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Dear Lukas

I am trying to use PyDHAMed to compute a PMF for a small molecule crossing a membrane bilayer. I performed umbrella sampling in 1.5Å windows, spanning approx. 7nm (57 umbrellas in total).

Following your code, I first created the list of transition matrices for each of the umbrellas:

def create_transition_matrix(traj: npt.NDArray, microstates: npt.NDArray)->npt.NDArray:
    """
    Parameters
    --------------
    traj: np.array of size n
    microstates: np.array of size m

    First, the trajectory is binned into the provided
    microstates. Next, a transition matrix is calculated
    giving the number of transitions between each of the
    microstates.
    
    Returns: m x m matrix with the transitions between 
    all possible pairs of bins in subsequent trajectory frames. 
    """
    traj_binned = np.digitize(traj, microstates)
    n_states = microstates.shape[0]+1 # digitize is 1 indexed.
    mat = np.zeros((n_states, n_states))
    for (x, y), c in six.iteritems(Counter(zip(traj_binned[:-1], traj_binned[1:]))):
        mat[int(y), int(x)] = c
    return mat

colvar_files = glob.glob("../gromacs/plumed_us_*-colvar.dat")

transition_matrices = list()
for i, f in enumerate(colvar_files):
    print("Processing trajectory: ", f)
    traj = np.loadtxt(f)[500:, 1]
    transition_matrices.append(create_transition_matrix(traj, microstates)[1:, 1:])
with open("NFP_membrane_transition_counts.pickle", "wb") as outfile:
    pickle.dump(transition_matrices, outfile)

Next, I calculated the bias grid (in kBT units) as follows:

def create_biasses(q0, kappa, microstates)->npt.NDArray:
    bias = (0.5 * force_constants[:, np.newaxis] * (centers[:, np.newaxis] - microstates)**2).T
    # convert to kBT
    return (bias*1000)/(R*T)

#col0 = bias number
#col1 = bias center position
#col2 = bias force constant

umbrellas = np.loadtxt("../gromacs/wham_input.txt", skiprows=1)
centers = umbrellas[:, 1]
force_constants = umbrellas[:, 2]

biasses = create_biasses(centers, force_constants, microstates)
np.save("NFP_membrane_biasses.npy", biasses)

, where the input file simply contains the centers and force constants of the harmonic potentials. But when I try to use run_dhamedI cannot seem to get sensible results. When I use jit_gradient=False, the calculation finished but I do not get a sensible result (see figure).

When I use jit_gradient=True, I get a division by zero error at '_loop_grad_dhamed_likelihood_0'. Would you have an idea of what is going wrong?

Best,
Warre

*Enable users to run binless WHAM in the same framework as DHAMed.

Hi,
I wanted to make sure that I understand the definition of the bias potential matrix correctly.
Assuming an umbrella sampling experiment with 4 windows A, B, C, D and 3 states 0, 1, 2. The restraining potential defined as k*(x-x0)^2. Should the cell A0 contain the following?
x=median value of bin 0,
x0=target value of window A

• Implement uncertainty estimation
• Benchmark for model system

Use Travis CI to run tests automatically :-)

To do:

1. Calculate rates trajectories where dynamics effectively evolve with the "true" dynamics (E.g., sets of short trajectories).
2. Calculate rates from biased dynamics (e.g., umbrella sampling)...

Add GLIC ion-permeation channel example Jupyter.

Dear Lukas,
thanks a lot for providing the software to DHAMed.
I am trying to use the program with the following test data:

traj=np.array([0., 0., 1., 2., 1., 0., 2., 2.])
c_l = [count_matrix(traj,n_states=3)]
v_ar=np.array([1, 1.5, 2]).reshape(3,1)

I get the following error:

File "dhamed.py", line 17, in
bl_g = run_dhamed(c_l, -np.log(v_ar))
....
....
InternalError: unsupported array index type float64 in [float64]
[1] During: typing of intrinsic-call at /home/andt88/miniconda2/lib/python2.7/site-packages/pydhamed/optimize_dhamed.py (21)
--%<-----------------------------------------------------------------

File "../../../../miniconda2/lib/python2.7/site-packages/pydhamed/optimize_dhamed.py", line 21

I have performed an Umbrella Sampling analysis on a membrane system in gromacs. My collective variable is the distance of a small molecule from the center of a membrane. Using the pullf file generated from gromacs how would I go about generating the bias force matrix for each of my 80 US windows?

• Transition counts and bias potentials of states not properly connect to the other states need to be excluded in a consistent fashion.
• Will be important for DHAMed calculations for complex systems.