Support old mlptrain npz files (#373)

* Patch ValueArray pickle protocol to allow loading of old npz files

* Add tests

* Add changelog entry

* Don't fail fast

* Format

* revert fail-fast

---------

Co-authored-by: Tom Young <39765193+t-young31@users.noreply.github.com>

Author: danielhollas

autode/values.py

@@ -664,8 +664,15 @@ def __reduce__(self):
         )
 
     def __setstate__(self, state, *args, **kwargs):
-        self.__dict__.update(state[-1])
-        super().__setstate__(state[:-1], *args, **kwargs)
+        """Extend default pickling protocol to include extra attributes from ValueArray"""
+
+        try:
+            self.__dict__.update(state[-1])
+            super().__setstate__(state[:-1], *args, **kwargs)
+        except TypeError:
+            # This is a fallback so we can load old .npz files in mlptrain, see:
+            # https://github.com/duartegroup/autodE/issues/372
+            super().__setstate__(state, *args, **kwargs)
 
     def to(self, units) -> Any:
         """

doc/changelog.rst

@@ -13,6 +13,7 @@ Functionality improvements
 Bug Fixes
 *********
 - Fixes coordinate extraction in some G16 output files
+- Fixes loading old mlptrain .npz files
 
 Usability improvements/Changes
 ******************************

tests/data/old_mlptrain.npz

@@ -1,3 +1,5 @@
+import os
+
 import numpy as np
 import pytest
 
@@ -12,6 +14,8 @@
     _to,
 )
 
+here = os.path.dirname(os.path.abspath(__file__))
+
 
 class TmpValues(ValueArray):
     implemented_units = [ha, ev]
@@ -123,3 +127,23 @@ def test_force_constant():
 
     # should be able to convert to Ha/a0^2 without any problems
     _ = fc.to("Ha/a0^2")
+
+
+def test_pickle():
+    """Regression test for https://github.com/duartegroup/autodE/issues/221"""
+    import pickle
+
+    x = Gradient([[1.0, 1.0, 1.0]], units=ha_per_ang)
+    pickled_x = pickle.dumps(x, pickle.HIGHEST_PROTOCOL)
+    unpickled_x = pickle.loads(pickled_x)
+    assert unpickled_x.units == ha_per_ang
+    assert unpickled_x == x
+
+
+def test_load_old_mlptrain_npz():
+    """Regression test for https://github.com/duartegroup/autodE/issues/372"""
+    import numpy as np
+
+    npz_file = os.path.join(here, "data", "old_mlptrain.npz")
+    data = np.load(npz_file, allow_pickle=True)
+    assert data["F_true"] is not None