[AMBER] Umbrella sampling sufficient overlap test

From: Martin Rosellen <ucbtmc7.ucl.ac.uk>
Date: Mon, 6 Jan 2020 12:20:06 +0000

Dear all,

I am running umbrella sampling productions using a dihedral angle as reaction coordinate. By eye, the histograms of the angles of the umbrella productions overlap well in most of the cases. I wrote myself a script that checks for overlap using quantiles. I currently test if the 5th 5-quantile of production n is greater than the 1th 5-quantile of production n+1. I wonder if that test is too strict? How much overlap is intended/enough?

This is my python script that you can also find here: https://github.com/Gimba/UmbrellaSamplingUtils/blob/master/check_overlap.py

import glob
import matplotlib.pyplot as plt
import numpy as np

def main():
    fig = plt.figure(figsize=(15, 10))

    data = {}
    files = []
    for file in glob.glob("*.dat"):

    files = sorted(files, key=lambda x: int(x.split('_')[-1].split('.')[0]))

    for file in files:
        with open(file, 'r') as f:
            file_number = int(file.split('_')[-1].split('.')[0])
            data[file_number] = []

            for line in f.readlines():
                dat = line.split()[-1]

            # plot and annotate histograms
            y, x, _ = plt.hist(data[file_number], bins=100, histtype='step')
            y_coord = max(y)

            x_coord = x[np.where(y == max(y))[0][0]]
            plt.annotate(str(file_number), (x_coord, y_coord), ha='center')

    plt.xlabel('dihedral angle')

    # use quantiles to check proper overlap of distributions
    with open('umbrella_stats.txt', 'w') as o:
        o.write('file number <-> filenumber : sufficient overlap\n')
        for key in sorted(data.keys()):
            key_next = key + 1
            if key_next in data.keys():
                dat = np.asarray(data[key])
                dat_next = np.asarray(data[key_next])
                dat_quantile = np.quantile(dat, 0.8)
                dat_next_quantile = np.quantile(dat_next, 0.2)
                # plt.axvline(dat_quantile, color='red')
                # plt.axvline(dat_next_quantile)
                if (dat_quantile > dat_next_quantile):
                    o.write('{} <-> {} : True\n'.format(key, key_next))
                    print('!!! {} <-> {} : False\n'.format(key, key_next))
                    o.write('{} <-> {} : False\n'.format(key, key_next))

if __name__ == '__main__':


Martin Rosellen
Phd, UCL Division of Biosciences

Hansen Lab (UCL), Shepherd Group (Birkbeck)
UCL (University College London)
Birkbeck, University of London

E: martin.rosellen.16.ucl.ac.uk<mailto:martin.rosellen.16.ucl.ac.uk>

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Received on Mon Jan 06 2020 - 04:30:02 PST
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