BranchesTags

Repository files navigation

Chandra Data Science 3ML Tutorial (Under Construction!)

A tutorial for the Chandra data science meeting

This tutorial covers the basics of:

  1. model building and fitting in 3ML
  2. x-ray analysis with the OGIPLike plugin
  3. advanced examples with joint fits of different plugins and advanced models

Examples make use of both Bayesian and maximum likelihood fitting techinques with a variety of packages. By the end of the tutorial you should have a basic idea of how to import x-ray data into 3ML, build models, perform fits, and save the results of an analysis to disk for distribution.

Running the tutorial

There are three ways you can run the tutorial ranging from easy to less easy.

Easy (Binder)

The tutorials live on a pre-built binder which has all the software installed and all the data needed already available. Just click the binder link below.

You can launch the binder here: Binder

Easy and Local (Docker)

You can install the 3ML notebook docker with the following instructions.

  1. To run this docker first pull it
docker pull threeml/notebook:latest
  1. Now clone this repo in a directory of your choosing:
git clone https://github.com/threeML/cds_tutorial.git
cd cds_tutorial
  1. Now you activate the docker with this command (note your choice of local port, here 8008)
docker run -it --rm -p 8008:8888 -v $PWD:/workdir -w /workdir threeml/notebook

then paste localhost:8008 in your browser and you are all set.

Advanced (install 3ML and dependencies)

Please do this before the tutorial. You can follow the installation instructions for 3ML and astromodels here

You can go with conda or pip, but I recommend some form of virtualenv to isolate your install.

If you go with conda, please use this enironment file:

name: threemlchannels:
- conda-forge
- threeml
- xspecmodels
- fermidependencies:
- astropy<4.3
- numpy
- scipy
- ultranest
- pygmo
- fermitools
- fermipy
- matplotlib
- dill
- pandas
- astromodels
- threeml
- xspec-modelsonly
- root==6.22
- pip
- pip:
- twopc
- jupyterthemes
- gbmgeometry
- gbm_drm_gen
- root_numpy

to ensure that you have all the required pacakges. Thus,

conda env create -f environment.yml
conda activate threeml

If you decided to go with pip, you will need to have all the external components you wish to use for the tutorials already installed. 3ML will warn you of things that are missing, e.g., multinest, ROOT, etc. You will also need to have a working installation of XSPEC installed if you wish to demo models comming from XSPEC. The tutorials can be run without these extra components. And you can always try them in the binder link above.

After installation, you can download the tutorial notebooks and start jupyter with:

git clone https://github.com/threeML/cds_tutorial.git
cd cds_tutorial

Questions

If you have questions, please post them as issues in this repo or email me jburgess@mpe.mpg.de

About

A tutorial for the Chandra data science meeting

Resources

Readme
Activity
Custom properties

Stars

2 stars

Watchers

3 watching

Forks

2 forks
Report repository

Releases

Packages

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
 blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

Skip to content
BranchesTags
Repository files navigation
Chandra Data Science 3ML Tutorial (Under Construction!)
A tutorial for the Chandra data science meeting
This tutorial covers the basics of:
  1. model building and fitting in 3ML
  2. x-ray analysis with the OGIPLike plugin
  3. advanced examples with joint fits of different plugins and advanced models
Examples make use of both Bayesian and maximum likelihood fitting techinques with a variety of packages. By the end of the tutorial you should have a basic idea of how to import x-ray data into 3ML, build models, perform fits, and save the results of an analysis to disk for distribution.
Running the tutorial
There are three ways you can run the tutorial ranging from easy to less easy.
Easy (Binder)
The tutorials live on a pre-built binder which has all the software installed and all the data needed already available. Just click the binder link below.
You can launch the binder here:
Binder
Easy and Local (Docker)
You can install the 3ML notebook docker with the following instructions.
  1. To run this docker first pull it
docker pull threeml/notebook:latest
  1. Now clone this repo in a directory of your choosing:
git clone https://github.com/threeML/cds_tutorial.git
cd cds_tutorial
  1. Now you activate the docker with this command (note your choice of local port, here 8008)
docker run -it --rm -p 8008:8888 -v $PWD:/workdir -w /workdir threeml/notebook
then paste localhost:8008 in your browser and you are all set.
Advanced (install 3ML and dependencies)
Please do this before the tutorial. You can follow the installation instructions for 3ML and astromodels here
You can go with conda or pip, but I recommend some form of virtualenv to isolate your install.
If you go with conda, please use this enironment file:
name: threemlchannels:
- conda-forge
- threeml
- xspecmodels
- fermidependencies:
- astropy<4.3
- numpy
- scipy
- ultranest
- pygmo
- fermitools
- fermipy
- matplotlib
- dill
- pandas
- astromodels
- threeml
- xspec-modelsonly
- root==6.22
- pip
- pip:
- twopc
- jupyterthemes
- gbmgeometry
- gbm_drm_gen
- root_numpy
to ensure that you have all the required pacakges. Thus,
conda env create -f environment.yml
conda activate threeml
If you decided to go with pip, you will need to have all the external components you wish to use for the tutorials already installed. 3ML will warn you of things that are missing, e.g., multinest, ROOT, etc. You will also need to have a working installation of XSPEC installed if you wish to demo models comming from XSPEC. The tutorials can be run without these extra components. And you can always try them in the binder link above.
After installation, you can download the tutorial notebooks and start jupyter with:
git clone https://github.com/threeML/cds_tutorial.git
cd cds_tutorial
Questions
If you have questions, please post them as issues in this repo or email me jburgess@mpe.mpg.de
About
A tutorial for the Chandra data science meeting
Resources
Readme
Activity
Custom properties
Stars
2 stars
Watchers
3 watching
Forks
2 forks
Report repository
Releases
Packages
Contributors
Languages

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

Skip to content
BranchesTags
Repository files navigation
Chandra Data Science 3ML Tutorial (Under Construction!)
A tutorial for the Chandra data science meeting
This tutorial covers the basics of:
  1. model building and fitting in 3ML
  2. x-ray analysis with the OGIPLike plugin
  3. advanced examples with joint fits of different plugins and advanced models
Examples make use of both Bayesian and maximum likelihood fitting techinques with a variety of packages. By the end of the tutorial you should have a basic idea of how to import x-ray data into 3ML, build models, perform fits, and save the results of an analysis to disk for distribution.
Running the tutorial
There are three ways you can run the tutorial ranging from easy to less easy.
Easy (Binder)
The tutorials live on a pre-built binder which has all the software installed and all the data needed already available. Just click the binder link below.
You can launch the binder here:
Binder
Easy and Local (Docker)
You can install the 3ML notebook docker with the following instructions.
  1. To run this docker first pull it
docker pull threeml/notebook:latest
  1. Now clone this repo in a directory of your choosing:
git clone https://github.com/threeML/cds_tutorial.git
cd cds_tutorial
  1. Now you activate the docker with this command (note your choice of local port, here 8008)
docker run -it --rm -p 8008:8888 -v $PWD:/workdir -w /workdir threeml/notebook
then paste localhost:8008 in your browser and you are all set.
Advanced (install 3ML and dependencies)
Please do this before the tutorial. You can follow the installation instructions for 3ML and astromodels here
You can go with conda or pip, but I recommend some form of virtualenv to isolate your install.
If you go with conda, please use this enironment file:
name: threemlchannels:
- conda-forge
- threeml
- xspecmodels
- fermidependencies:
- astropy<4.3
- numpy
- scipy
- ultranest
- pygmo
- fermitools
- fermipy
- matplotlib
- dill
- pandas
- astromodels
- threeml
- xspec-modelsonly
- root==6.22
- pip
- pip:
- twopc
- jupyterthemes
- gbmgeometry
- gbm_drm_gen
- root_numpy
to ensure that you have all the required pacakges. Thus,
conda env create -f environment.yml
conda activate threeml
If you decided to go with pip, you will need to have all the external components you wish to use for the tutorials already installed. 3ML will warn you of things that are missing, e.g., multinest, ROOT, etc. You will also need to have a working installation of XSPEC installed if you wish to demo models comming from XSPEC. The tutorials can be run without these extra components. And you can always try them in the binder link above.
After installation, you can download the tutorial notebooks and start jupyter with:
git clone https://github.com/threeML/cds_tutorial.git
cd cds_tutorial
Questions
If you have questions, please post them as issues in this repo or email me jburgess@mpe.mpg.de
About
A tutorial for the Chandra data science meeting
Resources
Readme
Activity
Custom properties
Stars
2 stars
Watchers
3 watching
Forks
2 forks
Report repository
Releases
Packages
Contributors
Languages

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

Skip to content
BranchesTags
Repository files navigation
Chandra Data Science 3ML Tutorial (Under Construction!)
A tutorial for the Chandra data science meeting
This tutorial covers the basics of:
  1. model building and fitting in 3ML
  2. x-ray analysis with the OGIPLike plugin
  3. advanced examples with joint fits of different plugins and advanced models
Examples make use of both Bayesian and maximum likelihood fitting techinques with a variety of packages. By the end of the tutorial you should have a basic idea of how to import x-ray data into 3ML, build models, perform fits, and save the results of an analysis to disk for distribution.
Running the tutorial
There are three ways you can run the tutorial ranging from easy to less easy.
Easy (Binder)
The tutorials live on a pre-built binder which has all the software installed and all the data needed already available. Just click the binder link below.
You can launch the binder here:
Binder
Easy and Local (Docker)
You can install the 3ML notebook docker with the following instructions.
  1. To run this docker first pull it
docker pull threeml/notebook:latest
  1. Now clone this repo in a directory of your choosing:
git clone https://github.com/threeML/cds_tutorial.git
cd cds_tutorial
  1. Now you activate the docker with this command (note your choice of local port, here 8008)
docker run -it --rm -p 8008:8888 -v $PWD:/workdir -w /workdir threeml/notebook
then paste localhost:8008 in your browser and you are all set.
Advanced (install 3ML and dependencies)
Please do this before the tutorial. You can follow the installation instructions for 3ML and astromodels here
You can go with conda or pip, but I recommend some form of virtualenv to isolate your install.
If you go with conda, please use this enironment file:
name: threemlchannels:
- conda-forge
- threeml
- xspecmodels
- fermidependencies:
- astropy<4.3
- numpy
- scipy
- ultranest
- pygmo
- fermitools
- fermipy
- matplotlib
- dill
- pandas
- astromodels
- threeml
- xspec-modelsonly
- root==6.22
- pip
- pip:
- twopc
- jupyterthemes
- gbmgeometry
- gbm_drm_gen
- root_numpy
to ensure that you have all the required pacakges. Thus,
conda env create -f environment.yml
conda activate threeml
If you decided to go with pip, you will need to have all the external components you wish to use for the tutorials already installed. 3ML will warn you of things that are missing, e.g., multinest, ROOT, etc. You will also need to have a working installation of XSPEC installed if you wish to demo models comming from XSPEC. The tutorials can be run without these extra components. And you can always try them in the binder link above.
After installation, you can download the tutorial notebooks and start jupyter with:
git clone https://github.com/threeML/cds_tutorial.git
cd cds_tutorial
Questions
If you have questions, please post them as issues in this repo or email me jburgess@mpe.mpg.de
About
A tutorial for the Chandra data science meeting
Resources
Readme
Activity
Custom properties
Stars
2 stars
Watchers
3 watching
Forks
2 forks
Report repository
Releases
Packages
Contributors
Languages

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

Skip to content
BranchesTags
Repository files navigation
Chandra Data Science 3ML Tutorial (Under Construction!)
A tutorial for the Chandra data science meeting
This tutorial covers the basics of:
  1. model building and fitting in 3ML
  2. x-ray analysis with the OGIPLike plugin
  3. advanced examples with joint fits of different plugins and advanced models
Examples make use of both Bayesian and maximum likelihood fitting techinques with a variety of packages. By the end of the tutorial you should have a basic idea of how to import x-ray data into 3ML, build models, perform fits, and save the results of an analysis to disk for distribution.
Running the tutorial
There are three ways you can run the tutorial ranging from easy to less easy.
Easy (Binder)
The tutorials live on a pre-built binder which has all the software installed and all the data needed already available. Just click the binder link below.
You can launch the binder here:
Binder
Easy and Local (Docker)
You can install the 3ML notebook docker with the following instructions.
  1. To run this docker first pull it
docker pull threeml/notebook:latest
  1. Now clone this repo in a directory of your choosing:
git clone https://github.com/threeML/cds_tutorial.git
cd cds_tutorial
  1. Now you activate the docker with this command (note your choice of local port, here 8008)
docker run -it --rm -p 8008:8888 -v $PWD:/workdir -w /workdir threeml/notebook
then paste localhost:8008 in your browser and you are all set.
Advanced (install 3ML and dependencies)
Please do this before the tutorial. You can follow the installation instructions for 3ML and astromodels here
You can go with conda or pip, but I recommend some form of virtualenv to isolate your install.
If you go with conda, please use this enironment file:
name: threemlchannels:
- conda-forge
- threeml
- xspecmodels
- fermidependencies:
- astropy<4.3
- numpy
- scipy
- ultranest
- pygmo
- fermitools
- fermipy
- matplotlib
- dill
- pandas
- astromodels
- threeml
- xspec-modelsonly
- root==6.22
- pip
- pip:
- twopc
- jupyterthemes
- gbmgeometry
- gbm_drm_gen
- root_numpy
to ensure that you have all the required pacakges. Thus,
conda env create -f environment.yml
conda activate threeml
If you decided to go with pip, you will need to have all the external components you wish to use for the tutorials already installed. 3ML will warn you of things that are missing, e.g., multinest, ROOT, etc. You will also need to have a working installation of XSPEC installed if you wish to demo models comming from XSPEC. The tutorials can be run without these extra components. And you can always try them in the binder link above.
After installation, you can download the tutorial notebooks and start jupyter with:
git clone https://github.com/threeML/cds_tutorial.git
cd cds_tutorial
Questions
If you have questions, please post them as issues in this repo or email me jburgess@mpe.mpg.de
About
A tutorial for the Chandra data science meeting
Resources
Readme
Activity
Custom properties
Stars
2 stars
Watchers
3 watching
Forks
2 forks
Report repository
Releases
Packages
Contributors
Languages

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

Skip to content
BranchesTags
Repository files navigation
Chandra Data Science 3ML Tutorial (Under Construction!)
A tutorial for the Chandra data science meeting
This tutorial covers the basics of:
  1. model building and fitting in 3ML
  2. x-ray analysis with the OGIPLike plugin
  3. advanced examples with joint fits of different plugins and advanced models
Examples make use of both Bayesian and maximum likelihood fitting techinques with a variety of packages. By the end of the tutorial you should have a basic idea of how to import x-ray data into 3ML, build models, perform fits, and save the results of an analysis to disk for distribution.
Running the tutorial
There are three ways you can run the tutorial ranging from easy to less easy.
Easy (Binder)
The tutorials live on a pre-built binder which has all the software installed and all the data needed already available. Just click the binder link below.
You can launch the binder here:
Binder
Easy and Local (Docker)
You can install the 3ML notebook docker with the following instructions.
  1. To run this docker first pull it
docker pull threeml/notebook:latest
  1. Now clone this repo in a directory of your choosing:
git clone https://github.com/threeML/cds_tutorial.git
cd cds_tutorial
  1. Now you activate the docker with this command (note your choice of local port, here 8008)
docker run -it --rm -p 8008:8888 -v $PWD:/workdir -w /workdir threeml/notebook
then paste localhost:8008 in your browser and you are all set.
Advanced (install 3ML and dependencies)
Please do this before the tutorial. You can follow the installation instructions for 3ML and astromodels here
You can go with conda or pip, but I recommend some form of virtualenv to isolate your install.
If you go with conda, please use this enironment file:
name: threemlchannels:
- conda-forge
- threeml
- xspecmodels
- fermidependencies:
- astropy<4.3
- numpy
- scipy
- ultranest
- pygmo
- fermitools
- fermipy
- matplotlib
- dill
- pandas
- astromodels
- threeml
- xspec-modelsonly
- root==6.22
- pip
- pip:
- twopc
- jupyterthemes
- gbmgeometry
- gbm_drm_gen
- root_numpy
to ensure that you have all the required pacakges. Thus,
conda env create -f environment.yml
conda activate threeml
If you decided to go with pip, you will need to have all the external components you wish to use for the tutorials already installed. 3ML will warn you of things that are missing, e.g., multinest, ROOT, etc. You will also need to have a working installation of XSPEC installed if you wish to demo models comming from XSPEC. The tutorials can be run without these extra components. And you can always try them in the binder link above.
After installation, you can download the tutorial notebooks and start jupyter with:
git clone https://github.com/threeML/cds_tutorial.git
cd cds_tutorial
Questions
If you have questions, please post them as issues in this repo or email me jburgess@mpe.mpg.de
About
A tutorial for the Chandra data science meeting
Resources
Readme
Activity
Custom properties
Stars
2 stars
Watchers
3 watching
Forks
2 forks
Report repository
Releases
Packages
Contributors
Languages

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

Skip to content
BranchesTags
Repository files navigation
Chandra Data Science 3ML Tutorial (Under Construction!)
A tutorial for the Chandra data science meeting
This tutorial covers the basics of:
  1. model building and fitting in 3ML
  2. x-ray analysis with the OGIPLike plugin
  3. advanced examples with joint fits of different plugins and advanced models
Examples make use of both Bayesian and maximum likelihood fitting techinques with a variety of packages. By the end of the tutorial you should have a basic idea of how to import x-ray data into 3ML, build models, perform fits, and save the results of an analysis to disk for distribution.
Running the tutorial
There are three ways you can run the tutorial ranging from easy to less easy.
Easy (Binder)
The tutorials live on a pre-built binder which has all the software installed and all the data needed already available. Just click the binder link below.
You can launch the binder here:
Binder
Easy and Local (Docker)
You can install the 3ML notebook docker with the following instructions.
  1. To run this docker first pull it
docker pull threeml/notebook:latest
  1. Now clone this repo in a directory of your choosing:
git clone https://github.com/threeML/cds_tutorial.git
cd cds_tutorial
  1. Now you activate the docker with this command (note your choice of local port, here 8008)
docker run -it --rm -p 8008:8888 -v $PWD:/workdir -w /workdir threeml/notebook
then paste localhost:8008 in your browser and you are all set.
Advanced (install 3ML and dependencies)
Please do this before the tutorial. You can follow the installation instructions for 3ML and astromodels here
You can go with conda or pip, but I recommend some form of virtualenv to isolate your install.
If you go with conda, please use this enironment file:
name: threemlchannels:
- conda-forge
- threeml
- xspecmodels
- fermidependencies:
- astropy<4.3
- numpy
- scipy
- ultranest
- pygmo
- fermitools
- fermipy
- matplotlib
- dill
- pandas
- astromodels
- threeml
- xspec-modelsonly
- root==6.22
- pip
- pip:
- twopc
- jupyterthemes
- gbmgeometry
- gbm_drm_gen
- root_numpy
to ensure that you have all the required pacakges. Thus,
conda env create -f environment.yml
conda activate threeml
If you decided to go with pip, you will need to have all the external components you wish to use for the tutorials already installed. 3ML will warn you of things that are missing, e.g., multinest, ROOT, etc. You will also need to have a working installation of XSPEC installed if you wish to demo models comming from XSPEC. The tutorials can be run without these extra components. And you can always try them in the binder link above.
After installation, you can download the tutorial notebooks and start jupyter with:
git clone https://github.com/threeML/cds_tutorial.git
cd cds_tutorial
Questions
If you have questions, please post them as issues in this repo or email me jburgess@mpe.mpg.de
About
A tutorial for the Chandra data science meeting
Resources
Readme
Activity
Custom properties
Stars
2 stars
Watchers
3 watching
Forks
2 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

Skip to content
BranchesTags
Repository files navigation
Chandra Data Science 3ML Tutorial (Under Construction!)
A tutorial for the Chandra data science meeting
This tutorial covers the basics of:
  1. model building and fitting in 3ML
  2. x-ray analysis with the OGIPLike plugin
  3. advanced examples with joint fits of different plugins and advanced models
Examples make use of both Bayesian and maximum likelihood fitting techinques with a variety of packages. By the end of the tutorial you should have a basic idea of how to import x-ray data into 3ML, build models, perform fits, and save the results of an analysis to disk for distribution.
Running the tutorial
There are three ways you can run the tutorial ranging from easy to less easy.
Easy (Binder)
The tutorials live on a pre-built binder which has all the software installed and all the data needed already available. Just click the binder link below.
You can launch the binder here:
Binder
Easy and Local (Docker)
You can install the 3ML notebook docker with the following instructions.
  1. To run this docker first pull it
docker pull threeml/notebook:latest
  1. Now clone this repo in a directory of your choosing:
git clone https://github.com/threeML/cds_tutorial.git
cd cds_tutorial
  1. Now you activate the docker with this command (note your choice of local port, here 8008)
docker run -it --rm -p 8008:8888 -v $PWD:/workdir -w /workdir threeml/notebook
then paste localhost:8008 in your browser and you are all set.
Advanced (install 3ML and dependencies)
Please do this before the tutorial. You can follow the installation instructions for 3ML and astromodels here
You can go with conda or pip, but I recommend some form of virtualenv to isolate your install.
If you go with conda, please use this enironment file:
name: threemlchannels:
- conda-forge
- threeml
- xspecmodels
- fermidependencies:
- astropy<4.3
- numpy
- scipy
- ultranest
- pygmo
- fermitools
- fermipy
- matplotlib
- dill
- pandas
- astromodels
- threeml
- xspec-modelsonly
- root==6.22
- pip
- pip:
- twopc
- jupyterthemes
- gbmgeometry
- gbm_drm_gen
- root_numpy
to ensure that you have all the required pacakges. Thus,
conda env create -f environment.yml
conda activate threeml
If you decided to go with pip, you will need to have all the external components you wish to use for the tutorials already installed. 3ML will warn you of things that are missing, e.g., multinest, ROOT, etc. You will also need to have a working installation of XSPEC installed if you wish to demo models comming from XSPEC. The tutorials can be run without these extra components. And you can always try them in the binder link above.
After installation, you can download the tutorial notebooks and start jupyter with:
git clone https://github.com/threeML/cds_tutorial.git
cd cds_tutorial
Questions
If you have questions, please post them as issues in this repo or email me jburgess@mpe.mpg.de
About
A tutorial for the Chandra data science meeting
Resources
Readme
Activity
Custom properties
Stars
2 stars
Watchers
3 watching
Forks
2 forks
Report repository
Releases
Packages
Contributors
Languages