def test_get_dftbp_data(self):
env = {}
database = Database()
#
src = 'test_dftbutils/scc'
dst = 'test.scc'
get_dftbp_data(env, database, src, dst)
modeldict = database.get(dst)
self.assertDictEqual(modeldict, self.ref_scc)
#
src = 'test_dftbutils/bs'
dst = 'test.bs'
get_dftbp_data(env, database, src, dst)
modeldict = database.get(dst)
self.assertDictEqual(modeldict, self.ref_bs)
def test_objtype_values_single_model_single_data(self):
"""Can we create value-type objective for a single model"""
yamldata = """objectives:
- band_gap:
doc: Band gap, Si
models: Si/bs
ref: 1.12
weight: 3.0
"""
dat = 1.2
ow = 1.
spec = yaml.load(yamldata)['objectives'][0]
que = 'band_gap'
ref = 1.12
www = 3.0
mnm = 'Si/bs'
# set data base
database = Database()
database.update('Si/bs')
modeldb = database.get('Si/bs')
# check declaration
objv = oo.get_objective(spec)
self.assertEqual(objv.objtype, 'values')
self.assertEqual(objv.model_names, mnm)
self.assertEqual(objv.model_weights, ow)
self.assertEqual(objv.weight, www)
self.assertEqual(objv.ref_data, ref)
self.assertEqual(objv.subweights, ow)
self.assertEqual(objv.query_key, que)
# check __call__()
modeldb['band_gap'] = dat
mdat, rdat, weights = objv.get(database)
self.assertEqual(mdat, dat)
self.assertEqual(rdat, ref)
self.assertEqual(weights, ow)
def test_skparplot(self):
"""Can we plot a band-structure objectives?"""
env = {}
database = Database()
latticeinfo = {'type': 'FCC', 'param': 5.4315}
model = 'Si.bs'
filename = '_workdir/test_plot/bs1.pdf'
get_bandstructure(env,
database,
'test_dftbutils/Si/bs/',
model,
latticeinfo=latticeinfo)
modeldb = database.get(model)
bands = modeldb['bands']
eps = 0.25
jitter = eps * (0.5 - random(bands.shape))
altbands = bands + jitter
if os.path.exists(filename):
os.remove(filename)
else:
os.makedirs('_workdir/test_plot', exist_ok=True)
skparplot(modeldb['kvector'], [altbands, bands],
filename=filename,
xticklabels=modeldb['kticklabels'],
xlabel='wave-vector',
ylabel='Energy, eV',
linelabels=['ref', 'model'],
ylim=(-13, 6))
self.assertTrue(os.path.exists(filename))
def test_get_special_Ek_options(self):
"""Get E(k) for explicitly given, and multiple bands"""
env = {}
database = Database()
model = 'test.Ek'
src = 'test_dftbutils/Si/bs'
get_bandstructure(env,
database,
src,
model,
latticeinfo={
'type': 'FCC',
'param': 5.431
})
dst = database.get(model)
get_special_Ek(env,
database,
model,
model,
sympts=['K', 'L'],
extract={
'cb': [0, 2, 4, 6],
'vb': [0, 2, 4, 6]
})
self.assertAlmostEqual(dst['Ec_L_4'], 2.8089, places=3)
self.assertAlmostEqual(dst['Ec_L_0'], 0.3995, places=3)
self.assertAlmostEqual(dst['Ec_K_0'], 0.6915, places=3)
#
self.assertAlmostEqual(dst['Ev_L_0'], -2.5016, places=3)
self.assertAlmostEqual(dst['Ev_L_4'], -7.842, places=3)
self.assertAlmostEqual(dst['Ev_L_6'], -11.3369, places=3)
self.assertAlmostEqual(dst['Ev_K_0'], -3.5884, places=3)
self.assertAlmostEqual(dst['Ev_K_2'], -4.963, places=3)
self.assertAlmostEqual(dst['Ev_K_4'], -8.694, places=3)
self.assertAlmostEqual(dst['Ev_K_6'], -9.8759, places=3)
def test_get_special_Ek(self):
"""Get E(k) for k obtained from the kLines"""
env = {}
database = Database()
model = 'test.Ek'
src = 'test_dftbutils/Si/bs'
get_bandstructure(env,
database,
src,
model,
latticeinfo={
'type': 'FCC',
'param': 5.431
})
dst = database.get(model)
get_special_Ek(env, database, model, model)
self.assertAlmostEqual(dst['Ec_L_0'], 0.4, places=3)
self.assertAlmostEqual(dst['Ec_G_0'], 1.616, places=3)
self.assertAlmostEqual(dst['Ec_X_0'], 0.2025, places=3)
self.assertAlmostEqual(dst['Ec_U_0'], 0.6915, places=3)
self.assertAlmostEqual(dst['Ec_K_0'], 0.6915, places=3)
#
self.assertAlmostEqual(dst['Ev_L_0'], -2.5016, places=3)
self.assertAlmostEqual(dst['Ev_G_0'], -1.1289, places=3)
self.assertAlmostEqual(dst['Ev_X_0'], -3.9592, places=3)
self.assertAlmostEqual(dst['Ev_U_0'], -3.5885, places=3)
self.assertAlmostEqual(dst['Ev_K_0'], -3.5885, places=3)
def test_evaluate_bands(self):
"""Can we evaluate value-type objective of type bands (2D array)"""
yamldata = """objectives:
- bands:
models: A
ref:
file: ./reference_data/fakebands.dat
loader_args: {unpack: False}
process:
rm_columns: 1
eval: [RMS, relerr]
"""
# set model data
database = Database()
database.update('A')
db1 = database.get('A')
# declaration of objective
spec = yaml.load(yamldata)['objectives'][0]
objv = oo.get_objective(spec)
self.assertAlmostEqual(1., np.sum(objv.subweights))
#logger.debug(objv.ref_data)
#logger.debug(objv.subweights)
db1['bands'] = objv.ref_data * 1.1
cost = np.sqrt(np.sum(objv.subweights*relerr(objv.ref_data, db1['bands'])**2))
#logger.debug(cost)
# evaluate
self.assertAlmostEqual(cost, objv(database))
def test_execution_get_dftbp(self):
"""Can we execute the declared get_dftbp_* tasks?"""
taskdict = {}
update_taskdict(taskdict,
[['skpar.core.taskdict', ['get', 'sub', 'run']]])
update_taskdict(
taskdict, [['skpar.dftbutils', ['get_bs', 'get_meff', 'get_Ek']]])
userinp = yaml.load(self.yamlin)
tasklist = get_tasklist(userinp['tasks'])
tasks = initialise_tasks(tasklist, taskdict)
#
database = Database()
env = {
'workroot': '.',
}
for task in tasks:
print(task)
task(env, database)
# 'Si.bs' should be added through the task execution
db = database.get('Si.bs')
self.assertAlmostEqual(db['Egap'], 1.129, places=3)
self.assertAlmostEqual(db['Ef'], -3.0621, places=4)
self.assertAlmostEqual(db['me_GX'], 0.935, places=3)
self.assertAlmostEqual(db['mh_GK'], -1.891, places=3)
self.assertAlmostEqual(db['Ec_L_0'], 0.4, places=3)
self.assertAlmostEqual(db['Ec_G_0'], 1.6156, places=3)
self.assertAlmostEqual(db['Ec_X_0'], 0.2025, places=3)
self.assertAlmostEqual(db['Ec_U_0'], 0.6915, places=3)
self.assertAlmostEqual(db['Ec_K_0'], 0.6915, places=3)
def test_evaluate_multiplemodels_singleitem(self):
"""Can we evaluate value-type objective for multiple models"""
yamldata = """objectives:
- item:
models: [A, B, C]
ref: [2.0, 2., 3.]
options:
# normalise: True
subweights: [2, 1, 1.5]
"""
# set model data
database = Database()
db1 = {'item': 1.0}
db2 = {'item': 1.0}
db3 = {'item': 1.0}
database.update('A', db1)
_db = database.get('A')
self.assertDictEqual(_db, db1)
database.update('B', db2)
database.update('C', db3)
# declaration of objective
spec = yaml.load(yamldata)['objectives'][0]
objv = oo.get_objective(spec)
# evaluate
self.assertAlmostEqual(1.4142135623730951, objv(database))
def test_simple(self):
"""Can we parse task declarations successfully"""
jsondata = """ {
"tasks": [
{"sub": [["./tmp/template.parameters.dat"]]} ,
{"run": ["cp parameters.dat value.dat", "./tmp"]} ,
{"get": ["value", "tmp/value.dat", "model"]}
]
}
"""
yamldata = """
tasks:
- sub: [[./tmp/template.parameters.dat]]
- run: ["cp parameters.dat value.dat", ./tmp]
- get: [value, tmp/value.dat, model]
"""
taskdict = {}
update_taskdict(taskdict,
[['skpar.core.taskdict', ['get', 'sub', 'run']]])
yamldata = yaml.load(yamldata)
# print('yaml data')
# pprint(yamldata)
jsondata = json.loads(jsondata)
# print('json data')
# pprint(jsondata)
# self.assertTrue(jsondata == yamldata) # fails for whatever reason
tasklist = []
userinp = yamldata
tasklist = get_tasklist(userinp['tasks'])
tasks = initialise_tasks(tasklist, taskdict)
#
var = 10
database = Database()
par = Parameter('p0', value=var)
workroot = './'
coreargs = {
'workroot': workroot,
'parametervalues': [par.value],
'parameternames': [par.name]
}
try:
shutil.rmtree('./tmp')
except FileNotFoundError:
pass
os.makedirs('./tmp')
with open('./tmp/template.parameters.dat', 'w') as template:
template.writelines("%(p0)f\n")
# with open('./tmp/template.parameters.dat', 'r') as template:
# tmplstr = template.readlines()
# print(tmplstr)
LOGGER.info('Executing tasks')
for task in tasks:
# LOGGER.info(task)
task(coreargs, database)
self.assertEqual(np.atleast_1d(var),
database.get('model', {}).get('value'))
shutil.rmtree('./tmp')
def test_objtype_values_single_model_array_data(self):
"""Can we create 1d-array-values-type objective for a single model"""
yamldata = """objectives:
- Etot(Vol):
doc: 'Energy-Volume dependnce of Wurtziteac structure'
models: GaN-W-ac
ref: [-20.236, -21.099, -21.829, -22.45, -22.967,
-23.387, -23.719, -23.974,
-24.158, -24.278, -24.304, -24.348, -24.309,
-24.228, -24.11 , -23.952,
-23.769, -23.559, -23.328, -23.076, -22.809]
options:
subweights: [1,1,1,1,1, 2,2,2, 3,3,3,3,3, 2,2,2, 1,1,1,1,1]
"""
data = [-20.24,-21.1,-21.83,-22.45,-22.97,
-23.4,-23.72,-23.97,
-24.2,-24.3,-24.3,-24.35,-24.31,
-24.23,-24.11,-23.9,
-23.77,-23.56,-23.3,-23.1,-22.8]
logger.info(data)
que = 'Etot(Vol)'
ref = [-20.236, -21.099, -21.829, -22.45,-22.967,
-23.387, -23.719, -23.974,
-24.158, -24.278, -24.304, -24.348, -24.309,
-24.228, -24.11, -23.952,
-23.769, -23.559, -23.328, -23.076, -22.809]
sbw = [1,1,1,1,1, 2,2,2, 3,3,3,3,3, 2,2,2, 1,1,1,1,1]
sbw = np.asarray(sbw)/np.sum(sbw) # normalise
model = 'GaN-W-ac'
# set data base
database = Database()
database.update(model)
modeldb = database.get(model)
# check declaration
spec = yaml.load(yamldata)['objectives'][0]
logger.info(spec)
objv = oo.get_objective(spec)
self.assertEqual(objv.model_names, model)
self.assertEqual(objv.model_weights, 1.)
self.assertEqual(objv.weight, 1)
nptest.assert_array_equal(objv.ref_data, ref, verbose=True)
nptest.assert_array_equal(objv.subweights, sbw, verbose=True)
self.assertEqual(objv.query_key, que)
self.assertEqual(objv.objtype, 'values')
# check __call__()
modeldb[que] = data
mdata, rdata, weights = objv.get(database)
nptest.assert_array_equal(mdata, data, verbose=True)
nptest.assert_array_equal(rdata, ref, verbose=True)
nptest.assert_array_equal(weights, sbw, verbose=True)
def test_get_bandstructure(self):
"""Can we get the bandstructure and gap/cb/vb details?"""
env = {}
database = Database()
src = 'test_dftbutils/bs'
dst = 'test.bs'
get_bandstructure(env, database, src, dst)
modeldict = database.get(dst)
nptest.assert_array_almost_equal(modeldict['bands'], self.ref_bands)
self.assertEqual(modeldict['nkpts'], self.ref_nk)
self.assertEqual(modeldict['nbands'], self.ref_nb)
self.assertEqual(modeldict['Ef'], self.ref_Ef)
self.assertEqual(modeldict['Egap'], self.ref_Eg)
self.assertEqual(modeldict['Ecb'], self.ref_Ec)
self.assertEqual(modeldict['Evb'], self.ref_Ev)
def test_evaluate_singleitem(self):
"""Can we evaluate value-type objective for a single model"""
yamldata = """objectives:
- item:
models: A
ref: 1.0
"""
# set data base
database = Database()
database.update('A')
db = database.get('A')
# declaration of objective
spec = yaml.load(yamldata)['objectives'][0]
objv = oo.get_objective(spec)
# evaluate
db['item'] = 1.2
self.assertAlmostEqual(0.2, objv(database))
def test_database(self):
"""Can we update model DB"""
database = Database()
self.assertTrue(database is not None)
#
database.update('m1', {'i1': 42})
self.assertDictEqual(database.all(), {'m1': {'i1': 42}})
#
database.update('m1', {'i1': 33})
self.assertDictEqual(database.all(), {'m1': {'i1': 33}})
#
database.update('m2', {'i1': 10})
self.assertDictEqual(database.all(), {'m1': {'i1': 33},
'm2': {'i1': 10}})
#
database.update('m2', {'i2': 20})
self.assertDictEqual(database.all(), {'m1': {'i1': 33},
'm2': {'i1': 10,
'i2': 20}})
update(database, 'm1', {'i2': 25})
self.assertDictEqual(database.all(), {'m1': {'i1': 33,
'i2': 25},
'm2': {'i1': 10,
'i2': 20}})
database.update({'m2': {'i3': 40}})
self.assertDictEqual(database.all(), {'m1': {'i1': 33,
'i2': 25},
'm2': {'i3': 40}})
#
mdb = database.get('m2')
self.assertDictEqual(mdb, {'i3': 40})
self.assertEqual(database.get_item('m1', 'i2'), 25)
#
# check query initialised without database
query = Query('m2', 'i1')
self.assertEqual(query(database, atleast_1d=False), None)
query = Query('m2', 'i3')
self.assertEqual(query(database, atleast_1d=False), 40)
#
# check query initialised with database within database.query method
self.assertEqual(database.query('m1', 'i1', atleast_1d=False), 33)
nptest.assert_array_equal(database.query('m1', 'i1'), [33])
#
database.clear()
self.assertDictEqual(database.all(), {})
def test_twopartemplates(self):
"""Can we parse task declarations successfully"""
yamldata = """
tasks:
- sub: [[./tmp/template.par1.dat, ./tmp/template.par2.dat]]
- run: ['bash run.sh', ./tmp]
- get: [value, tmp/values.dat, model]
"""
taskdict = {}
update_taskdict(taskdict,
[['skpar.core.taskdict', ['get', 'sub', 'run']]])
yamldata = yaml.load(yamldata)['tasks']
tasklist = []
tasklist = get_tasklist(yamldata)
tasks = initialise_tasks(tasklist, taskdict)
#
var1 = 10
var2 = 20
database = Database()
params = [Parameter('p0', value=var1), Parameter('p1', value=var2)]
workroot = './'
coreargs = {
'parametervalues': [p.value for p in params],
'parameternames': [p.name for p in params]
}
try:
shutil.rmtree('./tmp')
except FileNotFoundError:
pass
os.makedirs('./tmp')
with open('./tmp/template.par1.dat', 'w') as template:
template.writelines("%(p0)f\n")
with open('./tmp/template.par2.dat', 'w') as template:
template.writelines("%(p1)f\n")
with open('./tmp/run.sh', 'w') as template:
template.writelines('cat par*.dat > values.dat\n')
for task in tasks:
LOGGER.info(task)
task(coreargs, database)
self.assertListEqual([var1, var2],
list(database.get('model', {}).get('value')))
shutil.rmtree('./tmp')
def test_get_effmasses_default(self):
"""Can we get effective masses in addition to band-structure, with default settings?"""
env = {}
database = Database()
src = 'test_dftbutils/Si/bs'
model = 'test.meff'
get_bandstructure(env,
database,
src,
model,
latticeinfo={
'type': 'FCC',
'param': 5.431
})
dst = database.get(model)
# the values below are in oldskpar.debug.log in the above dir
self.assertTrue(dst['withSOC'])
self.assertEqual(dst['ivbtop'], 7)
self.assertEqual(dst['nkpts'], 206)
self.assertEqual(dst['nbands'], 36)
self.assertAlmostEqual(dst['Ef'], -3.0621, places=3)
self.assertAlmostEqual(dst['Egap'], 1.1289, places=3)
self.assertAlmostEqual(dst['Ecb'], -3.06221, places=3)
self.assertAlmostEqual(dst['Evb'], -4.19099, places=3)
#
ref_klines = [('L', 0), ('Gamma', 53), ('X', 113), ('U', 141),
('K', 142), ('Gamma', 205)]
ref_klinesdict = {
'K': [142],
'X': [113],
'Gamma': [53, 205],
'L': [0],
'U': [141]
}
self.assertListEqual(dst['kLines'], ref_klines)
self.assertDictEqual(dst['kLinesDict'], ref_klinesdict)
get_effmasses(env, database, model, model)
ref_meff_tags = ['me_LG', 'me_GX', 'me_XU', 'me_KG']
ref_meff_tags.extend(['mh_LG', 'mh_GX', 'mh_XU', 'mh_KG'])
self.assertTrue(all([key in dst for key in ref_meff_tags]))
def test_parse_input(self):
"""Can we parse input, create an optimiser instance, and run the tasks?
"""
filename = "skpar_in_optimise.yaml"
taskdict, tasklist, objectives, optimisation, config =\
parse_input(filename)
print (taskdict)
print (tasklist)
workroot = config.get('workroot', None)
templatedir = config.get('templatedir', None)
create_workdir(workroot, templatedir)
algo, options, parameters = optimisation
parnames = [p.name for p in parameters]
evaluate = Evaluator(objectives, tasklist, taskdict, parnames, config)
optimiser = Optimiser(algo, parameters, evaluate, options)
# initialise parameter values, pretending to be optimisation engine
params = np.array([10.0, -2.5, 0.5, 0.05])
for pini, par in zip(params, optimiser.parameters):
par.value = pini
logger.debug ("### ---------------------------------------- ###")
logger.debug ("### ----------- Parameters ----------------- ###")
logger.debug ("### ---------------------------------------- ###")
for pp in optimiser.parameters:
logger.debug (pp)
# initialise tasks manually
optimiser.evaluate.tasks = initialise_tasks(tasklist, taskdict,
report=True)
env = {'workroot': workroot,
'parameternames': parnames,
'parametervalues': params,
'iteration': None}
workdir = workroot
database = Database()
# check task 0
self.assertEqual(optimiser.evaluate.tasks[0].name, 'set')
self.assertEqual(optimiser.evaluate.tasks[0].func,
core_taskdict.substitute_parameters)
self.assertEqual(optimiser.evaluate.tasks[0].args,
[['template.parameters.dat']])
optimiser.evaluate.tasks[0](env, database)
parfile = os.path.abspath(os.path.join(workdir, 'parameters.dat'))
raw = np.loadtxt(parfile, dtype=[('keys', 'S15'), ('values', 'float')])
_values = np.array([pair[1] for pair in raw])
_names = [pair[0].decode("utf-8") for pair in raw]
nptest.assert_array_equal(params, _values)
self.assertListEqual(parnames, _names)
# check task 1
exe = 'python3'.split()
self.assertEqual(optimiser.evaluate.tasks[1].name, 'run')
self.assertEqual(optimiser.evaluate.tasks[1].func,
core_taskdict.execute)
self.assertEqual(optimiser.evaluate.tasks[1].args,
['python3 model_poly3.py'])
optimiser.evaluate.tasks[1](env, database)
# check task 2
self.assertEqual(optimiser.evaluate.tasks[2].name, 'get')
self.assertEqual(optimiser.evaluate.tasks[2].func,
core_taskdict.get_model_data)
self.assertEqual(optimiser.evaluate.tasks[2].args,
['yval', 'model_poly3_out.dat', 'poly3'])
optimiser.evaluate.tasks[2](env, database)
modeldb = database.get('poly3')
self.assertTrue(modeldb is not None)
datafile = os.path.abspath(os.path.join(workdir, 'model_poly3_out.dat'))
dataout = np.loadtxt(datafile)
nptest.assert_array_equal(modeldb['yval'], dataout)
logger.debug("Model DB poly3:")
logger.debug(database.get('poly3').items())
def test_get_effmasses_select(self):
"""Can we get select effective masses with a control options?"""
env = {}
database = Database()
model = 'test.meff'
# NOTABENE: the refdata here is from SOC calculation!!!
src = 'test_dftbutils/Si/bs'
get_bandstructure(env,
database,
src,
model,
latticeinfo={
'type': 'FCC',
'param': 5.431
})
dst = database.get(model)
directions = ['Gamma-X', 'Gamma-L', 'Gamma-K']
# Example how to extract different masses over a different energy window:
# Note that subsequent extractions overwrite final data in dst, so we start with
# the deepest bands, and than reduce the number of bands, towards to top of VB
# The energy window should be adjusted depending on the anticipated curvature of the band
get_effmasses(env,
database,
model,
model,
directions=directions,
carriers='e',
nb=1,
Erange=0.005,
usebandindex=True)
# get the lowest band masses: (spin-orbit); forceErange seems to not work properly?
get_effmasses(env,
database,
model,
model,
directions=directions,
carriers='h',
nb=5,
Erange=0.0015,
forceErange=True)
# get the light hole bands (3 and 4)
get_effmasses(env,
database,
model,
model,
directions=directions,
carriers='h',
nb=3,
Erange=0.008)
# get the top two (heavy hole) bands (1 and 2); enforce indexing! (i.e. add _0)
get_effmasses(env,
database,
model,
model,
directions=directions,
carriers='h',
nb=1,
Erange=0.002,
usebandindex=True)
self.assertAlmostEqual(dst['me_GX_0'], 0.935, places=3)
self.assertAlmostEqual(dst['mh_GX_0'], -0.278, places=2)
self.assertAlmostEqual(dst['mh_GK_0'], -1.891, places=3)
self.assertAlmostEqual(dst['mh_GL_0'], -0.633, places=3)
self.assertAlmostEqual(dst['mh_GX_2'], -0.286, places=3)
self.assertAlmostEqual(dst['mh_GK_2'], -0.362, places=3)
self.assertAlmostEqual(dst['mh_GL_2'], -2.2426, places=3)
self.assertAlmostEqual(dst['mh_GX_4'], -0.1389, places=3)
self.assertAlmostEqual(dst['mh_GK_4'], -0.095, places=3)
self.assertAlmostEqual(dst['mh_GL_4'], -0.086, places=3)
self.assertAlmostEqual(dst['cbminpos_GX_0'], 0.817, places=2)
