vibrav.numerical.redmass module

vibrav.numerical.redmass.rmass_cart(data, symbol)

Calculate the reduced masses from the normalized non-mass-weighted cartesian normal modes. With the equation,

\[\mu_i = \left(\sum_k^{3N} l_{CARTk,i}^2\right)^{-1}\]

Note

This assumes that the normal modes have already been placed in the ['dx', 'dy', 'dz'] columns.

Parameters:

• data (pandas.DataFrame) – Data frame the has the non-mass-weighted cartesian normal modes.

• symbol (list) – List-like object that has the atomic symbols.

Returns:

r_mass (numpy.ndarray) –

Array containing the calculated reduced

masses in Dalton or atomic mass units not atomic units of mass.

Examples

Usage of this method is as follows,

>>> import pandas as pd
>>> from vibrav.base import resource
>>> res_file = 'adf-ubr-1minus-b3lyp-numeric-norm-modes-cart.csv.xz'
>>> freqs = pd.read_csv(resource(res_file), compression='xz')
>>> symbols = ['U'] + ['Br']*6
>>> freqs.groupby('freqdx').apply(rmass_cart, symbols)
freqdx
0      78.918337
1      78.918337
2      78.918337
3      78.918337
4      78.918337
5      78.918337
6      93.006642
7      93.006642
8      93.006642
9      78.918337
10     78.918337
11     78.918337
12    111.682085
13    111.682085
14    111.682085
dtype: float64

It is also possible to use the method without the groupby/apply methods from a pandas data frame. However, the pandas data frame that is passed into the function must have the ['dx', 'dy', 'dz'] columns present. In addition the symbols parameter must have all of the atomic symbols that exists, including ones that are repeated.

vibrav.numerical.redmass.rmass_mwc(data, symbol)

Calculate the reduced masses from the mass-weighted normal modes. With the equation,

\[\mu_i = \left(\sum_k^{3N} \left(\frac{l_{MWCk,i}} {\sqrt{m_k}}\right)^2\right)^{-1}\]

Note

This assumes that the normal modes have already been placed in the ['dx', 'dy', 'dz'] columns.

Parameters:

• data (pandas.DataFrame) – Data frame the has the mass-weighted normal modes.

• symbol (list) – List-like object that has the atomic symbols.

Returns:

r_mass (numpy.ndarray) –

Array containing the calculated reduced

masses in Dalton or atomic mass units not atomic units of mass.

Examples

Usage of this method is as follows,

>>> import pandas as pd
>>> from vibrav.base import resource
>>> res_file = 'adf-ubr-1minus-b3lyp-numeric-norm-modes-mwc.csv.xz'
>>> freqs = pd.read_csv(resource(res_file), compression='xz')
>>> symbols = ['U'] + ['Br']*6
>>> freqs.groupby('freqdx').apply(rmass_mwc, symbols)
freqdx
0      78.918337
1      78.918337
2      78.918337
3      78.918337
4      78.918337
5      78.918337
6      93.006642
7      93.006642
8      93.006642
9      78.918337
10     78.918337
11     78.918337
12    111.682084
13    111.682084
14    111.682084
dtype: float64

It is also possible to use the method without the groupby/apply methods from a pandas data frame. However, the pandas data frame that is passed into the function must have the ['dx', 'dy', 'dz'] columns present. In addition the symbols parameter must have all of the atomic symbols that exists, including ones that are repeated.