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Warning

New Xarray-based Package for IMD Radar Data "Radarx"

  • Looking for a more modern, flexible, and efficient way to work with IMD radar data?
  • Check out our new package: Radarx at https://radarx.readthedocs.io

    It’s an xarray-based toolkit built on top of xradar that supports reading, visualizing, and analyzing IMD radar files with ease.

💬 Join the discussion and stay connected with the radar community at openradar.discourse.group

Gitter

PyScanCf

Creates Py-ART compatible cf-radial data from individual sweeps of Indian Meteorological Department (IMD) Radar data

Description

PyScanCf is a library for creating cfradial (polar) data from IMD radars that contain all 10 sweeps from single scans which are named as (Polar_ABC.nc) as well as gridded radar data from which are named as (grid_ABC.nc). Both formats are compatible for PyART. It uses Pyart to create grid data, so please remember to cite Py-ART as well.

Latest Documentation

https://syedha.com/PyScanCf/

Latest Examples

https://github.com/syedhamidali/pyscancf_examples

Installing from source

Installing PyScanCf from source is the only way to get the latest updates and enhancement to the software that have not yet made it into a release. The latest source code for PyScanCf can be obtained from the GitHub repository, https://github.com/syedhamidali/PyScanCf.git.

How to install::

conda create -n pcf arm_pyart nbclassic git -c conda-forge
conda activate pcf
pip install git+https://github.com/syedhamidali/PyScanCf.git

Or, to install in your home directory, use::

git clone https://github.com/syedhamidali/PyScanCf.git
python setup.py install --user

Or, Install via pip::

pip install pyscancf

Citation

DOI

Syed, H. A., Sayyed, I., Kalapureddy, M. C. R., & Grandhi, K. K. (2021). PyScanCf – The library for single sweep datasets of IMD weather radars. Zenodo. doi:10.5281/zenodo.5574160.

PyScanCf Tutorial on Youtube

https://youtu.be/OUrdhe5virA

Documentation

Import Library::

import pyscancf as pcf

Mention the data path::

inp = '/Users/rizvi/Downloads/goa16'

Convert data to cfradial format::

pcf.cfrad(inp,inp,True,'REF')

And you'll see the beautiful gridded data plot in your notebook, the figures will be saved in the directory from where you launched the notebook

image

Detailed and efficient way to use this toolkit

Detailed Notebook

About

Converts individual sweeps from IMD radars to Cf-Radial1 radar data.

pyscancf.readthedocs.io/

Topics

cfradialdwrgrid-radarimdjupyter-notebookpyartpythonqperadar

Resources

Readme
MIT license
Activity

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19 stars

Watchers

2 watching

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7 forks
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, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all \u003cpre\u003e\u003ccode\u003e 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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Warning

New Xarray-based Package for IMD Radar Data "Radarx"

  • Looking for a more modern, flexible, and efficient way to work with IMD radar data?
  • Check out our new package: Radarx at https://radarx.readthedocs.io

    It’s an xarray-based toolkit built on top of xradar that supports reading, visualizing, and analyzing IMD radar files with ease.

💬 Join the discussion and stay connected with the radar community at openradar.discourse.group

Gitter

PyScanCf

Creates Py-ART compatible cf-radial data from individual sweeps of Indian Meteorological Department (IMD) Radar data

Description

PyScanCf is a library for creating cfradial (polar) data from IMD radars that contain all 10 sweeps from single scans which are named as (Polar_ABC.nc) as well as gridded radar data from which are named as (grid_ABC.nc). Both formats are compatible for PyART. It uses Pyart to create grid data, so please remember to cite Py-ART as well.

Latest Documentation

https://syedha.com/PyScanCf/

Latest Examples

https://github.com/syedhamidali/pyscancf_examples

Installing from source

Installing PyScanCf from source is the only way to get the latest updates and enhancement to the software that have not yet made it into a release. The latest source code for PyScanCf can be obtained from the GitHub repository, https://github.com/syedhamidali/PyScanCf.git.

How to install::

conda create -n pcf arm_pyart nbclassic git -c conda-forge
conda activate pcf
pip install git+https://github.com/syedhamidali/PyScanCf.git

Or, to install in your home directory, use::

git clone https://github.com/syedhamidali/PyScanCf.git
python setup.py install --user

Or, Install via pip::

pip install pyscancf

Citation

DOI

Syed, H. A., Sayyed, I., Kalapureddy, M. C. R., & Grandhi, K. K. (2021). PyScanCf – The library for single sweep datasets of IMD weather radars. Zenodo. doi:10.5281/zenodo.5574160.

PyScanCf Tutorial on Youtube

https://youtu.be/OUrdhe5virA

Documentation

Import Library::

import pyscancf as pcf

Mention the data path::

inp = '/Users/rizvi/Downloads/goa16'

Convert data to cfradial format::

pcf.cfrad(inp,inp,True,'REF')

And you'll see the beautiful gridded data plot in your notebook, the figures will be saved in the directory from where you launched the notebook

image

Detailed and efficient way to use this toolkit

Detailed Notebook

About

Converts individual sweeps from IMD radars to Cf-Radial1 radar data.

pyscancf.readthedocs.io/

Topics

cfradialdwrgrid-radarimdjupyter-notebookpyartpythonqperadar

Resources

Readme
MIT license
Activity

Stars

19 stars

Watchers

2 watching

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7 forks
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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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Warning

New Xarray-based Package for IMD Radar Data "Radarx"

  • Looking for a more modern, flexible, and efficient way to work with IMD radar data?
  • Check out our new package: Radarx at https://radarx.readthedocs.io

    It’s an xarray-based toolkit built on top of xradar that supports reading, visualizing, and analyzing IMD radar files with ease.

💬 Join the discussion and stay connected with the radar community at openradar.discourse.group

Gitter

PyScanCf

Creates Py-ART compatible cf-radial data from individual sweeps of Indian Meteorological Department (IMD) Radar data

Description

PyScanCf is a library for creating cfradial (polar) data from IMD radars that contain all 10 sweeps from single scans which are named as (Polar_ABC.nc) as well as gridded radar data from which are named as (grid_ABC.nc). Both formats are compatible for PyART. It uses Pyart to create grid data, so please remember to cite Py-ART as well.

Latest Documentation

https://syedha.com/PyScanCf/

Latest Examples

https://github.com/syedhamidali/pyscancf_examples

Installing from source

Installing PyScanCf from source is the only way to get the latest updates and enhancement to the software that have not yet made it into a release. The latest source code for PyScanCf can be obtained from the GitHub repository, https://github.com/syedhamidali/PyScanCf.git.

How to install::

conda create -n pcf arm_pyart nbclassic git -c conda-forge
conda activate pcf
pip install git+https://github.com/syedhamidali/PyScanCf.git

Or, to install in your home directory, use::

git clone https://github.com/syedhamidali/PyScanCf.git
python setup.py install --user

Or, Install via pip::

pip install pyscancf

Citation

DOI

Syed, H. A., Sayyed, I., Kalapureddy, M. C. R., & Grandhi, K. K. (2021). PyScanCf – The library for single sweep datasets of IMD weather radars. Zenodo. doi:10.5281/zenodo.5574160.

PyScanCf Tutorial on Youtube

https://youtu.be/OUrdhe5virA

Documentation

Import Library::

import pyscancf as pcf

Mention the data path::

inp = '/Users/rizvi/Downloads/goa16'

Convert data to cfradial format::

pcf.cfrad(inp,inp,True,'REF')

And you'll see the beautiful gridded data plot in your notebook, the figures will be saved in the directory from where you launched the notebook

image

Detailed and efficient way to use this toolkit

Detailed Notebook

About

Converts individual sweeps from IMD radars to Cf-Radial1 radar data.

pyscancf.readthedocs.io/

Topics

cfradialdwrgrid-radarimdjupyter-notebookpyartpythonqperadar

Resources

Readme
MIT license
Activity

Stars

19 stars

Watchers

2 watching

Forks

7 forks
Report repository

Releases

Packages

Used by

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 \u003e 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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Warning

New Xarray-based Package for IMD Radar Data "Radarx"

  • Looking for a more modern, flexible, and efficient way to work with IMD radar data?
  • Check out our new package: Radarx at https://radarx.readthedocs.io

    It’s an xarray-based toolkit built on top of xradar that supports reading, visualizing, and analyzing IMD radar files with ease.

💬 Join the discussion and stay connected with the radar community at openradar.discourse.group

Gitter

PyScanCf

Creates Py-ART compatible cf-radial data from individual sweeps of Indian Meteorological Department (IMD) Radar data

Description

PyScanCf is a library for creating cfradial (polar) data from IMD radars that contain all 10 sweeps from single scans which are named as (Polar_ABC.nc) as well as gridded radar data from which are named as (grid_ABC.nc). Both formats are compatible for PyART. It uses Pyart to create grid data, so please remember to cite Py-ART as well.

Latest Documentation

https://syedha.com/PyScanCf/

Latest Examples

https://github.com/syedhamidali/pyscancf_examples

Installing from source

Installing PyScanCf from source is the only way to get the latest updates and enhancement to the software that have not yet made it into a release. The latest source code for PyScanCf can be obtained from the GitHub repository, https://github.com/syedhamidali/PyScanCf.git.

How to install::

conda create -n pcf arm_pyart nbclassic git -c conda-forge
conda activate pcf
pip install git+https://github.com/syedhamidali/PyScanCf.git

Or, to install in your home directory, use::

git clone https://github.com/syedhamidali/PyScanCf.git
python setup.py install --user

Or, Install via pip::

pip install pyscancf

Citation

DOI

Syed, H. A., Sayyed, I., Kalapureddy, M. C. R., & Grandhi, K. K. (2021). PyScanCf – The library for single sweep datasets of IMD weather radars. Zenodo. doi:10.5281/zenodo.5574160.

PyScanCf Tutorial on Youtube

https://youtu.be/OUrdhe5virA

Documentation

Import Library::

import pyscancf as pcf

Mention the data path::

inp = '/Users/rizvi/Downloads/goa16'

Convert data to cfradial format::

pcf.cfrad(inp,inp,True,'REF')

And you'll see the beautiful gridded data plot in your notebook, the figures will be saved in the directory from where you launched the notebook

image

Detailed and efficient way to use this toolkit

Detailed Notebook

About

Converts individual sweeps from IMD radars to Cf-Radial1 radar data.

pyscancf.readthedocs.io/

Topics

cfradialdwrgrid-radarimdjupyter-notebookpyartpythonqperadar

Resources

Readme
MIT license
Activity

Stars

19 stars

Watchers

2 watching

Forks

7 forks
Report repository

Releases

Packages

Used by

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" + '
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Warning

New Xarray-based Package for IMD Radar Data "Radarx"

  • Looking for a more modern, flexible, and efficient way to work with IMD radar data?
  • Check out our new package: Radarx at https://radarx.readthedocs.io

    It’s an xarray-based toolkit built on top of xradar that supports reading, visualizing, and analyzing IMD radar files with ease.

💬 Join the discussion and stay connected with the radar community at openradar.discourse.group

Gitter

PyScanCf

Creates Py-ART compatible cf-radial data from individual sweeps of Indian Meteorological Department (IMD) Radar data

Description

PyScanCf is a library for creating cfradial (polar) data from IMD radars that contain all 10 sweeps from single scans which are named as (Polar_ABC.nc) as well as gridded radar data from which are named as (grid_ABC.nc). Both formats are compatible for PyART. It uses Pyart to create grid data, so please remember to cite Py-ART as well.

Latest Documentation

https://syedha.com/PyScanCf/

Latest Examples

https://github.com/syedhamidali/pyscancf_examples

Installing from source

Installing PyScanCf from source is the only way to get the latest updates and enhancement to the software that have not yet made it into a release. The latest source code for PyScanCf can be obtained from the GitHub repository, https://github.com/syedhamidali/PyScanCf.git.

How to install::

conda create -n pcf arm_pyart nbclassic git -c conda-forge
conda activate pcf
pip install git+https://github.com/syedhamidali/PyScanCf.git

Or, to install in your home directory, use::

git clone https://github.com/syedhamidali/PyScanCf.git
python setup.py install --user

Or, Install via pip::

pip install pyscancf

Citation

DOI

Syed, H. A., Sayyed, I., Kalapureddy, M. C. R., & Grandhi, K. K. (2021). PyScanCf – The library for single sweep datasets of IMD weather radars. Zenodo. doi:10.5281/zenodo.5574160.

PyScanCf Tutorial on Youtube

https://youtu.be/OUrdhe5virA

Documentation

Import Library::

import pyscancf as pcf

Mention the data path::

inp = '/Users/rizvi/Downloads/goa16'

Convert data to cfradial format::

pcf.cfrad(inp,inp,True,'REF')

And you'll see the beautiful gridded data plot in your notebook, the figures will be saved in the directory from where you launched the notebook

image

Detailed and efficient way to use this toolkit

Detailed Notebook

About

Converts individual sweeps from IMD radars to Cf-Radial1 radar data.

pyscancf.readthedocs.io/

Topics

cfradialdwrgrid-radarimdjupyter-notebookpyartpythonqperadar

Resources

Readme
MIT license
Activity

Stars

19 stars

Watchers

2 watching

Forks

7 forks
Report repository

Releases

Packages

Used by

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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Warning

New Xarray-based Package for IMD Radar Data "Radarx"

  • Looking for a more modern, flexible, and efficient way to work with IMD radar data?
  • Check out our new package: Radarx at https://radarx.readthedocs.io

    It’s an xarray-based toolkit built on top of xradar that supports reading, visualizing, and analyzing IMD radar files with ease.

💬 Join the discussion and stay connected with the radar community at openradar.discourse.group

Gitter

PyScanCf

Creates Py-ART compatible cf-radial data from individual sweeps of Indian Meteorological Department (IMD) Radar data

Description

PyScanCf is a library for creating cfradial (polar) data from IMD radars that contain all 10 sweeps from single scans which are named as (Polar_ABC.nc) as well as gridded radar data from which are named as (grid_ABC.nc). Both formats are compatible for PyART. It uses Pyart to create grid data, so please remember to cite Py-ART as well.

Latest Documentation

https://syedha.com/PyScanCf/

Latest Examples

https://github.com/syedhamidali/pyscancf_examples

Installing from source

Installing PyScanCf from source is the only way to get the latest updates and enhancement to the software that have not yet made it into a release. The latest source code for PyScanCf can be obtained from the GitHub repository, https://github.com/syedhamidali/PyScanCf.git.

How to install::

conda create -n pcf arm_pyart nbclassic git -c conda-forge
conda activate pcf
pip install git+https://github.com/syedhamidali/PyScanCf.git

Or, to install in your home directory, use::

git clone https://github.com/syedhamidali/PyScanCf.git
python setup.py install --user

Or, Install via pip::

pip install pyscancf

Citation

DOI

Syed, H. A., Sayyed, I., Kalapureddy, M. C. R., & Grandhi, K. K. (2021). PyScanCf – The library for single sweep datasets of IMD weather radars. Zenodo. doi:10.5281/zenodo.5574160.

PyScanCf Tutorial on Youtube

https://youtu.be/OUrdhe5virA

Documentation

Import Library::

import pyscancf as pcf

Mention the data path::

inp = '/Users/rizvi/Downloads/goa16'

Convert data to cfradial format::

pcf.cfrad(inp,inp,True,'REF')

And you'll see the beautiful gridded data plot in your notebook, the figures will be saved in the directory from where you launched the notebook

image

Detailed and efficient way to use this toolkit

Detailed Notebook

About

Converts individual sweeps from IMD radars to Cf-Radial1 radar data.

pyscancf.readthedocs.io/

Topics

cfradialdwrgrid-radarimdjupyter-notebookpyartpythonqperadar

Resources

Readme
MIT license
Activity

Stars

19 stars

Watchers

2 watching

Forks

7 forks
Report repository

Releases

Packages

Used by

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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Warning

New Xarray-based Package for IMD Radar Data "Radarx"

  • Looking for a more modern, flexible, and efficient way to work with IMD radar data?
  • Check out our new package: Radarx at https://radarx.readthedocs.io

    It’s an xarray-based toolkit built on top of xradar that supports reading, visualizing, and analyzing IMD radar files with ease.

💬 Join the discussion and stay connected with the radar community at openradar.discourse.group

Gitter

PyScanCf

Creates Py-ART compatible cf-radial data from individual sweeps of Indian Meteorological Department (IMD) Radar data

Description

PyScanCf is a library for creating cfradial (polar) data from IMD radars that contain all 10 sweeps from single scans which are named as (Polar_ABC.nc) as well as gridded radar data from which are named as (grid_ABC.nc). Both formats are compatible for PyART. It uses Pyart to create grid data, so please remember to cite Py-ART as well.

Latest Documentation

https://syedha.com/PyScanCf/

Latest Examples

https://github.com/syedhamidali/pyscancf_examples

Installing from source

Installing PyScanCf from source is the only way to get the latest updates and enhancement to the software that have not yet made it into a release. The latest source code for PyScanCf can be obtained from the GitHub repository, https://github.com/syedhamidali/PyScanCf.git.

How to install::

conda create -n pcf arm_pyart nbclassic git -c conda-forge
conda activate pcf
pip install git+https://github.com/syedhamidali/PyScanCf.git

Or, to install in your home directory, use::

git clone https://github.com/syedhamidali/PyScanCf.git
python setup.py install --user

Or, Install via pip::

pip install pyscancf

Citation

DOI

Syed, H. A., Sayyed, I., Kalapureddy, M. C. R., & Grandhi, K. K. (2021). PyScanCf – The library for single sweep datasets of IMD weather radars. Zenodo. doi:10.5281/zenodo.5574160.

PyScanCf Tutorial on Youtube

https://youtu.be/OUrdhe5virA

Documentation

Import Library::

import pyscancf as pcf

Mention the data path::

inp = '/Users/rizvi/Downloads/goa16'

Convert data to cfradial format::

pcf.cfrad(inp,inp,True,'REF')

And you'll see the beautiful gridded data plot in your notebook, the figures will be saved in the directory from where you launched the notebook

image

Detailed and efficient way to use this toolkit

Detailed Notebook

About

Converts individual sweeps from IMD radars to Cf-Radial1 radar data.

pyscancf.readthedocs.io/

Topics

cfradialdwrgrid-radarimdjupyter-notebookpyartpythonqperadar

Resources

Readme
MIT license
Activity

Stars

19 stars

Watchers

2 watching

Forks

7 forks
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Warning

New Xarray-based Package for IMD Radar Data "Radarx"

  • Looking for a more modern, flexible, and efficient way to work with IMD radar data?
  • Check out our new package: Radarx at https://radarx.readthedocs.io

    It’s an xarray-based toolkit built on top of xradar that supports reading, visualizing, and analyzing IMD radar files with ease.

💬 Join the discussion and stay connected with the radar community at openradar.discourse.group

Gitter

PyScanCf

Creates Py-ART compatible cf-radial data from individual sweeps of Indian Meteorological Department (IMD) Radar data

Description

PyScanCf is a library for creating cfradial (polar) data from IMD radars that contain all 10 sweeps from single scans which are named as (Polar_ABC.nc) as well as gridded radar data from which are named as (grid_ABC.nc). Both formats are compatible for PyART. It uses Pyart to create grid data, so please remember to cite Py-ART as well.

Latest Documentation

https://syedha.com/PyScanCf/

Latest Examples

https://github.com/syedhamidali/pyscancf_examples

Installing from source

Installing PyScanCf from source is the only way to get the latest updates and enhancement to the software that have not yet made it into a release. The latest source code for PyScanCf can be obtained from the GitHub repository, https://github.com/syedhamidali/PyScanCf.git.

How to install::

conda create -n pcf arm_pyart nbclassic git -c conda-forge
conda activate pcf
pip install git+https://github.com/syedhamidali/PyScanCf.git

Or, to install in your home directory, use::

git clone https://github.com/syedhamidali/PyScanCf.git
python setup.py install --user

Or, Install via pip::

pip install pyscancf

Citation

DOI

Syed, H. A., Sayyed, I., Kalapureddy, M. C. R., & Grandhi, K. K. (2021). PyScanCf – The library for single sweep datasets of IMD weather radars. Zenodo. doi:10.5281/zenodo.5574160.

PyScanCf Tutorial on Youtube

https://youtu.be/OUrdhe5virA

Documentation

Import Library::

import pyscancf as pcf

Mention the data path::

inp = '/Users/rizvi/Downloads/goa16'

Convert data to cfradial format::

pcf.cfrad(inp,inp,True,'REF')

And you'll see the beautiful gridded data plot in your notebook, the figures will be saved in the directory from where you launched the notebook

image

Detailed and efficient way to use this toolkit

Detailed Notebook

About

Converts individual sweeps from IMD radars to Cf-Radial1 radar data.

pyscancf.readthedocs.io/

Topics

cfradialdwrgrid-radarimdjupyter-notebookpyartpythonqperadar

Resources

Readme
MIT license
Activity

Stars

19 stars

Watchers

2 watching

Forks

7 forks
Report repository

Releases

Packages

Used by

Contributors

Languages