Representing data in Q space is fine for viewing etc... but the conversion
from 2Th to Q needs a little thought. If unequal Q steps is not a problem
then a straight conversion is ok. However if someone is going to use that Q
data for further analysis then it is important to use the original data or
at least know where it came from for reasons I gave in a previous reply to
the mailing list which I have included again below.
In other words if a diffractomer or some other instrument collect data in Q
space at equal steps and this data is compared to data collected at 2Th then
the match wont be 100% depending on how the conversion is done.
Most importantly is that data from one or the other should not be thrown
away.
Thus to discuss the question of archiving data in Q space means
understanding the data conversion principles.
cheers
alan
Von Dreele write:
>However, the profile shape functions are not simple
> functions of Q but are simple (Gaussian &
> Lorentzian) functions of 2-theta. Case closed.
========== Previous reply on Q space conversion ===========
Converting from one x-axis to another; you may want to consider the
following Melinda when you do your conversion.
For a particular data point in Q space the area of the space sampled is:
Area(Q) = I(Q) del_Q
For 2Th the area is:
Area(2 Th) = I(2 Th) del_2Th
where del_Q and del_2Th corresponds to the size of the receiving slit in the
equitorial plane for Q and 2Th spaces respectively. We assume constant
counting time at each data point.
First transform point for point with equal areas at any particlar data
point, or
Area(Q) = Area(2 Th)
or,
I(2 Th) = I(Q) del_Q / del_2Th
If both data sets were collected with fixed receiving slits then
del_Q/del_2Th is a constant and can be ignored by setting it to 1.
I(2 Th) at this stage would be at unequal x-axis steps as you pointed out.
To convert to equal x-axis steps you need to sample I(2 Th) at equal 2Th
steps, lets call the chosen step size 2Th_step_size.
If you want the Sum of I(2 Th) to equal the Sum of I(Q) then you need to
sample I(2 Th) with a receiving slit width that has a size equal to
2Th_step_step.
Only when you do this do you use all of the observed data in the original
I(Q) and use it only once.
When it comes time to fitting the data you would then need to account for
the chosen receiving slit, this can be done by a convolution.
I dont know if GSAS does this but if it cant then I suggest you sample I(2
Th) at an infinitely small receiving slit and ignore any scaling constants.
In this approach some of the original data may not be sampled.
cheers
alan
