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--- processing:start [2018/07/10 14:46] – matthias
+++ processing:start [2019/06/07 18:00] (current) – [Workflow: Getting a list of grains and their orientations] matthias
@@ Line 5: / Line 5: @@
 {{ ::processing:workflow.jpg?nolink&600 |}}
-===== Software =====
+===== Data collection =====
-The scripts and software you should use for each step are
+Usually, the data is collected in synchrotron facilities by stepwise rotating the sample while the detector is acquiring diffraction images. For more information, click [[dac_experiments:geometry|here]].
-  * Data: you should look at your diffraction data with [[software:fabian|Fabian]]. Pay attention about image orientation and rotation. You can also start looking at diffraction intensity levels, in the background, in the peaks, etc.
-  * Generating backgrounds, median, average images: [[software:imagemath|Image Math]].
-  * Looking at images with background subtracted: [[software:fabian|Fabian]].
-  * Peak extraction: [[software:peaksearch|Peaksearch]]
-  * To be completed...
-===== Procedure for simulating data and their comparison with actual data (short) =====
+===== Workflow: Training with simulated data =====
-  - Create an input file with the ending **.inp**. It should contain information on instrumentals of the experiment, the grain, the sample, strain, background, peak shape, and so on. You find an example of an input file [[fileformat:inp:basic|here]].
+Starting with real data might be complicated if you are a beginner in MGC. Training the actual workflow with simulated data can help you to verify if your workflow is correct. It also makes you familiar with the software. Pitfalls are better visible with artificial data.
-  - Next you can run the simulation with [[software:polyxsim|PolyXSim]]. This simulation may take a while...
-  - Afterwards, you can look at the output with [[software:fabian|Fabian]].
-  - If you have "real" data, this would be the point when you work on the background (more information on this topic [[software:imagemath|here]]). If you also simulated noise, strain or other things that make your data look more like "real" data, it might be useful to do a background substraction, too.
-  - Now you can search for peaks using the software [[software:peaksearch|PeakSearch]].
-  - In [[software:imaged11|ImageD11]] the found peaks are fitted to the parameters of the sample and experiment, followed by the calculation of the g-vector.
-  - With the calculated g-vector, the grains will now be indexed, using [[software:grainspotter|GrainSpotter]].
-  - The calculated grains should then be compared and checked with the simulated grains.
-===== Procedure for simulating data and their comparison with actual data (long) =====
+But even when you are working with real data, you can compare your results with the outcome of the simulation to prove if they are reasonable.
-==== Producing data by simulation ====
+[[processing:workflow_training|Click here to train your workflow with a simulated dataset.]]
-Create an input file with the ending //.inp//. For a start, simply modify an existing one like [[fileformat:inp:basic|this]]. Afterwards, you can run the simulation with [[software:polyxsim|PolyXSim]]. The purpose of this step is to simulate the outcome of a DAC experiment (grains with random orientations, random strains etc.). The simulation will not only provide 2D diffraction images but also G-vectors, inverse Ub matrices and some more files. You will get at least 7 different files from the simulation plus the diffraction images. The amount of diffraction images depends on the ω range and the step size. For example, a ω range from -28° to +28° with a step size of 0.5° produces 112 images (numbers from 0 to 111).
+===== Workflow: Find out the phases in your sample and their cell parameters =====
+This step is actually not part of the MGC but a normal Rietveld refinement. However, it is a necessary step for further processing workflows.
-To run the simulation write the following to the Konsole:
-  PolyXSim.py -i 'some_input_file'.inp
-The 7 different files (which were just mentioned above) are usually created quite fast. The time consuming process is the creation of images. This time highly depends on the parameters you put in the input file, e.g. the amount of grains, the peak shape and if you switched on strain tensors or noise. If you just want to test if the software is working it is wise to use an input file with very simple parameters (only 1 grain, no strain tensors, no noise, small ω range etc.).
-While the simulation is running you can already look at the images, which are already created, with Fabian. Open a new tab in the Konsole and open Fabian:
-  fabian.py
+===== Workflow: Getting a list of grains and their orientations =====
+This workflow will provide you with a list of grains, as well as an orientation of each single grain in your sample. [[processing:workflow_dac_data|Click here when you feel ready to rock]]
+===== ... =====
+More to come ...