Slurm job submission script fix. (#109)

* Magnetic setup and LOCPOT update.

* Added LOCPOT, test Fermi velocity, test Tc

* Pycodestyle fix.

* LDAU module added.

* Magnetic ordering,EFG setup, Interface fix

* Pycodestyle fix.

* Pycodestyle fix.

* Delete rem.sh

* Atoms dim test.

* Slurm queue fix.

* Test coverage

* Pycodestyle fix.

* Pycodestyle fix in magmom_setup

jarvis/__init__.py

@@ -1,2 +1,2 @@
 """Version number."""
-__version__ = "2020.7.25"
+__version__ = "2020.8.7"

jarvis/analysis/magnetism/magmom_setup.py

@@ -199,23 +199,10 @@ def get_minimum_configs(self, min_configs=10, enforce_primitive=True):
         while len(symm_list) < min_configs:
             dim[index_to_expand[count]] += 1
             symm_list, ss = self.get_unique_magnetic_structures(
-                atoms, supercell_dim=dim, magnetic_ions=["Mn"]
+                atoms, supercell_dim=dim, magnetic_ions=self.get_mag_ions()
             )
             count = count + 1
             if count > 2:
                 count = 0
             print("Supercell dimension", dim)
         return symm_list, ss
-
-
-"""
-if __name__ == "__main__":
-    from jarvis.db.figshare import data
-    dft3d=data('dft_3d')
-    for i in dft3d:
-     if i['jid']=='JVASP-22693':
-        atoms=Atoms.from_dict(i['atoms']).get_primitive_atoms
-
-    Mag = MagneticOrdering(atoms).get_minimum_configs(min_configs=3)
-    print ('Mag',Mag)
-"""

jarvis/io/vasp/outputs.py

@@ -351,7 +351,7 @@ def converged(self):
             pass
         return cnvg
 
-    @property
+    #  @property
     def efg_tensor_diag(self, std_conv=True, prec=3):
         """Get diagonalized electric field gradient tensor."""
         # std_conv: |Vzz|>=|Vyy|>=|Vxx|, eta=(Vxx-Vyy)/Vzz

jarvis/tasks/queue_jobs.py

@@ -146,7 +146,7 @@ def slurm(
         f = open(filename, "w")
         f.write("%s\n" % shell)
         f.write("#SBATCH --nodes=%d\n" % (nnodes))
-        f.write("SBATCH --ntasks-per-node=%d\n" % (cores))
+        f.write("#SBATCH --ntasks-per-node=%d\n" % (cores))
 
         if walltime is not None:
             if isinstance(walltime, str):

jarvis/tests/testfiles/io/calphad/test_calphad.py

@@ -1,14 +1,19 @@
 from jarvis.io.calphad.write_decorated_poscar import get_selective_dyn_decorated_atoms
 from jarvis.core.atoms import Atoms
-
+from jarvis.io.vasp.inputs import Poscar
 
 def test_cal():
     box = [[2.715, 2.715, 0], [0, 2.715, 2.715], [2.715, 0, 2.715]]
     coords = [[0, 0, 0], [0.25, 0.2, 0.25]]
     elements = ["Si", "Si"]
     atoms = Atoms(lattice_mat=box, coords=coords, elements=elements)
     decorated_atoms, hall_number, wsymbols = get_selective_dyn_decorated_atoms(atoms)
+    print (decorated_atoms)
+    p = Poscar(decorated_atoms)
+    p.write_file('POSCAR')
+    #p2 = Poscar.from_file('POSCAR')
+    #print (p2)
     assert (wsymbols, hall_number) == (["i", "i"], 63)
 
 
-# test_cal()
+#test_cal()

jarvis/tests/testfiles/io/vasp/test_inputs.py

@@ -116,6 +116,8 @@ def test_inputs():
     assert (round(p.atoms.density, 2), i.to_dict()["ISIF"]) == (2.25, "3")
     d = i.to_dict()
     ii = Incar.from_dict(d)
+    ii.write_file('INCAR')
+    print (ii)
     pot = os.path.join(
         os.path.dirname(__file__), "POT_GGA_PAW_PBE", "Xe", "POTCAR",
     )

jarvis/tests/testfiles/io/vasp/test_outputs.py

@@ -228,9 +228,17 @@ def test_locpot():
     vac = loc.vac_potential()[0]
     assert round(vac,2) == round(7.62302803577618, 2)
 
+
     td = loc.to_dict()
     fd = Locpot.from_dict(td)
 
+    vac = loc.vac_potential(direction='Y')[0]
+    assert round(vac,2) == round(7.62302803577618, 2)
+
+    vac = loc.vac_potential(direction='Z')[0]
+    assert round(vac,2) == round(7.62302803577618, 2)
+
+
 def test_vrun():
     # print ('gapp',round(vrun.get_indir_gap,2))
     assert (round(vrun.get_indir_gap[0], 2)) == (0.73)
@@ -269,7 +277,8 @@ def test_out():
     out_efg_raw = Outcar(
         os.path.join(os.path.dirname(__file__), "OUTCAR.EFG-JVASP-12148")
     ).efg_raw_tensor
-    assert out_efg.efg_tensor_diag[0][0] == -4.766
+    assert out_efg.efg_tensor_diag()[0][0] == -4.766
+    assert out_efg.efg_tensor_diag(std_conv=False)[0][0] == -4.766
     assert out_efg.quad_mom[0][0] == 0.023
     assert out_efg.converged == True
     td = out_efg.to_dict()
@@ -278,7 +287,7 @@ def test_out():
     print()
     print("out_efg_raw", np.linalg.eig(out_efg_raw)[0])
     print()
-    print("out_efg", out_efg.efg_tensor_diag)
+    print("out_efg", out_efg.efg_tensor_diag())
     print()
 
 

setup.py

@@ -11,7 +11,7 @@
 
 setup(
     name="jarvis-tools",
-    version="2020.7.25",
+    version="2020.8.7",
     long_description=long_d,
     install_requires=[
         "numpy",