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add weights to the fits #118

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add weights to the fits #118

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15 changes: 15 additions & 0 deletions pytheranostics/dosimetry/base_dosimetry.py
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Original file line number Diff line number Diff line change
Expand Up @@ -477,6 +477,20 @@ def smart_fit_selection(
lmfit.model.ModelResult
The best fit model based on Akaike Information Criterion.
"""
y_data = numpy.array(region_data["Activity_MBq"], dtype=float)
sigma_config = self.config["VOIs"][region].get("sigma", None)

if sigma_config is None:
sigma = None
elif sigma_config["type"] == "fraction":
sigma = sigma_config["value"] * y_data
elif sigma_config["type"] == "sqrt":
sigma = numpy.sqrt(y_data)
elif sigma_config["type"] == "absolute":
sigma = numpy.full_like(y_data, sigma_config["value"], dtype=float)
else:
raise ValueError(f"Unknown sigma type: {sigma_config['type']}")

# If fit_order is defined by user:
if self.config["rois"][region]["fit_order"] is not None:
fit_results, _ = exponential_fit_lmfit(
Expand All @@ -487,6 +501,7 @@ def smart_fit_selection(
bounds=self.config["rois"][region]["bounds"],
params_init=self.config["rois"][region]["param_init"],
with_uptake=self.config["rois"][region]["with_uptake"],
sigma=sigma,
)

return fit_results
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