Metadata-Version: 2.1
Name: cowboe
Version: 1.0.0
Summary: Construction Of Windows Based On Energy
Home-page: https://github.com/kuroonai/cowboe
Author: Naveen Vasudevan, Li Xi
Author-email: naveenovan@gmail.com, xili@mcmaster.ca
License: GNU General Public License v3.0
Description: ## Construction Of Windows Based on Energy - COWBOE
        
        This package consists of the "COWBOE" algorithm to construct windows on the reaction coordinate based on the test PMF values.
        
        ## Installation
        
        Run the following to install
        
        '''
        pip install cowboe
        
        '''
        
        Module for optimization and selection of parameters for umbrella sampling
        
        ##################################################
        
        # COWBOE - Construction Of Windows Based On Energy
        
        ##################################################
        
        Current settings for the module are as follow
        
        "PMF unit"                    :        r'PMF - Kcal / (mol $\cdot~\AA^2$)'
        "reaction coordinate unit"    :        r'$\AA$'
        "polynomial fit order"        :        12 
        "param B"                     :        2.0 
        "Number of datapoints"        :        100000
        "conventional force constant" :        7
        "conventional window width"   :        0.5
        "conventional no of windows"  :        24
        "conv. min of 1st window"     :        2.5
        "conv. min of last window"    :        14.5
        "fill colour"                 :        'r'
        "NM_alpha"                    :        1
        "NM_gamma"                    :        2
        "NM_beta"                     :        0.5
        "NM_delta"                    :        0.5
        
        To update any settings, use dict.update()
                e.g. cowboe_settings.update({"param B" : 2.0001})
                
        ## usage
        
        from cowboe import pmftopoints, cowboe, cowboefit, cowboeNM, NMprogress, cowboe_settings
        
        cowboe_settings.update({"param B" : 2.0})
        
        A 	= [2.0, 2.9, 3.5]
        V 	= [0.75, 0.8700, 0.8000]
        fit 	= [21.2642, 17.6376, 24.5880]
        
        pmftopoints(testpmf='test_pmf.txt')
        
        cowboe(A=2.84, V = 0.895 , sc =8)
        
        cowboefit(test='1.txt',bench='bench.txt')
        
        cowboeNM(A = A, V = V, fit = fit)
        
        NMprogress(progressfile = 'progress.txt')
        
        
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: End Users/Desktop
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Chemistry
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Operating System :: OS Independent
Classifier: License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)
Requires-Python: >=3.6
Description-Content-Type: text/markdown
