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[SSO] Add outlier rejection, and bootstrap method. #600

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[SSO] Add outlier rejection, and bootstrap method. #600

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b6ee0c7
Add outlier rejection, and bootstrap method. Requires SOCCA 1.2.0
JulienPeloton Dec 3, 2025
af71a3a
Bring latest changes from asteroid_spinprops and fink-utils. Not sync…
JulienPeloton Dec 5, 2025
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27 changes: 18 additions & 9 deletions fink_science/ztf/ssoft/processor.py
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Original file line number Diff line number Diff line change
Expand Up @@ -40,6 +40,7 @@
from astropy.coordinates import SkyCoord
import astropy.units as u

from asteroid_spinprops.ssolib import dataprep
from asteroid_spinprops.ssolib import modelfit

import logging
Expand Down Expand Up @@ -251,15 +252,15 @@
},
"max_cos_lambda": {
"type": "double",
"description": "Maximum of the absolute value of the cosine for the aspect angle",
"description": "Maximum of the cosine for the aspect angle",
},
"mean_cos_lambda": {
"type": "double",
"description": "Mean of the absolute value of the cosine for the aspect angle",
"description": "Mean of the cosine for the aspect angle",
},
"min_cos_lambda": {
"type": "double",
"description": "Minimum of the absolute value of the cosine for the aspect angle",
"description": "Minimum of the cosine for the aspect angle",
},
"period": {
"type": "double",
Expand Down Expand Up @@ -344,15 +345,15 @@
},
"max_cos_lambda": {
"type": "double",
"description": "Maximum of the absolute value of the cosine for the aspect angle",
"description": "Maximum of the cosine for the aspect angle",
},
"mean_cos_lambda": {
"type": "double",
"description": "Mean of the absolute value of the cosine for the aspect angle",
"description": "Mean of the cosine for the aspect angle",
},
"min_cos_lambda": {
"type": "double",
"description": "Minimum of the absolute value of the cosine for the aspect angle",
"description": "Minimum of the cosine for the aspect angle",
},
}

Expand Down Expand Up @@ -480,7 +481,7 @@ def extract_ssoft_parameters(
),
},
"SOCCA": {
"p0": [15.0, 0.15, 0.15, np.pi, 0.0, 5.0, 1.05, 1.05, 0.0],
"p0": [15.0, 0.15, 0.15, np.pi, 0.0, 5.0, 1.05, 1.15, 0.0],
"bounds": (
[-3, 0, 0, 0, -np.pi / 2, 2.2 / 24.0, 1, 1, -np.pi / 2],
[30, 1, 1, 2 * np.pi, np.pi / 2, 1000, 5, 5, np.pi / 2],
Expand Down Expand Up @@ -525,16 +526,24 @@ def extract_ssoft_parameters(
colname: [pdf[colname].to_numpy()] for colname in pdf.columns
})

clean_data, _ = dataprep.errorbar_filtering(
data=pdf_transposed, mlimit=0.7928
)
clean_data, _ = dataprep.projection_filtering(data=clean_data)
clean_data, _ = dataprep.iterative_filtering(data=clean_data)

# parameter estimation
outdic = modelfit.get_fit_params(
pdf_transposed,
clean_data,
flavor=model_name,
shg1g2_constrained=True,
period_blind=True,
pole_blind=True,
pole_blind=False,
alt_spin=False,
period_in=None,
terminator=False,
period_quality_flag=True,
time_in=True,
)

# replace names inplace for the remaning computation
Expand Down
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