In [1]:
import plumed
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import os
import MDAnalysis
import numpy as np
import math
In [2]:
# set working directory for all future cells
os.chdir("/Users/max/build/PLUMED/plumed-masterclass/masterclass-21-7")
# and check with bash command pwd - note the exclamation mark at the beginning
!pwd
# or in python
os.getcwd()

/Users/max/build/PLUMED/plumed-masterclass/masterclass-21-7
Out[2]:
'/Users/max/build/PLUMED/plumed-masterclass/masterclass-21-7'
In [3]:
%%bash
# Exercise 2
# create directory for this exercise
mkdir Exercise-2; cd Exercise-2

# Time GROMACS alone
# using 4 CPU cores - OpenMP parallelization + 1 GPU
# Info machine: cores: 16  * CPU: Intel(R) Xeon(R) CPU E5-2667 v4 @ 3.20GHz * GPU: TITAN X (Pascal)
mkdir run_2A; cd run_2A

# run GROMACS
#gmx_mpi mdrun -s ../../data/exercise2/topol.tpr -nsteps 100000 -pin on -noddcheck -ntomp 4

# extract performances
grep Perf -B1 md.log

                 (ns/day)    (hour/ns)
Performance:      766.272        0.031

mkdir: Exercise-2: File exists
mkdir: run_2A: File exists
In [4]:
%%bash
# Exercise 2
cd Exercise-2

# Time MetaD using provided input file
# using 4 CPU cores - OpenMP parallelization + 1 GPU
# Info machine: cores: 16  * CPU: Intel(R) Xeon(R) CPU E5-2667 v4 @ 3.20GHz * GPU: TITAN X (Pascal)
mkdir run_2B; cd run_2B

# link useful files here
ln -s ../../data/exercise2/* . 2>/dev/null

# run GROMACS
#gmx_mpi mdrun -s topol.tpr -plumed plumed.dat -nsteps 100000 -pin on -noddcheck -ntomp 4

# extract performances
tail -n 15 md.log

               Core t (s)   Wall t (s)        (%)
       Time:     1155.875      288.970      400.0
                 (ns/day)    (hour/ns)
Performance:       14.950        1.605
Finished mdrun on rank 0 Tue Apr 27 08:56:04 2021

PLUMED:                                               Cycles        Total      Average      Minimum      Maximum
PLUMED:                                                    1   281.577806   281.577806   281.577806   281.577806
PLUMED: 1 Prepare dependencies                        100001     3.118821     0.000031     0.000029     0.000860
PLUMED: 2 Sharing data                                100001     0.425394     0.000004     0.000004     0.000079
PLUMED: 3 Waiting for data                            100001     0.046471     0.000000     0.000000     0.000007
PLUMED: 4 Calculating (forward loop)                  100001   147.393191     0.001474     0.001400     0.002363
PLUMED: 5 Applying (backward loop)                    100001   127.418219     0.001274     0.001193     0.002111
PLUMED: 6 Update                                      100001     1.284446     0.000013     0.000009     0.001763

mkdir: run_2B: File exists
In [5]:
%%bash
# Exercise 2
cd Exercise-2

# Time MetaD using optimized input file
# using 4 CPU cores - OpenMP parallelization + 1 GPU
# Info machine: cores: 16  * CPU: Intel(R) Xeon(R) CPU E5-2667 v4 @ 3.20GHz * GPU: TITAN X (Pascal)
mkdir run_2C; cd run_2C

# create PLUMED optimized input file
cat > "plumed_opt.dat" << EOF
# reconstruct molecule
WHOLEMOLECULES ENTITY0=1-330

# CA-RMSDs from the two reference conformations
rmsd_A: RMSD REFERENCE=stateA.pdb TYPE=OPTIMAL NOPBC
rmsd_B: RMSD REFERENCE=stateB.pdb TYPE=OPTIMAL NOPBC

cv: COORDINATION ...
NOPBC 
GROUPA=1,1,1,2,2,2,2,2,3,3,3,3,4,5,5,6,9,10,10,10,10,13,13,13,13,13,13,13,14,14,14,14,14,14,14,14,14,16,16,16,16,16,18,18,18,18,19,21,22,22,22,22,22,22,24,25,25,25,27,27,27,27,27,27,27,27,28,28,28,28,29,29,29,29,29,29,29,30,30,30,30,30,30,30,30,30,30,32,32,32,32,32,32,34,34,34,38,39,41,41,41,47,47,47,48,48,48,52,52,57,57,60,62,62,63,63,63,66,68,68,68,68,83,84,84,84,84,84,84,89,89,89,93,95,98,101,101,101,101,101,101,103,103,104,104,104,104,104,104,104,105,107,107,107,107,107,108,109,109,110,111,111,114,114,114,114,114,114,114,116,116,116,116,119,119,119,120,120,120,120,120,126,126,126,126,128,128,129,129,129,129,129,129,129,130,130,130,130,130,130,130,130,133,133,133,133,133,135,140,141,141,141,141,141,144,144,144,144,145,145,145,145,149,149,149,149,151,151,153,153,153,153,153,153,154,154,154,158,160,160,160,160,162,166,166,166,169,169,169,174,174,174,174,174,174,174,176,176,176,176,176,178,178,178,178,180,180,180,184,186,186,186,186,188,188,188,189,189,189,191,191,191,191,191,191,193,193,193,193,195,195,196,197,197,197,197,197,200,200,200,200,200,202,202,202,204,204,204,204,204,205,205,207,207,207,207,207,209,209,209,209,210,211,212,212,212,212,212,212,212,212,213,213,213,213,216,216,216,216,218,218,218,220,220,220,220,220,220,220,221,221,221,223,223,223,223,223,223,225,225,225,226,226,232,232,232,232,232,235,235,235,236,236,236,236,237,239,239,239
GROUPB=110,115,122,106,108,110,112,115,95,96,98,102,112,95,98,112,123,95,102,106,115,106,108,112,115,123,203,205,92,102,103,104,106,113,202,205,208,92,94,96,102,106,82,92,94,96,96,78,79,80,92,94,96,99,205,78,82,92,60,68,70,72,78,82,84,92,60,68,70,311,82,92,102,104,205,310,311,60,68,82,84,92,104,221,309,310,311,68,70,72,78,82,92,70,72,75,71,73,72,74,75,58,71,74,70,71,72,69,71,86,87,221,218,221,236,237,279,295,82,84,93,221,229,217,218,219,221,229,231,229,231,237,229,229,229,215,217,219,224,229,231,215,224,202,204,208,215,217,219,220,203,201,202,208,210,215,202,210,213,210,213,215,133,199,201,203,208,210,215,199,201,203,204,192,199,201,188,203,204,205,327,194,199,201,208,286,287,194,196,197,199,206,284,300,199,208,210,212,213,285,286,287,192,194,196,197,199,196,199,187,192,194,195,196,185,187,192,195,185,187,189,199,185,187,195,196,195,196,170,175,176,177,185,195,177,179,182,177,175,177,186,328,189,189,327,328,186,188,328,313,315,316,317,323,325,328,313,315,317,323,328,315,317,319,323,317,319,320,328,303,313,315,323,310,313,315,323,327,328,300,302,303,307,310,313,300,302,307,310,302,303,303,284,291,301,302,303,300,302,307,310,313,300,307,310,300,302,307,310,313,310,313,281,283,291,300,310,281,283,285,291,287,267,267,270,274,281,283,285,287,288,267,270,287,288,274,278,281,291,278,279,281,278,279,281,283,291,293,300,278,279,293,264,266,274,277,278,281,266,267,268,268,271,266,268,274,277,278,266,274,278,274,277,278,279,279,256,258,265
PAIR SWITCH={CUSTOM FUNC=1-erf(x^4) R_0=1.0}
...

# metadynamics parameters
metad: METAD ARG=cv ...
  # Deposit a Gaussian every 500 time steps, with initial height
  # equal to 1.2 kJ/mol and bias factor equal to 60
  PACE=500 HEIGHT=1.2 BIASFACTOR=60
  # Gaussian width (sigma) based on the CV fluctuations in unbiased run
  SIGMA=10.0
  # Gaussians will be written to file
  FILE=HILLS
...

# print useful stuff
PRINT ARG=cv,rmsd_A,rmsd_B,metad.bias STRIDE=500 FILE=COLVAR
EOF

# link useful files here
ln -s ../../data/exercise2/* . 2>/dev/null

# Time MetaD using optimize PLUMED input file (using 4 cores)
#gmx_mpi mdrun -s topol.tpr -plumed plumed_opt.dat -nsteps 100000 -pin on -noddcheck -ntomp 4

# extract performances
tail -n 15 md.log

               Core t (s)   Wall t (s)        (%)
       Time:       54.486       13.622      400.0
                 (ns/day)    (hour/ns)
Performance:      317.132        0.076
Finished mdrun on rank 0 Tue Apr 27 09:28:48 2021

PLUMED:                                               Cycles        Total      Average      Minimum      Maximum
PLUMED:                                                    1     7.225220     7.225220     7.225220     7.225220
PLUMED: 1 Prepare dependencies                        100001     0.062965     0.000001     0.000001     0.000010
PLUMED: 2 Sharing data                                100001     0.187364     0.000002     0.000002     0.000087
PLUMED: 3 Waiting for data                            100001     0.045188     0.000000     0.000000     0.000008
PLUMED: 4 Calculating (forward loop)                  100001     4.075646     0.000041     0.000037     0.000818
PLUMED: 5 Applying (backward loop)                    100001     0.895213     0.000009     0.000008     0.000489
PLUMED: 6 Update                                      100001     0.385592     0.000004     0.000001     0.001268

mkdir: run_2C: File exists
In [6]:
%%bash
# Check definition of CV
head -n 2 Exercise-2/run_2B/COLVAR Exercise-2/run_2C/COLVAR

==> Exercise-2/run_2B/COLVAR <==
#! FIELDS time cv rmsd_A rmsd_B metad.bias
 0.000000 55.990713 1.240984 1.202054 0.000000

==> Exercise-2/run_2C/COLVAR <==
#! FIELDS time cv rmsd_A rmsd_B metad.bias
 0.000000 55.990713 1.240984 1.202054 0.000000
In [7]:
%%bash
# Exercise 2
cd Exercise-2

# Run production MetaD using optimized input file
# Info machine: cores: 16  * CPU: Intel(R) Xeon(R) CPU E5-2667 v4 @ 3.20GHz * GPU: TITAN X (Pascal)
mkdir run_2D; cd run_2D

# create PLUMED optimized input file
cat > "plumed_opt.dat" << EOF
# reconstruct molecule
WHOLEMOLECULES ENTITY0=1-330

# CA-RMSDs from the two reference conformations
rmsd_A: RMSD REFERENCE=stateA.pdb TYPE=OPTIMAL NOPBC
rmsd_B: RMSD REFERENCE=stateB.pdb TYPE=OPTIMAL NOPBC

cv: COORDINATION ...
NOPBC 
GROUPA=1,1,1,2,2,2,2,2,3,3,3,3,4,5,5,6,9,10,10,10,10,13,13,13,13,13,13,13,14,14,14,14,14,14,14,14,14,16,16,16,16,16,18,18,18,18,19,21,22,22,22,22,22,22,24,25,25,25,27,27,27,27,27,27,27,27,28,28,28,28,29,29,29,29,29,29,29,30,30,30,30,30,30,30,30,30,30,32,32,32,32,32,32,34,34,34,38,39,41,41,41,47,47,47,48,48,48,52,52,57,57,60,62,62,63,63,63,66,68,68,68,68,83,84,84,84,84,84,84,89,89,89,93,95,98,101,101,101,101,101,101,103,103,104,104,104,104,104,104,104,105,107,107,107,107,107,108,109,109,110,111,111,114,114,114,114,114,114,114,116,116,116,116,119,119,119,120,120,120,120,120,126,126,126,126,128,128,129,129,129,129,129,129,129,130,130,130,130,130,130,130,130,133,133,133,133,133,135,140,141,141,141,141,141,144,144,144,144,145,145,145,145,149,149,149,149,151,151,153,153,153,153,153,153,154,154,154,158,160,160,160,160,162,166,166,166,169,169,169,174,174,174,174,174,174,174,176,176,176,176,176,178,178,178,178,180,180,180,184,186,186,186,186,188,188,188,189,189,189,191,191,191,191,191,191,193,193,193,193,195,195,196,197,197,197,197,197,200,200,200,200,200,202,202,202,204,204,204,204,204,205,205,207,207,207,207,207,209,209,209,209,210,211,212,212,212,212,212,212,212,212,213,213,213,213,216,216,216,216,218,218,218,220,220,220,220,220,220,220,221,221,221,223,223,223,223,223,223,225,225,225,226,226,232,232,232,232,232,235,235,235,236,236,236,236,237,239,239,239
GROUPB=110,115,122,106,108,110,112,115,95,96,98,102,112,95,98,112,123,95,102,106,115,106,108,112,115,123,203,205,92,102,103,104,106,113,202,205,208,92,94,96,102,106,82,92,94,96,96,78,79,80,92,94,96,99,205,78,82,92,60,68,70,72,78,82,84,92,60,68,70,311,82,92,102,104,205,310,311,60,68,82,84,92,104,221,309,310,311,68,70,72,78,82,92,70,72,75,71,73,72,74,75,58,71,74,70,71,72,69,71,86,87,221,218,221,236,237,279,295,82,84,93,221,229,217,218,219,221,229,231,229,231,237,229,229,229,215,217,219,224,229,231,215,224,202,204,208,215,217,219,220,203,201,202,208,210,215,202,210,213,210,213,215,133,199,201,203,208,210,215,199,201,203,204,192,199,201,188,203,204,205,327,194,199,201,208,286,287,194,196,197,199,206,284,300,199,208,210,212,213,285,286,287,192,194,196,197,199,196,199,187,192,194,195,196,185,187,192,195,185,187,189,199,185,187,195,196,195,196,170,175,176,177,185,195,177,179,182,177,175,177,186,328,189,189,327,328,186,188,328,313,315,316,317,323,325,328,313,315,317,323,328,315,317,319,323,317,319,320,328,303,313,315,323,310,313,315,323,327,328,300,302,303,307,310,313,300,302,307,310,302,303,303,284,291,301,302,303,300,302,307,310,313,300,307,310,300,302,307,310,313,310,313,281,283,291,300,310,281,283,285,291,287,267,267,270,274,281,283,285,287,288,267,270,287,288,274,278,281,291,278,279,281,278,279,281,283,291,293,300,278,279,293,264,266,274,277,278,281,266,267,268,268,271,266,268,274,277,278,266,274,278,274,277,278,279,279,256,258,265
PAIR SWITCH={CUSTOM FUNC=1-erf(x^4) R_0=1.0}
...

# metadynamics parameters
metad: METAD ARG=cv ...
  # Deposit a Gaussian every 500 time steps, with initial height
  # equal to 1.2 kJ/mol and bias factor equal to 60
  PACE=500 HEIGHT=1.2 BIASFACTOR=60
  # Gaussian width (sigma) based on the CV fluctuations in unbiased run
  SIGMA=2.0
  # Gaussians will be written to file
  FILE=HILLS
  # Store MetaD bias potential on a grid
  GRID_MIN=0 GRID_MAX=400
...

# print useful stuff
PRINT ARG=cv,rmsd_A,rmsd_B,metad.bias STRIDE=500 FILE=COLVAR
EOF

# link useful files here
ln -s ../../data/exercise2/* . 2>/dev/null

# Run MetaD using optimize PLUMED input file (using 4 cores)
#gmx_mpi mdrun -s topol.tpr -plumed plumed_opt.dat -noddcheck -pin on -ntomp 4

mkdir: run_2D: File exists
In [8]:
# visualize CV file
data=plumed.read_as_pandas("Exercise-2/run_2D/COLVAR")
# plot cv during simulation
plt.plot(data["time"]/1000.0,data["cv"],'o', ms=1, c="green")
# x-y axis labels
plt.xlabel("Simulation time [ns]")
plt.ylabel("# native contacts")
Out[8]:
Text(0, 0.5, '# native contacts')
No description has been provided for this image
In [9]:
# plot cv vs RMSD from State A
plt.plot(data["cv"],data["rmsd_A"],'o', ms=0.5)
# x-y axis labels
plt.xlabel("# native contacts")
plt.ylabel("RMSD from State A [nm]")
Out[9]:
Text(0, 0.5, 'RMSD from State A [nm]')
No description has been provided for this image
In [10]:
# plot cv vs RMSD from State B
plt.plot(data["cv"],data["rmsd_B"],'o', ms=0.5, c="r")
# x-y axis labels
plt.xlabel("# native contacts")
plt.ylabel("RMSD from State B [nm]")
Out[10]:
Text(0, 0.5, 'RMSD from State B [nm]')
No description has been provided for this image
In [11]:
%%bash
# compute free energy as a function of simulation time
cd Exercise-2/run_2D
plumed sum_hills --hills HILLS --stride 10000 --mintozero

PLUMED: PLUMED is starting
PLUMED: Version: 2.7.0 (git: Unknown) compiled on Dec 23 2020 at 20:47:11
PLUMED: Please cite these papers when using PLUMED [1][2]
PLUMED: For further information see the PLUMED web page at http://www.plumed.org
PLUMED: Root: /usr/local/anaconda3/envs/plumed-masterclass/lib/plumed
PLUMED: For installed feature, see /usr/local/anaconda3/envs/plumed-masterclass/lib/plumed/src/config/config.txt
PLUMED: Molecular dynamics engine: 
PLUMED: Precision of reals: 8
PLUMED: Running over 1 node
PLUMED: Number of threads: 1
PLUMED: Cache line size: 512
PLUMED: Number of atoms: 1
PLUMED: File suffix: 
PLUMED: Timestep: 0.000000
PLUMED: KbT has not been set by the MD engine
PLUMED: It should be set by hand where needed
PLUMED: Relevant bibliography:
PLUMED:   [1] The PLUMED consortium, Nat. Methods 16, 670 (2019)
PLUMED:   [2] Tribello, Bonomi, Branduardi, Camilloni, and Bussi, Comput. Phys. Commun. 185, 604 (2014)
PLUMED: Please read and cite where appropriate!
PLUMED: Finished setup
PLUMED: Action FAKE
PLUMED:   with label cv
PLUMED: Action FUNCSUMHILLS
PLUMED:   with label @1
PLUMED:   with arguments cv
PLUMED:   Output format is %14.9f
PLUMED:   hillsfile  : HILLS
PLUMED:    
PLUMED:   No boundaries defined: need to do a prescreening of hills 
PLUMED:   doing serialread 
PLUMED:   opening file HILLS
PLUMED:   closing file HILLS
PLUMED:   now total 224180 kernels 
PLUMED:   final chunk: now with 224180 kernels  
PLUMED:   found boundaries from hillsfile: 
PLUMED:   variable cv min: -4.69271 max: 369.042 nbin: 529
PLUMED:   done!
PLUMED:    
PLUMED:   Doing integration slices every 10000 kernels
PLUMED:   mintozero: bias/histogram will be translated to have the minimum value equal to zero
PLUMED:   output file for fes/bias  is :  fes_
PLUMED: 
PLUMED:   Now calculating...
PLUMED: 
PLUMED:   reading hills: 
PLUMED:   doing serialread 
PLUMED:   opening file HILLS
PLUMED:   done with this chunk: now with 10000 kernels  
PLUMED: 
PLUMED:   Writing full grid on file fes_0.dat 
PLUMED:   reading hills: 
PLUMED:   doing serialread 
PLUMED:   done with this chunk: now with 20000 kernels  
PLUMED: 
PLUMED:   Writing full grid on file fes_1.dat 
PLUMED:   reading hills: 
PLUMED:   doing serialread 
PLUMED:   done with this chunk: now with 30000 kernels  
PLUMED: 
PLUMED:   Writing full grid on file fes_2.dat 
PLUMED:   reading hills: 
PLUMED:   doing serialread 
PLUMED:   done with this chunk: now with 40000 kernels  
PLUMED: 
PLUMED:   Writing full grid on file fes_3.dat 
PLUMED:   reading hills: 
PLUMED:   doing serialread 
PLUMED:   done with this chunk: now with 50000 kernels  
PLUMED: 
PLUMED:   Writing full grid on file fes_4.dat 
PLUMED:   reading hills: 
PLUMED:   doing serialread 
PLUMED:   done with this chunk: now with 60000 kernels  
PLUMED: 
PLUMED:   Writing full grid on file fes_5.dat 
PLUMED:   reading hills: 
PLUMED:   doing serialread 
PLUMED:   done with this chunk: now with 70000 kernels  
PLUMED: 
PLUMED:   Writing full grid on file fes_6.dat 
PLUMED:   reading hills: 
PLUMED:   doing serialread 
PLUMED:   done with this chunk: now with 80000 kernels  
PLUMED: 
PLUMED:   Writing full grid on file fes_7.dat 
PLUMED:   reading hills: 
PLUMED:   doing serialread 
PLUMED:   done with this chunk: now with 90000 kernels  
PLUMED: 
PLUMED:   Writing full grid on file fes_8.dat 
PLUMED:   reading hills: 
PLUMED:   doing serialread 
PLUMED:   done with this chunk: now with 100000 kernels  
PLUMED: 
PLUMED:   Writing full grid on file fes_9.dat 
PLUMED:   reading hills: 
PLUMED:   doing serialread 
PLUMED:   done with this chunk: now with 110000 kernels  
PLUMED: 
PLUMED:   Writing full grid on file fes_10.dat 
PLUMED:   reading hills: 
PLUMED:   doing serialread 
PLUMED:   done with this chunk: now with 120000 kernels  
PLUMED: 
PLUMED:   Writing full grid on file fes_11.dat 
PLUMED:   reading hills: 
PLUMED:   doing serialread 
PLUMED:   done with this chunk: now with 130000 kernels  
PLUMED: 
PLUMED:   Writing full grid on file fes_12.dat 
PLUMED:   reading hills: 
PLUMED:   doing serialread 
PLUMED:   done with this chunk: now with 140000 kernels  
PLUMED: 
PLUMED:   Writing full grid on file fes_13.dat 
PLUMED:   reading hills: 
PLUMED:   doing serialread 
PLUMED:   done with this chunk: now with 150000 kernels  
PLUMED: 
PLUMED:   Writing full grid on file fes_14.dat 
PLUMED:   reading hills: 
PLUMED:   doing serialread 
PLUMED:   done with this chunk: now with 160000 kernels  
PLUMED: 
PLUMED:   Writing full grid on file fes_15.dat 
PLUMED:   reading hills: 
PLUMED:   doing serialread 
PLUMED:   done with this chunk: now with 170000 kernels  
PLUMED: 
PLUMED:   Writing full grid on file fes_16.dat 
PLUMED:   reading hills: 
PLUMED:   doing serialread 
PLUMED:   done with this chunk: now with 180000 kernels  
PLUMED: 
PLUMED:   Writing full grid on file fes_17.dat 
PLUMED:   reading hills: 
PLUMED:   doing serialread 
PLUMED:   done with this chunk: now with 190000 kernels  
PLUMED: 
PLUMED:   Writing full grid on file fes_18.dat 
PLUMED:   reading hills: 
PLUMED:   doing serialread 
PLUMED:   done with this chunk: now with 200000 kernels  
PLUMED: 
PLUMED:   Writing full grid on file fes_19.dat 
PLUMED:   reading hills: 
PLUMED:   doing serialread 
PLUMED:   done with this chunk: now with 210000 kernels  
PLUMED: 
PLUMED:   Writing full grid on file fes_20.dat 
PLUMED:   reading hills: 
PLUMED:   doing serialread 
PLUMED:   done with this chunk: now with 220000 kernels  
PLUMED: 
PLUMED:   Writing full grid on file fes_21.dat 
PLUMED:   reading hills: 
PLUMED:   doing serialread 
PLUMED:   closing file HILLS
PLUMED:   now total 224180 kernels 
PLUMED:   final chunk: now with 224180 kernels  
PLUMED: 
PLUMED:   Writing full grid on file fes_22.dat 
PLUMED:                                               Cycles        Total      Average      Minimum      Maximum
PLUMED: 0 Summing hills                                    1     6.914519     6.914519     6.914519     6.914519
PLUMED:                                               Cycles        Total      Average      Minimum      Maximum
PLUMED:                                                    1     0.000166     0.000166     0.000166     0.000166
In [12]:
# plot free energy as a function of simulation time
for i in range(19,23,1):   
 # import fes file into pandas dataset
 data=plumed.read_as_pandas("Exercise-2/run_2D/fes_"+str(i)+".dat")
 # plot fes
 plt.plot(data["cv"],data["file.free"], label="Ng="+str(int(i)*10)+"k") 
# labels
plt.xlabel("# native contacts")
plt.ylabel("free energy [kJ/mol]")
plt.legend(ncol=2)
Out[12]:
<matplotlib.legend.Legend at 0x7fccd905a050>
No description has been provided for this image
In [13]:
%%bash
# Exercise 2
cd Exercise-2/run_2D

# prepare PLUMED input file for reweighting
cat > "plumed_reweight.dat" << EOF
# reconstruct molecule
WHOLEMOLECULES ENTITY0=1-330

# CA-RMSDs from the two reference conformations
rmsd_A: RMSD REFERENCE=stateA.pdb TYPE=OPTIMAL NOPBC
rmsd_B: RMSD REFERENCE=stateB.pdb TYPE=OPTIMAL NOPBC

cv: COORDINATION ...
NOPBC 
GROUPA=1,1,1,2,2,2,2,2,3,3,3,3,4,5,5,6,9,10,10,10,10,13,13,13,13,13,13,13,14,14,14,14,14,14,14,14,14,16,16,16,16,16,18,18,18,18,19,21,22,22,22,22,22,22,24,25,25,25,27,27,27,27,27,27,27,27,28,28,28,28,29,29,29,29,29,29,29,30,30,30,30,30,30,30,30,30,30,32,32,32,32,32,32,34,34,34,38,39,41,41,41,47,47,47,48,48,48,52,52,57,57,60,62,62,63,63,63,66,68,68,68,68,83,84,84,84,84,84,84,89,89,89,93,95,98,101,101,101,101,101,101,103,103,104,104,104,104,104,104,104,105,107,107,107,107,107,108,109,109,110,111,111,114,114,114,114,114,114,114,116,116,116,116,119,119,119,120,120,120,120,120,126,126,126,126,128,128,129,129,129,129,129,129,129,130,130,130,130,130,130,130,130,133,133,133,133,133,135,140,141,141,141,141,141,144,144,144,144,145,145,145,145,149,149,149,149,151,151,153,153,153,153,153,153,154,154,154,158,160,160,160,160,162,166,166,166,169,169,169,174,174,174,174,174,174,174,176,176,176,176,176,178,178,178,178,180,180,180,184,186,186,186,186,188,188,188,189,189,189,191,191,191,191,191,191,193,193,193,193,195,195,196,197,197,197,197,197,200,200,200,200,200,202,202,202,204,204,204,204,204,205,205,207,207,207,207,207,209,209,209,209,210,211,212,212,212,212,212,212,212,212,213,213,213,213,216,216,216,216,218,218,218,220,220,220,220,220,220,220,221,221,221,223,223,223,223,223,223,225,225,225,226,226,232,232,232,232,232,235,235,235,236,236,236,236,237,239,239,239
GROUPB=110,115,122,106,108,110,112,115,95,96,98,102,112,95,98,112,123,95,102,106,115,106,108,112,115,123,203,205,92,102,103,104,106,113,202,205,208,92,94,96,102,106,82,92,94,96,96,78,79,80,92,94,96,99,205,78,82,92,60,68,70,72,78,82,84,92,60,68,70,311,82,92,102,104,205,310,311,60,68,82,84,92,104,221,309,310,311,68,70,72,78,82,92,70,72,75,71,73,72,74,75,58,71,74,70,71,72,69,71,86,87,221,218,221,236,237,279,295,82,84,93,221,229,217,218,219,221,229,231,229,231,237,229,229,229,215,217,219,224,229,231,215,224,202,204,208,215,217,219,220,203,201,202,208,210,215,202,210,213,210,213,215,133,199,201,203,208,210,215,199,201,203,204,192,199,201,188,203,204,205,327,194,199,201,208,286,287,194,196,197,199,206,284,300,199,208,210,212,213,285,286,287,192,194,196,197,199,196,199,187,192,194,195,196,185,187,192,195,185,187,189,199,185,187,195,196,195,196,170,175,176,177,185,195,177,179,182,177,175,177,186,328,189,189,327,328,186,188,328,313,315,316,317,323,325,328,313,315,317,323,328,315,317,319,323,317,319,320,328,303,313,315,323,310,313,315,323,327,328,300,302,303,307,310,313,300,302,307,310,302,303,303,284,291,301,302,303,300,302,307,310,313,300,307,310,300,302,307,310,313,310,313,281,283,291,300,310,281,283,285,291,287,267,267,270,274,281,283,285,287,288,267,270,287,288,274,278,281,291,278,279,281,278,279,281,283,291,293,300,278,279,293,264,266,274,277,278,281,266,267,268,268,271,266,268,274,277,278,266,274,278,274,277,278,279,279,256,258,265
PAIR SWITCH={CUSTOM FUNC=1-erf(x^4) R_0=1.0}
...

# metadynamics parameters
metad: METAD ARG=cv ...
  # Deposit a Gaussian every 10000000 time steps (never!), with initial height equal to 0.0 kJ/mol 
  PACE=10000000 HEIGHT=0.0 BIASFACTOR=60
  # Gaussian width (sigma) based on the CV fluctuations in unbiased run
  SIGMA=2.0
  # Gaussians will be written to file
  FILE=HILLS
  # Store MetaD bias potential on a grid
  GRID_MIN=0 GRID_MAX=400
  # Say that METAD should be restarting (= reading an existing HILLS file) 
  RESTART=YES # <- this is the new stuff! 
...

# Print out the values of cv and the metadynamics bias potential
PRINT ARG=cv,metad.bias STRIDE=1 FILE=COLVAR_REWEIGHT
EOF

# analyze with PLUMED driver
plumed driver --mf_trr traj.trr --plumed plumed_reweight.dat --kt 0.498868

DRIVER: Found molfile format trajectory trr with name traj.trr
PLUMED: PLUMED is starting
PLUMED: Version: 2.7.0 (git: Unknown) compiled on Dec 23 2020 at 20:47:11
PLUMED: Please cite these papers when using PLUMED [1][2]
PLUMED: For further information see the PLUMED web page at http://www.plumed.org
PLUMED: Root: /usr/local/anaconda3/envs/plumed-masterclass/lib/plumed
PLUMED: For installed feature, see /usr/local/anaconda3/envs/plumed-masterclass/lib/plumed/src/config/config.txt
PLUMED: Molecular dynamics engine: driver
PLUMED: Precision of reals: 8
PLUMED: Running over 1 node
PLUMED: Number of threads: 1
PLUMED: Cache line size: 512
PLUMED: Number of atoms: 330
PLUMED: File suffix: 
PLUMED: FILE: plumed_reweight.dat
PLUMED: Action WHOLEMOLECULES
PLUMED:   with label @0
PLUMED:   with stride 1
PLUMED:   atoms in entity 0 : 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 
PLUMED: Action RMSD
PLUMED:   with label rmsd_A
PLUMED:   reference from file stateA.pdb
PLUMED:   which contains 330 atoms
PLUMED:   with indices : 
PLUMED: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 
PLUMED: 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 
PLUMED: 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 
PLUMED: 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 
PLUMED: 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 
PLUMED: 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 
PLUMED: 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 
PLUMED: 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 
PLUMED: 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 
PLUMED: 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 
PLUMED: 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 
PLUMED: 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 
PLUMED: 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 
PLUMED: 326 327 328 329 330 
PLUMED:   method for alignment : OPTIMAL 
PLUMED:   without periodic boundary conditions
PLUMED: Action RMSD
PLUMED:   with label rmsd_B
PLUMED:   reference from file stateB.pdb
PLUMED:   which contains 330 atoms
PLUMED:   with indices : 
PLUMED: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 
PLUMED: 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 
PLUMED: 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 
PLUMED: 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 
PLUMED: 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 
PLUMED: 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 
PLUMED: 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 
PLUMED: 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 
PLUMED: 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 
PLUMED: 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 
PLUMED: 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 
PLUMED: 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 
PLUMED: 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 
PLUMED: 326 327 328 329 330 
PLUMED:   method for alignment : OPTIMAL 
PLUMED:   without periodic boundary conditions
PLUMED: Action COORDINATION
PLUMED:   with label cv
PLUMED:   between two groups of 379 and 379 atoms
PLUMED:   first group:
PLUMED:   1  1  1  2  2  2  2  2  3  3  3  3  4  5  5  6  9  10  10  10  10  13  13  13  
PLUMED:   13  13  13  13  14  14  14  14  14  14  14  14  14  16  16  16  16  16  18  18  18  18  19  21  22  
PLUMED:   22  22  22  22  22  24  25  25  25  27  27  27  27  27  27  27  27  28  28  28  28  29  29  29  29  
PLUMED:   29  29  29  30  30  30  30  30  30  30  30  30  30  32  32  32  32  32  32  34  34  34  38  39  41  
PLUMED:   41  41  47  47  47  48  48  48  52  52  57  57  60  62  62  63  63  63  66  68  68  68  68  83  84  
PLUMED:   84  84  84  84  84  89  89  89  93  95  98  101  101  101  101  101  101  103  103  104  104  104  104  104  104  
PLUMED:   104  105  107  107  107  107  107  108  109  109  110  111  111  114  114  114  114  114  114  114  116  116  116  116  119  
PLUMED:   119  119  120  120  120  120  120  126  126  126  126  128  128  129  129  129  129  129  129  129  130  130  130  130  130  
PLUMED:   130  130  130  133  133  133  133  133  135  140  141  141  141  141  141  144  144  144  144  145  145  145  145  149  149  
PLUMED:   149  149  151  151  153  153  153  153  153  153  154  154  154  158  160  160  160  160  162  166  166  166  169  169  169  
PLUMED:   174  174  174  174  174  174  174  176  176  176  176  176  178  178  178  178  180  180  180  184  186  186  186  186  188  
PLUMED:   188  188  189  189  189  191  191  191  191  191  191  193  193  193  193  195  195  196  197  197  197  197  197  200  200  
PLUMED:   200  200  200  202  202  202  204  204  204  204  204  205  205  207  207  207  207  207  209  209  209  209  210  211  212  
PLUMED:   212  212  212  212  212  212  212  213  213  213  213  216  216  216  216  218  218  218  220  220  220  220  220  220  220  
PLUMED:   221  221  221  223  223  223  223  223  223  225  225  225  226  226  232  232  232  232  232  235  235  235  236  236  236  
PLUMED:   236  237  239  239  239  
PLUMED:   second group:
PLUMED:   110  115  122  106  108  110  112  115  95  96  98  102  112  95  98  112  123  95  102  106  115  106  108  112  
PLUMED:   115  123  203  205  92  102  103  104  106  113  202  205  208  92  94  96  102  106  82  92  94  96  96  78  79  
PLUMED:   80  92  94  96  99  205  78  82  92  60  68  70  72  78  82  84  92  60  68  70  311  82  92  102  104  
PLUMED:   205  310  311  60  68  82  84  92  104  221  309  310  311  68  70  72  78  82  92  70  72  75  71  73  72  
PLUMED:   74  75  58  71  74  70  71  72  69  71  86  87  221  218  221  236  237  279  295  82  84  93  221  229  217  
PLUMED:   218  219  221  229  231  229  231  237  229  229  229  215  217  219  224  229  231  215  224  202  204  208  215  217  219  
PLUMED:   220  203  201  202  208  210  215  202  210  213  210  213  215  133  199  201  203  208  210  215  199  201  203  204  192  
PLUMED:   199  201  188  203  204  205  327  194  199  201  208  286  287  194  196  197  199  206  284  300  199  208  210  212  213  
PLUMED:   285  286  287  192  194  196  197  199  196  199  187  192  194  195  196  185  187  192  195  185  187  189  199  185  187  
PLUMED:   195  196  195  196  170  175  176  177  185  195  177  179  182  177  175  177  186  328  189  189  327  328  186  188  328  
PLUMED:   313  315  316  317  323  325  328  313  315  317  323  328  315  317  319  323  317  319  320  328  303  313  315  323  310  
PLUMED:   313  315  323  327  328  300  302  303  307  310  313  300  302  307  310  302  303  303  284  291  301  302  303  300  302  
PLUMED:   307  310  313  300  307  310  300  302  307  310  313  310  313  281  283  291  300  310  281  283  285  291  287  267  267  
PLUMED:   270  274  281  283  285  287  288  267  270  287  288  274  278  281  291  278  279  281  278  279  281  283  291  293  300  
PLUMED:   278  279  293  264  266  274  277  278  281  266  267  268  268  271  266  268  274  277  278  266  274  278  274  277  278  
PLUMED:   279  279  256  258  265  
PLUMED:   without periodic boundary conditions
PLUMED:   with PAIR option
PLUMED:   contacts are counted with cutoff 1.  Using lepton switching function with parameters d0=0 func=1-erf(x^4)
PLUMED: Action METAD
PLUMED:   with label metad
PLUMED:   with arguments cv
PLUMED:   added component to this action:  metad.bias 
PLUMED:   Binsize not specified, 1/5 of sigma will be be used
PLUMED:   Gaussian width  2.000000  Gaussian height 0.000000
PLUMED:   Gaussian deposition pace 10000000
PLUMED:   Gaussian file HILLS
PLUMED:   Well-Tempered Bias Factor 60.000000
PLUMED:   Hills relaxation time (tau) inf
PLUMED:   KbT 0.498868
PLUMED:   Grid min 0
PLUMED:   Grid max 400
PLUMED:   Grid bin 1001
PLUMED:   Grid uses spline interpolation
PLUMED:   added component to this action:  metad.work 
PLUMED:   Restarting from HILLS:      224180 Gaussians read
PLUMED:   Bibliography [3][4]
PLUMED: Action PRINT
PLUMED:   with label @5
PLUMED:   with stride 1
PLUMED:   with arguments cv metad.bias
PLUMED:   on file COLVAR_REWEIGHT
PLUMED:   with format  %f
PLUMED: END FILE: plumed_reweight.dat
PLUMED: Timestep: 1.000000
PLUMED: KbT: 0.498868
PLUMED: Relevant bibliography:
PLUMED:   [1] The PLUMED consortium, Nat. Methods 16, 670 (2019)
PLUMED:   [2] Tribello, Bonomi, Branduardi, Camilloni, and Bussi, Comput. Phys. Commun. 185, 604 (2014)
PLUMED:   [3] Laio and Parrinello, PNAS 99, 12562 (2002)
PLUMED:   [4] Barducci, Bussi, and Parrinello, Phys. Rev. Lett. 100, 020603 (2008)
PLUMED: Please read and cite where appropriate!
PLUMED: Finished setup
PLUMED:                                               Cycles        Total      Average      Minimum      Maximum
PLUMED:                                                    1     9.037984     9.037984     9.037984     9.037984
PLUMED: 1 Prepare dependencies                         22416     0.011183     0.000000     0.000000     0.000035
PLUMED: 2 Sharing data                                 22416     0.041052     0.000002     0.000001     0.001700
PLUMED: 3 Waiting for data                             22416     0.003287     0.000000     0.000000     0.000035
PLUMED: 4 Calculating (forward loop)                   22416     1.110212     0.000050     0.000038     0.000302
PLUMED: 5 Applying (backward loop)                     22416     0.164747     0.000007     0.000005     0.000304
PLUMED: 6 Update                                       22416     0.103847     0.000005     0.000003     0.000230
In [14]:
%%bash
# Exercise 2
cd Exercise-2/run_2D

# create cv.weight file with cv and weight from COLVAR_REWEIGHT
# find maximum of bias
bmax=`sort -n -k 3 COLVAR_REWEIGHT  | tail -n 1 | awk '{print $3}'`
# create cv.weight file
awk '{if($1!="#!") print $2,exp(($3-bm)/0.498868)}' bm=$bmax COLVAR_REWEIGHT > cv.weight

# and now do block analysis with block sizes from 1 to 1000 (every 10)
# create PLUMED-like header for output file
echo "#! FIELDS bsize err" > err.blocks
for i in `seq 1 10 2000`
do
 # run the python script
 python ../../data/do_block_fes.py cv.weight 1 0 400 100 0.498868 $i
 # calculate average error along the free-energy profile
 grep -v Inf fes.$i.dat | awk 'BEGIN{tot=0}{tot+=$3}END{print i,tot/NR}' i=$i
done >> err.blocks
In [15]:
# import err.blocks file into pandas dataset
data=plumed.read_as_pandas("Exercise-2/run_2D/err.blocks")
# plot error as a function of block size
plt.plot(data["bsize"],data["err"])
# x-y axis labels
plt.xlabel("Block size")
plt.ylabel("Average free-energy error [kJ/mol]")
Out[15]:
Text(0, 0.5, 'Average free-energy error [kJ/mol]')
No description has been provided for this image
In [16]:
%%bash
# Exercise 2
cd Exercise-2

# Run production MetaD using optimized input file and Multiple Time Stepping with STRIDE=2
# Info machine: cores: 16  * CPU: Intel(R) Xeon(R) CPU E5-2667 v4 @ 3.20GHz * GPU: TITAN X (Pascal)
mkdir run_2D-STRIDE_2; cd run_2D-STRIDE_2

# create PLUMED optimized input file
cat > "plumed_opt.dat" << EOF
# reconstruct molecule
WHOLEMOLECULES ENTITY0=1-330

# CA-RMSDs from the two reference conformations
rmsd_A: RMSD REFERENCE=stateA.pdb TYPE=OPTIMAL NOPBC
rmsd_B: RMSD REFERENCE=stateB.pdb TYPE=OPTIMAL NOPBC

cv: COORDINATION NOPBC GROUPA=1,1,1,2,2,2,2,2,3,3,3,3,4,5,5,6,9,10,10,10,10,13,13,13,13,13,13,13,14,14,14,14,14,14,14,14,14,16,16,16,16,16,18,18,18,18,19,21,22,22,22,22,22,22,24,25,25,25,27,27,27,27,27,27,27,27,28,28,28,28,29,29,29,29,29,29,29,30,30,30,30,30,30,30,30,30,30,32,32,32,32,32,32,34,34,34,38,39,41,41,41,47,47,47,48,48,48,52,52,57,57,60,62,62,63,63,63,66,68,68,68,68,83,84,84,84,84,84,84,89,89,89,93,95,98,101,101,101,101,101,101,103,103,104,104,104,104,104,104,104,105,107,107,107,107,107,108,109,109,110,111,111,114,114,114,114,114,114,114,116,116,116,116,119,119,119,120,120,120,120,120,126,126,126,126,128,128,129,129,129,129,129,129,129,130,130,130,130,130,130,130,130,133,133,133,133,133,135,140,141,141,141,141,141,144,144,144,144,145,145,145,145,149,149,149,149,151,151,153,153,153,153,153,153,154,154,154,158,160,160,160,160,162,166,166,166,169,169,169,174,174,174,174,174,174,174,176,176,176,176,176,178,178,178,178,180,180,180,184,186,186,186,186,188,188,188,189,189,189,191,191,191,191,191,191,193,193,193,193,195,195,196,197,197,197,197,197,200,200,200,200,200,202,202,202,204,204,204,204,204,205,205,207,207,207,207,207,209,209,209,209,210,211,212,212,212,212,212,212,212,212,213,213,213,213,216,216,216,216,218,218,218,220,220,220,220,220,220,220,221,221,221,223,223,223,223,223,223,225,225,225,226,226,232,232,232,232,232,235,235,235,236,236,236,236,237,239,239,239 GROUPB=110,115,122,106,108,110,112,115,95,96,98,102,112,95,98,112,123,95,102,106,115,106,108,112,115,123,203,205,92,102,103,104,106,113,202,205,208,92,94,96,102,106,82,92,94,96,96,78,79,80,92,94,96,99,205,78,82,92,60,68,70,72,78,82,84,92,60,68,70,311,82,92,102,104,205,310,311,60,68,82,84,92,104,221,309,310,311,68,70,72,78,82,92,70,72,75,71,73,72,74,75,58,71,74,70,71,72,69,71,86,87,221,218,221,236,237,279,295,82,84,93,221,229,217,218,219,221,229,231,229,231,237,229,229,229,215,217,219,224,229,231,215,224,202,204,208,215,217,219,220,203,201,202,208,210,215,202,210,213,210,213,215,133,199,201,203,208,210,215,199,201,203,204,192,199,201,188,203,204,205,327,194,199,201,208,286,287,194,196,197,199,206,284,300,199,208,210,212,213,285,286,287,192,194,196,197,199,196,199,187,192,194,195,196,185,187,192,195,185,187,189,199,185,187,195,196,195,196,170,175,176,177,185,195,177,179,182,177,175,177,186,328,189,189,327,328,186,188,328,313,315,316,317,323,325,328,313,315,317,323,328,315,317,319,323,317,319,320,328,303,313,315,323,310,313,315,323,327,328,300,302,303,307,310,313,300,302,307,310,302,303,303,284,291,301,302,303,300,302,307,310,313,300,307,310,300,302,307,310,313,310,313,281,283,291,300,310,281,283,285,291,287,267,267,270,274,281,283,285,287,288,267,270,287,288,274,278,281,291,278,279,281,278,279,281,283,291,293,300,278,279,293,264,266,274,277,278,281,266,267,268,268,271,266,268,274,277,278,266,274,278,274,277,278,279,279,256,258,265 PAIR SWITCH={CUSTOM FUNC=1-erf(x^4) R_0=1.0}

# metadynamics parameters
metad: METAD ARG=cv ...
  # Deposit a Gaussian every 500 time steps, with initial height
  # equal to 1.2 kJ/mol and bias factor equal to 60
  PACE=500 HEIGHT=1.2 BIASFACTOR=60
  # Gaussian width (sigma) based on the CV fluctuations in unbiased run
  SIGMA=2.0
  # Store MetaD bias potential on a grid
  GRID_MIN=0 GRID_MAX=400
  # Gaussians will be written to file
  FILE=HILLS
  # Multiple time stepping
  STRIDE=2
...

# Energy drift
EFFECTIVE_ENERGY_DRIFT PRINT_STRIDE=500 FILE=COLVAR_ENE

# print useful stuff
PRINT ARG=cv,rmsd_A,rmsd_B,metad.bias STRIDE=500 FILE=COLVAR
EOF

# link useful files here
ln -s ../../data/exercise2/* . 2>/dev/null

# Run MetaD using optimize PLUMED input file (using 4 cores)
#gmx_mpi mdrun -s topol.tpr -plumed plumed_opt.dat -noddcheck -pin on -ntomp 4

mkdir: run_2D-STRIDE_2: File exists
In [17]:
%%bash
# Exercise 2
cd Exercise-2

# Run production MetaD using optimized input file and Multiple Time Stepping with STRIDE=4
# Info machine: cores: 16  * CPU: Intel(R) Xeon(R) CPU E5-2667 v4 @ 3.20GHz * GPU: TITAN X (Pascal)
mkdir run_2D-STRIDE_4; cd run_2D-STRIDE_4

# create PLUMED optimized input file
cat > "plumed_opt.dat" << EOF
# reconstruct molecule
WHOLEMOLECULES ENTITY0=1-330

# CA-RMSDs from the two reference conformations
rmsd_A: RMSD REFERENCE=stateA.pdb TYPE=OPTIMAL NOPBC
rmsd_B: RMSD REFERENCE=stateB.pdb TYPE=OPTIMAL NOPBC

cv: COORDINATION NOPBC GROUPA=1,1,1,2,2,2,2,2,3,3,3,3,4,5,5,6,9,10,10,10,10,13,13,13,13,13,13,13,14,14,14,14,14,14,14,14,14,16,16,16,16,16,18,18,18,18,19,21,22,22,22,22,22,22,24,25,25,25,27,27,27,27,27,27,27,27,28,28,28,28,29,29,29,29,29,29,29,30,30,30,30,30,30,30,30,30,30,32,32,32,32,32,32,34,34,34,38,39,41,41,41,47,47,47,48,48,48,52,52,57,57,60,62,62,63,63,63,66,68,68,68,68,83,84,84,84,84,84,84,89,89,89,93,95,98,101,101,101,101,101,101,103,103,104,104,104,104,104,104,104,105,107,107,107,107,107,108,109,109,110,111,111,114,114,114,114,114,114,114,116,116,116,116,119,119,119,120,120,120,120,120,126,126,126,126,128,128,129,129,129,129,129,129,129,130,130,130,130,130,130,130,130,133,133,133,133,133,135,140,141,141,141,141,141,144,144,144,144,145,145,145,145,149,149,149,149,151,151,153,153,153,153,153,153,154,154,154,158,160,160,160,160,162,166,166,166,169,169,169,174,174,174,174,174,174,174,176,176,176,176,176,178,178,178,178,180,180,180,184,186,186,186,186,188,188,188,189,189,189,191,191,191,191,191,191,193,193,193,193,195,195,196,197,197,197,197,197,200,200,200,200,200,202,202,202,204,204,204,204,204,205,205,207,207,207,207,207,209,209,209,209,210,211,212,212,212,212,212,212,212,212,213,213,213,213,216,216,216,216,218,218,218,220,220,220,220,220,220,220,221,221,221,223,223,223,223,223,223,225,225,225,226,226,232,232,232,232,232,235,235,235,236,236,236,236,237,239,239,239 GROUPB=110,115,122,106,108,110,112,115,95,96,98,102,112,95,98,112,123,95,102,106,115,106,108,112,115,123,203,205,92,102,103,104,106,113,202,205,208,92,94,96,102,106,82,92,94,96,96,78,79,80,92,94,96,99,205,78,82,92,60,68,70,72,78,82,84,92,60,68,70,311,82,92,102,104,205,310,311,60,68,82,84,92,104,221,309,310,311,68,70,72,78,82,92,70,72,75,71,73,72,74,75,58,71,74,70,71,72,69,71,86,87,221,218,221,236,237,279,295,82,84,93,221,229,217,218,219,221,229,231,229,231,237,229,229,229,215,217,219,224,229,231,215,224,202,204,208,215,217,219,220,203,201,202,208,210,215,202,210,213,210,213,215,133,199,201,203,208,210,215,199,201,203,204,192,199,201,188,203,204,205,327,194,199,201,208,286,287,194,196,197,199,206,284,300,199,208,210,212,213,285,286,287,192,194,196,197,199,196,199,187,192,194,195,196,185,187,192,195,185,187,189,199,185,187,195,196,195,196,170,175,176,177,185,195,177,179,182,177,175,177,186,328,189,189,327,328,186,188,328,313,315,316,317,323,325,328,313,315,317,323,328,315,317,319,323,317,319,320,328,303,313,315,323,310,313,315,323,327,328,300,302,303,307,310,313,300,302,307,310,302,303,303,284,291,301,302,303,300,302,307,310,313,300,307,310,300,302,307,310,313,310,313,281,283,291,300,310,281,283,285,291,287,267,267,270,274,281,283,285,287,288,267,270,287,288,274,278,281,291,278,279,281,278,279,281,283,291,293,300,278,279,293,264,266,274,277,278,281,266,267,268,268,271,266,268,274,277,278,266,274,278,274,277,278,279,279,256,258,265 PAIR SWITCH={CUSTOM FUNC=1-erf(x^4) R_0=1.0}

# metadynamics parameters
metad: METAD ARG=cv ...
  # Deposit a Gaussian every 500 time steps, with initial height
  # equal to 1.2 kJ/mol and bias factor equal to 60
  PACE=500 HEIGHT=1.2 BIASFACTOR=60
  # Gaussian width (sigma) based on the CV fluctuations in unbiased run
  SIGMA=2.0
  # Store MetaD bias potential on a grid
  GRID_MIN=0 GRID_MAX=400
  # Gaussians will be written to file
  FILE=HILLS
  # Multiple time stepping
  STRIDE=4
...

# Energy drift
EFFECTIVE_ENERGY_DRIFT PRINT_STRIDE=500 FILE=COLVAR_ENE

# print useful stuff
PRINT ARG=cv,rmsd_A,rmsd_B,metad.bias STRIDE=500 FILE=COLVAR
EOF

# link useful files here
ln -s ../../data/exercise2/* . 2>/dev/null

# Run MetaD using optimize PLUMED input file (using 4 cores)
#gmx_mpi mdrun -s topol.tpr -plumed plumed_opt.dat -noddcheck -pin on -ntomp 4

mkdir: run_2D-STRIDE_4: File exists
In [18]:
%%bash
# Exercise 2
cd Exercise-2

# First we measure the performances of the runs with STRIDE=1, 2, and 4
grep -B1 Perf run_2D/md.log run_2D-STRIDE_2/md.log run_2D-STRIDE_4/md.log

run_2D/md.log-                 (ns/day)    (hour/ns)
run_2D/md.log:Performance:      322.797        0.074
--
run_2D-STRIDE_2/md.log-                 (ns/day)    (hour/ns)
run_2D-STRIDE_2/md.log:Performance:      366.119        0.066
--
run_2D-STRIDE_4/md.log-                 (ns/day)    (hour/ns)
run_2D-STRIDE_4/md.log:Performance:      367.190        0.065
In [19]:
# and the effective energy conservation when using Multiple Time Stepping
data_2=plumed.read_as_pandas("Exercise-2/run_2D-STRIDE_2/COLVAR_ENE")
data_4=plumed.read_as_pandas("Exercise-2/run_2D-STRIDE_4/COLVAR_ENE")
# plot error as a function of block size
plt.plot(data_2["time"]/1000.0,data_2["effective-energy"], label="MTS - STRIDE=2")
plt.plot(data_4["time"]/1000.0,data_4["effective-energy"], label="MTS - STRIDE=4")
# x-y axis labels
plt.xlabel("Simulation time [ns]")
plt.ylabel("Effective Energy [kJ/mol]")
plt.legend()
Out[19]:
<matplotlib.legend.Legend at 0x7fccf8fd7dd0>
No description has been provided for this image
In [20]:
%%bash
# Exercise 2
cd Exercise-2

# now we calculate the final free-energy for STRIDE=1, 2, and 4
cd run_2D
plumed sum_hills --hills HILLS --mintozero
cd ../run_2D-STRIDE_2
plumed sum_hills --hills HILLS --mintozero
cd ../run_2D-STRIDE_4
plumed sum_hills --hills HILLS --mintozero

PLUMED: PLUMED is starting
PLUMED: Version: 2.7.0 (git: Unknown) compiled on Dec 23 2020 at 20:47:11
PLUMED: Please cite these papers when using PLUMED [1][2]
PLUMED: For further information see the PLUMED web page at http://www.plumed.org
PLUMED: Root: /usr/local/anaconda3/envs/plumed-masterclass/lib/plumed
PLUMED: For installed feature, see /usr/local/anaconda3/envs/plumed-masterclass/lib/plumed/src/config/config.txt
PLUMED: Molecular dynamics engine: 
PLUMED: Precision of reals: 8
PLUMED: Running over 1 node
PLUMED: Number of threads: 1
PLUMED: Cache line size: 512
PLUMED: Number of atoms: 1
PLUMED: File suffix: 
PLUMED: Timestep: 0.000000
PLUMED: KbT has not been set by the MD engine
PLUMED: It should be set by hand where needed
PLUMED: Relevant bibliography:
PLUMED:   [1] The PLUMED consortium, Nat. Methods 16, 670 (2019)
PLUMED:   [2] Tribello, Bonomi, Branduardi, Camilloni, and Bussi, Comput. Phys. Commun. 185, 604 (2014)
PLUMED: Please read and cite where appropriate!
PLUMED: Finished setup
PLUMED: Action FAKE
PLUMED:   with label cv
PLUMED: Action FUNCSUMHILLS
PLUMED:   with label @1
PLUMED:   with arguments cv
PLUMED:   Output format is %14.9f
PLUMED:   hillsfile  : HILLS
PLUMED:    
PLUMED:   No boundaries defined: need to do a prescreening of hills 
PLUMED:   doing serialread 
PLUMED:   opening file HILLS
PLUMED:   closing file HILLS
PLUMED:   now total 224180 kernels 
PLUMED:   final chunk: now with 224180 kernels  
PLUMED:   found boundaries from hillsfile: 
PLUMED:   variable cv min: -4.69271 max: 369.042 nbin: 529
PLUMED:   done!
PLUMED:    
PLUMED:   Doing only one integration: no stride 
PLUMED:   mintozero: bias/histogram will be translated to have the minimum value equal to zero
PLUMED:   output file for fes/bias  is :  fes.dat
PLUMED: 
PLUMED:   Now calculating...
PLUMED: 
PLUMED:   reading hills: 
PLUMED:   doing serialread 
PLUMED:   opening file HILLS
PLUMED:   closing file HILLS
PLUMED:   now total 224180 kernels 
PLUMED:   final chunk: now with 224180 kernels  
PLUMED: 
PLUMED:   Writing full grid on file fes.dat 
PLUMED:                                               Cycles        Total      Average      Minimum      Maximum
PLUMED: 0 Summing hills                                    1     6.806530     6.806530     6.806530     6.806530
PLUMED:                                               Cycles        Total      Average      Minimum      Maximum
PLUMED:                                                    1     0.000135     0.000135     0.000135     0.000135
PLUMED: PLUMED is starting
PLUMED: Version: 2.7.0 (git: Unknown) compiled on Dec 23 2020 at 20:47:11
PLUMED: Please cite these papers when using PLUMED [1][2]
PLUMED: For further information see the PLUMED web page at http://www.plumed.org
PLUMED: Root: /usr/local/anaconda3/envs/plumed-masterclass/lib/plumed
PLUMED: For installed feature, see /usr/local/anaconda3/envs/plumed-masterclass/lib/plumed/src/config/config.txt
PLUMED: Molecular dynamics engine: 
PLUMED: Precision of reals: 8
PLUMED: Running over 1 node
PLUMED: Number of threads: 1
PLUMED: Cache line size: 512
PLUMED: Number of atoms: 1
PLUMED: File suffix: 
PLUMED: Timestep: 0.000000
PLUMED: KbT has not been set by the MD engine
PLUMED: It should be set by hand where needed
PLUMED: Relevant bibliography:
PLUMED:   [1] The PLUMED consortium, Nat. Methods 16, 670 (2019)
PLUMED:   [2] Tribello, Bonomi, Branduardi, Camilloni, and Bussi, Comput. Phys. Commun. 185, 604 (2014)
PLUMED: Please read and cite where appropriate!
PLUMED: Finished setup
PLUMED: Action FAKE
PLUMED:   with label cv
PLUMED: Action FUNCSUMHILLS
PLUMED:   with label @1
PLUMED:   with arguments cv
PLUMED:   Output format is %14.9f
PLUMED:   hillsfile  : HILLS
PLUMED:    
PLUMED:   No boundaries defined: need to do a prescreening of hills 
PLUMED:   doing serialread 
PLUMED:   opening file HILLS
PLUMED:   closing file HILLS
PLUMED:   now total 253260 kernels 
PLUMED:   final chunk: now with 253260 kernels  
PLUMED:   found boundaries from hillsfile: 
PLUMED:   variable cv min: -4.85155 max: 369.1 nbin: 529
PLUMED:   done!
PLUMED:    
PLUMED:   Doing only one integration: no stride 
PLUMED:   mintozero: bias/histogram will be translated to have the minimum value equal to zero
PLUMED:   output file for fes/bias  is :  fes.dat
PLUMED: 
PLUMED:   Now calculating...
PLUMED: 
PLUMED:   reading hills: 
PLUMED:   doing serialread 
PLUMED:   opening file HILLS
PLUMED:   closing file HILLS
PLUMED:   now total 253260 kernels 
PLUMED:   final chunk: now with 253260 kernels  
PLUMED: 
PLUMED:   Writing full grid on file fes.dat 
PLUMED:                                               Cycles        Total      Average      Minimum      Maximum
PLUMED: 0 Summing hills                                    1     7.946409     7.946409     7.946409     7.946409
PLUMED:                                               Cycles        Total      Average      Minimum      Maximum
PLUMED:                                                    1     0.000126     0.000126     0.000126     0.000126
PLUMED: PLUMED is starting
PLUMED: Version: 2.7.0 (git: Unknown) compiled on Dec 23 2020 at 20:47:11
PLUMED: Please cite these papers when using PLUMED [1][2]
PLUMED: For further information see the PLUMED web page at http://www.plumed.org
PLUMED: Root: /usr/local/anaconda3/envs/plumed-masterclass/lib/plumed
PLUMED: For installed feature, see /usr/local/anaconda3/envs/plumed-masterclass/lib/plumed/src/config/config.txt
PLUMED: Molecular dynamics engine: 
PLUMED: Precision of reals: 8
PLUMED: Running over 1 node
PLUMED: Number of threads: 1
PLUMED: Cache line size: 512
PLUMED: Number of atoms: 1
PLUMED: File suffix: 
PLUMED: Timestep: 0.000000
PLUMED: KbT has not been set by the MD engine
PLUMED: It should be set by hand where needed
PLUMED: Relevant bibliography:
PLUMED:   [1] The PLUMED consortium, Nat. Methods 16, 670 (2019)
PLUMED:   [2] Tribello, Bonomi, Branduardi, Camilloni, and Bussi, Comput. Phys. Commun. 185, 604 (2014)
PLUMED: Please read and cite where appropriate!
PLUMED: Finished setup
PLUMED: Action FAKE
PLUMED:   with label cv
PLUMED: Action FUNCSUMHILLS
PLUMED:   with label @1
PLUMED:   with arguments cv
PLUMED:   Output format is %14.9f
PLUMED:   hillsfile  : HILLS
PLUMED:    
PLUMED:   No boundaries defined: need to do a prescreening of hills 
PLUMED:   doing serialread 
PLUMED:   opening file HILLS
PLUMED:   closing file HILLS
PLUMED:   now total 254480 kernels 
PLUMED:   final chunk: now with 254480 kernels  
PLUMED:   found boundaries from hillsfile: 
PLUMED:   variable cv min: -4.81938 max: 368.93 nbin: 529
PLUMED:   done!
PLUMED:    
PLUMED:   Doing only one integration: no stride 
PLUMED:   mintozero: bias/histogram will be translated to have the minimum value equal to zero
PLUMED:   output file for fes/bias  is :  fes.dat
PLUMED: 
PLUMED:   Now calculating...
PLUMED: 
PLUMED:   reading hills: 
PLUMED:   doing serialread 
PLUMED:   opening file HILLS
PLUMED:   closing file HILLS
PLUMED:   now total 254480 kernels 
PLUMED:   final chunk: now with 254480 kernels  
PLUMED: 
PLUMED:   Writing full grid on file fes.dat 
PLUMED:                                               Cycles        Total      Average      Minimum      Maximum
PLUMED: 0 Summing hills                                    1     8.542143     8.542143     8.542143     8.542143
PLUMED:                                               Cycles        Total      Average      Minimum      Maximum
PLUMED:                                                    1     0.000259     0.000259     0.000259     0.000259
In [21]:
# read free energies as pandas datasets
data_1=plumed.read_as_pandas("Exercise-2/run_2D/fes.dat")
data_2=plumed.read_as_pandas("Exercise-2/run_2D-STRIDE_2/fes.dat")
data_4=plumed.read_as_pandas("Exercise-2/run_2D-STRIDE_4/fes.dat")

# plot fes
plt.plot(data_1["cv"],data_1["file.free"], label="MTS - STRIDE=1")
plt.plot(data_2["cv"],data_2["file.free"], label="MTS - STRIDE=2")
plt.plot(data_4["cv"],data_4["file.free"], label="MTS - STRIDE=4")


# labels
plt.xlabel("# native contacts")
plt.ylabel("free energy [kJ/mol]")
plt.legend()
Out[21]:
<matplotlib.legend.Legend at 0x7fccf98f9b10>
No description has been provided for this image
In [22]:
# from Masterclass 21.4: fes as function of RMSD State A and B
img = mpimg.imread('old_fes.png')
plt.imshow(img)
Out[22]:
<matplotlib.image.AxesImage at 0x7fccf9951a90>
No description has been provided for this image
In [23]:
%%bash
# Exercise 2
cd Exercise-2

# now we want to measure the effect of using GRIDs in Metadynamics
# Info machine: cores: 16  * CPU: Intel(R) Xeon(R) CPU E5-2667 v4 @ 3.20GHz * GPU: TITAN X (Pascal)
mkdir run_2E; cd run_2E

# create PLUMED optimized input file
cat > "plumed_opt.dat" << EOF
RESTART
# reconstruct molecule
WHOLEMOLECULES ENTITY0=1-330

# CA-RMSDs from the two reference conformations
rmsd_A: RMSD REFERENCE=stateA.pdb TYPE=OPTIMAL NOPBC
rmsd_B: RMSD REFERENCE=stateB.pdb TYPE=OPTIMAL NOPBC

cv: COORDINATION NOPBC GROUPA=1,1,1,2,2,2,2,2,3,3,3,3,4,5,5,6,9,10,10,10,10,13,13,13,13,13,13,13,14,14,14,14,14,14,14,14,14,16,16,16,16,16,18,18,18,18,19,21,22,22,22,22,22,22,24,25,25,25,27,27,27,27,27,27,27,27,28,28,28,28,29,29,29,29,29,29,29,30,30,30,30,30,30,30,30,30,30,32,32,32,32,32,32,34,34,34,38,39,41,41,41,47,47,47,48,48,48,52,52,57,57,60,62,62,63,63,63,66,68,68,68,68,83,84,84,84,84,84,84,89,89,89,93,95,98,101,101,101,101,101,101,103,103,104,104,104,104,104,104,104,105,107,107,107,107,107,108,109,109,110,111,111,114,114,114,114,114,114,114,116,116,116,116,119,119,119,120,120,120,120,120,126,126,126,126,128,128,129,129,129,129,129,129,129,130,130,130,130,130,130,130,130,133,133,133,133,133,135,140,141,141,141,141,141,144,144,144,144,145,145,145,145,149,149,149,149,151,151,153,153,153,153,153,153,154,154,154,158,160,160,160,160,162,166,166,166,169,169,169,174,174,174,174,174,174,174,176,176,176,176,176,178,178,178,178,180,180,180,184,186,186,186,186,188,188,188,189,189,189,191,191,191,191,191,191,193,193,193,193,195,195,196,197,197,197,197,197,200,200,200,200,200,202,202,202,204,204,204,204,204,205,205,207,207,207,207,207,209,209,209,209,210,211,212,212,212,212,212,212,212,212,213,213,213,213,216,216,216,216,218,218,218,220,220,220,220,220,220,220,221,221,221,223,223,223,223,223,223,225,225,225,226,226,232,232,232,232,232,235,235,235,236,236,236,236,237,239,239,239 GROUPB=110,115,122,106,108,110,112,115,95,96,98,102,112,95,98,112,123,95,102,106,115,106,108,112,115,123,203,205,92,102,103,104,106,113,202,205,208,92,94,96,102,106,82,92,94,96,96,78,79,80,92,94,96,99,205,78,82,92,60,68,70,72,78,82,84,92,60,68,70,311,82,92,102,104,205,310,311,60,68,82,84,92,104,221,309,310,311,68,70,72,78,82,92,70,72,75,71,73,72,74,75,58,71,74,70,71,72,69,71,86,87,221,218,221,236,237,279,295,82,84,93,221,229,217,218,219,221,229,231,229,231,237,229,229,229,215,217,219,224,229,231,215,224,202,204,208,215,217,219,220,203,201,202,208,210,215,202,210,213,210,213,215,133,199,201,203,208,210,215,199,201,203,204,192,199,201,188,203,204,205,327,194,199,201,208,286,287,194,196,197,199,206,284,300,199,208,210,212,213,285,286,287,192,194,196,197,199,196,199,187,192,194,195,196,185,187,192,195,185,187,189,199,185,187,195,196,195,196,170,175,176,177,185,195,177,179,182,177,175,177,186,328,189,189,327,328,186,188,328,313,315,316,317,323,325,328,313,315,317,323,328,315,317,319,323,317,319,320,328,303,313,315,323,310,313,315,323,327,328,300,302,303,307,310,313,300,302,307,310,302,303,303,284,291,301,302,303,300,302,307,310,313,300,307,310,300,302,307,310,313,310,313,281,283,291,300,310,281,283,285,291,287,267,267,270,274,281,283,285,287,288,267,270,287,288,274,278,281,291,278,279,281,278,279,281,283,291,293,300,278,279,293,264,266,274,277,278,281,266,267,268,268,271,266,268,274,277,278,266,274,278,274,277,278,279,279,256,258,265 PAIR SWITCH={CUSTOM FUNC=1-erf(x^4) R_0=1.0}

# metadynamics parameters
metad: METAD ARG=cv ...
  # Deposit a Gaussian every 500 time steps, with initial height
  # equal to 1.2 kJ/mol and bias factor equal to 60
  PACE=500 HEIGHT=1.2 BIASFACTOR=60
  # Gaussian width (sigma) based on the CV fluctuations in unbiased run
  SIGMA=2.0
  # Gaussians will be written to file
  FILE=../run_2D/HILLS
...

# print useful stuff
PRINT ARG=cv,rmsd_A,rmsd_B,metad.bias STRIDE=500 FILE=COLVAR
EOF

# link useful files here
ln -s ../../data/exercise2/* . 2>/dev/null

# Run MetaD using optimized PLUMED input file (using 4 cores)
#gmx_mpi mdrun -s topol.tpr -plumed plumed_opt.dat -noddcheck -pin on -ntomp 4 -maxh 1.0

mkdir: run_2E: File exists
In [24]:
%%bash
# Exercise 2
cd Exercise-2

# let's compare the performances with/without GRID
grep -B1 Perf run_2C/md.log run_2D/md.log run_2E/md.log

run_2C/md.log-                 (ns/day)    (hour/ns)
run_2C/md.log:Performance:      317.132        0.076
--
run_2D/md.log-                 (ns/day)    (hour/ns)
run_2D/md.log:Performance:      322.797        0.074
--
run_2E/md.log-                 (ns/day)    (hour/ns)
run_2E/md.log:Performance:        3.570        6.722
In [25]:
%%bash
# Exercise 2
cd Exercise-2

# now we want to measure the effect of using the AsmJit library
# Info machine: cores: 16  * CPU: Intel(R) Xeon(R) CPU E5-2667 v4 @ 3.20GHz * GPU: TITAN X (Pascal)
mkdir run_2F; cd run_2F

# link useful files here
ln -s ../../data/exercise2/* . 2>/dev/null

# deactivate AsmJit library
export PLUMED_USE_ASMJIT=no
# run using input file of run_2D
#gmx_mpi mdrun -s topol.tpr -plumed ../run_2C/plumed_opt.dat -noddcheck -pin on -ntomp 4 -maxh 1.0

# extract performances
grep -B1 Perf md.log

                 (ns/day)    (hour/ns)
Performance:      297.694        0.081

mkdir: run_2F: File exists
In [26]:
# final performance plot
data=[766.272,14.950,322.797,366.119,367.190,3.570,297.694,382.820]
label=["Gromacs","Original","Optimized","STRIDE=2","STRIDE=4","No Grid","No AsmJit","C++"]
c=['red', 'magenta', 'green', 'orange', 'cyan', 'black', 'blue', 'violet']
ind=list(range(0,len(data)))
# make bar plot
plt.figure(figsize=(6,3))
plt.grid(color = 'black', linestyle = '--', linewidth = 0.5)
plt.bar(ind, data, 0.75, color=c)
plt.xticks(ind, label, rotation=45)
plt.ylabel("Performance [ns/day]", size="large")
Out[26]:
Text(0, 0.5, 'Performance [ns/day]')
No description has been provided for this image
In [ ]: