From 97acc1659b546b999deea79a9a7c4bb7b66a66ef Mon Sep 17 00:00:00 2001
From: gwm17 <gordonmccann215@gmail.com>
Date: Tue, 15 Jul 2025 07:33:12 -0500
Subject: [PATCH] Fix bug in printed Chi-Sq. value

---
 spspy/Fitter.py | 57 +++++++++++++++++++++++++++++--------------------
 1 file changed, 34 insertions(+), 23 deletions(-)

diff --git a/spspy/Fitter.py b/spspy/Fitter.py
index a252d23..1b77975 100644
--- a/spspy/Fitter.py
+++ b/spspy/Fitter.py
@@ -8,6 +8,7 @@ from typing import Optional
 INVALID_FIT_RESULT = np.inf
 INVALID_NDF = -1
 
+
 @dataclass
 class FitPoint:
     x: float = 0.0
@@ -15,7 +16,12 @@ class FitPoint:
     xError: float = 0.0
     yError: float = 0.0
 
-def convert_fit_points_to_arrays(data: list[FitPoint]) -> tuple[NDArray[np.float64], NDArray[np.float64], NDArray[np.float64], NDArray[np.float64]]:
+
+def convert_fit_points_to_arrays(
+    data: list[FitPoint],
+) -> tuple[
+    NDArray[np.float64], NDArray[np.float64], NDArray[np.float64], NDArray[np.float64]
+]:
     xArray = np.empty(len(data))
     yArray = np.empty(len(data))
     xErrorArray = np.empty(len(data))
@@ -27,13 +33,17 @@ def convert_fit_points_to_arrays(data: list[FitPoint]) -> tuple[NDArray[np.float
         yErrorArray[index] = point.yError
     return xArray, yArray, xErrorArray, yErrorArray
 
+
 @dataclass
 class FitResidual:
     x: float = 0.0
     residual: float = 0.0
     studentizedResidual: float = 0.0
 
-def convert_resid_points_to_arrays(data: list[FitResidual]) -> tuple[NDArray[np.float64], NDArray[np.float64], NDArray[np.float64]]:
+
+def convert_resid_points_to_arrays(
+    data: list[FitResidual],
+) -> tuple[NDArray[np.float64], NDArray[np.float64], NDArray[np.float64]]:
     xArray = np.empty(len(data))
     residArray = np.empty(len(data))
     studentResidArray = np.empty(len(data))
@@ -43,8 +53,9 @@ def convert_resid_points_to_arrays(data: list[FitResidual]) -> tuple[NDArray[np.
         studentResidArray[index] = point.studentizedResidual
     return xArray, residArray, studentResidArray
 
+
 class Fitter:
-    def __init__(self, order: int =1):
+    def __init__(self, order: int = 1):
         self.polynomialOrder: int = order
         self.fitResults: Optional[odr.Output] = None
         self.fitData: Optional[list[FitPoint]] = None
@@ -56,9 +67,11 @@ class Fitter:
     def run(self, data: list[FitPoint] = None) -> None:
         if data is not None:
             self.fitData = data
-        
+
         if self.fitData is not None:
-            xArray, yArray, xErrorArray, yErrorArray = convert_fit_points_to_arrays(self.fitData)
+            xArray, yArray, xErrorArray, yErrorArray = convert_fit_points_to_arrays(
+                self.fitData
+            )
             modelData = odr.RealData(xArray, y=yArray, sx=xErrorArray, sy=yErrorArray)
             model = odr.polynomial(self.polynomialOrder)
             self.fitResults = odr.ODR(modelData, model).run()
@@ -66,12 +79,12 @@ class Fitter:
         else:
             print("Cannot run fitter without setting data to be fit!")
 
-    def get_parameters(self) -> NDArray[np.float64] :
+    def get_parameters(self) -> NDArray[np.float64]:
         if self.fitResults is not None:
             return self.fitResults.beta
         return np.array({INVALID_FIT_RESULT})
 
-    def get_parameter_errors(self) -> NDArray[np.float64] :
+    def get_parameter_errors(self) -> NDArray[np.float64]:
         if self.fitResults is not None:
             return self.fitResults.sd_beta
         return np.array({INVALID_FIT_RESULT})
@@ -97,27 +110,23 @@ class Fitter:
         return INVALID_FIT_RESULT
 
     def get_chisquare(self) -> float:
-        if self.function is not None:
-            yEffErrorArray = [np.sqrt(point.yError**2.0 + (point.xError * self.evaluate_derivative(point.x))**2.0) for point in self.fitData]
-            chisq = 0.0
-            for index, point in enumerate(self.fitData):
-                chisq = ((point.y - self.evaluate(point.x)) / yEffErrorArray[index])**2.0
-            return chisq
-        return INVALID_FIT_RESULT
+        if self.fitResults is None:
+            return INVALID_FIT_RESULT
+        return self.fitResults.res_var * self.get_ndf()
 
     def get_reduced_chisquare(self) -> float:
-        ndf = self.get_ndf()
-        chisq = self.get_chisquare()
-        if chisq == INVALID_FIT_RESULT or ndf == INVALID_NDF:
+        if self.fitResults is None:
             return INVALID_FIT_RESULT
-        else:
-            return chisq/ndf
+        return self.fitResults.res_var
 
     def get_residuals(self) -> list[FitResidual]:
         if self.fitData is not None:
-            fitResiduals = [FitResidual(point.x, point.y - self.evaluate(point.x), 0.0) for point in self.fitData]
+            fitResiduals = [
+                FitResidual(point.x, point.y - self.evaluate(point.x), 0.0)
+                for point in self.fitData
+            ]
 
-            #compute the leverage and studentize
+            # compute the leverage and studentize
             xMean = 0.0
             rmse = 0.0
             npoints = len(fitResiduals)
@@ -132,7 +141,9 @@ class Fitter:
                 meanDiffSq += (resid.x - xMean) ** 2.0
             meanDiffSq /= npoints
             for resid in fitResiduals:
-                leverage = 1.0/npoints + (resid.x - xMean)/meanDiffSq
-                resid.studentizedResidual = resid.residual / (rmse * np.sqrt(1.0 - leverage))
+                leverage = 1.0 / npoints + (resid.x - xMean) / meanDiffSq
+                resid.studentizedResidual = resid.residual / (
+                    rmse * np.sqrt(1.0 - leverage)
+                )
             return fitResiduals
         return []