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Add minimum beam size check for fit validation. #370

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Add minimum beam size check for fit validation. #370

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0c1b7ce
Add minimum beam size check for fit validation.
dylanmkennedy May 19, 2026
e666364
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dylanmkennedy May 19, 2026
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16 changes: 16 additions & 0 deletions lcls_tools/common/image/fit.py
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Original file line number Diff line number Diff line change
Expand Up @@ -79,6 +79,9 @@ class ImageProjectionFit(ImageFit):
Fit amplitude to noise threshold for the fit. If the amplitude of the fit is below this
threshold times the noise standard deviation and `validate_fit` is True,
the fit parameters will be set to NaN.
min_beam_size: PositiveFloat
Minimum beam size in pixels for the fit. If the beam size of the fit is below this threshold,
and 'validate_fit' is True, the fit parameters will be set to NaN.
beam_extent_n_stds : PositiveFloat
Number of standard deviations on either side to use for the beam extent. If the beam
extent is outside the image and `validate_fit` is True, the fit parameters will be set to NaN.
Expand All @@ -94,6 +97,9 @@ class ImageProjectionFit(ImageFit):
signal_to_noise_threshold: PositiveFloat = Field(
2.0, description="Fit amplitude to noise threshold for the fit"
)
min_beam_size: PositiveFloat = Field(
1.0, description="Minimum beam size in pixels to accept for validation"
)
beam_extent_n_stds: PositiveFloat = Field(
2.0,
description="Number of standard deviations on either side to use for the beam extent",
Expand Down Expand Up @@ -164,3 +170,13 @@ def _validate_parameters(
warnings.warn(
f"Projection in {dim} was off the screen, fit cannot be trusted"
)

# if the beam size is smaller than the specified minimum number of pixels, fits cannot be trusted
if self.min_beam_size is not None:
if parameters["sigma"] < self.min_beam_size:
for name in parameters.keys():
parameters[name] = np.nan

warnings.warn(
f"Projection in {dim} had too small a beam size, fit cannot be trusted"
)
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