feat: Include way to broadcast arrays

Author: henryiii

notebooks/BoostHistogramHandsOn.ipynb

@@ -457,7 +457,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "This is transposed because pcolormesh requires ij indexing instead of xy."
+    "This is transposed because [`pcolormesh` expects it](https://matplotlib.org/3.2.2/api/_as_gen/matplotlib.pyplot.pcolormesh.html#axes-pcolormesh-grid-orientation)."
    ]
   },
   {

src/boost_histogram/_internal/axistuple.py

@@ -20,6 +20,14 @@ def __dir__(self):
     def __call__(self, *args, **kwargs):
         return self.__class__(a(*args, **kwargs) for a in self)
 
+    def broadcast(self):
+        """
+        The arrays in this tuple will be compressed if possible to save memory.
+        Use this method to broadcast them out into their full memory
+        representation.
+        """
+        return self.__class__(np.broadcast_arrays(*self))
+
 
 class AxesTuple(tuple):
     __slots__ = ()

tests/test_axes_object.py

@@ -26,26 +26,32 @@ def test_axes_all_at_once():
 
     centers = h.axes.centers
     answers = np.ogrid[0.5:10, 0.5:5, 0.5:2]
+    full_answers = np.mgrid[0.5:10, 0.5:5, 0.5:2]
 
     for i in range(3):
+        np.testing.assert_allclose(centers.broadcast()[i], full_answers[i])
         np.testing.assert_allclose(centers[i], answers[i])
         np.testing.assert_allclose(centers.T[i], answers[i].T)
         np.testing.assert_allclose(centers.flatten()[i], answers[i].flatten())
         np.testing.assert_allclose(h.axes[i].centers, answers[i].ravel())
 
     edges = h.axes.edges
     answers = np.ogrid[0:11, 0:6, 0:3]
+    full_answers = np.mgrid[0:11, 0:6, 0:3]
 
     for i in range(3):
+        np.testing.assert_allclose(edges.broadcast()[i], full_answers[i])
         np.testing.assert_allclose(edges[i], answers[i])
         np.testing.assert_allclose(edges.T[i], answers[i].T)
         np.testing.assert_allclose(edges.ravel()[i], answers[i].ravel())
         np.testing.assert_allclose(h.axes[i].edges, answers[i].ravel())
 
     widths = h.axes.widths
     answers = np.ogrid[1:1:10j, 1:1:5j, 1:1:2j]
+    full_answers = np.mgrid[1:1:10j, 1:1:5j, 1:1:2j]
 
     for i in range(3):
+        np.testing.assert_allclose(widths.broadcast()[i], full_answers[i])
         np.testing.assert_allclose(widths[i], answers[i])
         np.testing.assert_allclose(widths.T[i], answers[i].T)
         np.testing.assert_allclose(widths.ravel()[i], answers[i].ravel())