pass binedge_attrs through Histogram constructor

src/lgdo/types/histogram.py

@@ -62,7 +62,7 @@ def __init__(
                 if not isinstance(edges, Array):
                     edges = Array(edges, attrs=binedge_attrs)
                 elif binedge_attrs is not None:
-                    msg = "passed both binedge types.Array instance and binedge_attrs"
+                    msg = "passed both binedge as Array LGDO instance and binedge_attrs"
                     raise ValueError(msg)
 
                 if len(edges.nda.shape) != 1:
@@ -72,11 +72,13 @@ def __init__(
             super().__init__({"binedges": edges, "closedleft": Scalar(closedleft)})
 
         @classmethod
-        def from_edges(cls, edges: np.ndarray) -> Histogram.Axis:
+        def from_edges(
+            cls, edges: np.ndarray, binedge_attrs: dict[str, Any] | None = None
+        ) -> Histogram.Axis:
             edge_diff = np.diff(edges)
             if np.any(~np.isclose(edge_diff, edge_diff[0])):
-                return cls(edges, None, None, None, True)
-            return cls(None, edges[0], edges[-1], edge_diff[0], True)
+                return cls(edges, None, None, None, True, binedge_attrs)
+            return cls(None, edges[0], edges[-1], edge_diff[0], True, binedge_attrs)
 
         @property
         def is_range(self) -> bool:
@@ -132,13 +134,24 @@ def __str__(self) -> str:
                 string = f"edges={self.edges}"
             string += f", closedleft={self.closedleft}"
 
-            attrs = self["binedges"].getattrs()
+            attrs = self.get_binedgeattrs()
             if attrs:
                 string += f" with attrs={attrs}"
 
             np.set_printoptions(threshold=thr_orig)
             return string
 
+        def get_binedgeattrs(self, datatype: bool = False) -> dict:
+            """Return a copy of the LGDO attributes dictionary of the binedges
+
+            Parameters
+            ----------
+            datatype
+                if ``False``, remove ``datatype`` attribute from the output
+                dictionary.
+            """
+            return self["binedges"].getattrs(datatype)
+
     def __init__(
         self,
         weights: hist.Hist | np.ndarray,
@@ -148,6 +161,7 @@ def __init__(
         | list[tuple[float, float, float]] = None,
         isdensity: bool = False,
         attrs: dict[str, Any] | None = None,
+        binedge_attrs: dict[str, Any] | None = None,
     ) -> None:
         """A special struct to contain histogrammed data.
 
@@ -163,6 +177,8 @@ def __init__(
             * can be a list of pre-initialized :class:`Histogram.Axis`
             * can be a list of tuples, representing a range, ``(first, last, step)``
             * can be a list of numpy arrays, as returned by :func:`numpy.histogramdd`.
+        binedge_attrs
+            attributes that will be added to the all ``binedges`` of all axes.
         """
         if isinstance(weights, hist.Hist):
             if binning is not None:
@@ -186,7 +202,7 @@ def __init__(
                 if not isinstance(ax, (hist.axis.Regular, hist.axis.Variable)):
                     msg = "only regular or variable axes of hist.Hist can be converted"
                     raise ValueError(msg)
-                b.append(Histogram.Axis.from_edges(ax.edges))
+                b.append(Histogram.Axis.from_edges(ax.edges, binedge_attrs))
             b = self._create_binning(b)
         else:
             if binning is None:
@@ -195,11 +211,14 @@ def __init__(
             w = Array(weights)
 
             if all(isinstance(ax, Histogram.Axis) for ax in binning):
+                if binedge_attrs is not None:
+                    msg = "passed both binedges as Axis instances and binedge_attrs"
+                    raise ValueError(msg)
                 b = binning
             elif all(isinstance(ax, np.ndarray) for ax in binning):
-                b = [Histogram.Axis.from_edges(ax) for ax in binning]
+                b = [Histogram.Axis.from_edges(ax, binedge_attrs) for ax in binning]
             elif all(isinstance(ax, tuple) for ax in binning):
-                b = [Histogram.Axis(None, *ax, True) for ax in binning]
+                b = [Histogram.Axis(None, *ax, True, binedge_attrs) for ax in binning]
             else:
                 msg = "invalid binning object passed"
                 raise ValueError(msg)

tests/types/test_histogram.py

@@ -149,6 +149,13 @@ def test_axes():
     assert h.binning[0].nbins == 3
     assert str(h.binning[0]) == "edges=[0.  1.  2.5 3. ], closedleft=True"
 
+    with pytest.raises(ValueError, match="either from edges or from range"):
+        Histogram.Axis(np.array([0, 1, 2.5, 3]), 0, 1, None)
+    with pytest.raises(ValueError, match="all range parameters"):
+        Histogram.Axis(None, 0, 1, None)
+
+
+def test_ax_attributes():
     Histogram.Axis(
         np.array([0, 1, 2.5, 3]), None, None, None, binedge_attrs={"units": "m"}
     )
@@ -175,10 +182,21 @@ def test_axes():
         str(ax) == "edges=[0.  1.  2.5 3. ], closedleft=True with attrs={'units': 'm'}"
     )
 
-    with pytest.raises(ValueError, match="either from edges or from range"):
-        Histogram.Axis(np.array([0, 1, 2.5, 3]), 0, 1, None)
-    with pytest.raises(ValueError, match="all range parameters"):
-        Histogram.Axis(None, 0, 1, None)
+    h = Histogram(
+        np.array([[1, 1], [1, 1]]),
+        (np.array([0, 1, 2]), np.array([0, 1, 2])),
+        binedge_attrs={"units": "m"},
+    )
+    assert str(h.binning[0]).endswith(", closedleft=True with attrs={'units': 'm'}")
+    assert str(h.binning[1]).endswith(", closedleft=True with attrs={'units': 'm'}")
+    assert h.binning[0].get_binedgeattrs() == {"units": "m"}
+
+    with pytest.raises(ValueError):
+        h = Histogram(
+            np.array([[1, 1], [1, 1]]),
+            [Histogram.Axis(None, 1, 3, 1, True), Histogram.Axis(None, 4, 6, 1, False)],
+            binedge_attrs={"units": "m"},
+        )
 
 
 def test_view_as_hist():