This code was developed as part of my M.Sc. thesis at the University of Copenhagen and is meant to improve data
analysis of x-ray data. More specifical to improve data analysis of in situ measurements using the Pair
Distribution Function (PDF).
This simple program is meant to ease the workload of preprocessing the data before modeling is preformed and to
help the user keep track of all used parameters making data reproducible.
This framework is built using the following two packages:
Calibration and integration is implemented using PyFAI. What program to use for these tasks are
an almost religous question, PyFAI was chosen as it supports the most used ones:
Fit2D3 and
Dioptas4.
PyFAI can load both calibration and mask files from either of those programs while still having its own framework for
handling these tasks. This flexibility made it the obvious choice.
The two following sections will provide a simple guide to installing and running the program.
A more complete guide for installing, how to use examples and implementation can be found in
PDFconverter_manual.pdf.
The README.md file consist of the following sections:
For running this program I recommend using Python 3.7 but it is compatible down to Python 3.4. If you do not have Python installed the easiest way is to install Anaconda. Remember to add Anaconda to your path when installing it. To verify that python has been installed correctly after installing Anaconda open your terminal and type python --version, if this does not produce an error then you have installed Python correctly!
python --version
>>> Python 3.7.4
The "hardest" packages to install for this program are PyFAI and PDFgetX3. I recommend reading their installation guides on their homapages, for getting help installing PyFAI press here and for PDFgetX3 press here. Remember to choose the right operating system! When these packages are correctly installed then you are practically done, all of the remaining packages can simply be installed using either Anaconda or pip, which ever you prefer. Remember only to install the needed packages with either of them and not both of them, as it will confuse Python!
pip install tqdm
or
conda install tqdm
Unfortunately, the simplest way to install the remaining packages, is to run the program and install the missing packages when the following error is produced:
>>> Traceback (most recent call last):
>>> File "<stdin>", line 1, in <module>
>>> ModuleNotFoundError: No module named 'prompter'
The number of packages needed to run this program depends on how you chose to install Python. If you chose Anaconda then you should only have to install 2-3 additional packages.
This program has three core functions: calibration, integration and background subtraction. It is so far
recommended to use Fit2D for calibration.
The main_config.init is used to configure the program. To run only the program only three parameters are needed,
Importdir, Outputdir and Calibrationconfig. If nothing else is specified default values will be imported from main_default.init.
To ignore/use default values within the program either use '#' at the beginning of the line, set the variable to None or simply delete it
from main_config.init.
The first parameter that needs to be specific is Importdir.
Importdir = /Home/Folder/Data, /Home/Folder/Background
or
Importdir = /Home/Folder/Data
All '.tif' files within these two directories will be imported. The first specified directory is data of interest while
the second is background data. It is not necessary to specify a background directory, hence no background will be subtracted
from the data.
The second parameter is the Outputdir variable.
Outputdir = /Home/Folder
This is the directory where the project folder will be created. The project folder will be named after
the parameter Stemname and is where all generated data and used configurations are saved.
The calibration and mask file is specified through the parameters Calibrationconfig and Mask.
To get a better overview of how background subtraction and change in parameters affect the PDFs a simple GUI was implemented. The GUI consist of 4 different plots, different possibilities for automated background subtraction and easy access to the parameters needed for the Fourier Transformation.
On the left side of the GUI 4 different plots are present and the header shows the current plotted data set and its
scaling factor. From the top and down I(q), F(q), G(r) and scaling factors as a function of time. By hovering the scaling
plot the 3 top graphs will change to the corresponding timeframe hovered. E.g. This gives the possibility of deciding the best
Qmax and to remove unique atom-atom distances from the PDF through the background subtraction.
The method box is an automatic way of calculating the scaling factor/factors for a large dataset. The different
methods are explained in the table below. When a method is chosen and Recalculating scaling is pressed, then the
program will calculate the highest possible scaling factor/factors within within the range of Qmin
and Qmax.
| Method | Description |
|---|---|
| 1 | One scaling factor is calculated |
| 2 | A scaling factor for each data frame is calculated. |
| 3 | Not implemented, room for improvement. |
| 4 | Not implemented, room for improvement. |
All scaling factors can be altered by the relative scale, either by giving a float or changing the scale bar.
The chance is committed by pressing the Calculate button. Furthermore, specific time areas of the data set can be
adjusted by using the First and Last box and then pressing Choose frames. This will mark an area on the
4th plot indicating which frames will have their scaling factors changed by the next Calculate. Scaling
factors can also be set to absolute values by using the Scale field and then pressing Calculate. To remove
miss selected frames the Clear button can be pressed.
Parameters such as Qmin, Qmax, rstep etc. determine the range of how the scaling factors
are determined and how the Fourier transformation is done. By pressing Set q and r range the plots will be redrawn.
In the upper right corner, 4 checkboxes are shown. Here the outputs generated are determined. In the example shown below
only F(q) and G(r) are save in the project folder.
- I(q)
- S(q)
- F(q)
- G(r)
The GUI is closed and outputs are created by pressing Continue.
Possible arguments for PDF Converter.
| Arg | Description |
|---|---|
-h or --help |
Prints help message. |
-c or --create |
Create can take 2 different inputs or a combination of them. fit2D or cfg |
The create argument can create two types of files, either a cfg file or a fit2d calibration file. A '.cfg' file is needed
for PDFgetX3 to specify required parameters for calculating the PDFs. The fit2D is a file where calibration configurations
from Fit2D can be store for future calibration.
python __init__.py --create fit2d
>>> Creating .Fit2D calibration file!
- Emil T. S. Kjær, Ph.D. student in Nanoscience at the University of Copenhagen
- Supervisor Kirsten M. Ø. Jensen, associate professor at the University of Copenhagen.
Should there be any question, desired improvement or bugs please contact me on GitHub or through my email [email protected].
This project is licensed under the MIT License - see the LICENSE.md file for details
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- Hammersley, A. P. (2016). J. Appl. Cryst. 49, 646-652.
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