mtpy.modeling.simpeg package
Subpackages
- mtpy.modeling.simpeg.recipes package
- Submodules
- mtpy.modeling.simpeg.recipes.inversion_1d module
Simpeg1DSimpeg1D.cull_from_difference()Simpeg1D.cull_from_interpolated()Simpeg1D.cull_from_model()Simpeg1D.dataSimpeg1D.data_errorSimpeg1D.frequenciesSimpeg1D.meshSimpeg1D.modeSimpeg1D.periodsSimpeg1D.plot_model_fitting()Simpeg1D.plot_response()Simpeg1D.run_fixed_layer_inversion()Simpeg1D.thicknesses
- mtpy.modeling.simpeg.recipes.inversion_2d module
Simpeg2DSimpeg2D.active_mapSimpeg2D.beta_scheduleSimpeg2D.conductivity_mapSimpeg2D.data_misfitSimpeg2D.directivesSimpeg2D.exponent_mapSimpeg2D.inverse_problemSimpeg2D.iterationsSimpeg2D.make_mesh()Simpeg2D.optimizationSimpeg2D.plot_iteration()Simpeg2D.plot_responses()Simpeg2D.plot_tikhonov_curve()Simpeg2D.reference_modelSimpeg2D.regularizationSimpeg2D.run_inversion()Simpeg2D.starting_betaSimpeg2D.target_misfitSimpeg2D.te_data_misfitSimpeg2D.te_simulationSimpeg2D.tm_data_misfitSimpeg2D.tm_simulation
- Module contents
Simpeg1DSimpeg1D.cull_from_difference()Simpeg1D.cull_from_interpolated()Simpeg1D.cull_from_model()Simpeg1D.dataSimpeg1D.data_errorSimpeg1D.frequenciesSimpeg1D.meshSimpeg1D.modeSimpeg1D.periodsSimpeg1D.plot_model_fitting()Simpeg1D.plot_response()Simpeg1D.run_fixed_layer_inversion()Simpeg1D.thicknesses
Simpeg2DSimpeg2D.active_mapSimpeg2D.beta_scheduleSimpeg2D.conductivity_mapSimpeg2D.data_misfitSimpeg2D.directivesSimpeg2D.exponent_mapSimpeg2D.inverse_problemSimpeg2D.iterationsSimpeg2D.make_mesh()Simpeg2D.optimizationSimpeg2D.plot_iteration()Simpeg2D.plot_responses()Simpeg2D.plot_tikhonov_curve()Simpeg2D.reference_modelSimpeg2D.regularizationSimpeg2D.run_inversion()Simpeg2D.starting_betaSimpeg2D.target_misfitSimpeg2D.te_data_misfitSimpeg2D.te_simulationSimpeg2D.tm_data_misfitSimpeg2D.tm_simulation
Submodules
mtpy.modeling.simpeg.data_2d module
Created on Fri Aug 9 12:11:57 2024
@author: jpeacock
- class mtpy.modeling.simpeg.data_2d.Simpeg2DData(dataframe, **kwargs)[source]
Bases:
object- property frequencies
frequencies from the data frame
- Returns:
DESCRIPTION
- Return type:
TYPE
- property invert_impedance
- property n_frequencies
- property n_stations
- plot_response(**kwargs)[source]
- Parameters:
**kwargs –
DESCRIPTION
- Returns:
DESCRIPTION
- Return type:
TYPE
- property station_locations
get station locations in utm geographic coordinates if True, otherwise will be in model coordinates.
- Parameters:
geographic (TYPE, optional) – DESCRIPTION, defaults to True
- Returns:
DESCRIPTION
- Return type:
TYPE
- property te_data
simpeg Data object
- Returns:
DESCRIPTION
- Return type:
TYPE
- property te_data_errors
- property te_observations
TE observations
- property te_survey
survey for TE mode (simpeg = “yx”)
- Returns:
DESCRIPTION
- Return type:
TYPE
- property tm_data
simpeg Data object
- Returns:
DESCRIPTION
- Return type:
TYPE
- property tm_data_errors
- property tm_observations
TM observations
- property tm_survey
survey for TM mode (simpeg = “xy”)
- Returns:
DESCRIPTION
- Return type:
TYPE
mtpy.modeling.simpeg.data_3d module
- class mtpy.modeling.simpeg.data_3d.Simpeg3DData(dataframe, **kwargs)[source]
Bases:
object- property components_to_invert
get a list of components to invert base on user input
- property frequencies
unique frequencies from the dataframe
- from_simpeg_data_object(data_object)[source]
ingest a Simpeg.data.Data object into a dataframe
- Parameters:
data_object (_type_) – _description_
- get_survey(index)[source]
get a survey object for a particular frequency index
Useful for using MetaClass
- Parameters:
index (_type_) – _description_
- Returns:
_description_
- Return type:
_type_
- property n_frequencies
- property n_orientation
number of components to invert
- property n_stations
- property source_t_zx
zx source [simpeg zx -> nez+ zy]
- property source_t_zy
zy source [simpeg zy -> nez+ zx]
- property source_z_xx
xx source [simpeg xx -> nez+ yy]
- property source_z_xy
xy source [simpeg xy -> nez+ yx]
- property source_z_yx
yx source [simpeg yx -> nez+ xy]
- property source_z_yy
yy source [simpeg yy -> nez+ xx]
- property sources
- property station_locations
return just station locations in appropriate coordinates, default is geographic.
- property station_names
list of station names
- property survey
returns a survey object with the requested components
mtpy.modeling.simpeg.make_2d_mesh module
Created on Thu Nov 9 10:43:06 2023
@author: jpeacock
- class mtpy.modeling.simpeg.make_2d_mesh.QuadTreeMesh(station_locations, frequencies, **kwargs)[source]
Bases:
objectbuild a quad tree mesh based on station locations and frequencies to invert
dimensions are x for the lateral dimension and z for the vertical.
station locations should be offsets from a single point [offset, elevation]. should be shape [n, 2]
topography should be [x, z] -: [n, 2] and in station location coordinate system.
- property active_cell_index
return active cell mask
TODO: include topographic surface
- Returns:
DESCRIPTION
- Return type:
TYPE
- property dx
- property dz
- property number_of_active_cells
number of active cells
- property nx
- property nz
- property x_pad
- property x_total
get the total distance in the horizontal direction.
- property z_core
- property z_max
- property z_pad_down
- property z_pad_up
- property z_total
- class mtpy.modeling.simpeg.make_2d_mesh.StructuredMesh(station_locations: DataFrame, frequencies: ndarray[tuple[int, ...], dtype[_ScalarType_co]] | list[float], **kwargs)[source]
Bases:
object- property active_cell_index
return active cell mask
TODO: include topographic surface
- Returns:
DESCRIPTION
- Return type:
TYPE
- property dx: float
- property frequency_max: float
- property frequency_min: float
- property n_station_x_cells: int
- property n_x_padding: int
- property number_of_active_cells
number of active cells
- property station_total_length: float
- property x_padding_cells: float
- property z1_layer_thickness: float
- property z_bottom: float
- property z_mesh_down: ndarray[tuple[int, ...], dtype[float64]]
- property z_mesh_up: ndarray[tuple[int, ...], dtype[float64]]
Module contents
Created on Wed Nov 1 11:58:31 2023
@author: jpeacock