make centroid threshold configurable

src/toolbox_scs/detectors/hrixs.py

@@ -197,7 +197,7 @@ def _esrf_centroid(image, threshold=THRESHOLD, curvature=(CURVE_A, CURVE_B)):
     return res
 
 
-def _new_centroid(image, threshold=THRESHOLD, curvature=(CURVE_A, CURVE_B)):
+def _new_centroid(image, threshold=THRESHOLD, std_threshold=3.5, curvature=(CURVE_A, CURVE_B)):
     """find the position of photons with sub-pixel precision
 
     A photon is supposed to have hit the detector if the intensity within a
@@ -208,7 +208,8 @@ def _new_centroid(image, threshold=THRESHOLD, curvature=(CURVE_A, CURVE_B)):
     """
     base = image.mean()
     corners = image[1:, 1:] + image[:-1, 1:] + image[1:, :-1] + image[:-1, :-1]
-    threshold = corners.mean() + 3.5 * corners.std()
+    if threshold is None:
+        threshold = corners.mean() + std_threshold * corners.std()
     middle = corners[1:-1, 1:-1]
     candidates = (
             (middle > threshold)
@@ -283,7 +284,8 @@ class hRIXS:
     Y_RANGE = np.s_[:]
 
     # centroid
-    THRESHOLD = THRESHOLD  # pixel counts above which a hit candidate is assumed
+    THRESHOLD = None  # pixel counts above which a hit candidate is assumed
+    STD_THRESHOLD = 3.5  # same as THRESHOLD, in standard deviations
     CURVE_A = CURVE_A  # curvature parameters as determined elsewhere
     CURVE_B = CURVE_B
 
@@ -347,6 +349,7 @@ class hRIXS:
             c = centroid(
                 image.to_numpy()[self.X_RANGE, self.Y_RANGE].T,
                 threshold=self.THRESHOLD,
+                std_threshold=self.STD_THRESHOLD,
                 curvature=(self.CURVE_A, self.CURVE_B))
             if not len(c):
                 continue