gstools.field.SRF¶
- class gstools.field.SRF(model, mean=0.0, normalizer=None, trend=None, upscaling='no_scaling', generator='RandMeth', **generator_kwargs)[source]¶
Bases:
gstools.field.base.Field
A class to generate spatial random fields (SRF).
- Parameters
model (
CovModel
) – Covariance Model of the spatial random field.mean (
float
orcallable
, optional) – Mean of the SRF (in normal form). Could also be a callable. The default is 0.0.normalizer (
None
orNormalizer
, optional) – Normalizer to be applied to the SRF to transform the field values. The default is None.trend (
None
orfloat
orcallable
, optional) – Trend of the SRF (in transformed form). If no normalizer is applied, this behaves equal to ‘mean’. The default is None.upscaling (
str
, optional) –Method to be used for upscaling the variance at each point depending on the related element volume. See the
point_volumes
keyword in theSRF.__call__
routine. At the moment, the following upscaling methods are provided:”no_scaling” : No upscaling is applied to the variance. See:
var_no_scaling
”coarse_graining” : A volume depended variance is calculated by the upscaling technique coarse graining. See:
var_coarse_graining
Default: “no_scaling”
generator (
str
, optional) –Name of the field generator to be used. At the moment, the following generators are provided:
”RandMeth” : The Randomization Method. See:
RandMeth
”IncomprRandMeth” : The incompressible Randomization Method. This is the original algorithm proposed by Kraichnan 1970 See:
IncomprRandMeth
”VectorField” : an alias for “IncomprRandMeth”
”VelocityField” : an alias for “IncomprRandMeth”
Default: “RandMeth”
**generator_kwargs – Keyword arguments that are forwarded to the generator in use. Have a look at the provided generators for further information.
- Attributes
dim
int
: Dimension of the field.generator
callable
: The generator of the field.latlon
bool
: Whether the field depends on geographical coords.mean
model
CovModel
: The covariance model of the field.name
str
: The name of the class.normalizer
Normalizer
: Normalizer of the field.trend
upscaling
str
: Name of the upscaling method.value_type
str
: Type of the field values (scalar, vector).
Methods
__call__
(pos[, seed, point_volumes, mesh_type])Generate the spatial random field.
mesh
(mesh[, points, direction, name])Generate a field on a given meshio, ogs5py or PyVista mesh.
plot
([field, fig, ax])Plot the spatial random field.
post_field
(field[, name, process, save])Postprocessing field values.
pre_pos
(pos[, mesh_type])Preprocessing positions and mesh_type.
set_generator
(generator, **generator_kwargs)Set the generator for the field.
structured
(*args, **kwargs)Generate a field on a structured mesh.
to_pyvista
([field_select, fieldname])Create a VTK/PyVista grid of the stored field.
unstructured
(*args, **kwargs)Generate a field on an unstructured mesh.
upscaling_func
(*args, **kwargs)Upscaling method applied to the field variance.
vtk_export
(filename[, field_select, fieldname])Export the stored field to vtk.
- __call__(pos, seed=nan, point_volumes=0.0, mesh_type='unstructured')[source]¶
Generate the spatial random field.
The field is saved as self.field and is also returned.
- Parameters
pos (
list
) – the position tuple, containing main direction and transversal directionsseed (
int
, optional) – seed for RNG for reseting. Default: keep seed from generatorpoint_volumes (
float
ornumpy.ndarray
) – If your evaluation points for the field are coming from a mesh, they are probably representing a certain element volume. This volume can be passed by point_volumes to apply the given variance upscaling. If point_volumes is0
nothing is changed. Default:0
mesh_type (
str
) – ‘structured’ / ‘unstructured’
- Returns
field – the SRF
- Return type
- mesh(mesh, points='centroids', direction='all', name='field', **kwargs)¶
Generate a field on a given meshio, ogs5py or PyVista mesh.
- Parameters
mesh (meshio.Mesh or ogs5py.MSH or PyVista mesh) – The given mesh
points (
str
, optional) – The points to evaluate the field at. Either the “centroids” of the mesh cells (calculated as mean of the cell vertices) or the “points” of the given mesh. Default: “centroids”direction (
str
orlist
, optional) – Here you can state which direction should be choosen for lower dimension. For example, if you got a 2D mesh in xz direction, you have to pass “xz”. By default, all directions are used. One can also pass a list of indices. Default: “all”name (
str
orlist
ofstr
, optional) – Name(s) to store the field(s) in the given mesh as point_data or cell_data. If to few names are given, digits will be appended. Default: “field”**kwargs – Keyword arguments forwarded to
__call__
.
Notes
This will store the field in the given mesh under the given name, if a meshio or PyVista mesh was given.
- See:
- plot(field='field', fig=None, ax=None, **kwargs)¶
Plot the spatial random field.
- Parameters
field (
str
, optional) – Field that should be plotted. Default: “field”fig (
Figure
orNone
) – Figure to plot the axes on. If None, a new one will be created. Default: Noneax (
Axes
orNone
) – Axes to plot on. If None, a new one will be added to the figure. Default: None**kwargs – Forwarded to the plotting routine.
- post_field(field, name='field', process=True, save=True)¶
Postprocessing field values.
- Parameters
field (
numpy.ndarray
) – Field values.name (
str
, optional) – Name. to store the field. The default is “field”.process (
bool
, optional) – Whether to process field to apply mean, normalizer and trend. The default is True.save (
bool
, optional) – Whether to store the field under the given name. The default is True.
- Returns
field – Processed field values.
- Return type
- pre_pos(pos, mesh_type='unstructured')¶
Preprocessing positions and mesh_type.
- Parameters
- Returns
iso_pos ((d, n),
numpy.ndarray
) – the isometrized position tupleshape (
tuple
) – Shape of the resulting field.
- set_generator(generator, **generator_kwargs)[source]¶
Set the generator for the field.
- Parameters
generator (
str
, optional) – Name of the generator to use for field generation. Default: “RandMeth”**generator_kwargs – keyword arguments that are forwarded to the generator in use.
- to_pyvista(field_select='field', fieldname='field')¶
Create a VTK/PyVista grid of the stored field.
- vtk_export(filename, field_select='field', fieldname='field')¶
Export the stored field to vtk.
- Parameters
filename (
str
) – Filename of the file to be saved, including the path. Note that an ending (.vtr or .vtu) will be added to the name.field_select (
str
, optional) – Field that should be stored. Can be: “field”, “raw_field”, “krige_field”, “err_field” or “krige_var”. Default: “field”fieldname (
str
, optional) – Name of the field in the VTK file. Default: “field”
- property normalizer¶
Normalizer of the field.
- Type
- property upscaling¶
Name of the upscaling method.
See the
point_volumes
keyword in theSRF.__call__
routine. Default: “no_scaling”- Type