def update_additional_data(model: Model,
update_structure=True,
update_kriging=True):
warnings.warn(
'This function is going to be deprecated. Use Model.update_additional_data instead',
DeprecationWarning)
return model.update_additional_data(update_structure, update_kriging)
def set_interpolator(geo_model: Model, output: list = None, compile_theano: bool = True,
theano_optimizer=None, verbose: list = None, grid=None, type_=None,
update_structure=True, update_kriging=True,
**kwargs):
"""
Method to create a graph and compile the theano code to compute the interpolation.
Args:
geo_model (:class:`gempy.core.model.Project`): [s0]
output (list[str:{geo, grav}]): type of interpolation.
compile_theano (bool): [s1]
theano_optimizer (str {'fast_run', 'fast_compile'}): [s2]
verbose:
update_kriging (bool): reset kriging values to its default.
update_structure (bool): sync Structure instance before setting theano graph.
Keyword Args:
- pos_density (Optional[int]): Only necessary when type='grav'. Location on the Surfaces().df
where density is located (starting on id being 0).
- Vs
- pos_magnetics
Returns:
"""
# output = list(output)
if output is None:
output = ['geology']
if type(output) is not list:
raise TypeError('Output must be a list.')
# TODO Geology is necessary for everthing?
if 'gravity' in output and 'geology' not in output:
output.append('geology')
if 'magnetics' in output and 'geology' not in output:
output.append('geology')
if type_ is not None:
warnings.warn('type warn is going to be deprecated. Use output insted', FutureWarning)
output = type_
if theano_optimizer is not None:
geo_model._additional_data.options.df.at['values', 'theano_optimizer'] = theano_optimizer
if verbose is not None:
geo_model._additional_data.options.df.at['values', 'verbosity'] = verbose
if 'dtype' in kwargs:
geo_model._additional_data.options.df.at['values', 'dtype'] = kwargs['dtype']
if 'device' in kwargs:
geo_model._additional_data.options.df.at['values', 'device'] = kwargs['device']
# TODO add kwargs
geo_model._rescaling.rescale_data()
geo_model.update_additional_data(update_structure=update_structure, update_kriging=update_kriging)
geo_model.update_to_interpolator()
geo_model._surface_points.sort_table()
geo_model._orientations.sort_table()
geo_model._interpolator.create_theano_graph(geo_model._additional_data, inplace=True,
output=output, **kwargs)
if 'gravity' in output:
pos_density = kwargs.get('pos_density', 1)
tz = kwargs.get('tz', 'auto')
if geo_model._grid.centered_grid is not None:
geo_model._interpolator.set_theano_shared_gravity(tz, pos_density)
if 'magnetics' in output:
pos_magnetics = kwargs.get('pos_magnetics', 1)
Vs = kwargs.get('Vs', 'auto')
incl = kwargs.get('incl')
decl = kwargs.get('decl')
B_ext = kwargs.get('B_ext', 52819.8506939139e-9)
if geo_model._grid.centered_grid is not None:
geo_model._interpolator.set_theano_shared_magnetics(Vs, pos_magnetics, incl, decl, B_ext)
if 'topology' in output:
# This id is necessary for topology
id_list = geo_model._surfaces.df.groupby('isFault').cumcount() + 1
geo_model.add_surface_values(id_list, 'topology_id')
geo_model._interpolator.set_theano_shared_topology()
# TODO it is missing to pass to theano the position of topology_id
if compile_theano is True:
geo_model._interpolator.set_all_shared_parameters(reset_ctrl=True)
geo_model._interpolator.compile_th_fn_geo(inplace=True, grid=grid)
else:
if grid == 'shared':
geo_model._interpolator.set_theano_shared_grid(grid)
print('Kriging values: \n', geo_model._additional_data.kriging_data)
return geo_model._interpolator
