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from signac_dashboard import Dashboard
from signac_dashboard.modules import StatepointList, ImageViewer, VideoViewer
from signac_dashboard.modules import Notes


class PlotDashboard(Dashboard):
    def job_sorter(self, job):
        return [job.sp.pressure, job.sp.kT]

    def job_title(self, job):

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# how to wrap a single coordinate
x_wrapped = (x - box.mins[0]) % box.lenghts[0] + box.mins[0]

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def rotacf(x, y, funlen, dstart=2):
    """Calculate the autocorrelation of a function
    Params
    ------
    forces : np.ndarray, shape=(n,)
        The force timeseries acting on a molecules
    timestep : float
        Simulation timestep in fs
    funlen : int
        The desired length of the correlation function

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system = hoomd.deprecated.init.create_random_polymers(
    box=hoomd.data.boxdim(L=60),
    polymers=[polymer1],
    separation=dict(A=0.25, B=0.25), seed=52)
charges = {'A': -1, 'B': 1}
for p in system.particles:
    p.charge = charges[p.type]

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# import curve fit
from scipy.optimize import curve_fit

# this is the function you want to fit to
def gauss(r, *p):
    A, sigma, r0 = p
    return A / (sigma * (np.pi/2)**0.5) * np.exp(-2*(r - r0)**2/sigma**2)
  
# p0 = initial guesstes
p0 = (np.amax(hist), (bins[-1]-bins[0])/2, bins[np.argmax(hist)])

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from numpy import pi
import mbuild as mb

cer2 = mb.load('cer2.pdb')
grid = mb.pattern.Grid2DPattern(50, 50)
leaflet, system = mb.Compound(), mb.Compound()
repeat_spacing = 6  # repeat spacing in nm
leaflet = grid.apply(cer2)  # put lipids on gird points
leaflet = mb.Compound(leaflet)
for layer_num in range(4):  # add 4 leaflets to the system