PyHydroGeophysX.Hydro_modular package

Submodules

PyHydroGeophysX.Hydro_modular.hydro_to_ert module

Module for converting hydrologic model output to ERT apparent resistivity.

PyHydroGeophysX.Hydro_modular.hydro_to_ert.hydro_to_ert(water_content: ndarray, porosity: ndarray, mesh: pygimli.Mesh, profile_interpolator: ProfileInterpolator, layer_idx: int | List[int], structure: ndarray, marker_labels: List[int], rho_parameters: Dict[str, Any], electrode_spacing: float = 1.0, electrode_start: float = 0.0, num_electrodes: int = 72, scheme_name: str = 'wa', noise_level: float = 0.05, abs_error: float = 0.0, rel_error: float = 0.05, save_path: str | None = None, mesh_markers: ndarray | None = None, verbose: bool = False, seed: int | None = None) → Tuple[pygimli.DataContainer, ndarray]

Convert hydrologic model output to ERT apparent resistivity.

This function performs the complete workflow from water content to synthetic ERT data: 1. Interpolates water content to mesh 2. Calculates saturation 3. Converts saturation to resistivity using petrophysical models 4. Creates electrode array along surface profile 5. Performs forward modeling to generate synthetic ERT data

Parameters:

• water_content – Water content array (nlay, ny, nx) or mesh values

• porosity – Porosity array (nlay, ny, nx) or mesh values

• mesh – PyGIMLI mesh

• profile_interpolator – ProfileInterpolator for surface interpolation

• marker_labels – Layer marker labels [top, middle, bottom]

• rho_parameters –

  Dictionary of resistivity parameters: {

  ’rho_sat’: [100, 500, 2400], # Saturated resistivity values ‘n’: [2.2, 1.8, 2.5], # Cementation exponents ‘sigma_s’: [1/500, 0, 0] # Surface conductivity values

  }

• electrode_spacing – Spacing between electrodes

• electrode_start – Starting position of electrode array

• num_electrodes – Number of electrodes

• scheme_name – ERT scheme name (‘wa’, ‘dd’, etc.)

• noise_level – Relative noise level for synthetic data

• abs_error – Absolute error for data estimation

• rel_error – Relative error for data estimation

• save_path – Path to save synthetic data (None = don’t save)

• mesh_markers – Mesh cell markers (None = get from mesh)

• verbose – Whether to display verbose information

• seed – Random seed for noise generation

Returns:

Tuple of (synthetic ERT data container, resistivity model)

PyHydroGeophysX.Hydro_modular.hydro_to_srt module

Module for converting hydrologic model output to seismic travel times.

PyHydroGeophysX.Hydro_modular.hydro_to_srt.hydro_to_srt(water_content: ndarray, porosity: ndarray, mesh: pygimli.Mesh, profile_interpolator: ProfileInterpolator, layer_idx: int | List[int], structure: ndarray, marker_labels: List[int], vel_parameters: Dict[str, Any], sensor_spacing: float = 1.0, sensor_start: float = 0.0, num_sensors: int = 72, shot_distance: float = 5, noise_level: float = 0.05, noise_abs: float = 1e-05, save_path: str | None = None, mesh_markers: ndarray | None = None, verbose: bool = False, seed: int | None = None) → Tuple[pygimli.DataContainer, ndarray]

Convert hydrologic model output to seismic travel times.

This function performs the complete workflow from water content to synthetic SRT data:

1. Interpolates water content to mesh

2. Calculates saturation

3. Converts saturation to seismic velocities using petrophysical models

4. Creates sensor array along surface profile

5. Performs forward modeling to generate synthetic travel time data

Parameters:

• water_content – Water content array (nlay, ny, nx) or mesh values

• porosity – Porosity array (nlay, ny, nx) or mesh values

• mesh – PyGIMLI mesh

• profile_interpolator – ProfileInterpolator for surface interpolation

• marker_labels – Layer marker labels [top, middle, bottom]

• vel_parameters – Dictionary of velocity parameters containing ‘top’: {‘bulk_modulus’: 30.0, ‘shear_modulus’: 20.0, ‘mineral_density’: 2650, ‘depth’: 1.0}, ‘mid’: {‘bulk_modulus’: 50.0, ‘shear_modulus’: 35.0, ‘mineral_density’: 2670, ‘aspect_ratio’: 0.05}, ‘bot’: {‘bulk_modulus’: 55.0, ‘shear_modulus’: 50.0, ‘mineral_density’: 2680, ‘aspect_ratio’: 0.03}

• sensor_spacing – Spacing between sensors

• sensor_start – Starting position of sensor array

• num_sensors – Number of sensors

• shot_distance – Distance between shot points

• noise_level – Relative noise level for synthetic data

• noise_abs – Absolute noise level for synthetic data

• save_path – Path to save synthetic data (None = don’t save)

• mesh_markers – Mesh cell markers (None = get from mesh)

• verbose – Whether to display verbose information

• seed – Random seed for noise generation

Returns:

Tuple of (synthetic SRT data container, velocity model)

Module contents

Hydro_modular package for hydrologic to geophysical conversion utilities.

PyHydroGeophysX.Hydro_modular.hydro_to_ert(water_content: ndarray, porosity: ndarray, mesh: pygimli.Mesh, profile_interpolator: ProfileInterpolator, layer_idx: int | List[int], structure: ndarray, marker_labels: List[int], rho_parameters: Dict[str, Any], electrode_spacing: float = 1.0, electrode_start: float = 0.0, num_electrodes: int = 72, scheme_name: str = 'wa', noise_level: float = 0.05, abs_error: float = 0.0, rel_error: float = 0.05, save_path: str | None = None, mesh_markers: ndarray | None = None, verbose: bool = False, seed: int | None = None) → Tuple[pygimli.DataContainer, ndarray]

Convert hydrologic model output to ERT apparent resistivity.

This function performs the complete workflow from water content to synthetic ERT data: 1. Interpolates water content to mesh 2. Calculates saturation 3. Converts saturation to resistivity using petrophysical models 4. Creates electrode array along surface profile 5. Performs forward modeling to generate synthetic ERT data

Parameters:

• water_content – Water content array (nlay, ny, nx) or mesh values

• porosity – Porosity array (nlay, ny, nx) or mesh values

• mesh – PyGIMLI mesh

• profile_interpolator – ProfileInterpolator for surface interpolation

• marker_labels – Layer marker labels [top, middle, bottom]

• rho_parameters –

  Dictionary of resistivity parameters: {

  ’rho_sat’: [100, 500, 2400], # Saturated resistivity values ‘n’: [2.2, 1.8, 2.5], # Cementation exponents ‘sigma_s’: [1/500, 0, 0] # Surface conductivity values

  }

• electrode_spacing – Spacing between electrodes

• electrode_start – Starting position of electrode array

• num_electrodes – Number of electrodes

• scheme_name – ERT scheme name (‘wa’, ‘dd’, etc.)

• noise_level – Relative noise level for synthetic data

• abs_error – Absolute error for data estimation

• rel_error – Relative error for data estimation

• save_path – Path to save synthetic data (None = don’t save)

• mesh_markers – Mesh cell markers (None = get from mesh)

• verbose – Whether to display verbose information

• seed – Random seed for noise generation

Returns:

Tuple of (synthetic ERT data container, resistivity model)

PyHydroGeophysX.Hydro_modular.hydro_to_srt(water_content: ndarray, porosity: ndarray, mesh: pygimli.Mesh, profile_interpolator: ProfileInterpolator, layer_idx: int | List[int], structure: ndarray, marker_labels: List[int], vel_parameters: Dict[str, Any], sensor_spacing: float = 1.0, sensor_start: float = 0.0, num_sensors: int = 72, shot_distance: float = 5, noise_level: float = 0.05, noise_abs: float = 1e-05, save_path: str | None = None, mesh_markers: ndarray | None = None, verbose: bool = False, seed: int | None = None) → Tuple[pygimli.DataContainer, ndarray]

Convert hydrologic model output to seismic travel times.

This function performs the complete workflow from water content to synthetic SRT data:

1. Interpolates water content to mesh

2. Calculates saturation

3. Converts saturation to seismic velocities using petrophysical models

4. Creates sensor array along surface profile

5. Performs forward modeling to generate synthetic travel time data

Parameters:

• water_content – Water content array (nlay, ny, nx) or mesh values

• porosity – Porosity array (nlay, ny, nx) or mesh values

• mesh – PyGIMLI mesh

• profile_interpolator – ProfileInterpolator for surface interpolation

• marker_labels – Layer marker labels [top, middle, bottom]

• vel_parameters – Dictionary of velocity parameters containing ‘top’: {‘bulk_modulus’: 30.0, ‘shear_modulus’: 20.0, ‘mineral_density’: 2650, ‘depth’: 1.0}, ‘mid’: {‘bulk_modulus’: 50.0, ‘shear_modulus’: 35.0, ‘mineral_density’: 2670, ‘aspect_ratio’: 0.05}, ‘bot’: {‘bulk_modulus’: 55.0, ‘shear_modulus’: 50.0, ‘mineral_density’: 2680, ‘aspect_ratio’: 0.03}

• sensor_spacing – Spacing between sensors

• sensor_start – Starting position of sensor array

• num_sensors – Number of sensors

• shot_distance – Distance between shot points

• noise_level – Relative noise level for synthetic data

• noise_abs – Absolute noise level for synthetic data

• save_path – Path to save synthetic data (None = don’t save)

• mesh_markers – Mesh cell markers (None = get from mesh)

• verbose – Whether to display verbose information

• seed – Random seed for noise generation

Returns:

Tuple of (synthetic SRT data container, velocity model)