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Eqs default depth bug #91

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Oct 3, 2024
Merged

Eqs default depth bug #91

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acec795
fix: enable `default` eq source depth for regional constraints
mdtanker Oct 3, 2024
2557889
fix: fixes error of using 1x not 4.5x default depth for eq sources
mdtanker Oct 3, 2024
fda0f27
docs: update and rerun docs
mdtanker Oct 3, 2024
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1,262 changes: 441 additions & 821 deletions docs/gallery/bishop_basement_model.ipynb
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601 changes: 303 additions & 298 deletions docs/gallery/uieda_et_al_2017_CRUST1.ipynb
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211 changes: 108 additions & 103 deletions docs/gallery/uieda_et_al_2017_synthetic.ipynb
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800 changes: 256 additions & 544 deletions docs/user_guide/adhering_to_constraints.ipynb
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5,950 changes: 5,078 additions & 872 deletions docs/user_guide/combining_it_all.ipynb
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829 changes: 444 additions & 385 deletions docs/user_guide/damping_cross_validation.ipynb
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388 changes: 233 additions & 155 deletions docs/user_guide/density_cross_validation.ipynb
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85 changes: 47 additions & 38 deletions docs/user_guide/discretization.ipynb
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4,087 changes: 2,491 additions & 1,596 deletions docs/user_guide/estimating_regional_field.ipynb
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761 changes: 398 additions & 363 deletions docs/user_guide/including_starting_model.ipynb
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480 changes: 299 additions & 181 deletions docs/user_guide/reference_level_cross_validation.ipynb
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5,891 changes: 4,597 additions & 1,294 deletions docs/user_guide/regional_field_hyperparameters.ipynb
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1,359 changes: 1,049 additions & 310 deletions docs/user_guide/simple_inversion.ipynb
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894 changes: 391 additions & 503 deletions docs/user_guide/uncertainty_analysis.ipynb
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947 changes: 23 additions & 924 deletions docs/user_guide/variable_density_contrast.ipynb
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12 changes: 6 additions & 6 deletions src/invert4geom/optimization.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1768,7 +1768,7 @@ def __call__(self, trial: optuna.trial) -> float:
depth = kwargs.pop("depth", "default")
# calculate 4.5 times the mean distance between points
if depth == "default":
depth = np.mean(
depth = 4.5 * np.mean(
vd.median_distance(
(kwargs.get("coordinates")[0], kwargs.get("coordinates")[1]), # type: ignore[unused-ignore, index]
k_nearest=1,
Expand Down Expand Up @@ -1977,7 +1977,7 @@ def optimize_eq_source_params(
log.warning(msg)
best_depth = "default"
if best_depth == "default":
best_depth = np.mean(
best_depth = 4.5 * np.mean(
vd.median_distance((coordinates[0], coordinates[1]), k_nearest=1)
)
if best_block_size is None:
Expand Down Expand Up @@ -2376,7 +2376,7 @@ def __call__(self, trial: optuna.trial) -> float:
eq_depth = self.kwargs.get("depth", "default")
if eq_depth == "default":
# calculate 4.5 times the mean distance between points
eq_depth = np.mean(
eq_depth = 4.5 * np.mean(
vd.median_distance(
(self.training_df.easting, self.training_df.northing),
k_nearest=1,
Expand Down Expand Up @@ -2429,7 +2429,7 @@ def __call__(self, trial: optuna.trial) -> float:
eq_depth = self.kwargs.get("depth", "default")
if eq_depth == "default":
# calculate 4.5 times the mean distance between points
eq_depth = np.mean(
eq_depth = 4.5 * np.mean(
vd.median_distance(
(
self.training_df[i].easting,
Expand Down Expand Up @@ -2941,7 +2941,7 @@ def optimize_regional_eq_sources(
depth = best_trial.params.get("depth", kwargs.pop("depth", "default"))
if depth == "default":
# calculate 4.5 times the mean distance between points
depth = np.mean(
depth = 4.5 * np.mean(
vd.median_distance((grav_df.easting, grav_df.northing), k_nearest=1)
)
damping = best_trial.params.get("damping", kwargs.pop("damping", None))
Expand Down Expand Up @@ -3247,7 +3247,7 @@ def optimize_regional_constraint_point_minimization(
depth = best_trial.params.get("depth", kwargs.pop("depth", "default"))
if depth == "default":
# calculate 4.5 times the mean distance between points
depth = np.mean(
depth = 4.5 * np.mean(
vd.median_distance(
(constraints_df.easting, constraints_df.northing), k_nearest=1
)
Expand Down
17 changes: 13 additions & 4 deletions src/invert4geom/regional.py
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Original file line number Diff line number Diff line change
Expand Up @@ -338,7 +338,7 @@ def regional_constraints(
tension_factor: float = 1,
registration: str = "g",
spline_dampings: float | list[float] | None = None,
depth: float | None = None,
depth: float | str | None = None,
damping: float | None = None,
cv: bool = False,
block_size: float | None = None,
Expand Down Expand Up @@ -378,7 +378,7 @@ def regional_constraints(
grid registration used if `grid_method` is "pygmt",, by default "g"
spline_dampings : float | list[float] | None, optional
damping values used if `grid_method` is "verde", by default None
depth : float | None, optional
depth : float | str | None, optional
depth of each source relative to the data elevation, positive downwards in
meters, by default None
damping : float | None, optional
Expand Down Expand Up @@ -433,7 +433,6 @@ def regional_constraints(
no_skip=True,
verbose="q",
)
log.debug("sampled constraints: %s", constraints_df.describe())

# drop rows with NaN values
constraints_df = constraints_df[constraints_df.sampled_grav.notna()]
Expand Down Expand Up @@ -539,6 +538,15 @@ def regional_constraints(
constraints_df.northing,
constraints_df.sampled_grav_height,
)

if depth == "default":
depth = 4.5 * np.mean(
vd.median_distance(
(coords[0], coords[1]),
k_nearest=1,
)
)

if cv is True:
# eqs = utils.best_equivalent_source_damping(
_, eqs = optimization.optimize_eq_source_params(
Expand Down Expand Up @@ -566,6 +574,8 @@ def regional_constraints(
weights=weights,
)

log.debug(f"depth: {eqs.depth}, damping: {eqs.damping}")

# predict sources at gravity points and chosen height for upward continuation
grav_df["reg"] = eqs.predict(
(
Expand Down Expand Up @@ -630,7 +640,6 @@ def regional_constraints_cv(
df,
**split_kwargs,
)
log.debug("cv constraints split: %s", testing_training_df.describe())

_, grav_df, _ = optimization.optimize_regional_constraint_point_minimization(
testing_training_df=testing_training_df,
Expand Down
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