Merge pull request #55 from WMD-group/youngwonwoo-DFTexample

PyTASER DFT Workflow change in MAPI example

CHANGELOG.rst

@@ -1,6 +1,11 @@
 Change log
 ==========
 
+v2.1.4
+~~~~~~
+- Addition of MAPI example outputs download instructions to DFT example by @youngwonwoo.
+- Update to `from_dict()` method for `Tas` objects by @kavanase & @LucasGVerga
+
 v2.1.3
 ~~~~~~
 - Change of np.arange to np.linspace to avoid e_grid arrays with sizes different from NEDOS. (see the warning on numpy.arange documentation)

pytaser/tas.py

@@ -134,4 +134,9 @@ def decode_dict(subdict):
 
         d_dec = {k: convert_to_tuple(v) for k, v in d.items()}
         d_decoded = {k: decode_dict(v) for k, v in d_dec.items()}
+
+        for monty_key in ["@module", "@class"]:
+            if monty_key in d_decoded.keys():
+                d_decoded.pop(monty_key)
+
         return cls(**d_decoded)

setup.py

@@ -10,7 +10,7 @@
 long_description = pathlib.Path("README.md").read_text()
 setup(
     name="pytaser",
-    version="2.1.3",
+    version="2.1.4",
     description="TAS prediction tool",
     url="https://pytaser.readthedocs.io/en/latest/",
     author="Savyasanchi Aggarwal",

tests/test_generator.py

@@ -7,7 +7,7 @@
 from monty.serialization import dumpfn, loadfn
 from pymatgen.electronic_structure.core import Spin
 
-from pytaser import generator
+from pytaser import generator, tas
 
 
 def test_gaussian(datapath_gaas):
@@ -307,6 +307,50 @@ def test_save_and_load_tas_to_json(
         os.remove("tas.json")  # cleanup
 
 
+def test_save_and_load_tas_to_dict(
+    tas_object, cdte_tas_object, cdte_vasp_tas_object
+):
+    for tas_object in [tas_object, cdte_tas_object, cdte_vasp_tas_object]:
+        tas_as_dict = tas_object.as_dict()
+        tas_object_loaded = tas.Tas.from_dict(tas_as_dict)
+
+        # assert attributes are equal:
+        np.testing.assert_array_almost_equal(
+            tas_object.tas_total, tas_object_loaded.tas_total, decimal=1
+        )
+        for dict_attribute in [
+            "jdos_diff_if",
+            "jdos_light_if",
+            "jdos_dark_if",
+            "alpha_light_dict",
+            "weighted_jdos_light_if",
+            "weighted_jdos_dark_if",
+            "weighted_jdos_diff_if",
+        ]:
+            if getattr(tas_object, dict_attribute) is not None:
+                for key, array in getattr(tas_object, dict_attribute).items():
+                    np.testing.assert_array_almost_equal(
+                        array, getattr(tas_object_loaded, dict_attribute)[key]
+                    )
+        np.testing.assert_array_almost_equal(
+            tas_object.jdos_light_total, tas_object_loaded.jdos_light_total
+        )
+        np.testing.assert_array_almost_equal(
+            tas_object.jdos_dark_total, tas_object_loaded.jdos_dark_total
+        )
+        np.testing.assert_array_almost_equal(
+            tas_object.energy_mesh_ev, tas_object_loaded.energy_mesh_ev
+        )
+        assert tas_object.bandgap == tas_object_loaded.bandgap
+        assert tas_object.temp == tas_object_loaded.temp
+        assert tas_object.conc == tas_object_loaded.conc
+
+        if tas_object.alpha_dark is not None:
+            np.testing.assert_array_almost_equal(
+                tas_object.alpha_dark, tas_object_loaded.alpha_dark
+            )
+
+
 def test_generate_tas(generated_class, light, dark, tas_object, conditions):
     energy_min = 0
     energy_max = 4

tests/test_plotter.py

@@ -15,9 +15,9 @@ def test_ev_to_lambda():
     assert round(ev_to_lambda(input_ev), 2) == 495.94
 
 
-def test_lamda_to_ev():
-    input_lamda = 495.94
-    assert round(lambda_to_ev(input_lamda), 2) == 2.5
+def test_lambda_to_ev():
+    input_lambda = 495.94
+    assert round(lambda_to_ev(input_lambda), 2) == 2.5
 
 
 def test_cutoff_transitions(plotter_gaas):