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FIX: Use lsqr solver for spline fit, rerun on extreme values #366

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Merged
merged 2 commits into from
Jun 8, 2023
Merged

FIX: Use lsqr solver for spline fit, rerun on extreme values #366

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59501c6
FIX: Rerun bspline fit 3 times, check for extreme values
effigies Jun 8, 2023
bd8d9fd
FIX: Use lsqr solver
effigies Jun 8, 2023
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16 changes: 14 additions & 2 deletions sdcflows/interfaces/bspline.py
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Original file line number Diff line number Diff line change
Expand Up @@ -208,8 +208,20 @@ def _run_interface(self, runtime):
)

# Fit the model
model = lm.Ridge(alpha=self.inputs.ridge_alpha, fit_intercept=False)
model.fit(colmat[mask.reshape(-1), :], data[mask])
model = lm.Ridge(alpha=self.inputs.ridge_alpha, fit_intercept=False, solver='lsqr')
for attempt in range(3):
model.fit(colmat[mask.reshape(-1), :], data[mask])
extreme = np.abs(model.coef_).max()
LOGGER.debug(f"Model fit attempt {attempt}: max(|coeffs|) = {extreme}")
# Normal values seem to be ~1e2, bad ~1e8. May want to tweak this if
# these distributions are wider than I think.
if extreme < 1e4:
break
else:
raise RuntimeError(
f"Spline fit of input file {self.inputs.in_data} failed. "
f"Extreme value {extreme:.2e} detected in spline coefficients."
)

# Store coefficients
index = 0
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