Make more robust for numba's picky type selection

stingray/utils.py

@@ -46,11 +46,11 @@
 
     HAS_NUMBA = True
     from numba import njit, prange, vectorize, float32, float64, int32, int64
-    from numba.core.errors import NumbaValueError
+    from numba.core.errors import NumbaValueError, NumbaNotImplementedError
 except ImportError:
     warnings.warn("Numba not installed. Faking it")
     HAS_NUMBA = False
-    NumbaValueError = Exception
+    NumbaValueError = NumbaNotImplementedError = Exception
 
     def njit(f=None, *args, **kwargs):
         def decorator(func, *a, **kw):
@@ -1979,18 +1979,25 @@ def histogram2d(*args, **kwargs):
         ...                   ranges=[[0., 1.], [2., 3.]])
         >>> assert np.all(Hn1 == Hn2)
         """
-        if "range" in kwargs:
-            kwargs["ranges"] = kwargs.pop("range")
+        kwargs_copy = kwargs.copy()
+        if "range" in kwargs_copy:
+            kwargs_copy["ranges"] = kwargs_copy.pop("range")
 
-        if "weights" not in kwargs:
-            return hist2d_numba_seq(*args, **kwargs)
+        if "weights" not in kwargs_copy:
+            return hist2d_numba_seq(*args, **kwargs_copy)
 
-        weights = kwargs.pop("weights")
+        weights = kwargs_copy.pop("weights")
 
-        if weights is not None:
-            return hist2d_numba_seq_weight(*args, weights, **kwargs)
+        try:
+            if weights is not None:
+                return hist2d_numba_seq_weight(*args, weights, **kwargs_copy)
 
-        return hist2d_numba_seq(*args, **kwargs)
+            return hist2d_numba_seq(*args, **kwargs_copy)
+        except NumbaValueError:
+            warnings.warn("Numba could not calculate the histogram. Trying standard numpy.")
+            return histogram2d_np(*args, **kwargs)[0]
+        except:
+            raise
 
     def histogram(*args, **kwargs):
         """
@@ -2006,18 +2013,25 @@ def histogram(*args, **kwargs):
         >>> Hn2 = histogram(x, bins=5, ranges=[0., 1.])
         >>> assert np.all(Hn1 == Hn2)
         """
-        if "range" in kwargs:
-            kwargs["ranges"] = kwargs.pop("range")
-
-        if "weights" not in kwargs:
-            return hist1d_numba_seq(*args, **kwargs)
+        kwargs_copy = kwargs.copy()
+        if "range" in kwargs_copy:
+            kwargs_copy["ranges"] = kwargs_copy.pop("range")
 
-        weights = kwargs.pop("weights")
+        if "weights" not in kwargs_copy:
+            return hist1d_numba_seq(*args, **kwargs_copy)
 
-        if weights is not None:
-            return hist1d_numba_seq_weight(*args, weights, **kwargs)
+        weights = kwargs_copy.pop("weights")
 
-        return hist1d_numba_seq(*args, **kwargs)
+        try:
+            if weights is not None:
+                return hist1d_numba_seq_weight(*args, weights, **kwargs_copy)
+
+            return hist1d_numba_seq(*args, **kwargs_copy)
+        except (NumbaValueError, NumbaNotImplementedError):
+            warnings.warn("Numba could not calculate the histogram. Trying standard numpy.")
+            return histogram_np(*args, **kwargs)[0]
+        except:
+            raise
 
 else: