refactor: bool view instead of mode

Author: henryiii

src/boost_histogram/_internal/hist.py

@@ -562,11 +562,11 @@ def _compute_commonindex(self, index):
 
         return indexes
 
-    @inject_signature("self, flow=False, *, dd=False, mode='numpy'")
+    @inject_signature("self, flow=False, *, dd=False, view=False")
     def to_numpy(self, flow=False, **kwargs):
         """
-        Convert to a Numpy style tuple of return arrays. Edges are converted
-        to exactly match NumPy standards, with upper edge inclusive, unlike
+        Convert to a Numpy style tuple of return arrays. Edges are converted to
+        match NumPy standards, with upper edge inclusive, unlike
         boost-histogram, where upper edge is exclusive.
 
         Parameters
@@ -576,11 +576,11 @@ def to_numpy(self, flow=False, **kwargs):
         dd : bool = False
             Use the histogramdd return syntax, where the edges are in a tuple.
             Otherwise, this is the histogram/histogram2d return style.
-        mode : Literal["numpy", "view"] = "numpy"
-            The behavior for the return value. "numpy" will return the NumPy
+        view : bool  = False
+            The behavior for the return value. By default, this will return
             array of the values only regardless of the storage (which is all
-            NumPy's histogram function can do). "view" will leave the
-            boost-histogram view of the storage untouched.
+            NumPy's histogram function can do). view=True will return the
+            boost-histogram view of the storage.
 
         Return
         ------
@@ -592,18 +592,16 @@ def to_numpy(self, flow=False, **kwargs):
 
         with KWArgs(kwargs) as kw:
             dd = kw.optional("dd", False)
-            mode = kw.optional("mode", "numpy")
+            view = kw.optional("view", False)
 
         # Python 3+ would be simpler
         return_tuple = self._hist.to_numpy(flow)
         hist = return_tuple[0]
 
-        if mode == "numpy":
-            hist = self.values(flow=flow)
-        elif mode == "view":
+        if view:
             hist = self.view(flow=flow)
         else:
-            raise KeyError("Invalid mode")
+            hist = self.values(flow=flow)
 
         if dd:
             return hist, return_tuple[1:]

src/boost_histogram/numpy.py

@@ -79,10 +79,10 @@ def histogramdd(
         density = hist.view() / hist.sum() / areas
         return (density, hist.to_numpy()[1:])
 
-    # Note: this is mode="view" since users have to ask explicilty for special
-    # storages, so mode="numpy" would throw away part of what they are asking
-    # for. Users can use a histogram return type if they need mode="numpy".
-    return hist if bh_cls is not None else hist.to_numpy(dd=True, mode="view")
+    # Note: this is view=True since users have to ask explicitly for special
+    # storages, so view=False would throw away part of what they are asking
+    # for. Users can use a histogram return type if they need view=False.
+    return hist if bh_cls is not None else hist.to_numpy(view=True, dd=True)
 
 
 @_inject_signature(

tests/test_internal_histogram.py

@@ -146,15 +146,15 @@ def test_numpy_weights():
             v = i + j * 10 + 1
             h.fill([x] * v, [y] * v)
 
-    h2, x2, y2 = h.to_numpy(mode="numpy")
-    h1, (x1, y1) = h.to_numpy(dd=True, mode="numpy")
+    h2, x2, y2 = h.to_numpy(view=False)
+    h1, (x1, y1) = h.to_numpy(dd=True, view=False)
 
     assert_array_equal(h1, h2)
     assert_array_equal(x1, x2)
     assert_array_equal(y1, y2)
 
-    h1, (x1, y1) = h.to_numpy(dd=True, mode="numpy")
-    h2, x2, y2 = h.to_numpy(mode="view")
+    h1, (x1, y1) = h.to_numpy(dd=True, view=False)
+    h2, x2, y2 = h.to_numpy(view=True)
 
     assert_array_equal(h1, h2.value)
     assert_array_equal(x1, x2)