Class Monte_carlo

Instance Methods

__init__(self, relax)
Class containing functions for Monte Carlo simulations.

create_data(self, run=None, method=None)
Function for creating simulation data.

error_analysis(self, run=None, prune=0.0)
Function for calculating errors from the Monte Carlo simulations.

initial_values(self, run=None)
Function for setting the initial simulation parameter values.

off(self, run=None)
Function for turning simulations off.

on(self, run=None)
Function for turning simulations on.

select_all_sims(self, number=None, all_select_sim=None)
Function for setting the select flag of all simulations of all instances to one.

setup(self, run=None, number=None, all_select_sim=None)
Function for setting up Monte Carlo simulations.

Method Details

create_data(self, run=None, method=None)

Function for creating simulation data.

It is assumed that all data types are residue specific.

error_analysis(self, run=None, prune=0.0)

Function for calculating errors from the Monte Carlo simulations.

The standard deviation formula used to calculate the errors is the square root of the
bias-corrected variance, given by the formula:

               ____________________________
              /   1
    sd  =    /  ----- * sum({Xi - Xav}^2)]
           \/   n - 1

where:
    n is the total number of simulations.
    Xi is the parameter value for simulation i.
    Xav is the mean parameter value for all simulations.

setup(self, run=None, number=None, all_select_sim=None)

Function for setting up Monte Carlo simulations.

Parameters:

• run (str) - The name of the run.
• number (int) - The number of Monte Carlo simulations to set up.
• all_select_sim (Numeric matrix (int))