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python_codes_for_DREAM

contains the python scripts to generate the voxel table for the DREAM detectors

Scripts written by Irina Stefanescu, ESS NSS Detector Group and Celine Durniak, ESS DMSC DRAM Group

irina.stefanescu@ess.eu

Description

To be completed

One Python script per detectors' part ,i.e., EndCap FORWARD (SUMO3, SUMO4, SUMO5, SUMO6), EndCap BACKWARD (SUMO3, SUMO4, SUMO5, SUMO6), Mantle, High-resolution and SANS.

File lists:

  • DREAMHR_calculate_voxels.py
  • DREAMMantle_calculate_voxels.py
  • DREAMSUMO3_calculate_voxels.py
  • DREAMSUMO4_calculate_voxels.py
  • DREAMSUMO5_calculate_voxels.py
  • DREAMSUMO6_calculate_voxels.py
  • DREAMSANS_calculate_voxels.py
  • dream.py
  • globals.py
  • run_scripts.py

The result of the calculation with run_scripts.py is a number of txt files (one per detector (sub)system) containing the information on the location (x, y, z coordinates with respect to the sample position at (0, 0, 0)) and shape parameters (trapezoidal) of each individual detector voxel along with some hardware information (wire number, strip number, segment number, module number) that will make it possible to match the calculated detector voxels to the real ones (when available). The number of Mantle and EndCap detector modules included in the calculation can be controlled from the globals.py file. The file DREAMAll_voxels.txt is obtained through the concatenation of the (sub)system files and it is used by the script dream.py to generate the off- and nxs-files of the DREAM detector.

Installation and usage

  • Create and activate a virtual environment in the folder containing the scripts using Python 3 (tested with Python 3.9). In the following we assume that python refers to the version of Python you want to use.

    python -m venv .venv
    source .venv/bin/activate
    

    Executing this last command should change the prompt of your terminal. It should now start with (.venv).

  • Upgrade pip (optional)

    python -m pip install --upgrade pip
    
  • Install the required libraries

    python -m pip install -r requirements.txt
    
  • Generate the tables of voxels for all detector sub-systems for DREAM.

    python run_scripts.py
    

    You can comment out the tables not needed for your studies before running the above command.

  • To deactivate the virtual environment, simply type deactivate in the terminal. The prompt should change back to its initial state. And if you do not need this environment, you can simply delete the .venv folder.

see here the result of the calculation: https://github.com/ess-dg/python_codes_for_DREAM/wiki

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contains python codes to generate the voxel table for the DREAM detectors

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GitHub - ess-dg/python_codes_for_DREAM: contains python codes to generate the voxel table for the DREAM detectors · GitHub
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python_codes_for_DREAM

contains the python scripts to generate the voxel table for the DREAM detectors

Scripts written by Irina Stefanescu, ESS NSS Detector Group and Celine Durniak, ESS DMSC DRAM Group

irina.stefanescu@ess.eu

Description

To be completed

One Python script per detectors' part ,i.e., EndCap FORWARD (SUMO3, SUMO4, SUMO5, SUMO6), EndCap BACKWARD (SUMO3, SUMO4, SUMO5, SUMO6), Mantle, High-resolution and SANS.

File lists:

  • DREAMHR_calculate_voxels.py
  • DREAMMantle_calculate_voxels.py
  • DREAMSUMO3_calculate_voxels.py
  • DREAMSUMO4_calculate_voxels.py
  • DREAMSUMO5_calculate_voxels.py
  • DREAMSUMO6_calculate_voxels.py
  • DREAMSANS_calculate_voxels.py
  • dream.py
  • globals.py
  • run_scripts.py

The result of the calculation with run_scripts.py is a number of txt files (one per detector (sub)system) containing the information on the location (x, y, z coordinates with respect to the sample position at (0, 0, 0)) and shape parameters (trapezoidal) of each individual detector voxel along with some hardware information (wire number, strip number, segment number, module number) that will make it possible to match the calculated detector voxels to the real ones (when available). The number of Mantle and EndCap detector modules included in the calculation can be controlled from the globals.py file. The file DREAMAll_voxels.txt is obtained through the concatenation of the (sub)system files and it is used by the script dream.py to generate the off- and nxs-files of the DREAM detector.

Installation and usage

  • Create and activate a virtual environment in the folder containing the scripts using Python 3 (tested with Python 3.9). In the following we assume that python refers to the version of Python you want to use.

    python -m venv .venv
    source .venv/bin/activate
    

    Executing this last command should change the prompt of your terminal. It should now start with (.venv).

  • Upgrade pip (optional)

    python -m pip install --upgrade pip
    
  • Install the required libraries

    python -m pip install -r requirements.txt
    
  • Generate the tables of voxels for all detector sub-systems for DREAM.

    python run_scripts.py
    

    You can comment out the tables not needed for your studies before running the above command.

  • To deactivate the virtual environment, simply type deactivate in the terminal. The prompt should change back to its initial state. And if you do not need this environment, you can simply delete the .venv folder.

see here the result of the calculation: https://github.com/ess-dg/python_codes_for_DREAM/wiki

About

contains python codes to generate the voxel table for the DREAM detectors

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, 'i'); if (__m === '*' || __re.test(location.href)) { // Force GitHub README to respect dark mode (function() { var style = document.createElement('style'); style.textContent = ' .markdown-body { color-scheme: dark light; } .markdown-body pre { background: #161b22 !important; } .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; } .markdown-body table th, .markdown-body table td { border-color: #30363d !important; } .markdown-body img { background: #0d1117; } .markdown-body blockquote { border-left-color: #8b949e; } .markdown-body hr { border-color: #30363d; } '; document.head.appendChild(style); })(); } } catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + ' GitHub - ess-dg/python_codes_for_DREAM: contains python codes to generate the voxel table for the DREAM detectors · GitHub
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python_codes_for_DREAM

contains the python scripts to generate the voxel table for the DREAM detectors

Scripts written by Irina Stefanescu, ESS NSS Detector Group and Celine Durniak, ESS DMSC DRAM Group

irina.stefanescu@ess.eu

Description

To be completed

One Python script per detectors' part ,i.e., EndCap FORWARD (SUMO3, SUMO4, SUMO5, SUMO6), EndCap BACKWARD (SUMO3, SUMO4, SUMO5, SUMO6), Mantle, High-resolution and SANS.

File lists:

  • DREAMHR_calculate_voxels.py
  • DREAMMantle_calculate_voxels.py
  • DREAMSUMO3_calculate_voxels.py
  • DREAMSUMO4_calculate_voxels.py
  • DREAMSUMO5_calculate_voxels.py
  • DREAMSUMO6_calculate_voxels.py
  • DREAMSANS_calculate_voxels.py
  • dream.py
  • globals.py
  • run_scripts.py

The result of the calculation with run_scripts.py is a number of txt files (one per detector (sub)system) containing the information on the location (x, y, z coordinates with respect to the sample position at (0, 0, 0)) and shape parameters (trapezoidal) of each individual detector voxel along with some hardware information (wire number, strip number, segment number, module number) that will make it possible to match the calculated detector voxels to the real ones (when available). The number of Mantle and EndCap detector modules included in the calculation can be controlled from the globals.py file. The file DREAMAll_voxels.txt is obtained through the concatenation of the (sub)system files and it is used by the script dream.py to generate the off- and nxs-files of the DREAM detector.

Installation and usage

  • Create and activate a virtual environment in the folder containing the scripts using Python 3 (tested with Python 3.9). In the following we assume that python refers to the version of Python you want to use.

    python -m venv .venv
    source .venv/bin/activate
    

    Executing this last command should change the prompt of your terminal. It should now start with (.venv).

  • Upgrade pip (optional)

    python -m pip install --upgrade pip
    
  • Install the required libraries

    python -m pip install -r requirements.txt
    
  • Generate the tables of voxels for all detector sub-systems for DREAM.

    python run_scripts.py
    

    You can comment out the tables not needed for your studies before running the above command.

  • To deactivate the virtual environment, simply type deactivate in the terminal. The prompt should change back to its initial state. And if you do not need this environment, you can simply delete the .venv folder.

see here the result of the calculation: https://github.com/ess-dg/python_codes_for_DREAM/wiki

About

contains python codes to generate the voxel table for the DREAM detectors

Resources

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0 stars

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2 watching

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, 'i'); if (__m === '*' || __re.test(location.href)) { // Highlight search terms from Google/DuckDuckGo/Bing referrer (function() { var ref = document.referrer; var terms = []; if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) { var url = new URL(ref); var q = url.searchParams.get('q') || url.searchParams.get('p'); if (q) { terms = q.split(/\s+/).filter(function(t) { return t.length > 2; }); } } if (terms.length === 0) return; var style = document.createElement('style'); style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }'; document.head.appendChild(style); function highlight(node) { if (node.nodeType === 3) { // text node var text = node.textContent; var found = false; terms.forEach(function(term) { var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\]\\]/g, '\\') + ')', 'gi'); if (regex.test(text)) { found = true; var frag = document.createDocumentFragment(); var parts = text.split(regex); parts.forEach(function(part, i) { if (i % 2 === 0) { frag.appendChild(document.createTextNode(part)); } else { var span = document.createElement('span'); span.className = 'userscript-highlight'; span.textContent = part; frag.appendChild(span); } }); node.parentNode.replaceChild(frag, node); } }); } else if (node.nodeType === 1 && node.childNodes) { // element var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT']; if (!skipTags.includes(node.tagName)) { Array.from(node.childNodes).forEach(highlight); } } } highlight(document.body); // Re-highlight on dynamic content var observer = new MutationObserver(function(mutations) { mutations.forEach(function(m) { m.addedNodes.forEach(function(node) { if (node.nodeType === 1 || node.nodeType === 3) highlight(node); }); }); }); observer.observe(document.body, { childList: true, subtree: true }); })(); } } catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + ' GitHub - ess-dg/python_codes_for_DREAM: contains python codes to generate the voxel table for the DREAM detectors · GitHub
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python_codes_for_DREAM

contains the python scripts to generate the voxel table for the DREAM detectors

Scripts written by Irina Stefanescu, ESS NSS Detector Group and Celine Durniak, ESS DMSC DRAM Group

irina.stefanescu@ess.eu

Description

To be completed

One Python script per detectors' part ,i.e., EndCap FORWARD (SUMO3, SUMO4, SUMO5, SUMO6), EndCap BACKWARD (SUMO3, SUMO4, SUMO5, SUMO6), Mantle, High-resolution and SANS.

File lists:

  • DREAMHR_calculate_voxels.py
  • DREAMMantle_calculate_voxels.py
  • DREAMSUMO3_calculate_voxels.py
  • DREAMSUMO4_calculate_voxels.py
  • DREAMSUMO5_calculate_voxels.py
  • DREAMSUMO6_calculate_voxels.py
  • DREAMSANS_calculate_voxels.py
  • dream.py
  • globals.py
  • run_scripts.py

The result of the calculation with run_scripts.py is a number of txt files (one per detector (sub)system) containing the information on the location (x, y, z coordinates with respect to the sample position at (0, 0, 0)) and shape parameters (trapezoidal) of each individual detector voxel along with some hardware information (wire number, strip number, segment number, module number) that will make it possible to match the calculated detector voxels to the real ones (when available). The number of Mantle and EndCap detector modules included in the calculation can be controlled from the globals.py file. The file DREAMAll_voxels.txt is obtained through the concatenation of the (sub)system files and it is used by the script dream.py to generate the off- and nxs-files of the DREAM detector.

Installation and usage

  • Create and activate a virtual environment in the folder containing the scripts using Python 3 (tested with Python 3.9). In the following we assume that python refers to the version of Python you want to use.

    python -m venv .venv
    source .venv/bin/activate
    

    Executing this last command should change the prompt of your terminal. It should now start with (.venv).

  • Upgrade pip (optional)

    python -m pip install --upgrade pip
    
  • Install the required libraries

    python -m pip install -r requirements.txt
    
  • Generate the tables of voxels for all detector sub-systems for DREAM.

    python run_scripts.py
    

    You can comment out the tables not needed for your studies before running the above command.

  • To deactivate the virtual environment, simply type deactivate in the terminal. The prompt should change back to its initial state. And if you do not need this environment, you can simply delete the .venv folder.

see here the result of the calculation: https://github.com/ess-dg/python_codes_for_DREAM/wiki

About

contains python codes to generate the voxel table for the DREAM detectors

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, 'i'); if (__m === '*' || __re.test(location.href)) { // Strip utm_, fbclid, gclid, etc. from all links on page (function() { var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content', 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid', 'ref', 'ref_src', 'source', 'medium', 'campaign']; function cleanUrl(url) { try { var u = new URL(url, window.location.origin); var changed = false; trackingParams.forEach(function(p) { if (u.searchParams.has(p)) { u.searchParams.delete(p); changed = true; } }); return changed ? u.toString() : url; } catch (e) { return url; } } function cleanLinks() { document.querySelectorAll('a[href]').forEach(function(a) { var clean = cleanUrl(a.href); if (clean !== a.href) a.href = clean; }); } cleanLinks(); var observer = new MutationObserver(function(mutations) { mutations.forEach(function(m) { m.addedNodes.forEach(function(node) { if (node.nodeType === 1) { if (node.tagName === 'A') cleanLinks(); node.querySelectorAll('a[href]').forEach(function(a) { var clean = cleanUrl(a.href); if (clean !== a.href) a.href = clean; }); } }); }); }); observer.observe(document.body, { childList: true, subtree: true }); })(); } } catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); } })(); (function(){ try { var __m = "youtube.com"; var __re = new RegExp('^' + "youtube\\.com" + ' GitHub - ess-dg/python_codes_for_DREAM: contains python codes to generate the voxel table for the DREAM detectors · GitHub
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python_codes_for_DREAM

contains the python scripts to generate the voxel table for the DREAM detectors

Scripts written by Irina Stefanescu, ESS NSS Detector Group and Celine Durniak, ESS DMSC DRAM Group

irina.stefanescu@ess.eu

Description

To be completed

One Python script per detectors' part ,i.e., EndCap FORWARD (SUMO3, SUMO4, SUMO5, SUMO6), EndCap BACKWARD (SUMO3, SUMO4, SUMO5, SUMO6), Mantle, High-resolution and SANS.

File lists:

  • DREAMHR_calculate_voxels.py
  • DREAMMantle_calculate_voxels.py
  • DREAMSUMO3_calculate_voxels.py
  • DREAMSUMO4_calculate_voxels.py
  • DREAMSUMO5_calculate_voxels.py
  • DREAMSUMO6_calculate_voxels.py
  • DREAMSANS_calculate_voxels.py
  • dream.py
  • globals.py
  • run_scripts.py

The result of the calculation with run_scripts.py is a number of txt files (one per detector (sub)system) containing the information on the location (x, y, z coordinates with respect to the sample position at (0, 0, 0)) and shape parameters (trapezoidal) of each individual detector voxel along with some hardware information (wire number, strip number, segment number, module number) that will make it possible to match the calculated detector voxels to the real ones (when available). The number of Mantle and EndCap detector modules included in the calculation can be controlled from the globals.py file. The file DREAMAll_voxels.txt is obtained through the concatenation of the (sub)system files and it is used by the script dream.py to generate the off- and nxs-files of the DREAM detector.

Installation and usage

  • Create and activate a virtual environment in the folder containing the scripts using Python 3 (tested with Python 3.9). In the following we assume that python refers to the version of Python you want to use.

    python -m venv .venv
    source .venv/bin/activate
    

    Executing this last command should change the prompt of your terminal. It should now start with (.venv).

  • Upgrade pip (optional)

    python -m pip install --upgrade pip
    
  • Install the required libraries

    python -m pip install -r requirements.txt
    
  • Generate the tables of voxels for all detector sub-systems for DREAM.

    python run_scripts.py
    

    You can comment out the tables not needed for your studies before running the above command.

  • To deactivate the virtual environment, simply type deactivate in the terminal. The prompt should change back to its initial state. And if you do not need this environment, you can simply delete the .venv folder.

see here the result of the calculation: https://github.com/ess-dg/python_codes_for_DREAM/wiki

About

contains python codes to generate the voxel table for the DREAM detectors

Resources

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2 watching

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Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { // Auto-enable theater mode on YouTube (function() { function tryTheater() { var btn = document.querySelector('button[aria-label="Theater mode"], ytd-player #player button[title="Theater mode"]'); if (btn && !btn.classList.contains('activated')) { btn.click(); } } // Try immediately tryTheater(); // Try after navigation (SPA) var lastUrl = location.href; setInterval(function() { if (location.href !== lastUrl) { lastUrl = location.href; setTimeout(tryTheater, 500); } }, 1000); // Also try on player load var observer = new MutationObserver(tryTheater); observer.observe(document.body, { childList: true, subtree: true }); })(); } } catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + ' GitHub - ess-dg/python_codes_for_DREAM: contains python codes to generate the voxel table for the DREAM detectors · GitHub
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python_codes_for_DREAM

contains the python scripts to generate the voxel table for the DREAM detectors

Scripts written by Irina Stefanescu, ESS NSS Detector Group and Celine Durniak, ESS DMSC DRAM Group

irina.stefanescu@ess.eu

Description

To be completed

One Python script per detectors' part ,i.e., EndCap FORWARD (SUMO3, SUMO4, SUMO5, SUMO6), EndCap BACKWARD (SUMO3, SUMO4, SUMO5, SUMO6), Mantle, High-resolution and SANS.

File lists:

  • DREAMHR_calculate_voxels.py
  • DREAMMantle_calculate_voxels.py
  • DREAMSUMO3_calculate_voxels.py
  • DREAMSUMO4_calculate_voxels.py
  • DREAMSUMO5_calculate_voxels.py
  • DREAMSUMO6_calculate_voxels.py
  • DREAMSANS_calculate_voxels.py
  • dream.py
  • globals.py
  • run_scripts.py

The result of the calculation with run_scripts.py is a number of txt files (one per detector (sub)system) containing the information on the location (x, y, z coordinates with respect to the sample position at (0, 0, 0)) and shape parameters (trapezoidal) of each individual detector voxel along with some hardware information (wire number, strip number, segment number, module number) that will make it possible to match the calculated detector voxels to the real ones (when available). The number of Mantle and EndCap detector modules included in the calculation can be controlled from the globals.py file. The file DREAMAll_voxels.txt is obtained through the concatenation of the (sub)system files and it is used by the script dream.py to generate the off- and nxs-files of the DREAM detector.

Installation and usage

  • Create and activate a virtual environment in the folder containing the scripts using Python 3 (tested with Python 3.9). In the following we assume that python refers to the version of Python you want to use.

    python -m venv .venv
    source .venv/bin/activate
    

    Executing this last command should change the prompt of your terminal. It should now start with (.venv).

  • Upgrade pip (optional)

    python -m pip install --upgrade pip
    
  • Install the required libraries

    python -m pip install -r requirements.txt
    
  • Generate the tables of voxels for all detector sub-systems for DREAM.

    python run_scripts.py
    

    You can comment out the tables not needed for your studies before running the above command.

  • To deactivate the virtual environment, simply type deactivate in the terminal. The prompt should change back to its initial state. And if you do not need this environment, you can simply delete the .venv folder.

see here the result of the calculation: https://github.com/ess-dg/python_codes_for_DREAM/wiki

About

contains python codes to generate the voxel table for the DREAM detectors

Resources

Stars

0 stars

Watchers

2 watching

Forks

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Packages

Used by

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { // Remove or un-stick sticky/fixed headers that block content (function() { function unstick() { document.querySelectorAll('header, nav, [role="banner"], .header, .navbar, .sticky, .fixed-top, [style*="position: fixed"], [style*="position:sticky"]').forEach(function(el) { if (el.style.position === 'fixed' || el.style.position === 'sticky' || getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') { el.style.position = 'static'; el.style.top = 'auto'; el.style.zIndex = 'auto'; } }); } unstick(); var observer = new MutationObserver(unstick); observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] }); })(); } } catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + ' GitHub - ess-dg/python_codes_for_DREAM: contains python codes to generate the voxel table for the DREAM detectors · GitHub
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python_codes_for_DREAM

contains the python scripts to generate the voxel table for the DREAM detectors

Scripts written by Irina Stefanescu, ESS NSS Detector Group and Celine Durniak, ESS DMSC DRAM Group

irina.stefanescu@ess.eu

Description

To be completed

One Python script per detectors' part ,i.e., EndCap FORWARD (SUMO3, SUMO4, SUMO5, SUMO6), EndCap BACKWARD (SUMO3, SUMO4, SUMO5, SUMO6), Mantle, High-resolution and SANS.

File lists:

  • DREAMHR_calculate_voxels.py
  • DREAMMantle_calculate_voxels.py
  • DREAMSUMO3_calculate_voxels.py
  • DREAMSUMO4_calculate_voxels.py
  • DREAMSUMO5_calculate_voxels.py
  • DREAMSUMO6_calculate_voxels.py
  • DREAMSANS_calculate_voxels.py
  • dream.py
  • globals.py
  • run_scripts.py

The result of the calculation with run_scripts.py is a number of txt files (one per detector (sub)system) containing the information on the location (x, y, z coordinates with respect to the sample position at (0, 0, 0)) and shape parameters (trapezoidal) of each individual detector voxel along with some hardware information (wire number, strip number, segment number, module number) that will make it possible to match the calculated detector voxels to the real ones (when available). The number of Mantle and EndCap detector modules included in the calculation can be controlled from the globals.py file. The file DREAMAll_voxels.txt is obtained through the concatenation of the (sub)system files and it is used by the script dream.py to generate the off- and nxs-files of the DREAM detector.

Installation and usage

  • Create and activate a virtual environment in the folder containing the scripts using Python 3 (tested with Python 3.9). In the following we assume that python refers to the version of Python you want to use.

    python -m venv .venv
    source .venv/bin/activate
    

    Executing this last command should change the prompt of your terminal. It should now start with (.venv).

  • Upgrade pip (optional)

    python -m pip install --upgrade pip
    
  • Install the required libraries

    python -m pip install -r requirements.txt
    
  • Generate the tables of voxels for all detector sub-systems for DREAM.

    python run_scripts.py
    

    You can comment out the tables not needed for your studies before running the above command.

  • To deactivate the virtual environment, simply type deactivate in the terminal. The prompt should change back to its initial state. And if you do not need this environment, you can simply delete the .venv folder.

see here the result of the calculation: https://github.com/ess-dg/python_codes_for_DREAM/wiki

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python_codes_for_DREAM

contains the python scripts to generate the voxel table for the DREAM detectors

Scripts written by Irina Stefanescu, ESS NSS Detector Group and Celine Durniak, ESS DMSC DRAM Group

irina.stefanescu@ess.eu

Description

To be completed

One Python script per detectors' part ,i.e., EndCap FORWARD (SUMO3, SUMO4, SUMO5, SUMO6), EndCap BACKWARD (SUMO3, SUMO4, SUMO5, SUMO6), Mantle, High-resolution and SANS.

File lists:

  • DREAMHR_calculate_voxels.py
  • DREAMMantle_calculate_voxels.py
  • DREAMSUMO3_calculate_voxels.py
  • DREAMSUMO4_calculate_voxels.py
  • DREAMSUMO5_calculate_voxels.py
  • DREAMSUMO6_calculate_voxels.py
  • DREAMSANS_calculate_voxels.py
  • dream.py
  • globals.py
  • run_scripts.py

The result of the calculation with run_scripts.py is a number of txt files (one per detector (sub)system) containing the information on the location (x, y, z coordinates with respect to the sample position at (0, 0, 0)) and shape parameters (trapezoidal) of each individual detector voxel along with some hardware information (wire number, strip number, segment number, module number) that will make it possible to match the calculated detector voxels to the real ones (when available). The number of Mantle and EndCap detector modules included in the calculation can be controlled from the globals.py file. The file DREAMAll_voxels.txt is obtained through the concatenation of the (sub)system files and it is used by the script dream.py to generate the off- and nxs-files of the DREAM detector.

Installation and usage

  • Create and activate a virtual environment in the folder containing the scripts using Python 3 (tested with Python 3.9). In the following we assume that python refers to the version of Python you want to use.

    python -m venv .venv
    source .venv/bin/activate
    

    Executing this last command should change the prompt of your terminal. It should now start with (.venv).

  • Upgrade pip (optional)

    python -m pip install --upgrade pip
    
  • Install the required libraries

    python -m pip install -r requirements.txt
    
  • Generate the tables of voxels for all detector sub-systems for DREAM.

    python run_scripts.py
    

    You can comment out the tables not needed for your studies before running the above command.

  • To deactivate the virtual environment, simply type deactivate in the terminal. The prompt should change back to its initial state. And if you do not need this environment, you can simply delete the .venv folder.

see here the result of the calculation: https://github.com/ess-dg/python_codes_for_DREAM/wiki

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contains python codes to generate the voxel table for the DREAM detectors

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