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Fix/qgis fixes #277

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Merged
lachlangrose merged 4 commits into from
Jan 15, 2026
Merged

Fix/qgis fixes #277

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8ab6bca
fix: add matrix scaling to improve performance
lachlangrose Jan 8, 2026
c049fa7
fix: add framework to rebuild fault data if a geometry parameter chan…
lachlangrose Jan 8, 2026
48823fe
fix: strikedip2vector works for single floats not only list like
lachlangrose Jan 8, 2026
23e0b21
Initial plan (#278)
Copilot Jan 14, 2026
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43 changes: 39 additions & 4 deletions LoopStructural/interpolators/_discrete_interpolator.py
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Original file line number Diff line number Diff line change
Expand Up @@ -62,7 +62,9 @@ def __init__(self, support, data={}, c=None, up_to_date=False):
self.interpolation_weights = {}
logger.info("Creating discrete interpolator with {} degrees of freedom".format(self.dof))
self.type = InterpolatorType.BASE_DISCRETE

self.apply_scaling_matrix = True
self.add_ridge_regulatisation = True
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Corrected spelling of 'regulatisation' to 'regularisation'.

Suggested change
self.add_ridge_regulatisation = True
self.add_ridge_regularisation = True

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self.ridge_factor = 1e-8
def set_nelements(self, nelements: int) -> int:
return self.support.set_nelements(nelements)

Expand Down Expand Up @@ -511,6 +513,25 @@ def build_matrix(self):

B = np.hstack(bs)
return A, B
def compute_column_scaling_matrix(self, A: sparse.csr_matrix) -> sparse.dia_matrix:
"""Compute column scaling matrix S for matrix A so that A @ S has columns with unit norm.

Parameters
----------
A : sparse.csr_matrix
interpolation matrix

Returns
-------
scipy.sparse.dia_matrix
diagonal scaling matrix S
"""
col_norms = sparse.linalg.norm(A, axis=0)
scaling_factors = np.ones(A.shape[1])
mask = col_norms > 0
scaling_factors[mask] = 1.0 / col_norms[mask]
S = sparse.diags(scaling_factors)
return S

def add_equality_block(self, A, B):
if len(self.equal_constraints) > 0:
Expand Down Expand Up @@ -591,6 +612,15 @@ def solve_system(
raise ValueError("Pre solve failed")

A, b = self.build_matrix()
if self.add_ridge_regulatisation:
ridge = sparse.eye(A.shape[1]) * self.ridge_factor
A = sparse.vstack([A, ridge])
b = np.hstack([b, np.zeros(A.shape[1])])
logger.info("Adding ridge regularisation to interpolation matrix")
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Corrected spelling of 'regularisation' to 'regularization' for consistency with American English spelling used elsewhere in scientific computing libraries.

Suggested change
logger.info("Adding ridge regularisation to interpolation matrix")
logger.info("Adding ridge regularization to interpolation matrix")

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if self.apply_scaling_matrix:
S = self.compute_column_scaling_matrix(A)
A = A @ S

Q, bounds = self.build_inequality_matrix()
if callable(solver):
logger.warning('Using custom solver')
Expand Down Expand Up @@ -620,12 +650,14 @@ def solve_system(

elif solver == 'lsmr':
logger.info("Solving using lsmr")
if 'atol' not in solver_kwargs:
if tol is not None:
solver_kwargs['atol'] = tol
# if 'atol' not in solver_kwargs:
# if tol is not None:
# solver_kwargs['atol'] = tol
Comment on lines +653 to +655
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This comment appears to contain commented-out code.

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# if 'atol' not in solver_kwargs:
# if tol is not None:
# solver_kwargs['atol'] = tol

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if 'btol' not in solver_kwargs:
if tol is not None:
solver_kwargs['btol'] = tol
solver_kwargs['atol'] = 0.
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This expression mutates a default value.
This expression mutates a default value.

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logger.info(f"Setting lsmr btol to {tol}")
logger.info(f"Solver kwargs: {solver_kwargs}")
res = sparse.linalg.lsmr(A, b, **solver_kwargs)
if res[1] == 1 or res[1] == 4 or res[1] == 2 or res[1] == 5:
Expand Down Expand Up @@ -684,6 +716,9 @@ def solve_system(
logger.error(f"Unknown solver {solver}")
self.up_to_date = False
# self._post_solve()
# apply scaling matrix to solution
if self.apply_scaling_matrix:
self.c = S @ self.c
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Variable S is only defined when self.apply_scaling_matrix is True (line 621), but this code path can be reached through multiple solver branches (callable, cg, lsmr, admm, unknown solver) where S might not be in scope. If apply_scaling_matrix is False initially but somehow becomes True, or if an error path is taken, S will be undefined. The variable should be initialized to None at the start of the method, or this block should be moved inside the earlier if self.apply_scaling_matrix block.

Suggested change
self.c = S @ self.c
S = locals().get("S", None)
if S is None:
logger.error("Scaling matrix S is not defined; skipping scaling of solution.")
self.up_to_date = False
else:
self.c = S @ self.c

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return self.up_to_date

def update(self) -> bool:
Expand Down
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