%matplotlib inline
import numpy as np
import pylab as plt
import matplotlib as mpl
from py4xs.local import ExpPara
from py4xs.data2d import Data2d,Axes2dPlot,DataType
import warnings
warnings.filterwarnings('ignore')
Setting up the ExpPara for the detector
The detector rotation angles are defined as described in DOI:10.1107/S0909049512048984.
The rotation of the detector can be defined by three different angles, as long as the rotation matrix is revised accordingly.
ew = ExpPara(1042, 1042)
ew.wavelength = 0.886
ew.bm_ctr_x = 27
ew.bm_ctr_y = 1039
ew.ratioDw = 2.52
ew.det_orient = 45
ew.det_tilt = -17
ew.det_phi = 0
ew.grazing_incident = True
ew.flip = -3
ew.incident_angle = 0.6
ew.sample_normal = 0.25
ew.calc_rot_matrix()
ew.init_coordinates()
Reading the data from TIF files
Clean up the background a bit before displaying the data
gid_file = 'data/no36_500A_PTCDI_Td_RT-Ta_140C-ODTS-sth0.60.60s_WAXS'
xr_file = 'data/no36_500A_PTCDI_Td_RT-Ta_140C-ODTS-sth_-0.5_10-attn0.5_42s_WAXS'
bkg_file = 'data/no83_bare_Si-sth0.60.60s_WAXS'
dbkg = Data2d(bkg_file, exp=ew)
dbkg.data.d = (dbkg.data.d-1000)*15/10
dwaxs = Data2d(gid_file, exp=ew)
dwaxs.data.d = np.abs(dwaxs.data.d-dbkg.data.d-850)
dwaxs.conv_Iqrqz(Nqr=480, Nqz=480)
Displaying the data using Axes2dPlot
The scattering pattern as collected
plt.figure(figsize=(6,6))
ax = plt.gca()
paxr = Axes2dPlot(ax, dwaxs.data)
paxr.plot(logScale=True)
paxr.img.set_clim(240,2400)
The scattering data after translated to \(q_r\)-\(q_z\) coordinates
plt.figure(figsize=(8,6))
ax = plt.gca()
paxq = Axes2dPlot(ax, dwaxs.qrqz_data, DataType.qrqz)
paxq.plot(logScale=True)
paxq.img.set_clim(240,2400)
