def run_oo_dvr(oh_pots, desired_energies=None, num_pts=None, plot=False):
"""Runs the secondary DVR (over the OO coordinate) using the potentials created by some treatment of the OH.
(then uses wfn_flipper to rephase wavefunctions whatever the ground state wavefunctions look like.)
:param oh_pots: Potential curves of the OH=0 and OH=1. (col0: roo, col1: OH=0, col2: OH=1)
:type oh_pots: np.ndarray
:param desired_energies: number of energies/wavefunctions of the DVR to be saved to results objects
:type desired_energies: int
:param num_pts: number of points to cut the grid into.
:type num_pts: int
:param plot: If true, plots the potentials with the wavefunctions overlaid at their appropriate energies.
:type plot: bool
:return: energies_array (col0-?: energies, row0: OH=0, row1: OH=0),
wavefunctions_array (col0-?: wavefunction values, 3rd dimension: OH=0 or 1)
:rtype: 2 np.ndarrays
"""
from PotentialHandlers import Potentials1D
from Analysis2D import wfn_flipper
dvr_1D = DVR("ColbertMiller1D")
energies_array = np.zeros((2, desired_energies))
wavefunctions_array = np.zeros((2, num_pts, desired_energies))
mO = O / amutome
muOO = mO / 2
x = oh_pots[:, 0] * angtobohr
mini = min(x) - 0.3
maxi = max(x) + 0.15
for j in np.arange(2):
en = oh_pots[:, j + 1] / hartowave
res = dvr_1D.run(potential_function=Potentials1D().potlint(x, en),
mass=muOO,
divs=num_pts,
domain=(mini, maxi),
num_wfns=desired_energies)
potential = res.potential_energy.diagonal()
ens = res.wavefunctions.energies * hartowave
energies_array[j, :] = ens
wavefunctions_array[j, :, :] = res.wavefunctions.wavefunctions
if plot:
forreal_potential = potential * hartowave
ang_grid = res.grid / angtobohr
plt.rcParams.update({'font.size': 22})
plt.plot(ang_grid, forreal_potential, '-k', linewidth=6.0)
plt.ylim(0, 8000)
plt.xlim(2, 3.5)
colors = ["purple", "violet", "orchid", "plum", "hotpink"]
for i, wf in enumerate(res.wavefunctions):
wfn = wf.data * 1000
wfn += ens[i]
plt.plot(ang_grid, wfn, colors[i], linewidth=6.0)
plt.title("OH = %s" % j)
# plt.savefig(os.path.join(
# os.path.dirname(os.path.dirname(__file__)), 'figures', 'cut DVR', 'rigid_OH_%s.png' % j))
plt.show()
plt.close()
wavefunctions_array = wfn_flipper(wavefunctions_array)
return energies_array, wavefunctions_array
def run_harmonic(mass_hd8o4, reference_xyz, log_data):
finitedict = log_data.finite_dict(midpoint=True)
ohHARpots, HARwfnarray = run_harmonic_dvr(finitedict,
desired_energies=4,
num_pts=500)
HARwfnarray = wfn_flipper(HARwfnarray)
# harmon = transition_moment(log_data, reference_xyz, mass_hd8o4, HARwfnarray)
ooHARenergies, ooHARwavefunctions = run_oo_dvr(ohHARpots,
desired_energies=3,
num_pts=500,
plot=False)
# har_trans_mom = calculate_intensities(ooHARwavefunctions, trans_mom=harmon)
# har_notm = calculate_intensities(ooHARwavefunctions)
make_adiabatplots(log_data.minimum_pot(), ohHARpots, ooHARenergies)
plt.show()
def run_og(mass_hd8o4, reference_xyz, log_data):
cut_dict = log_data.cut_dictionary(midpoint=True)
ohpots, wfnarray = run_oh_dvr(cut_dict,
mass='H',
desired_energies=4,
num_pts=500)
wfnarray = wfn_flipper(wfnarray)
ooh_energies, ooh_wavefunctions = run_oo_dvr(ohpots,
desired_energies=3,
num_pts=500,
plot=False)
# original = transition_moment(log_data, reference_xyz, mass_hd8o4, wfnarray, plot=False)
# plt.show()
# og_intensities = calculate_intensities(ooh_wavefunctions, trans_mom=original)
make_adiabatplots(log_data.minimum_pot(), ohpots, ooh_energies)
plt.show()
def run_allh(mass_h9o4, reference_xyz, log_data):
cut_dict = log_data.cut_dictionary(midpoint=True)
ohpots, wfnarray = run_oh_dvr(cut_dict,
mass='H',
desired_energies=4,
num_pts=500)
wfnarray = wfn_flipper(wfnarray)
ooh_energies, ooh_wavefunctions = run_oo_dvr(ohpots,
desired_energies=4,
num_pts=500,
plot=False)
allh_trans_mom = transition_moment(log_data, reference_xyz, mass_h9o4,
wfnarray)
allh_intensities = calculate_intensities(ooh_wavefunctions,
trans_mom=allh_trans_mom)
make_spect(ooh_energies,
allh_intensities,
line_type='g-',
label_name="All H - Transition moment",
freq_shift=0)
def run_lintrans(mass_hd8o4, reference_xyz, log_data):
cut_dict = log_data.cut_dictionary(midpoint=True)
ohpots, wfnarray = run_oh_dvr(cut_dict,
mass='H',
desired_energies=4,
num_pts=500)
wfnarray = wfn_flipper(wfnarray)
ooh_energies, ooh_wavefunctions = run_oo_dvr(ohpots,
desired_energies=3,
num_pts=500,
plot=False)
lin_trans_mom = linear_tm(log_data,
reference_xyz,
mass_hd8o4,
wfnarray,
plot=False)
lin_intensities = calculate_intensities(ooh_wavefunctions,
trans_mom=lin_trans_mom)
make_spect(ooh_energies,
lin_intensities,
line_type='C1-',
label_name=" Anharmonic - Linear Transition moment",
freq_shift=15)
def run_relax(mass_hd8o4, reference_xyz, log_data):
cut_dict = log_data.cut_dictionary(midpoint=True)
ohpots, wfnarray = run_oh_dvr(cut_dict,
mass='H',
desired_energies=4,
num_pts=500)
wfnarray = wfn_flipper(wfnarray)
ooh_energies, ooh_wavefunctions = run_oo_dvr(ohpots,
desired_energies=3,
num_pts=500,
plot=False)
original = transition_moment(log_data,
reference_xyz,
mass_hd8o4,
wfnarray,
plot=False)
# plt.show()
og_intensities = calculate_intensities(ooh_wavefunctions,
trans_mom=original)
make_spect(ooh_energies,
og_intensities,
line_type='C3-',
label_name="Relaxed Scan",
freq_shift=0)
plt.xlabel("OO distance")
plt.ylabel("Transition Moment")
# plt.ylim(-1, 1)
plt.legend()
plt.show()
return mus
main_dir = os.path.dirname(os.path.dirname(__file__))
scan_dir = os.path.join(main_dir, "2D Scans", "logs")
VAA_dir = os.path.join(main_dir, 'VAA')
if __name__ == '__main__':
from GaussianHandler import LogInterpreter
from Analysis2D import run_dvr, wfn_flipper
from MakeSpectra import to_eck_struct_new
ref_xyz = os.path.join(main_dir, "structures",
"reference_structure_official.xyz")
all_scans = list(
sorted(glob.glob(os.path.join(scan_dir, "2Dtet_rig*.log"))))
cut_dict = LogInterpreter(*all_scans).cut_dictionary(midpoint=True)
ohpots, wfnarray = run_dvr(cut_dict, desired_energies=4, num_pts=100)
wfnarray = wfn_flipper(wfnarray)
tet = (np.array((15.999, 15.999, 1.008, 2.014, 2.014, 15.999, 2.014, 2.014,
15.999, 2.014, 2.014, 2.014, 2.014)) / amutome)
results = to_eck_struct_new(ref_xyz, all_scans, tet)
dipadedodas = interp_dipoles(results, len(wfnarray[0]))
derivies = deriv_dipoles(dipadedodas)
mus = psi_trans(dipadedodas, wfnarray, plot=True)
lin_mus = lin_psi_trans(dipadedodas, derivies, wfnarray, plot=True)