def test_vs_reference(self):
qs = np.arange(2, 3.52, 0.02)
silver = structure.load_coor(ref_file('SilverSphere.coor'))
cl = scatter.sph_hrm_coefficients(silver, q_magnitudes=qs,
num_coefficients=2)[1,:,:]
ref = np.loadtxt(ref_file('ag_kam.dat')) # computed in matlab
assert_allclose(cl, ref)
def test_fromfiles(self):
ss = xray.Shotset.fromfiles( [ref_file('test_cbf.cbf'),
ref_file('test_cbf2.cbf')] )
assert ss.num_shots == 2
n = 0
for i in ss.intensities:
n += 1
assert ss.num_shots == n
def test_reporter():
# stolen/modified from MDTraj/tests/test_reporter.py ... thanks rmcgibbo
tempdir = os.path.join(testdir, 'test_reporter')
os.makedirs(tempdir)
pdb = PDBFile( ref_file('ala2.pdb') )
forcefield = ForceField('amber99sbildn.xml', 'amber99_obc.xml')
system = forcefield.createSystem(pdb.topology,
nonbondedMethod=CutoffNonPeriodic,
nonbondedCutoff=1.0*nanometers,
constraints=HBonds,
rigidWater=True)
integrator = LangevinIntegrator(300*kelvin, 1.0/picoseconds, 2.0*femtoseconds)
integrator.setConstraintTolerance(0.00001)
platform = Platform.getPlatformByName('Reference')
simulation = Simulation(pdb.topology, system, integrator, platform)
simulation.context.setPositions(pdb.positions)
simulation.context.setVelocitiesToTemperature(300*kelvin)
reffile = os.path.join(tempdir, 'traj.h5')
testfile = os.path.join(tempdir, 'traj-test.h5')
ref_reporter = HDF5Reporter(reffile, 2, coordinates=True, time=True,
cell=True, potentialEnergy=True, kineticEnergy=True, temperature=True,
velocities=True)
test_reporter = sample.MCReporter(testfile, 2, coordinates=True, time=True,
cell=True, potentialEnergy=True, kineticEnergy=True, temperature=True,
velocities=True)
simulation.reporters.append(ref_reporter)
simulation.reporters.append(test_reporter)
simulation.step(100)
ref_reporter.close()
test_reporter.close()
with HDF5TrajectoryFile(testfile) as f:
got = f.read()
yield lambda: eq(got.temperature.shape, (50,))
yield lambda: eq(got.potentialEnergy.shape, (50,))
yield lambda: eq(got.kineticEnergy.shape, (50,))
yield lambda: eq(got.coordinates.shape, (50, 22, 3))
yield lambda: eq(got.velocities.shape, (50, 22, 3))
yield lambda: eq(got.time, 0.002*2*(1+np.arange(50)))
yield lambda: f.topology == mdtraj.load(ref_file('ala2.pdb')).top
ref_traj = mdtraj.load(reffile)
test_traj = mdtraj.load(testfile)
yield lambda: eq(ref_traj.xyz, test_traj.xyz)
yield lambda: eq(ref_traj.unitcell_vectors, test_traj.unitcell_vectors)
yield lambda: eq(ref_traj.time, test_traj.time)
yield lambda: eq(ref_traj.xyz, test_traj.xyz)
yield lambda: eq(ref_traj.unitcell_vectors, test_traj.unitcell_vectors)
def test_fromfiles(self):
ss = xray.Shotset.fromfiles(
[ref_file('test_cbf.cbf'),
ref_file('test_cbf2.cbf')])
assert ss.num_shots == 2
n = 0
for i in ss.intensities:
n += 1
assert ss.num_shots == n
def setup(self):
if not HAVE_OPENMM: return
self.potential = potential.FlatPotential()
self.prior = 'amber99sbildn.xml'
self.pdb = mdtraj.load(ref_file('ala2.pdb'))
self.topology = PDBFile(ref_file('ala2.pdb')).topology # NEED TO CHANGE LATER
self.starting_positions = self.pdb.xyz[0]
self.mdmc = sample.MDMC(self.potential, self.prior,
self.topology, self.starting_positions,
openmm_platform='Reference', platform_properties={},
steps_per_iter=10)
def setup(self):
self.nq = 2 # number of detector vectors to do
xyzQ = np.loadtxt(ref_file('512_atom_benchmark.xyz'))
self.xyzlist = xyzQ[:, :3] * 10.0 # nm -> ang.
self.atomic_numbers = xyzQ[:, 3].flatten()
self.q_grid = np.loadtxt(ref_file('512_q.xyz'))[:self.nq]
self.rfloats = np.loadtxt(ref_file('512_x_3_random_floats.txt'))
self.num_molecules = self.rfloats.shape[0]
def setup(self):
self.nq = 2 # number of detector vectors to do
xyzQ = np.loadtxt(ref_file('512_atom_benchmark.xyz'))
self.xyzlist = xyzQ[:,:3] * 10.0 # nm -> ang.
self.atomic_numbers = xyzQ[:,3].flatten()
self.q_grid = np.loadtxt(ref_file('512_q.xyz'))[:self.nq]
self.rfloats = np.loadtxt(ref_file('512_x_3_random_floats.txt'))
self.num_molecules = self.rfloats.shape[0]
def setup(self):
if not HAVE_OPENMM: return
self.potential = potential.FlatPotential()
self.prior = 'amber99sbildn.xml'
self.pdb = mdtraj.load(ref_file('ala2.pdb'))
self.topology = PDBFile(
ref_file('ala2.pdb')).topology # NEED TO CHANGE LATER
self.starting_positions = self.pdb.xyz[0]
self.mdmc = sample.MDMC(self.potential,
self.prior,
self.topology,
self.starting_positions,
openmm_platform='Reference',
platform_properties={},
steps_per_iter=10)
def test_intensity_profile(self):
q_values = [2.4, 2.67, 3.0] # should be a peak at |q|=2.67
t = structure.load_coor(ref_file('gold1k.coor'))
rings = xray.Rings.simulate(t, 10, q_values, self.num_phi, 1) # 3 molec, 1 shots
ip = rings.intensity_profile()
assert ip[1,1] > ip[0,1]
assert ip[1,1] > ip[2,1]
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
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.createEArray(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 test_to_rings(self):
t = structure.load_coor(ref_file('gold1k.coor'))
shot = xray.Shotset.simulate(t, self.d, 1, 2)
shot_ip = shot.intensity_profile(0.1)
q_values = shot_ip[:, 0]
rings = shot.to_rings(q_values)
assert rings.num_shots == shot.num_shots
rings_ip = rings.intensity_profile()
# normalize to the 6th entry, and discard values before that
# which are usually just large + uninformative
rings_ip[:, 1] /= rings_ip[5, 1]
shot_ip[:, 1] /= shot_ip[5, 1]
# for some reason assert_allclose not working, but this is
x = np.sum(np.abs(rings_ip[5:, 1] - shot_ip[5:, 1]))
x /= float(len(rings_ip[5:, 1]))
print x
assert x < 0.2 # intensity mismatch
assert_allclose(rings_ip[:, 0],
shot_ip[:, 0],
err_msg='test impl error')
def test_i_profile(self):
# doubles as a test for intensity_maxima()
t = structure.load_coor(ref_file('gold1k.coor'))
s = xray.Shotset.simulate(t, self.d, 5, 1)
p = s.intensity_profile()
m = s.intensity_maxima()
assert np.any(np.abs(p[m,0] - 2.67) < 1e-1) # |q| = 2.67 is in {maxima}
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.i = np.abs(np.random.randn(self.d.num_pixels))
self.t = trajectory.load(ref_file('ala2.pdb'))
self.shot = xray.Shotset(self.i, self.d)
def test_rm_com():
t = trajectory.load( ref_file('ala2.pdb') )
r = structure.remove_COM(t)
masses = [ a.element.mass for a in t.topology.atoms() ]
for i in range(t.n_frames):
assert_array_almost_equal(np.zeros(3), np.average(t.xyz[i,:,:], weights=masses, axis=0))
def test_multi_panel_interp(self):
# regression test ensuring detectors w/multiple basisgrid panels
# are handled correctly
t = structure.load_coor(ref_file('gold1k.coor'))
q_values = np.array([2.66])
multi_d = xray.Detector.load(ref_file('lcls_test.dtc'))
num_phi = 1080
num_molecules = 1
xyzlist = t.xyz[0, :, :] * 10.0 # convert nm -> ang. / first snapshot
atomic_numbers = np.array(
[a.element.atomic_number for a in t.topology.atoms])
# generate a set of random numbers that we can use to make sure the
# two simulations have the same molecular orientation (and therefore)
# output
rfloats = np.random.rand(num_molecules, 3)
# --- first, scatter onto a perfect ring
q_grid = xray.xray._q_grid_as_xyz(q_values, num_phi, multi_d.k)
ring_i = _cpuscatter.simulate(num_molecules,
q_grid,
xyzlist,
atomic_numbers,
rfloats=rfloats)
perf = xray.Rings(q_values, ring_i[None, None, :], multi_d.k)
# --- next, to the full detector
q_grid2 = multi_d.reciprocal
real_i = _cpuscatter.simulate(num_molecules,
q_grid2,
xyzlist,
atomic_numbers,
rfloats=rfloats)
# interpolate
ss = xray.Shotset(real_i, multi_d)
real = ss.to_rings(q_values, num_phi)
# count the number of points that differ significantly between the two
diff = ( np.abs((perf.polar_intensities[0,0,:] - real.polar_intensities[0,0,:]) \
/ (real.polar_intensities[0,0,:] + 1e-300) ) > 1e-3)
print np.sum(diff)
assert np.sum(diff) < 300
def test_rm_com():
t = trajectory.load( ref_file('ala2.pdb') )
r = structure.remove_COM(t)
masses = [ a.element.mass for a in t.topology.atoms() ]
for i in range(t.n_frames):
assert_array_almost_equal(np.zeros(3), np.average(t.xyz[i,:,:], weights=masses, axis=0))
def test_i_profile(self):
# doubles as a test for intensity_maxima()
t = structure.load_coor(ref_file('gold1k.coor'))
s = xray.Shotset.simulate(t, self.d, 5, 1)
p = s.intensity_profile()
m = s.intensity_maxima()
assert np.any(
np.abs(p[m, 0] - 2.67) < 1e-1) # |q| = 2.67 is in {maxima}
def test_intensity_profile(self):
q_values = [2.4, 2.67, 3.0] # should be a peak at |q|=2.67
t = structure.load_coor(ref_file('gold1k.coor'))
rings = xray.Rings.simulate(t, 10, q_values, self.num_phi,
1) # 3 molec, 1 shots
ip = rings.intensity_profile()
assert ip[1, 1] > ip[0, 1]
assert ip[1, 1] > ip[2, 1]
def test_python_call(self):
print "testing python wrapper fxn..."
traj = trajectory.load(ref_file('ala2.pdb'))
num_molecules = 512
detector = Detector.generic()
py_I = xray.simulate_shot(traj, num_molecules, detector, verbose=True)
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.i = np.abs( np.random.randn(self.d.num_pixels) )
self.t = trajectory.load(ref_file('ala2.pdb'))
self.shot = xray.Shotset(self.i, self.d)
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
self.rings = xray.Rings.simulate(self.traj, 1, self.q_values,
self.num_phi,
self.num_shots) # 1 molec
def test_plotiq():
if not MPL: raise SkipTest
if TRAVIS: raise SkipTest
cmd = 'plotiq -i %s -m 1.0 > /dev/null 2>&1' % ref_file('refshot.shot')
subprocess.check_call(cmd, shell=True)
if not os.path.exists('intensity_plot.pdf'):
raise RuntimeError('no output produced')
else:
os.remove('intensity_plot.pdf')
def test_cbf2shot():
if TRAVIS: raise SkipTest
cmd = 'cbf2shot -i %s -o test.shot > /dev/null 2>&1' % ref_file('test1.cbf')
subprocess.check_call(cmd, shell=True)
if not os.path.exists('test.shot'):
raise RuntimeError('no output produced')
else:
o = xray.Shotset.load('test.shot')
os.remove('test.shot')
def test_replicate():
if TRAVIS: raise SkipTest
cmd = 'replicate -i %s -n 10 -d 0.1 > /dev/null 2>&1' % ref_file('goldBenchMark.coor')
subprocess.check_call(cmd, shell=True)
if not os.path.exists('replicated.pdb'):
raise RuntimeError('no output produced')
else:
o = trajectory.load('replicated.pdb')
os.remove('replicated.pdb')
def test_plotcorr():
if not MPL: raise SkipTest
if TRAVIS: raise SkipTest
cmd = 'plotcorr -i %s > /dev/null 2>&1' % ref_file('refshot.shot')
subprocess.check_call(cmd, shell=True)
if not os.path.exists('correlation_plot.pdf'):
raise RuntimeError('no output produced')
else:
os.remove('correlation_plot.pdf')
def test_interpolate_to_polar(self):
# doubles as a test for _implicit_interpolation
q_values = np.array([2.0, 2.67, 3.7]) # should be a peak at |q|=2.67
t = structure.load_coor(ref_file('gold1k.coor'))
s = xray.Shotset.simulate(t, self.d, 3, 1)
pi, pm = s.interpolate_to_polar(q_values=q_values)
ip = np.sum(pi[0,:,:], axis=1)
assert ip[1] > ip[0]
assert ip[1] > ip[2]
def test_cbf2shot():
if TRAVIS: raise SkipTest
cmd = 'cbf2shot -i %s -o test.shot > /dev/null 2>&1' % ref_file('test_cbf.cbf')
subprocess.check_call(cmd, shell=True)
if not os.path.exists('test.shot'):
raise RuntimeError('no output produced')
else:
o = xray.Shotset.load('test.shot')
os.remove('test.shot')
def test_plotcorr():
if not MPL: raise SkipTest
if TRAVIS: raise SkipTest
cmd = 'plotcorr -i %s > /dev/null 2>&1' % ref_file('reference_shot.shot')
subprocess.check_call(cmd, shell=True)
if not os.path.exists('correlation_plot.pdf'):
raise RuntimeError('no output produced')
else:
os.remove('correlation_plot.pdf')
def test_interpolate_to_polar(self):
# doubles as a test for _implicit_interpolation
q_values = np.array([2.0, 2.67, 3.7]) # should be a peak at |q|=2.67
t = structure.load_coor(ref_file('gold1k.coor'))
s = xray.Shotset.simulate(t, self.d, 3, 1)
pi, pm = s.interpolate_to_polar(q_values=q_values)
ip = np.sum(pi[0, :, :], axis=1)
assert ip[1] > ip[0]
assert ip[1] > ip[2]
def test_solvate():
if not OPENMM: raise SkipTest
if TRAVIS: raise SkipTest
cmd = 'solvate -i %s > /dev/null 2>&1' % ref_file('ala2.pdb')
subprocess.check_call(cmd, shell=True)
if not os.path.exists('solvated.pdb'):
raise RuntimeError('no output produced')
else:
o = trajectory.load('solvated.pdb')
os.remove('solvated.pdb')
def test_solvate():
if not OPENMM: raise SkipTest
if TRAVIS: raise SkipTest
cmd = 'solvate -i %s > /dev/null 2>&1' % ref_file('ala2.pdb')
subprocess.check_call(cmd, shell=True)
if not os.path.exists('solvated.pdb'):
raise RuntimeError('no output produced')
else:
o = trajectory.load('solvated.pdb')
os.remove('solvated.pdb')
def setup(self):
self.t = trajectory.load( ref_file('ala2.pdb') )
# make a fake restraint array
self.restraint_array = np.zeros((2,4))
self.restraint_array[0,:] = np.array([0, 5, 1.0, 1])
self.restraint_array[1,:] = np.array([4, 10, 10.0, 0])
self.dr = exptdata.DistanceRestraint(self.restraint_array)
def setup(self):
self.t = trajectory.load(ref_file('ala2.pdb'))
# make a fake restraint array
self.restraint_array = np.zeros((2, 4))
self.restraint_array[0, :] = np.array([0, 5, 1.0, 1])
self.restraint_array[1, :] = np.array([4, 10, 10.0, 0])
self.dr = exptdata.DistanceRestraint(self.restraint_array)
def test_predictions(self):
ala2 = mdtraj.trajectory.load(ref_file('ala2.pdb'))
p = self.wep.predictions(ala2)
assert p.shape == (1,5)
#print 'pred0', self.expt1.predict(ala2)
#print 'prediction', p
def test_plotiq():
if not MPL: raise SkipTest
if TRAVIS: raise SkipTest
cmd = 'odin.xray.plotiq -i %s -m 1.0 > /dev/null 2>&1' % ref_file(
'reference_shot.shot')
subprocess.check_call(cmd, shell=True)
if not os.path.exists('intensity_plot.pdf'):
raise RuntimeError('no output produced')
else:
os.remove('intensity_plot.pdf')
def test_gpu_scatter(self):
print "testing c code..."
xyzQ = np.loadtxt(ref_file('512_atom_benchmark.xyz'))
xyzlist = xyzQ[:,:3]
atomic_numbers = xyzQ[:,3].flatten()
q_grid = np.loadtxt(ref_file('512_q.xyz'))[:self.nq]
rfloats = np.loadtxt(ref_file('512_x_3_random_floats.txt'))
num_molecules = rfloats.shape[0]
gpu_I = call_gpuscatter(xyzlist, atomic_numbers, num_molecules, q_grid, rfloats)
self.ref_I = ref_simulate_shot(xyzlist, atomic_numbers, num_molecules, q_grid, rfloats)
print "GPU", gpu_I
print "CPU", self.ref_I
assert_allclose(gpu_I, self.ref_I, rtol=1e-03,
err_msg='scatter: gpu/cpu reference mismatch')
def test_all_on_many_img(self):
image = imread(ref_file('chough-test2.png'))
CM = om.CircularHough(radii=np.arange(10, 40, 2))
maxima = CM(image, mode='all')
print "many circles:", maxima
# the reference was confirmed visually TJL 12.27.12, the last
# circle is, in fact, a false positive... (not sure how to fix it)
ref = [(20, 62, 272), (20, 63, 168), (20, 64, 64), (22, 59, 376),
(22, 60, 482), (26, 57, 691), (26, 58, 587), (26, 59, 589),
(30, 56, 795), (34, 52, 952)]
assert_allclose(maxima, ref)
def test_load_coor():
s = structure.load_coor( ref_file('goldBenchMark.coor') )
s.save('s.pdb')
t = trajectory.load('s.pdb')
assert_array_almost_equal(s.xyz, t.xyz, decimal=3)
for a in t.topology.atoms():
assert a.element.symbol == 'Au'
if os.path.exists('s.pdb'):
os.remove('s.pdb')
def test_all_on_many_img(self):
image = imread(ref_file('chough-test2.png'))
CM = om.CircularHough(radii=np.arange(10,40,2))
maxima = CM(image, mode='all')
print "many circles:", maxima
# the reference was confirmed visually TJL 12.27.12, the last
# circle is, in fact, a false positive... (not sure how to fix it)
ref = [(20, 62, 272), (20, 63, 168), (20, 64, 64), (22, 59, 376),
(22, 60, 482), (26, 57, 691), (26, 58, 587), (26, 59, 589),
(30, 56, 795), (34, 52, 952)]
assert_allclose(maxima, ref)
def test_load_coor():
s = structure.load_coor( ref_file('goldBenchMark.coor') )
s.save('s.pdb')
t = trajectory.load('s.pdb')
assert_array_almost_equal(s.xyz, t.xyz, decimal=3)
for a in t.topology.atoms():
assert a.element.symbol == 'Au'
if os.path.exists('s.pdb'):
os.remove('s.pdb')
def test_multi_panel_interp(self):
# regression test ensuring detectors w/multiple basisgrid panels
# are handled correctly
t = structure.load_coor(ref_file('gold1k.coor'))
q_values = np.array([2.66])
multi_d = xray.Detector.load(ref_file('lcls_test.dtc'))
num_phi = 1080
num_molecules = 1
xyzlist = t.xyz[0,:,:] * 10.0 # convert nm -> ang. / first snapshot
atomic_numbers = np.array([ a.element.atomic_number for a in t.topology.atoms ])
# generate a set of random numbers that we can use to make sure the
# two simulations have the same molecular orientation (and therefore)
# output
rfloats = np.random.rand(num_molecules, 3)
# --- first, scatter onto a perfect ring
q_grid = xray.xray._q_grid_as_xyz(q_values, num_phi, multi_d.k)
ring_i = _cpuscatter.simulate(num_molecules, q_grid, xyzlist,
atomic_numbers, rfloats=rfloats)
perf = xray.Rings(q_values, ring_i[None,None,:], multi_d.k)
# --- next, to the full detector
q_grid2 = multi_d.reciprocal
real_i = _cpuscatter.simulate(num_molecules, q_grid2, xyzlist,
atomic_numbers, rfloats=rfloats)
# interpolate
ss = xray.Shotset(real_i, multi_d)
real = ss.to_rings(q_values, num_phi)
# count the number of points that differ significantly between the two
diff = ( np.abs((perf.polar_intensities[0,0,:] - real.polar_intensities[0,0,:]) \
/ (real.polar_intensities[0,0,:] + 1e-300) ) > 1e-3)
print np.sum(diff)
assert np.sum(diff) < 300
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 setup(self):
restraint_array = np.zeros((2,4))
restraint_array[0,:] = np.array([0, 5, 1.0, 1])
restraint_array[1,:] = np.array([4, 10, 10.0, 0])
dr = exptdata.DistanceRestraint(restraint_array)
self.expts = [dr]
self.confs = mdtraj.load(ref_file('ala3_3frames.h5'))
self.meem = models.MaxEntEnsembleModel('IdealGas.xml', *self.expts)
self.meem._conformations = self.confs # NEED TO REPLACE
self.lambdas = np.ones(self.meem.num_measurements)
return
def setup(self):
restraint_array = np.zeros((2, 4))
restraint_array[0, :] = np.array([0, 5, 1.0, 1])
restraint_array[1, :] = np.array([4, 10, 10.0, 0])
dr = exptdata.DistanceRestraint(restraint_array)
self.expts = [dr]
self.confs = mdtraj.load(ref_file('ala3_3frames.h5'))
self.meem = models.MaxEntEnsembleModel('IdealGas.xml', *self.expts)
self.meem._conformations = self.confs # NEED TO REPLACE
self.lambdas = np.ones(self.meem.num_measurements)
return
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 test_to_rings_on_disk(self):
# this test uses the Rings `rings_filename` flag
t = structure.load_coor(ref_file('gold1k.coor'))
shot = xray.Shotset.simulate(t, self.d, 1, 1)
q_values = [1.0, 2.0]
rings_ref = shot.to_rings(q_values)
if os.path.exists('tmp.ring'): os.remove('tmp.ring')
shot.to_rings(q_values, rings_filename='tmp.ring')
rings = xray.Rings.load('tmp.ring')
assert_array_almost_equal(rings_ref.polar_intensities,
rings.polar_intensities)
if os.path.exists('tmp.ring'): os.remove('tmp.ring')
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 test_multiply_conformations():
traj = structure.load_coor(ref_file('goldBenchMark.coor'))
n_samples = 150
otraj = structure.multiply_conformations(traj, n_samples, 0.1)
# iterate over x,y,z and check if any of the bins are more than 3 STD from the mean
for i in [0,1,2]:
h = np.histogram(otraj.xyz[:,0,i])[0]
cutoff = h.std() * 3.0 # chosen arbitrarily
deviations = np.abs(h - h.mean())
print deviations / h.std()
if np.any( deviations > cutoff ):
raise RuntimeError('Highly unlikely centers of mass are randomly '
'distributed in space. Test is stochastic, though, so'
' try running again to make sure you didn\'t hit a '
'statistical anomaly')
def test_to_rings_on_disk(self):
# this test uses the Rings `rings_filename` flag
t = structure.load_coor(ref_file('gold1k.coor'))
shot = xray.Shotset.simulate(t, self.d, 1, 1)
q_values = [1.0, 2.0]
rings_ref = shot.to_rings(q_values)
if os.path.exists('tmp.ring'): os.remove('tmp.ring')
shot.to_rings(q_values, rings_filename='tmp.ring')
rings = xray.Rings.load('tmp.ring')
assert_array_almost_equal(rings_ref.polar_intensities,
rings.polar_intensities)
if os.path.exists('tmp.ring'): os.remove('tmp.ring')
def test_multiply_conformations():
traj = structure.load_coor(ref_file('goldBenchMark.coor'))
n_samples = 150
otraj = structure.multiply_conformations(traj, n_samples, 0.1)
# iterate over x,y,z and check if any of the bins are more than 3 STD from the mean
for i in [0,1,2]:
h = np.histogram(otraj.xyz[:,0,i])[0]
cutoff = h.std() * 3.0 # chosen arbitrarily
deviations = np.abs(h - h.mean())
print deviations / h.std()
if np.any( deviations > cutoff ):
raise RuntimeError('Highly unlikely centers of mass are randomly '
'distributed in space. Test is stochastic, though, so'
' try running again to make sure you didn\'t hit a '
'statistical anomaly')
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_iprofile_consistency(self):
t = structure.load_coor(ref_file('gold1k.coor'))
d = xray.Detector.generic()
s = xray.Shotset.simulate(t, d, 5, 1)
q_values = np.arange(1.0, 4.0, 0.02)
num_phi = 360
# compute from polar interp
pi, pm = s._implicit_interpolation(q_values, num_phi)
pi = pi.reshape(len(q_values), num_phi)
ip1 = np.zeros((len(q_values), 2))
ip1[:, 0] = q_values
ip1[:, 1] = pi.sum(1)
# compute from detector
ip2 = s.intensity_profile(0.02)
# compute from rings
r = xray.Rings.simulate(t, 10, q_values, 360, 1)
ip3 = r.intensity_profile()
# make sure maxima are all similar
ind1 = utils.maxima(math2.smooth(ip1[:, 1], beta=15.0, window_size=21))
ind2 = utils.maxima(math2.smooth(ip2[:, 1], beta=15.0, window_size=21))
ind3 = utils.maxima(math2.smooth(ip3[:, 1], beta=15.0, window_size=21))
m1 = ip1[ind1, 0]
m2 = ip2[ind2, 0]
m3 = ip3[ind3, 0]
# discard the tails of the sim -- they have weak/noisy peaks
# there should be strong peaks at |q| ~ 2.66, 3.06
m1 = m1[(m1 > 2.0) * (m1 < 3.2)]
m2 = m2[(m2 > 2.0) * (m2 < 3.2)]
m3 = m3[(m3 > 2.0) * (m3 < 3.2)]
# I'll let them be two q-brackets off
assert_allclose(m1, m2, atol=0.045)
assert_allclose(m1, m3, atol=0.045)
assert_allclose(m2, m3, atol=0.045)
def test_iprofile_consistency(self):
t = structure.load_coor(ref_file('gold1k.coor'))
d = xray.Detector.generic()
s = xray.Shotset.simulate(t, d, 5, 1)
q_values = np.arange(1.0, 4.0, 0.02)
num_phi = 360
# compute from polar interp
pi, pm = s._implicit_interpolation(q_values, num_phi)
pi = pi.reshape(len(q_values), num_phi)
ip1 = np.zeros((len(q_values), 2))
ip1[:,0] = q_values
ip1[:,1] = pi.sum(1)
# compute from detector
ip2 = s.intensity_profile(0.02)
# compute from rings
r = xray.Rings.simulate(t, 10, q_values, 360, 1)
ip3 = r.intensity_profile()
# make sure maxima are all similar
ind1 = utils.maxima( math2.smooth(ip1[:,1], beta=15.0, window_size=21) )
ind2 = utils.maxima( math2.smooth(ip2[:,1], beta=15.0, window_size=21) )
ind3 = utils.maxima( math2.smooth(ip3[:,1], beta=15.0, window_size=21) )
m1 = ip1[ind1,0]
m2 = ip2[ind2,0]
m3 = ip3[ind3,0]
# discard the tails of the sim -- they have weak/noisy peaks
# there should be strong peaks at |q| ~ 2.66, 3.06
m1 = m1[(m1 > 2.0) * (m1 < 3.2)]
m2 = m2[(m2 > 2.0) * (m2 < 3.2)]
m3 = m3[(m3 > 2.0) * (m3 < 3.2)]
# I'll let them be two q-brackets off
assert_allclose(m1, m2, atol=0.045)
assert_allclose(m1, m3, atol=0.045)
assert_allclose(m2, m3, atol=0.045)
def test_to_rings(self):
t = structure.load_coor(ref_file('gold1k.coor'))
shot = xray.Shotset.simulate(t, self.d, 1, 1)
shot_ip = shot.intensity_profile(0.1)
q_values = shot_ip[:,0]
rings = shot.to_rings(q_values)
rings_ip = rings.intensity_profile()
# normalize to the 6th entry, and discard values before that
# which are usually just large + uninformative
rings_ip[:,1] /= rings_ip[5,1]
shot_ip[:,1] /= shot_ip[5,1]
# for some reason assert_allclose not working, but this is
x = np.sum( np.abs(rings_ip[5:,1] - shot_ip[5:,1]) )
x /= float(len(rings_ip[5:,1]))
print x
assert x < 0.2 # intensity mismatch
assert_allclose(rings_ip[:,0], shot_ip[:,0], err_msg='test impl error')
def test_rotated_beam(self):
# shift a detector up (in x) a bit and test to make sure there's no diff
t = structure.load_coor(ref_file('gold1k.coor'))
s = xray.Shotset.simulate(t, self.d, 5, 1)
sh = 50.0 # the shift mag
xyz = self.d.xyz.copy()
shift = np.zeros_like(xyz)
shift[:, 0] += sh
beam_vector = np.array([sh / self.l, 0.0, 1.0])
# note that the detector du is further from the interaction site
du = xray.Detector(xyz + shift, self.d.k, beam_vector=beam_vector)
su = xray.Shotset.simulate(t, du, 5, 1)
p1 = s.intensity_profile(q_spacing=0.05)
p2 = su.intensity_profile(q_spacing=0.05)
p1 /= p1.max()
p2 /= p2.max()
p1 = p2[:10, :]
p2 = p2[:p1.shape[0], :]
assert_allclose(p1, p2, rtol=0.1)
def setup(self):
self.file = ref_file('ala2.pdb')
