def workup():
trive.exp.set_coord(trive.d1, 100.)
trive.exp.set_coord(trive.d2, 200.)
trive.exp.set_coord(trive.ss, 50.)
# hamiltonian
H0.tau_ag = 50.
H0.tau_2aa = 50.
H0.tau_2ag = 50.
H = H0.Omega()
H.out_group = [[5, 6]]
# scan
w1 = trive.w1
w1.points = np.linspace(5000, 9000, 41)
w2 = trive.w2
w2.points = np.linspace(5000, 9000, 41)
scan = trive.exp.scan(w1, w2, H=H)
scan.run(mp=False, autosave=False)
# measure
mono = m.Mono()
mono.slitwidth = 120 # wn
sld = m.SLD()
measure = m.Measure(scan, mono, sld)
measure.run()
# data
data = wt.data.from_NISE(measure)
data.transpose()
data.scale() # stored as amplitude level
data.normalize()
# save
data.save(out_path)
return data, data.copy()
def workup():
trive.exp.set_coord(trive.d1, 100.)
trive.exp.set_coord(trive.d2, 200.)
trive.exp.set_coord(trive.ss, 50.)
# hamiltonian
H0.tau_ag = 50.
H0.tau_2aa = 50.
H0.tau_2ag = 50.
H = H0.Omega()
H.out_group = [[5, 6]]
# scan
w1 = trive.w1
w1.points = np.linspace(5000, 9000, 41)
w2 = trive.w2
w2.points = np.linspace(5000, 9000, 41)
scan = trive.exp.scan(w1, w2, H=H)
scan.run(mp=False, autosave=False)
# kernal
# currently no way to NOT do this in multiprocessing
# additionally this spams my NISE/data folder :-(
if __name__ == '__main__':
scan.smear(0, 1, 500, 1e-3, theta=np.pi/4, save=False)
# measure
mono = m.Mono()
mono.slitwidth = 120 # wn
sld = m.SLD()
measure = m.Measure(scan, mono, sld)
measure.run()
# data
data = wt.data.from_NISE(measure)
data.transpose()
data.scale() # stored as amplitude level
data.normalize()
# save
data.save(out_path)
return data, data.copy()
out1.run(autosave=autosave, mp=True, chunk=False)
t.exp.set_coord(dzs, 1.5e-5)
out2 = t.exp.scan(w1, w2, d1, H=H, inhom_object=inhom_object)
out2.run(autosave=autosave, mp=True, chunk=False)
if add_nrb:
for obj in [out1, out2]:
nrb1 = obj.nrb()
print nrb1.shape
print obj.sig.shape
nrb1_max = np.abs(nrb1).max()
obj_smax = np.abs(obj.sig.sum(axis=-2)).max()
#print nrb1_max, out1_smax
nrb1 *= obj_smax / nrb1_max * nrb_level
#print np.abs(nrb1).max(), np.abs(out1.sig).max()
# careful...don't collapse the out_groups axis
obj.sig = obj.sig.sum(axis=-2)[..., None, :]
obj.sig += nrb1[..., None, :]
m1 = m.Measure(out1, m.Mono, m.SLD)
m.Mono.slitwidth = slitwidth
m2 = m.Measure(out2, m.Mono, m.SLD)
m.Mono.slitwidth = slitwidth
if plot1:
m1.run()
m1.plot(0, yaxis=1, zoom=1)
if plot2:
m2.run()
m2.plot(0, yaxis=1, zoom=1)
out2.run()
#trive.set_coord(d1, 0.)
#trive.set_coord(d2, 0.)
#out1 = trive.scan(w1, w2)
# manually plotting the output of out2
sig2o = (np.abs(out2.sig.sum(axis=-2))**2).sum(axis=-1) * out2.timestep
plt.figure()
plt.subplot(131)
plt.contourf(trive.d1.points, trive.d2.points, sig2o, 200)
plt.title('sig2 manual')
plt.grid()
plt.colorbar()
# using measure processes - shoudl be equivalent to sig2o
sig2 = m.Measure(out2, m.SLD)
sig2.run()
plt.subplot(132)
plt.contourf(trive.d1.points, trive.d2.points, sig2.pol, 200)
plt.title('sig2 measure')
plt.grid()
plt.colorbar()
ratio1 = sig2.pol / sig2o
print ratio1.min(), ratio1.max()
# using measure processes, but with a mono
sig2m = m.Measure(out2, m.Mono, m.SLD)
# should be equivalent to the others if we set mono to pass
m.Mono.slitwidth = slitwidth
sig2m.run()
inhom_object = inhom.Inhom()
H = H_1.Omega()
out1 = tsf.exp.scan(w1, w2, H=H, inhom_object=inhom_object)
out1.run(autosave=autosave)
if add_nrb:
"""
need to rewrite this part? maybe not rigorously correct...
"""
nrb1 = out1.nrb()
print nrb1.shape
print out1.sig.shape
nrb1_max = np.abs(nrb1).sum(axis=-1).max()
out1_smax = np.abs(out1.sig).sum(axis=-1).max()
#print nrb1_max, out1_smax
nrb1 *= out1_smax / nrb1_max * nrb_level
#print np.abs(nrb1).max(), np.abs(out1.sig).max()
out1.sig = out1.sig.sum(axis=-2)[..., None, :]
out1.sig += nrb1[..., None, :]
sig1 = m.Measure(out1, m.Mono, m.SLD)
# should be equivalent to the others if we set mono to pass
m.Mono.slitwidth = slitwidth
sig1.run()
print sig1.pol.shape
# run out1.axes() if you forgot which axis is which
sig1.plot(0, yaxis=1, zoom=3)
#sig1.plot(0,yaxis=2)
#sig1.plot(1,yaxis=2)
inhom_object = inhom.Inhom(inhom_sampling='linear',
num=100,
sigma=100.0,
zeta_bound=2)
else:
inhom_object = inhom.Inhom()
H = H_1.Omega()
H.TOs = TOs
trive.exp.late_buffer = 250.
out1 = trive.exp.scan(w1, w2, d2, H=H, inhom_object=inhom_object)
#out1 = trive.exp.scan(d1, d2, H=H, inhom_object=inhom_object)
if mp:
out1.run(autosave=autosave, mp=True, chunk=False)
else:
out1.run(autosave=autosave, mp=False)
sig1 = m.Measure(out1, m.Mono, m.SLD)
m.Mono.slitwidth = slitwidth
if plot1:
sig1.run()
sig1.plot(0, yaxis=1, zoom=2)
#sig1.plot(0,yaxis=2)
if imported_after:
filepath = r''.join([folder_path, rel_path2])
out2 = trive.S.Scan._import(filepath)
else:
out1.smear(0, 1, smear_extent, 20, theta=angle)
out2 = out1
if view_kernel:
pass
"""
import matplotlib.pyplot as plt