def setup_detector(theta, calib_csv=calib_csv):
det_param_df = pd.read_csv(calib_csv)
det_kwargs = dict(zip(det_param_df['param'], det_param_df['val']))
# Detector only holds pixel size for whatever reason
detector = pyFAI.detectors.Detector(det_kwargs['det_pix'],
det_kwargs['det_pix'])
# Transform holds everything else
pg = pygix.Transform(
incident_angle=theta,
detector=detector,
**{k: v
for k, v in det_kwargs.items() if k != 'det_pix'})
return pg
def create_ai_from_dict(poni_dict, gi=False):
"""Create Azimuthal Integrator object from Dictionary"""
ai = AzimuthalIntegrator()
for k, v in poni_dict.items():
ai.__setattr__(k, v)
if not gi:
ai._rot3 -= np.deg2rad(90)
else:
calib_pars = dict(dist=ai._dist,
poni1=ai._poni1,
poni2=ai._poni2,
rot1=ai._rot1,
rot2=ai._rot2,
rot3=ai._rot3,
wavelength=ai._wavelength,
detector=ai.detector)
ai = pygix.Transform(**calib_pars)
ai.sample_orientation = 3 # 1 is horizontal, 2 is vertical
return ai
directory = '/Users/rbelisle/Desktop/5050onoff/'
file_interest = 'D7a_MAPbIBr2_PTAA_L60On_30s_01231947_0001.tif'
dataFile = directory + file_interest
data = fabio.open(dataFile).data # Use fabio to open file as a np.array
# plot the imported file (this will not be calibrated)
fig1, ax1 = plt.subplots()
ax1.set_xlabel("x-pixel (#)")
ax1.set_ylabel("y-pixel (#)")
ax1.yaxis.set_ticks_position('both')
ax1.xaxis.set_ticks_position('both')
ax1.imshow(data, vmin=3, vmax=100,
origin='lower') #use imshow to rasterize np.array
# %% Load calibration file and set sample geomtetry
pg = pygix.Transform() # set up the transformation file
pg.load('/Users/rbelisle/Desktop/lab6_calib_315_0122.poni'
) # load the callibration file
pg.sample_orientation = 3 # set sample orientation: 1 is horizontal, 2 is vertical, 3 is horizontal rotated by 180 deg, 4 is vertical rotated by 180 deg (for more details see: https://github.com/tgdane/pygix/blob/master/pygix/transform.py)
pg.incident_angle = 3 # set indicent x-ray angle in deg
pg.tilt_angle = 0 # tilt angle of sample in deg (misalignment in "chi")
pg # optionally print geometry
#%% Run calibration accounting for solid angle correction
ii_2d, qxy_2d, qz_2d = pg.transform_reciprocal(data,
correctSolidAngle=True,
method='bbox',
npt=3000)
#plot the corrected file in the correct units
fig2, ax2 = plt.subplots()
r[1:, 0] = q * .1
r[0, i + 1] = os.path.basename(tif)
r[1:, i + 1] = intensity
df = pd.DataFrame(r[1:], columns=r[0])
df['q'] = df['q'].apply(lambda x: x * 10)
df.set_index(df['q'], inplace=True)
df.drop(['q'], axis=1, inplace=True)
plt.imshow(np.log(img))
plt.savefig(os.path.join(
parentdir, 'results', 'png',
os.path.basename(tif).replace('.tif', '') + '.png'),
bbox_inches='tight')
plt.close()
pg = pygix.Transform()
pg.load(ponifile)
pg.incident_angle = incident_angle
pg.sample_orientation = sample_orientation
# qxyxz plot:
intensity, qxy, qz = pg.transform_reciprocal(img,
npt=(qbins, qbins),
polarization_factor=-.95,
method='nearest')
with open('{}/png_qxyqz/{}_imageData.dat'.format(resultdir, filename),
'w') as f:
np.savetxt(f, intensity)
# default method is "splitpix", which for some reason fills the wedge with interpolated pixels. Function is defined in C:/Anaconda2/Lib/site-packages/pyFAI/ext/splitpixelFull.pyd, which is already compiled, so cannot be fixed.
# Methods 'np' and 'cython' don't fill wedge, but returned array is much too big and mostly black, so valuable data fills only a few pixels. ip_range and op_range are defined to customize the range, but don't work