def integrate(df_path, tilts, Nz, **kwargs):
df = pd.read_pickle(df_path)
iBs, iZs = np.arange(5), np.arange(100, Nz, 100)
nbs, nzs = iBs.size, iZs.size
I, Iint = np.zeros((nts, nbs, nzs)), np.zeros((nbs, Nz))
for it, f in enumerate(df.index):
multi = pp.load_multi_obj(name + f)
hks, t, Ib = multi.get_beams()[[0, 1, -1]]
I[it, :, :] = Ib[iBs, :][:, iZs]
Iint[iBs, :] += Ib[iBs, :]
hks = [hk[1:-1].split(',') for hk in hks]
hk = ['(%d,%d)' % ((int(hk[0]) / 8, int(hk[1]) / 8)) for hk in hks]
cs = dsp.getCs('jet', nbs)
for iz, iZ in enumerate(iZs):
tle = 'z=$%.0f \AA$' % t[iZ]
plts = [[tilts[:, 0], I[:, iB, iz], [cs[iB], '-o'],
'%s' % hk[iB]] for iB in range(nbs)]
dsp.stddisp(plts,
labs=[r'$\theta(^{\circ})$', '$I_b$'],
title=tle,
lw=2,
opt='ps',
name=fig_path + 'SC_tilt.svg')
plts = [[t, Iint[iB, :], [cs[iB], '-'],
'%s' % hk[iB]] for iB in range(nbs)]
dsp.stddisp(plts, labs=[r'$z(\AA)$', '$I_b$'], lw=2, **kwargs)
def test_001():
lat_params = [1, 2, 1]
lat_vec = np.diag(lat_params)
pattern = np.array([[6, 0.5, 0.5, 1, 1, 1], [8, 0.75, 0.75, 0.5, 1, 1]])
name = path + 'carbone001.xyz'
n = [0, 0, 1] # beam along z
u = [1, 0, 0] # rotation axis along x
rep, pad = [20, 20, 10], 4
mut.make_xyz(name,
pattern,
lat_vec,
lat_params,
n=n,
pad=pad,
rep=rep,
fmt='%.4f',
dopt='s')
# mut.show_grid(name,'xy')
# mut.show_grid(name,'xz')
# mut.show_grid(name,'yz')
# multi = run(data=name,tail='001',Nhk=31,hk_sym=0,fopt=1,ppopt='wBP')
multi = pp.load_multi_obj(path + 'Carbone_SC_001_autoslic.pkl')
P = multi.show_patterns(Iopt='Incs',
out=False,
Nmax=256,
caxis=[0, 0.01],
imOpt='cv',
axPos='V',
cmap='gray')
def update_patterns(dfname='df.pkl', ssh='', hostpath=''):
df = pp.update_df_info(path + dfname, hostpath=hostpath)
for dat in df.index:
multi = pp.load_multi_obj(path + dsp.dirname(dfname) + dat)
multi.ssh_get(ssh, 'pattern', hostpath=hostpath)
multi.save_pattern()
return df
def pp_simus():
for i,data in enumerate(files):
i_str = data.split('_')[-1].replace('.xyz','')
pkl = datpath+'ireloh2_pad2_'+data.replace('.xyz','')+'_autoslic.pkl'
multi = pp.load_multi_obj(pkl)
multi.outf['patternS'] = multi.outf['patternnpy'].replace('.npy','S.npy')
multi.postprocess(ppopt='uwS',ssh_alias='badb')
qx,qy,I = np.load(multi._outf('patternS')); print(I.shape)
def plot_S():
df = pd.read_pickle(df_name)
for obj_pkl in df.index: #[6:]:
val = df.loc[obj_pkl].data.split('_')[0]
multi = pp.load_multi_obj(datpath + obj_pkl)
dutil.plot_npy(multi._outf('patternS'),
log=True,
caxis=[-9, -6],
title=r'%s' % val,
xylims=0.2,
name=figpath + val + 'log.png',
opt='sc')
def get_figs(dfname='df.pkl'):
df = pd.read_pickle(path + dfname)
cs = dsp.getCs('Blues', 3) #,dsp.getCs('Reds'),dsp.getCs('Greens')
plts = [[], [], []]
#pad = int(np.log10(df.index.size))+1
for i, dat in enumerate(df.index):
multi = pp.load_multi_obj(path + dsp.dirname(dfname) + dat)
multi.pattern(
tol=1e-4,
Iopt='Insgl',
gs=0.25,
caxis=[-6.3, 0],
Nmax=500,
cmap='binary',
imOpt='hc', #rings=[0.1,0.2],#,1],,
pOpt='Xt',
xyTicks=1,
xylims=[-3, 3.01, -3, 3.01], #xylims=[-2,2.01,-2,2.01],
opt='s',
name=path + 'figures/%s_pattern.png' % dat.replace('.pkl', ''))
def run_temsim(load_opt=0, Nz=1):
if load_opt:
mp_ms = pp.load_multi_obj(datpath + 'Si110_autoslic.pkl')
else:
mp_ms = ms.Multislice(datpath,
mulslice=False,
data=Si110,
keV=200,
slice_thick=dz,
NxNy=nxy,
repeat=[1, 1, Nz],
Nhk=5,
v=1,
opt='rs',
ppopt='w',
fopt='f',
i_slice=1)
# mp_ms.pattern(Iopt='Icns',cmap='gray',imOpt='ch',xylims=[0,12,0,12],
# name='docs_fig/Si110_autoslic_pattern.png',axPos='T',setPos=1)
# mp_ms.beam_vs_thickness(bOpt='fa',tol=1e-4)
return mp_ms
n_TDS=4,
T=300,
tail='bf2',
mulslice=False,
keV=200,
NxNy=2**10,
repeat=[1, 1, 1],
slice_thick=1,
opt='srw',
fopt='f',
ssh='badb')
# run_simu()
pkl = datpath + 'TDS_bf2_autoslic.pkl'
multi = pp.load_multi_obj(pkl)
multi.postprocess(ppopt='uwS', ssh_alias='badb')
# dutil.plot_npy(multi._outf('patternS'),log=True,
# caxis=[-9,-6],xylims=0.2,
# name=figpath+'TDS_log.png',opt='p')
dutil.plot_npy(multi._outf('patternS'),
log=False,
caxis=[0, 1e-7],
xylims=0.2,
title='TDS',
name=figpath + 'TDS_lin.png',
opt='p')
crys = Crystal.from_cif(file)
lat_params = crys.lattice_parameters[:3]
a1,a2,a3 = lat_params
b12 = np.sqrt(1/a1**2+1/a2**2)
fs = {'leg':30,'lab':40,'tick':25}
if 'E' in opts:
#Ewald configuration [010]
mut.ewald_sphere(lat_params,lam=cst.eV2mum(12000)*1e4,tmax=60,T=20.,nx=5 ,ny=20,opt='p',name=figpath+'E_MX.png',xylims=[-1,1.01,-0.1,2.01],xyTicks=1,legLoc='upper right',fonts=fs)
mut.ewald_sphere(lat_params,lam=cst.keV2lam(200) ,tmax=7 ,T=0.2,nx=20,ny=10,opt='p',name=figpath+'E_ED.png',xylims=[-3,3.01,-0.1,1.01],xyTicks=1,legLoc='upper right',fonts=fs)
if 'B' in opts:
df = pd.read_pickle(path+'df0.pkl')
p1 = pp.load_multi_obj(path+'biotin_m0_autoslic.pkl')
p1.datpath = p1.datpath.replace('ronan','tarik')
p1.get_beams(bOpt='na')
#plot
iBs = ['(64,0)','(0,32)','(0,64)','(32,32)','(64,64)']
fig,ax = p1.beam_vs_thickness(iBs=iBs,cm='jet',
fonts=fs,opt='ps',name=figpath+'biotin_m0_beams.png')
if 'F' in opts:
# structure factor
lat_vec = crys.reciprocal_vectors
pattern = np.array([ np.hstack([a.coords_cartesian,a.atomic_number]) for a in crys.atoms])
hkl,F3d = structure_factor3D(pattern,lat_vec,hkl=None,hklMax=3,sym=0)
#excitation error
K = 1/cst.keV2lam(200)
k = [2/a1,2/a2, b12, 2*b12]
for i in range(-ny + 1, ny)] + ['$q_x=-q_y$', '$q_x=q_y$']
sc = dsp.getCs('Spectral', len(ss))
plts = [[qx[s], qy[s], c, l] for s, l, c in zip(ss, sl, sc)]
dsp.stddisp(plts, fig=fig, ax=ax, lw=2)
dsp.stddisp([[q[s], I[s], c, l] for s, l, c in zip(ss, sl, sc)],
lw=2,
xylims=['y', 0, 0.001])
# multi.beam_vs_thickness(iBs=range(10),cm='Spectral',name=figpath+'900_B.svg',opt='sp')
# multi.beam_vs_thickness(tol=1e-3,cm='Spectral',name=figpath+'900_B.svg',opt='sp',xylims=['y',0,0.005])
# multi = pp.load_multi_obj('../dat/ireloh/ireloh_t1_autoslic.pkl')
multi = pp.load_multi_obj('../dat/ireloh/ireloh_484_autoslic.pkl')
# multi = pp.load_multi_obj('../dat/ireloh/ireloh_900_autoslic.pkl')
# multi = pp.load_multi_obj('../dat/ireloh/ireloh_t1_autoslic.pkl')
# multi = pp.load_multi_obj('../dat/ireloh/ireloh_pptest_autoslic.pkl')
# multi.postprocess(ssh_alias='badb',ppopt='uB')
# postpp(multi)
def plot_transmission_vs_structure_factor():
plts = []
#### Structure factor
if 'F' in opts:
(qxF, qyF, qzF), Fhkl = multi.get_structure_factor(hkl=None,
hklMax=hklM,
sym=1,