add fitting models

src/ibeatles/core/fitting/kropff/models.py

@@ -0,0 +1,53 @@
+#!/usr/bin/env python
+"""Kropff models for fitting."""
+
+from typing import Dict, List, Tuple
+from pydantic import BaseModel, Field
+from ibeatles.core.config import (
+    PixelBinning,
+    FittingCriteria,
+    RejectionCriteria,
+    ThresholdFinder,
+)
+
+
+class KropffFittingParameters(BaseModel):
+    lambda_min: float = Field(..., description="Minimum lambda value for fitting")
+    lambda_max: float = Field(..., description="Maximum lambda value for fitting")
+    threshold_finder: ThresholdFinder = Field(
+        ..., description="Threshold finder configuration"
+    )
+    fitting_criteria: FittingCriteria = Field(..., description="Fitting criteria")
+    rejection_criteria: RejectionCriteria = Field(..., description="Rejection criteria")
+    pixel_binning: PixelBinning = Field(..., description="Pixel binning parameters")
+
+
+class KropffBinData(BaseModel):
+    xaxis: List[float] = Field(..., description="X-axis data for the bin")
+    yaxis: List[float] = Field(..., description="Y-axis data for the bin")
+    bin_coordinates: Dict[str, int] = Field(..., description="Coordinates of the bin")
+    bragg_peak_threshold: Dict[str, float] = Field(
+        ..., description="Bragg peak threshold values"
+    )
+
+
+class KropffFittingInput(BaseModel):
+    parameters: KropffFittingParameters
+    bin_data: Dict[str, KropffBinData] = Field(
+        ..., description="Dictionary of bin data"
+    )
+
+
+class KropffFittingResult(BaseModel):
+    a0: Tuple[float, float] = Field(..., description="Fitted a0 value and error")
+    b0: Tuple[float, float] = Field(..., description="Fitted b0 value and error")
+    ahkl: Tuple[float, float] = Field(..., description="Fitted ahkl value and error")
+    bhkl: Tuple[float, float] = Field(..., description="Fitted bhkl value and error")
+    lambda_hkl: Tuple[float, float] = Field(
+        ..., description="Fitted lambda_hkl value and error"
+    )
+    tau: Tuple[float, float] = Field(..., description="Fitted tau value and error")
+    sigma: Tuple[float, float] = Field(..., description="Fitted sigma value and error")
+    fitted_data: Dict[str, List[float]] = Field(
+        ..., description="Fitted data for each region"
+    )