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How to use nanosecond method in freezegun

Best Python code snippet using freezegun

datetime_helpers.py

Source:datetime_helpers.py

...99            # if neither ms or ns were provided, passthru previous nanos.100            inst._nanosecond = prev_nanos101        return inst102    @property103    def nanosecond(self):104        """Read-only: nanosecond precision."""105        return self._nanosecond or self.microsecond * 1000106    def rfc3339(self):107        """Return an RFC3339-compliant timestamp.108        Returns:109            (str): Timestamp string according to RFC3339 spec.110        """111        if self._nanosecond == 0:112            return _to_rfc3339(self)113        nanos = str(self._nanosecond).rjust(9, "0").rstrip("0")114        return "{}.{}Z".format(self.strftime(_RFC3339_NO_FRACTION), nanos)115    @classmethod116    def from_rfc3339(cls, stamp):117        """Parse RFC3339-compliant timestamp, preserving nanoseconds....

plot_msd.py

Source:plot_msd.py

1import numpy as np2import h5py3from yaff import System, Cell4import matplotlib.pyplot as pt5from molmod.units import picosecond, angstrom, nanosecond6frac_coords_pores = np.array([[0.0,0.0,0.0],[0.5,0.5,0.5]])7n_framework_atoms = 2768with h5py.File('msd_long.h5', 'r') as f:9    loc_molecule = np.array(f['loc_molecules'])10    pos_molecule = np.array(f['pos_molecules'])11    time = np.array(f['time'])12for i in range(pos_molecule.shape[1]):13    pos_molecule[:,i,:] -= pos_molecule[0,i,:]14n_molecules = pos_molecule.shape[1]15msd_all = np.zeros((pos_molecule.shape[0], pos_molecule.shape[1]))16print(pos_molecule.shape)17for t in range(pos_molecule.shape[0]):18    dt = t+119    # Run over every molecule20    for j in range(pos_molecule.shape[1]):21        msd_tot = 022        counter = 023        # Run over every time interval24        for i in range(len(time)//dt):25            msd_tot += ((pos_molecule[(i+1)*dt-1,j,:] - pos_molecule[i*dt,j,:])**2).sum()26            counter += 127        msd_all[t,j] = msd_tot/counter28pt.clf()29pt.xlabel('Simulation time [ns]')30pt.ylabel('Mean squared displacement [\AA$^2$]')31pt.plot(time/nanosecond,(pos_molecule**2).sum(axis=1).sum(axis=1)/n_molecules/(angstrom**2), '0.5',label='total')32pt.plot(time/nanosecond,(pos_molecule[:,:,0]**2).sum(axis=1)/n_molecules/(angstrom**2), '#ef6548', label='x component')33pt.plot(time/nanosecond,(pos_molecule[:,:,1]**2).sum(axis=1)/n_molecules/(angstrom**2), '#41ab5d', label='y component')34pt.plot(time/nanosecond,(pos_molecule[:,:,2]**2).sum(axis=1)/n_molecules/(angstrom**2), '#3690c0', label='z component')35pt.plot(time[:len(time)/2]/nanosecond,msd_all[:len(time)/2,:].sum(axis=1)/n_molecules/(angstrom**2), 'k', label='multiple origin')36legend = pt.legend(loc='upper left',fancybox=True)37pt.xlim([0,5])38pt.tight_layout()39pt.savefig('ZIF8_diff_H2O_long.svg', format='svg', bbox_inches = 'tight')40pt.savefig('ZIF8_diff_H2O_long.png', bbox_inches = 'tight')41pt.clf()42pt.xlabel('Simulation time [ns]')43pt.ylabel('Diffusion coefficient [\AA$^2$/nanosecond]')44pt.plot(time[1000:]/nanosecond,(pos_molecule[1000:,:,:]**2).sum(axis=1).sum(axis=1)/(6*time[1000:])/n_molecules/(angstrom**2/nanosecond), '0.5',label='total')45pt.plot(time[1000:]/nanosecond,(pos_molecule[1000:,:,0]**2).sum(axis=1)/(6*time[1000:])/n_molecules/(angstrom**2/nanosecond), '#ef6548', label='x component')46pt.plot(time[1000:]/nanosecond,(pos_molecule[1000:,:,1]**2).sum(axis=1)/(6*time[1000:])/n_molecules/(angstrom**2/nanosecond), '#41ab5d', label='y component')47pt.plot(time[1000:]/nanosecond,(pos_molecule[1000:,:,2]**2).sum(axis=1)/(6*time[1000:])/n_molecules/(angstrom**2/nanosecond), '#3690c0', label='z component')48pt.plot(time[1000:len(time)/2]/nanosecond,(msd_all[1000:len(time)/2,:]).sum(axis=1)/n_molecules/(6*time[1000:len(time)/2])/(angstrom**2/nanosecond), 'k', label='multiple origin')49legend = pt.legend(loc='upper right',fancybox=True)50pt.xlim([0,5])51pt.tight_layout()52pt.savefig('ZIF8_D_H2O_long.svg', format='svg', bbox_inches = 'tight')...

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