracture_zones is None: raise ValueError("No fracture zones passed to PlotTopologies.") fracture_zone_lines = shapelify_feature_lines(self.fracture_zones) gdf = gpd.GeoDataFrame({"geometry": fracture_zone_lines}, geometry="geometry") return gdf def get_inferred_paleo_boundaries(self)-
Create a geopandas.GeoDataFrame object containing geometries of reconstructed inferred paleo boundary lines.
Notes
The
inferred_paleo_boundariesneeded to produce the GeoDataFrame are automatically constructed if the optionaltimeparameter is passed to thePlotTopologiesobject before calling this function.timecan be passed either whenPlotTopologiesis first called…gplot = gplately.PlotTopologies(..., time=100,...)or anytime afterwards, by setting:
time = 100 #Ma gplot.time = time…after which this function can be re-run. Once the
inferred_paleo_boundariesare reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame.Returns
gdf:instanceof<geopandas.GeoDataFrame>- A pandas.DataFrame that has a column with
inferred_paleo_boundariesgeometry.
Raises
ValueError If the optional
timeparameter has not been passed toPlotTopologies. This is needed to constructinferred_paleo_boundariesto the requestedtimeand thus populate the GeoDataFrame.Expand source code
def get_inferred_paleo_boundaries(self): """Create a geopandas.GeoDataFrame object containing geometries of reconstructed inferred paleo boundary lines. Notes ----- The `inferred_paleo_boundaries` needed to produce the GeoDataFrame are automatically constructed if the optional `time` parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed either when `PlotTopologies` is first called... gplot = gplately.PlotTopologies(..., time=100,...) or anytime afterwards, by setting: time = 100 #Ma gplot.time = time ...after which this function can be re-run. Once the `inferred_paleo_boundaries` are reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame. Returns ------- gdf : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `inferred_paleo_boundaries` geometry. Raises ------ ValueError If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct `inferred_paleo_boundaries` to the requested `time` and thus populate the GeoDataFrame. """ if self._time is None: raise ValueError("No inferred paleo boundaries have been resolved. Set `PlotTopologies.time` to construct them.") if self.inferred_paleo_boundaries is None: raise ValueError("No inferred paleo boundaries passed to PlotTopologies.") inferred_paleo_boundary_lines = shapelify_feature_lines(self.inferred_paleo_boundaries) gdf = gpd.GeoDataFrame({"geometry": inferred_paleo_boundary_lines}, geometry="geometry") return gdf def get_misc_boundaries(self)-
Create a geopandas.GeoDataFrame object containing geometries of other reconstructed lines.
Notes
The
othergeometries needed to produce the GeoDataFrame are automatically constructed if the optionaltimeparameter is passed to thePlotTopologiesobject before calling this function.timecan be passed either whenPlotTopologiesis first called…gplot = gplately.PlotTopologies(..., time=100,...)or anytime afterwards, by setting:
time = 100 #Ma gplot.time = time…after which this function can be re-run. Once the
othergeometries are reconstructed, they are converted into Shapely features whose coordinates are passed to a geopandas GeoDataFrame.Returns
gdf:instanceof<geopandas.GeoDataFrame>- A pandas.DataFrame that has a column with
othergeometry.
Raises
ValueError If the optional
timeparameter has not been passed toPlotTopologies. This is needed to constructothergeometries to the requestedtimeand thus populate the GeoDataFrame.Expand source code
def get_misc_boundaries(self): """Create a geopandas.GeoDataFrame object containing geometries of other reconstructed lines. Notes ----- The `other` geometries needed to produce the GeoDataFrame are automatically constructed if the optional `time` parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed either when `PlotTopologies` is first called... gplot = gplately.PlotTopologies(..., time=100,...) or anytime afterwards, by setting: time = 100 #Ma gplot.time = time ...after which this function can be re-run. Once the `other` geometries are reconstructed, they are converted into Shapely features whose coordinates are passed to a geopandas GeoDataFrame. Returns ------- gdf : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `other` geometry. Raises ------ ValueError If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct `other` geometries to the requested `time` and thus populate the GeoDataFrame. """ if self._time is None: raise ValueError("No miscellaneous topologies have been resolved. Set `PlotTopologies.time` to construct them.") if self.other is None: raise ValueError("No miscellaneous topologies passed to PlotTopologies.") lines = shapelify_features(self.other) gdf = gpd.GeoDataFrame({"geometry": lines}, geometry="geometry") return gdf def get_misc_transforms(self)-
Create a geopandas.GeoDataFrame object containing geometries of reconstructed misc transform lines.
Notes
The
misc_transformsneeded to produce the GeoDataFrame are automatically constructed if the optionaltimeparameter is passed to thePlotTopologiesobject before calling this function.timecan be passed either whenPlotTopologiesis first called…gplot = gplately.PlotTopologies(..., time=100,...)or anytime afterwards, by setting:
time = 100 #Ma gplot.time = time…after which this function can be re-run. Once the
misc_transformsare reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame.Returns
gdf:instanceof<geopandas.GeoDataFrame>- A pandas.DataFrame that has a column with
misc_transformsgeometry.
Raises
ValueError If the optional
timeparameter has not been passed toPlotTopologies. This is needed to constructmisc_transformsto the requestedtimeand thus populate the GeoDataFrame.Expand source code
def get_misc_transforms(self): """Create a geopandas.GeoDataFrame object containing geometries of reconstructed misc transform lines. Notes ----- The `misc_transforms` needed to produce the GeoDataFrame are automatically constructed if the optional `time` parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed either when `PlotTopologies` is first called... gplot = gplately.PlotTopologies(..., time=100,...) or anytime afterwards, by setting: time = 100 #Ma gplot.time = time ...after which this function can be re-run. Once the `misc_transforms` are reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame. Returns ------- gdf : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `misc_transforms` geometry. Raises ------ ValueError If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct `misc_transforms` to the requested `time` and thus populate the GeoDataFrame. """ if self._time is None: raise ValueError("No miscellaneous transforms have been resolved. Set `PlotTopologies.time` to construct them.") if self.misc_transforms is None: raise ValueError("No miscellaneous transforms passed to PlotTopologies.") misc_transform_lines = shapelify_feature_lines(self.misc_transforms) gdf = gpd.GeoDataFrame({"geometry": misc_transform_lines}, geometry="geometry") return gdf def get_orogenic_belts(self)-
Create a geopandas.GeoDataFrame object containing geometries of reconstructed orogenic belt lines.
Notes
The
orogenic_beltsneeded to produce the GeoDataFrame are automatically constructed if the optionaltimeparameter is passed to thePlotTopologiesobject before calling this function.timecan be passed either whenPlotTopologiesis first called…gplot = gplately.PlotTopologies(..., time=100,...)or anytime afterwards, by setting:
time = 100 #Ma gplot.time = time…after which this function can be re-run. Once the
orogenic_beltsare reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame.Returns
gdf:instanceof<geopandas.GeoDataFrame>- A pandas.DataFrame that has a column with
orogenic_beltsgeometry.
Raises
ValueError If the optional
timeparameter has not been passed toPlotTopologies. This is needed to constructorogenic_beltsto the requestedtimeand thus populate the GeoDataFrame.Expand source code
def get_orogenic_belts(self): """Create a geopandas.GeoDataFrame object containing geometries of reconstructed orogenic belt lines. Notes ----- The `orogenic_belts` needed to produce the GeoDataFrame are automatically constructed if the optional `time` parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed either when `PlotTopologies` is first called... gplot = gplately.PlotTopologies(..., time=100,...) or anytime afterwards, by setting: time = 100 #Ma gplot.time = time ...after which this function can be re-run. Once the `orogenic_belts` are reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame. Returns ------- gdf : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `orogenic_belts` geometry. Raises ------ ValueError If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct `orogenic_belts` to the requested `time` and thus populate the GeoDataFrame. """ if self._time is None: raise ValueError("No orogenic belts have been resolved. Set `PlotTopologies.time` to construct them.") if self.orogenic_belts is None: raise ValueError("No orogenic belts passed to PlotTopologies.") orogenic_belt_lines = shapelify_feature_lines(self.orogenic_belts) gdf = gpd.GeoDataFrame({"geometry": orogenic_belt_lines}, geometry="geometry") return gdf def get_passive_continental_boundaries(self)-
Create a geopandas.GeoDataFrame object containing geometries of reconstructed passive continental boundary lines.
Notes
The
passive_continental_boundariesneeded to produce the GeoDataFrame are automatically constructed if the optionaltimeparameter is passed to thePlotTopologiesobject before calling this function.timecan be passed either whenPlotTopologiesis first called…gplot = gplately.PlotTopologies(..., time=100,...)or anytime afterwards, by setting:
time = 100 #Ma gplot.time = time…after which this function can be re-run. Once the
passive_continental_boundariesare reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame.Returns
gdf:instanceof<geopandas.GeoDataFrame>- A pandas.DataFrame that has a column with
passive_continental_boundariesgeometry.
Raises
ValueError If the optional
timeparameter has not been passed toPlotTopologies. This is needed to constructpassive_continental_boundariesto the requestedtimeand thus populate the GeoDataFrame.Expand source code
def get_passive_continental_boundaries(self): """Create a geopandas.GeoDataFrame object containing geometries of reconstructed passive continental boundary lines. Notes ----- The `passive_continental_boundaries` needed to produce the GeoDataFrame are automatically constructed if the optional `time` parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed either when `PlotTopologies` is first called... gplot = gplately.PlotTopologies(..., time=100,...) or anytime afterwards, by setting: time = 100 #Ma gplot.time = time ...after which this function can be re-run. Once the `passive_continental_boundaries` are reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame. Returns ------- gdf : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `passive_continental_boundaries` geometry. Raises ------ ValueError If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct `passive_continental_boundaries` to the requested `time` and thus populate the GeoDataFrame. """ if self._time is None: raise ValueError("No passive continental boundaries have been resolved. Set `PlotTopologies.time` to construct them.") if self.passive_continental_boundaries is None: raise ValueError("No passive continental boundaries passed to PlotTopologies.") passive_continental_boundary_lines = shapelify_feature_lines(self.passive_continental_boundaries) gdf = gpd.GeoDataFrame({"geometry": passive_continental_boundary_lines}, geometry="geometry") return gdf def get_ridges(self)-
Create a geopandas.GeoDataFrame object containing geometries of reconstructed ridge lines.
Notes
The
ridgesneeded to produce the GeoDataFrame are automatically constructed if the optionaltimeparameter is passed to thePlotTopologiesobject before calling this function.timecan be passed either whenPlotTopologiesis first called…gplot = gplately.PlotTopologies(..., time=100,...)or anytime afterwards, by setting:
time = 100 #Ma gplot.time = time…after which this function can be re-run. Once the
ridgesare reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame.Returns
gdf:instanceof<geopandas.GeoDataFrame>- A pandas.DataFrame that has a column with
ridgesgeometry.
Raises
ValueError If the optional
timeparameter has not been passed toPlotTopologies. This is needed to constructridgesto the requestedtimeand thus populate the GeoDataFrame.Expand source code
def get_ridges(self): """Create a geopandas.GeoDataFrame object containing geometries of reconstructed ridge lines. Notes ----- The `ridges` needed to produce the GeoDataFrame are automatically constructed if the optional `time` parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed either when `PlotTopologies` is first called... gplot = gplately.PlotTopologies(..., time=100,...) or anytime afterwards, by setting: time = 100 #Ma gplot.time = time ...after which this function can be re-run. Once the `ridges` are reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame. Returns ------- gdf : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `ridges` geometry. Raises ------ ValueError If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct `ridges` to the requested `time` and thus populate the GeoDataFrame. """ if self._time is None: raise ValueError("No ridges have been resolved. Set `PlotTopologies.time` to construct ridges.") if self.ridges is None: raise ValueError("No ridge topologies passed to PlotTopologies.") ridge_lines = shapelify_feature_lines(self.ridges) gdf = gpd.GeoDataFrame({"geometry": ridge_lines}, geometry="geometry") return gdf def get_ridges_and_transforms(self)-
Create a geopandas.GeoDataFrame object containing geometries of reconstructed ridge and transform lines.
Notes
The
ridge_transformsneeded to produce the GeoDataFrame are automatically constructed if the optionaltimeparameter is passed to thePlotTopologiesobject before calling this function.timecan be passed either whenPlotTopologiesis first called…gplot = gplately.PlotTopologies(..., time=100,...)or anytime afterwards, by setting:
time = 100 #Ma gplot.time = time…after which this function can be re-run. Once the
ridge_transformsare reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame.Returns
gdf:instanceof<geopandas.GeoDataFrame>- A pandas.DataFrame that has a column with
ridgesgeometry.
Raises
ValueError If the optional
timeparameter has not been passed toPlotTopologies. This is needed to constructridge_transformsto the requestedtimeand thus populate the GeoDataFrame.Expand source code
def get_ridges_and_transforms(self): """Create a geopandas.GeoDataFrame object containing geometries of reconstructed ridge and transform lines. Notes ----- The `ridge_transforms` needed to produce the GeoDataFrame are automatically constructed if the optional `time` parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed either when `PlotTopologies` is first called... gplot = gplately.PlotTopologies(..., time=100,...) or anytime afterwards, by setting: time = 100 #Ma gplot.time = time ...after which this function can be re-run. Once the `ridge_transforms` are reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame. Returns ------- gdf : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `ridges` geometry. Raises ------ ValueError If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct `ridge_transforms` to the requested `time` and thus populate the GeoDataFrame. """ if self._time is None: raise ValueError("No ridges and transforms have been resolved. Set `PlotTopologies.time` to construct ridges and transforms.") if self.ridge_transforms is None: raise ValueError("No ridge and transform topologies passed to PlotTopologies.") ridge_transform_lines = shapelify_feature_lines(self.ridge_transforms) gdf = gpd.GeoDataFrame({"geometry": ridge_transform_lines}, geometry="geometry") return gdf def get_slab_edges(self)-
Create a geopandas.GeoDataFrame object containing geometries of reconstructed slab edge lines.
Notes
The
slab_edgesneeded to produce the GeoDataFrame are automatically constructed if the optionaltimeparameter is passed to thePlotTopologiesobject before calling this function.timecan be passed either whenPlotTopologiesis first called…gplot = gplately.PlotTopologies(..., time=100,...)or anytime afterwards, by setting:
time = 100 #Ma gplot.time = time…after which this function can be re-run. Once the
slab_edgesare reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame.Returns
gdf:instanceof<geopandas.GeoDataFrame>- A pandas.DataFrame that has a column with
slab_edgesgeometry.
Raises
ValueError If the optional
timeparameter has not been passed toPlotTopologies. This is needed to constructslab_edgesto the requestedtimeand thus populate the GeoDataFrame.Expand source code
def get_slab_edges(self): """Create a geopandas.GeoDataFrame object containing geometries of reconstructed slab edge lines. Notes ----- The `slab_edges` needed to produce the GeoDataFrame are automatically constructed if the optional `time` parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed either when `PlotTopologies` is first called... gplot = gplately.PlotTopologies(..., time=100,...) or anytime afterwards, by setting: time = 100 #Ma gplot.time = time ...after which this function can be re-run. Once the `slab_edges` are reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame. Returns ------- gdf : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `slab_edges` geometry. Raises ------ ValueError If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct `slab_edges` to the requested `time` and thus populate the GeoDataFrame. """ if self._time is None: raise ValueError("No slab edges have been resolved. Set `PlotTopologies.time` to construct them.") if self.slab_edges is None: raise ValueError("No slab edges passed to PlotTopologies.") slab_edge_lines = shapelify_feature_lines(self.slab_edges) gdf = gpd.GeoDataFrame({"geometry": slab_edge_lines}, geometry="geometry") return gdf def get_subduction_direction(self)-
Create a geopandas.GeoDataFrame object containing geometries of trench directions.
Notes
The
trench_leftandtrench_rightgeometries needed to produce the GeoDataFrame are automatically constructed if the optionaltimeparameter is passed to thePlotTopologiesobject before calling this function.timecan be passed either whenPlotTopologiesis first called…gplot = gplately.PlotTopologies(..., time=100,...)or anytime afterwards, by setting:
time = 100 #Ma gplot.time = time…after which this function can be re-run. Once the
othergeometries are reconstructed, they are converted into Shapely features whose coordinates are passed to a geopandas GeoDataFrame.Returns
gdf_left:instanceof<geopandas.GeoDataFrame>- A pandas.DataFrame that has a column with
trench_leftgeometry. gdf_right:instanceof<geopandas.GeoDataFrame>- A pandas.DataFrame that has a column with
trench_rightgeometry.
Raises
ValueError If the optional
timeparameter has not been passed toPlotTopologies. This is needed to constructtrench_leftortrench_rightgeometries to the requestedtimeand thus populate the GeoDataFrame.Expand source code
def get_subduction_direction(self): """Create a geopandas.GeoDataFrame object containing geometries of trench directions. Notes ----- The `trench_left` and `trench_right` geometries needed to produce the GeoDataFrame are automatically constructed if the optional `time` parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed either when `PlotTopologies` is first called... gplot = gplately.PlotTopologies(..., time=100,...) or anytime afterwards, by setting: time = 100 #Ma gplot.time = time ...after which this function can be re-run. Once the `other` geometries are reconstructed, they are converted into Shapely features whose coordinates are passed to a geopandas GeoDataFrame. Returns ------- gdf_left : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `trench_left` geometry. gdf_right : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `trench_right` geometry. Raises ------ ValueError If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct `trench_left` or `trench_right` geometries to the requested `time` and thus populate the GeoDataFrame. """ if self._time is None: raise ValueError("No miscellaneous topologies have been resolved. Set `PlotTopologies.time` to construct them.") if self.trench_left is None or self.trench_right is None: raise ValueError("No trench_left or trench_right topologies passed to PlotTopologies.") trench_left_features = shapelify_feature_lines(self.trench_left) trench_right_features = shapelify_feature_lines(self.trench_right) gdf_left = gpd.GeoDataFrame({"geometry": trench_left_features}, geometry="geometry") gdf_right = gpd.GeoDataFrame({"geometry": trench_right_features}, geometry="geometry") return gdf_left, gdf_right def get_sutures(self)-
Create a geopandas.GeoDataFrame object containing geometries of reconstructed suture lines.
Notes
The
suturesneeded to produce the GeoDataFrame are automatically constructed if the optionaltimeparameter is passed to thePlotTopologiesobject before calling this function.timecan be passed either whenPlotTopologiesis first called…gplot = gplately.PlotTopologies(..., time=100,...)or anytime afterwards, by setting:
time = 100 #Ma gplot.time = time…after which this function can be re-run. Once the
suturesare reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame.Returns
gdf:instanceof<geopandas.GeoDataFrame>- A pandas.DataFrame that has a column with
suturesgeometry.
Raises
ValueError If the optional
timeparameter has not been passed toPlotTopologies. This is needed to constructsuturesto the requestedtimeand thus populate the GeoDataFrame.Expand source code
def get_sutures(self): """Create a geopandas.GeoDataFrame object containing geometries of reconstructed suture lines. Notes ----- The `sutures` needed to produce the GeoDataFrame are automatically constructed if the optional `time` parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed either when `PlotTopologies` is first called... gplot = gplately.PlotTopologies(..., time=100,...) or anytime afterwards, by setting: time = 100 #Ma gplot.time = time ...after which this function can be re-run. Once the `sutures` are reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame. Returns ------- gdf : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `sutures` geometry. Raises ------ ValueError If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct `sutures` to the requested `time` and thus populate the GeoDataFrame. """ if self._time is None: raise ValueError("No sutures have been resolved. Set `PlotTopologies.time` to construct them.") if self.sutures is None: raise ValueError("No sutures passed to PlotTopologies.") suture_lines = shapelify_feature_lines(self.sutures) gdf = gpd.GeoDataFrame({"geometry": suture_lines}, geometry="geometry") return gdf def get_terrane_boundaries(self)-
Create a geopandas.GeoDataFrame object containing geometries of reconstructed terrane boundary lines.
Notes
The
terrane_boundariesneeded to produce the GeoDataFrame are automatically constructed if the optionaltimeparameter is passed to thePlotTopologiesobject before calling this function.timecan be passed either whenPlotTopologiesis first called…gplot = gplately.PlotTopologies(..., time=100,...)or anytime afterwards, by setting:
time = 100 #Ma gplot.time = time…after which this function can be re-run. Once the
terrane_boundariesare reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame.Returns
gdf:instanceof<geopandas.GeoDataFrame>- A pandas.DataFrame that has a column with
terrane_boundariesgeometry.
Raises
ValueError If the optional
timeparameter has not been passed toPlotTopologies. This is needed to constructterrane_boundariesto the requestedtimeand thus populate the GeoDataFrame.Expand source code
def get_terrane_boundaries(self): """Create a geopandas.GeoDataFrame object containing geometries of reconstructed terrane boundary lines. Notes ----- The `terrane_boundaries` needed to produce the GeoDataFrame are automatically constructed if the optional `time` parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed either when `PlotTopologies` is first called... gplot = gplately.PlotTopologies(..., time=100,...) or anytime afterwards, by setting: time = 100 #Ma gplot.time = time ...after which this function can be re-run. Once the `terrane_boundaries` are reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame. Returns ------- gdf : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `terrane_boundaries` geometry. Raises ------ ValueError If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct `terrane_boundaries` to the requested `time` and thus populate the GeoDataFrame. """ if self._time is None: raise ValueError("No terrane boundaries have been resolved. Set `PlotTopologies.time` to construct them.") if self.terrane_boundaries is None: raise ValueError("No terrane boundaries passed to PlotTopologies.") terrane_boundary_lines = shapelify_feature_lines(self.terrane_boundaries) gdf = gpd.GeoDataFrame({"geometry": terrane_boundary_lines}, geometry="geometry") return gdf def get_transforms(self)-
Create a geopandas.GeoDataFrame object containing geometries of reconstructed transform lines.
Notes
The
transformsneeded to produce the GeoDataFrame are automatically constructed if the optionaltimeparameter is passed to thePlotTopologiesobject before calling this function.timecan be passed either whenPlotTopologiesis first called…gplot = gplately.PlotTopologies(..., time=100,...)or anytime afterwards, by setting:
time = 100 #Ma gplot.time = time…after which this function can be re-run. Once the
transformsare reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame.Returns
gdf:instanceof<geopandas.GeoDataFrame>- A pandas.DataFrame that has a column with
transformsgeometry.
Raises
ValueError If the optional
timeparameter has not been passed toPlotTopologies. This is needed to constructtransformsto the requestedtimeand thus populate the GeoDataFrame.Expand source code
def get_transforms(self): """Create a geopandas.GeoDataFrame object containing geometries of reconstructed transform lines. Notes ----- The `transforms` needed to produce the GeoDataFrame are automatically constructed if the optional `time` parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed either when `PlotTopologies` is first called... gplot = gplately.PlotTopologies(..., time=100,...) or anytime afterwards, by setting: time = 100 #Ma gplot.time = time ...after which this function can be re-run. Once the `transforms` are reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame. Returns ------- gdf : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `transforms` geometry. Raises ------ ValueError If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct `transforms` to the requested `time` and thus populate the GeoDataFrame. """ if self._time is None: raise ValueError("No transforms have been resolved. Set `PlotTopologies.time` to construct transforms.") if self.transforms is None: raise ValueError("No transform topologies passed to PlotTopologies.") transform_lines = shapelify_feature_lines(self.transforms) gdf = gpd.GeoDataFrame({"geometry": transform_lines}, geometry="geometry") return gdf def get_transitional_crusts(self)-
Create a geopandas.GeoDataFrame object containing geometries of reconstructed transitional crust lines.
Notes
The
transitional_crustsneeded to produce the GeoDataFrame are automatically constructed if the optionaltimeparameter is passed to thePlotTopologiesobject before calling this function.timecan be passed either whenPlotTopologiesis first called…gplot = gplately.PlotTopologies(..., time=100,...)or anytime afterwards, by setting:
time = 100 #Ma gplot.time = time…after which this function can be re-run. Once the
transitional_crustsare reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame.Returns
gdf:instanceof<geopandas.GeoDataFrame>- A pandas.DataFrame that has a column with
transitional_crustsgeometry.
Raises
ValueError If the optional
timeparameter has not been passed toPlotTopologies. This is needed to constructtransitional_cruststo the requestedtimeand thus populate the GeoDataFrame.Expand source code
def get_transitional_crusts(self): """Create a geopandas.GeoDataFrame object containing geometries of reconstructed transitional crust lines. Notes ----- The `transitional_crusts` needed to produce the GeoDataFrame are automatically constructed if the optional `time` parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed either when `PlotTopologies` is first called... gplot = gplately.PlotTopologies(..., time=100,...) or anytime afterwards, by setting: time = 100 #Ma gplot.time = time ...after which this function can be re-run. Once the `transitional_crusts` are reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame. Returns ------- gdf : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `transitional_crusts` geometry. Raises ------ ValueError If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct `transitional_crusts` to the requested `time` and thus populate the GeoDataFrame. """ if self._time is None: raise ValueError("No transitional crusts have been resolved. Set `PlotTopologies.time` to construct them.") if self.transitional_crusts is None: raise ValueError("No transitional crusts passed to PlotTopologies.") transitional_crust_lines = shapelify_feature_lines(self.transitional_crusts) gdf = gpd.GeoDataFrame({"geometry": transitional_crust_lines}, geometry="geometry") return gdf def get_trenches(self)-
Create a geopandas.GeoDataFrame object containing geometries of reconstructed trench lines.
Notes
The
trenchesneeded to produce the GeoDataFrame are automatically constructed if the optionaltimeparameter is passed to thePlotTopologiesobject before calling this function.timecan be passed either whenPlotTopologiesis first called…gplot = gplately.PlotTopologies(..., time=100,...)or anytime afterwards, by setting:
time = 100 #Ma gplot.time = time…after which this function can be re-run. Once the
trenchesare reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame.Returns
gdf:instanceof<geopandas.GeoDataFrame>- A pandas.DataFrame that has a column with
trenchesgeometry.
Raises
ValueError If the optional
timeparameter has not been passed toPlotTopologies. This is needed to constructtrenchesto the requestedtimeand thus populate the GeoDataFrame.Expand source code
def get_trenches(self): """Create a geopandas.GeoDataFrame object containing geometries of reconstructed trench lines. Notes ----- The `trenches` needed to produce the GeoDataFrame are automatically constructed if the optional `time` parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed either when `PlotTopologies` is first called... gplot = gplately.PlotTopologies(..., time=100,...) or anytime afterwards, by setting: time = 100 #Ma gplot.time = time ...after which this function can be re-run. Once the `trenches` are reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame. Returns ------- gdf : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `trenches` geometry. Raises ------ ValueError If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct `trenches` to the requested `time` and thus populate the GeoDataFrame. """ if self._time is None: raise ValueError("No trenches have been resolved. Set `PlotTopologies.time` to construct trenches.") if self.trenches is None: raise ValueError("No trenches passed to PlotTopologies.") trench_lines = shapelify_feature_lines(self.trenches) gdf = gpd.GeoDataFrame({"geometry": trench_lines}, geometry="geometry") return gdf def get_unclassified_features(self)-
Create a geopandas.GeoDataFrame object containing geometries of reconstructed unclassified feature lines.
Notes
The
unclassified_featuresneeded to produce the GeoDataFrame are automatically constructed if the optionaltimeparameter is passed to thePlotTopologiesobject before calling this function.timecan be passed either whenPlotTopologiesis first called…gplot = gplately.PlotTopologies(..., time=100,...)or anytime afterwards, by setting:
time = 100 #Ma gplot.time = time…after which this function can be re-run. Once the
unclassified_featuresare reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame.Returns
gdf:instanceof<geopandas.GeoDataFrame>- A pandas.DataFrame that has a column with
unclassified_featuresgeometry.
Raises
ValueError If the optional
timeparameter has not been passed toPlotTopologies. This is needed to constructunclassified_featuresto the requestedtimeand thus populate the GeoDataFrame.Expand source code
def get_unclassified_features(self): """Create a geopandas.GeoDataFrame object containing geometries of reconstructed unclassified feature lines. Notes ----- The `unclassified_features` needed to produce the GeoDataFrame are automatically constructed if the optional `time` parameter is passed to the `PlotTopologies` object before calling this function. `time` can be passed either when `PlotTopologies` is first called... gplot = gplately.PlotTopologies(..., time=100,...) or anytime afterwards, by setting: time = 100 #Ma gplot.time = time ...after which this function can be re-run. Once the `unclassified_features` are reconstructed, they are converted into Shapely lines whose coordinates are passed to a geopandas GeoDataFrame. Returns ------- gdf : instance of <geopandas.GeoDataFrame> A pandas.DataFrame that has a column with `unclassified_features` geometry. Raises ------ ValueError If the optional `time` parameter has not been passed to `PlotTopologies`. This is needed to construct `unclassified_features` to the requested `time` and thus populate the GeoDataFrame. """ if self._time is None: raise ValueError("No unclassified features have been resolved. Set `PlotTopologies.time` to construct them.") if self.unclassified_features is None: raise ValueError("No unclassified features passed to PlotTopologies.") unclassified_feature_lines = shapelify_feature_lines(self.unclassified_features) gdf = gpd.GeoDataFrame({"geometry": unclassified_feature_lines}, geometry="geometry") return gdf def plot_all_topologies(self, ax, color='black', **kwargs)-
Plot all topologies on a standard map projection.
Parameters
ax:instanceof<cartopy.mpl.geoaxes.GeoAxes>or<cartopy.mpl.geoaxes.GeoAxesSubplot>- A subclass of
matplotlib.axes.Axeswhich represents a map Projection. The map should be set at a particular Cartopy projection. color:str, default=’black’- The colour of the trench lines. By default, it is set to black.
**kwargs- Keyword arguments for parameters such as
alpha, etc. for plotting trench geometries. SeeMatplotlibkeyword arguments here.
Returns
ax:instanceof<geopandas.GeoDataFrame.plot>- A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with unclassified features plotted onto the chosen map projection.
Expand source code
def plot_all_topologies(self, ax, color='black', **kwargs): """Plot all topologies on a standard map projection. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. color : str, default=’black’ The colour of the trench lines. By default, it is set to black. **kwargs : Keyword arguments for parameters such as `alpha`, etc. for plotting trench geometries. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with unclassified features plotted onto the chosen map projection. """ gdf = self.get_all_topologies() return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs) def plot_coastlines(self, ax, **kwargs)-
Plot reconstructed coastline polygons onto a standard map Projection.
Notes
The
coastlinesfor plotting are accessed from thePlotTopologiesobject'scoastlinesattribute. Thesecoastlinesare reconstructed to thetimepassed to thePlotTopologiesobject and converted into Shapely polylines. The reconstructedcoastlinesare added onto the GeoAxes or GeoAxesSubplot mapaxusing GeoPandas. Map resentation details (e.g. facecolor, edgecolor, alpha…) are permitted as keyword arguments.Parameters
ax:instanceof<cartopy.mpl.geoaxes.GeoAxes>or<cartopy.mpl.geoaxes.GeoAxesSubplot>- A subclass of
matplotlib.axes.Axeswhich represents a map Projection. The map should be set at a particular Cartopy projection. **kwargs- Keyword arguments for parameters such as
facecolor,alpha, etc. for plotting coastline geometries. SeeMatplotlibkeyword arguments here.
Returns
ax:instanceof<geopandas.GeoDataFrame.plot>- A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with coastline features plotted onto the chosen map projection.
Expand source code
def plot_coastlines(self, ax, **kwargs): """Plot reconstructed coastline polygons onto a standard map Projection. Notes ----- The `coastlines` for plotting are accessed from the `PlotTopologies` object's `coastlines` attribute. These `coastlines` are reconstructed to the `time` passed to the `PlotTopologies` object and converted into Shapely polylines. The reconstructed `coastlines` are added onto the GeoAxes or GeoAxesSubplot map `ax` using GeoPandas. Map resentation details (e.g. facecolor, edgecolor, alpha…) are permitted as keyword arguments. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. **kwargs : Keyword arguments for parameters such as `facecolor`, `alpha`, etc. for plotting coastline geometries. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with coastline features plotted onto the chosen map projection. """ gdf = self.get_coastlines() return gdf.plot(ax=ax, transform=self.base_projection, **kwargs) def plot_continent_ocean_boundaries(self, ax, **kwargs)-
Plot reconstructed continent-ocean boundary (COB) polygons onto a standard map Projection.
Notes
The
COBsfor plotting are accessed from thePlotTopologiesobject'sCOBsattribute. TheseCOBsare reconstructed to thetimepassed to thePlotTopologiesobject and converted into Shapely polylines. The reconstructedCOBsare plotted onto the GeoAxes or GeoAxesSubplot mapaxusing GeoPandas. Map presentation details (e.g.facecolor,edgecolor,alpha…) are permitted as keyword arguments.These COBs are transformed into shapely geometries and added onto the chosen map for a specific geological time (supplied to the PlotTopologies object). Map presentation details (e.g. facecolor, edgecolor, alpha…) are permitted.
Parameters
ax:instanceof<cartopy.mpl.geoaxes.GeoAxes>or<cartopy.mpl.geoaxes.GeoAxesSubplot>- A subclass of
matplotlib.axes.Axeswhich represents a map Projection. The map should be set at a particular Cartopy projection. **kwargs- Keyword arguments for parameters such as
facecolor,alpha, etc. for plotting COB geometries. SeeMatplotlibkeyword arguments here.
Returns
ax:instanceof<geopandas.GeoDataFrame.plot>- A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with COB features plotted onto the chosen map projection.
Expand source code
def plot_continent_ocean_boundaries(self, ax, **kwargs): """Plot reconstructed continent-ocean boundary (COB) polygons onto a standard map Projection. Notes ----- The `COBs` for plotting are accessed from the `PlotTopologies` object's `COBs` attribute. These `COBs` are reconstructed to the `time` passed to the `PlotTopologies` object and converted into Shapely polylines. The reconstructed `COBs` are plotted onto the GeoAxes or GeoAxesSubplot map `ax` using GeoPandas. Map presentation details (e.g. `facecolor`, `edgecolor`, `alpha`…) are permitted as keyword arguments. These COBs are transformed into shapely geometries and added onto the chosen map for a specific geological time (supplied to the PlotTopologies object). Map presentation details (e.g. facecolor, edgecolor, alpha…) are permitted. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. **kwargs : Keyword arguments for parameters such as `facecolor`, `alpha`, etc. for plotting COB geometries. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with COB features plotted onto the chosen map projection. """ gdf = self.get_continent_ocean_boundaries() return gdf.plot(ax=ax, transform=self.base_projection, **kwargs) def plot_continental_crusts(self, ax, color='black', **kwargs)-
Plot continental crust lines on a standard map projection.
Parameters
ax:instanceof<cartopy.mpl.geoaxes.GeoAxes>or<cartopy.mpl.geoaxes.GeoAxesSubplot>- A subclass of
matplotlib.axes.Axeswhich represents a map Projection. The map should be set at a particular Cartopy projection. color:str, default=’black’- The colour of the trench lines. By default, it is set to black.
**kwargs- Keyword arguments for parameters such as
alpha, etc. for plotting trench geometries. SeeMatplotlibkeyword arguments here.
Returns
ax:instanceof<geopandas.GeoDataFrame.plot>- A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with continental crust lines plotted onto the chosen map projection.
Expand source code
def plot_continental_crusts(self, ax, color='black', **kwargs): """Plot continental crust lines on a standard map projection. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. color : str, default=’black’ The colour of the trench lines. By default, it is set to black. **kwargs : Keyword arguments for parameters such as `alpha`, etc. for plotting trench geometries. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with continental crust lines plotted onto the chosen map projection. """ gdf = self.get_continental_crusts() return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs) def plot_continental_rifts(self, ax, color='black', **kwargs)-
Plot continental rifts on a standard map projection.
Parameters
ax:instanceof<cartopy.mpl.geoaxes.GeoAxes>or<cartopy.mpl.geoaxes.GeoAxesSubplot>- A subclass of
matplotlib.axes.Axeswhich represents a map Projection. The map should be set at a particular Cartopy projection. color:str, default=’black’- The colour of the trench lines. By default, it is set to black.
**kwargs- Keyword arguments for parameters such as
alpha, etc. for plotting trench geometries. SeeMatplotlibkeyword arguments here.
Returns
ax:instanceof<geopandas.GeoDataFrame.plot>- A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with continental rifts plotted onto the chosen map projection.
Expand source code
def plot_continental_rifts(self, ax, color='black', **kwargs): """Plot continental rifts on a standard map projection. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. color : str, default=’black’ The colour of the trench lines. By default, it is set to black. **kwargs : Keyword arguments for parameters such as `alpha`, etc. for plotting trench geometries. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with continental rifts plotted onto the chosen map projection. """ gdf = self.get_continental_rifts() return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs) def plot_continents(self, ax, **kwargs)-
Plot reconstructed continental polygons onto a standard map Projection.
Notes
The
continentsfor plotting are accessed from thePlotTopologiesobject'scontinentsattribute. Thesecontinentsare reconstructed to thetimepassed to thePlotTopologiesobject and converted into Shapely polygons. The reconstructedcoastlinesare plotted onto the GeoAxes or GeoAxesSubplot mapaxusing GeoPandas. Map presentation details (e.g. facecolor, edgecolor, alpha…) are permitted as keyword arguments.Parameters
ax:instanceof<cartopy.mpl.geoaxes.GeoAxes>or<cartopy.mpl.geoaxes.GeoAxesSubplot>- A subclass of
matplotlib.axes.Axeswhich represents a map Projection. The map should be set at a particular Cartopy projection. **kwargs- Keyword arguments for parameters such as
facecolor,alpha, etc. for plotting continental geometries. SeeMatplotlibkeyword arguments here.
Returns
ax:instanceof<geopandas.GeoDataFrame.plot>- A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with continent features plotted onto the chosen map projection.
Expand source code
def plot_continents(self, ax, **kwargs): """Plot reconstructed continental polygons onto a standard map Projection. Notes ----- The `continents` for plotting are accessed from the `PlotTopologies` object's `continents` attribute. These `continents` are reconstructed to the `time` passed to the `PlotTopologies` object and converted into Shapely polygons. The reconstructed `coastlines` are plotted onto the GeoAxes or GeoAxesSubplot map `ax` using GeoPandas. Map presentation details (e.g. facecolor, edgecolor, alpha…) are permitted as keyword arguments. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. **kwargs : Keyword arguments for parameters such as `facecolor`, `alpha`, etc. for plotting continental geometries. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with continent features plotted onto the chosen map projection. """ gdf = self.get_continents() return gdf.plot(ax=ax, transform=self.base_projection, **kwargs) def plot_extended_continental_crusts(self, ax, color='black', **kwargs)-
Plot extended continental crust lines on a standard map projection.
Parameters
ax:instanceof<cartopy.mpl.geoaxes.GeoAxes>or<cartopy.mpl.geoaxes.GeoAxesSubplot>- A subclass of
matplotlib.axes.Axeswhich represents a map Projection. The map should be set at a particular Cartopy projection. color:str, default=’black’- The colour of the trench lines. By default, it is set to black.
**kwargs- Keyword arguments for parameters such as
alpha, etc. for plotting trench geometries. SeeMatplotlibkeyword arguments here.
Returns
ax:instanceof<geopandas.GeoDataFrame.plot>- A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with extended continental crust lines plotted onto the chosen map projection.
Expand source code
def plot_extended_continental_crusts(self, ax, color='black', **kwargs): """Plot extended continental crust lines on a standard map projection. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. color : str, default=’black’ The colour of the trench lines. By default, it is set to black. **kwargs : Keyword arguments for parameters such as `alpha`, etc. for plotting trench geometries. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with extended continental crust lines plotted onto the chosen map projection. """ gdf = self.get_extended_continental_crusts() return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs) def plot_faults(self, ax, color='black', **kwargs)-
Plot faults on a standard map projection.
Parameters
ax:instanceof<cartopy.mpl.geoaxes.GeoAxes>or<cartopy.mpl.geoaxes.GeoAxesSubplot>- A subclass of
matplotlib.axes.Axeswhich represents a map Projection. The map should be set at a particular Cartopy projection. color:str, default=’black’- The colour of the trench lines. By default, it is set to black.
**kwargs- Keyword arguments for parameters such as
alpha, etc. for plotting trench geometries. SeeMatplotlibkeyword arguments here.
Returns
ax:instanceof<geopandas.GeoDataFrame.plot>- A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with faults plotted onto the chosen map projection.
Expand source code
def plot_faults(self, ax, color='black', **kwargs): """Plot faults on a standard map projection. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. color : str, default=’black’ The colour of the trench lines. By default, it is set to black. **kwargs : Keyword arguments for parameters such as `alpha`, etc. for plotting trench geometries. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with faults plotted onto the chosen map projection. """ gdf = self.get_faults() return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs) def plot_feature(self, ax, feature, **kwargs)-
Plot pygplates.FeatureCollection or pygplates.Feature onto a map.
Parameters
ax:instanceof<cartopy.mpl.geoaxes.GeoAxes>or<cartopy.mpl.geoaxes.GeoAxesSubplot>- A subclass of
matplotlib.axes.Axeswhich represents a map Projection. The map should be set at a particular Cartopy projection. **kwargs- Keyword arguments for parameters such as
facecolor,alpha, etc. for plotting coastline geometries. SeeMatplotlibkeyword arguments here.
Returns
ax:instanceof<geopandas.GeoDataFrame.plot>- A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with coastline features plotted onto the chosen map projection.
Expand source code
def plot_feature(self, ax, feature, **kwargs): """ Plot pygplates.FeatureCollection or pygplates.Feature onto a map. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. **kwargs : Keyword arguments for parameters such as `facecolor`, `alpha`, etc. for plotting coastline geometries. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with coastline features plotted onto the chosen map projection. """ gdf = self.get_feature(feature) return gdf.plot(ax=ax, transform=self.base_projection, **kwargs) def plot_fracture_zones(self, ax, color='black', **kwargs)-
Plot fracture zones on a standard map projection.
Parameters
ax:instanceof<cartopy.mpl.geoaxes.GeoAxes>or<cartopy.mpl.geoaxes.GeoAxesSubplot>- A subclass of
matplotlib.axes.Axeswhich represents a map Projection. The map should be set at a particular Cartopy projection. color:str, default=’black’- The colour of the trench lines. By default, it is set to black.
**kwargs- Keyword arguments for parameters such as
alpha, etc. for plotting trench geometries. SeeMatplotlibkeyword arguments here.
Returns
ax:instanceof<geopandas.GeoDataFrame.plot>- A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with fracture zones plotted onto the chosen map projection.
Expand source code
def plot_fracture_zones(self, ax, color='black', **kwargs): """Plot fracture zones on a standard map projection. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. color : str, default=’black’ The colour of the trench lines. By default, it is set to black. **kwargs : Keyword arguments for parameters such as `alpha`, etc. for plotting trench geometries. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with fracture zones plotted onto the chosen map projection. """ gdf = self.get_fracture_zones() return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs) def plot_grid(self, ax, grid, extent=[-180, 180, -90, 90], **kwargs)-
Plot a
MaskedArrayraster or grid onto a standard map Projection.Notes
Uses Matplotlib's
imshowfunction.Parameters
ax:instanceof<cartopy.mpl.geoaxes.GeoAxes>or<cartopy.mpl.geoaxes.GeoAxesSubplot>- A subclass of
matplotlib.axes.Axeswhich represents a map Projection. The map should be set at a particular Cartopy projection. grid:MaskedArrayorRaster- A
MaskedArraywith elements that define a grid. The number of rows in the raster corresponds to the number of latitudinal coordinates, while the number of raster columns corresponds to the number of longitudinal coordinates. extent:1d array, default=[-180,180,-90,90]- A four-element array to specify the [min lon, max lon, min lat, max lat] with which to constrain the grid image. If no extents are supplied, full global extent is assumed.
**kwargs- Keyword arguments for map presentation parameters such as
alpha, etc. for plotting the grid. SeeMatplotlib'simshowkeyword arguments here.
Returns
ax:instanceof<geopandas.GeoDataFrame.plot>- A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with the grid plotted onto the chosen map projection.
Expand source code
def plot_grid(self, ax, grid, extent=[-180,180,-90,90], **kwargs): """Plot a `MaskedArray` raster or grid onto a standard map Projection. Notes ----- Uses Matplotlib's `imshow` [function](https://matplotlib.org/3.5.1/api/_as_gen/matplotlib.axes.Axes.imshow.html). Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. grid : MaskedArray or `gplately.grids.Raster` A `MaskedArray` with elements that define a grid. The number of rows in the raster corresponds to the number of latitudinal coordinates, while the number of raster columns corresponds to the number of longitudinal coordinates. extent : 1d array, default=[-180,180,-90,90] A four-element array to specify the [min lon, max lon, min lat, max lat] with which to constrain the grid image. If no extents are supplied, full global extent is assumed. **kwargs : Keyword arguments for map presentation parameters such as `alpha`, etc. for plotting the grid. See `Matplotlib`'s `imshow` keyword arguments [here](https://matplotlib.org/3.5.1/api/_as_gen/matplotlib.axes.Axes.imshow.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with the grid plotted onto the chosen map projection. """ # Override matplotlib default origin ('upper') origin = kwargs.pop("origin", "lower") from .grids import Raster if isinstance(grid, Raster): # extract extent and origin extent = grid.extent origin = grid.origin data = grid.data else: data = grid return ax.imshow( data, extent=extent, transform=self.base_projection, origin=origin, **kwargs, ) def plot_grid_from_netCDF(self, ax, filename, **kwargs)-
Read a raster from a netCDF file, convert it to a
MaskedArrayand plot it onto a standard map Projection.Notes
plot_grid_from_netCDFuses Matplotlib'simshowfunction.Parameters
ax:instanceof<cartopy.mpl.geoaxes.GeoAxes>or<cartopy.mpl.geoaxes.GeoAxesSubplot>- A subclass of
matplotlib.axes.Axeswhich represents a map Projection. The map should be set at a particular Cartopy projection. filename:str- Full path to a netCDF filename.
**kwargs- Keyword arguments for map presentation parameters for
plotting the grid. See
Matplotlib'simshowkeyword arguments here.
Returns
ax:instanceof<geopandas.GeoDataFrame.plot>- A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with the netCDF grid plotted onto the chosen map projection.
Expand source code
def plot_grid_from_netCDF(self, ax, filename, **kwargs): """Read a raster from a netCDF file, convert it to a `MaskedArray` and plot it onto a standard map Projection. Notes ----- `plot_grid_from_netCDF` uses Matplotlib's `imshow` [function](https://matplotlib.org/3.5.1/api/_as_gen/matplotlib.axes.Axes.imshow.html). Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. filename : str Full path to a netCDF filename. **kwargs : Keyword arguments for map presentation parameters for plotting the grid. See `Matplotlib`'s `imshow` keyword arguments [here](https://matplotlib.org/3.5.1/api/_as_gen/matplotlib.axes.Axes.imshow.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with the netCDF grid plotted onto the chosen map projection. """ # Override matplotlib default origin ('upper') origin = kwargs.pop("origin", "lower") from .grids import read_netcdf_grid raster, lon_coords, lat_coords = read_netcdf_grid(filename, return_grids=True) extent = [lon_coords[0], lon_coords[-1], lat_coords[0], lat_coords[-1]] if lon_coords[0] < lat_coords[-1]: origin = "lower" else: origin = "upper" return self.plot_grid(ax, raster, extent=extent, origin=origin, **kwargs) def plot_inferred_paleo_boundaries(self, ax, color='black', **kwargs)-
Plot inferred paleo boundaries on a standard map projection.
Parameters
ax:instanceof<cartopy.mpl.geoaxes.GeoAxes>or<cartopy.mpl.geoaxes.GeoAxesSubplot>- A subclass of
matplotlib.axes.Axeswhich represents a map Projection. The map should be set at a particular Cartopy projection. color:str, default=’black’- The colour of the trench lines. By default, it is set to black.
**kwargs- Keyword arguments for parameters such as
alpha, etc. for plotting trench geometries. SeeMatplotlibkeyword arguments here.
Returns
ax:instanceof<geopandas.GeoDataFrame.plot>- A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with inferred paleo boundaries plotted onto the chosen map projection.
Expand source code
def plot_inferred_paleo_boundaries(self, ax, color='black', **kwargs): """Plot inferred paleo boundaries on a standard map projection. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. color : str, default=’black’ The colour of the trench lines. By default, it is set to black. **kwargs : Keyword arguments for parameters such as `alpha`, etc. for plotting trench geometries. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with inferred paleo boundaries plotted onto the chosen map projection. """ gdf = get_inferred_paleo_boundaries() return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs) def plot_misc_boundaries(self, ax, color='black', **kwargs)-
Plot reconstructed miscellaneous plate boundary polylines onto a standard map Projection.
Notes
The miscellaneous boundary sections for plotting are accessed from the
PlotTopologiesobject'sotherattribute. Theseotherboundaries are reconstructed to thetimepassed to thePlotTopologiesobject and converted into Shapely polylines. The reconstructedotherboundaries are plotted onto the GeoAxes or GeoAxesSubplot mapaxusing GeoPandas. Map presentation details (e.g.facecolor,edgecolor,alpha…) are permitted as keyword arguments.Miscellaneous boundary geometries are wrapped to the dateline using pyGPlates' DateLineWrapper by splitting a polyline into multiple polylines at the dateline. This is to avoid horizontal lines being formed between polylines at longitudes of -180 and 180 degrees. Point features near the poles (-89 & 89 degree latitude) are also clipped to ensure compatibility with Cartopy.
Parameters
ax:instanceof<cartopy.mpl.geoaxes.GeoAxes>or<cartopy.mpl.geoaxes.GeoAxesSubplot>- A subclass of
matplotlib.axes.Axeswhich represents a map Projection. The map should be set at a particular Cartopy projection. color:str, default=’black’- The colour of the boundary lines. By default, it is set to black.
**kwargs- Keyword arguments for parameters such as ‘alpha’, etc. for
plotting miscellaneous boundary geometries.
See
Matplotlibkeyword arguments here.
Returns
ax:instanceof<geopandas.GeoDataFrame.plot>- A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with miscellaneous boundary features plotted onto the chosen map projection.
Expand source code
def plot_misc_boundaries(self, ax, color="black", **kwargs): """Plot reconstructed miscellaneous plate boundary polylines onto a standard map Projection. Notes ----- The miscellaneous boundary sections for plotting are accessed from the `PlotTopologies` object's `other` attribute. These `other` boundaries are reconstructed to the `time` passed to the `PlotTopologies` object and converted into Shapely polylines. The reconstructed `other` boundaries are plotted onto the GeoAxes or GeoAxesSubplot map `ax` using GeoPandas. Map presentation details (e.g. `facecolor`, `edgecolor`, `alpha`…) are permitted as keyword arguments. Miscellaneous boundary geometries are wrapped to the dateline using pyGPlates' [DateLineWrapper](https://www.gplates.org/docs/pygplates/generated/pygplates.datelinewrapper) by splitting a polyline into multiple polylines at the dateline. This is to avoid horizontal lines being formed between polylines at longitudes of -180 and 180 degrees. Point features near the poles (-89 & 89 degree latitude) are also clipped to ensure compatibility with Cartopy. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. color : str, default=’black’ The colour of the boundary lines. By default, it is set to black. **kwargs : Keyword arguments for parameters such as ‘alpha’, etc. for plotting miscellaneous boundary geometries. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with miscellaneous boundary features plotted onto the chosen map projection. """ gdf = self.get_misc_boundaries() return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs) def plot_misc_transforms(self, ax, color='black', **kwargs)-
Plot miscellaneous transform boundaries on a standard map projection.
Parameters
ax:instanceof<cartopy.mpl.geoaxes.GeoAxes>or<cartopy.mpl.geoaxes.GeoAxesSubplot>- A subclass of
matplotlib.axes.Axeswhich represents a map Projection. The map should be set at a particular Cartopy projection. color:str, default=’black’- The colour of the trench lines. By default, it is set to black.
**kwargs- Keyword arguments for parameters such as
alpha, etc. for plotting trench geometries. SeeMatplotlibkeyword arguments here.
Returns
ax:instanceof<geopandas.GeoDataFrame.plot>- A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with miscellaneous transform boundaries plotted onto the chosen map projection.
Expand source code
def plot_misc_transforms(self, ax, color='black', **kwargs): """Plot miscellaneous transform boundaries on a standard map projection. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. color : str, default=’black’ The colour of the trench lines. By default, it is set to black. **kwargs : Keyword arguments for parameters such as `alpha`, etc. for plotting trench geometries. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with miscellaneous transform boundaries plotted onto the chosen map projection. """ gdf = self.get_misc_transforms() return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs) def plot_orogenic_belts(self, ax, color='black', **kwargs)-
Plot orogenic belts on a standard map projection.
Parameters
ax:instanceof<cartopy.mpl.geoaxes.GeoAxes>or<cartopy.mpl.geoaxes.GeoAxesSubplot>- A subclass of
matplotlib.axes.Axeswhich represents a map Projection. The map should be set at a particular Cartopy projection. color:str, default=’black’- The colour of the trench lines. By default, it is set to black.
**kwargs- Keyword arguments for parameters such as
alpha, etc. for plotting trench geometries. SeeMatplotlibkeyword arguments here.
Returns
ax:instanceof<geopandas.GeoDataFrame.plot>- A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with orogenic belts plotted onto the chosen map projection.
Expand source code
def plot_orogenic_belts(self, ax, color='black', **kwargs): """Plot orogenic belts on a standard map projection. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. color : str, default=’black’ The colour of the trench lines. By default, it is set to black. **kwargs : Keyword arguments for parameters such as `alpha`, etc. for plotting trench geometries. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with orogenic belts plotted onto the chosen map projection. """ gdf = self.get_orogenic_belts() return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs) def plot_passive_continental_boundaries(self, ax, color='black', **kwargs)-
Plot passive continental boundaries on a standard map projection.
Parameters
ax:instanceof<cartopy.mpl.geoaxes.GeoAxes>or<cartopy.mpl.geoaxes.GeoAxesSubplot>- A subclass of
matplotlib.axes.Axeswhich represents a map Projection. The map should be set at a particular Cartopy projection. color:str, default=’black’- The colour of the trench lines. By default, it is set to black.
**kwargs- Keyword arguments for parameters such as
alpha, etc. for plotting trench geometries. SeeMatplotlibkeyword arguments here.
Returns
ax:instanceof<geopandas.GeoDataFrame.plot>- A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with passive continental boundaries plotted onto the chosen map projection.
Expand source code
def plot_passive_continental_boundaries(self, ax, color='black', **kwargs): """Plot passive continental boundaries on a standard map projection. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. color : str, default=’black’ The colour of the trench lines. By default, it is set to black. **kwargs : Keyword arguments for parameters such as `alpha`, etc. for plotting trench geometries. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with passive continental boundaries plotted onto the chosen map projection. """ gdf = self.get_passive_continental_boundaries() return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs) def plot_plate_id(self, ax, plate_id, **kwargs)-
Plot a plate polygon with an associated
plate_idonto a standard map Projection.Parameters
ax:instanceof<cartopy.mpl.geoaxes.GeoAxes>or<cartopy.mpl.geoaxes.GeoAxesSubplot>- A subclass of
matplotlib.axes.Axeswhich represents a map Projection. The map should be set at a particular Cartopy projection. plate_id:int- A plate ID that identifies the continental polygon to plot. See the Global EarthByte plate IDs list for a full list of plate IDs to plot.
**kwargs- Keyword arguments for map presentation parameters such as
alpha, etc. for plotting the grid. SeeMatplotlib'simshowkeyword arguments here.
Expand source code
def plot_plate_id(self, ax, plate_id, **kwargs): """Plot a plate polygon with an associated `plate_id` onto a standard map Projection. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. plate_id : int A plate ID that identifies the continental polygon to plot. See the [Global EarthByte plate IDs list](https://www.earthbyte.org/webdav/ftp/earthbyte/GPlates/SampleData/FeatureCollections/Rotations/Global_EarthByte_PlateIDs_20071218.pdf) for a full list of plate IDs to plot. **kwargs : Keyword arguments for map presentation parameters such as `alpha`, etc. for plotting the grid. See `Matplotlib`'s `imshow` keyword arguments [here](https://matplotlib.org/3.5.1/api/_as_gen/matplotlib.axes.Axes.imshow.html). """ for feature in self.topologies: if feature.get_reconstruction_plate_id() == plate_id: ft_plate = shapelify_feature_polygons([feature]) return ax.add_geometries(ft_plate, crs=self.base_projection, **kwargs) def plot_plate_motion_vectors(self, ax, spacingX=10, spacingY=10, normalise=False, **kwargs)-
Calculate plate motion velocity vector fields at a particular geological time and plot them onto a standard map Projection.
Notes
plot_plate_motion_vectorsgenerates a MeshNode domain of point features using given spacings in the X and Y directions (spacingXandspacingY). Each point in the domain is assigned a plate ID, and these IDs are used to obtain equivalent stage rotations of identified tectonic plates over a 5 Ma time interval. Each point and its stage rotation are used to calculate plate velocities at a particular geological time. Velocities for each domain point are represented in the north-east-down coordinate system and plotted on a GeoAxes.Vector fields can be optionally normalised by setting
normalisetoTrue. This makes vector arrow lengths uniform.Parameters
ax:instanceof<cartopy.mpl.geoaxes.GeoAxes>or<cartopy.mpl.geoaxes.GeoAxesSubplot>- A subclass of
matplotlib.axes.Axeswhich represents a map Projection. The map should be set at a particular Cartopy projection. spacingX:int, default=10- The spacing in the X direction used to make the velocity domain point feature mesh.
spacingY:int, default=10- The spacing in the Y direction used to make the velocity domain point feature mesh.
normalise:bool, default=False- Choose whether to normalise the velocity magnitudes so that vector lengths are all equal.
**kwargs- Keyword arguments for quiver presentation parameters for plotting
the velocity vector field. See
Matplotlibquiver keyword arguments here.
Returns
ax:instanceof<geopandas.GeoDataFrame.plot>- A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with the velocity vector field plotted onto the chosen map projection.
Expand source code
def plot_plate_motion_vectors(self, ax, spacingX=10, spacingY=10, normalise=False, **kwargs): """Calculate plate motion velocity vector fields at a particular geological time and plot them onto a standard map Projection. Notes ----- `plot_plate_motion_vectors` generates a MeshNode domain of point features using given spacings in the X and Y directions (`spacingX` and `spacingY`). Each point in the domain is assigned a plate ID, and these IDs are used to obtain equivalent stage rotations of identified tectonic plates over a 5 Ma time interval. Each point and its stage rotation are used to calculate plate velocities at a particular geological time. Velocities for each domain point are represented in the north-east-down coordinate system and plotted on a GeoAxes. Vector fields can be optionally normalised by setting `normalise` to `True`. This makes vector arrow lengths uniform. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. spacingX : int, default=10 The spacing in the X direction used to make the velocity domain point feature mesh. spacingY : int, default=10 The spacing in the Y direction used to make the velocity domain point feature mesh. normalise : bool, default=False Choose whether to normalise the velocity magnitudes so that vector lengths are all equal. **kwargs : Keyword arguments for quiver presentation parameters for plotting the velocity vector field. See `Matplotlib` quiver keyword arguments [here](https://matplotlib.org/3.5.1/api/_as_gen/matplotlib.axes.Axes.quiver.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with the velocity vector field plotted onto the chosen map projection. """ lons = np.arange(-180, 180+spacingX, spacingX) lats = np.arange(-90, 90+spacingY, spacingY) lonq, latq = np.meshgrid(lons, lats) # create a feature from all the points velocity_domain_features = ptt.velocity_tools.make_GPML_velocity_feature(lonq.ravel(), latq.ravel()) rotation_model = self.plate_reconstruction.rotation_model topology_features = self.plate_reconstruction.topology_features delta_time = 5.0 all_velocities = ptt.velocity_tools.get_plate_velocities( velocity_domain_features, topology_features, rotation_model, self.time, delta_time, 'vector_comp') X, Y, U, V = ptt.velocity_tools.get_x_y_u_v(lons, lats, all_velocities) if normalise: mag = np.hypot(U, V) mag[mag == 0] = 1 U /= mag V /= mag with warnings.catch_warnings(): warnings.simplefilter("ignore", UserWarning) quiver = ax.quiver( X, Y, U, V, transform=self.base_projection, **kwargs ) return quiver def plot_ridges(self, ax, color='black', **kwargs)-
Plot reconstructed ridge polylines onto a standard map Projection.
Notes
The
ridgesfor plotting are accessed from thePlotTopologiesobject'sridgesattribute. Theseridgesare reconstructed to thetimepassed to thePlotTopologiesobject and converted into Shapely polylines. The reconstructedridgesare plotted onto the GeoAxes or GeoAxesSubplot mapaxusing GeoPandas. Map presentation details (e.g.facecolor,edgecolor,alpha…) are permitted as keyword arguments.Ridge geometries are wrapped to the dateline using pyGPlates' DateLineWrapper by splitting a polyline into multiple polylines at the dateline. This is to avoid horizontal lines being formed between polylines at longitudes of -180 and 180 degrees. Point features near the poles (-89 & 89 degree latitude) are also clipped to ensure compatibility with Cartopy.
Parameters
ax:instanceof<cartopy.mpl.geoaxes.GeoAxes>or<cartopy.mpl.geoaxes.GeoAxesSubplot>- A subclass of
matplotlib.axes.Axeswhich represents a map Projection. The map should be set at a particular Cartopy projection. color:str, default=’black’- The colour of the ridge lines. By default, it is set to black.
**kwargs- Keyword arguments for parameters such as
alpha, etc. for plotting ridge geometries. SeeMatplotlibkeyword arguments here.
Returns
ax:instanceof<geopandas.GeoDataFrame.plot>- A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with ridge features plotted onto the chosen map projection.
Expand source code
def plot_ridges(self, ax, color='black', **kwargs): """Plot reconstructed ridge polylines onto a standard map Projection. Notes ----- The `ridges` for plotting are accessed from the `PlotTopologies` object's `ridges` attribute. These `ridges` are reconstructed to the `time` passed to the `PlotTopologies` object and converted into Shapely polylines. The reconstructed `ridges` are plotted onto the GeoAxes or GeoAxesSubplot map `ax` using GeoPandas. Map presentation details (e.g. `facecolor`, `edgecolor`, `alpha`…) are permitted as keyword arguments. Ridge geometries are wrapped to the dateline using pyGPlates' [DateLineWrapper](https://www.gplates.org/docs/pygplates/generated/pygplates.datelinewrapper) by splitting a polyline into multiple polylines at the dateline. This is to avoid horizontal lines being formed between polylines at longitudes of -180 and 180 degrees. Point features near the poles (-89 & 89 degree latitude) are also clipped to ensure compatibility with Cartopy. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. color : str, default=’black’ The colour of the ridge lines. By default, it is set to black. **kwargs : Keyword arguments for parameters such as `alpha`, etc. for plotting ridge geometries. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with ridge features plotted onto the chosen map projection. """ gdf = self.get_ridges() return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs) def plot_ridges_and_transforms(self, ax, color='black', **kwargs)-
Plot reconstructed ridge & transform boundary polylines onto a standard map Projection.
Notes
The ridge & transform sections for plotting are accessed from the
PlotTopologiesobject'sridge_transformsattribute. Theseridge_transformsare reconstructed to thetimepassed to thePlotTopologiesobject and converted into Shapely polylines. The reconstructedridge_transformsare plotted onto the GeoAxes or GeoAxesSubplot mapaxusing GeoPandas. Map presentation details (e.g.facecolor,edgecolor,alpha…) are permitted as keyword arguments.Note: Ridge & transform geometries are wrapped to the dateline using pyGPlates' DateLineWrapper by splitting a polyline into multiple polylines at the dateline. This is to avoid horizontal lines being formed between polylines at longitudes of -180 and 180 degrees. Point features near the poles (-89 & 89 degree latitude) are also clipped to ensure compatibility with Cartopy.
Parameters
ax:instanceof<cartopy.mpl.geoaxes.GeoAxes>or<cartopy.mpl.geoaxes.GeoAxesSubplot>- A subclass of
matplotlib.axes.Axeswhich represents a map Projection. The map should be set at a particular Cartopy projection. color:str, default=’black’- The colour of the ridge & transform lines. By default, it is set to black.
**kwargs- Keyword arguments for parameters such as ‘alpha’, etc. for
plotting ridge & transform geometries.
See
Matplotlibkeyword arguments here.
Returns
ax:instanceof<geopandas.GeoDataFrame.plot>- A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with ridge & transform features plotted onto the chosen map projection.
Expand source code
def plot_ridges_and_transforms(self, ax, color='black', **kwargs): """Plot reconstructed ridge & transform boundary polylines onto a standard map Projection. Notes ----- The ridge & transform sections for plotting are accessed from the `PlotTopologies` object's `ridge_transforms` attribute. These `ridge_transforms` are reconstructed to the `time` passed to the `PlotTopologies` object and converted into Shapely polylines. The reconstructed `ridge_transforms` are plotted onto the GeoAxes or GeoAxesSubplot map `ax` using GeoPandas. Map presentation details (e.g. `facecolor`, `edgecolor`, `alpha`…) are permitted as keyword arguments. Note: Ridge & transform geometries are wrapped to the dateline using pyGPlates' [DateLineWrapper](https://www.gplates.org/docs/pygplates/generated/pygplates.datelinewrapper) by splitting a polyline into multiple polylines at the dateline. This is to avoid horizontal lines being formed between polylines at longitudes of -180 and 180 degrees. Point features near the poles (-89 & 89 degree latitude) are also clipped to ensure compatibility with Cartopy. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. color : str, default=’black’ The colour of the ridge & transform lines. By default, it is set to black. **kwargs : Keyword arguments for parameters such as ‘alpha’, etc. for plotting ridge & transform geometries. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with ridge & transform features plotted onto the chosen map projection. """ gdf = self.get_ridges_and_transforms() return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs) def plot_slab_edges(self, ax, color='black', **kwargs)-
Plot slab edges on a standard map projection.
Parameters
ax:instanceof<cartopy.mpl.geoaxes.GeoAxes>or<cartopy.mpl.geoaxes.GeoAxesSubplot>- A subclass of
matplotlib.axes.Axeswhich represents a map Projection. The map should be set at a particular Cartopy projection. color:str, default=’black’- The colour of the trench lines. By default, it is set to black.
**kwargs- Keyword arguments for parameters such as
alpha, etc. for plotting trench geometries. SeeMatplotlibkeyword arguments here.
Returns
ax:instanceof<geopandas.GeoDataFrame.plot>- A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with slab edges plotted onto the chosen map projection.
Expand source code
def plot_slab_edges(self, ax, color='black', **kwargs): """Plot slab edges on a standard map projection. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. color : str, default=’black’ The colour of the trench lines. By default, it is set to black. **kwargs : Keyword arguments for parameters such as `alpha`, etc. for plotting trench geometries. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with slab edges plotted onto the chosen map projection. """ gdf = self.get_slab_edges() return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs) def plot_subduction_teeth(self, ax, spacing=0.07, size=None, aspect=None, color='black', **kwargs)-
Plot subduction teeth onto a standard map Projection.
Notes
Subduction teeth are tessellated from
PlotTopologiesobject attributestrench_leftandtrench_right, and transformed into Shapely polygons for plotting.Parameters
ax:instanceof<cartopy.mpl.geoaxes.GeoAxes>or<cartopy.mpl.geoaxes.GeoAxesSubplot>- A subclass of
matplotlib.axes.Axeswhich represents a map Projection. The map should be set at a particular Cartopy projection. spacing:float, default=0.1- The tessellation threshold (in radians). Parametrises subduction tooth density. Triangles are generated only along line segments with distances that exceed the given threshold ‘spacing’.
size:float, default=None- Length of teeth triangle base (in radians). If kept at
None, thensize = 0.5*spacing. aspect:float, default=None- Aspect ratio of teeth triangles. If kept at
None, thenaspect = 2/3*size. color:str, default=’black’- The colour of the teeth. By default, it is set to black.
**kwargs- Keyword arguments parameters such as ‘alpha’, etc.
for plotting subduction tooth polygons.
See
Matplotlibkeyword arguments here.
Returns
ax:instanceof<geopandas.GeoDataFrame.plot>- A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with subduction teeth plotted onto the chosen map projection.
Expand source code
def plot_subduction_teeth(self, ax, spacing=0.07, size=None, aspect=None, color='black', **kwargs): """Plot subduction teeth onto a standard map Projection. Notes ----- Subduction teeth are tessellated from `PlotTopologies` object attributes `trench_left` and `trench_right`, and transformed into Shapely polygons for plotting. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. spacing : float, default=0.1 The tessellation threshold (in radians). Parametrises subduction tooth density. Triangles are generated only along line segments with distances that exceed the given threshold ‘spacing’. size : float, default=None Length of teeth triangle base (in radians). If kept at `None`, then `size = 0.5*spacing`. aspect : float, default=None Aspect ratio of teeth triangles. If kept at `None`, then `aspect = 2/3*size`. color : str, default=’black’ The colour of the teeth. By default, it is set to black. **kwargs : Keyword arguments parameters such as ‘alpha’, etc. for plotting subduction tooth polygons. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with subduction teeth plotted onto the chosen map projection. """ if self._time is None: raise ValueError("No miscellaneous topologies have been resolved. Set `PlotTopologies.time` to construct them.") spacing = spacing * EARTH_RADIUS * 1e3 if aspect is None: aspect = 2.0/3.0 if size is None: size = spacing*0.5 height = size*aspect trench_left_features = shapelify_feature_lines(self.trench_left) trench_right_features = shapelify_feature_lines(self.trench_right) return( plot_subduction_teeth(trench_left_features, size, 'l', height, spacing, ax=ax, color=color, **kwargs), plot_subduction_teeth(trench_right_features, size, 'r', height, spacing, ax=ax, color=color, **kwargs) ) def plot_subduction_teeth_deprecated(self, ax, spacing=0.1, size=2.0, aspect=1, color='black', **kwargs)-
Plot subduction teeth onto a standard map Projection.
Notes
Subduction teeth are tessellated from
PlotTopologiesobject attributestrench_leftandtrench_right, and transformed into Shapely polygons for plotting.Parameters
ax:instanceof<cartopy.mpl.geoaxes.GeoAxes>or<cartopy.mpl.geoaxes.GeoAxesSubplot>- A subclass of
matplotlib.axes.Axeswhich represents a map Projection. The map should be set at a particular Cartopy projection. spacing:float, default=0.1- The tessellation threshold (in radians). Parametrises subduction tooth density. Triangles are generated only along line segments with distances that exceed the given threshold ‘spacing’.
size:float, default=2.0- Length of teeth triangle base.
aspect:float, default=1- Aspect ratio of teeth triangles. Ratio is 1.0 by default.
color:str, default=’black’- The colour of the teeth. By default, it is set to black.
**kwargs- Keyword arguments for parameters such as ‘alpha’, etc. for
plotting subduction tooth polygons.
See
Matplotlibkeyword arguments here.
Returns
ax:instanceof<geopandas.GeoDataFrame.plot>- A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with subduction teeth plotted onto the chosen map projection.
Expand source code
def plot_subduction_teeth_deprecated(self, ax, spacing=0.1, size=2.0, aspect=1, color='black', **kwargs): """Plot subduction teeth onto a standard map Projection. Notes ----- Subduction teeth are tessellated from `PlotTopologies` object attributes `trench_left` and `trench_right`, and transformed into Shapely polygons for plotting. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. spacing : float, default=0.1 The tessellation threshold (in radians). Parametrises subduction tooth density. Triangles are generated only along line segments with distances that exceed the given threshold ‘spacing’. size : float, default=2.0 Length of teeth triangle base. aspect : float, default=1 Aspect ratio of teeth triangles. Ratio is 1.0 by default. color : str, default=’black’ The colour of the teeth. By default, it is set to black. **kwargs : Keyword arguments for parameters such as ‘alpha’, etc. for plotting subduction tooth polygons. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with subduction teeth plotted onto the chosen map projection. """ import shapely # add Subduction Teeth subd_xL, subd_yL = self._tessellate_triangles( self.trench_left, tesselation_radians=spacing, triangle_base_length=size, triangle_aspect=-aspect) subd_xR, subd_yR = self._tessellate_triangles( self.trench_right, tesselation_radians=spacing, triangle_base_length=size, triangle_aspect=aspect) teeth = [] for tX, tY in zip(subd_xL, subd_yL): triangle_xy_points = np.c_[tX, tY] shp = shapely.geometry.Polygon(triangle_xy_points) teeth.append(shp) for tX, tY in zip(subd_xR, subd_yR): triangle_xy_points = np.c_[tX, tY] shp = shapely.geometry.Polygon(triangle_xy_points) teeth.append(shp) return ax.add_geometries(teeth, crs=self.base_projection, color=color, **kwargs) def plot_sutures(self, ax, color='black', **kwargs)-
Plot sutures on a standard map projection.
Parameters
ax:instanceof<cartopy.mpl.geoaxes.GeoAxes>or<cartopy.mpl.geoaxes.GeoAxesSubplot>- A subclass of
matplotlib.axes.Axeswhich represents a map Projection. The map should be set at a particular Cartopy projection. color:str, default=’black’- The colour of the trench lines. By default, it is set to black.
**kwargs- Keyword arguments for parameters such as
alpha, etc. for plotting trench geometries. SeeMatplotlibkeyword arguments here.
Returns
ax:instanceof<geopandas.GeoDataFrame.plot>- A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with sutures plotted onto the chosen map projection.
Expand source code
def plot_sutures(self, ax, color='black', **kwargs): """Plot sutures on a standard map projection. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. color : str, default=’black’ The colour of the trench lines. By default, it is set to black. **kwargs : Keyword arguments for parameters such as `alpha`, etc. for plotting trench geometries. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with sutures plotted onto the chosen map projection. """ gdf = self.get_sutures() return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs) def plot_terrane_boundaries(self, ax, color='black', **kwargs)-
Plot terrane boundaries on a standard map projection.
Parameters
ax:instanceof<cartopy.mpl.geoaxes.GeoAxes>or<cartopy.mpl.geoaxes.GeoAxesSubplot>- A subclass of
matplotlib.axes.Axeswhich represents a map Projection. The map should be set at a particular Cartopy projection. color:str, default=’black’- The colour of the trench lines. By default, it is set to black.
**kwargs- Keyword arguments for parameters such as
alpha, etc. for plotting trench geometries. SeeMatplotlibkeyword arguments here.
Returns
ax:instanceof<geopandas.GeoDataFrame.plot>- A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with terrane boundaries plotted onto the chosen map projection.
Expand source code
def plot_terrane_boundaries(self, ax, color='black', **kwargs): """Plot terrane boundaries on a standard map projection. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. color : str, default=’black’ The colour of the trench lines. By default, it is set to black. **kwargs : Keyword arguments for parameters such as `alpha`, etc. for plotting trench geometries. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with terrane boundaries plotted onto the chosen map projection. """ gdf = self.get_terrane_boundaries() return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs) def plot_transforms(self, ax, color='black', **kwargs)-
Plot reconstructed transform boundary polylines onto a standard map.
Notes
The transform sections for plotting are accessed from the
PlotTopologiesobject'stransformsattribute. Thesetransformsare reconstructed to thetimepassed to thePlotTopologiesobject and converted into Shapely polylines. The reconstructedtransformsare plotted onto the GeoAxes or GeoAxesSubplot mapaxusing GeoPandas. Map presentation details (e.g.facecolor,edgecolor,alpha…) are permitted as keyword arguments.Transform geometries are wrapped to the dateline using pyGPlates' DateLineWrapper by splitting a polyline into multiple polylines at the dateline. This is to avoid horizontal lines being formed between polylines at longitudes of -180 and 180 degrees. Point features near the poles (-89 & 89 degree latitude) are also clipped to ensure compatibility with Cartopy.
Parameters
ax:instanceof<cartopy.mpl.geoaxes.GeoAxes>or<cartopy.mpl.geoaxes.GeoAxesSubplot>- A subclass of
matplotlib.axes.Axeswhich represents a map Projection. The map should be set at a particular Cartopy projection. color:str, default=’black’- The colour of the transform lines. By default, it is set to black.
**kwargs- Keyword arguments for parameters such as
alpha, etc. for plotting transform geometries. SeeMatplotlibkeyword arguments here.
Returns
ax:instanceof<geopandas.GeoDataFrame.plot>- A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with transform features plotted onto the chosen map projection.
Expand source code
def plot_transforms(self, ax, color='black', **kwargs): """Plot reconstructed transform boundary polylines onto a standard map. Notes ----- The transform sections for plotting are accessed from the `PlotTopologies` object's `transforms` attribute. These `transforms` are reconstructed to the `time` passed to the `PlotTopologies` object and converted into Shapely polylines. The reconstructed `transforms` are plotted onto the GeoAxes or GeoAxesSubplot map `ax` using GeoPandas. Map presentation details (e.g. `facecolor`, `edgecolor`, `alpha`…) are permitted as keyword arguments. Transform geometries are wrapped to the dateline using pyGPlates' [DateLineWrapper](https://www.gplates.org/docs/pygplates/generated/pygplates.datelinewrapper) by splitting a polyline into multiple polylines at the dateline. This is to avoid horizontal lines being formed between polylines at longitudes of -180 and 180 degrees. Point features near the poles (-89 & 89 degree latitude) are also clipped to ensure compatibility with Cartopy. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. color : str, default=’black’ The colour of the transform lines. By default, it is set to black. **kwargs : Keyword arguments for parameters such as `alpha`, etc. for plotting transform geometries. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with transform features plotted onto the chosen map projection. """ gdf = self.get_transforms() return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs) def plot_transitional_crusts(self, ax, color='black', **kwargs)-
Plot transitional crust on a standard map projection.
Parameters
ax:instanceof<cartopy.mpl.geoaxes.GeoAxes>or<cartopy.mpl.geoaxes.GeoAxesSubplot>- A subclass of
matplotlib.axes.Axeswhich represents a map Projection. The map should be set at a particular Cartopy projection. color:str, default=’black’- The colour of the trench lines. By default, it is set to black.
**kwargs- Keyword arguments for parameters such as
alpha, etc. for plotting trench geometries. SeeMatplotlibkeyword arguments here.
Returns
ax:instanceof<geopandas.GeoDataFrame.plot>- A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with transitional crust plotted onto the chosen map projection.
Expand source code
def plot_transitional_crusts(self, ax, color='black', **kwargs): """Plot transitional crust on a standard map projection. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. color : str, default=’black’ The colour of the trench lines. By default, it is set to black. **kwargs : Keyword arguments for parameters such as `alpha`, etc. for plotting trench geometries. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with transitional crust plotted onto the chosen map projection. """ gdf = self.get_transitional_crusts() return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs) def plot_trenches(self, ax, color='black', **kwargs)-
Plot reconstructed subduction trench polylines onto a standard map Projection.
Notes
The trench sections for plotting are accessed from the
PlotTopologiesobject'strenchesattribute. Thesetrenchesare reconstructed to thetimepassed to thePlotTopologiesobject and converted into Shapely polylines. The reconstructedtrenchesare plotted onto the GeoAxes or GeoAxesSubplot mapaxusing GeoPandas. Map presentation details (e.g.facecolor,edgecolor,alpha…) are permitted as keyword arguments.Trench geometries are wrapped to the dateline using pyGPlates' DateLineWrapper by splitting a polyline into multiple polylines at the dateline. This is to avoid horizontal lines being formed between polylines at longitudes of -180 and 180 degrees. Point features near the poles (-89 & 89 degree latitude) are also clipped to ensure compatibility with Cartopy.
Parameters
ax:instanceof<cartopy.mpl.geoaxes.GeoAxes>or<cartopy.mpl.geoaxes.GeoAxesSubplot>- A subclass of
matplotlib.axes.Axeswhich represents a map Projection. The map should be set at a particular Cartopy projection. color:str, default=’black’- The colour of the trench lines. By default, it is set to black.
**kwargs- Keyword arguments for parameters such as
alpha, etc. for plotting trench geometries. SeeMatplotlibkeyword arguments here.
Returns
ax:instanceof<geopandas.GeoDataFrame.plot>- A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with transform features plotted onto the chosen map projection.
Expand source code
def plot_trenches(self, ax, color='black', **kwargs): """Plot reconstructed subduction trench polylines onto a standard map Projection. Notes ----- The trench sections for plotting are accessed from the `PlotTopologies` object's `trenches` attribute. These `trenches` are reconstructed to the `time` passed to the `PlotTopologies` object and converted into Shapely polylines. The reconstructed `trenches` are plotted onto the GeoAxes or GeoAxesSubplot map `ax` using GeoPandas. Map presentation details (e.g. `facecolor`, `edgecolor`, `alpha`…) are permitted as keyword arguments. Trench geometries are wrapped to the dateline using pyGPlates' [DateLineWrapper](https://www.gplates.org/docs/pygplates/generated/pygplates.datelinewrapper) by splitting a polyline into multiple polylines at the dateline. This is to avoid horizontal lines being formed between polylines at longitudes of -180 and 180 degrees. Point features near the poles (-89 & 89 degree latitude) are also clipped to ensure compatibility with Cartopy. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. color : str, default=’black’ The colour of the trench lines. By default, it is set to black. **kwargs : Keyword arguments for parameters such as `alpha`, etc. for plotting trench geometries. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with transform features plotted onto the chosen map projection. """ gdf = self.get_trenches() return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs) def plot_unclassified_features(self, ax, color='black', **kwargs)-
Plot GPML unclassified features on a standard map projection.
Parameters
ax:instanceof<cartopy.mpl.geoaxes.GeoAxes>or<cartopy.mpl.geoaxes.GeoAxesSubplot>- A subclass of
matplotlib.axes.Axeswhich represents a map Projection. The map should be set at a particular Cartopy projection. color:str, default=’black’- The colour of the trench lines. By default, it is set to black.
**kwargs- Keyword arguments for parameters such as
alpha, etc. for plotting trench geometries. SeeMatplotlibkeyword arguments here.
Returns
ax:instanceof<geopandas.GeoDataFrame.plot>- A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with unclassified features plotted onto the chosen map projection.
Expand source code
def plot_unclassified_features(self, ax, color='black', **kwargs): """Plot GPML unclassified features on a standard map projection. Parameters ---------- ax : instance of <cartopy.mpl.geoaxes.GeoAxes> or <cartopy.mpl.geoaxes.GeoAxesSubplot> A subclass of `matplotlib.axes.Axes` which represents a map Projection. The map should be set at a particular Cartopy projection. color : str, default=’black’ The colour of the trench lines. By default, it is set to black. **kwargs : Keyword arguments for parameters such as `alpha`, etc. for plotting trench geometries. See `Matplotlib` keyword arguments [here](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html). Returns ------- ax : instance of <geopandas.GeoDataFrame.plot> A standard cartopy.mpl.geoaxes.GeoAxes or cartopy.mpl.geoaxes.GeoAxesSubplot map with unclassified features plotted onto the chosen map projection. """ gdf = self.get_unclassified_features() return gdf.plot(ax=ax, facecolor='none', edgecolor=color, transform=self.base_projection, **kwargs) def update_time(self, time)-
Re-reconstruct features and topologies to the time specified by the
PlotTopologiestimeattribute whenever it or the anchor plate is updated.Notes
The following
PlotTopologiesattributes are updated whenever a reconstructiontimeattribute is set:- resolved topology features (topological plates and networks)
- ridge and transform boundary sections (resolved features)
- ridge boundary sections (resolved features)
- transform boundary sections (resolved features)
- subduction boundary sections (resolved features)
- left subduction boundary sections (resolved features)
- right subduction boundary sections (resolved features)
- other boundary sections (resolved features) that are not subduction zones or mid-ocean ridges (ridge/transform)
Moreover, coastlines, continents and COBs are reconstructed to the new specified
time.Expand source code
def update_time(self, time): """Re-reconstruct features and topologies to the time specified by the `PlotTopologies` `time` attribute whenever it or the anchor plate is updated. Notes ----- The following `PlotTopologies` attributes are updated whenever a reconstruction `time` attribute is set: - resolved topology features (topological plates and networks) - ridge and transform boundary sections (resolved features) - ridge boundary sections (resolved features) - transform boundary sections (resolved features) - subduction boundary sections (resolved features) - left subduction boundary sections (resolved features) - right subduction boundary sections (resolved features) - other boundary sections (resolved features) that are not subduction zones or mid-ocean ridges (ridge/transform) Moreover, coastlines, continents and COBs are reconstructed to the new specified `time`. """ self._time = float(time) resolved_topologies = ptt.resolve_topologies.resolve_topologies_into_features( self.plate_reconstruction.rotation_model, self.plate_reconstruction.topology_features, self.time) self.topologies, self.ridge_transforms, self.ridges, self.transforms, self.trenches, self.trench_left, self.trench_right, self.other = resolved_topologies # miscellaneous boundaries self.continental_rifts = [] self.faults = [] self.fracture_zones = [] self.inferred_paleo_boundaries = [] self.terrane_boundaries = [] self.transitional_crusts = [] self.orogenic_belts = [] self.sutures = [] self.continental_crusts = [] self.extended_continental_crusts = [] self.passive_continental_boundaries = [] self.slab_edges = [] self.misc_transforms = [] self.unclassified_features = [] for topol in self.other: if topol.get_feature_type() == pygplates.FeatureType.gpml_continental_rift: self.continental_rifts.append(topol) elif topol.get_feature_type() == pygplates.FeatureType.gpml_fault: self.faults.append(topol) elif topol.get_feature_type() == pygplates.FeatureType.gpml_fracture_zone: self.fracture_zones.append(topol) elif topol.get_feature_type() == pygplates.FeatureType.gpml_inferred_paleo_boundary: self.inferred_paleo_boundaries.append(topol) elif topol.get_feature_type() == pygplates.FeatureType.gpml_terrane_boundary: self.terrane_boundaries.append(topol) elif topol.get_feature_type() == pygplates.FeatureType.gpml_transitional_crust: self.transitional_crusts.append(topol) elif topol.get_feature_type() == pygplates.FeatureType.gpml_orogenic_belt: self.orogenic_belts.append(topol) elif topol.get_feature_type() == pygplates.FeatureType.gpml_suture: self.sutures.append(topol) elif topol.get_feature_type() == pygplates.FeatureType.gpml_continental_crust: self.continental_crusts.append(topol) elif topol.get_feature_type() == pygplates.FeatureType.gpml_extended_continental_crust: self.extended_continental_crusts.append(topol) elif topol.get_feature_type() == pygplates.FeatureType.gpml_passive_continental_boundary: self.passive_continental_boundaries.append(topol) elif topol.get_feature_type() == pygplates.FeatureType.gpml_slab_edge: self.slab_edges.append(topol) elif topol.get_feature_type() == pygplates.FeatureType.gpml_transform: self.misc_transforms.append(topol) elif topol.get_feature_type() == pygplates.FeatureType.gpml_unclassified_feature: self.unclassified_features.append(topol) # reconstruct other important polygons and lines if self._coastlines: self.coastlines = self.plate_reconstruction.reconstruct( self._coastlines, self.time, from_time=0, anchor_plate_id=self.anchor_plate_id) if self._continents: self.continents = self.plate_reconstruction.reconstruct( self._continents, self.time, from_time=0, anchor_plate_id=self.anchor_plate_id) if self._COBs: self.COBs = self.plate_reconstruction.reconstruct( self._COBs, self.time, from_time=0, anchor_plate_id=self.anchor_plate_id)