From 251e20a230cc29721d8d15961a5851084fa5a298 Mon Sep 17 00:00:00 2001 From: Brendan Collins Date: Tue, 16 Dec 2025 08:06:36 -0800 Subject: [PATCH 1/2] removed references to xarray-spatial.org --- CONTRIBUTING.md | 2 +- docs/source/_templates/versions.html | 4 ++-- docs/source/user_guide/local.ipynb | 20 +++++++++---------- examples/user_guide/8_Local_Tools.ipynb | 20 +++++++++---------- ...array-spatial_classification-methods.ipynb | 12 +++++------ 5 files changed, 29 insertions(+), 29 deletions(-) diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md index c9a1afb8..10a4b6b4 100644 --- a/CONTRIBUTING.md +++ b/CONTRIBUTING.md @@ -4,7 +4,7 @@ As stated in [Xarray Spatial code of conduct](https://github.com/makepath/xarray ### Getting Started -Information about installation and setting up a development environment can be found at the [Getting Started page] https://xarray-spatial.org/getting_started/index.html. +Information about installation and setting up a development environment can be found at the [Getting Started page] https://xarray-spatial.readthedocs.io/getting_started/index.html. ### Choosing something to work on diff --git a/docs/source/_templates/versions.html b/docs/source/_templates/versions.html index d77040a6..8dac88c6 100644 --- a/docs/source/_templates/versions.html +++ b/docs/source/_templates/versions.html @@ -1,7 +1,7 @@
The documentation on this page refers to a PREVIOUS VERSION. For the latest release, go to https://xarray-spatial.org/
+ href="https://xarray-spatial.readthedocs.io/">https://xarray-spatial.readthedocs.io/
Versions @@ -15,4 +15,4 @@
- \ No newline at end of file + diff --git a/docs/source/user_guide/local.ipynb b/docs/source/user_guide/local.ipynb index 418579bb..fe253915 100644 --- a/docs/source/user_guide/local.ipynb +++ b/docs/source/user_guide/local.ipynb @@ -28,7 +28,7 @@ "id": "867a9d39", "metadata": {}, "source": [ - "In this notebook, we'll demonstrate how to use the [Xarray-spatial](http://xarray-spatial.org/) local tools functions supported by [Numpy](https://numpy.org/). The spatial functions available are:\n", + "In this notebook, we'll demonstrate how to use the [Xarray-spatial](http://xarray-spatial.readthedocs.io/) local tools functions supported by [Numpy](https://numpy.org/). The spatial functions available are:\n", "\n", "- [Cell Statistics](#Cell-Statistics) \n", "- [Combine](#Combine) \n", @@ -146,7 +146,7 @@ "id": "01ab159c", "metadata": {}, "source": [ - "[xrspatial.local.cell_stats](https://xarray-spatial.org/reference/_autosummary/xrspatial.local.cell_stats.html) calculates statistics from a raster dataset on a cell-by-cell basis." + "[xrspatial.local.cell_stats](https://xarray-spatial.readthedocs.io/reference/_autosummary/xrspatial.local.cell_stats.html) calculates statistics from a raster dataset on a cell-by-cell basis." ] }, { @@ -210,7 +210,7 @@ "id": "87c34a83", "metadata": {}, "source": [ - "[xrspatial.local.combine](https://xarray-spatial.org/reference/_autosummary/xrspatial.local.combine.html) combines multiple arrays from a raster dataset, assigning a unique output value to each unique combination of raster values." + "[xrspatial.local.combine](https://xarray-spatial.readthedocs.io/reference/_autosummary/xrspatial.local.combine.html) combines multiple arrays from a raster dataset, assigning a unique output value to each unique combination of raster values." ] }, { @@ -258,7 +258,7 @@ "id": "4f6da50e", "metadata": {}, "source": [ - "[xrspatial.local.lesser_frequency](https://xarray-spatial.org/reference/_autosummary/xrspatial.local.lesser_frequency.html) calculates, given a raster dataset, the number of times the data variables values are lower than the values of a given reference data variable on a cell-by-cell basis." + "[xrspatial.local.lesser_frequency](https://xarray-spatial.readthedocs.io/reference/_autosummary/xrspatial.local.lesser_frequency.html) calculates, given a raster dataset, the number of times the data variables values are lower than the values of a given reference data variable on a cell-by-cell basis." ] }, { @@ -308,7 +308,7 @@ "id": "0a2d8118", "metadata": {}, "source": [ - "[xrspatial.local.equal_frequency](https://xarray-spatial.org/reference/_autosummary/xrspatial.local.equal_frequency.html) calculates, given a raster dataset, the number of times the data variables values are equal than the values of a given reference data variable on a cell-by-cell basis." + "[xrspatial.local.equal_frequency](https://xarray-spatial.readthedocs.io/reference/_autosummary/xrspatial.local.equal_frequency.html) calculates, given a raster dataset, the number of times the data variables values are equal than the values of a given reference data variable on a cell-by-cell basis." ] }, { @@ -358,7 +358,7 @@ "id": "43c18c06", "metadata": {}, "source": [ - "[xrspatial.local.greater_frequency](https://xarray-spatial.org/reference/_autosummary/xrspatial.local.greater_frequency.html) calculates, given a raster dataset, the number of times the data variables values are greater than the values of a given reference data variable on a cell-by-cell basis." + "[xrspatial.local.greater_frequency](https://xarray-spatial.readthedocs.io/reference/_autosummary/xrspatial.local.greater_frequency.html) calculates, given a raster dataset, the number of times the data variables values are greater than the values of a given reference data variable on a cell-by-cell basis." ] }, { @@ -408,7 +408,7 @@ "id": "8d7235ec", "metadata": {}, "source": [ - "[xrspatial.local.lowest_position](https://xarray-spatial.org/reference/_autosummary/xrspatial.local.lowest_position.html) calculates the data variable index of the lowest value on a cell-by-cell basis." + "[xrspatial.local.lowest_position](https://xarray-spatial.readthedocs.io/reference/_autosummary/xrspatial.local.lowest_position.html) calculates the data variable index of the lowest value on a cell-by-cell basis." ] }, { @@ -457,7 +457,7 @@ "id": "a17c6e93", "metadata": {}, "source": [ - "[xrspatial.local.highest_position](https://xarray-spatial.org/reference/_autosummary/xrspatial.local.highest_position.html) calculates the data variable index of the highest value on a cell-by-cell basis." + "[xrspatial.local.highest_position](https://xarray-spatial.readthedocs.io/reference/_autosummary/xrspatial.local.highest_position.html) calculates the data variable index of the highest value on a cell-by-cell basis." ] }, { @@ -506,7 +506,7 @@ "id": "e5408cea", "metadata": {}, "source": [ - "[xrspatial.local.popularity](https://xarray-spatial.org/reference/_autosummary/xrspatial.local.popularity.html) calculates the number of occurrences of each value of a raster dataset, on a cell-by-cell basis. The output value is assigned based on the reference data variable nth most popular." + "[xrspatial.local.popularity](https://xarray-spatial.readthedocs.io/reference/_autosummary/xrspatial.local.popularity.html) calculates the number of occurrences of each value of a raster dataset, on a cell-by-cell basis. The output value is assigned based on the reference data variable nth most popular." ] }, { @@ -557,7 +557,7 @@ "id": "385dac65", "metadata": {}, "source": [ - "[xrspatial.local.rank](https://xarray-spatial.org/reference/_autosummary/xrspatial.local.rank.html) calculates the rank of each value of a raster dataset, on a cell-by-cell basis. The output value is assigned based on the rank of the reference data variable rank." + "[xrspatial.local.rank](https://xarray-spatial.readthedocs.io/reference/_autosummary/xrspatial.local.rank.html) calculates the rank of each value of a raster dataset, on a cell-by-cell basis. The output value is assigned based on the rank of the reference data variable rank." ] }, { diff --git a/examples/user_guide/8_Local_Tools.ipynb b/examples/user_guide/8_Local_Tools.ipynb index 13c510eb..34591794 100644 --- a/examples/user_guide/8_Local_Tools.ipynb +++ b/examples/user_guide/8_Local_Tools.ipynb @@ -26,7 +26,7 @@ "id": "ea55ffed", "metadata": {}, "source": [ - "In this notebook, we'll demonstrate how to use the [Xarray-spatial](http://xarray-spatial.org/) local tools functions supported by [Numpy](https://numpy.org/). The spatial functions available are:\n", + "In this notebook, we'll demonstrate how to use the [Xarray-spatial](http://xarray-spatial.readthedocs.io/) local tools functions supported by [Numpy](https://numpy.org/). The spatial functions available are:\n", "- [Cell Statistics](#Cell-Statistics)\n", "- [Combine](#Combine)\n", "- [Lesser Frequency](#Lesser-Frequency)\n", @@ -143,7 +143,7 @@ "id": "01ab159c", "metadata": {}, "source": [ - "[`xrspatial.local.cell_stats`](https://xarray-spatial.org/reference/_autosummary/xrspatial.local.cell_stats.html) calculates statistics from a raster dataset on a cell-by-cell basis." + "[`xrspatial.local.cell_stats`](https://xarray-spatial.readthedocs.io/reference/_autosummary/xrspatial.local.cell_stats.html) calculates statistics from a raster dataset on a cell-by-cell basis." ] }, { @@ -186,7 +186,7 @@ "id": "87c34a83", "metadata": {}, "source": [ - "[`xrspatial.local.combine`](https://xarray-spatial.org/reference/_autosummary/xrspatial.local.combine.html) combines multiple arrays from a raster dataset, assigning a unique output value to each unique combination of raster values." + "[`xrspatial.local.combine`](https://xarray-spatial.readthedocs.io/reference/_autosummary/xrspatial.local.combine.html) combines multiple arrays from a raster dataset, assigning a unique output value to each unique combination of raster values." ] }, { @@ -223,7 +223,7 @@ "id": "4f6da50e", "metadata": {}, "source": [ - "[`xrspatial.local.lesser_frequency`](https://xarray-spatial.org/reference/_autosummary/xrspatial.local.lesser_frequency.html) calculates, given a raster dataset, the number of times the data variables values are lower than the values of a given reference data variable on a cell-by-cell basis." + "[`xrspatial.local.lesser_frequency`](https://xarray-spatial.readthedocs.io/reference/_autosummary/xrspatial.local.lesser_frequency.html) calculates, given a raster dataset, the number of times the data variables values are lower than the values of a given reference data variable on a cell-by-cell basis." ] }, { @@ -262,7 +262,7 @@ "id": "intelligent-philadelphia", "metadata": {}, "source": [ - "[`xrspatial.local.equal_frequency`](https://xarray-spatial.org/reference/_autosummary/xrspatial.local.equal_frequency.html) calculates, given a raster dataset, the number of times the data variables values are equal than the values of a given reference data variable on a cell-by-cell basis." + "[`xrspatial.local.equal_frequency`](https://xarray-spatial.readthedocs.io/reference/_autosummary/xrspatial.local.equal_frequency.html) calculates, given a raster dataset, the number of times the data variables values are equal than the values of a given reference data variable on a cell-by-cell basis." ] }, { @@ -301,7 +301,7 @@ "id": "vocational-inside", "metadata": {}, "source": [ - "[`xrspatial.local.greater_frequency`](https://xarray-spatial.org/reference/_autosummary/xrspatial.local.greater_frequency.html) calculates, given a raster dataset, the number of times the data variables values are greater than the values of a given reference data variable on a cell-by-cell basis." + "[`xrspatial.local.greater_frequency`](https://xarray-spatial.readthedocs.io/reference/_autosummary/xrspatial.local.greater_frequency.html) calculates, given a raster dataset, the number of times the data variables values are greater than the values of a given reference data variable on a cell-by-cell basis." ] }, { @@ -340,7 +340,7 @@ "id": "8d7235ec", "metadata": {}, "source": [ - "[`xrspatial.local.lowest_position`](https://xarray-spatial.org/reference/_autosummary/xrspatial.local.lowest_position.html) calculates the data variable index of the lowest value on a cell-by-cell basis." + "[`xrspatial.local.lowest_position`](https://xarray-spatial.readthedocs.io/reference/_autosummary/xrspatial.local.lowest_position.html) calculates the data variable index of the lowest value on a cell-by-cell basis." ] }, { @@ -378,7 +378,7 @@ "id": "a17c6e93", "metadata": {}, "source": [ - "[`xrspatial.local.highest_position`](https://xarray-spatial.org/reference/_autosummary/xrspatial.local.highest_position.html) calculates the data variable index of the highest value on a cell-by-cell basis." + "[`xrspatial.local.highest_position`](https://xarray-spatial.readthedocs.io/reference/_autosummary/xrspatial.local.highest_position.html) calculates the data variable index of the highest value on a cell-by-cell basis." ] }, { @@ -416,7 +416,7 @@ "id": "e5408cea", "metadata": {}, "source": [ - "[`xrspatial.local.popularity`](https://xarray-spatial.org/reference/_autosummary/xrspatial.local.popularity.html) calculates the number of occurrences of each value of a raster dataset, on a cell-by-cell basis. The output value is assigned based on the reference data variable nth most popular." + "[`xrspatial.local.popularity`](https://xarray-spatial.readthedocs.io/reference/_autosummary/xrspatial.local.popularity.html) calculates the number of occurrences of each value of a raster dataset, on a cell-by-cell basis. The output value is assigned based on the reference data variable nth most popular." ] }, { @@ -456,7 +456,7 @@ "id": "385dac65", "metadata": {}, "source": [ - "[`xrspatial.local.rank`](https://xarray-spatial.org/reference/_autosummary/xrspatial.local.rank.html) calculates the rank of each value of a raster dataset, on a cell-by-cell basis. The output value is assigned based on the rank of the reference data variable rank." + "[`xrspatial.local.rank`](https://xarray-spatial.readthedocs.io/reference/_autosummary/xrspatial.local.rank.html) calculates the rank of each value of a raster dataset, on a cell-by-cell basis. The output value is assigned based on the rank of the reference data variable rank." ] }, { diff --git a/examples/xarray-spatial_classification-methods.ipynb b/examples/xarray-spatial_classification-methods.ipynb index de98feec..76684b4c 100644 --- a/examples/xarray-spatial_classification-methods.ipynb +++ b/examples/xarray-spatial_classification-methods.ipynb @@ -19,7 +19,7 @@ "\n", "This tutorial walks you through:\n", "1. Loading and rendering the area of interest data using the Grand Canyon's latitude and longitude.\n", - "2. Classifying the data using xarray-spatial's [natural breaks](https://xarray-spatial.org/reference/_autosummary/xrspatial.classify.natural_breaks.html), [equal interval](https://xarray-spatial.org/reference/_autosummary/xrspatial.classify.equal_interval.html), [quantile](https://xarray-spatial.org/reference/_autosummary/xrspatial.classify.quantile.html), and [reclassify](https://xarray-spatial.org/reference/_autosummary/xrspatial.classify.reclassify.html) functions.\n", + "2. Classifying the data using xarray-spatial's [natural breaks](https://xarray-spatial.readthedocs.io/reference/_autosummary/xrspatial.classify.natural_breaks.html), [equal interval](https://xarray-spatial.readthedocs.io/reference/_autosummary/xrspatial.classify.equal_interval.html), [quantile](https://xarray-spatial.readthedocs.io/reference/_autosummary/xrspatial.classify.quantile.html), and [reclassify](https://xarray-spatial.readthedocs.io/reference/_autosummary/xrspatial.classify.reclassify.html) functions.\n", "\n", "\n", "This tutorial uses the [NASADEM](https://github.com/microsoft/AIforEarthDatasets#nasadem) dataset from the [Microsoft Planetary Computer Data Catalog](https://planetarycomputer.microsoft.com/catalog). The area of interest roughly covers the Grand Canyon National Park. The [NASADEM](https://github.com/microsoft/AIforEarthDatasets#nasadem) dataset provides global topographic data at 1 arc-second (~30m) horizontal resolution. The data is derived primarily from data captured via the [Shuttle Radar Topography Mission](https://www2.jpl.nasa.gov/srtm/) (SRTM) and is stored on Azure Storage in [cloud-optimized GeoTIFF](https://www.cogeo.org/) format.\n" @@ -181,7 +181,7 @@ "id": "41759319", "metadata": {}, "source": [ - "Use the [natural breaks](https://xarray-spatial.org/reference/_autosummary/xrspatial.classify.natural_breaks.html) function to classify data with the [Jenks natural breaks classification](http://wiki.gis.com/wiki/index.php/Jenks_Natural_Breaks_Classification) method. This method is designed to distribute data into classes according to clusters that form a \"natural\" group within the data. The algorithm minimizes the average deviation from the class mean while also maximizing the deviation from the means of the other groups. Therefore, it is generally not recommended for data with low variance." + "Use the [natural breaks](https://xarray-spatial.readthedocs.io/reference/_autosummary/xrspatial.classify.natural_breaks.html) function to classify data with the [Jenks natural breaks classification](http://wiki.gis.com/wiki/index.php/Jenks_Natural_Breaks_Classification) method. This method is designed to distribute data into classes according to clusters that form a \"natural\" group within the data. The algorithm minimizes the average deviation from the class mean while also maximizing the deviation from the means of the other groups. Therefore, it is generally not recommended for data with low variance." ] }, { @@ -221,7 +221,7 @@ "id": "baed3e1b", "metadata": {}, "source": [ - "To classify data into sets based on intervals of equal width, use the [equal interval](https://xarray-spatial.org/reference/_autosummary/xrspatial.classify.equal_interval.html) function. The [equal interval classification](http://wiki.gis.com/wiki/index.php/Equal_Interval_classification) is useful in cases where you want to emphasize the amount of an attribute value relative to the other values." + "To classify data into sets based on intervals of equal width, use the [equal interval](https://xarray-spatial.readthedocs.io/reference/_autosummary/xrspatial.classify.equal_interval.html) function. The [equal interval classification](http://wiki.gis.com/wiki/index.php/Equal_Interval_classification) is useful in cases where you want to emphasize the amount of an attribute value relative to the other values." ] }, { @@ -251,7 +251,7 @@ "id": "a4630ca7", "metadata": {}, "source": [ - "To classify data based on quantile groups of equal size, use the [quantile](https://xarray-spatial.org/reference/_autosummary/xrspatial.classify.quantile.html) function. With [quantile classification](http://wiki.gis.com/wiki/index.php/Quantile), each class contains the same amount of data points. This means that each class is equally represented on the map. However, intervals of uneven sizes can lead to an over-weighting of outliers and other effects." + "To classify data based on quantile groups of equal size, use the [quantile](https://xarray-spatial.readthedocs.io/reference/_autosummary/xrspatial.classify.quantile.html) function. With [quantile classification](http://wiki.gis.com/wiki/index.php/Quantile), each class contains the same amount of data points. This means that each class is equally represented on the map. However, intervals of uneven sizes can lead to an over-weighting of outliers and other effects." ] }, { @@ -281,7 +281,7 @@ "id": "13f0851f", "metadata": {}, "source": [ - "To define your own arbitrary bins to classify data, use the [reclassify](https://xarray-spatial.org/reference/_autosummary/xrspatial.classify.reclassify.html) function. This function is helpful to highlight specific sections of your data, for example. Use `reclassify()` to only visualize elevations greater than 2500m:" + "To define your own arbitrary bins to classify data, use the [reclassify](https://xarray-spatial.readthedocs.io/reference/_autosummary/xrspatial.classify.reclassify.html) function. This function is helpful to highlight specific sections of your data, for example. Use `reclassify()` to only visualize elevations greater than 2500m:" ] }, { @@ -320,7 +320,7 @@ "source": [ "The [Microsoft Planetary Computer Data Catalog](https://planetarycomputer.microsoft.com/catalog) includes petabytes of environmental monitoring data. All data sets are available in consistent, analysis-ready formats. You can access them through APIs as well as directly via [Azure Storage](https://docs.microsoft.com/en-us/azure/storage/). \n", "\n", - "Try using [xarray-spatial's](https://xarray-spatial.org/index.html) classification methods with these datasets:" + "Try using [xarray-spatial's](https://xarray-spatial.readthedocs.io/index.html) classification methods with these datasets:" ] }, { From 8670d33982000c541de456c90a5974e4b85d77f5 Mon Sep 17 00:00:00 2001 From: Brendan Collins Date: Thu, 18 Dec 2025 06:54:34 -0800 Subject: [PATCH 2/2] updated citation and added conda version badge --- README.md | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index 656d358c..cfa9268c 100644 --- a/README.md +++ b/README.md @@ -5,7 +5,9 @@ Latest Release
- pypi version + Last Conda Release + pypi version + conda-forge version
@@ -282,6 +284,6 @@ However, wrapping GDAL has a few drawbacks for Python developers and data scient With the introduction of projects like Numba, Python gained new ways to provide high-performance code directly in Python, without depending on or being constrained by separate C/C++ extensions. `xarray-spatial` implements algorithms using Numba and Dask, making all of its source code available as pure Python without any "black box" barriers that obscure what is going on and prevent full optimization. Projects can make use of the functionality provided by `xarray-spatial` where available, while still using GDAL where required for other tasks. #### Citation -Cite our code: +Cite this code: -`makepath/xarray-spatial, https://github.com/makepath/xarray-spatial, ©2020-2024.` +`makepath/xarray-spatial, https://github.com/makepath/xarray-spatial, ©2020-2026.`