From 87630aec0be8fbcc8c887465903865faa4dfd0c3 Mon Sep 17 00:00:00 2001 From: Benjamin Glitsos Date: Mon, 18 Dec 2023 17:28:31 +1100 Subject: [PATCH] Reverted some remaining links to be .py links --- DEA_products/DEA_Wetlands_Insight_Tool.ipynb | 4 ++-- How_to_guides/Generating_composites.ipynb | 2 +- Real_world_examples/Scalable_machine_learning/README.rst | 2 +- 3 files changed, 4 insertions(+), 4 deletions(-) diff --git a/DEA_products/DEA_Wetlands_Insight_Tool.ipynb b/DEA_products/DEA_Wetlands_Insight_Tool.ipynb index dc9e0eed9..f2ac0ab26 100755 --- a/DEA_products/DEA_Wetlands_Insight_Tool.ipynb +++ b/DEA_products/DEA_Wetlands_Insight_Tool.ipynb @@ -69,9 +69,9 @@ "Licencing information is provided at the bottom of this notebook, and requires attribution.** \n", "\n", "## Related products\n", - "* [DEA Fractional Cover (Landsat)](https://docs.dea.ga.gov.au/notebooks/DEA_products/DEA_Fractional_Cover.ipynb)\n", + "* [DEA Fractional Cover (Landsat)](../DEA_products/DEA_Fractional_Cover.ipynb)\n", "* [DEA Tasseled Cap Indices Percentiles Calendar Year (Landsat)](https://docs.dea.ga.gov.au/data/product/dea-wetness-percentiles-landsat)\n", - "* [DEA Water Observations (Landsat)](https://docs.dea.ga.gov.au/notebooks/DEA_products/DEA_Water_Observations/)" + "* [DEA Water Observations (Landsat)](../DEA_products/DEA_Water_Observations.ipynb)" ] }, { diff --git a/How_to_guides/Generating_composites.ipynb b/How_to_guides/Generating_composites.ipynb index addd2f3a6..168f0ac75 100644 --- a/How_to_guides/Generating_composites.ipynb +++ b/How_to_guides/Generating_composites.ipynb @@ -1131,7 +1131,7 @@ "source": [ "To get an image at a certain time, often there is missing data, due to clouds and other masking. We can fill in these gaps by using data from surrounding times.\n", "\n", - "To generate these images, we can use the custom functions `first`, `last` and `nearest` from the [dea_datahandling](https://docs.dea.ga.gov.au/notebooks/Tools/gen/dea_tools.datahandling/) script.\n", + "To generate these images, we can use the custom functions `first`, `last` and `nearest` from the [datahandling](../Tools/dea_tools/datahandling.py) script.\n", "\n", "You can also use the in-built `.first()` and `.last()` methods when doing `groupby` and `resample` as described above. They are described in the [xarray documentation](http://xarray.pydata.org/en/stable/groupby.html#first-and-last) on grouped data." ] diff --git a/Real_world_examples/Scalable_machine_learning/README.rst b/Real_world_examples/Scalable_machine_learning/README.rst index e306ec1d1..54dae1d5c 100644 --- a/Real_world_examples/Scalable_machine_learning/README.rst +++ b/Real_world_examples/Scalable_machine_learning/README.rst @@ -38,7 +38,7 @@ extensively documented. And secondly, a number of custom python functions have been written to ease the complexity of running ML on the ODC. These include (among others) ``collect_training_data``, and ``predict_xr``, both of which are contained in the -`dea\_tools.classification `__ +`dea\_tools.classification <../Tools/dea_tools/classification.py>`__ package. These functions are introduced and explained further in the relevant sections of the notebooks.