Revision of texture_corr_steps.md

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texture_corr_steps.md

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texture_corr_steps.md

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texture_corr_steps.md

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texture_corr_steps.md

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texture_corr_steps.md

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texture_corr_steps.md (file created)

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			@@ -25,7 +25,7 @@ Steps for Texture Correction
25	25
26	26		4. The reduced data is saved in the NeXus format and we want to extract out the data in plain text form. To do this, I created a Python script [`wksp2data.py`](https://pf.iris-home.net/yuanpeng/626459d2140f4ba6a6a61f1a7249604a). In the script, we specify that location to the reduced NeXus file and the output directory for hosting the extracted plain text data files.
27	27
28		-	5. The reduced data for some of those small detector groups are just bad, for some reason that we are not sure at this moment. Basically, they are pretty noisy so we want to remove them since otherwise they will mess up with the spherical harmonics corrections at later stage. In the [`wksp2data.py`](https://pf.iris-home.net/yuanpeng/626459d2140f4ba6a6a61f1a7249604a) script, I was specifying the output directory as `./texture_proc` (here follows, I will be assuming this as our output directory), meaning all the extracted data will be saved into `texture_proc` under the working directory. By 'working directory', I mean the directory where we ran the `mts` reduction and the `wksp2data.py` script. So, if things are working properly till this stage, you should see the following sub-directories in the `working directory`,
	28	+	5. The reduced data for some of those small detector groups are just bad, for some reason that we are not sure at this moment. Basically, they are pretty noisy so we want to remove them since otherwise they will mess up with the spherical harmonics corrections at the later stage. In the [`wksp2data.py`](https://pf.iris-home.net/yuanpeng/626459d2140f4ba6a6a61f1a7249604a) script, I was specifying the output directory as `./texture_proc` (here follows, I will be assuming this as our output directory), meaning all the extracted data will be saved into `texture_proc` under the working directory. By 'working directory', I mean the directory where we ran the `mts` reduction and the `wksp2data.py` script. So, if things are working properly till this stage, you should see the following sub-directories in the `working directory`,
29	29
30	30		```
31	31		GSAS
			@@ -40,7 +40,7 @@ Steps for Texture Correction
40	40		wksp2data.py
41	41		```
42	42
43		-	We want to run `mantidpython wksp2data.py`
	43	+	> We want to run `mantidpython wksp2data.py` for the data extraction.
44	44
45	45		We want to use the script [`remove_invalid_banks.py`](https://pf.iris-home.net/yuanpeng/2bc13a89757a40ff97bf0cebd75d8d5f) to remove those `bad` groups. The list of those `bad` groups is stored in [this](https://pf.iris-home.net/yuanpeng/4dbf30801c5f40bb8326ee784d17f60a) file. Copy these two files into the `texture_proc` directory, `cd` into `texture_proc` and run `python remove_invalid_banks.py`.
46	46

			@@ -40,6 +40,8 @@ Steps for Texture Correction
40	40		wksp2data.py
41	41		```
42	42
	43	+	We want to run `mantidpython wksp2data.py`
	44	+
43	45		We want to use the script [`remove_invalid_banks.py`](https://pf.iris-home.net/yuanpeng/2bc13a89757a40ff97bf0cebd75d8d5f) to remove those `bad` groups. The list of those `bad` groups is stored in [this](https://pf.iris-home.net/yuanpeng/4dbf30801c5f40bb8326ee784d17f60a) file. Copy these two files into the `texture_proc` directory, `cd` into `texture_proc` and run `python remove_invalid_banks.py`.
44	46
45	47		> Fortunately, this `bad` groups list is consistent between runs so we don't need to create the list again. In case we do need to, the dirty way is to plot all the reduced data for those small groups (could be several hundreds of them) and visually pick out those bad groups. This is exactly what I did to arrive at the list we are using here.

			@@ -86,6 +86,7 @@ Steps for Texture Correction
86	86		---
87	87
88	88		Yuanpeng Zhang @ 03/17/2025 14:18:09 EST
	89	+
89	90		SNS-HFIR, ORNL
90	91
91	92		---

			@@ -9,7 +9,7 @@ Steps for Texture Correction
9	9		mantidpython texture_group_gen.py
10	10		```
11	11
12		-	which will create the grouping file in XML format, named `nom_texture_grouping.xml`, together with a detector information file called `nom_texture_pointer.json` which contains the information about those generated small groups of detectors, like the corresponding polar and azimuthal angles and the group ID. We will be using this JSON file at later stage.
	12	+	which will create the grouping file in XML format, named `nom_texture_grouping.xml`, together with a detector information file called `nom_texture_pointer.json` which contains the information about those generated small groups of detectors, like the corresponding polar and azimuthal angles and the group ID. We will be using this JSON file at later stage.
13	13
14	14		2. Copy the grouping file from previous step to the location where we want to run the `MTS` reduction. In my case, I was working in `/SNS/users/y8z/Temp/Monika_IPTS-27956_Texture_Correction/silicon`, and [here](https://pf.iris-home.net/yuanpeng/cc8c9e40970e450fa7558839f934eda1) is the input file for running `MTS` with the grouping file provided. Then we need to run `MTS` reduction, with the command,
15	15

			@@ -5,9 +5,9 @@ Steps for Texture Correction
5	5
6	6		- Go to `/SNS/NOM/shared/scripts/texture` and run the `texture_group_gen.py` script like this,
7	7
8		-	```bash
9		-	mantidpython texture_group_gen.py
10		-	```
	8	+	```bash
	9	+	mantidpython texture_group_gen.py
	10	+	```
11	11
12	12		which will create the grouping file in XML format, named `nom_texture_grouping.xml`, together with a detector information file called `nom_texture_pointer.json` which contains the information about those generated small groups of detectors, like the corresponding polar and azimuthal angles and the group ID. We will be using this JSON file at later stage.
13	13