anncolvar 0.2

Coding collective variables by artificial neural networks

[](https://pypi.org/project/anncolvar/)
[](https://travis-ci.org/spiwokv/anncolvar)
[](https://codecov.io/gh/spiwokv/anncolvar/)

# anncolvar
Collective variables by artificial neural networks

```
usage: anncolvar [-h] [-i INFILE] [-p INTOP] [-c COLVAR] [-col COL]
[-boxx BOXX] [-boxy BOXY] [-boxz BOXZ] [-nofit NOFIT]
[-testset TESTSET] [-shuffle SHUFFLE] [-layers LAYERS]
[-layer1 LAYER1] [-layer2 LAYER2] [-layer3 LAYER3]
[-actfun1 ACTFUN1] [-actfun2 ACTFUN2] [-actfun3 ACTFUN3]
[-optim OPTIM] [-loss LOSS] [-epochs EPOCHS] [-batch BATCH]
[-o OFILE] [-model MODELFILE] [-plumed PLUMEDFILE]

Artificial neural network learning of collective variables of molecular
systems, requires numpy, keras and mdtraj

optional arguments:
-h, --help show this help message and exit
-i INFILE Input trajectory in pdb, xtc, trr, dcd, netcdf or mdcrd,
WARNING: the trajectory must be 1. centered in the PBC
box, 2. fitted to a reference structure and 3. must
contain only atoms to be analysed!
-p INTOP Input topology in pdb, WARNING: the structure must be 1.
centered in the PBC box and 2. must contain only atoms
to be analysed!
-c COLVAR Input collective variable file in text formate, must
contain the same number of lines as frames in the
trajectory
-col COL The index of the column containing collective variables
in the input collective variable file
-boxx BOXX Size of x coordinate of PBC box (from 0 to set value in
nm)
-boxy BOXY Size of y coordinate of PBC box (from 0 to set value in
nm)
-boxz BOXZ Size of z coordinate of PBC box (from 0 to set value in
nm)
-nofit NOFIT Disable fitting, the trajectory must be properly fited
(default False)
-testset TESTSET Size of test set (fraction of the trajectory, default =
0.1)
-shuffle SHUFFLE Shuffle trajectory frames to obtain training and test
set (default True)
-layers LAYERS Number of hidden layers (allowed values 1-3, default =
1)
-layer1 LAYER1 Number of neurons in the first encoding layer (default =
256)
-layer2 LAYER2 Number of neurons in the second encoding layer (default
= 256)
-layer3 LAYER3 Number of neurons in the third encoding layer (default =
256)
-actfun1 ACTFUN1 Activation function of the first layer (default =
sigmoid, for options see keras documentation)
-actfun2 ACTFUN2 Activation function of the second layer (default =
linear, for options see keras documentation)
-actfun3 ACTFUN3 Activation function of the third layer (default =
linear, for options see keras documentation)
-optim OPTIM Optimizer (default = adam, for options see keras
documentation)
-loss LOSS Loss function (default = mean_squared_error, for options
see keras documentation)
-epochs EPOCHS Number of epochs (default = 100, >1000 may be necessary
for real life applications)
-batch BATCH Batch size (0 = no batches, default = 256)
-o OFILE Output file with original and approximated collective
variables (txt, default = no output)
-model MODELFILE Prefix for output model files (experimental, default =
no output)
-plumed PLUMEDFILE Output file for Plumed (default = plumed.dat)

```