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Inscopy

Inscopy is a set of Python scripts for quick and convenient analysis of Inscopix miniscope data.

Input data

Example Cells

Overview of the cells included in the example data 'Mouse3_AC1' as identified by the Inscopix software. Input data are the .csv files. Usually one with the fluorescence of the identified cells and one with TTL stamps.

Code

All functions and classes used in Inscopy are annotated. The most important functions are in the file 'main.py'. This file can be run as a stand alone library if you prefer to do your analysis from the command line. There is a variable called 'run_example' if this variable is set to True (default) it will run some example analysis on the input data.

# Will run example analyses on the included example data$python -i main.py
# Will run example analyses on the files new_mouse_test.csv and new_mouse_TTL_test.csv$python -i main.py new_mouse

Jupyter Notebook

Most users will prefer to walk trough an analysis of an example mouse using the included Jupyter notebook, 'Inscopy_Jupyter.ipynb'. Jupyter Notebooks can be run on your system after you install the Jupyter Notebook program. The easiest way to do this is by first installing Anaconda and to follow the guidelines here.

About

A set of Python scripts to load and analyze Inscopix miniscope data.

Resources

Readme
MIT license
Activity

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1 star

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, '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" + '

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Repository files navigation
Inscopy
Inscopy is a set of Python scripts for quick and convenient analysis of Inscopix miniscope data.
Input data
Example Cells

Overview of the cells included in the example data 'Mouse3_AC1' as identified by the Inscopix software.
Input data are the .csv files. Usually one with the fluorescence of the identified cells and one with TTL stamps.

Code
All functions and classes used in Inscopy are annotated. The most important functions are in the file 'main.py'. This file can be run as a stand alone library if you prefer to do your analysis from the command line. There is a variable called 'run_example' if this variable is set to True (default) it will run some example analysis on the input data.
# Will run example analyses on the included example data$python -i main.py
# Will run example analyses on the files new_mouse_test.csv and new_mouse_TTL_test.csv$python -i main.py new_mouse

Jupyter Notebook
Most users will prefer to walk trough an analysis of an example mouse using the included Jupyter notebook, 'Inscopy_Jupyter.ipynb'. Jupyter Notebooks can be run on your system after you install the Jupyter Notebook program. The easiest way to do this is by first installing Anaconda and to follow the guidelines here.
About
A set of Python scripts to load and analyze Inscopix miniscope data.
Resources
Readme
MIT license
Activity
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1 watching
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0 forks
Report repository
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, '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('^' + ".*" + '

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LICENSE
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README.md
Repository files navigation
Inscopy
Inscopy is a set of Python scripts for quick and convenient analysis of Inscopix miniscope data.
Input data
Example Cells

Overview of the cells included in the example data 'Mouse3_AC1' as identified by the Inscopix software.
Input data are the .csv files. Usually one with the fluorescence of the identified cells and one with TTL stamps.

Code
All functions and classes used in Inscopy are annotated. The most important functions are in the file 'main.py'. This file can be run as a stand alone library if you prefer to do your analysis from the command line. There is a variable called 'run_example' if this variable is set to True (default) it will run some example analysis on the input data.
# Will run example analyses on the included example data$python -i main.py
# Will run example analyses on the files new_mouse_test.csv and new_mouse_TTL_test.csv$python -i main.py new_mouse

Jupyter Notebook
Most users will prefer to walk trough an analysis of an example mouse using the included Jupyter notebook, 'Inscopy_Jupyter.ipynb'. Jupyter Notebooks can be run on your system after you install the Jupyter Notebook program. The easiest way to do this is by first installing Anaconda and to follow the guidelines here.
About
A set of Python scripts to load and analyze Inscopix miniscope data.
Resources
Readme
MIT license
Activity
Stars
1 star
Watchers
1 watching
Forks
0 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('^' + ".*" + '

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Inscopy_Jupyter.ipynb
LICENSE
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README.md
README.md
Repository files navigation
Inscopy
Inscopy is a set of Python scripts for quick and convenient analysis of Inscopix miniscope data.
Input data
Example Cells

Overview of the cells included in the example data 'Mouse3_AC1' as identified by the Inscopix software.
Input data are the .csv files. Usually one with the fluorescence of the identified cells and one with TTL stamps.

Code
All functions and classes used in Inscopy are annotated. The most important functions are in the file 'main.py'. This file can be run as a stand alone library if you prefer to do your analysis from the command line. There is a variable called 'run_example' if this variable is set to True (default) it will run some example analysis on the input data.
# Will run example analyses on the included example data$python -i main.py
# Will run example analyses on the files new_mouse_test.csv and new_mouse_TTL_test.csv$python -i main.py new_mouse

Jupyter Notebook
Most users will prefer to walk trough an analysis of an example mouse using the included Jupyter notebook, 'Inscopy_Jupyter.ipynb'. Jupyter Notebooks can be run on your system after you install the Jupyter Notebook program. The easiest way to do this is by first installing Anaconda and to follow the guidelines here.
About
A set of Python scripts to load and analyze Inscopix miniscope data.
Resources
Readme
MIT license
Activity
Stars
1 star
Watchers
1 watching
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0 forks
Report repository
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, '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" + '

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Inscopy_Jupyter.ipynb
LICENSE
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README.md
README.md
Repository files navigation
Inscopy
Inscopy is a set of Python scripts for quick and convenient analysis of Inscopix miniscope data.
Input data
Example Cells

Overview of the cells included in the example data 'Mouse3_AC1' as identified by the Inscopix software.
Input data are the .csv files. Usually one with the fluorescence of the identified cells and one with TTL stamps.

Code
All functions and classes used in Inscopy are annotated. The most important functions are in the file 'main.py'. This file can be run as a stand alone library if you prefer to do your analysis from the command line. There is a variable called 'run_example' if this variable is set to True (default) it will run some example analysis on the input data.
# Will run example analyses on the included example data$python -i main.py
# Will run example analyses on the files new_mouse_test.csv and new_mouse_TTL_test.csv$python -i main.py new_mouse

Jupyter Notebook
Most users will prefer to walk trough an analysis of an example mouse using the included Jupyter notebook, 'Inscopy_Jupyter.ipynb'. Jupyter Notebooks can be run on your system after you install the Jupyter Notebook program. The easiest way to do this is by first installing Anaconda and to follow the guidelines here.
About
A set of Python scripts to load and analyze Inscopix miniscope data.
Resources
Readme
MIT license
Activity
Stars
1 star
Watchers
1 watching
Forks
0 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('^' + ".*" + '

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LICENSE
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README.md
README.md
Repository files navigation
Inscopy
Inscopy is a set of Python scripts for quick and convenient analysis of Inscopix miniscope data.
Input data
Example Cells

Overview of the cells included in the example data 'Mouse3_AC1' as identified by the Inscopix software.
Input data are the .csv files. Usually one with the fluorescence of the identified cells and one with TTL stamps.

Code
All functions and classes used in Inscopy are annotated. The most important functions are in the file 'main.py'. This file can be run as a stand alone library if you prefer to do your analysis from the command line. There is a variable called 'run_example' if this variable is set to True (default) it will run some example analysis on the input data.
# Will run example analyses on the included example data$python -i main.py
# Will run example analyses on the files new_mouse_test.csv and new_mouse_TTL_test.csv$python -i main.py new_mouse

Jupyter Notebook
Most users will prefer to walk trough an analysis of an example mouse using the included Jupyter notebook, 'Inscopy_Jupyter.ipynb'. Jupyter Notebooks can be run on your system after you install the Jupyter Notebook program. The easiest way to do this is by first installing Anaconda and to follow the guidelines here.
About
A set of Python scripts to load and analyze Inscopix miniscope data.
Resources
Readme
MIT license
Activity
Stars
1 star
Watchers
1 watching
Forks
0 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('^' + ".*" + '

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LICENSE
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README.md
README.md
Repository files navigation
Inscopy
Inscopy is a set of Python scripts for quick and convenient analysis of Inscopix miniscope data.
Input data
Example Cells

Overview of the cells included in the example data 'Mouse3_AC1' as identified by the Inscopix software.
Input data are the .csv files. Usually one with the fluorescence of the identified cells and one with TTL stamps.

Code
All functions and classes used in Inscopy are annotated. The most important functions are in the file 'main.py'. This file can be run as a stand alone library if you prefer to do your analysis from the command line. There is a variable called 'run_example' if this variable is set to True (default) it will run some example analysis on the input data.
# Will run example analyses on the included example data$python -i main.py
# Will run example analyses on the files new_mouse_test.csv and new_mouse_TTL_test.csv$python -i main.py new_mouse

Jupyter Notebook
Most users will prefer to walk trough an analysis of an example mouse using the included Jupyter notebook, 'Inscopy_Jupyter.ipynb'. Jupyter Notebooks can be run on your system after you install the Jupyter Notebook program. The easiest way to do this is by first installing Anaconda and to follow the guidelines here.
About
A set of Python scripts to load and analyze Inscopix miniscope data.
Resources
Readme
MIT license
Activity
Stars
1 star
Watchers
1 watching
Forks
0 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); }
})();
})();

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LICENSE
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README.md
README.md
Repository files navigation
Inscopy
Inscopy is a set of Python scripts for quick and convenient analysis of Inscopix miniscope data.
Input data
Example Cells

Overview of the cells included in the example data 'Mouse3_AC1' as identified by the Inscopix software.
Input data are the .csv files. Usually one with the fluorescence of the identified cells and one with TTL stamps.

Code
All functions and classes used in Inscopy are annotated. The most important functions are in the file 'main.py'. This file can be run as a stand alone library if you prefer to do your analysis from the command line. There is a variable called 'run_example' if this variable is set to True (default) it will run some example analysis on the input data.
# Will run example analyses on the included example data$python -i main.py
# Will run example analyses on the files new_mouse_test.csv and new_mouse_TTL_test.csv$python -i main.py new_mouse

Jupyter Notebook
Most users will prefer to walk trough an analysis of an example mouse using the included Jupyter notebook, 'Inscopy_Jupyter.ipynb'. Jupyter Notebooks can be run on your system after you install the Jupyter Notebook program. The easiest way to do this is by first installing Anaconda and to follow the guidelines here.
About
A set of Python scripts to load and analyze Inscopix miniscope data.
Resources
Readme
MIT license
Activity
Stars
1 star
Watchers
1 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages