Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

Add link to SciPy talk to docs #704

Merged
merged 1 commit into from
Oct 2, 2024
Merged

Add link to SciPy talk to docs #704

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
1 change: 1 addition & 0 deletions docs/demos.rst
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -16,4 +16,5 @@ This page includes relevant xCDAT presentations, demos, and papers.
DOE EESM Research Highlight <https://climatemodeling.science.energy.gov/research-highlights/xcdat-python-package-simple-and-robust-analysis-climate-data>
SciPy 2024 (Abstract) <https://cfp.scipy.org/2024/talk/VRACYW/>
SciPy 2024 (Presentation Notebook) <demos/24-07-11-scipy-2024/scipy-2024.ipynb>
SciPy 2024 (Recorded Talk) <https://www.youtube.com/watch?v=hcUnb_IztSs>
DOE EESM PI Meeting Presentation <https://climatemodeling.science.energy.gov/presentations/xcdat-xarray-climate-data-analysis-tools-python-package-simple-and-robust-analysis>
4 changes: 4 additions & 0 deletions docs/demos.yml
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -26,6 +26,10 @@
path: demos/24-07-11-scipy-2024/scipy-2024.ipynb
thumbnail: _static/thumbnails/scipy-logo.png

- title: SciPy 2024 (Recorded Talk, 07/11/24)
path: https://www.youtube.com/watch?v=hcUnb_IztSs
thumbnail: _static/thumbnails/scipy-logo.png

- title: DOE EESM PI Meeting 2024 Presentation (08/08/24)
path: https://climatemodeling.science.energy.gov/presentations/xcdat-xarray-climate-data-analysis-tools-python-package-simple-and-robust-analysis
thumbnail: _static/thumbnails/doe-logo.jpg
63 changes: 28 additions & 35 deletions docs/demos/24-07-11-scipy-2024/scipy-2024.ipynb
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -155,14 +155,14 @@
"source": [
"## An Overview of this Talk\n",
"\n",
"__Objective: Learn about the grounds-up development of an open-source Python package targeted at a specific scientific domain__\n",
"\n",
"* Driving force behind xCDAT\n",
"* Scope and mission of xCDAT\n",
"* Design philosophy and key features\n",
"* Technical demo of an end-to-end analysis workflow\n",
"* Parallelism with Dask\n",
"* How to get involved\n"
"**Objective: Learn about the grounds-up development of an open-source Python package targeted at a specific scientific domain**\n",
"\n",
"- Driving force behind xCDAT\n",
"- Scope and mission of xCDAT\n",
"- Design philosophy and key features\n",
"- Technical demo of an end-to-end analysis workflow\n",
"- Parallelism with Dask\n",
"- How to get involved\n"
]
},
{
Expand All @@ -175,13 +175,13 @@
"source": [
"## The Driving Force Behind xCDAT\n",
"\n",
"- Analysis of climate data frequently requires a number of core operations. For example: \n",
" - Reading and writing netCDF files\n",
" - Regridding\n",
" - Spatial and temporal averaging \n",
"- Highly performant operations to handle the growing volume of climate data \n",
" - Larger pool of data products \n",
" - Increasing spatiotemporal resolution of model and observational data\n"
"- Analysis of climate data frequently requires a number of core operations. For example:\n",
" - Reading and writing netCDF files\n",
" - Regridding\n",
" - Spatial and temporal averaging\n",
"- Highly performant operations to handle the growing volume of climate data\n",
" - Larger pool of data products\n",
" - Increasing spatiotemporal resolution of model and observational data\n"
]
},
{
Expand All @@ -198,10 +198,7 @@
"<img src=\"../../_static/cdat-logo.png\" alt=\"CDAT logo\" align=\\\"center\\\" style=\"display: inline-block; width:200px;\">\n",
"</div>\n",
"\n",
"- CDAT (Community Data Analysis Tools) library provided open-source climate data analysis and visualization packages for over 20 years\n",
"\n",
"\n",
"\n"
"- CDAT (Community Data Analysis Tools) library provided open-source climate data analysis and visualization packages for over 20 years\n"
]
},
{
Expand All @@ -215,8 +212,7 @@
"### The present-day challenge: **CDAT is end-of-life** as of December 2023\n",
"\n",
"- A big issue for users and packages that depend on CDAT\n",
"- A driving need for new analysis software\n",
"\n"
"- A driving need for new analysis software\n"
]
},
{
Expand All @@ -227,7 +223,7 @@
}
},
"source": [
" xCDAT addresses this need by **combining the power of Xarray** with **geospatial analysis features inspired by CDAT**."
"xCDAT addresses this need by **combining the power of Xarray** with **geospatial analysis features inspired by CDAT**.\n"
]
},
{
Expand Down Expand Up @@ -266,18 +262,16 @@
"</div>\n",
"<h2>\"N-D labeled arrays and datasets in Python\"</h2>\n",
"\n",
"\n",
"**Why is Xarray the core technology of xCDAT?**\n",
"\n",
"- Mature widely adopted \n",
"- Mature widely adopted\n",
"- Fiscal funding from NumFocus\n",
"- Introduces labels in the form of dimensions, coordinates, and attributes on top of raw NumPy-like arrays\n",
"- Intuitive, more concise, and less error-prone user experience\n",
"\n",
"<div style=\"text-align: center; margin-top:10px\">\n",
" <img src=\"../../_static/numfocus-logo.png\" alt=\"NumFocus logo\" align=\\\"center\\\" style=\"display: inline-block; width:200px;\">\n",
"</div>\n",
"\n"
" <img src=\"../../_static/NumFocus-logo.png\" alt=\"NumFocus logo\" align=\\\"center\\\" style=\"display: inline-block; width:200px;\">\n",
"</div>\n"
]
},
{
Expand Down Expand Up @@ -335,8 +329,7 @@
" <img src=\"../../_static/esmf-logo.png\" alt=\"ESMF logo\" style=\"display: inline-block; margin-right:50px; width:200px;\">\n",
" <img src=\"../../_static/xgcm-logo.png\" alt=\"xgcm logo\" align=\\\"center\\\" style=\"display: inline-block; margin-right:50px; width:200px;\">\n",
" <img src=\"../../_static/CF-xarray.png\" alt=\"CF xarray logo\" align=\\\"center\\\" style=\"display: inline-block; margin-right:50px; width:200px;\">\n",
"</div>\n",
"\n"
"</div>\n"
]
},
{
Expand Down Expand Up @@ -653,7 +646,7 @@
"3. Horizontal Regridding\n",
"4. Vertical Regridding\n",
"5. Spatial Averaging\n",
"6. Temporal Computations"
"6. Temporal Computations\n"
]
},
{
Expand Down Expand Up @@ -773,7 +766,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"Analyzing monthly `tas` (near-sea surface air temperature) data from 2000 to 2014."
"Analyzing monthly `tas` (near-sea surface air temperature) data from 2000 to 2014.\n"
]
},
{
Expand Down Expand Up @@ -4805,7 +4798,7 @@
}
},
"source": [
"#### Calculate the near-surface air temperature (`tas`) in the Niño 3.4 region."
"#### Calculate the near-surface air temperature (`tas`) in the Niño 3.4 region.\n"
]
},
{
Expand All @@ -4815,7 +4808,7 @@
"Users can also specify their own bounds for a region. In this case, we specified `keep_weights=True`.\n",
"\n",
"- Full weight for grid cells entirely in the region\n",
"- Partial weights for grid cells partially in the region"
"- Partial weights for grid cells partially in the region\n"
]
},
{
Expand Down Expand Up @@ -5065,7 +5058,7 @@
"source": [
"ds_global_anomaly = ds_global.temporal.departures(\n",
" \"tas\", freq=\"month\", reference_period=(\"2000-01-01\", \"2009-12-31\")\n",
") "
")"
]
},
{
Expand Down Expand Up @@ -6340,7 +6333,7 @@
"</div>\n",
"\n",
"- xCDAT is an **extension of Xarray for climate data analysis on structured grids**\n",
"- Focused on routine **climate research analysis operations** \n",
"- Focused on routine **climate research analysis operations**\n",
"- Designed to encourages **software sustainability and reproducible science**\n",
"- **Parallelizable** through Xarray’s support for Dask, which enables efficient processing of large datasets\n"
]
Expand Down
Loading