def setUp(self):
self.data, self.logfile = getdatafile(Gaussian, "basicGaussian03",
["dvb_un_sp.out"])
self.analysis = CSPA(self.data)
self.analysis.logger.setLevel(0)
self.analysis.calculate()
def WriteCovalencyReport(fileName,
calculationType='LPA',
element='Fe',
homoLumoRange=15,
printThreshold=5):
filename = fileName
data = ccread(filename)
if calculationType == 'LPA':
m = LPA(data) #This is for Lowdin Analysis.
elif calculationType == 'MPA':
m = MPA(data) #Mulliken Population Analysis
elif calculationType == 'csquared':
m = CSPA(data) #C-squared Analysis
else:
Exception('Calculation type not supported.')
print(element)
#Section: Regular Expression Variables
regexZ2 = re.compile(element + '.*DZ2')
regexXZ = re.compile(element + '.*DXZ')
regexYZ = re.compile(element + '.*DYZ')
regexX2Y2 = re.compile(element + '.*DX2Y2')
regexXY = re.compile(element + '.*DXY')
regexPX = re.compile(element + '.*PX')
regexPY = re.compile(element + '.*PY')
regexPZ = re.compile(element + '.*PZ')
regexS = re.compile(element + '.*S')
#Section: Finding Atomic Orbitals
Z2, matches1 = zip(*[(idx, string)
for idx, string in enumerate(data.aonames)
if re.match(regexZ2, string)])
XZ, matches2 = zip(*[(idx, string)
for idx, string in enumerate(data.aonames)
if re.match(regexXZ, string)])
YZ, matches3 = zip(*[(idx, string)
for idx, string in enumerate(data.aonames)
if re.match(regexYZ, string)])
X2Y2, matches4 = zip(*[(idx, string)
for idx, string in enumerate(data.aonames)
if re.match(regexX2Y2, string)])
XY, matches5 = zip(*[(idx, string)
for idx, string in enumerate(data.aonames)
if re.match(regexXY, string)])
PX, matches6 = zip(*[(idx, string)
for idx, string in enumerate(data.aonames)
if re.match(regexPX, string)])
PY, matches7 = zip(*[(idx, string)
for idx, string in enumerate(data.aonames)
if re.match(regexPY, string)])
PZ, matches8 = zip(*[(idx, string)
for idx, string in enumerate(data.aonames)
if re.match(regexPZ, string)])
S, matches9 = zip(*[(idx, string)
for idx, string in enumerate(data.aonames)
if re.match(regexS, string)])
#OxoOrbs, matches = zip(*[(idx, string) for idx, string in enumerate(data.aonames) if re.match('O', string)])#For oxo orbitals
otherOrbs, matches = zip(*[(idx, string)
for idx, string in enumerate(data.aonames)
if not (re.match(element, string))])
#Section: Population Calculation
m.calculate([S, Z2, XZ, YZ, X2Y2, XY, PX, PY, PZ, otherOrbs])
Spin = 0 #Alpha orbitals
h**o = data.homos[Spin]
character = m.fragresults[Spin].T[:] * 100
indices = np.arange(0, len(data.aonames), 1)
orbital = [data.aonames[i][-1] for i in np.argmax(data.mocoeffs[Spin], 1)]
aos = [
re.split(('_'), str(data.aonames[i]))
for i in np.argmax(data.mocoeffs[Spin]**2, 1)
]
AO = np.array(aos).T
dominantAtom = np.array([
data.aonames[i].split('_')[0]
for i in np.argmax(data.mocoeffs[Spin], 1)
]).T
dominantAO = np.array([
data.aonames[i].split('_')[1]
for i in np.argmax(data.mocoeffs[Spin], 1)
]).T
energies = data.moenergies[Spin]
energyArray = np.column_stack(
(indices, energies, dominantAtom, dominantAO))
#Section: Building Alpha Dataframe.
alp = pd.DataFrame(energyArray,
columns=[
'Orbital Number', 'Energy (eV)', 'Dominant Atom',
'Dominant AO'
])
h**o = data.homos[0]
alp.loc[0:h**o + 1, 'Occupancy'] = 1
alp.loc[h**o + 1:, 'Occupancy'] = 0
alp['Spin'] = 'Alpha'
alp[element + '_S'] = character[0]
alp[element + '_DZ2'] = character[1]
alp[element + '_DXZ'] = character[2]
alp[element + '_DYZ'] = character[3]
alp[element + '_DX2Y2'] = character[4]
alp[element + '_DXY'] = character[5]
alp[element + '_PX'] = character[6]
alp[element + '_PY'] = character[7]
alp[element + '_PZ'] = character[8]
alp['Other_Character'] = character[9]
alp['Total_Metal_Character'] = np.sum(character[0:6], axis=0)
alp['Total_p_Character'] = np.sum(character[6:8], axis=0)
outDF = alp.loc[(alp.index > h**o - homoLumoRange)
& (alp.index < h**o + homoLumoRange) &
(alp['Total_Metal_Character'] > printThreshold)].round(3)
#Section: Final Alpha Output
outDFalp = outDF[[
'Spin', 'Orbital Number', 'Energy (eV)', 'Occupancy', element + '_S',
element + '_DXY', element + '_DXZ', element + '_DYZ',
element + '_DX2Y2', element + '_DZ2', element + '_PX', element + '_PY',
element + '_PZ', 'Other_Character', 'Total_Metal_Character',
'Total_p_Character'
]]
SumAlpha = outDFalp[[
'Spin', element + '_S', element + '_DXY', element + '_DXZ',
element + '_DYZ', element + '_DX2Y2', element + '_DZ2',
element + '_PX', element + '_PY', element + '_PZ', 'Other_Character',
'Total_Metal_Character', 'Total_p_Character'
]].loc[outDFalp['Occupancy'] == 0].sum(axis=0)
Spin = 1 #beta orbitals
h**o = data.homos[Spin]
character = m.fragresults[Spin].T[:] * 100
indices = np.arange(0, len(data.aonames), 1)
orbital = [data.aonames[i][-1] for i in np.argmax(data.mocoeffs[Spin], 1)]
aos = [
re.split(('_'), str(data.aonames[i]))
for i in np.argmax(data.mocoeffs[Spin]**2, 1)
]
AO = np.array(aos).T
dominantAtom = np.array([
data.aonames[i].split('_')[0]
for i in np.argmax(data.mocoeffs[Spin], 1)
]).T
dominantAO = np.array([
data.aonames[i].split('_')[1]
for i in np.argmax(data.mocoeffs[Spin], 1)
]).T
energies = data.moenergies[Spin]
energyArray = np.column_stack(
(indices, energies, dominantAtom, dominantAO))
#Section: Building Beta Dataframe.
bet = pd.DataFrame(energyArray,
columns=[
'Orbital Number', 'Energy (eV)', 'Dominant Atom',
'Dominant AO'
])
bet.loc[0:h**o + 1, 'Occupancy'] = 1
bet.loc[h**o + 1:, 'Occupancy'] = 0
bet['Spin'] = "Beta"
bet[element + '_S'] = character[0]
bet[element + '_DZ2'] = character[1]
bet[element + '_DXZ'] = character[2]
bet[element + '_DYZ'] = character[3]
bet[element + '_DX2Y2'] = character[4]
bet[element + '_DXY'] = character[5]
bet[element + '_PX'] = character[6]
bet[element + '_PY'] = character[7]
bet[element + '_PZ'] = character[8]
#bet['O_Character']=character[8]
bet['Other_Character'] = character[9]
bet['Total_Metal_Character'] = np.sum(character[0:6], axis=0)
bet['Total_p_Character'] = np.sum(character[6:8], axis=0)
outDF = bet.loc[(bet.index > h**o - homoLumoRange)
& (bet.index < h**o + homoLumoRange) &
(bet['Total_Metal_Character'] > printThreshold)].round(3)
#Section: Final Beta Output
outDFbet = outDF[[
'Spin', 'Orbital Number', 'Energy (eV)', 'Occupancy', element + '_S',
element + '_DXY', element + '_DXZ', element + '_DYZ',
element + '_DX2Y2', element + '_DZ2', element + '_PX', element + '_PY',
element + '_PZ', 'Other_Character', 'Total_Metal_Character',
'Total_p_Character'
]]
SumBeta = outDFbet[[
'Spin', element + '_S', element + '_DXY', element + '_DXZ',
element + '_DYZ', element + '_DX2Y2', element + '_DZ2',
element + '_PX', element + '_PY', element + '_PZ', 'Other_Character',
'Total_Metal_Character', 'Total_p_Character'
]].loc[outDFbet['Occupancy'] == 0].sum(axis=0)
#Section: Write Final Ouput File
TotalDF = outDFalp.append(outDFbet)
SumTotal = (SumAlpha + SumBeta)[1:]
f = open(fileName.split('.')[0] + '.' + calculationType + '.report', 'w')
f.write('Alpha Hole Character Sum:\n' + str(SumAlpha[1:])[:-13] +
'\nBeta Hole Character Sum:\n' + str(SumBeta[1:])[:-13] +
'\nTotal Hole Sum:\n' + str(SumTotal[1:])[:-13])
TotalDF.to_csv(f, sep='\t')
return (TotalDF)
f.close()