AFL.agent.reduce_usaxs module#

Calculate R(Q) from raw USAXS data.

AFL.agent.reduce_usaxs.amplifier_corrections(signal, seconds, dark, gain)#

correct for amplifier dark current and gain $v=(s-t\ast d)/g$

AFL.agent.reduce_usaxs.calc_R_Q(wavelength, ar, seconds, pd, pd_bkg, pd_gain, I0, I0_bkg=None, I0_gain=None, ar_center=None, V_f_gain=None)#

Calculate 1-D $R(Q)$ from raw USAXS data.

Parameters:

• wavelength (float) – $lambda$, ($\text{A}$)

• ar_center (float) – center of rocking curve along AR axis

• ar (numpy.ndarray([float])) – array of crystal analyzer angles

• seconds (numpy.ndarray([float])) – array of counting time for each point

• pd (numpy.ndarray([float])) – array of photodiode counts

• pd_bkg (numpy.ndarray([float])) – array of photodiode amplifier backgrounds

• pd_gain (numpy.ndarray([float])) – array of photodiode amplifier gains

• I0 (numpy.ndarray([float])) – array of incident monitor counts

• I0_bkg (numpy.ndarray([float])) – array of I0 backgrounds

• I0_amp_gain (numpy.ndarray([float])) – array of I0 amplifier gains

• V_f_gain (numpy.ndarray([float])) – array of voltage-frequency converter gains

• qVec (numpy.ndarray([float])) – $Q$

• rVec (numpy.ndarray([float])) – $R=I/I_o$

Returns dictionary:

Q, R

AFL.agent.reduce_usaxs.centroid(x, y)#

Compute centroid of y(x).

AFL.agent.reduce_usaxs.reduce_uascan(root)#

1-D data reduction, from livedata.

AFL.agent.reduce_usaxs.remove_masked_data(data, mask)#

Remove all masked data, convenience routine.