Collect Map Class

This module contains the CollectMapData class that is used to build an empirical map from a series of QM calculations on a 1D potential.

Notes:

This code works on the gaussian calculations setup by emp_setup.py and then fits the potential energy surfaces. It then goes through and uses those potential energy surfaces for a sinc function discrete variable representation (See Colbert, Miller Paper) to obtain the eigenvalues and eigenvectors. For each directory, a value of the key parameters w01, w12… etc. are obtained. These are then used to fit an empirical map based on the total data.

To Do:

1. Write the map files consistent with frequencymap.org

class empmap.collect_map_data.CollectMapData(file_list=None, file_start=0, file_end=200, file_prefix='scan_', calc_dir='run_qm/')

The EmpiricalMap Class that builds an empirical map from a series of QM calculations on a 1D potential.

Notes:

This code works on the gaussian calculations setup by emp_setup.py and then fits the potential energy surfaces and then goes through and uses those potential energy surfaces for a sinc function discrete variable representation (See Colbert, Miller Paper) to obtain the eigenvalues and eigenvectors. For each directory, a value of the key parameters w01, w12… etc. are obtained. These are then used to fit an empirical map based on the total data.

build_base_data(**kwargs)

Build data using the DVR approach.

Paramters:

kwargsarguments

Keyword arguemnts to be passed to the _obtain_dvrs function.

Returns:

None

classmethod load_self(filename)

Load the EmpiricalMap from a file.

obtain_dvr(file, emax=3.0, xmax=1.3, mass1=2.014, mass2=15.999, pot_poly_order=5, dip_poly_order=3, pol_poly_order=3)

Obtain a DVR for a given file.

save_self(filename)

Save the EmpiricalMap to a file.