def D(self, h_and_edges):
h, edges = h_and_edges
d = density.Density(h,
edges,
parameters={'isDensity': False},
units={'length': 'A'})
d.make_density()
return d
def check_density_from_Universe(self, atomselection, ref_meandensity,
universe, tmpdir, **kwargs):
with tmpdir.as_cwd():
D = density.density_from_Universe(universe,
select=atomselection,
delta=self.delta,
**kwargs)
assert_almost_equal(D.grid.mean(),
ref_meandensity,
err_msg="mean density does not match")
D.export(self.outfile)
D2 = density.Density(self.outfile)
assert_almost_equal(
D.grid,
D2.grid,
decimal=self.precision,
err_msg="DX export failed: different grid sizes")
def _conclude(self):
self._grid = self._results[:].sum(axis=0)
self._grid /= float(self.n_frames)
metadata = self._metadata if self._metadata is not None else {}
metadata['psf'] = self._atomgroup.universe.filename
metadata['dcd'] = self._trajectory.filename
metadata['atomselection'] = self._atomselection
metadata['n_frames'] = self.n_frames
metadata['totaltime'] = self._atomgroup.universe.trajectory.totaltime
metadata['dt'] = self._trajectory.dt
metadata['time_unit'] = "ps"
parameters = self._parameters if self._parameters is not None else {}
parameters['isDensity'] = False # must override
density = serial_density.Density(
grid=self._grid, edges=self._edges,
units={'length': "Angstrom"},
parameters=parameters,
metadata=metadata)
density.make_density()
self.density = density
def check_DensityAnalysis(self,
ag,
ref_meandensity,
tmpdir,
runargs=None,
**kwargs):
runargs = runargs if runargs else {}
with tmpdir.as_cwd():
D = density.DensityAnalysis(ag, delta=self.delta,
**kwargs).run(**runargs)
assert_almost_equal(D.density.grid.mean(),
ref_meandensity,
err_msg="mean density does not match")
D.density.export(self.outfile)
D2 = density.Density(self.outfile)
assert_almost_equal(
D.density.grid,
D2.grid,
decimal=self.precision,
err_msg="DX export failed: different grid sizes")
#add up slices
#make sure you can graph density over z so you can look at it.
u=mda.Universe(SPH,topology_format='PDB')
interp_values=np.zeros(len(u.atoms))
cylinder_height=np.abs(u.atoms.positions[0][2]-u.atoms.positions[1][2])
spacing=0.2
stride=np.int(np.round(spacing/cylinder_height))
stride=1
cylinder_height=stride*cylinder_height
stride_pos=u.atoms.positions[0:-1:stride]
stride_rad=u.atoms.tempfactors[0:-1:stride]
big_sample=np.zeros(len(stride_pos))
x=de.Density(DX)
y=(x.centers())
for i in range(len(u.atoms)):
pos=u.atoms.positions[i]
rad=u.atoms.tempfactors[i]
interp_values[i]=(x.interpolated(pos[0],pos[1],pos[2]))
for i in range(len(stride_pos)):
pos=stride_pos[i]
rad=stride_rad[i]
grid_sample_values=np.zeros(num_sample_points)