Rename prisms_layer for prism_layer (#223)

Also rename the xarray accessor to DatasetAccessorPrismLayer

doc/api/index.rst

@@ -35,8 +35,8 @@ Forward modelling
  point_mass_gravity
  prism_gravity
  tesseroid_gravity
- prisms_layer
- DatasetAccessorPrismsLayer
+ prism_layer
+ DatasetAccessorPrismLayer
 
 Isostasy
 --------

examples/forward/prisms_layer.py → examples/forward/prism_layer.py

@@ -10,7 +10,7 @@
 
 One way to model three dimensional structures is to create a set of prisms that
 approximates their geometry and its physical properties (density,
-susceptibility, etc.). The :func:`harmonica.prisms_layer` offers a simple way
+susceptibility, etc.). The :func:`harmonica.prism_layer` offers a simple way
 to create a layer of prisms: a regular grid of prisms of equal size on the
 horizontal directions with variable top and bottom boundaries. It returns
 a :class:`xarray.Dataset` with the coordinates of the centers of the prisms and
@@ -33,7 +33,7 @@
 (easting, northing) = vd.grid_coordinates(region=region, spacing=spacing)
 surface = 100 * np.exp(-((easting - 50e3) ** 2 + northing ** 2) / 1e9)
 density = 2670.0 * np.ones_like(surface)
-prisms = hm.prisms_layer(
+prisms = hm.prism_layer(
  coordinates=(easting[0, :], northing[:, 0]),
  surface=surface,
  reference=0,
@@ -42,7 +42,7 @@
 
 # Compute gravity field of prisms on a regular grid of observation points
 coordinates = vd.grid_coordinates(region, spacing=spacing, extra_coords=1e3)
-gravity = prisms.prisms_layer.gravity(coordinates, field="g_z")
+gravity = prisms.prism_layer.gravity(coordinates, field="g_z")
 
 # Plot gravity field
 plt.pcolormesh(*coordinates[:2], gravity)

examples/forward/prisms_topo_gravity.py

@@ -8,7 +8,7 @@
 Gravitational effect of topography
 ==================================
 
-One possible application of the :func:`harmonica.prisms_layer` function is to
+One possible application of the :func:`harmonica.prism_layer` function is to
 create a model of the terrain and compute its gravity effect. Here we will use
 a regular grid of topographic and bathymetric heights for South Africa to
 create a prisms layer that model the terrain with a density of 2670 kg/m^3 and
@@ -43,7 +43,7 @@
 density = density.where(south_africa_topo >= 0, 1000 - 2900)
 
 # Create layer of prisms
-prisms = hm.prisms_layer(
+prisms = hm.prism_layer(
  (south_africa_topo.easting, south_africa_topo.northing),
  surface=south_africa_topo.values,
  reference=0,
@@ -56,7 +56,7 @@
 )
 easting, northing = projection(*coordinates[:2])
 coordinates_projected = (easting, northing, coordinates[-1])
-prisms_gravity = prisms.prisms_layer.gravity(coordinates_projected, field="g_z")
+prisms_gravity = prisms.prism_layer.gravity(coordinates_projected, field="g_z")
 
 # Make a plot of the computed gravity
 plt.figure(figsize=(8, 8))

harmonica/__init__.py

@@ -15,7 +15,7 @@
 from .forward.point_mass import point_mass_gravity
 from .forward.tesseroid import tesseroid_gravity
 from .forward.prism import prism_gravity
-from .forward.prisms_layer import prisms_layer, DatasetAccessorPrismsLayer
+from .forward.prism_layer import prism_layer, DatasetAccessorPrismLayer
 from .equivalent_layer.harmonic import EQLHarmonic
 from .equivalent_layer.harmonic_spherical import EQLHarmonicSpherical
 

harmonica/forward/prisms_layer.py → harmonica/forward/prism_layer.py

@@ -15,7 +15,7 @@
 from .prism import prism_gravity
 
 
-def prisms_layer(
+def prism_layer(
  coordinates,
  surface,
  reference,
@@ -32,7 +32,7 @@ def prisms_layer(
  ``northing`` coordinates correspond to the location of the center of each
  prism.
 
- The ``prisms_layer`` dataset accessor can be used to access special methods
+ The ``prism_layer`` dataset accessor can be used to access special methods
  and attributes for the layer of prisms, like the horizontal dimensions of
  the prisms, getting the boundaries of each prisms, etc.
  See :class:`XarrayAcessorPrismLayer` for the definition of these methods
@@ -85,7 +85,7 @@ def prisms_layer(
  >>> surface = np.arange(20, dtype=float).reshape((4, 5))
  >>> density = 2670.0 * np.ones_like(surface)
  >>> # Define a layer of prisms
- >>> prisms = prisms_layer(
+ >>> prisms = prism_layer(
  ... (easting, northing),
  ... surface,
  ... reference=0,
@@ -105,10 +105,10 @@ def prisms_layer(
  coords_units: meters
  properties_units: SI
  >>> # Get the boundaries of the layer (will exceed the region)
- >>> print(prisms.prisms_layer.boundaries)
+ >>> print(prisms.prism_layer.boundaries)
  (-1.25, 11.25, 1.0, 9.0)
  >>> # Get the boundaries of one of the prisms
- >>> print(prisms.prisms_layer.get_prism((0, 2)))
+ >>> print(prisms.prism_layer.get_prism((0, 2)))
  (3.75, 6.25, 1.0, 3.0, 0.0, 2.0)
  """ # noqa: W505
  dims = ("northing", "easting")
@@ -128,7 +128,7 @@ def prisms_layer(
  attrs = {"coords_units": "meters", "properties_units": "SI"}
  prisms.attrs = attrs
  # Create the top and bottom coordinates of the prisms
- prisms.prisms_layer.update_top_bottom(surface, reference)
+ prisms.prism_layer.update_top_bottom(surface, reference)
  return prisms
 
 
@@ -146,20 +146,20 @@ def _check_regular_grid(easting, northing):
  raise ValueError("Passed northing coordiantes are not evenly spaced.")
 
 
-@xr.register_dataset_accessor("prisms_layer")
-class DatasetAccessorPrismsLayer:
+@xr.register_dataset_accessor("prism_layer")
+class DatasetAccessorPrismLayer:
  """
  Defines dataset accessor for layer of prisms
 
  .. warning::
 
  This class is not intended to be initialized.
- Use the `prisms_layer` accessor for accessing the methods and
+ Use the `prism_layer` accessor for accessing the methods and
  attributes of this class.
 
  See also
  --------
- harmonica.prisms_layer
+ harmonica.prism_layer
  """
 
  def __init__(self, xarray_obj):