harmonica.prism_layer#
- harmonica.prism_layer(coordinates, surface, reference, properties=None)[source]#
Create a layer of prisms of equal size
Build a regular grid of prisms of equal size on the horizontal directions with variable top and bottom boundaries and properties like density, magnetization, etc. The function returns a
xarray.Dataset
containingeasting
,northing
,top
andbottom
coordinates, and all physical properties asdata_var
s. Theeasting
andnorthing
coordinates correspond to the location of the center of each prism.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. SeeDatasetAccessorPrismLayer
for the definition of these methods and attributes.- Parameters:
- coordinates
tuple
List containing the coordinates of the centers of the prisms in the following order:
easting
,northing
. The arrays must be 1d arrays containing the coordinates of the centers per axis, or could be 2d arrays as the ones returned bynumpy.meshgrid
. All coordinates should be in meters and should define a regular grid.- surface2d-array
Array used to create the uppermost boundary of the prisms layer. All heights should be in meters. On every point where
surface
is belowreference
, thesurface
value will be used to set thebottom
boundary of that prism, while thereference
value will be used to set thetop
boundary of the prism.- reference
float
or 2d-array Reference surface used to create the lowermost boundary of the prisms layer. It can be either a plane or an irregular surface passed as 2d array. Height(s) must be in meters.
- properties
dict
orNone
Dictionary containing the physical properties of the prisms. The keys must be strings that will be used to name the corresponding
data_var
inside thexarray.Dataset
, while the values must be 2d-arrays. All physical properties must be passed in SI units. If None, nodata_var
will be added to thexarray.Dataset
. Default is None.
- coordinates
- Returns:
- dataset
xarray.Dataset
Dataset containing the coordinates of the center of each prism, the height of its top and bottom boundaries and its corresponding physical properties.
- dataset
See also
Examples
>>> # Create a synthetic relief >>> import numpy as np >>> easting = np.linspace(0, 10, 5) >>> northing = np.linspace(2, 8, 4) >>> surface = np.arange(20, dtype=float).reshape((4, 5)) >>> density = 2670.0 * np.ones_like(surface) >>> # Define a layer of prisms >>> prisms = prism_layer( ... (easting, northing), ... surface, ... reference=0, ... properties={"density": density}, ... ) >>> print(prisms) <xarray.Dataset> Dimensions: (northing: 4, easting: 5) Coordinates: * easting (easting) float64 0.0 2.5 5.0 7.5 10.0 * northing (northing) float64 2.0 4.0 6.0 8.0 top (northing, easting) float64 0.0 1.0 2.0 3.0 ... 17.0 18.0 19.0 bottom (northing, easting) float64 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 Data variables: density (northing, easting) float64 2.67e+03 2.67e+03 ... 2.67e+03 Attributes: coords_units: meters properties_units: SI >>> # Get the boundaries of the layer (will exceed the region) >>> boundaries = prisms.prism_layer.boundaries >>> list(float(b) for b in boundaries) [-1.25, 11.25, 1.0, 9.0] >>> # Get the boundaries of one of the prisms >>> prism = prisms.prism_layer.get_prism((0, 2)) >>> list(float(b) for b in prism) [3.75, 6.25, 1.0, 3.0, 0.0, 2.0]
Examples using harmonica.prism_layer
#
Gravitational effect of topography