Add the DASDAE inventory model layer

dascore/__init__.py

@@ -9,6 +9,7 @@
 from dascore.core.attrs import PatchAttrs
 from dascore.core.summary import PatchSummary
 from dascore.core.spool import BaseSpool, Spool, spool
+from dascore.core.inventory import Inventory, inventory
 from dascore.core.coordmanager import get_coord_manager, CoordManager
 from dascore.core.coords import get_coord
 from dascore.config import (

dascore/core/__init__.py

@@ -2,7 +2,10 @@
 Core routines and functionality for processing distributed fiber data.
 """
 from __future__ import annotations
+
+from . import inventory  # noqa
+from .coordmanager import CoordManager, get_coord_manager
+from .coords import CoordSegmented, CoordSummary, concat_coords, get_coord
+from .inventory import Inventory  # noqa
 from .patch import Patch  # noqa
 from .summary import PatchSummary  # noqa
-from .coords import CoordSegmented, CoordSummary, concat_coords, get_coord
-from .coordmanager import get_coord_manager, CoordManager

dascore/core/coords.py

@@ -59,6 +59,7 @@
     all_close,
     all_diffs_close_enough,
     cached_method,
+    is_strictly_monotonic,
     iterate,
     sanitize_range_param,
 )
@@ -2995,11 +2996,7 @@ def _maybe_get_start_stop_step(data):
             return None, None, None, False
         view2 = data[1:]
         view1 = data[:-1]
-        try:
-            # ascending first; it is by far the more common case.
-            is_monotonic = np.all(view2 > view1) or np.all(view1 > view2)
-        except TypeError:
-            return None, None, None, False
+        is_monotonic = is_strictly_monotonic(data)
         # the array cannot be evenly sampled if it isn't monotonic
         if is_monotonic:
             try: