def datamining(filep): """ Read some output variables from abinit-o_OUT.nc """ print('Extracting ecut and etotal') if os.path.isfile(filep + os.sep + 'abinit-o_OUT.nc'): data = netcdf2dict(filep + os.sep + 'abinit-o_OUT.nc') else: data = netcdf2dict(path + os.sep + 'abinit_04' + os.sep + 'abinit-o_OUT.nc') print(data) print(data['ecut'], data['etotal']) return data['ecut'], data['etotal']
def datamining(filep): """ Read some output variables from abinit-o_OUT.nc """ print('Extracting ecut and etotal') if os.path.isfile(filep + os.sep + 'abinit-o_OUT.nc'): data = netcdf2dict(filep + os.sep + 'abinit-o_OUT.nc') else: data = netcdf2dict(path + os.sep + 'abinit_04' + os.sep + 'abinit-o_OUT.nc') print(data) print(data['ecut'], data['etotal']) return data['ecut'], data['etotal']
def test_abinit_utils(): """ Test (pychemia.code.abinit) [utils] : """ from pychemia.utils.netcdf import netcdf2dict from pychemia.code.abinit import xyz2input, psp_name filename = "tests/data/abinit_05/abinit-o_OUT.nc" print(len(netcdf2dict(filename))) assert len(netcdf2dict(filename)) == 45 assert psp_name(1, 'LDA', 'FHI') == '01-H.LDA.fhi' filename = "tests/data/abinit_01/abinit_DS11.xyz" assert xyz2input(filename).variables['natom'] == 2
def test_abinit_utils(): """ Tests (pychemia.code.abinit) [utils] : """ from pychemia.utils.netcdf import netcdf2dict from pychemia.code.abinit import xyz2input, psp_name filename = "tests/data/abinit_05/abinit-o_OUT.nc" print(len(netcdf2dict(filename))) assert len(netcdf2dict(filename)) == 45 assert psp_name(1, 'LDA', 'FHI') == '01-H.LDA.fhi' filename = "tests/data/abinit_01/abinit_DS11.xyz" assert xyz2input(filename).variables['natom'] == 2
def __init__(self, input_filename=None): CodeInput.__init__(self) if input_filename is None: self.input_file = 'abinit.in' else: self.input_file = input_filename if os.path.isfile(self.input_file): if self.input_file[-6:] == 'OUT.nc': self.variables = netcdf2dict(self.input_file) else: self.read()
def __init__(self, input_filename=None): CodeInput.__init__(self) if input_filename is None: self.input_file = 'abinit.in' else: self.input_file = input_filename if os.path.isfile(self.input_file): if self.input_file[-6:] == 'OUT.nc': self.variables = netcdf2dict(self.input_file) else: self.read()
def test_example2(): """ Example of a multiple calc : """ path = 'tests/data' assert (os.path.isdir(path)) if which('abinit') is None: print('The executable "abinit" is not in the PATH') print('Using the results of a previous calc') check_results(path + os.sep + 'abinit_04') return workdir = tempfile.mkdtemp() print("Work directory: %s" % workdir) assert (os.path.isfile(path + '/abinit_04/t44.in')) av = pychemia.code.abinit.AbinitInput(path + '/abinit_04/t44.in') print('Original input:\n%s' % av) abifiles = pychemia.code.abinit.AbiFiles(workdir) abifiles.set_input(av) abifiles.set_psps('LDA', 'FHI') abifiles.create() res = [] wf = open(workdir + '/results.json', 'w') cwd = os.getcwd() os.chdir(workdir) for i in range(3): av.set_value('ecut', av.get_value('ecut') + 3) print('Computing convergence study with ecut=%f ' % av.get_value('ecut'), end='') if i > 0: av.set_value('irdwfk', 1) av.write(abifiles.get_input_filename()) abifile = open(workdir + '/abinit.files') logfile = open(workdir + '/abinit.log', 'w') subprocess.call(['abinit'], stdin=abifile, stdout=logfile) if os.path.isfile('abinit-o_WFK'): shutil.copyfile('abinit-o_WFK', 'abinit-i_WFK') data = netcdf2dict(workdir + '/abinit-o_OUT.nc') os.rename(workdir + '/abinit-o_OUT.nc', '%s/abinit-o_OUT.nc_%d' % (workdir, i)) res.append({'ecut': data['ecut'], 'etotal': data['etotal']}) print('Total energy: %f' % data['etotal']) os.chdir(cwd) json.dump(res, wf) wf.close() check_results(workdir) shutil.rmtree(workdir)
def test_example2(): """ Example of a multiple calc : """ path = 'tests/data' assert (os.path.isdir(path)) if which('abinit') is None: print('The executable "abinit" is not in the PATH') print('Using the results of a previous calc') check_results(path + os.sep + 'abinit_04') return workdir = tempfile.mkdtemp() print("Work directory: %s" % workdir) assert (os.path.isfile(path + '/abinit_04/t44.in')) av = pychemia.code.abinit.AbinitInput(path + '/abinit_04/t44.in') print('Original input:\n%s' % av) abifiles = pychemia.code.abinit.AbiFiles(workdir) abifiles.set_input(av) abifiles.set_psps('LDA', 'FHI') abifiles.create() res = [] wf = open(workdir + '/results.json', 'w') cwd = os.getcwd() os.chdir(workdir) for i in range(3): av.set_value('ecut', av.get_value('ecut') + 3) print('Computing convergence study with ecut=%f ' % av.get_value('ecut'), end='') if i > 0: av.set_value('irdwfk', 1) av.write(abifiles.get_input_filename()) abifile = open(workdir + '/abinit.files') logfile = open(workdir + '/abinit.log', 'w') subprocess.call(['abinit'], stdin=abifile, stdout=logfile) if os.path.isfile('abinit-o_WFK'): shutil.copyfile('abinit-o_WFK', 'abinit-i_WFK') data = netcdf2dict(workdir + '/abinit-o_OUT.nc') os.rename(workdir + '/abinit-o_OUT.nc', '%s/abinit-o_OUT.nc_%d' % (workdir, i)) res.append({'ecut': data['ecut'], 'etotal': data['etotal']}) print('Total energy: %f' % data['etotal']) os.chdir(cwd) json.dump(res, wf) wf.close() check_results(workdir) shutil.rmtree(workdir)