def setup(self):
self.q_values = np.array([1.0, 2.0])
self.num_phi = 360
self.traj = Trajectory.load(ref_file('ala2.pdb'))
self.num_shots = 4
self.rings = xray.Rings.simulate(self.traj, 1, self.q_values,
self.num_phi, self.num_shots) # 1 molec
def setup(self):
self.q_values = np.array([1.0, 2.0])
self.num_phi = 360
self.traj = Trajectory.load(ref_file('ala2.pdb'))
self.num_shots = 2
# generate the tables file on disk, then re-open it
intensities = np.abs( np.random.randn(self.num_shots, len(self.q_values),
self.num_phi) / 100.0 + \
np.cos( np.linspace(0.0, 4.0*np.pi, self.num_phi) ) )
if os.path.exists('tmp_tables.h5'):
os.remove('tmp_tables.h5')
hdf = tables.File('tmp_tables.h5', 'w')
a = tables.Atom.from_dtype(np.dtype(np.float64))
node = hdf.create_earray(where='/', name='data',
shape=(0, len(self.q_values), self.num_phi),
atom=a, filters=io.COMPRESSION)
node.append(intensities)
hdf.close()
self.tables_file = tables.File('tmp_tables.h5', 'r+')
pi = self.tables_file.root.data
pm = np.random.binomial(1, 0.9, size=(len(self.q_values), self.num_phi))
k = 1.0
self.rings = xray.Rings(self.q_values, pi, k, pm)
return
def setup(self):
self.q_values = np.array([1.0, 2.0])
self.num_phi = 360
self.l = 50.0
self.d = xray.Detector.generic(spacing=0.4, l=self.l)
self.num_shots = 2
self.i = np.abs( np.random.randn(self.num_shots, self.d.num_pixels) )
self.t = Trajectory.load(ref_file('ala2.pdb'))
self.shot = xray.Shotset(self.i, self.d)
def test_sph_harm():
# -----------------------
traj = Trajectory.load(ref_file('pentagon.pdb'))
q_magnitudes = [1.6]
num_coefficients = 44
num_molecules = 1
num_shots = 20000
num_phi = 2048
# -----------------------
q = q_magnitudes[0]
# compute the Kam-theoretic values of the Legendre coefficients C_ell, which
# we will call "coeffsh"
coeffsh_even = scatter.sph_harm_coefficients(traj, q_magnitudes,
num_coefficients=num_coefficients/2)
coeffsh_even = np.nan_to_num(coeffsh_even)
coeffsh_even /= coeffsh_even[1]
coeffsh = np.zeros(num_coefficients)
coeffsh[0::2] = coeffsh_even.flatten()
# next, preform a simulation of the scattering and empirically compute the
# correlation function
rings = xray.Rings.simulate(traj, num_molecules, q_magnitudes,
num_phi, num_shots)
c = rings.correlate_intra(q, q, mean_only=True)
# it seems best to compare the solutions in the expanded basis
c_sh = np.polynomial.legendre.legval(rings.cospsi(q, q), coeffsh.flatten())
c = c - c.mean()
c_sh = c_sh - c_sh.mean()
# plt.figure()
# plt.plot(c_sh / c_sh[0])
# plt.plot(c / c[0])
# plt.show()
# if these are more than 10% different, fail the test
error = (np.sum(np.abs( (c_sh / c_sh[0]) - (c / c[0]) )) / float(num_phi))
assert error < 0.1, 'simulation and analytical computation >10%% different (%f %%)' % error
return
def test_py_cpu_smoke(self):
traj = Trajectory.load(ref_file('ala2.pdb'))
num_molecules = 1
detector = xray.Detector.generic()
detector.beam.photons_scattered_per_shot = 1e3
I = scatter.simulate_shot(traj, num_molecules, detector,
finite_photon=True)
# simple statistical sanity check
assert np.abs(I.sum() - detector.beam.photons_scattered_per_shot) < \
np.sqrt(detector.beam.photons_scattered_per_shot)*6.0
def test_python_call(self):
"""
Test the GPU scattering simulation interface (scatter.simulate)
"""
if not GPU: raise SkipTest
print "testing python wrapper fxn..."
traj = Trajectory.load(ref_file('ala2.pdb'))
num_molecules = 512
detector = xray.Detector.generic()
py_I = scatter.simulate_shot(traj, num_molecules, detector)
assert not np.all( py_I == 0.0 )
assert not np.isnan(np.sum( py_I ))
def setup(self):
self.q_values = np.array([1.0, 2.0])
self.num_phi = 360
self.l = 50.0
self.d = xray.Detector.generic(spacing=0.4, l=self.l)
self.t = Trajectory.load(ref_file('ala2.pdb'))
self.num_shots = 2
intensities = np.abs(np.random.randn(self.num_shots, self.d.num_pixels))
io.saveh('tmp_tables.h5', data=intensities)
self.tables_file = tables.File('tmp_tables.h5')
self.i = self.tables_file.root.data
self.shot = xray.Shotset(self.i, self.d)
return
def test_no_hydrogens():
traj = Trajectory.load(ref_file('ala2.pdb'))
num_molecules = 1
detector = xray.Detector.generic()
detector.beam.photons_scattered_per_shot = 1e3
I_noH = scatter.simulate_shot(traj, num_molecules, detector,
ignore_hydrogens=True,
dont_rotate=True)
I_wH = scatter.simulate_shot(traj, num_molecules, detector,
ignore_hydrogens=False,
dont_rotate=True)
assert not np.all(I_noH == I_wH)
# compute the differece -- we're not setting random numbers here so just
# looking at radially averaged stuff...
diff = np.sum(np.abs(I_noH - I_wH) / I_wH) / float(len(I_wH))
print diff
assert diff < 1.0, 'ignoring hydrogens makes too big of a difference...'
#!/usr/bin/env python
import mdtraj
from mdtraj import Trajectory as t
import os
# combine trajectories
trjs = [f for f in os.listdir('.') if 'trj' in f]
ts = {}
tn = []
for i in trjs:
num = i.split('.')[0].split('j')[-1]
tn.append(num)
ts[i] = t.load('./trj%i.h5' % int(num))
tn.sort()
z = ts['trj0.h5']
for i in tn:
z = z.join(ts['trj%s.h5' % i])
# trim data to have a frame every 1 ns
frames = []
for i in range(len(z)):
if i % 10 == 0:
frames.append(i)
zp = z.slice(frames)
# save combined data
zp.save_pdb('ns.pdb')
parser.add_argument('--pro', action='store_true', help='write trj of protein only', default=False)
parser.add_argument('--sr', type=str, help='script root', default='/home/kmckiern/scripts/')
args = parser.parse_args()
sr = args.sr
sys.path.insert(0, sr + 'py_general/')
from toolz import natural_sort
ext_i = '.' + args.trj_ext
td = args.trj_dir
# combine trajectories
trjs = [f for f in os.listdir(td) if ext_i in f]
trjs = natural_sort(trjs)
ts = t.load(trjs[0], top=args.top, stride=args.stride1)
if args.vs:
# i'm going to pad these residues by 8
arg = ts.top.select('resid 23 to 39')
lysglu = ts.top.select('resid 118 to 135')
lys = ts.top.select('resid 308 to 324')
vs = np.concatenate([arg, lysglu, lys])
ts = ts.atom_slice(vs)
try:
ts[0].save_pdb('/home/kmckiern/clc/analysis/vs_dihed/pro/vs_ref.pdb')
except:
print 'usual protonation error, probably'
nt = len(trjs)
for ndx, i in enumerate(trjs[1:]):
# for newest trj, cut end just in case write is incomplete
if ndx + 1 == nt:
