def test_velocity_traj():
# Test Trajectory.get_velocity() against velocities output from CP2K. The
# agreement is very good. Works only for fixed-cell MDs, however!
dr = 'files/cp2k/md/nvt_print_low'
base = os.path.dirname(dr)
fn = '%s/cp2k.out' %dr
print common.backtick('tar -C {0} -xzf {1}.tgz'.format(base,dr))
tr = io.read_cp2k_md(fn)
# read from data file
v1 = tr.velocity.copy()
# If tr.velocity != None, then get_velocity() doesn't calculate it. Then,
# it simply returns tr.velocity, which is what we of course usually want.
tr.velocity = None
# calculate from coords + time step, b/c of central diffs, only steps 1:-1
# are the same
v2 = tr.get_velocity()
print ">>>> np.abs(v1).max()", np.abs(v1).max()
print ">>>> np.abs(v1).min()", np.abs(v1).min()
print ">>>> np.abs(v2).max()", np.abs(v2).max()
print ">>>> np.abs(v2).min()", np.abs(v2).min()
print ">>>> np.abs(v1-v2).max()", np.abs(v1-v2).max()
print ">>>> np.abs(v1-v2).min()", np.abs(v1-v2).min()
assert np.allclose(v1[1:-1,...], v2[1:-1,...], atol=1e-4)
##from pwtools import mpl
##fig,ax = mpl.fig_ax()
##ax.plot(v1[1:-1,:,0], 'b')
##ax.plot(v2[1:-1,:,0], 'r')
##mpl.plt.show()
shape = (100,10,3)
arr = np.random.rand(*shape)
assert crys.velocity_traj(arr, axis=0).shape == shape
assert crys.velocity_traj(arr, axis=0, endpoints=False).shape == (98,10,3)
def test_velocity_traj():
# Test Trajectory.get_velocity() against velocities output from CP2K. The
# agreement is very good. Works only for fixed-cell MDs, however!
dr = 'files/cp2k/md/nvt_print_low'
base = os.path.dirname(dr)
fn = '%s/cp2k.out' %dr
print(common.backtick('tar -C {0} -xzf {1}.tgz'.format(base,dr)))
tr = io.read_cp2k_md(fn)
# read from data file
v1 = tr.velocity.copy()
# If tr.velocity != None, then get_velocity() doesn't calculate it. Then,
# it simply returns tr.velocity, which is what we of course usually want.
tr.velocity = None
# calculate from coords + time step, b/c of central diffs, only steps 1:-1
# are the same
v2 = tr.get_velocity()
print(">>>> np.abs(v1).max()", np.abs(v1).max())
print(">>>> np.abs(v1).min()", np.abs(v1).min())
print(">>>> np.abs(v2).max()", np.abs(v2).max())
print(">>>> np.abs(v2).min()", np.abs(v2).min())
print(">>>> np.abs(v1-v2).max()", np.abs(v1-v2).max())
print(">>>> np.abs(v1-v2).min()", np.abs(v1-v2).min())
assert np.allclose(v1[1:-1,...], v2[1:-1,...], atol=1e-4)
##from pwtools import mpl
##fig,ax = mpl.fig_ax()
##ax.plot(v1[1:-1,:,0], 'b')
##ax.plot(v2[1:-1,:,0], 'r')
##mpl.plt.show()
shape = (100,10,3)
arr = np.random.rand(*shape)
assert crys.velocity_traj(arr, axis=0).shape == shape
assert crys.velocity_traj(arr, axis=0, endpoints=False).shape == (98,10,3)
def pdos(coords_arr_3d, axis=0):
f, d = pd.direct_pdos(velocity_traj(coords_arr_3d, axis=axis))
return d
# Use most settings (nfreq, ...) from above. Create random array of x,y,z time
# traces for `natoms` atoms. Each x,y,z trajectory is a sum of sin's (`coords`
# in the 1d case).
natoms = 5
coords = np.empty((nstep, natoms, 3))
# `nfreq` frequencies for each x,y,z component of each atom
freqs = rand(natoms, 3, nfreq) * fmax
for i in range(natoms):
for k in range(3):
# vector w/ frequencies: freqs[i,k,:] <=> f_j, j=0, ..., nfreq-1
# sum_j sin(2*pi*f_j*t)
coords[:, i, k] = np.sin(2 * pi * freqs[i, k, :][:, None] *
taxis).sum(axis=0)
##arr = coords
arr = crys.velocity_traj(coords)
massvec = rand(natoms)
# no mass weighting
M = None
f4, y4n = pydos.vacf_pdos(arr, dt=dt, m=M, mirr=True)
f5, y5n = pydos.direct_pdos(arr, dt=dt, m=M)
# with mass weighting
M = massvec
f6, y6nm = pydos.vacf_pdos(arr, dt=dt, m=M, mirr=True)
f7, y7nm = pydos.direct_pdos(arr, dt=dt, m=M)
if use_fourier:
# For each atom, write an array (time.shape[0], 3) with coords at all time
# steps, run fourier.x on that, sum up the power spectra. No mass
def pdos(coords_arr_3d, axis=0):
f, d = pd.direct_pdos(velocity_traj(coords_arr_3d, axis=axis))
return d
# Use most settings (nfreq, ...) from above. Create random array of x,y,z time
# traces for `natoms` atoms. Each x,y,z trajectory is a sum of sin's (`coords`
# in the 1d case).
natoms = 5
coords = np.empty((nstep, natoms, 3))
# `nfreq` frequencies for each x,y,z component of each atom
freqs = rand(natoms, 3, nfreq)*fmax
for i in range(natoms):
for k in range(3):
# vector w/ frequencies: freqs[i,k,:] <=> f_j, j=0, ..., nfreq-1
# sum_j sin(2*pi*f_j*t)
coords[:,i,k] = np.sin(2*pi*freqs[i,k,:][:,None]*taxis).sum(axis=0)
##arr = coords
arr = crys.velocity_traj(coords)
massvec = rand(natoms)
# no mass weighting
M = None
f4, y4n = pydos.vacf_pdos(arr, dt=dt, m=M, mirr=True)
f5, y5n = pydos.direct_pdos(arr, dt=dt, m=M)
# with mass weighting
M = massvec
f6, y6nm = pydos.vacf_pdos(arr, dt=dt, m=M, mirr=True)
f7, y7nm = pydos.direct_pdos(arr, dt=dt, m=M)
if use_fourier:
# For each atom, write an array (time.shape[0], 3) with coords at all time
# steps, run fourier.x on that, sum up the power spectra. No mass