pycsamt.emtools.dimensionality

Functions

classify_dimensionality(sites, *[, skew_th, ...])
encode_dimensionality(sites, model, *[, ...])
learn_dim_dictionary(sites, *[, n_atoms, ...])
mask_by_dictionary(sites, model, *[, keep, ...])
mask_by_dimensionality(sites, *[, keep, ...])
phase_features_table(sites, *[, recursive, ...])
plot_atom_psection(sites, model, *[, ...])
plot_dim_confidence_grid(sites, *[, ...])
plot_dim_map(sites, *[, period, skew_th, ...])
plot_dim_occupancy_area(sites, *[, skew_th, ...])
pre2d_inversion_assessment(sites, *[, band, ...])	Summarise dimensionality and strike checks before 2-D inversion.
project_to_2d(sites, *[, strike, method, ...])

pycsamt.emtools.dimensionality.phase_features_table(sites, *, recursive=True, on_dup='replace', strict=False, verbose=0, api=None)

Parameters:

• sites (Any)

• recursive (bool)

• on_dup (str)

• strict (bool)

• verbose (int)

• api (bool | None)

Return type:

Any

pycsamt.emtools.dimensionality.classify_dimensionality(sites, *, skew_th=3.0, ellipt_th=0.2, recursive=True, on_dup='replace', strict=False, verbose=0, api=None)

Parameters:

• sites (Any)

• skew_th (float)

• ellipt_th (float)

• recursive (bool)

• on_dup (str)

• strict (bool)

• verbose (int)

• api (bool | None)

Return type:

Any

pycsamt.emtools.dimensionality.pre2d_inversion_assessment(sites, *, band=None, skew_th=3.0, ellipt_th=0.2, rotation_applied=False, rotation_method='consensus', groom_bailey_attempted=False, groom_bailey_applied=False, groom_bailey_reason=None, recursive=True, on_dup='replace', strict=False, verbose=0, api=None)

Summarise dimensionality and strike checks before 2-D inversion.

The table is designed for audit trails and manuscript responses. It combines phase-tensor skew/ellipticity dimensionality labels, impedance sweep strike, phase-tensor strike, consensus strike, and frequency-dependent strike variability. It also records whether data were rotated to strike and whether Groom-Bailey decomposition was attempted/applied.

Parameters:

• sites (Any)

• band (tuple[float, float] | None)

• skew_th (float)

• ellipt_th (float)

• rotation_applied (bool)

• rotation_method (str)

• groom_bailey_attempted (bool)

• groom_bailey_applied (bool)

• groom_bailey_reason (str | None)

• recursive (bool)

• on_dup (str)

• strict (bool)

• verbose (int)

• api (bool | None)

Return type:

Any

pycsamt.emtools.dimensionality.mask_by_dimensionality(sites, *, keep=(0, 1), inplace=False, recursive=True, on_dup='replace', strict=False, verbose=0)

Parameters:

• sites (Any)

• keep (tuple[int, ...])

• inplace (bool)

• recursive (bool)

• on_dup (str)

• strict (bool)

• verbose (int)

pycsamt.emtools.dimensionality.project_to_2d(sites, *, strike=None, method='swift', antisym=True, inplace=False, recursive=True, on_dup='replace', strict=False, verbose=0)

Parameters:

• sites (Any)

• strike (float | None)

• method (str)

• antisym (bool)

• inplace (bool)

• recursive (bool)

• on_dup (str)

• strict (bool)

• verbose (int)

pycsamt.emtools.dimensionality.learn_dim_dictionary(sites, *, n_atoms=6, lam=0.05, n_iter=40, code_iter=50, recursive=True, on_dup='replace', strict=False, verbose=0)

Parameters:

• sites (Any)

• n_atoms (int)

• lam (float)

• n_iter (int)

• code_iter (int)

• recursive (bool)

• on_dup (str)

• strict (bool)

• verbose (int)

Return type:

dict[str, Any]

pycsamt.emtools.dimensionality.encode_dimensionality(sites, model, *, lam=0.05, code_iter=50, recursive=True, on_dup='replace', strict=False, verbose=0, api=None)

Parameters:

• sites (Any)

• model (dict[str, Any])

• lam (float)

• code_iter (int)

• recursive (bool)

• on_dup (str)

• strict (bool)

• verbose (int)

• api (bool | None)

Return type:

Any

pycsamt.emtools.dimensionality.mask_by_dictionary(sites, model, *, keep=(0, 1), lam=0.05, code_iter=50, inplace=False, recursive=True, on_dup='replace', strict=False, verbose=0)

Parameters:

• sites (Any)

• model (dict[str, Any])

• keep (tuple[int, ...])

• lam (float)

• code_iter (int)

• inplace (bool)

• recursive (bool)

• on_dup (str)

• strict (bool)

• verbose (int)

pycsamt.emtools.dimensionality.plot_atom_psection(sites, model, *, energy='l2', figsize=(9.0, 4.8), recursive=True, on_dup='replace', strict=False, verbose=0, ax=None)

Parameters:

• sites (Any)

• model (dict[str, Any])

• energy (str)

• figsize (tuple[float, float])

• recursive (bool)

• on_dup (str)

• strict (bool)

• verbose (int)

• ax (Axes | None)

Return type:

Axes

pycsamt.emtools.dimensionality.plot_dim_confidence_grid(sites, *, skew_th=3.0, ellipt_th=0.2, figsize=(8.8, 4.2), recursive=True, on_dup='replace', strict=False, verbose=0, ax=None)

Parameters:

• sites (Any)

• skew_th (float)

• ellipt_th (float)

• figsize (tuple[float, float])

• recursive (bool)

• on_dup (str)

• strict (bool)

• verbose (int)

• ax (Axes | None)

Return type:

Axes

pycsamt.emtools.dimensionality.plot_dim_occupancy_area(sites, *, skew_th=3.0, ellipt_th=0.2, n_bands=24, figsize=(8.8, 3.6), recursive=True, on_dup='replace', strict=False, verbose=0, ax=None)

Parameters:

• sites (Any)

• skew_th (float)

• ellipt_th (float)

• n_bands (int)

• figsize (tuple[float, float])

• recursive (bool)

• on_dup (str)

• strict (bool)

• verbose (int)

• ax (Axes | None)

Return type:

Axes

pycsamt.emtools.dimensionality.plot_dim_map(sites, *, period=10.0, skew_th=3.0, ellipt_th=0.2, figsize=(8.0, 6.0), recursive=True, on_dup='replace', strict=False, verbose=0, ax=None)

Parameters:

• sites (Any)

• period (float)

• skew_th (float)

• ellipt_th (float)

• figsize (tuple[float, float])

• recursive (bool)

• on_dup (str)

• strict (bool)

• verbose (int)

• ax (Axes | None)

Return type:

Axes