6.6. ligandparam.multiresp.functions
- ligandparam.multiresp.functions.WriteFrcmodObj(self, native_frcmod, angfact=1.0, uniqueparams=False, selected_names=None, changed_frcmod=None, with_mass=True, with_nonb=True)[source]
Writes an frcmod file from a parmed object
- Parameters:
self (parmed object) – The parmed object
native_frcmod (str) – The filename of the nonsubstituted parameters
angfact (float, optional) – The angle factor. Default is 1.0
uniqueparams (bool, optional) – If True, only write unique parameters. Default is False
selected_names (dict, optional) – The selected atom names. Default is None
changed_frcmod (str, optional) – The filename listing the new atom-type parameters. Default is None
with_mass (bool, optional) – If True, include mass parameters. Default is True
with_nonb (bool, optional) – If True, include nonbonded parameters. Default is True
- ligandparam.multiresp.functions.WriteLeapSh(leapsh, param, lib, frcmod, pdb, base, fh=None, overwrite=False)[source]
Writes a shell-script for running tleap
@param leapsh: name of shell-script to write @param param: parm7 object (from parmed) @param lib: list of off files to read @param frcmod: list of frcmod files to read @param pdb: pdb file to read @param base: the output basnemae of the parm7 and rst7 files @return none
- ligandparam.multiresp.functions.WriteMaskedFrcmod(param, aidxs, native_frcmod, changes_frcmod, with_mass=True, with_nonb=True)[source]
Converts selected atoms to new atom-types and writes two frcmod files, one containing the those parameters involving non-substituted atoms, and the other for those involving the substituted atoms.
- Parameters:
param (Amber parm file object) – The parameter file object
aidxs (list of int) – List of atoms that will use new atom-type parameters
native_frcmod (str) – The filename of the nonsubstituted parameters
changes_frcmod (str) – The filename listing the new atom-type parameters
with_mass (bool, optional) – If True, include mass parameters. Default is True
with_nonb (bool, optional) – If True, include nonbonded parameters. Default is True
- ligandparam.multiresp.functions.statisticalInefficiency(A_n)[source]
Compute the (cross) statistical inefficiency of (two) timeseries.
- Parameters:
A_n (np.ndarray, float) – A_n[n] is nth value of timeseries A. Length is deduced from vector.
B_n (np.ndarray, float, optional, default=None) – B_n[n] is nth value of timeseries B. Length is deduced from vector. If supplied, the cross-correlation of timeseries A and B will be estimated instead of the autocorrelation of timeseries A.
- Returns:
g – g is the estimated statistical inefficiency (equal to 1 + 2 tau, where tau is the correlation time). We enforce g >= 1.0.
- Return type:
np.ndarray,
- Raises:
ValueError – If the sample covariance is zero, the statistical inefficiency cannot be computed.
Notes
The same timeseries can be used for both A_n and B_n to get the autocorrelation statistical inefficiency. The fast method described in Ref [1] is used to compute g.
References
- [1] J. D. Chodera, W. C. Swope, J. W. Pitera, C. Seok, and K. A. Dill. Use of the weighted
histogram analysis method for the analysis of simulated and parallel tempering simulations. JCTC 3(1):26-41, 2007.