Merge branch 'main' into logpolar

Author: dkazanc

httomolibgpu/recon/rotation.py

@@ -21,6 +21,7 @@
 """Modules for finding the axis of rotation for 180 and 360 degrees scans"""
 
 import numpy as np
+from numpy.polynomial import Polynomial
 from httomolibgpu import cupywrapper
 
 cp = cupywrapper.cp
@@ -712,9 +713,23 @@ def _calculate_curvature(list_metric):
 
     # work mostly on CPU here - we have very small arrays here
     list1 = cp.asnumpy(list_metric[min_pos - radi : min_pos + radi + 1])
-    afact1 = np.polyfit(np.arange(0, 2 * radi + 1), list1, 2)[0]
+    if not all(map(np.isfinite, list1)):
+        raise ValueError(
+            "The list of metrics (list1) contains nan's or infs. Check your input data"
+        )
+
+    series1 = Polynomial.fit(np.arange(0, 2 * radi + 1), list1, deg=2)
+    afact1 = series1.convert().coef[-1]
+
     list2 = cp.asnumpy(list_metric[min_pos - 1 : min_pos + 2])
-    (afact2, bfact2, _) = np.polyfit(np.arange(min_pos - 1, min_pos + 2), list2, 2)
+    if not all(map(np.isfinite, list2)):
+        raise ValueError(
+            "The list of metrics (list2) contains nan's or infs. Check your input data"
+        )
+
+    series2 = Polynomial.fit(np.arange(min_pos - 1, min_pos + 2), list2, deg=2)
+    afact2 = series2.convert().coef[-1]
+    bfact2 = series2.convert().coef[-1 - 1]
 
     curvature = np.abs(afact1)
     if afact2 != 0.0:

tests/test_recon/test_rotation.py

@@ -112,6 +112,17 @@ def test_find_center_360_1D_raises(data):
         find_center_360(cp.ones(10))
 
 
+def test_find_center_360_NaN_infs_raises(data, flats, darks):
+    #: find_center_360 raises if the data with NaNs or Infs given
+    data = data.astype(cp.float32)
+    data[:] = cp.inf
+    with pytest.raises(ValueError):
+        find_center_360(data)
+    data[:] = cp.nan
+    with pytest.raises(ValueError):
+        find_center_360(data)
+
+
 @pytest.mark.parametrize("norm", [False, True], ids=["no_normalise", "normalise"])
 @pytest.mark.parametrize("overlap", [False, True], ids=["no_overlap", "overlap"])
 @pytest.mark.parametrize("denoise", [False, True], ids=["no_denoise", "denoise"])