def load_Qlk(filepath, min_step=0, max_step='all', stride=1, ignore_steps=[]):
data, cols, timesteps = XYZ.read_xyz_file(filename=filepath,
num_data_cols=1,
min_step=min_step,
max_step=max_step,
stride=stride,
ignore_steps=ignore_steps)
cols = np.array(cols).astype(int)
return (data, cols), timesteps
def load_frc(filepath, min_step=0, max_step='all', stride=1, ignore_steps=[]):
"""
Load diabatic forces
"""
data, cols, timesteps = XYZ.read_xyz_file(filename=filepath,
num_data_cols=3,
min_step=min_step,
max_step=max_step,
stride=stride,
ignore_steps=ignore_steps)
return data, cols, timesteps
def load_pos(filepath, min_step=0, max_step='all', stride=1, ignore_steps=[]):
"""
Load forces
"""
data, cols, timesteps = XYZ.read_xyz_file(filename=filepath,
num_data_cols=3,
min_step=min_step,
max_step=max_step,
stride=stride,
ignore_steps=ignore_steps)
return data / 0.52917720859, cols, timesteps #/0.52917720859
def load_QM_0(filepath, min_step=0, max_step='all', stride=1, ignore_steps=[]):
"""
Will load a single traj QM_0 (the quantum momentum without the lk indices)
"""
data, cols, timesteps = XYZ.read_xyz_file(filename=filepath,
num_data_cols=3,
min_step=min_step,
max_step=max_step,
stride=stride,
ignore_steps=ignore_steps)
cols = np.array(cols).astype(int)
return data, cols, timesteps
def load_tintf(filepath,
min_step=0,
max_step='all',
stride=1,
ignore_steps=[]):
data, cols, timesteps = XYZ.read_xyz_file(filename=filepath,
num_data_cols=3,
min_step=min_step,
max_step=max_step,
stride=stride,
ignore_steps=ignore_steps)
data = Utils.reshape_by_state(data, cols)
cols = cols[:, :, 0]
return data, cols, timesteps
def load_ham(filepath,
num_basis,
metadata,
min_step=0,
max_step='all',
stride=1,
ignore_steps=[]):
data, cols, timesteps = XYZ.read_xyz_file(filepath,
num_basis,
min_step=min_step,
max_step=max_step,
stride=stride,
ignore_steps=ignore_steps,
metadata=metadata)
return data * 27000, cols, timesteps
def load_ad_frc(filepath,
min_step=0,
max_step='all',
stride=1,
ignore_steps=[]):
"""
Load adiabatic forces
"""
data, cols, timesteps = XYZ.read_xyz_file(filename=filepath,
num_data_cols=3,
min_step=min_step,
max_step=max_step,
stride=stride,
ignore_steps=ignore_steps)
data = Utils.reshape_by_state(data, cols)
cols = cols[:, :, 0].shape
return data, cols, timesteps
def load_coeff(filepath,
min_step=0,
max_step='all',
stride=1,
ignore_steps=[],
metadata=False):
data, cols, timesteps = XYZ.read_xyz_file(filename=filepath,
num_data_cols=2,
min_step=min_step,
max_step=max_step,
stride=stride,
ignore_steps=ignore_steps,
metadata=metadata)
pops = np.linalg.norm(data, axis=2)**2
data = np.array([np.array([complex(*j) for j in i]) for i in data])
return np.array(data), np.array(cols), np.array(timesteps), np.array(pops)