Bandstructure wf

aiida_kkr/tests/files/db_dump_bs/test_energy_points

@@ -0,0 +1,12 @@
+-4.545469976344376217e-01
+9.090971898855952915e-01
+2.272727771712620193e+00
+3.636358353539645538e+00
+5.000002541059678229e+00
+-1.000000188750263952e+01
+-8.636357699982605496e+00
+-7.272727118155581927e+00
+-5.909096536328555693e+00
+-4.545452348808522558e+00
+-3.181821766981497213e+00
+-1.818177579461462745e+00

aiida_kkr/tests/workflows/test_bs_wc.py

@@ -0,0 +1,111 @@
+#!/usr/bin/env python
+# coding: utf-8
+
+from __future__ import absolute_import
+from __future__ import print_function
+import pytest
+from aiida_kkr.tests.dbsetup import *
+from aiida.engine import WorkChain, if_, ToContext, submit
+
+@pytest.mark.usefixtures("aiida_env")
+class Test_dbs_workflow():
+    """
+    Tests for the kkr_startpot workflow
+    """
+
+    @pytest.mark.timeout(240, method='thread')
+    def test_bs_wc_Cu(self):
+
+        from aiida import get_version
+        from aiida.orm import Code, load_node, Dict, StructureData
+        from aiida.plugins import DataFactory
+        from aiida.orm import Computer
+        from aiida.orm.querybuilder import QueryBuilder
+        from masci_tools.io.kkr_params import kkrparams
+        from aiida_kkr.workflows.bs import kkr_bs_wc
+        from numpy import array
+        import numpy as np   
+
+        print('AiiDA version: {}'.format(get_version()))  
+        Dict = DataFactory('dict')
+        StructureData = DataFactory('structure')
+
+        # preparation for computer and code 
+        kkr_codename = 'kkr'
+        computername = 'claix18_init'
+
+        wfbs = kkr_bs_wc.get_wf_default()
+
+        wfbs['NPT2'] = 12
+        wfbs['EMAX'] = 5
+        wfbs['EMIN'] = 10
+        wfbs['RCLUSTZ'] = 2.3
+        wfbs['TEMPR'] = 50.0  
+
+        params_bs = Dict(dict=wfbs)
+
+        # for runing in cluster or remote computer and should be rewiten for diferent computer
+        options1 = {'max_wallclock_seconds': 36000,'resources': 
+                  {'tot_num_mpiprocs': 48, 'num_machines': 1},
+                  'custom_scheduler_commands': 
+                  '#SBATCH --account=jara0191\n\nulimit -s unlimited; export OMP_STACKSIZE=2g',
+                  'withmpi':
+                  True}
+
+        # for runing in local computer        
+        options2 = {'queue_name' : queuename, 'resources': {"num_machines": 1}, 'max_wallclock_seconds' : 5*60, 'withmpi' : False, 'custom_scheduler_commands' : ''}
+        options = Dict(dict=options1)
+
+        # The scf-workflow needs also the voronoi and KKR codes to be able to run the calulations
+        KKRCode = Code.get_from_string(kkr_codename+'@'+computername)
+
+        label = 'bs calc Cu bulk'
+        descr = ' testing bs workflow for Cu bulk'
+
+        from aiida.tools.importexport import import_data
+
+        import_data('files/db_dump_bs/db_dump_kkrcalc_bs.tar.gz', silent=True)
+        kkr_calc_remote = load_node('d5782162-8393-4212-9340-c8ee8b725474').outputs.remote_folder
+
+        builder = kkr_bs_wc.get_builder()
+        builder.metadata.description = descr
+        builder.metadata.label = label
+        builder.kkr = KKRCode#kkrhost_local_code
+        builder.wf_parameters = params_bs
+        builder.options = options
+        builder.remote_data = kkr_calc_remote
+
+        from aiida.engine import run
+
+        out = run(builder)
+        n = out['results_wf']
+        n = n.get_dict()
+        assert n.get('successful')
+        assert n.get('list_of_errors') == []
+        d = out['BS_Data']
+        kpts = d.get_array('Kpts')
+        eng_points = d.get_array('energy_points')
+        BlochSpectral = d.get_array('BlochSpectralFunction')
+
+        # Loading the data from the previous calc (run manually) with the same config 
+        test_BSF = np.loadtxt('files/db_dump_bs/test_spectral')
+        test_Kpts = np.loadtxt('files/db_dump_bs/test_Kpts')
+        test_eng = np.loadtxt('files/db_dump_bs/test_energy_points')
+        # Define the error boundary
+        dos_limt = abs(np.amin(BlochSpectral)*1E-2)
+        eng_min = abs(np.amin(eng_points)*1E-7)
+
+        differ_BSF = np.subtract(BlochSpectral,test_BSF)
+        shape_differ_BSF = np.shape(differ_BSF)
+         # shape(differ_BSF) =~ (kpts*eng) =~ (y*x) 
+        for i in range(shape_differ_BSF[0]): 
+
+            assert sum(abs(kpts[i,:] - test_Kpts[i,:] )) < 10**-7
+            for j in range(shape_differ_BSF[1]):    
+                # here to inspect the density validity
+                assert dos_limt > abs(differ_BSF[i,j])
+                if i==0 :
+                    # here to inspect the energy validity     
+                    assert eng_min > abs(eng_points[j] -test_eng[j])
+
+