From ad39988c865ef409f942c823bb825c2fca2d3fce Mon Sep 17 00:00:00 2001 From: Robbi Bishop-Taylor Date: Wed, 31 Jul 2024 02:54:55 +0000 Subject: [PATCH 01/45] Update notebooks --- notebooks/DEACoastlines_generation_CLI.ipynb | 172 +++++++++- notebooks/DEACoastlines_utils.ipynb | 83 ++++- notebooks/DEACoastlines_validation.ipynb | 311 ++++++++++++++++--- 3 files changed, 517 insertions(+), 49 deletions(-) diff --git a/notebooks/DEACoastlines_generation_CLI.ipynb b/notebooks/DEACoastlines_generation_CLI.ipynb index ea763c29..346ade12 100644 --- a/notebooks/DEACoastlines_generation_CLI.ipynb +++ b/notebooks/DEACoastlines_generation_CLI.ipynb @@ -77,7 +77,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "id": "4729d261-6b27-4a61-a937-366c5174ce05", "metadata": { "tags": [] @@ -85,9 +85,9 @@ "outputs": [], "source": [ "study_area = 283\n", - "raster_version = 'testing2022'\n", - "vector_version = 'testing2022'\n", - "continental_version = 'testing2022'\n", + "raster_version = 'testing2023'\n", + "vector_version = 'testing2023'\n", + "continental_version = 'testing2023'\n", "config_path = 'configs/dea_coastlines_config.yaml'\n", "\n", "# study_area = 9\n", @@ -108,7 +108,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 3, "id": "dc5632c4-f872-46e5-9762-80b8556f3622", "metadata": { "tags": [] @@ -178,7 +178,8 @@ " access\n", " --overwrite / --no-overwrite Whether to overwrite tiles with existing\n", " outputs, or skip these tiles entirely.\n", - " --help Show this message and exit.\n" + " --help Show this message and exit.\n", + "\u001b[0m" ] } ], @@ -196,12 +197,137 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "id": "47397eb8-ddec-46c6-9f7c-431a50bb7eae", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "/env/lib/python3.10/site-packages/distributed/node.py:182: UserWarning: Port 8787 is already in use.\n", + "Perhaps you already have a cluster running?\n", + "Hosting the HTTP server on port 37049 instead\n", + " warnings.warn(\n", + "\n", + "2024-07-31 02:44:57 INFO Study area 283: Loaded study area grid\n", + "2024-07-31 02:45:03 INFO Study area 283: Loaded virtual product\n", + "Creating reduced resolution 5000 x 5000 metre tide modelling array\n", + "Modelling tides using FES2014 in parallel\n", + "100%|█████████████████████████████████████████████| 5/5 [00:09<00:00, 1.82s/it]\n", + "Reprojecting tides into original array\n", + "/env/lib/python3.10/site-packages/rasterio/warp.py:344: NotGeoreferencedWarning: Dataset has no geotransform, gcps, or rpcs. The identity matrix will be returned.\n", + " _reproject(\n", + "2024-07-31 02:45:31 INFO Study area 283: Finished modelling tide heights\n", + "2024-07-31 02:45:32 INFO Study area 283: Calculating low and high tide cutoffs for each pixel\n", + "2024-07-31 02:45:32 INFO Study area 283: Started exporting raster data\n", + "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", + " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", + "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", + " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", + "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", + " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", + "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", + " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", + "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", + " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", + "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", + " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", + "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", + " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", + "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", + " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", + "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", + " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", + "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", + " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", + "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", + " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", + "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", + " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", + "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", + " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", + "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", + " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", + "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", + " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", + "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", + " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", + "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", + " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", + "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", + " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", + "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", + " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", + "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", + " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", + "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", + " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", + "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", + " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", + "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", + " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", + "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", + " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", + "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", + " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", + "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", + " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", + "/env/lib/python3.10/site-packages/distributed/client.py:3161: UserWarning: Sending large graph of size 38.13 MiB.\n", + "This may cause some slowdown.\n", + "Consider scattering data ahead of time and using futures.\n", + " warnings.warn(\n", + "/env/lib/python3.10/site-packages/distributed/client.py:3161: UserWarning: Sending large graph of size 76.22 MiB.\n", + "This may cause some slowdown.\n", + "Consider scattering data ahead of time and using futures.\n", + " warnings.warn(\n", + "/env/lib/python3.10/site-packages/distributed/client.py:3161: UserWarning: Sending large graph of size 102.88 MiB.\n", + "This may cause some slowdown.\n", + "Consider scattering data ahead of time and using futures.\n", + " warnings.warn(\n", + "/env/lib/python3.10/site-packages/distributed/client.py:3161: UserWarning: Sending large graph of size 91.46 MiB.\n", + "This may cause some slowdown.\n", + "Consider scattering data ahead of time and using futures.\n", + " warnings.warn(\n", + "/env/lib/python3.10/site-packages/distributed/client.py:3161: UserWarning: Sending large graph of size 87.65 MiB.\n", + "This may cause some slowdown.\n", + "Consider scattering data ahead of time and using futures.\n", + " warnings.warn(\n", + "/env/lib/python3.10/site-packages/distributed/client.py:3161: UserWarning: Sending large graph of size 91.46 MiB.\n", + "This may cause some slowdown.\n", + "Consider scattering data ahead of time and using futures.\n", + " warnings.warn(\n", + "/env/lib/python3.10/site-packages/distributed/client.py:3161: UserWarning: Sending large graph of size 110.50 MiB.\n", + "This may cause some slowdown.\n", + "Consider scattering data ahead of time and using futures.\n", + " warnings.warn(\n", + "/env/lib/python3.10/site-packages/distributed/client.py:3161: UserWarning: Sending large graph of size 106.69 MiB.\n", + "This may cause some slowdown.\n", + "Consider scattering data ahead of time and using futures.\n", + " warnings.warn(\n", + "/env/lib/python3.10/site-packages/distributed/client.py:3161: UserWarning: Sending large graph of size 110.51 MiB.\n", + "This may cause some slowdown.\n", + "Consider scattering data ahead of time and using futures.\n", + " warnings.warn(\n", + "/env/lib/python3.10/site-packages/distributed/client.py:3161: UserWarning: Sending large graph of size 110.52 MiB.\n", + "This may cause some slowdown.\n", + "Consider scattering data ahead of time and using futures.\n", + " warnings.warn(\n", + "/env/lib/python3.10/site-packages/distributed/client.py:3161: UserWarning: Sending large graph of size 118.14 MiB.\n", + "This may cause some slowdown.\n", + "Consider scattering data ahead of time and using futures.\n", + " warnings.warn(\n", + "/env/lib/python3.10/site-packages/distributed/client.py:3161: UserWarning: Sending large graph of size 53.38 MiB.\n", + "This may cause some slowdown.\n", + "Consider scattering data ahead of time and using futures.\n", + " warnings.warn(\n", + "2024-07-31 02:51:20 INFO Study area 283: Completed exporting raster data\n", + "\u001b[0m\u001b[0m" + ] + } + ], "source": [ - "!python -m coastlines.raster --config_path {config_path} --study_area {study_area} --raster_version {raster_version} --start_year 1988 --end_year 2022" + "!python -m coastlines.raster --config_path {config_path} --study_area {study_area} --raster_version {raster_version} --start_year 1988 --end_year 2023" ] }, { @@ -290,12 +416,32 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "id": "c23665e0-6d46-4185-b9f0-04a50d856174", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2024-07-31 02:51:31 INFO Study area 283: Starting vector generation\n", + "2024-07-31 02:51:31 ERROR Study area 283: Failed to run process with error module 'xarray' has no attribute 'open_rasterio'\n", + "Traceback (most recent call last):\n", + " File \"/home/jovyan/Robbi/dea-coastlines/coastlines/vector.py\", line 1810, in generate_vectors_cli\n", + " generate_vectors(\n", + " File \"/home/jovyan/Robbi/dea-coastlines/coastlines/vector.py\", line 1390, in generate_vectors\n", + " yearly_ds, gapfill_ds = load_rasters(\n", + " File \"/home/jovyan/Robbi/dea-coastlines/coastlines/vector.py\", line 132, in load_rasters\n", + " layer_da = xr.concat([xr.open_rasterio(i) for i in paths], dim=time_var)\n", + " File \"/home/jovyan/Robbi/dea-coastlines/coastlines/vector.py\", line 132, in \n", + " layer_da = xr.concat([xr.open_rasterio(i) for i in paths], dim=time_var)\n", + "AttributeError: module 'xarray' has no attribute 'open_rasterio'\n", + "\u001b[0m" + ] + } + ], "source": [ - "!python -m coastlines.vector --config_path {config_path} --study_area {study_area} --raster_version {raster_version} --start_year 1988 --end_year 2022 --baseline_year 2022" + "!python -m coastlines.vector --config_path {config_path} --study_area {study_area} --raster_version {raster_version} --start_year 1988 --end_year 2022 --baseline_year 2023" ] }, { @@ -526,7 +672,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.10" + "version": "3.10.13" }, "widgets": { "application/vnd.jupyter.widget-state+json": { diff --git a/notebooks/DEACoastlines_utils.ipynb b/notebooks/DEACoastlines_utils.ipynb index a2531fb8..1438acb3 100644 --- a/notebooks/DEACoastlines_utils.ipynb +++ b/notebooks/DEACoastlines_utils.ipynb @@ -136,6 +136,87 @@ "layer.drop(['geometry'], axis=1).to_csv('coastlines/styles.csv', index=False)" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Generate Geoserver annual shoreline hex codes" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1988 #000004\n", + "1989 #030210\n", + "1990 #0a0722\n", + "1991 #120a32\n", + "1992 #1e0c45\n", + "1993 #290b55\n", + "1994 #380962\n", + "1995 #440a68\n", + "1996 #510e6c\n", + "1997 #5c126e\n", + "1998 #69166e\n", + "1999 #741a6e\n", + "2000 #801f6c\n", + "2001 #8c2369\n", + "2002 #982766\n", + "2003 #a32c61\n", + "2004 #b0315b\n", + "2005 #bc3754\n", + "2006 #c63d4d\n", + "2007 #d04545\n", + "2008 #d94d3d\n", + "2009 #e25734\n", + "2010 #e9612b\n", + "2011 #ef6e21\n", + "2012 #f47918\n", + "2013 #f8870e\n", + "2014 #fa9407\n", + "2015 #fca309\n", + "2016 #fcb014\n", + "2017 #fac026\n", + "2018 #f8cd37\n", + "2019 #f4dd4f\n", + "2020 #f2ea69\n", + "2021 #f3f68a\n", + "2022 #fcffa4\n", + "2023 #ffffe1\n" + ] + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "import matplotlib.colors as mcolors\n", + "import numpy as np\n", + "\n", + "start_year = 1988\n", + "end_year = 2023\n", + "\n", + "def get_hex_colors_from_cmap(cmap_name, num_colors):\n", + " cmap = plt.get_cmap(cmap_name)\n", + " norm = plt.Normalize(vmin=0, vmax=num_colors - 1)\n", + " colors = [cmap(norm(i)) for i in range(num_colors)]\n", + " hex_colors = [mcolors.to_hex(color) for color in colors]\n", + " return hex_colors\n", + "\n", + "cmap_name = 'inferno' # Change this to the desired colormap name\n", + "num_colors = len(list(range(start_year, end_year)))\n", + "\n", + "hex_colors = get_hex_colors_from_cmap(cmap_name, num_colors) + [\"#ffffe1\"]\n", + "\n", + "for item, year in zip(hex_colors, list(range(start_year, end_year + 1))):\n", + " print(str(year) + \" \" + item.strip(\"'\"), sep=\"\\n\")" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -493,7 +574,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.10" + "version": "3.10.13" }, "widgets": { "application/vnd.jupyter.widget-state+json": { diff --git a/notebooks/DEACoastlines_validation.ipynb b/notebooks/DEACoastlines_validation.ipynb index 2f09ee18..2bf4a91c 100644 --- a/notebooks/DEACoastlines_validation.ipynb +++ b/notebooks/DEACoastlines_validation.ipynb @@ -12,7 +12,9 @@ { "cell_type": "code", "execution_count": 1, - "metadata": {}, + "metadata": { + "tags": [] + }, "outputs": [ { "name": "stdout", @@ -47,8 +49,10 @@ }, { "cell_type": "code", - "execution_count": 3, - "metadata": {}, + "execution_count": 2, + "metadata": { + "tags": [] + }, "outputs": [], "source": [ "%load_ext autoreload\n", @@ -64,8 +68,10 @@ }, { "cell_type": "code", - "execution_count": 4, - "metadata": {}, + "execution_count": 3, + "metadata": { + "tags": [] + }, "outputs": [ { "name": "stdout", @@ -102,19 +108,24 @@ }, { "cell_type": "code", - "execution_count": 10, - "metadata": {}, + "execution_count": 8, + "metadata": { + "tags": [] + }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " 0%| | 0/1 [00:00" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# coastlines.validation.validation_cli" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": { + "tags": [] + }, "outputs": [], "source": [ "outputs_df, stats_df = coastlines.validation.validation_cli(\n", @@ -177,26 +212,184 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, + "execution_count": 26, + "metadata": { + "tags": [] + }, "outputs": [], - "source": [] + "source": [ + "# Test to get all outputs for temporal plotting\n", + "outputs_df = coastlines.validation.validation_cli(\n", + " inputs_path=\"data/validation/interim/\",\n", + " deacl_path=\"data/releases/coastlines_v2.0.0.gpkg\",\n", + " prefix=\"tests\",\n", + " datum=\"0\",\n", + " overwrite=False,\n", + " layer_name='shorelines_annual',\n", + " append_stats=True,\n", + " parallelised=True,\n", + " markdown_report=True)\n", + " \n", + "\n", + "# prefix='tests'\n", + "# deacl_path=\"data/processed/tests/coastlines_tests.gpkg\"" + ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 29, + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "0 0.132725\n", + "1 18.480537\n", + "0 3.479032\n", + "1 73.598530\n", + "2 306.425871\n", + " ... \n", + "5 73.174714\n", + "6 17.937049\n", + "7 37.693972\n", + "8 68.825562\n", + "9 85.182771\n", + "Name: error_m, Length: 50010, dtype: float64" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(outputs_df.error_m ** 2).groupby(\"year\")" + ] + }, + { + "cell_type": "code", + "execution_count": 31, "metadata": { "tags": [] }, "outputs": [], - "source": [] + "source": [ + "outputs_df['error_sq'] = outputs_df.error_m ** 2" + ] }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, + "execution_count": 37, + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 37, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", 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" + ], + "text/plain": [ + " time n mae rmse stdev corr bias name\n", + "0 2023-02-08 00:01:06.359381 2669.0 4.8 6.07 5.49 0.976 -2.64 v1.1.0" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "outputs_df" + ] }, { "cell_type": "code", @@ -251,9 +444,33 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 5, + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Combining data\n" + ] + }, + { + "ename": "ValueError", + "evalue": "No objects to concatenate", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[5], line 6\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mCombining data\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m 5\u001b[0m stats_list \u001b[38;5;241m=\u001b[39m glob\u001b[38;5;241m.\u001b[39mglob(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mdata/validation/processed/outputs_\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mprefix\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m_*.csv\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[0;32m----> 6\u001b[0m stats_df \u001b[38;5;241m=\u001b[39m \u001b[43mpd\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mconcat\u001b[49m\u001b[43m(\u001b[49m\u001b[43m[\u001b[49m\u001b[43mpd\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mread_csv\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcsv\u001b[49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mcsv\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mstats_list\u001b[49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 8\u001b[0m \u001b[38;5;66;03m# # Rename smartline categories to smaller subset\u001b[39;00m\n\u001b[1;32m 9\u001b[0m \u001b[38;5;66;03m# stats_df['smartline'] = stats_df.smartline.replace(rename_dict)\u001b[39;00m\n\u001b[1;32m 10\u001b[0m \n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 16\u001b[0m \u001b[38;5;66;03m# # print(stats_df.T)\u001b[39;00m\n\u001b[1;32m 17\u001b[0m \u001b[38;5;66;03m# # stats_df.T.to_csv(f'data/validation/processed/stats_{prefix}.csv')\u001b[39;00m\n", + "File \u001b[0;32m/env/lib/python3.10/site-packages/pandas/util/_decorators.py:331\u001b[0m, in \u001b[0;36mdeprecate_nonkeyword_arguments..decorate..wrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 325\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(args) \u001b[38;5;241m>\u001b[39m num_allow_args:\n\u001b[1;32m 326\u001b[0m warnings\u001b[38;5;241m.\u001b[39mwarn(\n\u001b[1;32m 327\u001b[0m msg\u001b[38;5;241m.\u001b[39mformat(arguments\u001b[38;5;241m=\u001b[39m_format_argument_list(allow_args)),\n\u001b[1;32m 328\u001b[0m \u001b[38;5;167;01mFutureWarning\u001b[39;00m,\n\u001b[1;32m 329\u001b[0m stacklevel\u001b[38;5;241m=\u001b[39mfind_stack_level(),\n\u001b[1;32m 330\u001b[0m )\n\u001b[0;32m--> 331\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m/env/lib/python3.10/site-packages/pandas/core/reshape/concat.py:368\u001b[0m, in \u001b[0;36mconcat\u001b[0;34m(objs, axis, join, ignore_index, keys, levels, names, verify_integrity, sort, copy)\u001b[0m\n\u001b[1;32m 146\u001b[0m \u001b[38;5;129m@deprecate_nonkeyword_arguments\u001b[39m(version\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, allowed_args\u001b[38;5;241m=\u001b[39m[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mobjs\u001b[39m\u001b[38;5;124m\"\u001b[39m])\n\u001b[1;32m 147\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mconcat\u001b[39m(\n\u001b[1;32m 148\u001b[0m objs: Iterable[NDFrame] \u001b[38;5;241m|\u001b[39m Mapping[HashableT, NDFrame],\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 157\u001b[0m copy: \u001b[38;5;28mbool\u001b[39m \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mTrue\u001b[39;00m,\n\u001b[1;32m 158\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m DataFrame \u001b[38;5;241m|\u001b[39m Series:\n\u001b[1;32m 159\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 160\u001b[0m \u001b[38;5;124;03m Concatenate pandas objects along a particular axis.\u001b[39;00m\n\u001b[1;32m 161\u001b[0m \n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 366\u001b[0m \u001b[38;5;124;03m 1 3 4\u001b[39;00m\n\u001b[1;32m 367\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[0;32m--> 368\u001b[0m op \u001b[38;5;241m=\u001b[39m \u001b[43m_Concatenator\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 369\u001b[0m \u001b[43m \u001b[49m\u001b[43mobjs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 370\u001b[0m \u001b[43m \u001b[49m\u001b[43maxis\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43maxis\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 371\u001b[0m \u001b[43m \u001b[49m\u001b[43mignore_index\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mignore_index\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 372\u001b[0m \u001b[43m \u001b[49m\u001b[43mjoin\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mjoin\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 373\u001b[0m \u001b[43m \u001b[49m\u001b[43mkeys\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mkeys\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 374\u001b[0m \u001b[43m \u001b[49m\u001b[43mlevels\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mlevels\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 375\u001b[0m \u001b[43m \u001b[49m\u001b[43mnames\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mnames\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 376\u001b[0m \u001b[43m \u001b[49m\u001b[43mverify_integrity\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mverify_integrity\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 377\u001b[0m \u001b[43m \u001b[49m\u001b[43mcopy\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcopy\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 378\u001b[0m \u001b[43m \u001b[49m\u001b[43msort\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43msort\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 379\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 381\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m op\u001b[38;5;241m.\u001b[39mget_result()\n", + "File \u001b[0;32m/env/lib/python3.10/site-packages/pandas/core/reshape/concat.py:425\u001b[0m, in \u001b[0;36m_Concatenator.__init__\u001b[0;34m(self, objs, axis, join, keys, levels, names, ignore_index, verify_integrity, copy, sort)\u001b[0m\n\u001b[1;32m 422\u001b[0m objs \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mlist\u001b[39m(objs)\n\u001b[1;32m 424\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(objs) \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[0;32m--> 425\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mNo objects to concatenate\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 427\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m keys \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 428\u001b[0m objs \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mlist\u001b[39m(com\u001b[38;5;241m.\u001b[39mnot_none(\u001b[38;5;241m*\u001b[39mobjs))\n", + "\u001b[0;31mValueError\u001b[0m: No objects to concatenate" + ] + } + ], "source": [ "import glob\n", "prefix='v0.0.3'\n", @@ -262,16 +479,16 @@ "stats_list = glob.glob(f'data/validation/processed/outputs_{prefix}_*.csv')\n", "stats_df = pd.concat([pd.read_csv(csv) for csv in stats_list])\n", "\n", - "# Rename smartline categories to smaller subset\n", - "stats_df['smartline'] = stats_df.smartline.replace(rename_dict)\n", + "# # Rename smartline categories to smaller subset\n", + "# stats_df['smartline'] = stats_df.smartline.replace(rename_dict)\n", "\n", - "# Run stats\n", - "stats_df = coastlines.validation.deacl_val_stats(stats_df.val_dist,\n", - " stats_df.deacl_dist,\n", - " n=stats_df.n,\n", - " remove_bias=False)\n", - "# print(stats_df.T)\n", - "# stats_df.T.to_csv(f'data/validation/processed/stats_{prefix}.csv')" + "# # Run stats\n", + "# stats_df = coastlines.validation.deacl_val_stats(stats_df.val_dist,\n", + "# stats_df.deacl_dist,\n", + "# n=stats_df.n,\n", + "# remove_bias=False)\n", + "# # print(stats_df.T)\n", + "# # stats_df.T.to_csv(f'data/validation/processed/stats_{prefix}.csv')" ] }, { @@ -417,9 +634,33 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 6, + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Combining data\n" + ] + }, + { + "ename": "ValueError", + "evalue": "No objects to concatenate", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[6], line 4\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mCombining data\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m 3\u001b[0m stats_list \u001b[38;5;241m=\u001b[39m glob\u001b[38;5;241m.\u001b[39mglob(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mdata/validation/processed/\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mprefix\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m_*.csv\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[0;32m----> 4\u001b[0m stats_df \u001b[38;5;241m=\u001b[39m \u001b[43mpd\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mconcat\u001b[49m\u001b[43m(\u001b[49m\u001b[43m[\u001b[49m\u001b[43mpd\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mread_csv\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcsv\u001b[49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mcsv\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mstats_list\u001b[49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 6\u001b[0m \u001b[38;5;66;03m# Rename smartline categories to smaller subset\u001b[39;00m\n\u001b[1;32m 7\u001b[0m stats_df[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124msmartline\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;241m=\u001b[39m stats_df\u001b[38;5;241m.\u001b[39msmartline\u001b[38;5;241m.\u001b[39mreplace(rename_dict)\n", + "File \u001b[0;32m/env/lib/python3.10/site-packages/pandas/util/_decorators.py:331\u001b[0m, in \u001b[0;36mdeprecate_nonkeyword_arguments..decorate..wrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 325\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(args) \u001b[38;5;241m>\u001b[39m num_allow_args:\n\u001b[1;32m 326\u001b[0m warnings\u001b[38;5;241m.\u001b[39mwarn(\n\u001b[1;32m 327\u001b[0m msg\u001b[38;5;241m.\u001b[39mformat(arguments\u001b[38;5;241m=\u001b[39m_format_argument_list(allow_args)),\n\u001b[1;32m 328\u001b[0m \u001b[38;5;167;01mFutureWarning\u001b[39;00m,\n\u001b[1;32m 329\u001b[0m stacklevel\u001b[38;5;241m=\u001b[39mfind_stack_level(),\n\u001b[1;32m 330\u001b[0m )\n\u001b[0;32m--> 331\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m/env/lib/python3.10/site-packages/pandas/core/reshape/concat.py:368\u001b[0m, in \u001b[0;36mconcat\u001b[0;34m(objs, axis, join, ignore_index, keys, levels, names, verify_integrity, sort, copy)\u001b[0m\n\u001b[1;32m 146\u001b[0m \u001b[38;5;129m@deprecate_nonkeyword_arguments\u001b[39m(version\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, allowed_args\u001b[38;5;241m=\u001b[39m[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mobjs\u001b[39m\u001b[38;5;124m\"\u001b[39m])\n\u001b[1;32m 147\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mconcat\u001b[39m(\n\u001b[1;32m 148\u001b[0m objs: Iterable[NDFrame] \u001b[38;5;241m|\u001b[39m Mapping[HashableT, NDFrame],\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 157\u001b[0m copy: \u001b[38;5;28mbool\u001b[39m \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mTrue\u001b[39;00m,\n\u001b[1;32m 158\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m DataFrame \u001b[38;5;241m|\u001b[39m Series:\n\u001b[1;32m 159\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 160\u001b[0m \u001b[38;5;124;03m Concatenate pandas objects along a particular axis.\u001b[39;00m\n\u001b[1;32m 161\u001b[0m \n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 366\u001b[0m \u001b[38;5;124;03m 1 3 4\u001b[39;00m\n\u001b[1;32m 367\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[0;32m--> 368\u001b[0m op \u001b[38;5;241m=\u001b[39m \u001b[43m_Concatenator\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 369\u001b[0m \u001b[43m \u001b[49m\u001b[43mobjs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 370\u001b[0m \u001b[43m \u001b[49m\u001b[43maxis\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43maxis\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 371\u001b[0m \u001b[43m \u001b[49m\u001b[43mignore_index\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mignore_index\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 372\u001b[0m \u001b[43m \u001b[49m\u001b[43mjoin\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mjoin\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 373\u001b[0m \u001b[43m \u001b[49m\u001b[43mkeys\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mkeys\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 374\u001b[0m \u001b[43m \u001b[49m\u001b[43mlevels\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mlevels\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 375\u001b[0m \u001b[43m \u001b[49m\u001b[43mnames\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mnames\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 376\u001b[0m \u001b[43m \u001b[49m\u001b[43mverify_integrity\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mverify_integrity\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 377\u001b[0m \u001b[43m \u001b[49m\u001b[43mcopy\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcopy\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 378\u001b[0m \u001b[43m \u001b[49m\u001b[43msort\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43msort\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 379\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 381\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m op\u001b[38;5;241m.\u001b[39mget_result()\n", + "File \u001b[0;32m/env/lib/python3.10/site-packages/pandas/core/reshape/concat.py:425\u001b[0m, in \u001b[0;36m_Concatenator.__init__\u001b[0;34m(self, objs, axis, join, keys, levels, names, ignore_index, verify_integrity, copy, sort)\u001b[0m\n\u001b[1;32m 422\u001b[0m objs \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mlist\u001b[39m(objs)\n\u001b[1;32m 424\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(objs) \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[0;32m--> 425\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mNo objects to concatenate\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 427\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m keys \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 428\u001b[0m objs \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mlist\u001b[39m(com\u001b[38;5;241m.\u001b[39mnot_none(\u001b[38;5;241m*\u001b[39mobjs))\n", + "\u001b[0;31mValueError\u001b[0m: No objects to concatenate" + ] + } + ], "source": [ "# Load all results into a single file\n", "print('Combining data')\n", @@ -791,7 +1032,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.10" + "version": "3.10.13" }, "widgets": { "application/vnd.jupyter.widget-state+json": { From 4008a314fa4e4ae823ce3104a1b86324ecc5a0c6 Mon Sep 17 00:00:00 2001 From: Robbi Bishop-Taylor Date: Wed, 31 Jul 2024 07:47:08 +0000 Subject: [PATCH 02/45] 2023 update --- coastlines/continental.py | 2 +- coastlines/raster.py | 2 +- coastlines/styles.csv | 9695 +++++++++-------- coastlines/vector.py | 2 +- notebooks/DEACoastlines_generation_CLI.ipynb | 169 +- ...DEACoastlines_generation_continental.ipynb | 133 +- .../DEACoastlines_generation_vector.ipynb | 12 +- notebooks/DEACoastlines_utils.ipynb | 8 +- requirements.in | 44 +- requirements.txt | 505 +- 10 files changed, 5400 insertions(+), 5172 deletions(-) diff --git a/coastlines/continental.py b/coastlines/continental.py index 80faaaa8..6018810f 100644 --- a/coastlines/continental.py +++ b/coastlines/continental.py @@ -284,7 +284,7 @@ def continental_cli( # Aggregate/summarise values by taking median of all points # within each buffered polygon - hotspot_values = hotspot_grouped.median().round(2) + hotspot_values = hotspot_grouped.median(numeric_only=True).round(2) # Extract year from distance columns (remove "dist_") x_years = hotspot_values.columns.str.replace("dist_", "").astype(int) diff --git a/coastlines/raster.py b/coastlines/raster.py index 76600b94..2be4b47f 100644 --- a/coastlines/raster.py +++ b/coastlines/raster.py @@ -463,7 +463,7 @@ def export_annual_gapfill( # Ensure that time uses the correct datetime dtype so we # can combine this empty array with our data data - future_ds["time"] = future_ds.time.astype(np.dtype("datetime64[ms]")) + future_ds["time"] = future_ds.time.astype(np.dtype("datetime64[ns]")) # If the current year var contains data, combine these observations # into annual median composites and export GeoTIFFs diff --git a/coastlines/styles.csv b/coastlines/styles.csv index ec356e68..e99011f9 100644 --- a/coastlines/styles.csv +++ b/coastlines/styles.csv @@ -8619,5610 +8619,5760 @@ def my_form_open(dialog, layer, feature): ",1,Wed Oct 19 11:01:04 2022,,,2022-06-02T07:16:19+00:00 ,,shorelines_annual,geom,shorelines_annual," - + 1 1 1 0 - + - + - + - + - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + - + - + - - - - - - - - - - - + + + + + + + + + + + - + - + - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + - + - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + - + - + - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + - + - + - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + - + - + - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + 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+ + + + + + + + + + + + - + - + - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + - + - + - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + - + - + - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + - + - + - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + - + - + - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + - + - + - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + - + - + - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + - + - + - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + - + - + - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + - + - + - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + @@ -14234,161 +14384,161 @@ def my_form_open(dialog, layer, feature): - + - - - - + + + + - + - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + - + - + - - - - - - - - - - - + + + + + + + + + + + - + - ""/> - - + "" wrapChar="""" useMaxLineLengthForAutoWrap=""1"" leftDirectionSymbol=""<""/> + + - @@ -14396,81 +14546,81 @@ def my_form_open(dialog, layer, feature): 0 0 1 - - - - + + + + - + - + - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + @@ -14478,12 +14628,12 @@ def my_form_open(dialog, layer, feature): - + @@ -14491,7 +14641,7 @@ def my_form_open(dialog, layer, feature): - + @@ -14531,45 +14681,45 @@ def my_form_open(dialog, layer, feature): - - - - - + + + + + - - - - - + + + + + - - - - - + + + + + - - - - - + + + + + - + - + - @@ -14617,20 +14767,20 @@ def my_form_open(dialog, layer, feature): - - - - - - - - - - - - - - + + + + + + + + + + + + + + @@ -14646,7 +14796,7 @@ def my_form_open(dialog, layer, feature): 1 "," - + shorelines_annual @@ -15645,6 +15795,34 @@ def my_form_open(dialog, layer, feature): 0 25000 + + + #feffbf + 2 + bevel + square + + + + + 2023 + + 2023 + + + + + certainty + good + + + year + 2023 + + + + 0 + 25000 #ffffe1 @@ -16681,6 +16859,35 @@ def my_form_open(dialog, layer, feature): 0 25000 + + + #feffbf + 1 + bevel + square + 4 2 + + + + + 2023 + + 2023 + + + + + certainty + good + + + year + 2022 + + + + 0 + 25000 #ffffe1 @@ -16723,4 +16930,4 @@ def my_form_open(dialog, layer, feature): -",1,Mon Jul 31 15:19:16 2023,,,2022-06-02T07:16:19+00:00 +",1,Wed Jul 31 17:36:11 2024,,,2022-06-02T07:16:19+00:00 diff --git a/coastlines/vector.py b/coastlines/vector.py index 2a9ccabd..3c4f5ef3 100644 --- a/coastlines/vector.py +++ b/coastlines/vector.py @@ -129,7 +129,7 @@ def load_rasters( time_var = xr.Variable("year", [int(i.split("/")[-1][0:4]) for i in paths]) # Import data - layer_da = xr.concat([xr.open_rasterio(i) for i in paths], dim=time_var) + layer_da = xr.concat([xr.open_dataset(i, engine="rasterio").band_data for i in paths], dim=time_var) layer_da.name = f"{layer_name}" # Append to file diff --git a/notebooks/DEACoastlines_generation_CLI.ipynb b/notebooks/DEACoastlines_generation_CLI.ipynb index 346ade12..3405c381 100644 --- a/notebooks/DEACoastlines_generation_CLI.ipynb +++ b/notebooks/DEACoastlines_generation_CLI.ipynb @@ -77,14 +77,14 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "id": "4729d261-6b27-4a61-a937-366c5174ce05", "metadata": { "tags": [] }, "outputs": [], "source": [ - "study_area = 283\n", + "study_area = 64\n", "raster_version = 'testing2023'\n", "vector_version = 'testing2023'\n", "continental_version = 'testing2023'\n", @@ -108,7 +108,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 2, "id": "dc5632c4-f872-46e5-9762-80b8556f3622", "metadata": { "tags": [] @@ -197,135 +197,10 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "id": "47397eb8-ddec-46c6-9f7c-431a50bb7eae", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "/env/lib/python3.10/site-packages/distributed/node.py:182: UserWarning: Port 8787 is already in use.\n", - "Perhaps you already have a cluster running?\n", - "Hosting the HTTP server on port 37049 instead\n", - " warnings.warn(\n", - "\n", - "2024-07-31 02:44:57 INFO Study area 283: Loaded study area grid\n", - "2024-07-31 02:45:03 INFO Study area 283: Loaded virtual product\n", - "Creating reduced resolution 5000 x 5000 metre tide modelling array\n", - "Modelling tides using FES2014 in parallel\n", - "100%|█████████████████████████████████████████████| 5/5 [00:09<00:00, 1.82s/it]\n", - "Reprojecting tides into original array\n", - "/env/lib/python3.10/site-packages/rasterio/warp.py:344: NotGeoreferencedWarning: Dataset has no geotransform, gcps, or rpcs. The identity matrix will be returned.\n", - " _reproject(\n", - "2024-07-31 02:45:31 INFO Study area 283: Finished modelling tide heights\n", - "2024-07-31 02:45:32 INFO Study area 283: Calculating low and high tide cutoffs for each pixel\n", - "2024-07-31 02:45:32 INFO Study area 283: Started exporting raster data\n", - "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", - " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", - "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", - " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", - "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", - " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", - "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", - " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", - "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", - " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", - "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", - " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", - "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", - " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", - "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", - " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", - "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", - " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", - "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", - " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", - "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", - " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", - "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", - " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", - "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", - " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", - "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", - " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", - "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", - " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", - "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", - " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", - "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", - " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", - "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", - " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", - "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", - " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", - "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", - " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", - "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", - " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", - "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", - " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", - "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", - " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", - "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", - " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", - "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", - " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", - "/home/jovyan/Robbi/dea-coastlines/coastlines/raster.py:466: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.\n", - " future_ds[\"time\"] = future_ds.time.astype(np.dtype(\"datetime64[ms]\"))\n", - "/env/lib/python3.10/site-packages/distributed/client.py:3161: UserWarning: Sending large graph of size 38.13 MiB.\n", - "This may cause some slowdown.\n", - "Consider scattering data ahead of time and using futures.\n", - " warnings.warn(\n", - "/env/lib/python3.10/site-packages/distributed/client.py:3161: UserWarning: Sending large graph of size 76.22 MiB.\n", - "This may cause some slowdown.\n", - "Consider scattering data ahead of time and using futures.\n", - " warnings.warn(\n", - "/env/lib/python3.10/site-packages/distributed/client.py:3161: UserWarning: Sending large graph of size 102.88 MiB.\n", - "This may cause some slowdown.\n", - "Consider scattering data ahead of time and using futures.\n", - " warnings.warn(\n", - "/env/lib/python3.10/site-packages/distributed/client.py:3161: UserWarning: Sending large graph of size 91.46 MiB.\n", - "This may cause some slowdown.\n", - "Consider scattering data ahead of time and using futures.\n", - " warnings.warn(\n", - "/env/lib/python3.10/site-packages/distributed/client.py:3161: UserWarning: Sending large graph of size 87.65 MiB.\n", - "This may cause some slowdown.\n", - "Consider scattering data ahead of time and using futures.\n", - " warnings.warn(\n", - "/env/lib/python3.10/site-packages/distributed/client.py:3161: UserWarning: Sending large graph of size 91.46 MiB.\n", - "This may cause some slowdown.\n", - "Consider scattering data ahead of time and using futures.\n", - " warnings.warn(\n", - "/env/lib/python3.10/site-packages/distributed/client.py:3161: UserWarning: Sending large graph of size 110.50 MiB.\n", - "This may cause some slowdown.\n", - "Consider scattering data ahead of time and using futures.\n", - " warnings.warn(\n", - "/env/lib/python3.10/site-packages/distributed/client.py:3161: UserWarning: Sending large graph of size 106.69 MiB.\n", - "This may cause some slowdown.\n", - "Consider scattering data ahead of time and using futures.\n", - " warnings.warn(\n", - "/env/lib/python3.10/site-packages/distributed/client.py:3161: UserWarning: Sending large graph of size 110.51 MiB.\n", - "This may cause some slowdown.\n", - "Consider scattering data ahead of time and using futures.\n", - " warnings.warn(\n", - "/env/lib/python3.10/site-packages/distributed/client.py:3161: UserWarning: Sending large graph of size 110.52 MiB.\n", - "This may cause some slowdown.\n", - "Consider scattering data ahead of time and using futures.\n", - " warnings.warn(\n", - "/env/lib/python3.10/site-packages/distributed/client.py:3161: UserWarning: Sending large graph of size 118.14 MiB.\n", - "This may cause some slowdown.\n", - "Consider scattering data ahead of time and using futures.\n", - " warnings.warn(\n", - "/env/lib/python3.10/site-packages/distributed/client.py:3161: UserWarning: Sending large graph of size 53.38 MiB.\n", - "This may cause some slowdown.\n", - "Consider scattering data ahead of time and using futures.\n", - " warnings.warn(\n", - "2024-07-31 02:51:20 INFO Study area 283: Completed exporting raster data\n", - "\u001b[0m\u001b[0m" - ] - } - ], + "outputs": [], "source": [ "!python -m coastlines.raster --config_path {config_path} --study_area {study_area} --raster_version {raster_version} --start_year 1988 --end_year 2023" ] @@ -398,7 +273,8 @@ " access\n", " --overwrite / --no-overwrite Whether to overwrite tiles with existing\n", " outputs, or skip these tiles entirely.\n", - " --help Show this message and exit.\n" + " --help Show this message and exit.\n", + "\u001b[0m" ] } ], @@ -416,32 +292,12 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "id": "c23665e0-6d46-4185-b9f0-04a50d856174", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "2024-07-31 02:51:31 INFO Study area 283: Starting vector generation\n", - "2024-07-31 02:51:31 ERROR Study area 283: Failed to run process with error module 'xarray' has no attribute 'open_rasterio'\n", - "Traceback (most recent call last):\n", - " File \"/home/jovyan/Robbi/dea-coastlines/coastlines/vector.py\", line 1810, in generate_vectors_cli\n", - " generate_vectors(\n", - " File \"/home/jovyan/Robbi/dea-coastlines/coastlines/vector.py\", line 1390, in generate_vectors\n", - " yearly_ds, gapfill_ds = load_rasters(\n", - " File \"/home/jovyan/Robbi/dea-coastlines/coastlines/vector.py\", line 132, in load_rasters\n", - " layer_da = xr.concat([xr.open_rasterio(i) for i in paths], dim=time_var)\n", - " File \"/home/jovyan/Robbi/dea-coastlines/coastlines/vector.py\", line 132, in \n", - " layer_da = xr.concat([xr.open_rasterio(i) for i in paths], dim=time_var)\n", - "AttributeError: module 'xarray' has no attribute 'open_rasterio'\n", - "\u001b[0m" - ] - } - ], + "outputs": [], "source": [ - "!python -m coastlines.vector --config_path {config_path} --study_area {study_area} --raster_version {raster_version} --start_year 1988 --end_year 2022 --baseline_year 2023" + "!python -m coastlines.vector --config_path {config_path} --study_area {study_area} --raster_version {raster_version} --start_year 1988 --end_year 2023 --baseline_year 2023" ] }, { @@ -514,7 +370,8 @@ " --include-styles / --no-include-styles\n", " Set this to indicate whether to include\n", " styles in the output OGC GeoPackage file.\n", - " --help Show this message and exit.\n" + " --help Show this message and exit.\n", + "\u001b[0m" ] } ], @@ -537,7 +394,7 @@ "metadata": {}, "outputs": [], "source": [ - "!python -m coastlines.continental --vector_version {vector_version} --continental_version {continental_version} --shorelines True --ratesofchange True --hotspots True --baseline_year 2022" + "!python -m coastlines.continental --vector_version {vector_version} --continental_version {continental_version} --shorelines True --ratesofchange True --hotspots True --baseline_year 2023" ] }, { diff --git a/notebooks/DEACoastlines_generation_continental.ipynb b/notebooks/DEACoastlines_generation_continental.ipynb index 5d4eb06f..1ff186a8 100644 --- a/notebooks/DEACoastlines_generation_continental.ipynb +++ b/notebooks/DEACoastlines_generation_continental.ipynb @@ -30,7 +30,9 @@ { "cell_type": "code", "execution_count": 1, - "metadata": {}, + "metadata": { + "tags": [] + }, "outputs": [ { "name": "stdout", @@ -55,27 +57,19 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[33mWARNING: You are using pip version 22.0.2; however, version 22.3.1 is available.\n", - "You should consider upgrading via the '/env/bin/python -m pip install --upgrade pip' command.\u001b[0m\u001b[33m\n", - "\u001b[0mNote: you may need to restart the kernel to use updated packages.\n" - ] - } - ], + "outputs": [], "source": [ "pip install -r requirements.in --quiet" ] }, { "cell_type": "code", - "execution_count": 3, - "metadata": {}, + "execution_count": 2, + "metadata": { + "tags": [] + }, "outputs": [], "source": [ "%matplotlib inline\n", @@ -105,13 +99,15 @@ }, { "cell_type": "code", - "execution_count": 5, - "metadata": {}, + "execution_count": 3, + "metadata": { + "tags": [] + }, "outputs": [], "source": [ - "vector_version = \"development\"\n", - "continental_version = \"development\"\n", - "baseline_year = 2021\n", + "vector_version = \"testing2023\"\n", + "continental_version = \"testing2023\"\n", + "baseline_year = 2023\n", "hotspots_radius = [10000, 5000, 1000]\n" ] }, @@ -124,8 +120,10 @@ }, { "cell_type": "code", - "execution_count": 6, - "metadata": {}, + "execution_count": 4, + "metadata": { + "tags": [] + }, "outputs": [], "source": [ "# Make output directory \n", @@ -159,23 +157,18 @@ }, { "cell_type": "code", - "execution_count": 7, - "metadata": {}, + "execution_count": 5, + "metadata": { + "tags": [] + }, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Warning 1: A geometry of type MULTILINESTRING is inserted into layer shorelines_annual of geometry type LINESTRING, which is not normally allowed by the GeoPackage specification, but the driver will however do it. To create a conformant GeoPackage, if using ogr2ogr, the -nlt option can be used to override the layer geometry type. This warning will no longer be emitted for this combination of layer and feature geometry type.\n" - ] - }, { "data": { "text/plain": [ "0" ] }, - "execution_count": 7, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } @@ -198,8 +191,10 @@ }, { "cell_type": "code", - "execution_count": 8, - "metadata": {}, + "execution_count": 6, + "metadata": { + "tags": [] + }, "outputs": [ { "data": { @@ -207,7 +202,7 @@ "0" ] }, - "execution_count": 8, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } @@ -231,8 +226,10 @@ }, { "cell_type": "code", - "execution_count": 9, - "metadata": {}, + "execution_count": 8, + "metadata": { + "tags": [] + }, "outputs": [], "source": [ "# Load continental rates of change data\n", @@ -243,6 +240,38 @@ "shorelines_gdf = shorelines_gdf.loc[shorelines_gdf.geometry.is_valid]" ] }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "Index(['rate_time', 'sig_time', 'se_time', 'outl_time', 'dist_1988',\n", + " 'dist_1989', 'dist_1990', 'dist_1991', 'dist_1992', 'dist_1993',\n", + " 'dist_1994', 'dist_1995', 'dist_1996', 'dist_1997', 'dist_1998',\n", + " 'dist_1999', 'dist_2000', 'dist_2001', 'dist_2002', 'dist_2003',\n", + " 'dist_2004', 'dist_2005', 'dist_2006', 'dist_2007', 'dist_2008',\n", + " 'dist_2009', 'dist_2010', 'dist_2011', 'dist_2012', 'dist_2013',\n", + " 'dist_2014', 'dist_2015', 'dist_2016', 'dist_2017', 'dist_2018',\n", + " 'dist_2019', 'dist_2020', 'dist_2021', 'dist_2022', 'dist_2023',\n", + " 'angle_mean', 'angle_std', 'valid_obs', 'valid_span', 'sce', 'nsm',\n", + " 'max_year', 'min_year', 'certainty', 'id_primary', 'geometry'],\n", + " dtype='object')" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ratesofchange_gdf.columns" + ] + }, { "cell_type": "markdown", "metadata": { @@ -254,8 +283,10 @@ }, { "cell_type": "code", - "execution_count": 10, - "metadata": {}, + "execution_count": 39, + "metadata": { + "tags": [] + }, "outputs": [ { "name": "stdout", @@ -299,7 +330,7 @@ "\n", " # Aggregate/summarise values by taking median of all points\n", " # within each buffered polygon\n", - " hotspot_values = hotspot_grouped.median().round(2)\n", + " hotspot_values = hotspot_grouped.median(numeric_only=True).round(2)\n", "\n", " # Extract year from distance columns (remove \"dist_\")\n", " x_years = hotspot_values.columns.str.replace(\"dist_\", \"\").astype(int)\n", @@ -336,7 +367,7 @@ " hotspots_gdf.loc[\n", " hotspots_gdf.n < (radius / 30), \"certainty\"\n", " ] = \"insufficient points\"\n", - " \n", + "\n", " # Generate a geohash UID for each point and set as index\n", " uids = (\n", " hotspots_gdf.geometry.to_crs(\"EPSG:4326\")\n", @@ -378,8 +409,10 @@ }, { "cell_type": "code", - "execution_count": 11, - "metadata": {}, + "execution_count": 40, + "metadata": { + "tags": [] + }, "outputs": [], "source": [ "# Add rates of change points to shapefile zip\n", @@ -397,8 +430,10 @@ }, { "cell_type": "code", - "execution_count": 12, - "metadata": {}, + "execution_count": 41, + "metadata": { + "tags": [] + }, "outputs": [], "source": [ "# Add annual shorelines to shapefile zip\n", @@ -421,8 +456,10 @@ }, { "cell_type": "code", - "execution_count": 13, - "metadata": {}, + "execution_count": 42, + "metadata": { + "tags": [] + }, "outputs": [], "source": [ "# Insert styles table into GeoPackage\n", @@ -476,7 +513,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.10" + "version": "3.10.13" }, "widgets": { "application/vnd.jupyter.widget-state+json": { diff --git a/notebooks/DEACoastlines_generation_vector.ipynb b/notebooks/DEACoastlines_generation_vector.ipynb index fd3161c5..b1eda3c4 100644 --- a/notebooks/DEACoastlines_generation_vector.ipynb +++ b/notebooks/DEACoastlines_generation_vector.ipynb @@ -115,9 +115,9 @@ }, "outputs": [], "source": [ - "study_area = 64\n", - "raster_version = 'testing2022'\n", - "vector_version = 'testing2022'\n", + "study_area = 283\n", + "raster_version = 'testing2023'\n", + "vector_version = 'testing2023'\n", "config_path = 'configs/dea_coastlines_config.yaml'\n", "\n", "# study_area = 9\n", @@ -128,8 +128,8 @@ "water_index = \"mndwi\"\n", "index_threshold = 0.00\n", "start_year = 1988\n", - "end_year = 2022\n", - "baseline_year = 2022\n", + "end_year = 2023\n", + "baseline_year = 2023\n", "\n", "# Load analysis params from config file\n", "config = coastlines.raster.load_config(\n", @@ -747,7 +747,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.10" + "version": "3.10.13" }, "widgets": { "application/vnd.jupyter.widget-state+json": { diff --git a/notebooks/DEACoastlines_utils.ipynb b/notebooks/DEACoastlines_utils.ipynb index 1438acb3..1838db42 100644 --- a/notebooks/DEACoastlines_utils.ipynb +++ b/notebooks/DEACoastlines_utils.ipynb @@ -24,7 +24,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 2, "metadata": { "tags": [] }, @@ -52,7 +52,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 4, "metadata": { "tags": [] }, @@ -125,14 +125,14 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 5, "metadata": { "tags": [] }, "outputs": [], "source": [ "# Load 'layer_styles' from geopackage and export as a CSV\n", - "layer = gpd.read_file(\"coastlines_testing2022 (1).gpkg\", layer=\"layer_styles\")\n", + "layer = gpd.read_file(\"coastlines_testing2023 (2).gpkg\", layer=\"layer_styles\")\n", "layer.drop(['geometry'], axis=1).to_csv('coastlines/styles.csv', index=False)" ] }, diff --git a/requirements.in b/requirements.in index 9461c875..95c5791a 100644 --- a/requirements.in +++ b/requirements.in @@ -2,29 +2,29 @@ aiohttp affine==2.4.0 botocore -click==8.1.3 -dask==2023.2.0 -datacube[s3,performance]==1.8.13 -dea_tools==0.2.8.dev117 -Fiona==1.8.22 -geopandas==0.13.2 -matplotlib==3.7.1 +click==8.1.7 +dask==2024.4.2 +datacube[s3,performance]==1.8.18 +dea_tools==0.3.4 +Fiona==1.9.4 +geopandas==0.14.3 +matplotlib==3.8.4 mdutils==1.5.0 -numpy==1.23.5 -odc-geo==0.4.0 -odc_ui==0.2.1.dev3676 -pandas==1.5.3 +numpy==1.26.4 +odc-geo==0.4.3 +odc_ui==0.2.1 +pandas==2.2.2 pygeos==0.14 -pyproj==3.4.1 -pyTMD==2.0.6 +pyproj==3.6.1 +pyTMD==2.1.4 python_geohash==0.8.5 -pytz==2023.3 -PyYAML==5.4.1 -rasterio==1.3.4 -scikit_image==0.19.3 -scikit_learn==1.2.2 -scipy==1.10.1 -setuptools==67.7.2 +pytz==2024.1 +PyYAML==6.0.1 +rasterio==1.3.8 +scikit_image==0.22.0 +scikit_learn==1.4.2 +scipy==1.13.0 +setuptools==69.5.1 Shapely==2.0.1 -tqdm==4.65.0 -xarray==2023.1.0 +tqdm==4.66.2 +xarray==2024.3.0 diff --git a/requirements.txt b/requirements.txt index 44b9fe61..51f8df9e 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,5 +1,5 @@ # -# This file is autogenerated by pip-compile with Python 3.8 +# This file is autogenerated by pip-compile with Python 3.10 # by the following command: # # pip-compile --extra-index-url=https://packages.dea.ga.gov.au/ --output-file=requirements.txt requirements.in @@ -10,76 +10,91 @@ affine==2.4.0 # via # -r requirements.in # datacube + # datacube-ows # odc-algo # odc-geo + # odc-stac # rasterio # rasterstats -aiohttp==3.8.4 +aiohappyeyeballs==2.3.2 + # via aiohttp +aiohttp==3.10.0 # via # -r requirements.in # dea-tools aiosignal==1.3.1 # via aiohttp -asttokens==2.2.1 +annotated-types==0.7.0 + # via pydantic +asttokens==2.4.1 # via stack-data -async-timeout==4.0.2 +async-timeout==4.0.3 # via aiohttp -attrs==22.2.0 +attrs==23.2.0 # via # aiohttp # datacube # fiona # jsonschema # rasterio -backcall==0.2.0 - # via ipython -boto3==1.26.73 + # referencing +babel==2.15.0 + # via + # datacube-ows + # flask-babel +blinker==1.8.2 + # via flask +boto3==1.34.151 # via # datacube # dea-tools -botocore==1.29.73 +botocore==1.34.151 # via # -r requirements.in # boto3 # datacube # dea-tools # s3transfer -bottleneck==1.3.6 +bottleneck==1.4.0 # via datacube -branca==0.6.0 +branca==0.7.2 # via # dea-tools # folium # ipyleaflet -cachetools==5.3.0 +cachetools==5.4.0 # via # datacube # odc-geo -certifi==2022.12.7 +certifi==2024.7.4 # via # fiona + # netcdf4 # pyproj # rasterio # requests -cftime==1.6.2 +cffi==1.16.0 + # via timezonefinder +cftime==1.6.4 # via netcdf4 -charset-normalizer==3.0.1 - # via - # aiohttp - # requests -ciso8601==2.3.0 +charset-normalizer==3.3.2 + # via requests +ciso8601==2.3.1 # via # datacube # dea-tools -click==8.1.3 +click==8.1.7 # via # -r requirements.in # click-plugins # cligj # dask # datacube + # datacube-ows # distributed # fiona + # flask + # planetary-computer # rasterio # rasterstats click-plugins==1.1.1 @@ -91,193 +106,223 @@ cligj==0.7.2 # fiona # rasterio # rasterstats -cloudpickle==2.2.1 +cloudpickle==3.0.0 # via # dask # dask-glm # datacube # distributed -comm==0.1.2 - # via ipykernel -contourpy==1.0.7 +colour==0.1.5 + # via datacube-ows +comm==0.2.2 + # via ipywidgets +contourpy==1.2.1 # via matplotlib -cycler==0.11.0 +cycler==0.12.1 # via matplotlib -dask[array,dataframe]==2023.2.0 +dask[array,dataframe]==2024.4.2 # via # -r requirements.in + # dask-expr # dask-glm # dask-image # dask-ml # datacube + # dea-tools # distributed # odc-algo -dask-glm==0.2.0 + # odc-stac +dask-expr==1.0.14 + # via dask +dask-glm==0.3.2 # via dask-ml -dask-image==2022.9.0 +dask-image==2024.5.3 # via odc-algo -dask-ml==2022.5.27 +dask-ml==2024.4.4 # via dea-tools -datacube[performance,s3]==1.8.13 +datacube[performance,s3]==1.8.18 # via # -r requirements.in + # datacube-ows # dea-tools # odc-algo # odc-ui -dea-tools==0.2.8.dev117 +datacube-ows==1.8.41 + # via dea-tools +dea-tools==0.3.4 # via -r requirements.in -debugpy==1.6.6 - # via ipykernel decorator==5.1.1 # via ipython -distributed==2023.2.0 +deepdiff==7.0.1 + # via datacube-ows +deprecat==2.1.3 + # via datacube +distributed==2024.4.2 # via + # dask-glm # dask-ml # datacube # odc-algo -executing==1.2.0 +exceptiongroup==1.2.2 + # via ipython +executing==2.0.1 # via stack-data -fiona==1.8.22 +fiona==1.9.4 # via # -r requirements.in # dea-tools # geopandas # rasterstats -folium==0.14.0 +flask==3.0.3 + # via + # datacube-ows + # flask-babel + # prometheus-flask-exporter +flask-babel==4.0.0 + # via datacube-ows +folium==0.17.0 # via dea-tools -fonttools==4.38.0 +fonttools==4.53.1 # via matplotlib -frozenlist==1.3.3 +frozenlist==1.4.1 # via # aiohttp # aiosignal -fsspec==2023.1.0 - # via dask -geoalchemy2==0.13.1 - # via datacube +fsspec==2024.6.1 + # via + # dask + # datacube-ows +geoalchemy2==0.15.2 + # via + # datacube + # datacube-ows geographiclib==2.0 # via geopy -geopandas==0.13.2 +geopandas==0.14.3 # via # -r requirements.in # dea-tools -geopy==2.3.0 +geopy==2.4.1 # via dea-tools -greenlet==2.0.2 +greenlet==3.0.3 # via sqlalchemy +h3==3.7.7 + # via timezonefinder hdstats==0.2.1 # via dea-tools -heapdict==1.0.1 - # via zict -idna==3.4 +idna==3.7 # via # requests # yarl -imageio==2.25.1 +imageio==2.34.2 # via # pims # scikit-image -importlib-metadata==6.0.0 - # via - # jupyter-client - # numba -importlib-resources==5.10.2 - # via - # jsonschema - # matplotlib -ipykernel==6.21.2 - # via ipywidgets -ipyleaflet==0.17.2 +importlib-metadata==8.2.0 + # via dask +ipyleaflet==0.19.2 # via odc-ui -ipython==8.10.0 +ipython==8.26.0 # via - # ipykernel # ipywidgets # jupyter-ui-poll # odc-ui -ipywidgets==8.0.4 +ipywidgets==8.1.3 # via # ipyleaflet # odc-ui -jedi==0.18.2 +iso8601==2.1.0 + # via pyows +itsdangerous==2.2.0 + # via flask +jedi==0.19.1 # via ipython -jinja2==3.1.2 +jinja2==3.1.4 # via # branca # distributed + # flask + # flask-babel # folium jmespath==1.0.1 # via # boto3 # botocore -joblib==1.2.0 +joblib==1.4.2 # via # dea-tools # scikit-learn -jsonschema==4.17.3 - # via datacube -jupyter-client==8.0.3 - # via ipykernel -jupyter-core==5.2.0 +jsonschema==4.23.0 # via - # ipykernel - # jupyter-client -jupyter-ui-poll==0.2.2 + # datacube + # pystac +jsonschema-specifications==2023.12.1 + # via jsonschema +jupyter-leaflet==0.19.2 + # via ipyleaflet +jupyter-ui-poll==1.0.0 # via odc-ui -jupyterlab-widgets==3.0.5 +jupyterlab-widgets==3.0.11 # via ipywidgets -kiwisolver==1.4.4 +kiwisolver==1.4.5 # via matplotlib -lark==1.1.5 - # via datacube -llvmlite==0.39.1 +lark==1.1.9 + # via + # datacube + # datacube-ows +lazy-loader==0.4 + # via scikit-image +llvmlite==0.43.0 # via numba locket==1.0.0 # via # distributed # partd -lxml==4.9.2 +lxml==5.2.2 # via + # datacube-ows # dea-tools + # owslib + # pyows # pytmd -markupsafe==2.1.2 - # via jinja2 -matplotlib==3.7.1 + # timescale +markupsafe==2.1.5 + # via + # jinja2 + # werkzeug +matplotlib==3.8.4 # via # -r requirements.in + # datacube-ows # dea-tools # odc-ui -matplotlib-inline==0.1.6 - # via - # ipykernel - # ipython +matplotlib-inline==0.1.7 + # via ipython mdutils==1.5.0 # via -r requirements.in -msgpack==1.0.4 +msgpack==1.0.8 # via distributed -multidict==6.0.4 +multidict==6.0.5 # via # aiohttp # yarl -multipledispatch==0.6.0 +multipledispatch==1.0.0 # via # dask-glm # dask-ml -munch==2.5.0 - # via fiona -nest-asyncio==1.5.6 - # via ipykernel -netcdf4==1.6.2 +netcdf4==1.7.1.post1 # via # datacube # pytmd -networkx==3.0 +networkx==3.3 # via scikit-image -numba==0.56.4 - # via dask-ml -numexpr==2.8.4 +numba==0.60.0 + # via + # dask-ml + # sparse +numexpr==2.10.1 # via odc-algo -numpy==1.23.5 +numpy==1.26.4 # via # -r requirements.in # bottleneck @@ -287,6 +332,7 @@ numpy==1.23.5 # dask-image # dask-ml # datacube + # datacube-ows # dea-tools # folium # hdstats @@ -297,32 +343,44 @@ numpy==1.23.5 # numexpr # odc-algo # odc-geo + # odc-stac # odc-ui # pandas # pims + # pyarrow # pygeos # pytmd - # pywavelets # rasterio # rasterstats + # rioxarray # scikit-image # scikit-learn # scipy # shapely # snuggs + # sparse # tifffile + # timescale + # timezonefinder # xarray odc-algo==0.2.3 # via odc-ui -odc-geo==0.4.0 - # via -r requirements.in -odc-ui==0.2.1.dev3676 +odc-geo==0.4.3 # via # -r requirements.in # dea-tools -owslib==0.27.2 + # odc-stac +odc-stac==0.3.9 # via dea-tools -packaging==23.0 +odc-ui==0.2.1 + # via + # -r requirements.in + # dea-tools +ordered-set==4.1.0 + # via deepdiff +owslib==0.31.0 + # via dea-tools +packaging==24.1 # via # dask # dask-ml @@ -331,61 +389,79 @@ packaging==23.0 # distributed # geoalchemy2 # geopandas - # ipykernel + # lazy-loader # matplotlib + # pims + # planetary-computer + # rioxarray # scikit-image # setuptools-scm # xarray -pandas==1.5.3 +pandas==2.2.2 # via # -r requirements.in # dask + # dask-expr + # dask-image # dask-ml # datacube # dea-tools # geopandas + # odc-stac # odc-ui # xarray -parso==0.8.3 +parso==0.8.4 # via jedi -partd==1.3.0 +partd==1.4.2 # via dask -pexpect==4.8.0 - # via ipython -pickleshare==0.7.5 +pexpect==4.9.0 # via ipython -pillow==9.4.0 +pillow==10.4.0 # via + # datacube-ows # imageio # matplotlib # scikit-image -pims==0.6.1 +pims==0.7 # via dask-image -pkgutil-resolve-name==1.3.10 - # via jsonschema -platformdirs==3.0.0 - # via jupyter-core -prompt-toolkit==3.0.36 +planetary-computer==1.0.0 + # via dea-tools +prometheus-client==0.20.0 + # via prometheus-flask-exporter +prometheus-flask-exporter==0.23.1 + # via datacube-ows +prompt-toolkit==3.0.47 # via ipython -psutil==5.9.4 +psutil==6.0.0 + # via distributed +psycopg2==2.9.9 # via - # distributed - # ipykernel -psycopg2==2.9.5 - # via datacube + # datacube + # datacube-ows ptyprocess==0.7.0 # via pexpect -pure-eval==0.2.2 +pure-eval==0.2.3 # via stack-data +pyarrow==17.0.0 + # via dask-expr +pycparser==2.22 + # via cffi +pydantic==2.8.2 + # via planetary-computer +pydantic-core==2.20.1 + # via pydantic pygeos==0.14 # via -r requirements.in -pygments==2.14.0 +pygments==2.18.0 # via ipython -pyparsing==3.0.9 +pyows==0.3.1 + # via datacube-ows +pyparsing==3.1.2 # via + # datacube-ows # matplotlib # snuggs -pyproj==3.4.1 +pyproj==3.6.1 # via # -r requirements.in # datacube @@ -393,89 +469,124 @@ pyproj==3.4.1 # geopandas # odc-geo # pytmd -pyrsistent==0.19.3 - # via jsonschema -python-dateutil==2.8.2 + # rioxarray +pystac[validation]==1.10.1 + # via + # odc-stac + # planetary-computer + # pystac-client +pystac-client==0.8.3 + # via + # dea-tools + # planetary-computer +python-dateutil==2.9.0.post0 # via # botocore # datacube + # datacube-ows # dea-tools - # jupyter-client # matplotlib # owslib # pandas + # pystac + # pystac-client # pytmd + # timescale +python-dotenv==1.0.1 + # via planetary-computer python-geohash==0.8.5 # via -r requirements.in -pytmd==2.0.6 +python-slugify==8.0.4 + # via datacube-ows +pytmd==2.1.4 # via # -r requirements.in # dea-tools -pytz==2023.3 +pytz==2024.1 # via # -r requirements.in + # datacube-ows # dea-tools + # flask-babel # owslib # pandas -pywavelets==1.4.1 - # via scikit-image -pyyaml==5.4.1 + # planetary-computer +pyyaml==6.0.1 # via # -r requirements.in # dask # datacube # distributed # owslib - # pytmd -pyzmq==25.0.0 - # via - # ipykernel - # jupyter-client -rasterio==1.3.4 +rasterio==1.3.8 # via # -r requirements.in # datacube + # datacube-ows # dea-tools # odc-algo + # odc-stac # odc-ui # rasterstats -rasterstats==0.18.0 + # rioxarray +rasterstats==0.19.0 # via dea-tools -requests==2.28.2 +referencing==0.35.1 # via + # jsonschema + # jsonschema-specifications +regex==2024.7.24 + # via datacube-ows +requests==2.32.3 + # via + # datacube-ows # dea-tools # folium # owslib -ruamel-yaml==0.17.21 + # planetary-computer + # pystac-client +rioxarray==0.17.0 + # via dea-tools +rpds-py==0.19.1 + # via + # jsonschema + # referencing +ruamel-yaml==0.18.6 # via datacube -ruamel-yaml-clib==0.2.7 +ruamel-yaml-clib==0.2.8 # via ruamel-yaml -s3transfer==0.6.0 +s3transfer==0.10.2 # via boto3 -scikit-image==0.19.3 +scikit-image==0.22.0 # via # -r requirements.in # dea-tools # odc-algo -scikit-learn==1.2.2 +scikit-learn==1.4.2 # via # -r requirements.in # dask-glm # dask-ml # dea-tools -scipy==1.10.1 +scipy==1.13.0 # via # -r requirements.in # dask-glm # dask-image # dask-ml + # datacube-ows # dea-tools # hdstats # pytmd # scikit-image # scikit-learn -setuptools-scm==7.1.0 - # via pytmd + # sparse + # timescale +setuptools-scm==8.1.0 + # via + # datacube-ows + # pytmd + # timescale shapely==2.0.1 # via # -r requirements.in @@ -484,14 +595,12 @@ shapely==2.0.1 # geopandas # odc-geo # rasterstats -simplejson==3.18.3 +simplejson==3.19.2 # via rasterstats six==1.16.0 # via # asttokens # fiona - # multipledispatch - # munch # python-dateutil slicerator==1.1.0 # via pims @@ -499,76 +608,94 @@ snuggs==1.4.7 # via rasterio sortedcontainers==2.4.0 # via distributed -sqlalchemy==1.4.46 +sparse==0.15.4 + # via dask-glm +sqlalchemy==1.4.53 # via # datacube # geoalchemy2 -stack-data==0.6.2 +stack-data==0.6.3 # via ipython -tblib==1.7.0 +tblib==3.0.0 # via distributed -threadpoolctl==3.1.0 +text-unidecode==1.3 + # via python-slugify +threadpoolctl==3.5.0 # via scikit-learn -tifffile==2023.2.3 - # via scikit-image +tifffile==2024.7.24 + # via + # dask-image + # pims + # scikit-image +timescale==0.0.4 + # via pytmd +timezonefinder==6.5.2 + # via datacube-ows tomli==2.0.1 # via setuptools-scm -toolz==0.12.0 +toolz==0.12.1 # via # dask # datacube # distributed # odc-algo + # odc-stac # partd -tornado==6.2 - # via - # distributed - # ipykernel - # jupyter-client -tqdm==4.65.0 +tornado==6.4.1 + # via distributed +tqdm==4.66.2 # via # -r requirements.in # dea-tools -traitlets==5.9.0 +traitlets==5.14.3 # via # comm - # ipykernel # ipython # ipywidgets - # jupyter-client - # jupyter-core # matplotlib-inline # traittypes traittypes==0.2.1 # via ipyleaflet -typing-extensions==4.5.0 - # via setuptools-scm -urllib3==1.26.14 +typing-extensions==4.12.2 + # via + # ipython + # pydantic + # pydantic-core +tzdata==2024.1 + # via pandas +urllib3==2.2.2 # via # botocore # distributed # requests -wcwidth==0.2.6 +wcwidth==0.2.13 # via prompt-toolkit -widgetsnbextension==4.0.5 +werkzeug==3.0.3 + # via flask +widgetsnbextension==4.0.11 # via ipywidgets -xarray==2023.1.0 +wrapt==1.16.0 + # via deprecat +xarray==2024.3.0 # via # -r requirements.in # datacube + # datacube-ows # dea-tools # odc-algo + # odc-stac # odc-ui -xyzservices==2022.9.0 - # via ipyleaflet -yarl==1.8.2 + # rioxarray +xyzservices==2024.6.0 + # via + # folium + # ipyleaflet +yarl==1.9.4 # via aiohttp -zict==2.2.0 +zict==3.0.0 # via distributed -zipp==3.13.0 - # via - # importlib-metadata - # importlib-resources +zipp==3.19.2 + # via importlib-metadata # The following packages are considered to be unsafe in a requirements file: # setuptools From febb077280f7c6feaf8bdd6c4163d2efad9849f4 Mon Sep 17 00:00:00 2001 From: Robbi Bishop-Taylor Date: Wed, 31 Jul 2024 07:48:28 +0000 Subject: [PATCH 03/45] Fix pep --- coastlines/vector.py | 29 ++++++++++++++++------------- 1 file changed, 16 insertions(+), 13 deletions(-) diff --git a/coastlines/vector.py b/coastlines/vector.py index 3c4f5ef3..949fd9df 100644 --- a/coastlines/vector.py +++ b/coastlines/vector.py @@ -129,7 +129,10 @@ def load_rasters( time_var = xr.Variable("year", [int(i.split("/")[-1][0:4]) for i in paths]) # Import data - layer_da = xr.concat([xr.open_dataset(i, engine="rasterio").band_data for i in paths], dim=time_var) + layer_da = xr.concat( + [xr.open_dataset(i, engine="rasterio").band_data for i in paths], + dim=time_var, + ) layer_da.name = f"{layer_name}" # Append to file @@ -1096,9 +1099,9 @@ def calculate_regressions(points_gdf): ), axis=1, ) - points_gdf[ - ["rate_time", "incpt_time", "sig_time", "se_time", "outl_time"] - ] = rate_out + points_gdf[["rate_time", "incpt_time", "sig_time", "se_time", "outl_time"]] = ( + rate_out + ) # Copy slope and intercept into points_subset so they can be # used to temporally de-trend annual distances @@ -1564,20 +1567,20 @@ def generate_vectors( ] = "likely rocky coastline" # Flag extreme rates of change - points_gdf.loc[ - points_gdf.rate_time.abs() > 50, "certainty" - ] = "extreme value (> 50 m)" + points_gdf.loc[points_gdf.rate_time.abs() > 50, "certainty"] = ( + "extreme value (> 50 m)" + ) # Flag points where change does not fall on a line - points_gdf.loc[ - points_gdf.angle_std > 30, "certainty" - ] = "high angular variability" + points_gdf.loc[points_gdf.angle_std > 30, "certainty"] = ( + "high angular variability" + ) # Flag shorelines with less than X valid shorelines valid_obs_thresh = int(points_gdf.columns.str.contains("dist_").sum() * 0.75) - points_gdf.loc[ - points_gdf.valid_obs < valid_obs_thresh, "certainty" - ] = "insufficient observations" + points_gdf.loc[points_gdf.valid_obs < valid_obs_thresh, "certainty"] = ( + "insufficient observations" + ) log.info(f"Study area {study_area}: Calculated rate of change certainty flags") From 9fa8506d9303e740267f91000683de6ca9559aaf Mon Sep 17 00:00:00 2001 From: Robbi Bishop-Taylor Date: Wed, 31 Jul 2024 07:50:21 +0000 Subject: [PATCH 04/45] Clean notebook --- ...DEACoastlines_generation_continental.ipynb | 32 ------------------- 1 file changed, 32 deletions(-) diff --git a/notebooks/DEACoastlines_generation_continental.ipynb b/notebooks/DEACoastlines_generation_continental.ipynb index 1ff186a8..bf56da98 100644 --- a/notebooks/DEACoastlines_generation_continental.ipynb +++ b/notebooks/DEACoastlines_generation_continental.ipynb @@ -240,38 +240,6 @@ "shorelines_gdf = shorelines_gdf.loc[shorelines_gdf.geometry.is_valid]" ] }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": { - "tags": [] - }, - "outputs": [ - { - "data": { - "text/plain": [ - "Index(['rate_time', 'sig_time', 'se_time', 'outl_time', 'dist_1988',\n", - " 'dist_1989', 'dist_1990', 'dist_1991', 'dist_1992', 'dist_1993',\n", - " 'dist_1994', 'dist_1995', 'dist_1996', 'dist_1997', 'dist_1998',\n", - " 'dist_1999', 'dist_2000', 'dist_2001', 'dist_2002', 'dist_2003',\n", - " 'dist_2004', 'dist_2005', 'dist_2006', 'dist_2007', 'dist_2008',\n", - " 'dist_2009', 'dist_2010', 'dist_2011', 'dist_2012', 'dist_2013',\n", - " 'dist_2014', 'dist_2015', 'dist_2016', 'dist_2017', 'dist_2018',\n", - " 'dist_2019', 'dist_2020', 'dist_2021', 'dist_2022', 'dist_2023',\n", - " 'angle_mean', 'angle_std', 'valid_obs', 'valid_span', 'sce', 'nsm',\n", - " 'max_year', 'min_year', 'certainty', 'id_primary', 'geometry'],\n", - " dtype='object')" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "ratesofchange_gdf.columns" - ] - }, { "cell_type": "markdown", "metadata": { From c0b671cccbba76325226063e68c493e201a1ed49 Mon Sep 17 00:00:00 2001 From: Robbi Bishop-Taylor Date: Wed, 31 Jul 2024 07:58:07 +0000 Subject: [PATCH 05/45] Update docker image base --- Dockerfile | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/Dockerfile b/Dockerfile index eccecec6..664e019a 100644 --- a/Dockerfile +++ b/Dockerfile @@ -1,4 +1,4 @@ -FROM osgeo/gdal:ubuntu-small-3.4.1 as base +FROM ghcr.io/osgeo/gdal:ubuntu-small-3.7.3 ENV CURL_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt From 7e7f86430cbc0e45d97863e0289f087e5e582af8 Mon Sep 17 00:00:00 2001 From: Robbi Bishop-Taylor Date: Thu, 1 Aug 2024 10:08:57 +1000 Subject: [PATCH 06/45] Update vector.py --- coastlines/vector.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/coastlines/vector.py b/coastlines/vector.py index 2a9ccabd..166e6a33 100644 --- a/coastlines/vector.py +++ b/coastlines/vector.py @@ -11,6 +11,8 @@ # * Compute rates of coastal change at every 30 m of coastline # using linear regression +# Test tests + import glob import os import sys From 223a3bd746d2ea29ad993827532c274d8a92c475 Mon Sep 17 00:00:00 2001 From: robbibt Date: Thu, 1 Aug 2024 00:28:22 +0000 Subject: [PATCH 07/45] Automatically update integration test validation results --- data/validation/processed/stats_tests.csv | 1 + tests/README.md | 2 +- tests/stats_tests.png | Bin 97733 -> 95524 bytes 3 files changed, 2 insertions(+), 1 deletion(-) diff --git a/data/validation/processed/stats_tests.csv b/data/validation/processed/stats_tests.csv index 8379889d..29c6058e 100644 --- a/data/validation/processed/stats_tests.csv +++ b/data/validation/processed/stats_tests.csv @@ -33,3 +33,4 @@ time,n,mae,rmse,stdev,corr,bias,name 2023-08-07 01:35:06.989065,2669.0,4.84,6.16,5.56,0.975,-2.67,tests 2023-12-13 02:41:20.170714,2669.0,4.84,6.16,5.56,0.975,-2.67,tests 2023-12-19 05:51:54.070412,2669.0,4.84,6.16,5.56,0.975,-2.67,tests +2024-08-01 00:27:59.036809,2669.0,4.84,6.16,5.56,0.975,-2.67,tests diff --git a/tests/README.md b/tests/README.md index 5acaf694..a492a989 100644 --- a/tests/README.md +++ b/tests/README.md @@ -15,7 +15,7 @@ In addition to testing whether the code runs without errors, we also run a small ## Latest integration test validation results -The latest integration test completed at **2023-12-19 16:51**. Compared to the previous run, it had an: +The latest integration test completed at **2024-08-01 10:27**. 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1 Aug 2024 10:45:44 +1000 Subject: [PATCH 08/45] Add experiment database access --- .github/workflows/dea-coastlines-image.yaml | 72 +++++++ .github/workflows/docker.yaml | 118 +++++------ .github/workflows/test.yaml | 214 ++++++++++---------- 3 files changed, 238 insertions(+), 166 deletions(-) create mode 100644 .github/workflows/dea-coastlines-image.yaml diff --git a/.github/workflows/dea-coastlines-image.yaml b/.github/workflows/dea-coastlines-image.yaml new file mode 100644 index 00000000..735f8db5 --- /dev/null +++ b/.github/workflows/dea-coastlines-image.yaml @@ -0,0 +1,72 @@ +name: Image build and test + +env: + IMAGE_NAME: geoscienceaustralia/dea-coastlines + +on: + push: + branches: + - develop + paths: + - 'coastlines/**' + - 'data/**' + - 'tests/**' + - '.github/workflows/dea-coastlines-image.yml' + - 'Dockerfile' + - 'requirements.in' + - 'setup.py' + - 'codecov.yaml' + + pull_request: + branches: + - main + paths: + - 'coastlines/**' + - 'data/**' + - 'tests/**' + - '.github/workflows/dea-coastlines-image.yml' + - 'Dockerfile' + - 'requirements.in' + - 'setup.py' + - 'codecov.yaml' + + release: + types: [edited, published] + +permissions: + id-token: write # Required for requesting Json web token + contents: write # Required for actions/checkout + pull-requests: write # Required for validation results comment bot + +jobs: + test: + runs-on: ubuntu-latest + steps: + - name: Checkout code + uses: actions/checkout@v3 + with: + fetch-depth: 0 + + - name: Configure AWS credentials + uses: aws-actions/configure-aws-credentials@v4 + with: + role-to-assume: arn:aws:iam::060378307146:role/github-actions-dea-notebooks--sandbox + aws-region: ap-southeast-2 + role-duration-seconds: 7200 # 2 hours + + - name: Get database credentials + run: | + username_password=$(aws ssm get-parameter --name /dea-sandbox-eks/sandbox_reader/db.creds --with-decryption --query Parameter.Value --output text) + echo DATACUBE_DB_URL=postgresql://${username_password}@localhost:5432/odc >> $GITHUB_ENV + + - name: Open port forward to RDS + run: | + npx basti connect \ + --custom-target-vpc vpc-086904199e505c1f6 \ + --custom-target-host db-aurora-dea-sandbox-eks-1.cos5zfpkso9m.ap-southeast-2.rds.amazonaws.com \ + --custom-target-port 5432 \ + --local-port 5432 & + # Wait until the connection comes up, but, if it doesn't, don't hang forever. + npx wait-on --timeout 120000 --interval 1000 tcp:127.0.0.1:5432 + echo "PGPORT=5432" >> $GITHUB_ENV + echo "PGHOST=localhost" >> $GITHUB_ENV \ No newline at end of file diff --git a/.github/workflows/docker.yaml b/.github/workflows/docker.yaml index 0a08a3c8..13d7a611 100644 --- a/.github/workflows/docker.yaml +++ b/.github/workflows/docker.yaml @@ -1,59 +1,59 @@ -name: Build and push image - -# Run action on both a push to the "develop" branch, -# and when a Github release is created/edited/published -on: - push: - branches: - - develop - paths: - - 'coastlines/**' - - '.github/workflows/docker.yaml' - - 'Dockerfile' - - release: - types: [created, edited, published] - -permissions: - id-token: write # This is required for requesting the JWT - contents: read # This is required for actions/checkout - -env: - IMAGE_NAME: geoscienceaustralia/dea-coastlines - -jobs: - push_ecr: - runs-on: ubuntu-latest - steps: - - name: Checkout code - uses: actions/checkout@v3 - - # If action is triggered by a release, push image to - # Dockerhub using custom image tag extracted from the release - - name: Get current version tag from release to use as image tag - if: github.event_name == 'release' - run: | - echo "RELEASE=${GITHUB_REF/refs\/tags\/}" >> $GITHUB_ENV - - # If action is trigged by a push (not release), push a - # latest/unstable image to Dockerhub using image tag based - # on the most recent Github tag and commit hash - - name: Get git commit hash for push to branch to use as image tag - if: github.event_name != 'release' - run: | - git fetch --all --tags - echo "RELEASE=$(git describe --tags)" >> $GITHUB_ENV - - - name: Configure AWS credentials - uses: aws-actions/configure-aws-credentials@v1 - with: - role-to-assume: arn:aws:iam::538673716275:role/github-actions-role - aws-region: ap-southeast-2 - - - name: Push image to ECR - uses: whoan/docker-build-with-cache-action@master - with: - context: ./ - registry: 538673716275.dkr.ecr.ap-southeast-2.amazonaws.com - image_name: ${{ env.IMAGE_NAME }} - image_tag: latest,${{ env.RELEASE }} +# name: Build and push image + +# # Run action on both a push to the "develop" branch, +# # and when a Github release is created/edited/published +# on: +# push: +# branches: +# - develop +# paths: +# - 'coastlines/**' +# - '.github/workflows/docker.yaml' +# - 'Dockerfile' + +# release: +# types: [created, edited, published] + +# permissions: +# id-token: write # This is required for requesting the JWT +# contents: read # This is required for actions/checkout + +# env: +# IMAGE_NAME: geoscienceaustralia/dea-coastlines + +# jobs: +# push_ecr: +# runs-on: ubuntu-latest +# steps: +# - name: Checkout code +# uses: actions/checkout@v3 + +# # If action is triggered by a release, push image to +# # Dockerhub using custom image tag extracted from the release +# - name: Get current version tag from release to use as image tag +# if: github.event_name == 'release' +# run: | +# echo "RELEASE=${GITHUB_REF/refs\/tags\/}" >> $GITHUB_ENV + +# # If action is trigged by a push (not release), push a +# # latest/unstable image to Dockerhub using image tag based +# # on the most recent Github tag and commit hash +# - name: Get git commit hash for push to branch to use as image tag +# if: github.event_name != 'release' +# run: | +# git fetch --all --tags +# echo "RELEASE=$(git describe --tags)" >> $GITHUB_ENV + +# - name: Configure AWS credentials +# uses: aws-actions/configure-aws-credentials@v1 +# with: +# role-to-assume: arn:aws:iam::538673716275:role/github-actions-role +# aws-region: ap-southeast-2 + +# - name: Push image to ECR +# uses: whoan/docker-build-with-cache-action@master +# with: +# context: ./ +# registry: 538673716275.dkr.ecr.ap-southeast-2.amazonaws.com +# image_name: ${{ env.IMAGE_NAME }} +# image_tag: latest,${{ env.RELEASE }} diff --git a/.github/workflows/test.yaml b/.github/workflows/test.yaml index b8b85abc..8bfb4560 100644 --- a/.github/workflows/test.yaml +++ b/.github/workflows/test.yaml @@ -1,109 +1,109 @@ ---- -name: Tests - -on: - pull_request: - branches: - - 'develop' - - 'tests_validation' - paths: - - '**' - - '.github/workflows/test.yml' - - '!docs/**' - - '!*.rst' - - '!*.md' - workflow_dispatch: - - push: - branches: - - 'develop' - - 'tests_validation' - paths: - - '**' - - '.github/workflows/test.yml' - - '!docs/**' - - '!*.rst' - - '!*.md' - -permissions: - id-token: write # This is required for requesting the JWT - contents: write # This is required for actions/checkout - -jobs: - integration-tests: - runs-on: ubuntu-latest - - steps: - - uses: actions/checkout@v2 - with: - fetch-depth: 0 - - - name: Configure AWS credentials from Test account - uses: aws-actions/configure-aws-credentials@v1 - with: - role-to-assume: arn:aws:iam::538673716275:role/github-actions-dea-coastlines-s3-role - aws-region: ap-southeast-2 - - - name: Copy files to the test website with the AWS CLI - run: | - aws s3 sync s3://dea-non-public-data/tide_models/tide_models/fes2014 tide_models/fes2014 - aws s3 sync s3://dea-non-public-data/tide_models/tide_models/hamtide tide_models/hamtide - - - name: Run dockerized integration tests and copy outputs - run: | - # Set up artifacts directory to house outputs from integration tests, - # giving all users read and write permissions - mkdir artifacts - chmod a+rw artifacts - - # Run integration tests using Docker - docker-compose up -d - docker-compose exec -T coastline /bin/sh -c "sh ./docker/coastline/run_tests" - docker-compose down - - # Copy out validation outputs produced by the integration tests and place them - # in correct output locations so they can be committed back into the repository - cp ./artifacts/stats_tests.png ./tests/stats_tests.png - cp ./artifacts/stats_tests.csv ./data/validation/processed/stats_tests.csv - cp ./artifacts/README.md ./tests/README.md - -# - name: Setup upterm session -# uses: lhotari/action-upterm@v1 - - # Commit validation results produced by integration tests back into repo - - uses: stefanzweifel/git-auto-commit-action@v4 - with: - commit_message: Automatically update integration test validation results - file_pattern: 'tests/stats_tests.png data/validation/processed/stats_tests.csv tests/README.md' - - # Add output GeoPackage data to Actions artifact so it can be downloaded - - uses: actions/upload-artifact@v3 - with: - name: output_geopackage - path: ./artifacts/coastlines_tests.gpkg - - # Add output ESRI Shapefile data to Actions artifact so it can be downloaded - - uses: actions/upload-artifact@v3 - with: - name: output_shps - path: ./artifacts/coastlines_tests.shp.zip +# --- +# name: Tests + +# on: +# pull_request: +# branches: +# - 'develop' +# - 'tests_validation' +# paths: +# - '**' +# - '.github/workflows/test.yml' +# - '!docs/**' +# - '!*.rst' +# - '!*.md' +# workflow_dispatch: + +# push: +# branches: +# - 'develop' +# - 'tests_validation' +# paths: +# - '**' +# - '.github/workflows/test.yml' +# - '!docs/**' +# - '!*.rst' +# - '!*.md' + +# permissions: +# id-token: write # This is required for requesting the JWT +# contents: write # This is required for actions/checkout + +# jobs: +# integration-tests: +# runs-on: ubuntu-latest + +# steps: +# - uses: actions/checkout@v2 +# with: +# fetch-depth: 0 + +# - name: Configure AWS credentials from Test account +# uses: aws-actions/configure-aws-credentials@v1 +# with: +# role-to-assume: arn:aws:iam::538673716275:role/github-actions-dea-coastlines-s3-role +# aws-region: ap-southeast-2 + +# - name: Copy files to the test website with the AWS CLI +# run: | +# aws s3 sync s3://dea-non-public-data/tide_models/tide_models/fes2014 tide_models/fes2014 +# aws s3 sync s3://dea-non-public-data/tide_models/tide_models/hamtide tide_models/hamtide + +# - name: Run dockerized integration tests and copy outputs +# run: | +# # Set up artifacts directory to house outputs from integration tests, +# # giving all users read and write permissions +# mkdir artifacts +# chmod a+rw artifacts + +# # Run integration tests using Docker +# docker-compose up -d +# docker-compose exec -T coastline /bin/sh -c "sh ./docker/coastline/run_tests" +# docker-compose down + +# # Copy out validation outputs produced by the integration tests and place them +# # in correct output locations so they can be committed back into the repository +# cp ./artifacts/stats_tests.png ./tests/stats_tests.png +# cp ./artifacts/stats_tests.csv ./data/validation/processed/stats_tests.csv +# cp ./artifacts/README.md ./tests/README.md + +# # - name: Setup upterm session +# # uses: lhotari/action-upterm@v1 + +# # Commit validation results produced by integration tests back into repo +# - uses: stefanzweifel/git-auto-commit-action@v4 +# with: +# commit_message: Automatically update integration test validation results +# file_pattern: 'tests/stats_tests.png data/validation/processed/stats_tests.csv tests/README.md' + +# # Add output GeoPackage data to Actions artifact so it can be downloaded +# - uses: actions/upload-artifact@v3 +# with: +# name: output_geopackage +# path: ./artifacts/coastlines_tests.gpkg + +# # Add output ESRI Shapefile data to Actions artifact so it can be downloaded +# - uses: actions/upload-artifact@v3 +# with: +# name: output_shps +# path: ./artifacts/coastlines_tests.shp.zip - # Add output test results 1 - - uses: actions/upload-artifact@v3 - with: - name: test_results - path: ./artifacts/stats_tests.png - - # Add output test results 2 - - uses: actions/upload-artifact@v3 - with: - name: test_results - path: ./artifacts/stats_tests.csv - - # Update code coverage - - name: Upload coverage to Codecov - uses: codecov/codecov-action@v3 - with: - directory: ./artifacts/ - fail_ci_if_error: false +# # Add output test results 1 +# - uses: actions/upload-artifact@v3 +# with: +# name: test_results +# path: ./artifacts/stats_tests.png + +# # Add output test results 2 +# - uses: actions/upload-artifact@v3 +# with: +# name: test_results +# path: ./artifacts/stats_tests.csv + +# # Update code coverage +# - name: Upload coverage to Codecov +# uses: codecov/codecov-action@v3 +# with: +# directory: ./artifacts/ +# fail_ci_if_error: false From bcdc60583ae1077c759d7f9a209357817610e687 Mon Sep 17 00:00:00 2001 From: Robbi Bishop-Taylor Date: Thu, 1 Aug 2024 10:46:57 +1000 Subject: [PATCH 09/45] Update --- .github/workflows/dea-coastlines-image.yaml | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/.github/workflows/dea-coastlines-image.yaml b/.github/workflows/dea-coastlines-image.yaml index 735f8db5..ba855975 100644 --- a/.github/workflows/dea-coastlines-image.yaml +++ b/.github/workflows/dea-coastlines-image.yaml @@ -14,12 +14,13 @@ on: - '.github/workflows/dea-coastlines-image.yml' - 'Dockerfile' - 'requirements.in' + - 'requirements.txt' - 'setup.py' - 'codecov.yaml' pull_request: branches: - - main + - develop paths: - 'coastlines/**' - 'data/**' @@ -27,6 +28,7 @@ on: - '.github/workflows/dea-coastlines-image.yml' - 'Dockerfile' - 'requirements.in' + - 'requirements.txt' - 'setup.py' - 'codecov.yaml' From c0ece89f2da88464831112e8b733cdc98638cc3e Mon Sep 17 00:00:00 2001 From: Robbi Bishop-Taylor Date: Thu, 1 Aug 2024 11:21:52 +1000 Subject: [PATCH 10/45] Update after permissions --- .github/workflows/dea-coastlines-image.yaml | 31 ++++++++++++++++++++- 1 file changed, 30 insertions(+), 1 deletion(-) diff --git a/.github/workflows/dea-coastlines-image.yaml b/.github/workflows/dea-coastlines-image.yaml index ba855975..deb7d123 100644 --- a/.github/workflows/dea-coastlines-image.yaml +++ b/.github/workflows/dea-coastlines-image.yaml @@ -71,4 +71,33 @@ jobs: # Wait until the connection comes up, but, if it doesn't, don't hang forever. npx wait-on --timeout 120000 --interval 1000 tcp:127.0.0.1:5432 echo "PGPORT=5432" >> $GITHUB_ENV - echo "PGHOST=localhost" >> $GITHUB_ENV \ No newline at end of file + echo "PGHOST=localhost" >> $GITHUB_ENV + + # - name: Build DEA Coastlines docker image + # timeout-minutes: 30 + # shell: bash + # run: | + # docker build -t dea_coastlines . + + # - name: Run integration tests + # run: | + # # Download tide modelling files and unzip + # # TODO: Replace with S3 sync from dea-non-public-data + # wget --no-verbose https://www.dropbox.com/s/uemd8ib2vfw5nad/tide_models.zip?dl=1 -O tide_models.zip + # unzip -q tide_models.zip + + # # Run integration tests using Docker, setting up datacube access, AWS configuration and + # # adding volumes that provide access to tide model data and allow us to export artifacts + # # from the run + # docker run \ + # --net=host \ + # --env DATACUBE_DB_URL \ + # --env AWS_SESSION_TOKEN \ + # --env AWS_REGION \ + # --env AWS_ACCESS_KEY_ID \ + # --env AWS_SECRET_ACCESS_KEY \ + # --env AWS_SESSION_TOKEN \ + # --volume ${GITHUB_WORKSPACE}:/code \ + # --volume ${GITHUB_WORKSPACE}/tide_models:/var/share/tide_models \ + # --volume ${GITHUB_WORKSPACE}/artifacts:/mnt/artifacts \ + # dea_coastlines pytest -v --cov=coastlines --cov-report=xml tests \ No newline at end of file From 2b5f60e8e76d26a3c7eb1d2e154777a57f9f6eae Mon Sep 17 00:00:00 2001 From: Robbi Bishop-Taylor Date: Thu, 1 Aug 2024 11:27:05 +1000 Subject: [PATCH 11/45] Update dockerfile and CI --- .github/workflows/dea-coastlines-image.yaml | 52 ++++++------- Dockerfile | 85 +++++++++------------ 2 files changed, 64 insertions(+), 73 deletions(-) diff --git a/.github/workflows/dea-coastlines-image.yaml b/.github/workflows/dea-coastlines-image.yaml index deb7d123..87d02647 100644 --- a/.github/workflows/dea-coastlines-image.yaml +++ b/.github/workflows/dea-coastlines-image.yaml @@ -73,31 +73,31 @@ jobs: echo "PGPORT=5432" >> $GITHUB_ENV echo "PGHOST=localhost" >> $GITHUB_ENV - # - name: Build DEA Coastlines docker image - # timeout-minutes: 30 - # shell: bash - # run: | - # docker build -t dea_coastlines . + - name: Build DEA Coastlines docker image + timeout-minutes: 30 + shell: bash + run: | + docker build -t dea_coastlines . - # - name: Run integration tests - # run: | - # # Download tide modelling files and unzip - # # TODO: Replace with S3 sync from dea-non-public-data - # wget --no-verbose https://www.dropbox.com/s/uemd8ib2vfw5nad/tide_models.zip?dl=1 -O tide_models.zip - # unzip -q tide_models.zip + - name: Run integration tests + run: | + # Download tide modelling files and unzip + # TODO: Replace with S3 sync from dea-non-public-data + wget --no-verbose https://www.dropbox.com/s/uemd8ib2vfw5nad/tide_models.zip?dl=1 -O tide_models.zip + unzip -q tide_models.zip - # # Run integration tests using Docker, setting up datacube access, AWS configuration and - # # adding volumes that provide access to tide model data and allow us to export artifacts - # # from the run - # docker run \ - # --net=host \ - # --env DATACUBE_DB_URL \ - # --env AWS_SESSION_TOKEN \ - # --env AWS_REGION \ - # --env AWS_ACCESS_KEY_ID \ - # --env AWS_SECRET_ACCESS_KEY \ - # --env AWS_SESSION_TOKEN \ - # --volume ${GITHUB_WORKSPACE}:/code \ - # --volume ${GITHUB_WORKSPACE}/tide_models:/var/share/tide_models \ - # --volume ${GITHUB_WORKSPACE}/artifacts:/mnt/artifacts \ - # dea_coastlines pytest -v --cov=coastlines --cov-report=xml tests \ No newline at end of file + # Run integration tests using Docker, setting up datacube access, AWS configuration and + # adding volumes that provide access to tide model data and allow us to export artifacts + # from the run + docker run \ + --net=host \ + --env DATACUBE_DB_URL \ + --env AWS_SESSION_TOKEN \ + --env AWS_REGION \ + --env AWS_ACCESS_KEY_ID \ + --env AWS_SECRET_ACCESS_KEY \ + --env AWS_SESSION_TOKEN \ + --volume ${GITHUB_WORKSPACE}:/code \ + --volume ${GITHUB_WORKSPACE}/tide_models:/var/share/tide_models \ + --volume ${GITHUB_WORKSPACE}/artifacts:/mnt/artifacts \ + dea_coastlines pytest -v --cov=coastlines --cov-report=xml tests \ No newline at end of file diff --git a/Dockerfile b/Dockerfile index eccecec6..ea2c73b8 100644 --- a/Dockerfile +++ b/Dockerfile @@ -1,57 +1,48 @@ -FROM osgeo/gdal:ubuntu-small-3.4.1 as base - -ENV CURL_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt - -RUN apt-get update \ - && apt-get install -y \ - # Build tools - build-essential \ - git \ - python3-pip \ - # For Psycopg2 - libpq-dev python3-dev \ - # For SSL - ca-certificates \ - # for pg_isready - postgresql-client \ - # Try adding libgeos-dev - libgeos-dev \ - # Tidy up +# Base image with: +# - Ubuntu 22.04 +# - Python 3.10.12 +# - GDAL 3.7.3, released 2023/10/30 +FROM ghcr.io/osgeo/gdal:ubuntu-small-3.7.3 + +ENV DEBIAN_FRONTEND=noninteractive \ + LC_ALL=C.UTF-8 \ + LANG=C.UTF-8 + +# Apt installation +RUN apt-get update && \ + apt-get install -y \ + build-essential \ + fish \ + git \ + vim \ + htop \ + wget \ + unzip \ + python3-pip \ + libpq-dev \ && apt-get autoclean && \ apt-get autoremove && \ rm -rf /var/lib/{apt,dpkg,cache,log} +# Install pip-tools +RUN pip install pip-tools -# Environment can be whatever is supported by setup.py -# so, either deployment, test -ARG ENVIRONMENT=deployment -# ARG ENVIRONMENT=test +# Pip installation +RUN mkdir -p /conf +COPY requirements.txt /conf/ +RUN pip install -r /conf/requirements.txt \ + && pip install --no-cache-dir awscli -RUN echo "Environment is: $ENVIRONMENT" +# Copy source code and install it +RUN mkdir -p /code +WORKDIR /code +ADD . /code -COPY requirements.txt /tmp/ -RUN pip install --no-cache-dir --upgrade pip \ - && pip install --no-cache-dir -r /tmp/requirements.txt \ - --no-binary rasterio \ - --no-binary shapely \ - --no-binary fiona \ - # Extras - && pip install --no-cache-dir awscli requests +RUN echo "Installing dea-coastlines through the Dockerfile." +RUN pip install --extra-index-url="https://packages.dea.ga.gov.au" . -# Set up a nice workdir and add the live code -ENV APPDIR=/code -RUN mkdir -p $APPDIR -WORKDIR $APPDIR -ADD . $APPDIR +RUN pip freeze && pip check -RUN if [ "$ENVIRONMENT" = "deployment" ] ; then\ - pip install .[$ENVIRONMENT] ; \ - else \ - pip install --editable .[$ENVIRONMENT] ; \ - fi - - -CMD ["python", "--version"] - -RUN deacoastlines-raster --help \ +# Make sure it's working +RUN deacoastlines-raster --help \ && deacoastlines-vector --help From 0f644a132a8cbd331a275b3153cf4ab66c6e4aad Mon Sep 17 00:00:00 2001 From: Robbi Bishop-Taylor Date: Thu, 1 Aug 2024 11:32:19 +1000 Subject: [PATCH 12/45] Update docker --- Dockerfile | 68 ++++++++++++++++++++++++++++++++++++------------------ 1 file changed, 46 insertions(+), 22 deletions(-) diff --git a/Dockerfile b/Dockerfile index ea2c73b8..825fb260 100644 --- a/Dockerfile +++ b/Dockerfile @@ -1,25 +1,49 @@ -# Base image with: -# - Ubuntu 22.04 -# - Python 3.10.12 -# - GDAL 3.7.3, released 2023/10/30 -FROM ghcr.io/osgeo/gdal:ubuntu-small-3.7.3 - -ENV DEBIAN_FRONTEND=noninteractive \ - LC_ALL=C.UTF-8 \ - LANG=C.UTF-8 - -# Apt installation -RUN apt-get update && \ - apt-get install -y \ - build-essential \ - fish \ - git \ - vim \ - htop \ - wget \ - unzip \ - python3-pip \ - libpq-dev \ +# # Base image with: +# # - Ubuntu 22.04 +# # - Python 3.10.12 +# # - GDAL 3.7.3, released 2023/10/30 +# FROM ghcr.io/osgeo/gdal:ubuntu-small-3.7.3 + +# ENV DEBIAN_FRONTEND=noninteractive \ +# LC_ALL=C.UTF-8 \ +# LANG=C.UTF-8 + +# # Apt installation +# RUN apt-get update && \ +# apt-get install -y \ +# build-essential \ +# fish \ +# git \ +# vim \ +# htop \ +# wget \ +# unzip \ +# python3-pip \ +# libpq-dev \ +# && apt-get autoclean && \ +# apt-get autoremove && \ +# rm -rf /var/lib/{apt,dpkg,cache,log} + + +FROM osgeo/gdal:ubuntu-small-3.4.1 as base + +ENV CURL_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt + +RUN apt-get update \ + && apt-get install -y \ + # Build tools + build-essential \ + git \ + python3-pip \ + # For Psycopg2 + libpq-dev python3-dev \ + # For SSL + ca-certificates \ + # for pg_isready + postgresql-client \ + # Try adding libgeos-dev + libgeos-dev \ + # Tidy up && apt-get autoclean && \ apt-get autoremove && \ rm -rf /var/lib/{apt,dpkg,cache,log} From 6165e67b8c667e448e810be6fc3c51f9081cc385 Mon Sep 17 00:00:00 2001 From: Robbi Bishop-Taylor Date: Thu, 1 Aug 2024 11:39:04 +1000 Subject: [PATCH 13/45] Remove AWS CLI --- Dockerfile | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/Dockerfile b/Dockerfile index 825fb260..e8e653a5 100644 --- a/Dockerfile +++ b/Dockerfile @@ -54,8 +54,7 @@ RUN pip install pip-tools # Pip installation RUN mkdir -p /conf COPY requirements.txt /conf/ -RUN pip install -r /conf/requirements.txt \ - && pip install --no-cache-dir awscli +RUN pip install -r /conf/requirements.txt # Copy source code and install it RUN mkdir -p /code From d1aea5d8bf74d5af350d86adac670042dd463993 Mon Sep 17 00:00:00 2001 From: Robbi Bishop-Taylor Date: Thu, 1 Aug 2024 11:48:17 +1000 Subject: [PATCH 14/45] Add test env --- Dockerfile | 2 ++ 1 file changed, 2 insertions(+) diff --git a/Dockerfile b/Dockerfile index e8e653a5..d3a88cfc 100644 --- a/Dockerfile +++ b/Dockerfile @@ -61,6 +61,8 @@ RUN mkdir -p /code WORKDIR /code ADD . /code +ARG ENVIRONMENT=test + RUN echo "Installing dea-coastlines through the Dockerfile." RUN pip install --extra-index-url="https://packages.dea.ga.gov.au" . From 309e8ebee3b5fd305acaac62617427330e3748d3 Mon Sep 17 00:00:00 2001 From: Robbi Bishop-Taylor Date: Thu, 1 Aug 2024 11:53:15 +1000 Subject: [PATCH 15/45] Simplify by installing pytest in setup.py --- Dockerfile | 2 -- setup.py | 15 +++------------ 2 files changed, 3 insertions(+), 14 deletions(-) diff --git a/Dockerfile b/Dockerfile index d3a88cfc..e8e653a5 100644 --- a/Dockerfile +++ b/Dockerfile @@ -61,8 +61,6 @@ RUN mkdir -p /code WORKDIR /code ADD . /code -ARG ENVIRONMENT=test - RUN echo "Installing dea-coastlines through the Dockerfile." RUN pip install --extra-index-url="https://packages.dea.ga.gov.au" . diff --git a/setup.py b/setup.py index f0697cae..b6987e85 100644 --- a/setup.py +++ b/setup.py @@ -6,16 +6,6 @@ # Where are we? IS_SANDBOX = "sandbox" in os.getenv("JUPYTER_IMAGE", default="") -tests_require = [ - "pytest", - "pytest-dependency", - "pytest-cov", -] - -extras = { - 'test': tests_require, -} - # What packages are required for this module to be executed? REQUIRED = [ "aiohttp", @@ -35,6 +25,9 @@ "pandas", "pygeos", "pyproj", + "pytest", + "pytest-dependency", + "pytest-cov", "pyTMD", "python_geohash", "pytz", @@ -68,8 +61,6 @@ "python_requires": REQUIRES_PYTHON, "url": URL, "install_requires": REQUIRED if not IS_SANDBOX else [], - "tests_require": tests_require, - "extras_require": extras, "packages": find_packages(), "include_package_data": True, "license": "Apache License 2.0", From 38c4e3146a7b4decfce3944c009309270755d00a Mon Sep 17 00:00:00 2001 From: Robbi Bishop-Taylor Date: Thu, 1 Aug 2024 13:10:25 +1000 Subject: [PATCH 16/45] Add file copying to workflow --- .github/workflows/dea-coastlines-image.yaml | 16 +++++++++++++++- 1 file changed, 15 insertions(+), 1 deletion(-) diff --git a/.github/workflows/dea-coastlines-image.yaml b/.github/workflows/dea-coastlines-image.yaml index 87d02647..814c09bf 100644 --- a/.github/workflows/dea-coastlines-image.yaml +++ b/.github/workflows/dea-coastlines-image.yaml @@ -100,4 +100,18 @@ jobs: --volume ${GITHUB_WORKSPACE}:/code \ --volume ${GITHUB_WORKSPACE}/tide_models:/var/share/tide_models \ --volume ${GITHUB_WORKSPACE}/artifacts:/mnt/artifacts \ - dea_coastlines pytest -v --cov=coastlines --cov-report=xml tests \ No newline at end of file + dea_coastlines sh -c " + pytest -v --cov=coastlines --cov-report=xml tests && + cp coverage.xml /mnt/artifacts/ && + cp data/processed/tests/coastlines_tests.gpkg /mnt/artifacts/coastlines_tests.gpkg && + cp data/processed/tests/coastlines_tests.shp.zip /mnt/artifacts/coastlines_tests.shp.zip && + cp data/validation/processed/stats_tests.png /mnt/artifacts/stats_tests.png && + cp data/validation/processed/stats_tests.csv /mnt/artifacts/stats_tests.csv && + cp tests/README.md /mnt/artifacts/README.md + " + + # Copy out validation outputs produced by the integration tests and place them + # in correct output locations so they can be committed back into the repository + cp ./artifacts/validation.jpg ./tests/validation.jpg + cp ./artifacts/validation.csv ./tests/validation.csv + cp ./artifacts/README.md ./tests/README.md \ No newline at end of file From 2dca8e7b956e6aa18afb8f4f19db77b3ec33462d Mon Sep 17 00:00:00 2001 From: Robbi Bishop-Taylor Date: Thu, 1 Aug 2024 13:35:19 +1000 Subject: [PATCH 17/45] Try new paths --- .github/workflows/dea-coastlines-image.yaml | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/.github/workflows/dea-coastlines-image.yaml b/.github/workflows/dea-coastlines-image.yaml index 814c09bf..92f5e7ae 100644 --- a/.github/workflows/dea-coastlines-image.yaml +++ b/.github/workflows/dea-coastlines-image.yaml @@ -110,8 +110,8 @@ jobs: cp tests/README.md /mnt/artifacts/README.md " - # Copy out validation outputs produced by the integration tests and place them - # in correct output locations so they can be committed back into the repository - cp ./artifacts/validation.jpg ./tests/validation.jpg - cp ./artifacts/validation.csv ./tests/validation.csv + # Copy out validation outputs produced by integration tests and place them in + # correct locations on the Github runner so they can be committed back into repo + cp ./artifacts/stats_tests.png ./data/validation/processed/stats_tests.png + cp ./artifacts/stats_tests.csv ./data/validation/processed/stats_tests.csv cp ./artifacts/README.md ./tests/README.md \ No newline at end of file From 08e4f6d5ab9182522589d3ecf9159aa09cbcaad6 Mon Sep 17 00:00:00 2001 From: Robbi Bishop-Taylor Date: Thu, 1 Aug 2024 15:48:49 +1000 Subject: [PATCH 18/45] Check everything works up to copy step --- .github/workflows/dea-coastlines-image.yaml | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/.github/workflows/dea-coastlines-image.yaml b/.github/workflows/dea-coastlines-image.yaml index 92f5e7ae..1c4ab3b4 100644 --- a/.github/workflows/dea-coastlines-image.yaml +++ b/.github/workflows/dea-coastlines-image.yaml @@ -110,8 +110,8 @@ jobs: cp tests/README.md /mnt/artifacts/README.md " - # Copy out validation outputs produced by integration tests and place them in - # correct locations on the Github runner so they can be committed back into repo - cp ./artifacts/stats_tests.png ./data/validation/processed/stats_tests.png - cp ./artifacts/stats_tests.csv ./data/validation/processed/stats_tests.csv - cp ./artifacts/README.md ./tests/README.md \ No newline at end of file + # # Copy out validation outputs produced by integration tests and place them in + # # correct locations on the Github runner so they can be committed back into repo + # cp ./artifacts/stats_tests.png ./data/validation/processed/stats_tests.png + # cp ./artifacts/stats_tests.csv ./data/validation/processed/stats_tests.csv + # cp ./artifacts/README.md ./tests/README.md \ No newline at end of file From ef10e19ff686e0c05c6e25928248f463d01ba98c Mon Sep 17 00:00:00 2001 From: Robbi Bishop-Taylor Date: Thu, 1 Aug 2024 16:07:19 +1000 Subject: [PATCH 19/45] Try ls --- .github/workflows/dea-coastlines-image.yaml | 67 +++++++++++++++------ 1 file changed, 47 insertions(+), 20 deletions(-) diff --git a/.github/workflows/dea-coastlines-image.yaml b/.github/workflows/dea-coastlines-image.yaml index 1c4ab3b4..8d79d4de 100644 --- a/.github/workflows/dea-coastlines-image.yaml +++ b/.github/workflows/dea-coastlines-image.yaml @@ -82,13 +82,10 @@ jobs: - name: Run integration tests run: | # Download tide modelling files and unzip - # TODO: Replace with S3 sync from dea-non-public-data wget --no-verbose https://www.dropbox.com/s/uemd8ib2vfw5nad/tide_models.zip?dl=1 -O tide_models.zip unzip -q tide_models.zip - # Run integration tests using Docker, setting up datacube access, AWS configuration and - # adding volumes that provide access to tide model data and allow us to export artifacts - # from the run + # Run integration tests using Docker docker run \ --net=host \ --env DATACUBE_DB_URL \ @@ -99,19 +96,49 @@ jobs: --env AWS_SESSION_TOKEN \ --volume ${GITHUB_WORKSPACE}:/code \ --volume ${GITHUB_WORKSPACE}/tide_models:/var/share/tide_models \ - --volume ${GITHUB_WORKSPACE}/artifacts:/mnt/artifacts \ - dea_coastlines sh -c " - pytest -v --cov=coastlines --cov-report=xml tests && - cp coverage.xml /mnt/artifacts/ && - cp data/processed/tests/coastlines_tests.gpkg /mnt/artifacts/coastlines_tests.gpkg && - cp data/processed/tests/coastlines_tests.shp.zip /mnt/artifacts/coastlines_tests.shp.zip && - cp data/validation/processed/stats_tests.png /mnt/artifacts/stats_tests.png && - cp data/validation/processed/stats_tests.csv /mnt/artifacts/stats_tests.csv && - cp tests/README.md /mnt/artifacts/README.md - " - - # # Copy out validation outputs produced by integration tests and place them in - # # correct locations on the Github runner so they can be committed back into repo - # cp ./artifacts/stats_tests.png ./data/validation/processed/stats_tests.png - # cp ./artifacts/stats_tests.csv ./data/validation/processed/stats_tests.csv - # cp ./artifacts/README.md ./tests/README.md \ No newline at end of file + dea_coastlines pytest -v --cov=coastlines --cov-report=xml tests + + ls -l ./data/validation/processed/ + + # # Copy files directly from the container to the correct locations + # docker cp $(docker ps -lq):/code/data/validation/processed/stats_tests.png ./data/validation/processed/stats_tests.png + # docker cp $(docker ps -lq):/code/data/validation/processed/stats_tests.csv ./data/validation/processed/stats_tests.csv + # docker cp $(docker ps -lq):/code/tests/README.md ./tests/README.md + + + # - name: Run integration tests + # run: | + # # Download tide modelling files and unzip + # # TODO: Replace with S3 sync from dea-non-public-data + # wget --no-verbose https://www.dropbox.com/s/uemd8ib2vfw5nad/tide_models.zip?dl=1 -O tide_models.zip + # unzip -q tide_models.zip + + # # Run integration tests using Docker, setting up datacube access, AWS configuration and + # # adding volumes that provide access to tide model data and allow us to export artifacts + # # from the run + # docker run \ + # --net=host \ + # --env DATACUBE_DB_URL \ + # --env AWS_SESSION_TOKEN \ + # --env AWS_REGION \ + # --env AWS_ACCESS_KEY_ID \ + # --env AWS_SECRET_ACCESS_KEY \ + # --env AWS_SESSION_TOKEN \ + # --volume ${GITHUB_WORKSPACE}:/code \ + # --volume ${GITHUB_WORKSPACE}/tide_models:/var/share/tide_models \ + # --volume ${GITHUB_WORKSPACE}/artifacts:/mnt/artifacts \ + # dea_coastlines sh -c " + # pytest -v --cov=coastlines --cov-report=xml tests && + # cp coverage.xml /mnt/artifacts/ && + # cp data/processed/tests/coastlines_tests.gpkg /mnt/artifacts/coastlines_tests.gpkg && + # cp data/processed/tests/coastlines_tests.shp.zip /mnt/artifacts/coastlines_tests.shp.zip && + # cp data/validation/processed/stats_tests.png /mnt/artifacts/stats_tests.png && + # cp data/validation/processed/stats_tests.csv /mnt/artifacts/stats_tests.csv && + # cp tests/README.md /mnt/artifacts/README.md + # " + + # # # Copy out validation outputs produced by integration tests and place them in + # # # correct locations on the Github runner so they can be committed back into repo + # # cp ./artifacts/stats_tests.png ./data/validation/processed/stats_tests.png + # # cp ./artifacts/stats_tests.csv ./data/validation/processed/stats_tests.csv + # # cp ./artifacts/README.md ./tests/README.md \ No newline at end of file From 8fc513e6ab88ec86d2dc6ebd4602e2bdf0c50e02 Mon Sep 17 00:00:00 2001 From: Robbi Bishop-Taylor Date: Thu, 1 Aug 2024 16:08:44 +1000 Subject: [PATCH 20/45] Fix --- .github/workflows/dea-coastlines-image.yaml | 6 ------ 1 file changed, 6 deletions(-) diff --git a/.github/workflows/dea-coastlines-image.yaml b/.github/workflows/dea-coastlines-image.yaml index 8d79d4de..9050b733 100644 --- a/.github/workflows/dea-coastlines-image.yaml +++ b/.github/workflows/dea-coastlines-image.yaml @@ -100,12 +100,6 @@ jobs: ls -l ./data/validation/processed/ - # # Copy files directly from the container to the correct locations - # docker cp $(docker ps -lq):/code/data/validation/processed/stats_tests.png ./data/validation/processed/stats_tests.png - # docker cp $(docker ps -lq):/code/data/validation/processed/stats_tests.csv ./data/validation/processed/stats_tests.csv - # docker cp $(docker ps -lq):/code/tests/README.md ./tests/README.md - - # - name: Run integration tests # run: | # # Download tide modelling files and unzip From f057520981df99922929bc31b87f480e3684479d Mon Sep 17 00:00:00 2001 From: Robbi Bishop-Taylor Date: Thu, 1 Aug 2024 16:25:59 +1000 Subject: [PATCH 21/45] Try combined approach --- .github/workflows/dea-coastlines-image.yaml | 61 +++++++++------------ 1 file changed, 25 insertions(+), 36 deletions(-) diff --git a/.github/workflows/dea-coastlines-image.yaml b/.github/workflows/dea-coastlines-image.yaml index 9050b733..341c1c40 100644 --- a/.github/workflows/dea-coastlines-image.yaml +++ b/.github/workflows/dea-coastlines-image.yaml @@ -98,41 +98,30 @@ jobs: --volume ${GITHUB_WORKSPACE}/tide_models:/var/share/tide_models \ dea_coastlines pytest -v --cov=coastlines --cov-report=xml tests + ls -l . ls -l ./data/validation/processed/ + git status - # - name: Run integration tests - # run: | - # # Download tide modelling files and unzip - # # TODO: Replace with S3 sync from dea-non-public-data - # wget --no-verbose https://www.dropbox.com/s/uemd8ib2vfw5nad/tide_models.zip?dl=1 -O tide_models.zip - # unzip -q tide_models.zip - - # # Run integration tests using Docker, setting up datacube access, AWS configuration and - # # adding volumes that provide access to tide model data and allow us to export artifacts - # # from the run - # docker run \ - # --net=host \ - # --env DATACUBE_DB_URL \ - # --env AWS_SESSION_TOKEN \ - # --env AWS_REGION \ - # --env AWS_ACCESS_KEY_ID \ - # --env AWS_SECRET_ACCESS_KEY \ - # --env AWS_SESSION_TOKEN \ - # --volume ${GITHUB_WORKSPACE}:/code \ - # --volume ${GITHUB_WORKSPACE}/tide_models:/var/share/tide_models \ - # --volume ${GITHUB_WORKSPACE}/artifacts:/mnt/artifacts \ - # dea_coastlines sh -c " - # pytest -v --cov=coastlines --cov-report=xml tests && - # cp coverage.xml /mnt/artifacts/ && - # cp data/processed/tests/coastlines_tests.gpkg /mnt/artifacts/coastlines_tests.gpkg && - # cp data/processed/tests/coastlines_tests.shp.zip /mnt/artifacts/coastlines_tests.shp.zip && - # cp data/validation/processed/stats_tests.png /mnt/artifacts/stats_tests.png && - # cp data/validation/processed/stats_tests.csv /mnt/artifacts/stats_tests.csv && - # cp tests/README.md /mnt/artifacts/README.md - # " - - # # # Copy out validation outputs produced by integration tests and place them in - # # # correct locations on the Github runner so they can be committed back into repo - # # cp ./artifacts/stats_tests.png ./data/validation/processed/stats_tests.png - # # cp ./artifacts/stats_tests.csv ./data/validation/processed/stats_tests.csv - # # cp ./artifacts/README.md ./tests/README.md \ No newline at end of file + # Commit validation results produced by integration tests back into repo + - name: Commit validation results into repository + uses: stefanzweifel/git-auto-commit-action@v4 + if: github.event_name == 'pull_request' + continue-on-error: true + with: + commit_message: Automatically update integration test validation results + file_pattern: 'tests/validation.jpg tests/validation.csv tests/README.md' + + # Post validation tesults as comment on PR + - name: Post validation results as comment + uses: mshick/add-pr-comment@v2 + if: github.event_name == 'pull_request' + with: + message: | + ![](https://github.com/GeoscienceAustralia/dea-intertidal/blob/${{ github.head_ref }}/tests/validation.jpg?raw=true") + + For full integration test results, refer to the [Tests directory README](https://github.com/GeoscienceAustralia/dea-intertidal/tree/${{ github.head_ref }}/tests). + + - name: Upload coverage reports to Codecov + uses: codecov/codecov-action@v3 + env: + CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }} \ No newline at end of file From 95d11fab0b33aa2d3f4356d9b3e423bd9121cec9 Mon Sep 17 00:00:00 2001 From: Robbi Bishop-Taylor Date: Thu, 1 Aug 2024 16:33:22 +1000 Subject: [PATCH 22/45] Try smaller tests --- tests/test_coastline.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/tests/test_coastline.py b/tests/test_coastline.py index 7ed3ba66..75569c79 100644 --- a/tests/test_coastline.py +++ b/tests/test_coastline.py @@ -18,7 +18,7 @@ def test_generate_rasters_cli(): "--raster_version", "tests", "--start_year", - "1988", + "2015", "--end_year", "2021", "--buffer", @@ -41,7 +41,7 @@ def test_generate_vector_cli(): "--raster_version", "tests", "--start_year", - "1988", + "2015", "--end_year", "2021", "--baseline_year", From e2511782c88e653ce6b24c8f3880f48d8f60d359 Mon Sep 17 00:00:00 2001 From: Robbi Bishop-Taylor Date: Thu, 1 Aug 2024 16:45:30 +1000 Subject: [PATCH 23/45] Fix paths --- .github/workflows/dea-coastlines-image.yaml | 6 +++--- tests/test_coastline.py | 4 ++-- 2 files changed, 5 insertions(+), 5 deletions(-) diff --git a/.github/workflows/dea-coastlines-image.yaml b/.github/workflows/dea-coastlines-image.yaml index 341c1c40..8e1dd1e9 100644 --- a/.github/workflows/dea-coastlines-image.yaml +++ b/.github/workflows/dea-coastlines-image.yaml @@ -109,7 +109,7 @@ jobs: continue-on-error: true with: commit_message: Automatically update integration test validation results - file_pattern: 'tests/validation.jpg tests/validation.csv tests/README.md' + file_pattern: 'tests/stats_tests.png data/validation/processed/stats_tests.csv tests/README.md' # Post validation tesults as comment on PR - name: Post validation results as comment @@ -117,9 +117,9 @@ jobs: if: github.event_name == 'pull_request' with: message: | - ![](https://github.com/GeoscienceAustralia/dea-intertidal/blob/${{ github.head_ref }}/tests/validation.jpg?raw=true") + ![](https://github.com/GeoscienceAustralia/dea-coastlines/blob/${{ github.head_ref }}/tests/stats_tests.png?raw=true") - For full integration test results, refer to the [Tests directory README](https://github.com/GeoscienceAustralia/dea-intertidal/tree/${{ github.head_ref }}/tests). + For full integration test results, refer to the [Tests directory README](https://github.com/GeoscienceAustralia/dea-coastlines/tree/${{ github.head_ref }}/tests). - name: Upload coverage reports to Codecov uses: codecov/codecov-action@v3 diff --git a/tests/test_coastline.py b/tests/test_coastline.py index 75569c79..7ed3ba66 100644 --- a/tests/test_coastline.py +++ b/tests/test_coastline.py @@ -18,7 +18,7 @@ def test_generate_rasters_cli(): "--raster_version", "tests", "--start_year", - "2015", + "1988", "--end_year", "2021", "--buffer", @@ -41,7 +41,7 @@ def test_generate_vector_cli(): "--raster_version", "tests", "--start_year", - "2015", + "1988", "--end_year", "2021", "--baseline_year", From dc7ed7d5869a7e7e6f958e6e644efd5d1f0bbf22 Mon Sep 17 00:00:00 2001 From: robbibt Date: Thu, 1 Aug 2024 06:58:42 +0000 Subject: [PATCH 24/45] Automatically update integration test validation results --- data/validation/processed/stats_tests.csv | 1 + tests/README.md | 8 ++++---- 2 files changed, 5 insertions(+), 4 deletions(-) diff --git a/data/validation/processed/stats_tests.csv b/data/validation/processed/stats_tests.csv index 29c6058e..22ebecda 100644 --- a/data/validation/processed/stats_tests.csv +++ b/data/validation/processed/stats_tests.csv @@ -34,3 +34,4 @@ time,n,mae,rmse,stdev,corr,bias,name 2023-12-13 02:41:20.170714,2669.0,4.84,6.16,5.56,0.975,-2.67,tests 2023-12-19 05:51:54.070412,2669.0,4.84,6.16,5.56,0.975,-2.67,tests 2024-08-01 00:27:59.036809,2669.0,4.84,6.16,5.56,0.975,-2.67,tests +2024-08-01 06:58:39.701964,2669.0,4.85,6.15,5.57,0.975,-2.65,tests diff --git a/tests/README.md b/tests/README.md index a492a989..bbc2b0cb 100644 --- a/tests/README.md +++ b/tests/README.md @@ -15,10 +15,10 @@ In addition to testing whether the code runs without errors, we also run a small ## Latest integration test validation results -The latest integration test completed at **2024-08-01 10:27**. Compared to the previous run, it had an: -- RMSE accuracy of **6.16 m (:heavy_minus_sign: no change)** -- MAE accuracy of **4.84 m (:heavy_minus_sign: no change)** -- Bias of **-2.67 m (:heavy_minus_sign: no change)** +The latest integration test completed at **2024-08-01 16:58**. Compared to the previous run, it had an: +- RMSE accuracy of **6.15 m (:heavy_check_mark: improved by 0.01)** +- MAE accuracy of **4.85 m (:heavy_exclamation_mark: worsened by 0.01)** +- Bias of **-2.65 m (:heavy_check_mark: improved by 0.02)** - Pearson correlation of **0.975 (:heavy_minus_sign: no change)** From 8991aff78098dccd91b9bbc753faffdc00053cd4 Mon Sep 17 00:00:00 2001 From: Robbi Bishop-Taylor Date: Thu, 1 Aug 2024 17:31:52 +1000 Subject: [PATCH 25/45] Try changing locations files are written to --- .github/workflows/dea-coastlines-image.yaml | 3 ++- coastlines/validation.py | 5 +++-- 2 files changed, 5 insertions(+), 3 deletions(-) diff --git a/.github/workflows/dea-coastlines-image.yaml b/.github/workflows/dea-coastlines-image.yaml index 8e1dd1e9..99660bd8 100644 --- a/.github/workflows/dea-coastlines-image.yaml +++ b/.github/workflows/dea-coastlines-image.yaml @@ -100,6 +100,7 @@ jobs: ls -l . ls -l ./data/validation/processed/ + ls -l .tests/ git status # Commit validation results produced by integration tests back into repo @@ -109,7 +110,7 @@ jobs: continue-on-error: true with: commit_message: Automatically update integration test validation results - file_pattern: 'tests/stats_tests.png data/validation/processed/stats_tests.csv tests/README.md' + file_pattern: 'tests/stats_tests.png tests/stats_tests.csv tests/README.md' # Post validation tesults as comment on PR - name: Post validation results as comment diff --git a/coastlines/validation.py b/coastlines/validation.py index 19b9e082..1c0a6ffa 100644 --- a/coastlines/validation.py +++ b/coastlines/validation.py @@ -2565,7 +2565,7 @@ def validation_cli( # Transpose and add index time and prefix name stats_df = pd.DataFrame({pd.to_datetime("now"): stats_df}).T.assign(name=prefix) stats_df.index.name = "time" - filename = f"data/validation/processed/stats_{prefix}.csv" + filename = f"tests/stats_{prefix}.csv" if append_stats: stats_df.to_csv( @@ -2647,7 +2647,8 @@ def validation_cli( ) # Export plot to file - plt.savefig(f"data/validation/processed/stats_{prefix}.png", bbox_inches="tight") + # plt.savefig(f"data/validation/processed/stats_{prefix}.png", bbox_inches="tight") + plt.savefig(f"tests/stats_{prefix}.png", bbox_inches="tight") # Create markdown file containing report on latest integration test run if markdown_report: From ad58f7edd141984e41e869155cdec67eed828721 Mon Sep 17 00:00:00 2001 From: Robbi Bishop-Taylor Date: Thu, 1 Aug 2024 17:57:52 +1000 Subject: [PATCH 26/45] Fix --- .github/workflows/dea-coastlines-image.yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/dea-coastlines-image.yaml b/.github/workflows/dea-coastlines-image.yaml index 99660bd8..5a6148be 100644 --- a/.github/workflows/dea-coastlines-image.yaml +++ b/.github/workflows/dea-coastlines-image.yaml @@ -100,7 +100,7 @@ jobs: ls -l . ls -l ./data/validation/processed/ - ls -l .tests/ + ls -l ./tests/ git status # Commit validation results produced by integration tests back into repo From 22ec4919b1b2dc4c470cae90d9ba141ddf6dd203 Mon Sep 17 00:00:00 2001 From: Robbi Bishop-Taylor Date: Thu, 1 Aug 2024 20:04:18 +1000 Subject: [PATCH 27/45] Update .gitignore --- .gitignore | 1 + 1 file changed, 1 insertion(+) diff --git a/.gitignore b/.gitignore index e6d20aa9..5f6dae27 100644 --- a/.gitignore +++ b/.gitignore @@ -12,3 +12,4 @@ !**.github !*.md !tests/*.png +!tests/*.csv From 2b5ed8ab695c5da5ba86b72a174de63a721e94e4 Mon Sep 17 00:00:00 2001 From: robbibt Date: Thu, 1 Aug 2024 10:19:51 +0000 Subject: [PATCH 28/45] Automatically update integration test validation results --- tests/README.md | 10 +++++----- tests/stats_tests.csv | 2 ++ tests/stats_tests.png | Bin 95524 -> 92077 bytes 3 files changed, 7 insertions(+), 5 deletions(-) create mode 100644 tests/stats_tests.csv diff --git a/tests/README.md b/tests/README.md index bbc2b0cb..02985f60 100644 --- a/tests/README.md +++ b/tests/README.md @@ -15,11 +15,11 @@ In addition to testing whether the code runs without errors, we also run a small ## Latest integration test validation results -The latest integration test completed at **2024-08-01 16:58**. Compared to the previous run, it had an: -- RMSE accuracy of **6.15 m (:heavy_check_mark: improved by 0.01)** -- MAE accuracy of **4.85 m (:heavy_exclamation_mark: worsened by 0.01)** -- Bias of **-2.65 m (:heavy_check_mark: improved by 0.02)** -- Pearson correlation of **0.975 (:heavy_minus_sign: no change)** +The latest integration test completed at **2024-08-01 20:19**. 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219c1c91..22ebecda 100644 --- a/tests/stats_tests.csv +++ b/tests/stats_tests.csv @@ -1,2 +1,37 @@ time,n,mae,rmse,stdev,corr,bias,name -2024-08-01 10:19:48.296125,2669.0,4.85,6.15,5.57,0.975,-2.65,tests +2023-02-03 12:17:37.156077,555.0,3.59,4.63,3.19,0.997,-3.43,tests +2023-02-04 03:37:32.808973,555.0,3.59,4.63,3.19,0.997,-3.43,tests +2023-02-04 03:55:59.838626,714.0,3.68,4.57,3.57,0.996,-2.95,tests +2023-02-04 04:15:26.032019,714.0,3.68,4.57,3.57,0.996,-2.95,tests +2023-02-04 07:17:59.017632,714.0,3.68,4.57,3.57,0.996,-2.95,tests +2023-02-04 08:01:48.131535,714.0,3.68,4.57,3.57,0.996,-2.95,tests +2023-02-04 08:23:53.380354,946.0,4.55,6.52,5.3,0.99,-3.92,tests +2023-02-04 10:28:16.613761,1274.0,4.38,6.19,4.99,0.99,-3.75,tests +2023-02-04 10:51:15.311142,1274.0,4.38,6.19,4.99,0.99,-3.75,tests +2023-02-04 11:14:33.645115,1344.0,4.87,6.52,4.94,0.988,-4.32,tests +2023-02-05 02:14:42.372693,1404.0,4.56,6.22,4.78,0.987,-4.05,tests +2023-02-05 02:51:09.680222,1404.0,4.56,6.22,4.78,0.987,-4.05,tests +2023-02-05 03:09:03.194812,1474.0,4.32,5.97,4.6,0.987,-3.86,tests +2023-02-05 03:40:17.021839,1538.0,4.86,6.52,4.8,0.985,-4.46,tests +2023-02-06 08:30:33.586563,1538.0,4.86,6.52,4.8,0.985,-4.46,tests +2023-02-07 01:09:43.241923,1538.0,4.86,6.52,4.8,0.985,-4.46,tests +2023-02-07 01:37:16.408622,2669.0,4.84,6.16,5.56,0.975,-2.67,tests +2023-02-07 02:09:51.266953,2669.0,4.84,6.16,5.56,0.975,-2.67,tests +2023-02-07 07:03:44.449612,2669.0,4.84,6.16,5.56,0.975,-2.67,tests +2023-02-08 01:40:52.534940,2669.0,4.84,6.16,5.56,0.975,-2.67,tests +2023-02-09 00:13:48.554877,2669.0,4.84,6.16,5.56,0.975,-2.67,tests +2023-02-09 01:29:44.258038,2669.0,4.84,6.16,5.56,0.975,-2.67,tests +2023-02-09 05:50:31.109630,2669.0,4.84,6.16,5.56,0.975,-2.67,tests +2023-02-10 03:44:43.562169,2669.0,4.84,6.16,5.56,0.975,-2.67,tests +2023-02-17 03:17:33.847153,2669.0,4.84,6.16,5.56,0.975,-2.67,tests +2023-02-22 03:25:38.671154,2669.0,4.84,6.16,5.56,0.975,-2.67,tests +2023-02-24 03:17:56.295549,2669.0,4.84,6.16,5.56,0.975,-2.67,tests +2023-02-27 00:08:14.931969,2669.0,4.84,6.16,5.56,0.975,-2.67,tests +2023-02-27 04:30:37.640963,2669.0,4.84,6.16,5.56,0.975,-2.67,tests +2023-08-01 04:31:52.289422,2669.0,4.84,6.16,5.56,0.975,-2.67,tests +2023-08-02 01:40:33.629540,2669.0,4.84,6.16,5.56,0.975,-2.67,tests +2023-08-07 01:35:06.989065,2669.0,4.84,6.16,5.56,0.975,-2.67,tests +2023-12-13 02:41:20.170714,2669.0,4.84,6.16,5.56,0.975,-2.67,tests +2023-12-19 05:51:54.070412,2669.0,4.84,6.16,5.56,0.975,-2.67,tests +2024-08-01 00:27:59.036809,2669.0,4.84,6.16,5.56,0.975,-2.67,tests +2024-08-01 06:58:39.701964,2669.0,4.85,6.15,5.57,0.975,-2.65,tests From 8bca469458dc47f814317b62d646794eaf018d10 Mon Sep 17 00:00:00 2001 From: robbibt Date: Thu, 1 Aug 2024 10:41:32 +0000 Subject: [PATCH 30/45] Automatically update integration test validation results --- tests/README.md | 10 +++++----- tests/stats_tests.csv | 1 + tests/stats_tests.png | Bin 92077 -> 95448 bytes 3 files changed, 6 insertions(+), 5 deletions(-) diff --git a/tests/README.md b/tests/README.md index 02985f60..77ff598f 100644 --- a/tests/README.md +++ b/tests/README.md @@ -15,11 +15,11 @@ In addition to testing whether the code runs without errors, we also run a small ## Latest integration test validation results -The latest integration test completed at **2024-08-01 20:19**. Compared to the previous run, it had an: -- RMSE accuracy of **6.15 m (nannan)** -- MAE accuracy of **4.85 m (nannan)** -- Bias of **-2.65 m (nannan)** -- Pearson correlation of **0.975 (nannan)** +The latest integration test completed at **2024-08-01 20:41**. Compared to the previous run, it had an: +- RMSE accuracy of **6.15 m (:heavy_minus_sign: no change)** +- MAE accuracy of **4.85 m (:heavy_minus_sign: no change)** +- Bias of **-2.65 m (:heavy_minus_sign: no change)** +- Pearson correlation of **0.975 (:heavy_minus_sign: no change)** \ No newline at end of file diff --git a/tests/stats_tests.csv b/tests/stats_tests.csv index 22ebecda..d47fdc4c 100644 --- a/tests/stats_tests.csv +++ b/tests/stats_tests.csv @@ -35,3 +35,4 @@ time,n,mae,rmse,stdev,corr,bias,name 2023-12-19 05:51:54.070412,2669.0,4.84,6.16,5.56,0.975,-2.67,tests 2024-08-01 00:27:59.036809,2669.0,4.84,6.16,5.56,0.975,-2.67,tests 2024-08-01 06:58:39.701964,2669.0,4.85,6.15,5.57,0.975,-2.65,tests +2024-08-01 10:41:29.546023,2669.0,4.85,6.15,5.57,0.975,-2.65,tests diff --git a/tests/stats_tests.png b/tests/stats_tests.png index a1e4fe105eb9153c21d3991a0db9411ce702dcdf..1f75f99898785c8deb8efa714e0f7169f70ccd94 100644 GIT binary patch literal 95448 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zT!-UPu!4x@Vm42xqY$Jj$ohtr1&3}C+~4x7?O@dv;Y$x*;uV3+=*SW^V)U5G6WAoQ zyMQxiMv)r^lh0qief!kC+9})nhfpFd0%xEBF@-!ii8gG9SIPCm8+w6R-8#y83=r5vlGofxsT5`3!`gx*yDhD7X&Uf`Iyt9ttqmVBVWDldye+w#BF3pbJCR5{Db3bxb3v6rUJ825S zY^mt>l-jND%queHSLj*lqB93Qza2#>eBjH(CtY|PmDo5FS)7Xx$%!O{YE_ImO(g`R z9hed;?nIw?E5^JIo5d!Pt;=+l%T`z9bZgU4vcN=V~#&Du)v?E_I+_%>~ux(!AAydXnHe>v5Dh0 z1)s*gq2%rYR3n@Gi8EWFZ{I&@nY;X)(cy|uc;a}yR3EwQg8M)LI`|<9f%luy^8Q2R z(;nXJ2I`iFyj(JWQ$gxxyEfGVKfb?m7 z9daEruUSR*vVm9ng^=AHcs6cQ@GJl=+{;fss&o&06Ccbpwm|m}+JLS>o)ZT3qz$4w zD*Vx)Vh+Eyr}5>FlMBBs^$f6<9|Wqv-zwy@wbXvbDQisfsA&oDMCVzPvPSbK# zC%f6(UjB!S{X(&4#PPWQ#mAoV?P-X6I6lVl|2?z+bJyy=CxcF8Iio-?kxVz4ZG3Xl HqD}t;&P8Mr From 1edb9b22b377ae159f5a32c60c7d241a91cc67eb Mon Sep 17 00:00:00 2001 From: Robbi Bishop-Taylor Date: Thu, 1 Aug 2024 22:05:26 +1000 Subject: [PATCH 31/45] Clean repo --- docker-compose.yaml | 37 - docker/README.md | 61 - docker/coastline/run_tests | 17 - docker/coastline/wait_for_database | 11 - docker/db/Dockerfile | 2 - docker/db/dump.sql | 3412 ---------------------------- docker/docker-compose.cleandb.yaml | 13 - docker/docker-compose.index.yaml | 17 - 8 files changed, 3570 deletions(-) delete mode 100644 docker-compose.yaml delete mode 100644 docker/README.md delete mode 100644 docker/coastline/run_tests delete mode 100644 docker/coastline/wait_for_database delete mode 100644 docker/db/Dockerfile delete mode 100644 docker/db/dump.sql delete mode 100644 docker/docker-compose.cleandb.yaml delete mode 100644 docker/docker-compose.index.yaml diff --git a/docker-compose.yaml b/docker-compose.yaml deleted file mode 100644 index 541ecfb2..00000000 --- a/docker-compose.yaml +++ /dev/null @@ -1,37 +0,0 @@ -version: '3.4' - -services: - postgres: - # db with some data from ls5, 7, 8 pre-indexed - build: docker/db/ - environment: - - POSTGRES_DB=odc - - POSTGRES_PASSWORD=odcpass - - POSTGRES_USER=odcuser - ports: - - "5432:5432" - restart: always - # Overwrite ows so it can talk to docker db - coastline: - build: - context: . - args: - ENVIRONMENT: test - links: - - postgres:postgres - environment: - DB_PORT: 5432 - DB_HOSTNAME: postgres - DB_USERNAME: odcuser - DB_PASSWORD: odcpass - DB_DATABASE: odc - AWS_NO_SIGN_REQUEST: "yes" - GDAL_HTTP_MAX_RETRY: 5 - depends_on: - - postgres - volumes: - - ./artifacts:/mnt/artifacts - - ./docker/coastline/wait-for-db:/usr/local/bin/wait-for-db - - ./tide_models/:/var/share/tide_models - restart: always - command: tail -f /dev/null diff --git a/docker/README.md b/docker/README.md deleted file mode 100644 index 8eef4127..00000000 --- a/docker/README.md +++ /dev/null @@ -1,61 +0,0 @@ -# Integration test setup - -## Integration test data -### Setting up a new database dump - -``` - # Bring up indexing and database container - docker-compose -f docker/docker-compose.index.yaml -f docker/docker-compose.cleandb.yaml up - - # Start by going to index container - docker exec -ti dea-coastlines_index_1 bash - datacube system init - exit -``` - -### Building on top of existing database dump - -``` - docker-compose -f docker-compose.yaml -f docker/docker-compose.index.yaml up -``` - -### Indexing and creating database dump - -The products indexed into the existing database dump are: - -- https://explorer.dev.dea.ga.gov.au/product/ga_ls8c_ard_3/regions/089083 -- https://explorer.dev.dea.ga.gov.au/product/ga_ls5t_ard_3/regions/089083 -- https://explorer.dev.dea.ga.gov.au/product/ga_ls7e_ard_3/regions/089083 -- https://explorer.dev.dea.ga.gov.au/product/ga_ls9c_ard_3/regions/089083 - -``` - # Start by going to index container - docker exec -ti dea-coastlines_index_1 bash - - # Indexing example: - # - Add a new product - datacube product add https://raw.githubusercontent.com/GeoscienceAustralia/dea-config/master/products/baseline_satellite_data/c3/ga_ls9c_ard_3.odc-product.yaml - - # - Index datasets from s3 - s3-to-dc --skip-lineage s3://dea-public-data/baseline/ga_ls9c_ard_3/089/083/**/*.odc-metadata.yaml ga_ls9c_ard_3 - - pg_dump -U odc -p 5432 -h postgres odc > dump.sql - # Enter password on prompt: odcpass or to check echo $DB_PASSWORD - - # Copy the new database dump to the dea-coastlines/docker/database folder - docker cp dea-coastlines_index_1:/dump.sql dea-coastlines/docker/db/dump.sql -``` - -### Running tests locally - -``` - mkdir artifacts - chmod a+rw artifacts - wget https://www.dropbox.com/s/ivx93rcdl9yfdaf/tide_models_clipped.zip?dl=1 -O tide_models_clipped.zip - unzip tide_models_clipped.zip - - docker-compose up -d - docker-compose exec -T coastline /bin/sh -c "sh ./docker/coastline/wait_for_database; pytest --cov=dea_coastlines --cov-report=xml tests/" - docker-compose exec -T coastline /bin/sh -c "cp /tmp/coverage.xml /mnt/artifacts" - docker-compose down -``` diff --git a/docker/coastline/run_tests b/docker/coastline/run_tests deleted file mode 100644 index 2a7e387b..00000000 --- a/docker/coastline/run_tests +++ /dev/null @@ -1,17 +0,0 @@ -#!/bin/sh - -# Wait for datacube database -sh docker/coastline/wait_for_database - -# Run integration tests and generate code coverage -pytest --cov=coastlines --cov-report=xml tests/ - -# Copy code coverage and other integration test validation -# outputs to to artifacts directory so they are accessible -# outside the docker container via the mounted volume -cp coverage.xml /mnt/artifacts/ -cp data/processed/tests/coastlines_tests.gpkg /mnt/artifacts/coastlines_tests.gpkg -cp data/processed/tests/coastlines_tests.shp.zip /mnt/artifacts/coastlines_tests.shp.zip -cp data/validation/processed/stats_tests.png /mnt/artifacts/stats_tests.png -cp data/validation/processed/stats_tests.csv /mnt/artifacts/stats_tests.csv -cp tests/README.md /mnt/artifacts/README.md diff --git a/docker/coastline/wait_for_database b/docker/coastline/wait_for_database deleted file mode 100644 index 3379cd11..00000000 --- a/docker/coastline/wait_for_database +++ /dev/null @@ -1,11 +0,0 @@ -#!/bin/sh - -RETRIES=10 - -# Wait until Datacube database is ready -until pg_isready --dbname=$DB_DATABASE --host=$DB_HOSTNAME --port=$DB_PORT --username=$DB_USERNAME || [ $RETRIES -eq 0 ]; do - echo "Waiting for $DB_HOSTNAME server, $((RETRIES-=1)) remaining attempts..." - sleep 2 -done - -exec "$@" \ No newline at end of file diff --git a/docker/db/Dockerfile b/docker/db/Dockerfile deleted file mode 100644 index 61d11b83..00000000 --- a/docker/db/Dockerfile +++ /dev/null @@ -1,2 +0,0 @@ -FROM kartoza/postgis:13-3.1 -COPY dump.sql /docker-entrypoint-initdb.d/ diff --git a/docker/db/dump.sql b/docker/db/dump.sql deleted file mode 100644 index ce93c4f0..00000000 --- a/docker/db/dump.sql +++ /dev/null @@ -1,3412 +0,0 @@ --- --- PostgreSQL database dump --- - --- Dumped from database version 13.4 (Debian 13.4-1.pgdg110+1) --- Dumped by pg_dump version 13.6 (Ubuntu 13.6-1.pgdg20.04+1+b1) - -SET statement_timeout = 0; -SET lock_timeout = 0; -SET idle_in_transaction_session_timeout = 0; -SET client_encoding = 'UTF8'; -SET standard_conforming_strings = on; -SELECT pg_catalog.set_config('search_path', '', false); -SET check_function_bodies = false; -SET xmloption = content; -SET client_min_messages = warning; -SET row_security = off; - --- --- Name: agdc; Type: SCHEMA; Schema: -; Owner: odcuser --- - -CREATE SCHEMA agdc; - - -ALTER SCHEMA agdc OWNER TO odcuser; - --- --- Name: pg_cron; Type: EXTENSION; Schema: -; Owner: - --- - -CREATE EXTENSION IF NOT EXISTS pg_cron WITH SCHEMA public; - - --- --- Name: EXTENSION pg_cron; Type: COMMENT; Schema: -; Owner: --- - -COMMENT ON EXTENSION pg_cron IS 'Job scheduler for PostgreSQL'; - - --- --- Name: tiger; Type: SCHEMA; Schema: -; Owner: odcuser --- - -CREATE SCHEMA tiger; - - -ALTER SCHEMA tiger OWNER TO odcuser; - --- --- Name: tiger_data; Type: SCHEMA; Schema: -; Owner: odcuser --- - -CREATE SCHEMA tiger_data; - - -ALTER SCHEMA tiger_data OWNER TO odcuser; - --- --- Name: topology; Type: SCHEMA; Schema: -; Owner: postgres --- - -CREATE SCHEMA topology; - - -ALTER SCHEMA topology OWNER TO postgres; - --- --- Name: SCHEMA topology; Type: COMMENT; Schema: -; Owner: postgres --- - -COMMENT ON SCHEMA topology IS 'PostGIS Topology schema'; - - --- --- Name: fuzzystrmatch; Type: EXTENSION; Schema: -; Owner: - --- - -CREATE EXTENSION IF NOT EXISTS fuzzystrmatch WITH SCHEMA public; - - --- --- Name: EXTENSION fuzzystrmatch; Type: COMMENT; Schema: -; Owner: --- - -COMMENT ON EXTENSION fuzzystrmatch IS 'determine similarities and distance between strings'; - - --- --- Name: hstore; Type: EXTENSION; Schema: -; Owner: - --- - -CREATE EXTENSION IF NOT EXISTS hstore WITH SCHEMA public; - - --- --- Name: EXTENSION hstore; Type: COMMENT; Schema: -; Owner: --- - -COMMENT ON EXTENSION hstore IS 'data type for storing sets of (key, value) pairs'; - - --- --- Name: postgis; Type: EXTENSION; Schema: -; Owner: - --- - -CREATE EXTENSION IF NOT EXISTS postgis WITH SCHEMA public; - - --- --- Name: EXTENSION postgis; Type: COMMENT; Schema: -; Owner: --- - -COMMENT ON EXTENSION postgis IS 'PostGIS geometry and geography spatial types and functions'; - - --- --- Name: pgrouting; Type: EXTENSION; Schema: -; Owner: - --- - -CREATE EXTENSION IF NOT EXISTS pgrouting WITH SCHEMA public; - - --- --- Name: EXTENSION pgrouting; Type: COMMENT; Schema: -; Owner: --- - -COMMENT ON EXTENSION pgrouting IS 'pgRouting Extension'; - - --- --- Name: postgis_raster; Type: EXTENSION; Schema: -; Owner: - --- - -CREATE EXTENSION IF NOT EXISTS postgis_raster WITH SCHEMA public; - - --- --- Name: EXTENSION postgis_raster; Type: COMMENT; Schema: -; Owner: --- - -COMMENT ON EXTENSION postgis_raster IS 'PostGIS raster types and functions'; - - --- --- Name: postgis_tiger_geocoder; Type: EXTENSION; Schema: -; Owner: - --- - -CREATE EXTENSION IF NOT EXISTS postgis_tiger_geocoder WITH SCHEMA tiger; - - --- --- Name: EXTENSION postgis_tiger_geocoder; Type: COMMENT; Schema: -; Owner: --- - -COMMENT ON EXTENSION postgis_tiger_geocoder IS 'PostGIS tiger geocoder and reverse geocoder'; - - --- --- Name: postgis_topology; Type: EXTENSION; Schema: -; Owner: - --- - -CREATE EXTENSION IF NOT EXISTS postgis_topology WITH SCHEMA topology; - - --- --- Name: EXTENSION postgis_topology; Type: COMMENT; Schema: -; Owner: --- - -COMMENT ON EXTENSION postgis_topology IS 'PostGIS topology spatial types and functions'; - - --- --- Name: float8range; Type: TYPE; Schema: agdc; Owner: odcuser --- - -CREATE TYPE agdc.float8range AS RANGE ( - subtype = double precision, - subtype_diff = float8mi -); - - -ALTER TYPE agdc.float8range OWNER TO odcuser; - --- --- Name: common_timestamp(text); Type: FUNCTION; Schema: agdc; Owner: odcuser --- - -CREATE FUNCTION agdc.common_timestamp(text) RETURNS timestamp with time zone - LANGUAGE sql IMMUTABLE STRICT - AS $_$ -select ($1)::timestamp at time zone 'utc'; -$_$; - - -ALTER FUNCTION agdc.common_timestamp(text) OWNER TO odcuser; - --- --- Name: set_row_update_time(); Type: FUNCTION; Schema: agdc; Owner: odcuser --- - -CREATE FUNCTION agdc.set_row_update_time() RETURNS trigger - LANGUAGE plpgsql - AS $$ -begin - new.updated = now(); - return new; -end; -$$; - - -ALTER FUNCTION agdc.set_row_update_time() OWNER TO odcuser; - --- --- Name: asbinary(public.geometry); Type: FUNCTION; Schema: public; Owner: postgres --- - -CREATE FUNCTION public.asbinary(public.geometry) RETURNS bytea - LANGUAGE c IMMUTABLE STRICT - AS '$libdir/postgis-3', 'LWGEOM_asBinary'; - - -ALTER FUNCTION public.asbinary(public.geometry) OWNER TO postgres; - --- --- Name: asbinary(public.geometry, text); Type: FUNCTION; Schema: public; Owner: postgres --- - -CREATE FUNCTION public.asbinary(public.geometry, text) RETURNS bytea - LANGUAGE c IMMUTABLE STRICT - AS '$libdir/postgis-3', 'LWGEOM_asBinary'; - - -ALTER FUNCTION public.asbinary(public.geometry, text) OWNER TO postgres; - --- --- Name: astext(public.geometry); Type: FUNCTION; Schema: public; Owner: postgres --- - -CREATE FUNCTION public.astext(public.geometry) RETURNS text - LANGUAGE c IMMUTABLE STRICT - AS '$libdir/postgis-3', 'LWGEOM_asText'; - - -ALTER FUNCTION public.astext(public.geometry) OWNER TO postgres; - --- --- Name: estimated_extent(text, text); Type: FUNCTION; Schema: public; Owner: postgres --- - -CREATE FUNCTION public.estimated_extent(text, text) RETURNS public.box2d - LANGUAGE c IMMUTABLE STRICT SECURITY DEFINER - AS '$libdir/postgis-3', 'geometry_estimated_extent'; - - -ALTER FUNCTION public.estimated_extent(text, text) OWNER TO postgres; - --- --- Name: estimated_extent(text, text, text); Type: FUNCTION; Schema: public; Owner: postgres --- - -CREATE FUNCTION public.estimated_extent(text, text, text) RETURNS public.box2d - LANGUAGE c IMMUTABLE STRICT SECURITY DEFINER - AS '$libdir/postgis-3', 'geometry_estimated_extent'; - - -ALTER FUNCTION public.estimated_extent(text, text, text) OWNER TO postgres; - --- --- Name: geomfromtext(text); Type: FUNCTION; Schema: public; Owner: postgres --- - -CREATE FUNCTION public.geomfromtext(text) RETURNS public.geometry - LANGUAGE sql IMMUTABLE STRICT - AS $_$SELECT ST_GeomFromText($1)$_$; - - -ALTER FUNCTION public.geomfromtext(text) OWNER TO postgres; - --- --- Name: geomfromtext(text, integer); Type: FUNCTION; Schema: public; Owner: postgres --- - -CREATE FUNCTION public.geomfromtext(text, integer) RETURNS public.geometry - LANGUAGE sql IMMUTABLE STRICT - AS $_$SELECT ST_GeomFromText($1, $2)$_$; - - -ALTER FUNCTION public.geomfromtext(text, integer) OWNER TO postgres; - --- --- Name: ndims(public.geometry); Type: FUNCTION; Schema: public; Owner: postgres --- - -CREATE FUNCTION public.ndims(public.geometry) RETURNS smallint - LANGUAGE c IMMUTABLE STRICT - AS '$libdir/postgis-3', 'LWGEOM_ndims'; - - -ALTER FUNCTION public.ndims(public.geometry) OWNER TO postgres; - --- --- Name: setsrid(public.geometry, integer); Type: FUNCTION; Schema: public; Owner: postgres --- - -CREATE FUNCTION public.setsrid(public.geometry, integer) RETURNS public.geometry - LANGUAGE c IMMUTABLE STRICT - AS '$libdir/postgis-3', 'LWGEOM_set_srid'; - - -ALTER FUNCTION public.setsrid(public.geometry, integer) OWNER TO postgres; - --- --- Name: srid(public.geometry); Type: FUNCTION; Schema: public; Owner: postgres --- - -CREATE FUNCTION public.srid(public.geometry) RETURNS integer - LANGUAGE c IMMUTABLE STRICT - AS '$libdir/postgis-3', 'LWGEOM_get_srid'; - - -ALTER FUNCTION public.srid(public.geometry) OWNER TO postgres; - --- --- Name: st_asbinary(text); Type: FUNCTION; Schema: public; Owner: postgres --- - -CREATE FUNCTION public.st_asbinary(text) RETURNS bytea - LANGUAGE sql IMMUTABLE STRICT - AS $_$ SELECT ST_AsBinary($1::geometry);$_$; - - -ALTER FUNCTION public.st_asbinary(text) OWNER TO postgres; - --- --- Name: st_astext(bytea); Type: FUNCTION; Schema: public; Owner: postgres --- - -CREATE FUNCTION public.st_astext(bytea) RETURNS text - LANGUAGE sql IMMUTABLE STRICT - AS $_$ SELECT ST_AsText($1::geometry);$_$; - - -ALTER FUNCTION public.st_astext(bytea) OWNER TO postgres; - --- --- Name: gist_geometry_ops; Type: OPERATOR FAMILY; Schema: public; Owner: postgres --- - -CREATE OPERATOR FAMILY public.gist_geometry_ops USING gist; - - -ALTER OPERATOR FAMILY public.gist_geometry_ops USING gist OWNER TO postgres; - --- --- Name: gist_geometry_ops; Type: OPERATOR CLASS; Schema: public; Owner: postgres --- - -CREATE OPERATOR CLASS public.gist_geometry_ops - FOR TYPE public.geometry USING gist FAMILY public.gist_geometry_ops AS - STORAGE public.box2df , - OPERATOR 1 public.<<(public.geometry,public.geometry) , - OPERATOR 2 public.&<(public.geometry,public.geometry) , - OPERATOR 3 public.&&(public.geometry,public.geometry) , - OPERATOR 4 public.&>(public.geometry,public.geometry) , - OPERATOR 5 public.>>(public.geometry,public.geometry) , - OPERATOR 6 public.~=(public.geometry,public.geometry) , - OPERATOR 7 public.~(public.geometry,public.geometry) , - OPERATOR 8 public.@(public.geometry,public.geometry) , - OPERATOR 9 public.&<|(public.geometry,public.geometry) , - OPERATOR 10 public.<<|(public.geometry,public.geometry) , - OPERATOR 11 public.|>>(public.geometry,public.geometry) , - OPERATOR 12 public.|&>(public.geometry,public.geometry) , - OPERATOR 13 public.<->(public.geometry,public.geometry) FOR ORDER BY pg_catalog.float_ops , - OPERATOR 14 public.<#>(public.geometry,public.geometry) FOR ORDER BY pg_catalog.float_ops , - FUNCTION 1 (public.geometry, public.geometry) public.geometry_gist_consistent_2d(internal,public.geometry,integer) , - FUNCTION 2 (public.geometry, public.geometry) public.geometry_gist_union_2d(bytea,internal) , - FUNCTION 3 (public.geometry, public.geometry) public.geometry_gist_compress_2d(internal) , - FUNCTION 4 (public.geometry, public.geometry) public.geometry_gist_decompress_2d(internal) , - FUNCTION 5 (public.geometry, public.geometry) public.geometry_gist_penalty_2d(internal,internal,internal) , - FUNCTION 6 (public.geometry, public.geometry) public.geometry_gist_picksplit_2d(internal,internal) , - FUNCTION 7 (public.geometry, public.geometry) public.geometry_gist_same_2d(public.geometry,public.geometry,internal) , - FUNCTION 8 (public.geometry, public.geometry) public.geometry_gist_distance_2d(internal,public.geometry,integer); - - -ALTER OPERATOR CLASS public.gist_geometry_ops USING gist OWNER TO postgres; - -SET default_tablespace = ''; - -SET default_table_access_method = heap; - --- --- Name: dataset; Type: TABLE; Schema: agdc; Owner: odcuser --- - -CREATE TABLE agdc.dataset ( - id uuid NOT NULL, - metadata_type_ref smallint NOT NULL, - dataset_type_ref smallint NOT NULL, - metadata jsonb NOT NULL, - archived timestamp with time zone, - added timestamp with time zone DEFAULT now() NOT NULL, - added_by name DEFAULT CURRENT_USER NOT NULL, - updated timestamp with time zone -); - - -ALTER TABLE agdc.dataset OWNER TO odcuser; - --- --- Name: dataset_location; Type: TABLE; Schema: agdc; Owner: odcuser --- - -CREATE TABLE agdc.dataset_location ( - id integer NOT NULL, - dataset_ref uuid NOT NULL, - uri_scheme character varying NOT NULL, - uri_body character varying NOT NULL, - added timestamp with time zone DEFAULT now() NOT NULL, - added_by name DEFAULT CURRENT_USER NOT NULL, - archived timestamp with time zone -); - - -ALTER TABLE agdc.dataset_location OWNER TO odcuser; - --- --- Name: dataset_location_id_seq; Type: SEQUENCE; Schema: agdc; Owner: odcuser --- - -CREATE SEQUENCE agdc.dataset_location_id_seq - AS integer - START WITH 1 - INCREMENT BY 1 - NO MINVALUE - NO MAXVALUE - CACHE 1; - - -ALTER TABLE agdc.dataset_location_id_seq OWNER TO odcuser; - --- --- Name: dataset_location_id_seq; Type: SEQUENCE OWNED BY; Schema: agdc; Owner: odcuser --- - -ALTER SEQUENCE agdc.dataset_location_id_seq OWNED BY agdc.dataset_location.id; - - --- --- Name: dataset_source; Type: TABLE; Schema: agdc; Owner: odcuser --- - -CREATE TABLE agdc.dataset_source ( - dataset_ref uuid NOT NULL, - classifier character varying NOT NULL, - source_dataset_ref uuid NOT NULL -); - - -ALTER TABLE agdc.dataset_source OWNER TO odcuser; - --- --- Name: dataset_type; Type: TABLE; Schema: agdc; Owner: odcuser --- - -CREATE TABLE agdc.dataset_type ( - id smallint NOT NULL, - name character varying NOT NULL, - metadata jsonb NOT NULL, - metadata_type_ref smallint NOT NULL, - definition jsonb NOT NULL, - added timestamp with time zone DEFAULT now() NOT NULL, - added_by name DEFAULT CURRENT_USER NOT NULL, - updated timestamp with time zone, - CONSTRAINT ck_dataset_type_alphanumeric_name CHECK (((name)::text ~* '^\w+$'::text)) -); - - -ALTER TABLE agdc.dataset_type OWNER TO odcuser; - --- --- Name: dataset_type_id_seq; Type: SEQUENCE; Schema: agdc; Owner: odcuser --- - -CREATE SEQUENCE agdc.dataset_type_id_seq - AS smallint - START WITH 1 - INCREMENT BY 1 - NO MINVALUE - NO MAXVALUE - CACHE 1; - - -ALTER TABLE agdc.dataset_type_id_seq OWNER TO odcuser; - --- --- Name: dataset_type_id_seq; Type: SEQUENCE OWNED BY; Schema: agdc; Owner: odcuser --- - -ALTER SEQUENCE agdc.dataset_type_id_seq OWNED BY agdc.dataset_type.id; - - --- --- Name: metadata_type; Type: TABLE; Schema: agdc; Owner: odcuser --- - -CREATE TABLE agdc.metadata_type ( - id smallint NOT NULL, - name character varying NOT NULL, - definition jsonb NOT NULL, - added timestamp with time zone DEFAULT now() NOT NULL, - added_by name DEFAULT CURRENT_USER NOT NULL, - updated timestamp with time zone, - CONSTRAINT ck_metadata_type_alphanumeric_name CHECK (((name)::text ~* '^\w+$'::text)) -); - - -ALTER TABLE agdc.metadata_type OWNER TO odcuser; - --- --- Name: dv_eo3_dataset; Type: VIEW; Schema: agdc; Owner: odcuser --- - -CREATE VIEW agdc.dv_eo3_dataset AS - SELECT dataset.id, - dataset.added AS indexed_time, - dataset.added_by AS indexed_by, - dataset_type.name AS product, - dataset.dataset_type_ref AS dataset_type_id, - metadata_type.name AS metadata_type, - dataset.metadata_type_ref AS metadata_type_id, - dataset.metadata AS metadata_doc, - agdc.common_timestamp((dataset.metadata #>> '{properties,odc:processing_datetime}'::text[])) AS creation_time, - (dataset.metadata #>> '{properties,odc:file_format}'::text[]) AS format, - (dataset.metadata #>> '{label}'::text[]) AS label, - agdc.float8range(((dataset.metadata #>> '{extent,lat,begin}'::text[]))::double precision, ((dataset.metadata #>> '{extent,lat,end}'::text[]))::double precision, '[]'::text) AS lat, - agdc.float8range(((dataset.metadata #>> '{extent,lon,begin}'::text[]))::double precision, ((dataset.metadata #>> '{extent,lon,end}'::text[]))::double precision, '[]'::text) AS lon, - tstzrange(LEAST(agdc.common_timestamp((dataset.metadata #>> '{properties,dtr:start_datetime}'::text[])), agdc.common_timestamp((dataset.metadata #>> '{properties,datetime}'::text[]))), GREATEST(agdc.common_timestamp((dataset.metadata #>> '{properties,dtr:end_datetime}'::text[])), agdc.common_timestamp((dataset.metadata #>> '{properties,datetime}'::text[]))), '[]'::text) AS "time", - (dataset.metadata #>> '{properties,eo:platform}'::text[]) AS platform, - (dataset.metadata #>> '{properties,eo:instrument}'::text[]) AS instrument, - ((dataset.metadata #>> '{properties,eo:cloud_cover}'::text[]))::double precision AS cloud_cover, - (dataset.metadata #>> '{properties,odc:region_code}'::text[]) AS region_code, - (dataset.metadata #>> '{properties,odc:product_family}'::text[]) AS product_family, - (dataset.metadata #>> '{properties,dea:dataset_maturity}'::text[]) AS dataset_maturity - FROM ((agdc.dataset - JOIN agdc.dataset_type ON ((dataset_type.id = dataset.dataset_type_ref))) - JOIN agdc.metadata_type ON ((metadata_type.id = dataset_type.metadata_type_ref))) - WHERE ((dataset.archived IS NULL) AND (dataset.metadata_type_ref = 1)); - - -ALTER TABLE agdc.dv_eo3_dataset OWNER TO odcuser; - --- --- Name: dv_eo3_landsat_ard_dataset; Type: VIEW; Schema: agdc; Owner: odcuser --- - -CREATE VIEW agdc.dv_eo3_landsat_ard_dataset AS - SELECT dataset.id, - dataset.added AS indexed_time, - dataset.added_by AS indexed_by, - dataset_type.name AS product, - dataset.dataset_type_ref AS dataset_type_id, - metadata_type.name AS metadata_type, - dataset.metadata_type_ref AS metadata_type_id, - dataset.metadata AS metadata_doc, - agdc.common_timestamp((dataset.metadata #>> '{properties,odc:processing_datetime}'::text[])) AS creation_time, - (dataset.metadata #>> '{properties,odc:file_format}'::text[]) AS format, - (dataset.metadata #>> '{label}'::text[]) AS label, - ((dataset.metadata #>> '{properties,gqa:cep90}'::text[]))::double precision AS gqa, - agdc.float8range(((dataset.metadata #>> '{extent,lat,begin}'::text[]))::double precision, ((dataset.metadata #>> '{extent,lat,end}'::text[]))::double precision, '[]'::text) AS lat, - agdc.float8range(((dataset.metadata #>> '{extent,lon,begin}'::text[]))::double precision, ((dataset.metadata #>> '{extent,lon,end}'::text[]))::double precision, '[]'::text) AS lon, - tstzrange(LEAST(agdc.common_timestamp((dataset.metadata #>> '{properties,dtr:start_datetime}'::text[])), agdc.common_timestamp((dataset.metadata #>> '{properties,datetime}'::text[]))), GREATEST(agdc.common_timestamp((dataset.metadata #>> '{properties,dtr:end_datetime}'::text[])), agdc.common_timestamp((dataset.metadata #>> '{properties,datetime}'::text[]))), '[]'::text) AS "time", - ((dataset.metadata #>> '{properties,eo:gsd}'::text[]))::double precision AS eo_gsd, - (dataset.metadata #>> '{crs}'::text[]) AS crs_raw, - (dataset.metadata #>> '{properties,eo:platform}'::text[]) AS platform, - ((dataset.metadata #>> '{properties,gqa:abs_x}'::text[]))::double precision AS gqa_abs_x, - ((dataset.metadata #>> '{properties,gqa:abs_y}'::text[]))::double precision AS gqa_abs_y, - ((dataset.metadata #>> '{properties,gqa:cep90}'::text[]))::double precision AS gqa_cep90, - ((dataset.metadata #>> '{properties,fmask:snow}'::text[]))::double precision AS fmask_snow, - ((dataset.metadata #>> '{properties,gqa:abs_xy}'::text[]))::double precision AS gqa_abs_xy, - ((dataset.metadata #>> '{properties,gqa:mean_x}'::text[]))::double precision AS gqa_mean_x, - ((dataset.metadata #>> '{properties,gqa:mean_y}'::text[]))::double precision AS gqa_mean_y, - (dataset.metadata #>> '{properties,eo:instrument}'::text[]) AS instrument, - ((dataset.metadata #>> '{properties,eo:cloud_cover}'::text[]))::double precision AS cloud_cover, - ((dataset.metadata #>> '{properties,fmask:clear}'::text[]))::double precision AS fmask_clear, - ((dataset.metadata #>> '{properties,fmask:water}'::text[]))::double precision AS fmask_water, - ((dataset.metadata #>> '{properties,gqa:mean_xy}'::text[]))::double precision AS gqa_mean_xy, - (dataset.metadata #>> '{properties,odc:region_code}'::text[]) AS region_code, - ((dataset.metadata #>> '{properties,gqa:stddev_x}'::text[]))::double precision AS gqa_stddev_x, - ((dataset.metadata #>> '{properties,gqa:stddev_y}'::text[]))::double precision AS gqa_stddev_y, - ((dataset.metadata #>> '{properties,gqa:stddev_xy}'::text[]))::double precision AS gqa_stddev_xy, - ((dataset.metadata #>> '{properties,eo:sun_azimuth}'::text[]))::double precision AS eo_sun_azimuth, - (dataset.metadata #>> '{properties,odc:product_family}'::text[]) AS product_family, - (dataset.metadata #>> '{properties,dea:dataset_maturity}'::text[]) AS dataset_maturity, - ((dataset.metadata #>> '{properties,eo:sun_elevation}'::text[]))::double precision AS eo_sun_elevation, - (dataset.metadata #>> '{properties,landsat:landsat_scene_id}'::text[]) AS landsat_scene_id, - ((dataset.metadata #>> '{properties,fmask:cloud_shadow}'::text[]))::double precision AS fmask_cloud_shadow, - (dataset.metadata #>> '{properties,landsat:landsat_product_id}'::text[]) AS landsat_product_id, - ((dataset.metadata #>> '{properties,gqa:iterative_mean_x}'::text[]))::double precision AS gqa_iterative_mean_x, - ((dataset.metadata #>> '{properties,gqa:iterative_mean_y}'::text[]))::double precision AS gqa_iterative_mean_y, - ((dataset.metadata #>> '{properties,gqa:iterative_mean_xy}'::text[]))::double precision AS gqa_iterative_mean_xy, - ((dataset.metadata #>> '{properties,gqa:iterative_stddev_x}'::text[]))::double precision AS gqa_iterative_stddev_x, - ((dataset.metadata #>> '{properties,gqa:iterative_stddev_y}'::text[]))::double precision AS gqa_iterative_stddev_y, - ((dataset.metadata #>> '{properties,gqa:iterative_stddev_xy}'::text[]))::double precision AS gqa_iterative_stddev_xy, - ((dataset.metadata #>> '{properties,gqa:abs_iterative_mean_x}'::text[]))::double precision AS gqa_abs_iterative_mean_x, - ((dataset.metadata #>> '{properties,gqa:abs_iterative_mean_y}'::text[]))::double precision AS gqa_abs_iterative_mean_y, - ((dataset.metadata #>> '{properties,gqa:abs_iterative_mean_xy}'::text[]))::double precision AS gqa_abs_iterative_mean_xy - FROM ((agdc.dataset - JOIN agdc.dataset_type ON ((dataset_type.id = dataset.dataset_type_ref))) - JOIN agdc.metadata_type ON ((metadata_type.id = dataset_type.metadata_type_ref))) - WHERE ((dataset.archived IS NULL) AND (dataset.metadata_type_ref = 4)); - - -ALTER TABLE agdc.dv_eo3_landsat_ard_dataset OWNER TO odcuser; - --- --- Name: dv_eo_dataset; Type: VIEW; Schema: agdc; Owner: odcuser --- - -CREATE VIEW agdc.dv_eo_dataset AS - SELECT dataset.id, - dataset.added AS indexed_time, - dataset.added_by AS indexed_by, - dataset_type.name AS product, - dataset.dataset_type_ref AS dataset_type_id, - metadata_type.name AS metadata_type, - dataset.metadata_type_ref AS metadata_type_id, - dataset.metadata AS metadata_doc, - agdc.common_timestamp((dataset.metadata #>> '{creation_dt}'::text[])) AS creation_time, - (dataset.metadata #>> '{format,name}'::text[]) AS format, - (dataset.metadata #>> '{ga_label}'::text[]) AS label, - agdc.float8range(LEAST(((dataset.metadata #>> '{extent,coord,ur,lat}'::text[]))::double precision, ((dataset.metadata #>> '{extent,coord,lr,lat}'::text[]))::double precision, ((dataset.metadata #>> '{extent,coord,ul,lat}'::text[]))::double precision, ((dataset.metadata #>> '{extent,coord,ll,lat}'::text[]))::double precision), GREATEST(((dataset.metadata #>> '{extent,coord,ur,lat}'::text[]))::double precision, ((dataset.metadata #>> '{extent,coord,lr,lat}'::text[]))::double precision, ((dataset.metadata #>> '{extent,coord,ul,lat}'::text[]))::double precision, ((dataset.metadata #>> '{extent,coord,ll,lat}'::text[]))::double precision), '[]'::text) AS lat, - agdc.float8range(LEAST(((dataset.metadata #>> '{extent,coord,ul,lon}'::text[]))::double precision, ((dataset.metadata #>> '{extent,coord,ur,lon}'::text[]))::double precision, ((dataset.metadata #>> '{extent,coord,ll,lon}'::text[]))::double precision, ((dataset.metadata #>> '{extent,coord,lr,lon}'::text[]))::double precision), GREATEST(((dataset.metadata #>> '{extent,coord,ul,lon}'::text[]))::double precision, ((dataset.metadata #>> '{extent,coord,ur,lon}'::text[]))::double precision, ((dataset.metadata #>> '{extent,coord,ll,lon}'::text[]))::double precision, ((dataset.metadata #>> '{extent,coord,lr,lon}'::text[]))::double precision), '[]'::text) AS lon, - tstzrange(LEAST(agdc.common_timestamp((dataset.metadata #>> '{extent,from_dt}'::text[])), agdc.common_timestamp((dataset.metadata #>> '{extent,center_dt}'::text[]))), GREATEST(agdc.common_timestamp((dataset.metadata #>> '{extent,to_dt}'::text[])), agdc.common_timestamp((dataset.metadata #>> '{extent,center_dt}'::text[]))), '[]'::text) AS "time", - (dataset.metadata #>> '{platform,code}'::text[]) AS platform, - (dataset.metadata #>> '{instrument,name}'::text[]) AS instrument, - (dataset.metadata #>> '{product_type}'::text[]) AS product_type - FROM ((agdc.dataset - JOIN agdc.dataset_type ON ((dataset_type.id = dataset.dataset_type_ref))) - JOIN agdc.metadata_type ON ((metadata_type.id = dataset_type.metadata_type_ref))) - WHERE ((dataset.archived IS NULL) AND (dataset.metadata_type_ref = 2)); - - -ALTER TABLE agdc.dv_eo_dataset OWNER TO odcuser; - --- --- Name: dv_ga_ls5t_ard_3_dataset; Type: VIEW; Schema: agdc; Owner: odcuser --- - -CREATE VIEW agdc.dv_ga_ls5t_ard_3_dataset AS - SELECT dataset.id, - dataset.added AS indexed_time, - dataset.added_by AS indexed_by, - dataset_type.name AS product, - dataset.dataset_type_ref AS dataset_type_id, - metadata_type.name AS metadata_type, - dataset.metadata_type_ref AS metadata_type_id, - dataset.metadata AS metadata_doc, - agdc.common_timestamp((dataset.metadata #>> '{properties,odc:processing_datetime}'::text[])) AS creation_time, - (dataset.metadata #>> '{properties,odc:file_format}'::text[]) AS format, - (dataset.metadata #>> '{label}'::text[]) AS label, - ((dataset.metadata #>> '{properties,gqa:cep90}'::text[]))::double precision AS gqa, - agdc.float8range(((dataset.metadata #>> '{extent,lat,begin}'::text[]))::double precision, ((dataset.metadata #>> '{extent,lat,end}'::text[]))::double precision, '[]'::text) AS lat, - agdc.float8range(((dataset.metadata #>> '{extent,lon,begin}'::text[]))::double precision, ((dataset.metadata #>> '{extent,lon,end}'::text[]))::double precision, '[]'::text) AS lon, - tstzrange(LEAST(agdc.common_timestamp((dataset.metadata #>> '{properties,dtr:start_datetime}'::text[])), agdc.common_timestamp((dataset.metadata #>> '{properties,datetime}'::text[]))), GREATEST(agdc.common_timestamp((dataset.metadata #>> '{properties,dtr:end_datetime}'::text[])), agdc.common_timestamp((dataset.metadata #>> '{properties,datetime}'::text[]))), '[]'::text) AS "time", - ((dataset.metadata #>> '{properties,eo:gsd}'::text[]))::double precision AS eo_gsd, - (dataset.metadata #>> '{crs}'::text[]) AS crs_raw, - (dataset.metadata #>> '{properties,eo:platform}'::text[]) AS platform, - ((dataset.metadata #>> '{properties,gqa:abs_x}'::text[]))::double precision AS gqa_abs_x, - ((dataset.metadata #>> '{properties,gqa:abs_y}'::text[]))::double precision AS gqa_abs_y, - ((dataset.metadata #>> '{properties,gqa:cep90}'::text[]))::double precision AS gqa_cep90, - ((dataset.metadata #>> '{properties,fmask:snow}'::text[]))::double precision AS fmask_snow, - ((dataset.metadata #>> '{properties,gqa:abs_xy}'::text[]))::double precision AS gqa_abs_xy, - ((dataset.metadata #>> '{properties,gqa:mean_x}'::text[]))::double precision AS gqa_mean_x, - ((dataset.metadata #>> '{properties,gqa:mean_y}'::text[]))::double precision AS gqa_mean_y, - (dataset.metadata #>> '{properties,eo:instrument}'::text[]) AS instrument, - ((dataset.metadata #>> '{properties,eo:cloud_cover}'::text[]))::double precision AS cloud_cover, - ((dataset.metadata #>> '{properties,fmask:clear}'::text[]))::double precision AS fmask_clear, - ((dataset.metadata #>> '{properties,fmask:water}'::text[]))::double precision AS fmask_water, - ((dataset.metadata #>> '{properties,gqa:mean_xy}'::text[]))::double precision AS gqa_mean_xy, - (dataset.metadata #>> '{properties,odc:region_code}'::text[]) AS region_code, - ((dataset.metadata #>> '{properties,gqa:stddev_x}'::text[]))::double precision AS gqa_stddev_x, - ((dataset.metadata #>> '{properties,gqa:stddev_y}'::text[]))::double precision AS gqa_stddev_y, - ((dataset.metadata #>> '{properties,gqa:stddev_xy}'::text[]))::double precision AS gqa_stddev_xy, - ((dataset.metadata #>> '{properties,eo:sun_azimuth}'::text[]))::double precision AS eo_sun_azimuth, - (dataset.metadata #>> '{properties,odc:product_family}'::text[]) AS product_family, - (dataset.metadata #>> '{properties,dea:dataset_maturity}'::text[]) AS dataset_maturity, - ((dataset.metadata #>> '{properties,eo:sun_elevation}'::text[]))::double precision AS eo_sun_elevation, - (dataset.metadata #>> '{properties,landsat:landsat_scene_id}'::text[]) AS landsat_scene_id, - ((dataset.metadata #>> '{properties,fmask:cloud_shadow}'::text[]))::double precision AS fmask_cloud_shadow, - (dataset.metadata #>> '{properties,landsat:landsat_product_id}'::text[]) AS landsat_product_id, - ((dataset.metadata #>> '{properties,gqa:iterative_mean_x}'::text[]))::double precision AS gqa_iterative_mean_x, - ((dataset.metadata #>> '{properties,gqa:iterative_mean_y}'::text[]))::double precision AS gqa_iterative_mean_y, - ((dataset.metadata #>> '{properties,gqa:iterative_mean_xy}'::text[]))::double precision AS gqa_iterative_mean_xy, - ((dataset.metadata #>> '{properties,gqa:iterative_stddev_x}'::text[]))::double precision AS gqa_iterative_stddev_x, - ((dataset.metadata #>> '{properties,gqa:iterative_stddev_y}'::text[]))::double precision AS gqa_iterative_stddev_y, - ((dataset.metadata #>> '{properties,gqa:iterative_stddev_xy}'::text[]))::double precision AS gqa_iterative_stddev_xy, - ((dataset.metadata #>> '{properties,gqa:abs_iterative_mean_x}'::text[]))::double precision AS gqa_abs_iterative_mean_x, - ((dataset.metadata #>> '{properties,gqa:abs_iterative_mean_y}'::text[]))::double precision AS gqa_abs_iterative_mean_y, - ((dataset.metadata #>> '{properties,gqa:abs_iterative_mean_xy}'::text[]))::double precision AS gqa_abs_iterative_mean_xy - FROM ((agdc.dataset - JOIN agdc.dataset_type ON ((dataset_type.id = dataset.dataset_type_ref))) - JOIN agdc.metadata_type ON ((metadata_type.id = dataset_type.metadata_type_ref))) - WHERE ((dataset.archived IS NULL) AND (dataset.dataset_type_ref = 1)); - - -ALTER TABLE agdc.dv_ga_ls5t_ard_3_dataset OWNER TO odcuser; - --- --- Name: dv_ga_ls7e_ard_3_dataset; Type: VIEW; Schema: agdc; Owner: odcuser --- - -CREATE VIEW agdc.dv_ga_ls7e_ard_3_dataset AS - SELECT dataset.id, - dataset.added AS indexed_time, - dataset.added_by AS indexed_by, - dataset_type.name AS product, - dataset.dataset_type_ref AS dataset_type_id, - metadata_type.name AS metadata_type, - dataset.metadata_type_ref AS metadata_type_id, - dataset.metadata AS metadata_doc, - agdc.common_timestamp((dataset.metadata #>> '{properties,odc:processing_datetime}'::text[])) AS creation_time, - (dataset.metadata #>> '{properties,odc:file_format}'::text[]) AS format, - (dataset.metadata #>> '{label}'::text[]) AS label, - ((dataset.metadata #>> '{properties,gqa:cep90}'::text[]))::double precision AS gqa, - agdc.float8range(((dataset.metadata #>> '{extent,lat,begin}'::text[]))::double precision, ((dataset.metadata #>> '{extent,lat,end}'::text[]))::double precision, '[]'::text) AS lat, - agdc.float8range(((dataset.metadata #>> '{extent,lon,begin}'::text[]))::double precision, ((dataset.metadata #>> '{extent,lon,end}'::text[]))::double precision, '[]'::text) AS lon, - tstzrange(LEAST(agdc.common_timestamp((dataset.metadata #>> '{properties,dtr:start_datetime}'::text[])), agdc.common_timestamp((dataset.metadata #>> '{properties,datetime}'::text[]))), GREATEST(agdc.common_timestamp((dataset.metadata #>> '{properties,dtr:end_datetime}'::text[])), agdc.common_timestamp((dataset.metadata #>> '{properties,datetime}'::text[]))), '[]'::text) AS "time", - ((dataset.metadata #>> '{properties,eo:gsd}'::text[]))::double precision AS eo_gsd, - (dataset.metadata #>> '{crs}'::text[]) AS crs_raw, - (dataset.metadata #>> '{properties,eo:platform}'::text[]) AS platform, - ((dataset.metadata #>> '{properties,gqa:abs_x}'::text[]))::double precision AS gqa_abs_x, - ((dataset.metadata #>> '{properties,gqa:abs_y}'::text[]))::double precision AS gqa_abs_y, - ((dataset.metadata #>> '{properties,gqa:cep90}'::text[]))::double precision AS gqa_cep90, - ((dataset.metadata #>> '{properties,fmask:snow}'::text[]))::double precision AS fmask_snow, - ((dataset.metadata #>> '{properties,gqa:abs_xy}'::text[]))::double precision AS gqa_abs_xy, - ((dataset.metadata #>> '{properties,gqa:mean_x}'::text[]))::double precision AS gqa_mean_x, - ((dataset.metadata #>> '{properties,gqa:mean_y}'::text[]))::double precision AS gqa_mean_y, - (dataset.metadata #>> '{properties,eo:instrument}'::text[]) AS instrument, - ((dataset.metadata #>> '{properties,eo:cloud_cover}'::text[]))::double precision AS cloud_cover, - ((dataset.metadata #>> '{properties,fmask:clear}'::text[]))::double precision AS fmask_clear, - ((dataset.metadata #>> '{properties,fmask:water}'::text[]))::double precision AS fmask_water, - ((dataset.metadata #>> '{properties,gqa:mean_xy}'::text[]))::double precision AS gqa_mean_xy, - (dataset.metadata #>> '{properties,odc:region_code}'::text[]) AS region_code, - ((dataset.metadata #>> '{properties,gqa:stddev_x}'::text[]))::double precision AS gqa_stddev_x, - ((dataset.metadata #>> '{properties,gqa:stddev_y}'::text[]))::double precision AS gqa_stddev_y, - ((dataset.metadata #>> '{properties,gqa:stddev_xy}'::text[]))::double precision AS gqa_stddev_xy, - ((dataset.metadata #>> '{properties,eo:sun_azimuth}'::text[]))::double precision AS eo_sun_azimuth, - (dataset.metadata #>> '{properties,odc:product_family}'::text[]) AS product_family, - (dataset.metadata #>> '{properties,dea:dataset_maturity}'::text[]) AS dataset_maturity, - ((dataset.metadata #>> '{properties,eo:sun_elevation}'::text[]))::double precision AS eo_sun_elevation, - (dataset.metadata #>> '{properties,landsat:landsat_scene_id}'::text[]) AS landsat_scene_id, - ((dataset.metadata #>> '{properties,fmask:cloud_shadow}'::text[]))::double precision AS fmask_cloud_shadow, - (dataset.metadata #>> '{properties,landsat:landsat_product_id}'::text[]) AS landsat_product_id, - ((dataset.metadata #>> '{properties,gqa:iterative_mean_x}'::text[]))::double precision AS gqa_iterative_mean_x, - ((dataset.metadata #>> '{properties,gqa:iterative_mean_y}'::text[]))::double precision AS gqa_iterative_mean_y, - ((dataset.metadata #>> '{properties,gqa:iterative_mean_xy}'::text[]))::double precision AS gqa_iterative_mean_xy, - ((dataset.metadata #>> '{properties,gqa:iterative_stddev_x}'::text[]))::double precision AS gqa_iterative_stddev_x, - ((dataset.metadata #>> '{properties,gqa:iterative_stddev_y}'::text[]))::double precision AS gqa_iterative_stddev_y, - ((dataset.metadata #>> '{properties,gqa:iterative_stddev_xy}'::text[]))::double precision AS gqa_iterative_stddev_xy, - ((dataset.metadata #>> '{properties,gqa:abs_iterative_mean_x}'::text[]))::double precision AS gqa_abs_iterative_mean_x, - ((dataset.metadata #>> '{properties,gqa:abs_iterative_mean_y}'::text[]))::double precision AS gqa_abs_iterative_mean_y, - ((dataset.metadata #>> '{properties,gqa:abs_iterative_mean_xy}'::text[]))::double precision AS gqa_abs_iterative_mean_xy - FROM ((agdc.dataset - JOIN agdc.dataset_type ON ((dataset_type.id = dataset.dataset_type_ref))) - JOIN agdc.metadata_type ON ((metadata_type.id = dataset_type.metadata_type_ref))) - WHERE ((dataset.archived IS NULL) AND (dataset.dataset_type_ref = 2)); - - -ALTER TABLE agdc.dv_ga_ls7e_ard_3_dataset OWNER TO odcuser; - --- --- Name: dv_ga_ls8c_ard_3_dataset; Type: VIEW; Schema: agdc; Owner: odcuser --- - -CREATE VIEW agdc.dv_ga_ls8c_ard_3_dataset AS - SELECT dataset.id, - dataset.added AS indexed_time, - dataset.added_by AS indexed_by, - dataset_type.name AS product, - dataset.dataset_type_ref AS dataset_type_id, - metadata_type.name AS metadata_type, - dataset.metadata_type_ref AS metadata_type_id, - dataset.metadata AS metadata_doc, - agdc.common_timestamp((dataset.metadata #>> '{properties,odc:processing_datetime}'::text[])) AS creation_time, - (dataset.metadata #>> '{properties,odc:file_format}'::text[]) AS format, - (dataset.metadata #>> '{label}'::text[]) AS label, - ((dataset.metadata #>> '{properties,gqa:cep90}'::text[]))::double precision AS gqa, - agdc.float8range(((dataset.metadata #>> '{extent,lat,begin}'::text[]))::double precision, ((dataset.metadata #>> '{extent,lat,end}'::text[]))::double precision, '[]'::text) AS lat, - agdc.float8range(((dataset.metadata #>> '{extent,lon,begin}'::text[]))::double precision, ((dataset.metadata #>> '{extent,lon,end}'::text[]))::double precision, '[]'::text) AS lon, - tstzrange(LEAST(agdc.common_timestamp((dataset.metadata #>> '{properties,dtr:start_datetime}'::text[])), agdc.common_timestamp((dataset.metadata #>> '{properties,datetime}'::text[]))), GREATEST(agdc.common_timestamp((dataset.metadata #>> '{properties,dtr:end_datetime}'::text[])), agdc.common_timestamp((dataset.metadata #>> '{properties,datetime}'::text[]))), '[]'::text) AS "time", - ((dataset.metadata #>> '{properties,eo:gsd}'::text[]))::double precision AS eo_gsd, - (dataset.metadata #>> '{crs}'::text[]) AS crs_raw, - (dataset.metadata #>> '{properties,eo:platform}'::text[]) AS platform, - ((dataset.metadata #>> '{properties,gqa:abs_x}'::text[]))::double precision AS gqa_abs_x, - ((dataset.metadata #>> '{properties,gqa:abs_y}'::text[]))::double precision AS gqa_abs_y, - ((dataset.metadata #>> '{properties,gqa:cep90}'::text[]))::double precision AS gqa_cep90, - ((dataset.metadata #>> '{properties,fmask:snow}'::text[]))::double precision AS fmask_snow, - ((dataset.metadata #>> '{properties,gqa:abs_xy}'::text[]))::double precision AS gqa_abs_xy, - ((dataset.metadata #>> '{properties,gqa:mean_x}'::text[]))::double precision AS gqa_mean_x, - ((dataset.metadata #>> '{properties,gqa:mean_y}'::text[]))::double precision AS gqa_mean_y, - (dataset.metadata #>> '{properties,eo:instrument}'::text[]) AS instrument, - ((dataset.metadata #>> '{properties,eo:cloud_cover}'::text[]))::double precision AS cloud_cover, - ((dataset.metadata #>> '{properties,fmask:clear}'::text[]))::double precision AS fmask_clear, - ((dataset.metadata #>> '{properties,fmask:water}'::text[]))::double precision AS fmask_water, - ((dataset.metadata #>> '{properties,gqa:mean_xy}'::text[]))::double precision AS gqa_mean_xy, - (dataset.metadata #>> '{properties,odc:region_code}'::text[]) AS region_code, - ((dataset.metadata #>> '{properties,gqa:stddev_x}'::text[]))::double precision AS gqa_stddev_x, - ((dataset.metadata #>> '{properties,gqa:stddev_y}'::text[]))::double precision AS gqa_stddev_y, - ((dataset.metadata #>> '{properties,gqa:stddev_xy}'::text[]))::double precision AS gqa_stddev_xy, - ((dataset.metadata #>> '{properties,eo:sun_azimuth}'::text[]))::double precision AS eo_sun_azimuth, - (dataset.metadata #>> '{properties,odc:product_family}'::text[]) AS product_family, - (dataset.metadata #>> '{properties,dea:dataset_maturity}'::text[]) AS dataset_maturity, - ((dataset.metadata #>> '{properties,eo:sun_elevation}'::text[]))::double precision AS eo_sun_elevation, - (dataset.metadata #>> '{properties,landsat:landsat_scene_id}'::text[]) AS landsat_scene_id, - ((dataset.metadata #>> '{properties,fmask:cloud_shadow}'::text[]))::double precision AS fmask_cloud_shadow, - (dataset.metadata #>> '{properties,landsat:landsat_product_id}'::text[]) AS landsat_product_id, - ((dataset.metadata #>> '{properties,gqa:iterative_mean_x}'::text[]))::double precision AS gqa_iterative_mean_x, - ((dataset.metadata #>> '{properties,gqa:iterative_mean_y}'::text[]))::double precision AS gqa_iterative_mean_y, - ((dataset.metadata #>> '{properties,gqa:iterative_mean_xy}'::text[]))::double precision AS gqa_iterative_mean_xy, - ((dataset.metadata #>> '{properties,gqa:iterative_stddev_x}'::text[]))::double precision AS gqa_iterative_stddev_x, - ((dataset.metadata #>> '{properties,gqa:iterative_stddev_y}'::text[]))::double precision AS gqa_iterative_stddev_y, - ((dataset.metadata #>> '{properties,gqa:iterative_stddev_xy}'::text[]))::double precision AS gqa_iterative_stddev_xy, - ((dataset.metadata #>> '{properties,gqa:abs_iterative_mean_x}'::text[]))::double precision AS gqa_abs_iterative_mean_x, - ((dataset.metadata #>> '{properties,gqa:abs_iterative_mean_y}'::text[]))::double precision AS gqa_abs_iterative_mean_y, - ((dataset.metadata #>> '{properties,gqa:abs_iterative_mean_xy}'::text[]))::double precision AS gqa_abs_iterative_mean_xy - FROM ((agdc.dataset - JOIN agdc.dataset_type ON ((dataset_type.id = dataset.dataset_type_ref))) - JOIN agdc.metadata_type ON ((metadata_type.id = dataset_type.metadata_type_ref))) - WHERE ((dataset.archived IS NULL) AND (dataset.dataset_type_ref = 3)); - - -ALTER TABLE agdc.dv_ga_ls8c_ard_3_dataset OWNER TO odcuser; - --- --- Name: dv_ga_ls9c_ard_3_dataset; Type: VIEW; Schema: agdc; Owner: odcuser --- - -CREATE VIEW agdc.dv_ga_ls9c_ard_3_dataset AS - SELECT dataset.id, - dataset.added AS indexed_time, - dataset.added_by AS indexed_by, - dataset_type.name AS product, - dataset.dataset_type_ref AS dataset_type_id, - metadata_type.name AS metadata_type, - dataset.metadata_type_ref AS metadata_type_id, - dataset.metadata AS metadata_doc, - agdc.common_timestamp((dataset.metadata #>> '{properties,odc:processing_datetime}'::text[])) AS creation_time, - (dataset.metadata #>> '{properties,odc:file_format}'::text[]) AS format, - (dataset.metadata #>> '{label}'::text[]) AS label, - ((dataset.metadata #>> '{properties,gqa:cep90}'::text[]))::double precision AS gqa, - agdc.float8range(((dataset.metadata #>> '{extent,lat,begin}'::text[]))::double precision, ((dataset.metadata #>> '{extent,lat,end}'::text[]))::double precision, '[]'::text) AS lat, - agdc.float8range(((dataset.metadata #>> '{extent,lon,begin}'::text[]))::double precision, ((dataset.metadata #>> '{extent,lon,end}'::text[]))::double precision, '[]'::text) AS lon, - tstzrange(LEAST(agdc.common_timestamp((dataset.metadata #>> '{properties,dtr:start_datetime}'::text[])), agdc.common_timestamp((dataset.metadata #>> '{properties,datetime}'::text[]))), GREATEST(agdc.common_timestamp((dataset.metadata #>> '{properties,dtr:end_datetime}'::text[])), agdc.common_timestamp((dataset.metadata #>> '{properties,datetime}'::text[]))), '[]'::text) AS "time", - ((dataset.metadata #>> '{properties,eo:gsd}'::text[]))::double precision AS eo_gsd, - (dataset.metadata #>> '{crs}'::text[]) AS crs_raw, - (dataset.metadata #>> '{properties,eo:platform}'::text[]) AS platform, - ((dataset.metadata #>> '{properties,gqa:abs_x}'::text[]))::double precision AS gqa_abs_x, - ((dataset.metadata #>> '{properties,gqa:abs_y}'::text[]))::double precision AS gqa_abs_y, - ((dataset.metadata #>> '{properties,gqa:cep90}'::text[]))::double precision AS gqa_cep90, - ((dataset.metadata #>> '{properties,fmask:snow}'::text[]))::double precision AS fmask_snow, - ((dataset.metadata #>> '{properties,gqa:abs_xy}'::text[]))::double precision AS gqa_abs_xy, - ((dataset.metadata #>> '{properties,gqa:mean_x}'::text[]))::double precision AS gqa_mean_x, - ((dataset.metadata #>> '{properties,gqa:mean_y}'::text[]))::double precision AS gqa_mean_y, - (dataset.metadata #>> '{properties,eo:instrument}'::text[]) AS instrument, - ((dataset.metadata #>> '{properties,eo:cloud_cover}'::text[]))::double precision AS cloud_cover, - ((dataset.metadata #>> '{properties,fmask:clear}'::text[]))::double precision AS fmask_clear, - ((dataset.metadata #>> '{properties,fmask:water}'::text[]))::double precision AS fmask_water, - ((dataset.metadata #>> '{properties,gqa:mean_xy}'::text[]))::double precision AS gqa_mean_xy, - (dataset.metadata #>> '{properties,odc:region_code}'::text[]) AS region_code, - ((dataset.metadata #>> '{properties,gqa:stddev_x}'::text[]))::double precision AS gqa_stddev_x, - ((dataset.metadata #>> '{properties,gqa:stddev_y}'::text[]))::double precision AS gqa_stddev_y, - ((dataset.metadata #>> '{properties,gqa:stddev_xy}'::text[]))::double precision AS gqa_stddev_xy, - ((dataset.metadata #>> '{properties,eo:sun_azimuth}'::text[]))::double precision AS eo_sun_azimuth, - (dataset.metadata #>> '{properties,odc:product_family}'::text[]) AS product_family, - (dataset.metadata #>> '{properties,dea:dataset_maturity}'::text[]) AS dataset_maturity, - ((dataset.metadata #>> '{properties,eo:sun_elevation}'::text[]))::double precision AS eo_sun_elevation, - (dataset.metadata #>> '{properties,landsat:landsat_scene_id}'::text[]) AS landsat_scene_id, - ((dataset.metadata #>> '{properties,fmask:cloud_shadow}'::text[]))::double precision AS fmask_cloud_shadow, - (dataset.metadata #>> '{properties,landsat:landsat_product_id}'::text[]) AS landsat_product_id, - ((dataset.metadata #>> '{properties,gqa:iterative_mean_x}'::text[]))::double precision AS gqa_iterative_mean_x, - ((dataset.metadata #>> '{properties,gqa:iterative_mean_y}'::text[]))::double precision AS gqa_iterative_mean_y, - ((dataset.metadata #>> '{properties,gqa:iterative_mean_xy}'::text[]))::double precision AS gqa_iterative_mean_xy, - ((dataset.metadata #>> '{properties,gqa:iterative_stddev_x}'::text[]))::double precision AS gqa_iterative_stddev_x, - ((dataset.metadata #>> '{properties,gqa:iterative_stddev_y}'::text[]))::double precision AS gqa_iterative_stddev_y, - ((dataset.metadata #>> '{properties,gqa:iterative_stddev_xy}'::text[]))::double precision AS gqa_iterative_stddev_xy, - ((dataset.metadata #>> '{properties,gqa:abs_iterative_mean_x}'::text[]))::double precision AS gqa_abs_iterative_mean_x, - ((dataset.metadata #>> '{properties,gqa:abs_iterative_mean_y}'::text[]))::double precision AS gqa_abs_iterative_mean_y, - ((dataset.metadata #>> '{properties,gqa:abs_iterative_mean_xy}'::text[]))::double precision AS gqa_abs_iterative_mean_xy - FROM ((agdc.dataset - JOIN agdc.dataset_type ON ((dataset_type.id = dataset.dataset_type_ref))) - JOIN agdc.metadata_type ON ((metadata_type.id = dataset_type.metadata_type_ref))) - WHERE ((dataset.archived IS NULL) AND (dataset.dataset_type_ref = 4)); - - -ALTER TABLE agdc.dv_ga_ls9c_ard_3_dataset OWNER TO odcuser; - --- --- Name: dv_telemetry_dataset; Type: VIEW; Schema: agdc; Owner: odcuser --- - -CREATE VIEW agdc.dv_telemetry_dataset AS - SELECT dataset.id, - dataset.added AS indexed_time, - dataset.added_by AS indexed_by, - dataset_type.name AS product, - dataset.dataset_type_ref AS dataset_type_id, - metadata_type.name AS metadata_type, - dataset.metadata_type_ref AS metadata_type_id, - dataset.metadata AS metadata_doc, - agdc.common_timestamp((dataset.metadata #>> '{creation_dt}'::text[])) AS creation_time, - (dataset.metadata #>> '{format,name}'::text[]) AS format, - (dataset.metadata #>> '{ga_label}'::text[]) AS label, - (dataset.metadata #>> '{acquisition,groundstation,code}'::text[]) AS gsi, - tstzrange(agdc.common_timestamp((dataset.metadata #>> '{acquisition,aos}'::text[])), agdc.common_timestamp((dataset.metadata #>> '{acquisition,los}'::text[])), '[]'::text) AS "time", - ((dataset.metadata #>> '{acquisition,platform_orbit}'::text[]))::integer AS orbit, - numrange((((dataset.metadata #>> '{image,satellite_ref_point_start,y}'::text[]))::integer)::numeric, (GREATEST(((dataset.metadata #>> '{image,satellite_ref_point_end,y}'::text[]))::integer, ((dataset.metadata #>> '{image,satellite_ref_point_start,y}'::text[]))::integer))::numeric, '[]'::text) AS sat_row, - (dataset.metadata #>> '{platform,code}'::text[]) AS platform, - numrange((((dataset.metadata #>> '{image,satellite_ref_point_start,x}'::text[]))::integer)::numeric, (GREATEST(((dataset.metadata #>> '{image,satellite_ref_point_end,x}'::text[]))::integer, ((dataset.metadata #>> '{image,satellite_ref_point_start,x}'::text[]))::integer))::numeric, '[]'::text) AS sat_path, - (dataset.metadata #>> '{instrument,name}'::text[]) AS instrument, - (dataset.metadata #>> '{product_type}'::text[]) AS product_type - FROM ((agdc.dataset - JOIN agdc.dataset_type ON ((dataset_type.id = dataset.dataset_type_ref))) - JOIN agdc.metadata_type ON ((metadata_type.id = dataset_type.metadata_type_ref))) - WHERE ((dataset.archived IS NULL) AND (dataset.metadata_type_ref = 3)); - - -ALTER TABLE agdc.dv_telemetry_dataset OWNER TO odcuser; - --- --- Name: metadata_type_id_seq; Type: SEQUENCE; Schema: agdc; Owner: odcuser --- - -CREATE SEQUENCE agdc.metadata_type_id_seq - AS smallint - START WITH 1 - INCREMENT BY 1 - NO MINVALUE - NO MAXVALUE - CACHE 1; - - -ALTER TABLE agdc.metadata_type_id_seq OWNER TO odcuser; - --- --- Name: metadata_type_id_seq; Type: SEQUENCE OWNED BY; Schema: agdc; Owner: odcuser --- - -ALTER SEQUENCE agdc.metadata_type_id_seq OWNED BY agdc.metadata_type.id; - - --- --- Name: dataset_location id; Type: DEFAULT; Schema: agdc; Owner: odcuser --- - -ALTER TABLE ONLY agdc.dataset_location ALTER COLUMN id SET DEFAULT nextval('agdc.dataset_location_id_seq'::regclass); - - --- --- Name: dataset_type id; Type: DEFAULT; Schema: agdc; Owner: odcuser --- - -ALTER TABLE ONLY agdc.dataset_type ALTER COLUMN id SET DEFAULT nextval('agdc.dataset_type_id_seq'::regclass); - - --- --- Name: metadata_type id; Type: DEFAULT; Schema: agdc; Owner: odcuser --- - -ALTER TABLE ONLY agdc.metadata_type ALTER COLUMN id SET DEFAULT nextval('agdc.metadata_type_id_seq'::regclass); - - --- --- Data for Name: dataset; Type: TABLE DATA; Schema: agdc; Owner: odcuser --- - -COPY agdc.dataset (id, metadata_type_ref, dataset_type_ref, metadata, archived, added, added_by, updated) FROM stdin; -c68c7620-664b-45c3-8dea-d621ac9bb43e 4 1 {"id": "c68c7620-664b-45c3-8dea-d621ac9bb43e", "crs": "epsg:32656", "grids": {"default": {"shape": [7001, 7861], "transform": [30.0, 0.0, 266985.0, 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23:59:45.963319+00 localuser \N -2 600b1921-fff5-4092-a591-3659a419f342 s3 //dea-public-data/baseline/ga_ls5t_ard_3/089/083/1987/05/22/ga_ls5t_ard_3-0-0_089083_1987-05-22_final.stac-item.json 2022-09-08 23:59:45.994452+00 localuser \N -3 b139d78d-50ca-4bda-bc30-66da07f39ba9 s3 //dea-public-data/baseline/ga_ls5t_ard_3/089/083/1987/09/11/ga_ls5t_ard_3-0-0_089083_1987-09-11_final.stac-item.json 2022-09-08 23:59:46.010582+00 localuser \N -4 05bbcfe5-725c-4535-81c1-212f9ef9c46f s3 //dea-public-data/baseline/ga_ls5t_ard_3/089/083/1988/08/28/ga_ls5t_ard_3-0-0_089083_1988-08-28_final.stac-item.json 2022-09-08 23:59:46.025029+00 localuser \N -5 95e4e781-6490-407c-87f2-7f5505162b20 s3 //dea-public-data/baseline/ga_ls5t_ard_3/089/083/1989/05/27/ga_ls5t_ard_3-0-0_089083_1989-05-27_final.stac-item.json 2022-09-08 23:59:46.15548+00 localuser \N -6 9599989f-1be2-49ab-bce5-a2082693f8b2 s3 //dea-public-data/baseline/ga_ls5t_ard_3/089/083/1990/03/27/ga_ls5t_ard_3-0-0_089083_1990-03-27_final.stac-item.json 2022-09-08 23:59:46.16904+00 localuser \N -7 49e8e92a-e2f7-41fc-92b4-528a05c19255 s3 //dea-public-data/baseline/ga_ls5t_ard_3/089/083/1988/02/18/ga_ls5t_ard_3-0-0_089083_1988-02-18_final.stac-item.json 2022-09-08 23:59:46.181842+00 localuser \N -8 99e8e075-946e-41b2-9eed-48e809091c18 s3 //dea-public-data/baseline/ga_ls5t_ard_3/089/083/1989/07/30/ga_ls5t_ard_3-0-0_089083_1989-07-30_final.stac-item.json 2022-09-08 23:59:46.195299+00 localuser \N -9 64138754-1fd4-40a5-903e-250d1c22c8e1 s3 //dea-public-data/baseline/ga_ls5t_ard_3/089/083/1988/12/02/ga_ls5t_ard_3-0-0_089083_1988-12-02_final.stac-item.json 2022-09-08 23:59:46.208702+00 localuser \N -10 4dbe7c56-0adb-4ee4-b236-befdf6358901 s3 //dea-public-data/baseline/ga_ls5t_ard_3/089/083/1988/06/09/ga_ls5t_ard_3-0-0_089083_1988-06-09_final.stac-item.json 2022-09-08 23:59:46.224688+00 localuser \N -11 33042116-067a-4273-a38f-a58ec0b6b9fc s3 //dea-public-data/baseline/ga_ls5t_ard_3/089/083/1987/11/14/ga_ls5t_ard_3-0-0_089083_1987-11-14_final.stac-item.json 2022-09-08 23:59:46.352487+00 localuser \N -12 a77f4bb1-a401-44a2-a302-08512b19ccf0 s3 //dea-public-data/baseline/ga_ls5t_ard_3/089/083/1989/11/19/ga_ls5t_ard_3-0-0_089083_1989-11-19_final.stac-item.json 2022-09-08 23:59:46.367392+00 localuser \N -13 3108d555-2af6-491e-a5a6-8c0da87a2de9 s3 //dea-public-data/baseline/ga_ls5t_ard_3/089/083/1990/07/01/ga_ls5t_ard_3-0-0_089083_1990-07-01_final.stac-item.json 2022-09-08 23:59:46.380895+00 localuser \N -14 17bc2c65-a90f-436b-823b-48deecb7e55c s3 //dea-public-data/baseline/ga_ls5t_ard_3/089/083/1989/08/15/ga_ls5t_ard_3-0-0_089083_1989-08-15_final.stac-item.json 2022-09-08 23:59:46.393636+00 localuser \N -15 9bc8b3bc-facb-4079-bf72-1c454f5d52ce s3 //dea-public-data/baseline/ga_ls5t_ard_3/089/083/1989/01/19/ga_ls5t_ard_3-0-0_089083_1989-01-19_final.stac-item.json 2022-09-08 23:59:46.408111+00 localuser \N -16 6184c9b5-583a-4ad8-adee-02295e9f087b s3 //dea-public-data/baseline/ga_ls5t_ard_3/089/083/1988/06/25/ga_ls5t_ard_3-0-0_089083_1988-06-25_final.stac-item.json 2022-09-08 23:59:46.421792+00 localuser \N -17 3e7d2e53-a2ab-4639-997d-6ebf3c8e5f4e s3 //dea-public-data/baseline/ga_ls5t_ard_3/089/083/1987/11/30/ga_ls5t_ard_3-0-0_089083_1987-11-30_final.stac-item.json 2022-09-08 23:59:46.552111+00 localuser \N -18 c52c4142-9ba1-4626-ac8b-ebd88f04c196 s3 //dea-public-data/baseline/ga_ls5t_ard_3/089/083/1988/03/05/ga_ls5t_ard_3-0-0_089083_1988-03-05_final.stac-item.json 2022-09-08 23:59:46.565398+00 localuser \N -19 206751ce-b611-41dd-a747-30713c2663bd s3 //dea-public-data/baseline/ga_ls5t_ard_3/089/083/1990/09/03/ga_ls5t_ard_3-0-0_089083_1990-09-03_final.stac-item.json 2022-09-08 23:59:46.578543+00 localuser \N -20 0389c84f-81b8-4b5a-8697-e87f7d19458e s3 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//dea-public-data/baseline/ga_ls5t_ard_3/089/083/1988/09/29/ga_ls5t_ard_3-0-0_089083_1988-09-29_final.stac-item.json 2022-09-08 23:59:47.017266+00 localuser \N -35 c8d14ac7-1f0e-46da-bf5b-df97c6c21a53 s3 //dea-public-data/baseline/ga_ls5t_ard_3/089/083/1988/01/01/ga_ls5t_ard_3-0-0_089083_1988-01-01_final.stac-item.json 2022-09-08 23:59:47.030984+00 localuser \N -36 7803f87a-f93a-449b-9c0d-2664f81ae35f s3 //dea-public-data/baseline/ga_ls5t_ard_3/089/083/1989/06/28/ga_ls5t_ard_3-0-0_089083_1989-06-28_final.stac-item.json 2022-09-08 23:59:47.044962+00 localuser \N -37 2099af0f-4d7c-4d7c-9af1-7b3c6ceaba16 s3 //dea-public-data/baseline/ga_ls5t_ard_3/089/083/1990/05/30/ga_ls5t_ard_3-0-0_089083_1990-05-30_final.stac-item.json 2022-09-08 23:59:47.05945+00 localuser \N -38 e48888b6-0f6a-4d40-8d5d-1e1bb977fcc7 s3 //dea-public-data/baseline/ga_ls5t_ard_3/089/083/1990/02/23/ga_ls5t_ard_3-0-0_089083_1990-02-23_final.stac-item.json 2022-09-08 23:59:47.18639+00 localuser \N -39 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03:02:42.832618+00 odcuser \N -954 a9a00b5a-f763-4b43-9a9b-bc0c11237cb9 s3 //dea-public-data/baseline/ga_ls9c_ard_3/089/083/2022/06/15/ga_ls9c_ard_3-2-1_089083_2022-06-15_final.odc-metadata.yaml 2022-11-08 03:02:42.840536+00 odcuser \N -955 f615455c-5f45-4df6-97ea-40f0fe4f932b s3 //dea-public-data/baseline/ga_ls9c_ard_3/089/083/2022/08/18/ga_ls9c_ard_3-2-1_089083_2022-08-18_final.odc-metadata.yaml 2022-11-08 03:02:42.84829+00 odcuser \N -956 7cec40be-736d-4387-b3f6-5565f6cf57c6 s3 //dea-public-data/baseline/ga_ls9c_ard_3/089/083/2022/08/02/ga_ls9c_ard_3-2-1_089083_2022-08-02_final.odc-metadata.yaml 2022-11-08 03:02:42.85603+00 odcuser \N -957 0872a08c-b262-4104-8ffb-b5c197f98bf0 s3 //dea-public-data/baseline/ga_ls9c_ard_3/089/083/2022/10/05/ga_ls9c_ard_3-2-1_089083_2022-10-05_final.odc-metadata.yaml 2022-11-08 03:02:42.863896+00 odcuser \N -958 18c3d875-326a-4540-b04a-1faa56bca383 s3 //dea-public-data/baseline/ga_ls9c_ard_3/089/083/2022/09/19/ga_ls9c_ard_3-2-1_089083_2022-09-19_final.odc-metadata.yaml 2022-11-08 03:02:42.871617+00 odcuser \N -959 d26f05bb-6619-4cb3-94b0-37079412f687 s3 //dea-public-data/baseline/ga_ls9c_ard_3/089/083/2022/07/01/ga_ls9c_ard_3-2-1_089083_2022-07-01_final.odc-metadata.yaml 2022-11-08 03:02:42.87943+00 odcuser \N -960 0ddeb9c8-9d52-442a-8060-d0075f00fb1c s3 //dea-public-data/baseline/ga_ls9c_ard_3/089/083/2022/09/03/ga_ls9c_ard_3-2-1_089083_2022-09-03_final.odc-metadata.yaml 2022-11-08 03:02:42.887248+00 odcuser \N -961 f960765c-94e4-4f22-a647-12f60bebd96d s3 //dea-public-data/baseline/ga_ls9c_ard_3/089/083/2022/05/30/ga_ls9c_ard_3-2-1_089083_2022-05-30_final.odc-metadata.yaml 2022-11-08 03:02:42.895032+00 odcuser \N -962 e63c05be-04e7-44db-b1de-804c30695371 s3 //dea-public-data/baseline/ga_ls9c_ard_3/089/083/2022/03/11/ga_ls9c_ard_3-2-1_089083_2022-03-11_final.odc-metadata.yaml 2022-11-08 03:02:42.903197+00 odcuser \N -\. - - --- --- Data for Name: dataset_source; Type: TABLE DATA; Schema: agdc; Owner: odcuser --- - -COPY agdc.dataset_source (dataset_ref, classifier, source_dataset_ref) FROM stdin; -\. - - --- --- Data for Name: dataset_type; Type: TABLE DATA; Schema: agdc; Owner: odcuser --- - -COPY agdc.dataset_type (id, name, metadata, metadata_type_ref, definition, added, added_by, updated) FROM stdin; -1 ga_ls5t_ard_3 {"product": {"name": "ga_ls5t_ard_3"}, "properties": {"eo:platform": "landsat-5", "odc:producer": "ga.gov.au", "eo:instrument": "TM", "odc:product_family": "ard"}} 4 {"name": "ga_ls5t_ard_3", "license": "CC-BY-4.0", "metadata": {"product": {"name": "ga_ls5t_ard_3"}, "properties": {"eo:platform": "landsat-5", "odc:producer": "ga.gov.au", "eo:instrument": "TM", "odc:product_family": "ard"}}, "description": "Geoscience Australia Landsat 5 Thematic Mapper Analysis Ready Data Collection 3", "measurements": [{"name": "nbart_blue", "dtype": "int16", "units": "1", "nodata": -999, "aliases": ["nbart_band01", "blue"]}, {"name": "nbart_green", "dtype": "int16", "units": "1", "nodata": -999, "aliases": ["nbart_band02", "green"]}, {"name": "nbart_red", "dtype": "int16", "units": "1", "nodata": -999, "aliases": ["nbart_band03", "red"]}, {"name": "nbart_nir", "dtype": "int16", "units": "1", "nodata": -999, "aliases": ["nbart_band04", "nir"]}, {"name": "nbart_swir_1", "dtype": "int16", "units": "1", "nodata": -999, "aliases": ["nbart_band05", "swir_1", "swir1"]}, {"name": "nbart_swir_2", "dtype": "int16", "units": "1", "nodata": -999, "aliases": ["nbart_band07", "swir_2", "swir2"]}, {"name": "oa_fmask", "dtype": "uint8", "units": "1", "nodata": 0, "aliases": ["fmask"], "flags_definition": {"fmask": {"bits": [0, 1, 2, 3, 4, 5, 6, 7], "values": {"0": "nodata", "1": "valid", "2": "cloud", "3": "shadow", "4": "snow", "5": "water"}, "description": "Fmask"}}}, {"name": "oa_nbart_contiguity", "dtype": "uint8", "units": "1", "nodata": 255, "aliases": ["nbart_contiguity"], "flags_definition": {"contiguous": {"bits": [0], "values": {"0": false, "1": true}}}}, {"name": "oa_azimuthal_exiting", "dtype": "float32", "units": "1", "nodata": "NaN", "aliases": ["azimuthal_exiting"]}, {"name": "oa_azimuthal_incident", "dtype": "float32", "units": "1", "nodata": "NaN", "aliases": ["azimuthal_incident"]}, {"name": "oa_combined_terrain_shadow", "dtype": "uint8", "units": "1", "nodata": 255, "aliases": ["combined_terrain_shadow"]}, {"name": "oa_exiting_angle", "dtype": "float32", "units": "1", "nodata": "NaN", "aliases": ["exiting_angle"]}, {"name": "oa_incident_angle", "dtype": "float32", "units": "1", "nodata": "NaN", "aliases": ["incident_angle"]}, {"name": "oa_relative_azimuth", "dtype": "float32", "units": "1", "nodata": "NaN", "aliases": ["relative_azimuth"]}, {"name": "oa_relative_slope", "dtype": "float32", "units": "1", "nodata": "NaN", "aliases": ["relative_slope"]}, {"name": "oa_satellite_azimuth", "dtype": "float32", "units": "1", "nodata": "NaN", "aliases": ["satellite_azimuth"]}, {"name": "oa_satellite_view", "dtype": "float32", "units": "1", "nodata": "NaN", "aliases": ["satellite_view"]}, {"name": "oa_solar_azimuth", "dtype": "float32", "units": "1", "nodata": "NaN", "aliases": ["solar_azimuth"]}, {"name": "oa_solar_zenith", "dtype": "float32", "units": "1", "nodata": "NaN", "aliases": ["solar_zenith"]}, {"name": "oa_time_delta", "dtype": "float32", "units": "1", "nodata": "NaN", "aliases": ["time_delta"]}], "metadata_type": "eo3_landsat_ard"} 2022-09-08 23:59:29.76661+00 localuser \N -2 ga_ls7e_ard_3 {"product": {"name": "ga_ls7e_ard_3"}, "properties": {"eo:platform": "landsat-7", "odc:producer": "ga.gov.au", "eo:instrument": "ETM", "odc:product_family": "ard"}} 4 {"name": "ga_ls7e_ard_3", "license": "CC-BY-4.0", "metadata": {"product": {"name": "ga_ls7e_ard_3"}, "properties": {"eo:platform": "landsat-7", "odc:producer": "ga.gov.au", "eo:instrument": "ETM", "odc:product_family": "ard"}}, "description": "Geoscience Australia Landsat 7 Enhanced Thematic Mapper Plus Analysis Ready Data Collection 3", "measurements": [{"name": "nbart_blue", "dtype": "int16", "units": "1", "nodata": -999, "aliases": ["nbart_band01", "blue"]}, {"name": "nbart_green", "dtype": "int16", "units": "1", "nodata": -999, "aliases": ["nbart_band02", "green"]}, {"name": "nbart_red", "dtype": "int16", "units": "1", "nodata": -999, "aliases": ["nbart_band03", "red"]}, {"name": "nbart_nir", "dtype": "int16", "units": "1", "nodata": -999, "aliases": ["nbart_band04", "nir"]}, {"name": "nbart_swir_1", "dtype": "int16", "units": "1", "nodata": -999, "aliases": ["nbart_band05", "swir_1", "swir1"]}, {"name": "nbart_swir_2", "dtype": "int16", "units": "1", "nodata": -999, "aliases": ["nbart_band07", "swir_2", "swir2"]}, {"name": "nbart_panchromatic", "dtype": "int16", "units": "1", "nodata": -999, "aliases": ["nbart_band08", "panchromatic"]}, {"name": "oa_fmask", "dtype": "uint8", "units": "1", "nodata": 0, "aliases": ["fmask"], "flags_definition": {"fmask": {"bits": [0, 1, 2, 3, 4, 5, 6, 7], "values": {"0": "nodata", "1": "valid", "2": "cloud", "3": "shadow", "4": "snow", "5": "water"}, "description": "Fmask"}}}, {"name": "oa_nbart_contiguity", "dtype": "uint8", "units": "1", "nodata": 255, "aliases": ["nbart_contiguity"], "flags_definition": {"contiguous": {"bits": [0], "values": {"0": false, "1": true}}}}, {"name": "oa_azimuthal_exiting", "dtype": "float32", "units": "1", "nodata": "NaN", "aliases": ["azimuthal_exiting"]}, {"name": "oa_azimuthal_incident", "dtype": "float32", "units": "1", "nodata": "NaN", "aliases": ["azimuthal_incident"]}, {"name": "oa_combined_terrain_shadow", "dtype": "uint8", "units": "1", "nodata": 255, "aliases": ["combined_terrain_shadow"]}, {"name": "oa_exiting_angle", "dtype": "float32", "units": "1", "nodata": "NaN", "aliases": ["exiting_angle"]}, {"name": "oa_incident_angle", "dtype": "float32", "units": "1", "nodata": "NaN", "aliases": ["incident_angle"]}, {"name": "oa_relative_azimuth", "dtype": "float32", "units": "1", "nodata": "NaN", "aliases": ["relative_azimuth"]}, {"name": "oa_relative_slope", "dtype": "float32", "units": "1", "nodata": "NaN", "aliases": ["relative_slope"]}, {"name": "oa_satellite_azimuth", "dtype": "float32", "units": "1", "nodata": "NaN", "aliases": ["satellite_azimuth"]}, {"name": "oa_satellite_view", "dtype": "float32", "units": "1", "nodata": "NaN", "aliases": ["satellite_view"]}, {"name": "oa_solar_azimuth", "dtype": "float32", "units": "1", "nodata": "NaN", "aliases": ["solar_azimuth"]}, {"name": "oa_solar_zenith", "dtype": "float32", "units": "1", "nodata": "NaN", "aliases": ["solar_zenith"]}, {"name": "oa_time_delta", "dtype": "float32", "units": "1", "nodata": "NaN", "aliases": ["time_delta"]}], "metadata_type": "eo3_landsat_ard"} 2022-09-09 00:00:24.571791+00 localuser \N -3 ga_ls8c_ard_3 {"product": {"name": "ga_ls8c_ard_3"}, "properties": {"eo:platform": "landsat-8", "odc:producer": "ga.gov.au", "eo:instrument": "OLI_TIRS", "odc:product_family": "ard"}} 4 {"name": "ga_ls8c_ard_3", "license": "CC-BY-4.0", "metadata": {"product": {"name": "ga_ls8c_ard_3"}, "properties": {"eo:platform": "landsat-8", "odc:producer": "ga.gov.au", "eo:instrument": "OLI_TIRS", "odc:product_family": "ard"}}, "description": "Geoscience Australia Landsat 8 Operational Land Imager and Thermal Infra-Red Scanner Analysis Ready Data Collection 3", "measurements": [{"name": "nbart_coastal_aerosol", "dtype": "int16", "units": "1", "nodata": -999, "aliases": ["nbart_band01", "coastal_aerosol"]}, {"name": "nbart_blue", "dtype": "int16", "units": "1", "nodata": -999, "aliases": ["nbart_band02", "blue"]}, {"name": "nbart_green", "dtype": "int16", "units": "1", "nodata": -999, "aliases": ["nbart_band03", "green"]}, {"name": "nbart_red", "dtype": "int16", "units": "1", "nodata": -999, "aliases": ["nbart_band04", "red"]}, {"name": "nbart_nir", "dtype": "int16", "units": "1", "nodata": -999, "aliases": ["nbart_band05", "nir"]}, {"name": "nbart_swir_1", "dtype": "int16", "units": "1", "nodata": -999, "aliases": ["nbart_band06", "swir_1", "swir1"]}, {"name": "nbart_swir_2", "dtype": "int16", "units": "1", "nodata": -999, "aliases": ["nbart_band07", "swir_2", "swir2"]}, {"name": "nbart_panchromatic", "dtype": "int16", "units": "1", "nodata": -999, "aliases": ["nbart_band08", "panchromatic"]}, {"name": "oa_fmask", "dtype": "uint8", "units": "1", "nodata": 0, "aliases": ["fmask"], "flags_definition": {"fmask": {"bits": [0, 1, 2, 3, 4, 5, 6, 7], "values": {"0": "nodata", "1": "valid", "2": "cloud", "3": "shadow", "4": "snow", "5": "water"}, "description": "Fmask"}}}, {"name": "oa_nbart_contiguity", "dtype": "uint8", "units": "1", "nodata": 255, "aliases": ["nbart_contiguity"], "flags_definition": {"contiguous": {"bits": [0], "values": {"0": false, "1": true}}}}, {"name": "oa_azimuthal_exiting", "dtype": "float32", "units": "1", "nodata": "NaN", "aliases": ["azimuthal_exiting"]}, {"name": "oa_azimuthal_incident", "dtype": "float32", "units": "1", "nodata": "NaN", "aliases": ["azimuthal_incident"]}, {"name": "oa_combined_terrain_shadow", "dtype": "uint8", "units": "1", "nodata": 255, "aliases": ["combined_terrain_shadow"]}, {"name": "oa_exiting_angle", "dtype": "float32", "units": "1", "nodata": "NaN", "aliases": ["exiting_angle"]}, {"name": "oa_incident_angle", "dtype": "float32", "units": "1", "nodata": "NaN", "aliases": ["incident_angle"]}, {"name": "oa_relative_azimuth", "dtype": "float32", "units": "1", "nodata": "NaN", "aliases": ["relative_azimuth"]}, {"name": "oa_relative_slope", "dtype": "float32", "units": "1", "nodata": "NaN", "aliases": ["relative_slope"]}, {"name": "oa_satellite_azimuth", "dtype": "float32", "units": "1", "nodata": "NaN", "aliases": ["satellite_azimuth"]}, {"name": "oa_satellite_view", "dtype": "float32", "units": "1", "nodata": "NaN", "aliases": ["satellite_view"]}, {"name": "oa_solar_azimuth", "dtype": "float32", "units": "1", "nodata": "NaN", "aliases": ["solar_azimuth"]}, {"name": "oa_solar_zenith", "dtype": "float32", "units": "1", "nodata": "NaN", "aliases": ["solar_zenith"]}, {"name": "oa_time_delta", "dtype": "float32", "units": "1", "nodata": "NaN", "aliases": ["time_delta"]}], "metadata_type": "eo3_landsat_ard"} 2022-09-09 00:00:55.740252+00 localuser \N -4 ga_ls9c_ard_3 {"product": {"name": "ga_ls9c_ard_3"}, "properties": {"eo:platform": "landsat-9", "odc:producer": "ga.gov.au", "eo:instrument": "OLI_TIRS", "odc:product_family": "ard"}} 4 {"name": "ga_ls9c_ard_3", "license": "CC-BY-4.0", "metadata": {"product": {"name": "ga_ls9c_ard_3"}, "properties": {"eo:platform": "landsat-9", "odc:producer": "ga.gov.au", "eo:instrument": "OLI_TIRS", "odc:product_family": "ard"}}, "description": "Geoscience Australia Landsat 9 Operational Land Imager and Thermal Infra-Red Scanner Analysis Ready Data Collection 3", "measurements": [{"name": "nbart_coastal_aerosol", "dtype": "int16", "units": "1", "nodata": -999, "aliases": ["nbart_band01", "coastal_aerosol"]}, {"name": "nbart_blue", "dtype": "int16", "units": "1", "nodata": -999, "aliases": ["nbart_band02", "blue"]}, {"name": "nbart_green", "dtype": "int16", "units": "1", "nodata": -999, "aliases": ["nbart_band03", "green"]}, {"name": "nbart_red", "dtype": "int16", "units": "1", "nodata": -999, "aliases": ["nbart_band04", "red"]}, {"name": "nbart_nir", "dtype": "int16", "units": "1", "nodata": -999, "aliases": ["nbart_band05", "nir"]}, {"name": "nbart_swir_1", "dtype": "int16", "units": "1", "nodata": -999, "aliases": ["nbart_band06", "swir_1", "swir1"]}, {"name": "nbart_swir_2", "dtype": "int16", "units": "1", "nodata": -999, "aliases": ["nbart_band07", "swir_2", "swir2"]}, {"name": "nbart_panchromatic", "dtype": "int16", "units": "1", "nodata": -999, "aliases": ["nbart_band08", "panchromatic"]}, {"name": "oa_fmask", "dtype": "uint8", "units": "1", "nodata": 0, "aliases": ["fmask"], "flags_definition": {"fmask": {"bits": [0, 1, 2, 3, 4, 5, 6, 7], "values": {"0": "nodata", "1": "valid", "2": "cloud", "3": "shadow", "4": "snow", "5": "water"}, "description": "Fmask"}}}, {"name": "oa_nbart_contiguity", "dtype": "uint8", "units": "1", "nodata": 255, "aliases": ["nbart_contiguity"], "flags_definition": {"contiguous": {"bits": [0], "values": {"0": false, "1": true}}}}, {"name": "oa_azimuthal_exiting", "dtype": "float32", "units": "1", "nodata": "NaN", "aliases": ["azimuthal_exiting"]}, {"name": "oa_azimuthal_incident", "dtype": "float32", "units": "1", "nodata": "NaN", "aliases": ["azimuthal_incident"]}, {"name": "oa_combined_terrain_shadow", "dtype": "uint8", "units": "1", "nodata": 255, "aliases": ["combined_terrain_shadow"]}, {"name": "oa_exiting_angle", "dtype": "float32", "units": "1", "nodata": "NaN", "aliases": ["exiting_angle"]}, {"name": "oa_incident_angle", "dtype": "float32", "units": "1", "nodata": "NaN", "aliases": ["incident_angle"]}, {"name": "oa_relative_azimuth", "dtype": "float32", "units": "1", "nodata": "NaN", "aliases": ["relative_azimuth"]}, {"name": "oa_relative_slope", "dtype": "float32", "units": "1", "nodata": "NaN", "aliases": ["relative_slope"]}, {"name": "oa_satellite_azimuth", "dtype": "float32", "units": "1", "nodata": "NaN", "aliases": ["satellite_azimuth"]}, {"name": "oa_satellite_view", "dtype": "float32", "units": "1", "nodata": "NaN", "aliases": ["satellite_view"]}, {"name": "oa_solar_azimuth", "dtype": "float32", "units": "1", "nodata": "NaN", "aliases": ["solar_azimuth"]}, {"name": "oa_solar_zenith", "dtype": "float32", "units": "1", "nodata": "NaN", "aliases": ["solar_zenith"]}, {"name": "oa_time_delta", "dtype": "float32", "units": "1", "nodata": "NaN", "aliases": ["time_delta"]}], "metadata_type": "eo3_landsat_ard"} 2022-11-08 02:58:14.43762+00 odcuser \N -\. - - --- --- Data for Name: metadata_type; Type: TABLE DATA; Schema: agdc; Owner: odcuser --- - -COPY agdc.metadata_type (id, name, definition, added, added_by, updated) FROM stdin; -1 eo3 {"name": "eo3", "dataset": {"id": ["id"], "label": ["label"], "format": ["properties", "odc:file_format"], "sources": ["lineage", "source_datasets"], "creation_dt": ["properties", "odc:processing_datetime"], "grid_spatial": ["grid_spatial", "projection"], "measurements": ["measurements"], "search_fields": {"lat": {"type": "double-range", "max_offset": [["extent", "lat", "end"]], "min_offset": [["extent", "lat", "begin"]], "description": "Latitude range"}, "lon": {"type": "double-range", "max_offset": [["extent", "lon", "end"]], "min_offset": [["extent", "lon", "begin"]], "description": "Longitude range"}, "time": {"type": "datetime-range", "max_offset": [["properties", "dtr:end_datetime"], ["properties", "datetime"]], "min_offset": [["properties", "dtr:start_datetime"], ["properties", "datetime"]], "description": "Acquisition time range"}, "platform": {"offset": ["properties", "eo:platform"], "indexed": false, "description": "Platform code"}, "instrument": {"offset": ["properties", "eo:instrument"], "indexed": false, "description": "Instrument name"}, "cloud_cover": {"type": "double", "offset": ["properties", "eo:cloud_cover"], "indexed": false, "description": "Cloud cover percentage [0, 100]"}, "region_code": {"offset": ["properties", "odc:region_code"], "description": "Spatial reference code from the provider. For Landsat region_code is a scene path row:\\n '{:03d}{:03d}.format(path,row)'.\\nFor Sentinel it is MGRS code. In general it is a unique string identifier that datasets covering roughly the same spatial region share.\\n"}, "product_family": {"offset": ["properties", "odc:product_family"], "indexed": false, "description": "Product family code"}, "dataset_maturity": {"offset": ["properties", "dea:dataset_maturity"], "indexed": false, "description": "One of - final|interim|nrt (near real time)"}}}, "description": "Default EO3 with no custom fields"} 2022-09-08 23:57:27.934903+00 localuser \N -2 eo {"name": "eo", "dataset": {"id": ["id"], "label": ["ga_label"], "format": ["format", "name"], "sources": ["lineage", "source_datasets"], "creation_dt": ["creation_dt"], "grid_spatial": ["grid_spatial", "projection"], "measurements": ["image", "bands"], "search_fields": {"lat": {"type": "double-range", "max_offset": [["extent", "coord", "ur", "lat"], ["extent", "coord", "lr", "lat"], ["extent", "coord", "ul", "lat"], ["extent", "coord", "ll", "lat"]], "min_offset": [["extent", "coord", "ur", "lat"], ["extent", "coord", "lr", "lat"], ["extent", "coord", "ul", "lat"], ["extent", "coord", "ll", "lat"]], "description": "Latitude range"}, "lon": {"type": "double-range", "max_offset": [["extent", "coord", "ul", "lon"], ["extent", "coord", "ur", "lon"], ["extent", "coord", "ll", "lon"], ["extent", "coord", "lr", "lon"]], "min_offset": [["extent", "coord", "ul", "lon"], ["extent", "coord", "ur", "lon"], ["extent", "coord", "ll", "lon"], ["extent", "coord", "lr", "lon"]], "description": "Longitude range"}, "time": {"type": "datetime-range", "max_offset": [["extent", "to_dt"], ["extent", "center_dt"]], "min_offset": [["extent", "from_dt"], ["extent", "center_dt"]], "description": "Acquisition time"}, "platform": {"offset": ["platform", "code"], "description": "Platform code"}, "instrument": {"offset": ["instrument", "name"], "description": "Instrument name"}, "product_type": {"offset": ["product_type"], "description": "Product code"}}}, "description": "Earth Observation datasets.\\n\\nExpected metadata structure produced by the eodatasets library, as used internally at GA.\\n\\nhttps://github.com/GeoscienceAustralia/eo-datasets\\n"} 2022-09-08 23:57:27.967731+00 localuser \N -3 telemetry {"name": "telemetry", "dataset": {"id": ["id"], "label": ["ga_label"], "sources": ["lineage", "source_datasets"], "creation_dt": ["creation_dt"], "search_fields": {"gsi": {"offset": ["acquisition", "groundstation", "code"], "indexed": false, "description": "Ground Station Identifier (eg. ASA)"}, "time": {"type": "datetime-range", "max_offset": [["acquisition", "los"]], "min_offset": [["acquisition", "aos"]], "description": "Acquisition time"}, "orbit": {"type": "integer", "offset": ["acquisition", "platform_orbit"], "description": "Orbit number"}, "sat_row": {"type": "integer-range", "max_offset": [["image", "satellite_ref_point_end", "y"], ["image", "satellite_ref_point_start", "y"]], "min_offset": [["image", "satellite_ref_point_start", "y"]], "description": "Landsat row"}, "platform": {"offset": ["platform", "code"], "description": "Platform code"}, "sat_path": {"type": "integer-range", "max_offset": [["image", "satellite_ref_point_end", "x"], ["image", "satellite_ref_point_start", "x"]], "min_offset": [["image", "satellite_ref_point_start", "x"]], "description": "Landsat path"}, "instrument": {"offset": ["instrument", "name"], "description": "Instrument name"}, "product_type": {"offset": ["product_type"], "description": "Product code"}}}, "description": "Satellite telemetry datasets.\\n\\nExpected metadata structure produced by telemetry datasets from the eodatasets library, as used internally at GA.\\n\\nhttps://github.com/GeoscienceAustralia/eo-datasets\\n"} 2022-09-08 23:57:27.997407+00 localuser \N -4 eo3_landsat_ard {"name": "eo3_landsat_ard", "dataset": {"id": ["id"], "label": ["label"], "format": ["properties", "odc:file_format"], "sources": ["lineage", "source_datasets"], "creation_dt": ["properties", "odc:processing_datetime"], "grid_spatial": ["grid_spatial", "projection"], "measurements": ["measurements"], "search_fields": {"gqa": {"type": "double", "offset": ["properties", "gqa:cep90"], "description": "GQA Circular error probable (90%)"}, "lat": {"type": "double-range", "max_offset": [["extent", "lat", "end"]], "min_offset": [["extent", "lat", "begin"]], "description": "Latitude range"}, "lon": {"type": "double-range", "max_offset": [["extent", "lon", "end"]], "min_offset": [["extent", "lon", "begin"]], "description": "Longitude range"}, "time": {"type": "datetime-range", "max_offset": [["properties", "dtr:end_datetime"], ["properties", "datetime"]], "min_offset": [["properties", "dtr:start_datetime"], ["properties", "datetime"]], "description": "Acquisition time range"}, "eo_gsd": {"type": "double", "offset": ["properties", "eo:gsd"], "indexed": false, "description": "Ground sample distance, meters"}, "crs_raw": {"offset": ["crs"], "indexed": false, "description": "The raw CRS string as it appears in metadata"}, "platform": {"offset": ["properties", "eo:platform"], "indexed": false, "description": "Platform code"}, "gqa_abs_x": {"type": "double", "offset": ["properties", "gqa:abs_x"], "indexed": false, "description": "TODO: "}, "gqa_abs_y": {"type": "double", "offset": ["properties", "gqa:abs_y"], "indexed": false, "description": "TODO: "}, "gqa_cep90": {"type": "double", "offset": ["properties", "gqa:cep90"], "indexed": false, "description": "TODO: "}, "fmask_snow": {"type": "double", "offset": ["properties", "fmask:snow"], "indexed": false, "description": "TODO: "}, "gqa_abs_xy": {"type": "double", "offset": ["properties", "gqa:abs_xy"], "indexed": false, "description": "TODO: "}, "gqa_mean_x": {"type": "double", "offset": ["properties", "gqa:mean_x"], "indexed": false, "description": "TODO: "}, "gqa_mean_y": {"type": "double", "offset": ["properties", "gqa:mean_y"], "indexed": false, "description": "TODO: "}, "instrument": {"offset": ["properties", "eo:instrument"], "indexed": false, "description": "Instrument name"}, "cloud_cover": {"type": "double", "offset": ["properties", "eo:cloud_cover"], "description": "Cloud cover percentage [0, 100]"}, "fmask_clear": {"type": "double", "offset": ["properties", "fmask:clear"], "indexed": false, "description": "TODO: "}, "fmask_water": {"type": "double", "offset": ["properties", "fmask:water"], "indexed": false, "description": "TODO: "}, "gqa_mean_xy": {"type": "double", "offset": ["properties", "gqa:mean_xy"], "indexed": false, "description": "TODO: "}, "region_code": {"offset": ["properties", "odc:region_code"], "description": "Spatial reference code from the provider. For Landsat region_code is a scene path row:\\n '{:03d}{:03d}.format(path,row)'\\nFor Sentinel it is MGRS code. In general it is a unique string identifier that datasets covering roughly the same spatial region share.\\n"}, "gqa_stddev_x": {"type": "double", "offset": ["properties", "gqa:stddev_x"], "indexed": false, "description": "TODO: "}, "gqa_stddev_y": {"type": "double", "offset": ["properties", "gqa:stddev_y"], "indexed": false, "description": "TODO: "}, "gqa_stddev_xy": {"type": "double", "offset": ["properties", "gqa:stddev_xy"], "indexed": false, "description": "TODO: "}, "eo_sun_azimuth": {"type": "double", "offset": ["properties", "eo:sun_azimuth"], "indexed": false, "description": "TODO: "}, "product_family": {"offset": ["properties", "odc:product_family"], "indexed": false, "description": "Product family code"}, "dataset_maturity": {"offset": ["properties", "dea:dataset_maturity"], "description": "One of - final|interim|nrt (near real time)"}, "eo_sun_elevation": {"type": "double", "offset": ["properties", "eo:sun_elevation"], "indexed": false, "description": "TODO: "}, "landsat_scene_id": {"offset": ["properties", "landsat:landsat_scene_id"], "indexed": false, "description": "Landsat Scene ID"}, "fmask_cloud_shadow": {"type": "double", "offset": ["properties", "fmask:cloud_shadow"], "indexed": false, "description": "TODO: "}, "landsat_product_id": {"offset": ["properties", "landsat:landsat_product_id"], "indexed": false, "description": "Landsat Product ID"}, "gqa_iterative_mean_x": {"type": "double", "offset": ["properties", "gqa:iterative_mean_x"], "indexed": false, "description": "TODO: "}, "gqa_iterative_mean_y": {"type": "double", "offset": ["properties", "gqa:iterative_mean_y"], "indexed": false, "description": "TODO: "}, "gqa_iterative_mean_xy": {"type": "double", "offset": ["properties", "gqa:iterative_mean_xy"], "indexed": false, "description": "TODO: "}, "gqa_iterative_stddev_x": {"type": "double", "offset": ["properties", "gqa:iterative_stddev_x"], "indexed": false, "description": "TODO: "}, "gqa_iterative_stddev_y": {"type": "double", "offset": ["properties", "gqa:iterative_stddev_y"], "indexed": false, "description": "TODO: "}, "gqa_iterative_stddev_xy": {"type": "double", "offset": ["properties", "gqa:iterative_stddev_xy"], "indexed": false, "description": "TODO: "}, "gqa_abs_iterative_mean_x": {"type": "double", "offset": ["properties", "gqa:abs_iterative_mean_x"], "indexed": false, "description": "TODO: "}, "gqa_abs_iterative_mean_y": {"type": "double", "offset": ["properties", "gqa:abs_iterative_mean_y"], "indexed": false, "description": "TODO: "}, "gqa_abs_iterative_mean_xy": {"type": "double", "offset": ["properties", "gqa:abs_iterative_mean_xy"], "indexed": false, "description": "TODO: "}}}, "description": "EO3 for ARD Landsat Collection 3"} 2022-09-08 23:59:27.2657+00 localuser \N -\. - - --- --- Data for Name: job; Type: TABLE DATA; Schema: cron; Owner: postgres --- - -COPY cron.job (jobid, schedule, command, nodename, nodeport, database, username, active, jobname) FROM stdin; -\. - - --- --- Data for Name: job_run_details; Type: TABLE DATA; Schema: cron; Owner: postgres --- - -COPY cron.job_run_details (jobid, runid, job_pid, database, username, command, status, return_message, start_time, end_time) FROM stdin; -\. - - --- --- Data for Name: spatial_ref_sys; Type: TABLE DATA; Schema: public; Owner: postgres --- - -COPY public.spatial_ref_sys (srid, auth_name, auth_srid, srtext, proj4text) FROM stdin; -\. - - --- --- Data for Name: geocode_settings; Type: TABLE DATA; Schema: tiger; Owner: odcuser --- - -COPY tiger.geocode_settings (name, setting, unit, category, short_desc) FROM stdin; -\. - - --- --- Data for Name: pagc_gaz; Type: TABLE DATA; Schema: tiger; Owner: odcuser --- - -COPY tiger.pagc_gaz (id, seq, word, stdword, token, is_custom) FROM stdin; -\. - - --- --- Data for Name: pagc_lex; Type: TABLE DATA; Schema: tiger; Owner: odcuser --- - -COPY tiger.pagc_lex (id, seq, word, stdword, token, is_custom) FROM stdin; -\. - - --- --- Data for Name: pagc_rules; Type: TABLE DATA; Schema: tiger; Owner: odcuser --- - -COPY tiger.pagc_rules (id, rule, is_custom) FROM stdin; -\. - - --- --- Data for Name: topology; Type: TABLE DATA; Schema: topology; Owner: postgres --- - -COPY topology.topology (id, name, srid, "precision", hasz) FROM stdin; -\. - - --- --- Data for Name: layer; Type: TABLE DATA; Schema: topology; Owner: postgres --- - -COPY topology.layer (topology_id, layer_id, schema_name, table_name, feature_column, feature_type, level, child_id) FROM stdin; -\. - - --- --- Name: dataset_location_id_seq; Type: SEQUENCE SET; Schema: agdc; Owner: odcuser --- - -SELECT pg_catalog.setval('agdc.dataset_location_id_seq', 962, true); - - --- --- Name: dataset_type_id_seq; Type: SEQUENCE SET; Schema: agdc; Owner: odcuser --- - -SELECT pg_catalog.setval('agdc.dataset_type_id_seq', 4, true); - - --- --- Name: metadata_type_id_seq; Type: SEQUENCE SET; Schema: agdc; Owner: odcuser --- - -SELECT pg_catalog.setval('agdc.metadata_type_id_seq', 4, true); - - --- --- Name: jobid_seq; Type: SEQUENCE SET; Schema: cron; Owner: postgres --- - -SELECT pg_catalog.setval('cron.jobid_seq', 1, false); - - --- --- Name: runid_seq; Type: SEQUENCE SET; Schema: cron; Owner: postgres --- - -SELECT pg_catalog.setval('cron.runid_seq', 1, false); - - --- --- Name: dataset pk_dataset; Type: CONSTRAINT; Schema: agdc; Owner: odcuser --- - -ALTER TABLE ONLY agdc.dataset - ADD CONSTRAINT pk_dataset PRIMARY KEY (id); - - --- --- Name: dataset_location pk_dataset_location; Type: CONSTRAINT; Schema: agdc; Owner: odcuser --- - -ALTER TABLE ONLY agdc.dataset_location - ADD CONSTRAINT pk_dataset_location PRIMARY KEY (id); - - --- --- Name: dataset_source pk_dataset_source; Type: CONSTRAINT; Schema: agdc; Owner: odcuser --- - -ALTER TABLE ONLY agdc.dataset_source - ADD CONSTRAINT pk_dataset_source PRIMARY KEY (dataset_ref, classifier); - - --- --- Name: dataset_type pk_dataset_type; Type: CONSTRAINT; Schema: agdc; Owner: odcuser --- - -ALTER TABLE ONLY agdc.dataset_type - ADD CONSTRAINT pk_dataset_type PRIMARY KEY (id); - - --- --- Name: metadata_type pk_metadata_type; Type: CONSTRAINT; Schema: agdc; Owner: odcuser --- - -ALTER TABLE ONLY agdc.metadata_type - ADD CONSTRAINT pk_metadata_type PRIMARY KEY (id); - - --- --- Name: dataset_location uq_dataset_location_uri_scheme; Type: CONSTRAINT; Schema: agdc; Owner: odcuser --- - -ALTER TABLE ONLY agdc.dataset_location - ADD CONSTRAINT uq_dataset_location_uri_scheme UNIQUE (uri_scheme, uri_body, dataset_ref); - - --- --- Name: dataset_source uq_dataset_source_source_dataset_ref; Type: CONSTRAINT; Schema: agdc; Owner: odcuser --- - -ALTER TABLE ONLY agdc.dataset_source - ADD CONSTRAINT uq_dataset_source_source_dataset_ref UNIQUE (source_dataset_ref, dataset_ref); - - --- --- Name: dataset_type uq_dataset_type_name; Type: CONSTRAINT; Schema: agdc; Owner: odcuser --- - -ALTER TABLE ONLY agdc.dataset_type - ADD CONSTRAINT uq_dataset_type_name UNIQUE (name); - - --- --- Name: metadata_type uq_metadata_type_name; Type: CONSTRAINT; Schema: agdc; Owner: odcuser --- - -ALTER TABLE ONLY agdc.metadata_type - ADD CONSTRAINT uq_metadata_type_name UNIQUE (name); - - --- --- Name: dix_ga_ls5t_ard_3_cloud_cover; Type: INDEX; Schema: agdc; Owner: odcuser --- - -CREATE INDEX dix_ga_ls5t_ard_3_cloud_cover ON agdc.dataset USING btree ((((metadata #>> '{properties,eo:cloud_cover}'::text[]))::double precision)) WHERE ((archived IS NULL) AND (dataset_type_ref = 1)); - - --- --- Name: dix_ga_ls5t_ard_3_dataset_maturity; Type: INDEX; Schema: agdc; Owner: odcuser --- - -CREATE INDEX dix_ga_ls5t_ard_3_dataset_maturity ON agdc.dataset USING btree (((metadata #>> '{properties,dea:dataset_maturity}'::text[]))) WHERE ((archived IS NULL) AND (dataset_type_ref = 1)); - - --- --- Name: dix_ga_ls5t_ard_3_gqa; Type: INDEX; Schema: agdc; Owner: odcuser --- - -CREATE INDEX dix_ga_ls5t_ard_3_gqa ON agdc.dataset USING btree ((((metadata #>> '{properties,gqa:cep90}'::text[]))::double precision)) WHERE ((archived IS NULL) AND (dataset_type_ref = 1)); - - --- --- Name: dix_ga_ls5t_ard_3_lat_lon_time; Type: INDEX; Schema: agdc; Owner: odcuser --- - -CREATE INDEX dix_ga_ls5t_ard_3_lat_lon_time ON agdc.dataset USING gist (agdc.float8range(((metadata #>> '{extent,lat,begin}'::text[]))::double precision, ((metadata #>> '{extent,lat,end}'::text[]))::double precision, '[]'::text), agdc.float8range(((metadata #>> '{extent,lon,begin}'::text[]))::double precision, ((metadata #>> '{extent,lon,end}'::text[]))::double precision, '[]'::text), tstzrange(LEAST(agdc.common_timestamp((metadata #>> '{properties,dtr:start_datetime}'::text[])), agdc.common_timestamp((metadata #>> '{properties,datetime}'::text[]))), GREATEST(agdc.common_timestamp((metadata #>> '{properties,dtr:end_datetime}'::text[])), agdc.common_timestamp((metadata #>> '{properties,datetime}'::text[]))), '[]'::text)) WHERE ((archived IS NULL) AND (dataset_type_ref = 1)); - - --- --- Name: dix_ga_ls5t_ard_3_region_code; Type: INDEX; Schema: agdc; Owner: odcuser --- - -CREATE INDEX dix_ga_ls5t_ard_3_region_code ON agdc.dataset USING btree (((metadata #>> '{properties,odc:region_code}'::text[]))) WHERE ((archived IS NULL) AND (dataset_type_ref = 1)); - - --- --- Name: dix_ga_ls5t_ard_3_time_lat_lon; Type: INDEX; Schema: agdc; Owner: odcuser --- - -CREATE INDEX dix_ga_ls5t_ard_3_time_lat_lon ON agdc.dataset USING gist (tstzrange(LEAST(agdc.common_timestamp((metadata #>> '{properties,dtr:start_datetime}'::text[])), agdc.common_timestamp((metadata #>> '{properties,datetime}'::text[]))), GREATEST(agdc.common_timestamp((metadata #>> '{properties,dtr:end_datetime}'::text[])), agdc.common_timestamp((metadata #>> '{properties,datetime}'::text[]))), '[]'::text), agdc.float8range(((metadata #>> '{extent,lat,begin}'::text[]))::double precision, ((metadata #>> '{extent,lat,end}'::text[]))::double precision, '[]'::text), agdc.float8range(((metadata #>> '{extent,lon,begin}'::text[]))::double precision, ((metadata #>> '{extent,lon,end}'::text[]))::double precision, '[]'::text)) WHERE ((archived IS NULL) AND (dataset_type_ref = 1)); - - --- --- Name: dix_ga_ls7e_ard_3_cloud_cover; Type: INDEX; Schema: agdc; Owner: odcuser --- - -CREATE INDEX dix_ga_ls7e_ard_3_cloud_cover ON agdc.dataset USING btree ((((metadata #>> '{properties,eo:cloud_cover}'::text[]))::double precision)) WHERE ((archived IS NULL) AND (dataset_type_ref = 2)); - - --- --- Name: dix_ga_ls7e_ard_3_dataset_maturity; Type: INDEX; Schema: agdc; Owner: odcuser --- - -CREATE INDEX dix_ga_ls7e_ard_3_dataset_maturity ON agdc.dataset USING btree (((metadata #>> '{properties,dea:dataset_maturity}'::text[]))) WHERE ((archived IS NULL) AND (dataset_type_ref = 2)); - - --- --- Name: dix_ga_ls7e_ard_3_gqa; Type: INDEX; Schema: agdc; Owner: odcuser --- - -CREATE INDEX dix_ga_ls7e_ard_3_gqa ON agdc.dataset USING btree ((((metadata #>> '{properties,gqa:cep90}'::text[]))::double precision)) WHERE ((archived IS NULL) AND (dataset_type_ref = 2)); - - --- --- Name: dix_ga_ls7e_ard_3_lat_lon_time; Type: INDEX; Schema: agdc; Owner: odcuser --- - -CREATE INDEX dix_ga_ls7e_ard_3_lat_lon_time ON agdc.dataset USING gist (agdc.float8range(((metadata #>> '{extent,lat,begin}'::text[]))::double precision, ((metadata #>> '{extent,lat,end}'::text[]))::double precision, '[]'::text), agdc.float8range(((metadata #>> '{extent,lon,begin}'::text[]))::double precision, ((metadata #>> '{extent,lon,end}'::text[]))::double precision, '[]'::text), tstzrange(LEAST(agdc.common_timestamp((metadata #>> '{properties,dtr:start_datetime}'::text[])), agdc.common_timestamp((metadata #>> '{properties,datetime}'::text[]))), GREATEST(agdc.common_timestamp((metadata #>> '{properties,dtr:end_datetime}'::text[])), agdc.common_timestamp((metadata #>> '{properties,datetime}'::text[]))), '[]'::text)) WHERE ((archived IS NULL) AND (dataset_type_ref = 2)); - - --- --- Name: dix_ga_ls7e_ard_3_region_code; Type: INDEX; Schema: agdc; Owner: odcuser --- - -CREATE INDEX dix_ga_ls7e_ard_3_region_code ON agdc.dataset USING btree (((metadata #>> '{properties,odc:region_code}'::text[]))) WHERE ((archived IS NULL) AND (dataset_type_ref = 2)); - - --- --- Name: dix_ga_ls7e_ard_3_time_lat_lon; Type: INDEX; Schema: agdc; Owner: odcuser --- - -CREATE INDEX dix_ga_ls7e_ard_3_time_lat_lon ON agdc.dataset USING gist (tstzrange(LEAST(agdc.common_timestamp((metadata #>> '{properties,dtr:start_datetime}'::text[])), agdc.common_timestamp((metadata #>> '{properties,datetime}'::text[]))), GREATEST(agdc.common_timestamp((metadata #>> '{properties,dtr:end_datetime}'::text[])), agdc.common_timestamp((metadata #>> '{properties,datetime}'::text[]))), '[]'::text), agdc.float8range(((metadata #>> '{extent,lat,begin}'::text[]))::double precision, ((metadata #>> '{extent,lat,end}'::text[]))::double precision, '[]'::text), agdc.float8range(((metadata #>> '{extent,lon,begin}'::text[]))::double precision, ((metadata #>> '{extent,lon,end}'::text[]))::double precision, '[]'::text)) WHERE ((archived IS NULL) AND (dataset_type_ref = 2)); - - --- --- Name: dix_ga_ls8c_ard_3_cloud_cover; Type: INDEX; Schema: agdc; Owner: odcuser --- - -CREATE INDEX dix_ga_ls8c_ard_3_cloud_cover ON agdc.dataset USING btree ((((metadata #>> '{properties,eo:cloud_cover}'::text[]))::double precision)) WHERE ((archived IS NULL) AND (dataset_type_ref = 3)); - - --- --- Name: dix_ga_ls8c_ard_3_dataset_maturity; Type: INDEX; Schema: agdc; Owner: odcuser --- - -CREATE INDEX dix_ga_ls8c_ard_3_dataset_maturity ON agdc.dataset USING btree (((metadata #>> '{properties,dea:dataset_maturity}'::text[]))) WHERE ((archived IS NULL) AND (dataset_type_ref = 3)); - - --- --- Name: dix_ga_ls8c_ard_3_gqa; Type: INDEX; Schema: agdc; Owner: odcuser --- - -CREATE INDEX dix_ga_ls8c_ard_3_gqa ON agdc.dataset USING btree ((((metadata #>> '{properties,gqa:cep90}'::text[]))::double precision)) WHERE ((archived IS NULL) AND (dataset_type_ref = 3)); - - --- --- Name: dix_ga_ls8c_ard_3_lat_lon_time; Type: INDEX; Schema: agdc; Owner: odcuser --- - -CREATE INDEX dix_ga_ls8c_ard_3_lat_lon_time ON agdc.dataset USING gist (agdc.float8range(((metadata #>> '{extent,lat,begin}'::text[]))::double precision, ((metadata #>> '{extent,lat,end}'::text[]))::double precision, '[]'::text), agdc.float8range(((metadata #>> '{extent,lon,begin}'::text[]))::double precision, ((metadata #>> '{extent,lon,end}'::text[]))::double precision, '[]'::text), tstzrange(LEAST(agdc.common_timestamp((metadata #>> '{properties,dtr:start_datetime}'::text[])), agdc.common_timestamp((metadata #>> '{properties,datetime}'::text[]))), GREATEST(agdc.common_timestamp((metadata #>> '{properties,dtr:end_datetime}'::text[])), agdc.common_timestamp((metadata #>> '{properties,datetime}'::text[]))), '[]'::text)) WHERE ((archived IS NULL) AND (dataset_type_ref = 3)); - - --- --- Name: dix_ga_ls8c_ard_3_region_code; Type: INDEX; Schema: agdc; Owner: odcuser --- - -CREATE INDEX dix_ga_ls8c_ard_3_region_code ON agdc.dataset USING btree (((metadata #>> '{properties,odc:region_code}'::text[]))) WHERE ((archived IS NULL) AND (dataset_type_ref = 3)); - - --- --- Name: dix_ga_ls8c_ard_3_time_lat_lon; Type: INDEX; Schema: agdc; Owner: odcuser --- - -CREATE INDEX dix_ga_ls8c_ard_3_time_lat_lon ON agdc.dataset USING gist (tstzrange(LEAST(agdc.common_timestamp((metadata #>> '{properties,dtr:start_datetime}'::text[])), agdc.common_timestamp((metadata #>> '{properties,datetime}'::text[]))), GREATEST(agdc.common_timestamp((metadata #>> '{properties,dtr:end_datetime}'::text[])), agdc.common_timestamp((metadata #>> '{properties,datetime}'::text[]))), '[]'::text), agdc.float8range(((metadata #>> '{extent,lat,begin}'::text[]))::double precision, ((metadata #>> '{extent,lat,end}'::text[]))::double precision, '[]'::text), agdc.float8range(((metadata #>> '{extent,lon,begin}'::text[]))::double precision, ((metadata #>> '{extent,lon,end}'::text[]))::double precision, '[]'::text)) WHERE ((archived IS NULL) AND (dataset_type_ref = 3)); - - --- --- Name: dix_ga_ls9c_ard_3_cloud_cover; Type: INDEX; Schema: agdc; Owner: odcuser --- - -CREATE INDEX dix_ga_ls9c_ard_3_cloud_cover ON agdc.dataset USING btree ((((metadata #>> '{properties,eo:cloud_cover}'::text[]))::double precision)) WHERE ((archived IS NULL) AND (dataset_type_ref = 4)); - - --- --- Name: dix_ga_ls9c_ard_3_dataset_maturity; Type: INDEX; Schema: agdc; Owner: odcuser --- - -CREATE INDEX dix_ga_ls9c_ard_3_dataset_maturity ON agdc.dataset USING btree (((metadata #>> '{properties,dea:dataset_maturity}'::text[]))) WHERE ((archived IS NULL) AND (dataset_type_ref = 4)); - - --- --- Name: dix_ga_ls9c_ard_3_gqa; Type: INDEX; Schema: agdc; Owner: odcuser --- - -CREATE INDEX dix_ga_ls9c_ard_3_gqa ON agdc.dataset USING btree ((((metadata #>> '{properties,gqa:cep90}'::text[]))::double precision)) WHERE ((archived IS NULL) AND (dataset_type_ref = 4)); - - --- --- Name: dix_ga_ls9c_ard_3_lat_lon_time; Type: INDEX; Schema: agdc; Owner: odcuser --- - -CREATE INDEX dix_ga_ls9c_ard_3_lat_lon_time ON agdc.dataset USING gist (agdc.float8range(((metadata #>> '{extent,lat,begin}'::text[]))::double precision, ((metadata #>> '{extent,lat,end}'::text[]))::double precision, '[]'::text), agdc.float8range(((metadata #>> '{extent,lon,begin}'::text[]))::double precision, ((metadata #>> '{extent,lon,end}'::text[]))::double precision, '[]'::text), tstzrange(LEAST(agdc.common_timestamp((metadata #>> '{properties,dtr:start_datetime}'::text[])), agdc.common_timestamp((metadata #>> '{properties,datetime}'::text[]))), GREATEST(agdc.common_timestamp((metadata #>> '{properties,dtr:end_datetime}'::text[])), agdc.common_timestamp((metadata #>> '{properties,datetime}'::text[]))), '[]'::text)) WHERE ((archived IS NULL) AND (dataset_type_ref = 4)); - - --- --- Name: dix_ga_ls9c_ard_3_region_code; Type: INDEX; Schema: agdc; Owner: odcuser --- - -CREATE INDEX dix_ga_ls9c_ard_3_region_code ON agdc.dataset USING btree (((metadata #>> '{properties,odc:region_code}'::text[]))) WHERE ((archived IS NULL) AND (dataset_type_ref = 4)); - - --- --- Name: dix_ga_ls9c_ard_3_time_lat_lon; Type: INDEX; Schema: agdc; Owner: odcuser --- - -CREATE INDEX dix_ga_ls9c_ard_3_time_lat_lon ON agdc.dataset USING gist (tstzrange(LEAST(agdc.common_timestamp((metadata #>> '{properties,dtr:start_datetime}'::text[])), agdc.common_timestamp((metadata #>> '{properties,datetime}'::text[]))), GREATEST(agdc.common_timestamp((metadata #>> '{properties,dtr:end_datetime}'::text[])), agdc.common_timestamp((metadata #>> '{properties,datetime}'::text[]))), '[]'::text), agdc.float8range(((metadata #>> '{extent,lat,begin}'::text[]))::double precision, ((metadata #>> '{extent,lat,end}'::text[]))::double precision, '[]'::text), agdc.float8range(((metadata #>> '{extent,lon,begin}'::text[]))::double precision, ((metadata #>> '{extent,lon,end}'::text[]))::double precision, '[]'::text)) WHERE ((archived IS NULL) AND (dataset_type_ref = 4)); - - --- --- Name: ix_agdc_dataset_dataset_type_ref; Type: INDEX; Schema: agdc; Owner: odcuser --- - -CREATE INDEX ix_agdc_dataset_dataset_type_ref ON agdc.dataset USING btree (dataset_type_ref); - - --- --- Name: ix_agdc_dataset_location_dataset_ref; Type: INDEX; Schema: agdc; Owner: odcuser --- - -CREATE INDEX ix_agdc_dataset_location_dataset_ref ON agdc.dataset_location USING btree (dataset_ref); - - --- --- Name: dataset row_update_time_dataset; Type: TRIGGER; Schema: agdc; Owner: odcuser --- - -CREATE TRIGGER row_update_time_dataset BEFORE UPDATE ON agdc.dataset FOR EACH ROW EXECUTE FUNCTION agdc.set_row_update_time(); - - --- --- Name: dataset_type row_update_time_dataset_type; Type: TRIGGER; Schema: agdc; Owner: odcuser --- - -CREATE TRIGGER row_update_time_dataset_type BEFORE UPDATE ON agdc.dataset_type FOR EACH ROW EXECUTE FUNCTION agdc.set_row_update_time(); - - --- --- Name: metadata_type row_update_time_metadata_type; Type: TRIGGER; Schema: agdc; Owner: odcuser --- - -CREATE TRIGGER row_update_time_metadata_type BEFORE UPDATE ON agdc.metadata_type FOR EACH ROW EXECUTE FUNCTION agdc.set_row_update_time(); - - --- --- Name: dataset fk_dataset_dataset_type_ref_dataset_type; Type: FK CONSTRAINT; Schema: agdc; Owner: odcuser --- - -ALTER TABLE ONLY agdc.dataset - ADD CONSTRAINT fk_dataset_dataset_type_ref_dataset_type FOREIGN KEY (dataset_type_ref) REFERENCES agdc.dataset_type(id); - - --- --- Name: dataset_location fk_dataset_location_dataset_ref_dataset; Type: FK CONSTRAINT; Schema: agdc; Owner: odcuser --- - -ALTER TABLE ONLY agdc.dataset_location - ADD CONSTRAINT fk_dataset_location_dataset_ref_dataset FOREIGN KEY (dataset_ref) REFERENCES agdc.dataset(id); - - --- --- Name: dataset fk_dataset_metadata_type_ref_metadata_type; Type: FK CONSTRAINT; Schema: agdc; Owner: odcuser --- - -ALTER TABLE ONLY agdc.dataset - ADD CONSTRAINT fk_dataset_metadata_type_ref_metadata_type FOREIGN KEY (metadata_type_ref) REFERENCES agdc.metadata_type(id); - - --- --- Name: dataset_source fk_dataset_source_dataset_ref_dataset; Type: FK CONSTRAINT; Schema: agdc; Owner: odcuser --- - -ALTER TABLE ONLY agdc.dataset_source - ADD CONSTRAINT fk_dataset_source_dataset_ref_dataset FOREIGN KEY (dataset_ref) REFERENCES agdc.dataset(id); - - --- --- Name: dataset_source fk_dataset_source_source_dataset_ref_dataset; Type: FK CONSTRAINT; Schema: agdc; Owner: odcuser --- - -ALTER TABLE ONLY agdc.dataset_source - ADD CONSTRAINT fk_dataset_source_source_dataset_ref_dataset FOREIGN KEY (source_dataset_ref) REFERENCES agdc.dataset(id); - - --- --- Name: dataset_type fk_dataset_type_metadata_type_ref_metadata_type; Type: FK CONSTRAINT; Schema: agdc; Owner: odcuser --- - -ALTER TABLE ONLY agdc.dataset_type - ADD CONSTRAINT fk_dataset_type_metadata_type_ref_metadata_type FOREIGN KEY (metadata_type_ref) REFERENCES agdc.metadata_type(id); - - --- --- Name: job cron_job_policy; Type: POLICY; Schema: cron; Owner: postgres --- - -CREATE POLICY cron_job_policy ON cron.job USING ((username = CURRENT_USER)); - - --- --- Name: job_run_details cron_job_run_details_policy; Type: POLICY; Schema: cron; Owner: postgres --- - -CREATE POLICY cron_job_run_details_policy ON cron.job_run_details USING ((username = CURRENT_USER)); - - --- --- Name: job; Type: ROW SECURITY; Schema: cron; Owner: postgres --- - -ALTER TABLE cron.job ENABLE ROW LEVEL SECURITY; - --- --- Name: job_run_details; Type: ROW SECURITY; Schema: cron; Owner: postgres --- - -ALTER TABLE cron.job_run_details ENABLE ROW LEVEL SECURITY; - --- --- Name: DEFAULT PRIVILEGES FOR TABLES; Type: DEFAULT ACL; Schema: public; Owner: odcuser --- - -ALTER DEFAULT PRIVILEGES FOR ROLE odcuser IN SCHEMA public GRANT SELECT ON TABLES TO replicator; - - --- --- PostgreSQL database dump complete --- - diff --git a/docker/docker-compose.cleandb.yaml b/docker/docker-compose.cleandb.yaml deleted file mode 100644 index 3c29cdf1..00000000 --- a/docker/docker-compose.cleandb.yaml +++ /dev/null @@ -1,13 +0,0 @@ -version: '3.4' - -services: - postgres: - # clean postgis db - image: kartoza/postgis:13-3.1 - environment: - - POSTGRES_DB=odc - - POSTGRES_PASSWORD=odcpass - - POSTGRES_USER=odcuser - ports: - - "5432:5432" - restart: always diff --git a/docker/docker-compose.index.yaml b/docker/docker-compose.index.yaml deleted file mode 100644 index d6be1cb9..00000000 --- a/docker/docker-compose.index.yaml +++ /dev/null @@ -1,17 +0,0 @@ -version: '3.4' - -services: - index: - image: opendatacube/datacube-index:latest - environment: - DB_PORT: 5432 - DB_HOSTNAME: postgres - DB_USERNAME: odcuser - DB_PASSWORD: odcpass - DB_DATABASE: odc - restart: always - depends_on: - - postgres - command: tail -f /dev/null - links: - - postgres:postgres From baf5642a95cfe61068b082e69f61608cfe192a17 Mon Sep 17 00:00:00 2001 From: Robbi Bishop-Taylor Date: Thu, 1 Aug 2024 22:06:55 +1000 Subject: [PATCH 32/45] Update gitignore --- .gitignore | 1 + 1 file changed, 1 insertion(+) diff --git a/.gitignore b/.gitignore index 5f6dae27..31ade6ef 100644 --- a/.gitignore +++ b/.gitignore @@ -11,5 +11,6 @@ !*.sql !**.github !*.md +!requirements.txt !tests/*.png !tests/*.csv From bcfeddd784bfdd346f883ea5baebc546c158cc18 Mon Sep 17 00:00:00 2001 From: Robbi Bishop-Taylor Date: Thu, 1 Aug 2024 23:28:01 +1000 Subject: [PATCH 33/45] Update test_coastline.py --- tests/test_coastline.py | 16 +++++++++++++--- 1 file changed, 13 insertions(+), 3 deletions(-) diff --git a/tests/test_coastline.py b/tests/test_coastline.py index 7ed3ba66..2327ffb3 100644 --- a/tests/test_coastline.py +++ b/tests/test_coastline.py @@ -5,6 +5,9 @@ from coastlines.continental import continental_cli from coastlines.validation import validation_cli +import os +os.environ['CLICK_DEBUG'] = '1' + @pytest.mark.dependency() def test_generate_rasters_cli(): runner = CliRunner() @@ -73,7 +76,7 @@ def test_generate_continental_cli(): assert result.exit_code == 0 @pytest.mark.dependency(depends=["test_generate_continental_cli"]) -def test_validation_cli(): +def test_validation_cli(capsys): runner = CliRunner() result = runner.invoke( validation_cli, @@ -90,5 +93,12 @@ def test_validation_cli(): "True", ], ) - # assert result.output == '' # for debugging - assert result.exit_code == 0 + + print("CLI Output:") + print(result.output) + + captured = capsys.readouterr() + print("Stdout:", captured.out) + print("Stderr:", captured.err) + + assert result.exit_code == 0, f"Command failed with exit code {result.exit_code}. Exception:\n{result.exception}" From 0758ecf8fa8b6c3614e9858260f52a26b43411ba Mon Sep 17 00:00:00 2001 From: Robbi Bishop-Taylor Date: Thu, 1 Aug 2024 23:55:59 +1000 Subject: [PATCH 34/45] Update test_coastline.py --- tests/test_coastline.py | 20 ++++++++++++-------- 1 file changed, 12 insertions(+), 8 deletions(-) diff --git a/tests/test_coastline.py b/tests/test_coastline.py index 2327ffb3..65f67927 100644 --- a/tests/test_coastline.py +++ b/tests/test_coastline.py @@ -94,11 +94,15 @@ def test_validation_cli(capsys): ], ) - print("CLI Output:") - print(result.output) - - captured = capsys.readouterr() - print("Stdout:", captured.out) - print("Stderr:", captured.err) - - assert result.exit_code == 0, f"Command failed with exit code {result.exit_code}. Exception:\n{result.exception}" + # Prepare detailed error information + error_info = { + "exit_code": result.exit_code, + "output": result.output, + "exception": str(result.exception) if result.exception else None, + } + + # Convert error_info to a formatted string + error_details = json.dumps(error_info, indent=2) + + # Use the detailed error information in the assertion message + assert result.exit_code == 0, f"Command failed. Error details:\n{error_details}" From 168f3b538270fd32f8217b9af7001f6a3dff0a57 Mon Sep 17 00:00:00 2001 From: Robbi Bishop-Taylor Date: Fri, 2 Aug 2024 00:37:51 +1000 Subject: [PATCH 35/45] Update test_coastline.py --- tests/test_coastline.py | 1 + 1 file changed, 1 insertion(+) diff --git a/tests/test_coastline.py b/tests/test_coastline.py index 65f67927..13ce47bf 100644 --- a/tests/test_coastline.py +++ b/tests/test_coastline.py @@ -6,6 +6,7 @@ from coastlines.validation import validation_cli import os +import json os.environ['CLICK_DEBUG'] = '1' @pytest.mark.dependency() From e0e9e8c98969cf59a2d10d1ad7276dda6fb118e4 Mon Sep 17 00:00:00 2001 From: Robbi Bishop-Taylor Date: Fri, 2 Aug 2024 09:29:35 +1000 Subject: [PATCH 36/45] Debug --- .github/workflows/dea-coastlines-image.yaml | 42 ++++++++++----------- 1 file changed, 21 insertions(+), 21 deletions(-) diff --git a/.github/workflows/dea-coastlines-image.yaml b/.github/workflows/dea-coastlines-image.yaml index 5a6148be..7c9ed25a 100644 --- a/.github/workflows/dea-coastlines-image.yaml +++ b/.github/workflows/dea-coastlines-image.yaml @@ -103,26 +103,26 @@ jobs: ls -l ./tests/ git status - # Commit validation results produced by integration tests back into repo - - name: Commit validation results into repository - uses: stefanzweifel/git-auto-commit-action@v4 - if: github.event_name == 'pull_request' - continue-on-error: true - with: - commit_message: Automatically update integration test validation results - file_pattern: 'tests/stats_tests.png tests/stats_tests.csv tests/README.md' - - # Post validation tesults as comment on PR - - name: Post validation results as comment - uses: mshick/add-pr-comment@v2 - if: github.event_name == 'pull_request' - with: - message: | - ![](https://github.com/GeoscienceAustralia/dea-coastlines/blob/${{ github.head_ref }}/tests/stats_tests.png?raw=true") + # # Commit validation results produced by integration tests back into repo + # - name: Commit validation results into repository + # uses: stefanzweifel/git-auto-commit-action@v4 + # if: github.event_name == 'pull_request' + # continue-on-error: true + # with: + # commit_message: Automatically update integration test validation results + # file_pattern: 'tests/stats_tests.png tests/stats_tests.csv tests/README.md' + + # # Post validation tesults as comment on PR + # - name: Post validation results as comment + # uses: mshick/add-pr-comment@v2 + # if: github.event_name == 'pull_request' + # with: + # message: | + # ![](https://github.com/GeoscienceAustralia/dea-coastlines/blob/${{ github.head_ref }}/tests/stats_tests.png?raw=true") - For full integration test results, refer to the [Tests directory README](https://github.com/GeoscienceAustralia/dea-coastlines/tree/${{ github.head_ref }}/tests). + # For full integration test results, refer to the [Tests directory README](https://github.com/GeoscienceAustralia/dea-coastlines/tree/${{ github.head_ref }}/tests). - - name: Upload coverage reports to Codecov - uses: codecov/codecov-action@v3 - env: - CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }} \ No newline at end of file + # - name: Upload coverage reports to Codecov + # uses: codecov/codecov-action@v3 + # env: + # CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }} \ No newline at end of file From 748297c98a9236432e3f1064417098f9d4084987 Mon Sep 17 00:00:00 2001 From: Robbi Bishop-Taylor Date: Fri, 2 Aug 2024 09:46:53 +1000 Subject: [PATCH 37/45] Debug --- tests/test_coastline.py | 56 ++++++++++++++++++++--------------------- 1 file changed, 28 insertions(+), 28 deletions(-) diff --git a/tests/test_coastline.py b/tests/test_coastline.py index 13ce47bf..1ebe4661 100644 --- a/tests/test_coastline.py +++ b/tests/test_coastline.py @@ -76,34 +76,34 @@ def test_generate_continental_cli(): # assert result.output == '' # for debugging assert result.exit_code == 0 -@pytest.mark.dependency(depends=["test_generate_continental_cli"]) -def test_validation_cli(capsys): - runner = CliRunner() - result = runner.invoke( - validation_cli, - [ - "--inputs_path", - "data/validation/interim/wrl_narrabeen", - "--deacl_path", - "data/processed/tests/coastlines_tests.gpkg", - "--prefix", - "tests", - "--append_stats", - "True", - "--markdown_report", - "True", - ], - ) +# @pytest.mark.dependency(depends=["test_generate_continental_cli"]) +# def test_validation_cli(capsys): +# runner = CliRunner() +# result = runner.invoke( +# validation_cli, +# [ +# "--inputs_path", +# "data/validation/interim/wrl_narrabeen", +# "--deacl_path", +# "data/processed/tests/coastlines_tests.gpkg", +# "--prefix", +# "tests", +# "--append_stats", +# "True", +# "--markdown_report", +# "True", +# ], +# ) - # Prepare detailed error information - error_info = { - "exit_code": result.exit_code, - "output": result.output, - "exception": str(result.exception) if result.exception else None, - } +# # Prepare detailed error information +# error_info = { +# "exit_code": result.exit_code, +# "output": result.output, +# "exception": str(result.exception) if result.exception else None, +# } - # Convert error_info to a formatted string - error_details = json.dumps(error_info, indent=2) +# # Convert error_info to a formatted string +# error_details = json.dumps(error_info, indent=2) - # Use the detailed error information in the assertion message - assert result.exit_code == 0, f"Command failed. Error details:\n{error_details}" +# # Use the detailed error information in the assertion message +# assert result.exit_code == 0, f"Command failed. Error details:\n{error_details}" From e5936c93d265bbf978c36ab874e01076fd6ea60a Mon Sep 17 00:00:00 2001 From: Robbi Bishop-Taylor Date: Fri, 2 Aug 2024 10:00:26 +1000 Subject: [PATCH 38/45] Finally fix validation bug --- .github/workflows/dea-coastlines-image.yaml | 45 ++++++++--------- coastlines/validation.py | 2 +- tests/test_coastline.py | 56 ++++++++++----------- 3 files changed, 49 insertions(+), 54 deletions(-) diff --git a/.github/workflows/dea-coastlines-image.yaml b/.github/workflows/dea-coastlines-image.yaml index 7c9ed25a..399b2d8c 100644 --- a/.github/workflows/dea-coastlines-image.yaml +++ b/.github/workflows/dea-coastlines-image.yaml @@ -98,31 +98,26 @@ jobs: --volume ${GITHUB_WORKSPACE}/tide_models:/var/share/tide_models \ dea_coastlines pytest -v --cov=coastlines --cov-report=xml tests - ls -l . - ls -l ./data/validation/processed/ - ls -l ./tests/ - git status - - # # Commit validation results produced by integration tests back into repo - # - name: Commit validation results into repository - # uses: stefanzweifel/git-auto-commit-action@v4 - # if: github.event_name == 'pull_request' - # continue-on-error: true - # with: - # commit_message: Automatically update integration test validation results - # file_pattern: 'tests/stats_tests.png tests/stats_tests.csv tests/README.md' + # Commit validation results produced by integration tests back into repo + - name: Commit validation results into repository + uses: stefanzweifel/git-auto-commit-action@v4 + if: github.event_name == 'pull_request' + continue-on-error: true + with: + commit_message: Automatically update integration test validation results + file_pattern: 'tests/stats_tests.png tests/stats_tests.csv tests/README.md' - # # Post validation tesults as comment on PR - # - name: Post validation results as comment - # uses: mshick/add-pr-comment@v2 - # if: github.event_name == 'pull_request' - # with: - # message: | - # ![](https://github.com/GeoscienceAustralia/dea-coastlines/blob/${{ github.head_ref }}/tests/stats_tests.png?raw=true") + # Post validation tesults as comment on PR + - name: Post validation results as comment + uses: mshick/add-pr-comment@v2 + if: github.event_name == 'pull_request' + with: + message: | + ![](https://github.com/GeoscienceAustralia/dea-coastlines/blob/${{ github.head_ref }}/tests/stats_tests.png?raw=true") - # For full integration test results, refer to the [Tests directory README](https://github.com/GeoscienceAustralia/dea-coastlines/tree/${{ github.head_ref }}/tests). + For full integration test results, refer to the [Tests directory README](https://github.com/GeoscienceAustralia/dea-coastlines/tree/${{ github.head_ref }}/tests). - # - name: Upload coverage reports to Codecov - # uses: codecov/codecov-action@v3 - # env: - # CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }} \ No newline at end of file + - name: Upload coverage reports to Codecov + uses: codecov/codecov-action@v3 + env: + CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }} \ No newline at end of file diff --git a/coastlines/validation.py b/coastlines/validation.py index 1c0a6ffa..7605d8b6 100644 --- a/coastlines/validation.py +++ b/coastlines/validation.py @@ -2295,7 +2295,7 @@ def deacl_validation( lambda x: pd.Series.mode(x).iloc[0] ) count_vals = val_df.groupby(["year", "id"]).year.count().rename("n") - median_vals = val_df.groupby(["year", "id"]).median() + median_vals = val_df.groupby(["year", "id"]).median(numeric_only=True) # Combine all aggregated stats into one dataframe val_df = pd.concat( diff --git a/tests/test_coastline.py b/tests/test_coastline.py index 1ebe4661..13ce47bf 100644 --- a/tests/test_coastline.py +++ b/tests/test_coastline.py @@ -76,34 +76,34 @@ def test_generate_continental_cli(): # assert result.output == '' # for debugging assert result.exit_code == 0 -# @pytest.mark.dependency(depends=["test_generate_continental_cli"]) -# def test_validation_cli(capsys): -# runner = CliRunner() -# result = runner.invoke( -# validation_cli, -# [ -# "--inputs_path", -# "data/validation/interim/wrl_narrabeen", -# "--deacl_path", -# "data/processed/tests/coastlines_tests.gpkg", -# "--prefix", -# "tests", -# "--append_stats", -# "True", -# "--markdown_report", -# "True", -# ], -# ) +@pytest.mark.dependency(depends=["test_generate_continental_cli"]) +def test_validation_cli(capsys): + runner = CliRunner() + result = runner.invoke( + validation_cli, + [ + "--inputs_path", + "data/validation/interim/wrl_narrabeen", + "--deacl_path", + "data/processed/tests/coastlines_tests.gpkg", + "--prefix", + "tests", + "--append_stats", + "True", + "--markdown_report", + "True", + ], + ) -# # Prepare detailed error information -# error_info = { -# "exit_code": result.exit_code, -# "output": result.output, -# "exception": str(result.exception) if result.exception else None, -# } + # Prepare detailed error information + error_info = { + "exit_code": result.exit_code, + "output": result.output, + "exception": str(result.exception) if result.exception else None, + } -# # Convert error_info to a formatted string -# error_details = json.dumps(error_info, indent=2) + # Convert error_info to a formatted string + error_details = json.dumps(error_info, indent=2) -# # Use the detailed error information in the assertion message -# assert result.exit_code == 0, f"Command failed. Error details:\n{error_details}" + # Use the detailed error information in the assertion message + assert result.exit_code == 0, f"Command failed. Error details:\n{error_details}" From d28ce32beb83c1352b2381be9b4a12e3c00b1088 Mon Sep 17 00:00:00 2001 From: robbibt Date: Fri, 2 Aug 2024 00:15:57 +0000 Subject: [PATCH 39/45] Automatically update integration test validation results --- tests/README.md | 2 +- tests/stats_tests.csv | 1 + tests/stats_tests.png | Bin 95448 -> 96061 bytes 3 files changed, 2 insertions(+), 1 deletion(-) diff --git a/tests/README.md b/tests/README.md index 77ff598f..9df406bc 100644 --- a/tests/README.md +++ b/tests/README.md @@ -15,7 +15,7 @@ In addition to testing whether the code runs without errors, we also run a small ## Latest integration test validation results -The latest integration test completed at **2024-08-01 20:41**. Compared to the previous run, it had an: +The latest integration test completed at **2024-08-02 10:15**. Compared to the previous run, it had an: - RMSE accuracy of **6.15 m (:heavy_minus_sign: no change)** - MAE accuracy of **4.85 m (:heavy_minus_sign: no change)** - Bias of **-2.65 m (:heavy_minus_sign: no change)** diff --git a/tests/stats_tests.csv b/tests/stats_tests.csv index d47fdc4c..2c1e5313 100644 --- a/tests/stats_tests.csv +++ b/tests/stats_tests.csv @@ -36,3 +36,4 @@ time,n,mae,rmse,stdev,corr,bias,name 2024-08-01 00:27:59.036809,2669.0,4.84,6.16,5.56,0.975,-2.67,tests 2024-08-01 06:58:39.701964,2669.0,4.85,6.15,5.57,0.975,-2.65,tests 2024-08-01 10:41:29.546023,2669.0,4.85,6.15,5.57,0.975,-2.65,tests +2024-08-02 00:15:55.377300,2669.0,4.85,6.15,5.57,0.975,-2.65,tests diff --git a/tests/stats_tests.png b/tests/stats_tests.png index 1f75f99898785c8deb8efa714e0f7169f70ccd94..dc6ff66b1333d9df426dcba6321dd9e217a61af1 100644 GIT binary patch literal 96061 zcmeFZc{J8-`!{;gBts}WB~hjZMI!S&l?+A5l+06- zRA!}28TaRW-uL&ecdxbgyVu%#?SJ;#_p|PG-}e*O^&QUhI6l*H-qzMU&OpmaOQBF0 zPN*vBQYdRXC=}`fn)Ud9)>c`$;2$z>%7$*IoX)vjwzy_gyw&si|E5d+5S(C+Z!_N0i1H-t6!gXYgK=6Ww)E;&zVm$?+UJ%V5hY zPVdex_3_fHrBv}W*Qx)myz^ds^J9~=Cd#|BB=qG<9hB)&~98Ujk?7 zFUe6U{nuaS{08aF|Ml0%HCDU-`U54evsIk`^#}L28|J9|*PkS8_`mrpI#E#~XVwQQ z^7*#4C+i%eW!$*2_UYQ6abaOhBUdiACExF@{dc-fSbWE^>&UyPMCbrPZXB%V=tCaJ5r;K_Q-%cAbWX#@X}dH}LTANZ5BVol4SF*3*m7 zTx=Q+@8+RiUYzR;^8Zm6X}|5bSC)Bs_4G(9GdnxY)~#CwBGn!~c~V(ZvtgU8+uMbi zv8jQ|TcJHQLvPjYY5nRq`1kOUzq;Q-*P@x`0(aAsm_Lb!irSXX{Q2Jb(=Jt_{tgp0 z|M7ckDeRn_mcyT(x8#2RZf)O_zj4imO-hMskzoq{eh(i%u4rl5yh}am{pEh&TU$lV ztY1x>DRO*{zkg3p2k52*+_C2jii zy>?Ba?nW&wEw`}_h9al_4$f8F)I$Y-`HStT>-Ox~!_LK3+1AFgef#zc-MPC~7RIug z9z@lI@>s1b{kzbaxlJuXfa>`1wfUTFblrJa<1J%WN8qeacDf7D0kxQ*y?AG*R+b%!;)syoMO z!}aUe!yY~q2vk0P+^WCKx2wpB$78(fTB3Ti8fyhlo~Zj?gY>r@8E5j`H{~-c#^Evy z%Y0r7FRd&u8s=JWG{`UxWZ*g&XHj|cKMP^)`t{#FJwKM~{vbSj>g&5ThpzmlJUQr4 zG1u=On?cLz+mdTpMVnHgXR4>iGW)AP6mOLO&>?R8$o1#XpKFeEm3kMMv8s1B(iK0H zyS%T^zWc#M{_qQ{ntSZ>KGN~=@%#N(e0=8mE`Nv??LXfw)f{~lyM4NQX0nfK9WBcd z4GntDr?P>^Zf!bBbM5l4FVFG!m6=gimAmZs2NoQ93zc7A`XNyvp4!%3?7r91(o&+L zvZCU5y=eJ`63_a&o&vk(GGFiRGYzutqj8sh)M*Pv2Hm~;zRY*=QbAz-P+Orx?`KWL zd#PABqn%l?y|o|oU0htUb8{E0dqoY>4PW|CGv8k+d+FWP`JiJR9h>T^BVJsGbaiz# zS=4pWqM=wVXO|ad$Wozv#VZ+ZPuqHL`(dFf|D}1co+2kv{R9>fW0r}Yg31EB&g^rI zoRqhC-#TSJo*|h@-F?x;d$gXN{rdKr*RzeUWn6!L5X!}6--=fbwrqSX`O0I0bMuxh z&Cic*Fe&w7&CJZCv`a)9CV*1v>TUeadr_eeUw29v&V7X9|T&N=tJtG{*}M`fHed zxU2a5>XRp2b&-2-MMOl{7p)c6j-xD0kGx=ZJR8?N(%99-j#c;`*Y|s6*<1Kbp@v=J zuIBP6-gtYtE5G9?yuMNUOdtP{#Z|FooGD@pq}$5o`R6;cii%1_U7cElkiMGF;zZFm zJSq-H^WHtn@8E2BU`ML{9g|T-Ss|wy)(bHpW-2eHr$#{3(aelLl7gG(( z{YuBB1DJN~-mP+Xo1DS?zkeH1(Jk!lg-uLMl!Dnr@*Vfc${N%2$eXmK>Z{{=Xw=o! z$)Cr>#3((Lb$^fIlrpp6*qy74O+<_OCYZ%4pnXKbu0um3Mp`E!A%S#1;jCY{%s{5c zo!X{Hj$G|n3iDgsz_^_S#e+|RdLlIO6OThx&Bjvb13Vo^}eH9Zqq zT3!x(`t<33EV+*#KgR2)8GM_c8Z>U@;^7g+hUEL)*B7Xp!lE3^#`<@tX)Bgk{qM_3 z&-O7gGBUHW?pm0g*lS{H8hGv6wTEI>H<=WJLb#;vV0+)*yi1J+4`{?pCqb3DIm=wZ zsK-@E0i|70@%lq~-{NH5#5-6Ok$-${tY>(S-68ocsr>loQt#6ZPvuTW278X{@ zv8;L@#&_&}+UVJ!@8WE2q3^FRhr9no zM6lc!HJ7*j*QBs29PsIveC&!(+A5p)n_C<2&%W7bURFZhrKYCl4hadpL;fp=TK~#< z{;_UOHxeHh9ONG#9}l>H|9*B(4l}mRR)y82JmJ`+a<(4%)I}WwTi@y7`{-s51o zt7>YlB%|ejew9Pv{WH`gidGgr@~^4k79)@KztXMNX_^l`e%3UhYugL9!F(o@5kGq1$^1iJ-dlpnpgce5EIJO#*G_W%3J$y91toW z4c{8@N!ZFdDr&l1ea8Ey?2N>DDJ`;Zjf>8{yWVXaJ#1HVM{>vE;Zx0nLqpNFe68*6 z`iK0M498~07uW3CwM!WbK&JH-N>kL~pt*_OJ@gC=;-*8WCW=8#r*d`&Frk)4SB-S% z4IO{#6p7;e;huYQymIb!YY$p=MVcuzmk%um9C{?4c9wcfJa%?*kxqJ8S0gco6R2zRoylxX| zS=n=5!q_#PBeEmLIR*t6^`C1CNX(+5Z=d>BMaQQ!E7W0Da)nPVdf!uvLnvrsu0J)5 zyuOtCi(*?AR6DgKoVZyoH{&KFEq!6>=*v_?I$GK~iHVMmj&CT5##u#W|3*eylj03? 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zm=>C#TY%X40U9U1jhI%bt3EO1z?NpD455B`R7WS+zF_`a|8B5N5Pk<>59>lGfd_!g z`|E>uojbdq;G&_M2B}?w@1WTK0Eh9Ifx$D3fRI5`*HHYAAZ_rMR(EWyoSbZ%8y_%> z7qiH{F2@n9C!YmY^$We3_V>bVXZ~eRu*;UXuK@Vb85+5Yp_c z1!zA%Eyl$q2ZH!6q{9KAJ^0%ICmPfNRK&1gLqD2BpNwZC@?f}!6$^>f2a>u;3|H<3 zw^tq}gmf(HX5VCfTPO}88YX{~=<4L^~LVCJAH*RB`ninRLuZ37DLw!h9Z_}CzgbOg1L z$TXmp1g2{#MfYYm7ot@v&b#pK=P;y@w8@f{0hQrklmw^n~#PS4KfP1=BXg0co+{ zULhSyMAZ?%%Hy^b1Jq9NDeV6j>f7;Dp-6ULIunD>9Rx>_$N~cqx5ge45@V1-n-!rS zjPy6<7L~rMtdzy$NQP>F1nrr%KEhyPbRl<#)`w%7r zPooKr5Gug;!IU7|5Y()L;3p|QJyi1uPl!_nWE+ZJrC$$Gb`#~c@*t`Yfx^>7dw>RU-M$;wA z{*B{0*Mo?J&qeyZHqY^{R#n*$E Date: Fri, 2 Aug 2024 10:19:29 +1000 Subject: [PATCH 40/45] Fix formatting --- coastlines/validation.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/coastlines/validation.py b/coastlines/validation.py index 7605d8b6..7a0e748d 100644 --- a/coastlines/validation.py +++ b/coastlines/validation.py @@ -2699,10 +2699,10 @@ def validation_cli( f"Compared to the previous run, it had an:" ) items = [ - f"RMSE accuracy of **{stats_df.rmse[-1]:.2f} m ({recent_diff.rmse})**", - f"MAE accuracy of **{stats_df.mae[-1]:.2f} m ({recent_diff.mae})**", - f"Bias of **{stats_df['bias'][-1]:.2f} m ({recent_diff['bias']})**", - f"Pearson correlation of **{stats_df['corr'][-1]:.3f} ({recent_diff['corr']})**", + f"RMSE accuracy of **{stats_df.rmse[-1]:.2f} m ( {recent_diff.rmse})**", + f"MAE accuracy of **{stats_df.mae[-1]:.2f} m ( {recent_diff.mae})**", + f"Bias of **{stats_df['bias'][-1]:.2f} m ( {recent_diff['bias']})**", + f"Pearson correlation of **{stats_df['corr'][-1]:.3f} ( {recent_diff['corr']})**", ] mdFile.new_list(items=items) mdFile.new_paragraph(Html.image(path=f"stats_tests.png", size="950")) From 3ec5129b6e190b5187648136c06b4fc8ad8b074c Mon Sep 17 00:00:00 2001 From: Robbi Bishop-Taylor Date: Fri, 2 Aug 2024 00:25:08 +0000 Subject: [PATCH 41/45] Fix pep8 --- coastlines/validation.py | 26 ++++++++++++++------------ tests/test_coastline.py | 11 +++++------ 2 files changed, 19 insertions(+), 18 deletions(-) diff --git a/coastlines/validation.py b/coastlines/validation.py index 7a0e748d..2706da9f 100644 --- a/coastlines/validation.py +++ b/coastlines/validation.py @@ -431,9 +431,11 @@ def coastal_transects( # Reverse transects so all point away from land transect_gdf["geometry"] = transect_gdf.apply( - lambda i: LineString([i.geometry.coords[1], i.geometry.coords[0]]) - if i.p1 < i.p2 - else i.geometry, + lambda i: ( + LineString([i.geometry.coords[1], i.geometry.coords[0]]) + if i.p1 < i.p2 + else i.geometry + ), axis=1, ) @@ -2663,15 +2665,15 @@ def validation_cli( recent_diff.loc["corr"] = -recent_diff.loc[ "corr" ] # Invert as higher corrs are good - recent_diff.loc[ - recent_diff["diff"] < 0, "prefix" - ] = ":heavy_check_mark: improved by " - recent_diff.loc[ - recent_diff["diff"] == 0, "prefix" - ] = ":heavy_minus_sign: no change" - recent_diff.loc[ - recent_diff["diff"] > 0, "prefix" - ] = ":heavy_exclamation_mark: worsened by " + recent_diff.loc[recent_diff["diff"] < 0, "prefix"] = ( + ":heavy_check_mark: improved by " + ) + recent_diff.loc[recent_diff["diff"] == 0, "prefix"] = ( + ":heavy_minus_sign: no change" + ) + recent_diff.loc[recent_diff["diff"] > 0, "prefix"] = ( + ":heavy_exclamation_mark: worsened by " + ) recent_diff["suffix"] = recent_diff["diff"].abs().round(3).replace({0: ""}) recent_diff = ( recent_diff.prefix.astype(str) + recent_diff.suffix.astype(str).str[0:5] diff --git a/tests/test_coastline.py b/tests/test_coastline.py index 13ce47bf..536a4abc 100644 --- a/tests/test_coastline.py +++ b/tests/test_coastline.py @@ -1,13 +1,11 @@ import pytest +import json from click.testing import CliRunner from coastlines.raster import generate_rasters_cli from coastlines.vector import generate_vectors_cli from coastlines.continental import continental_cli from coastlines.validation import validation_cli -import os -import json -os.environ['CLICK_DEBUG'] = '1' @pytest.mark.dependency() def test_generate_rasters_cli(): @@ -76,6 +74,7 @@ def test_generate_continental_cli(): # assert result.output == '' # for debugging assert result.exit_code == 0 + @pytest.mark.dependency(depends=["test_generate_continental_cli"]) def test_validation_cli(capsys): runner = CliRunner() @@ -101,9 +100,9 @@ def test_validation_cli(capsys): "output": result.output, "exception": str(result.exception) if result.exception else None, } - + # Convert error_info to a formatted string error_details = json.dumps(error_info, indent=2) - + # Use the detailed error information in the assertion message - assert result.exit_code == 0, f"Command failed. Error details:\n{error_details}" + assert result.exit_code == 0, f"Command failed. Error details:\n{error_details}" From 4f7b337469fafccbf78e5b0c01f95bd2e570d2ef Mon Sep 17 00:00:00 2001 From: Robbi Bishop-Taylor Date: Fri, 2 Aug 2024 10:31:47 +1000 Subject: [PATCH 42/45] Add image build and artifacts --- .github/workflows/dea-coastlines-image.yaml | 59 ++++++++++- .github/workflows/docker.yaml | 59 ----------- .github/workflows/test.yaml | 109 -------------------- 3 files changed, 58 insertions(+), 169 deletions(-) delete mode 100644 .github/workflows/docker.yaml delete mode 100644 .github/workflows/test.yaml diff --git a/.github/workflows/dea-coastlines-image.yaml b/.github/workflows/dea-coastlines-image.yaml index 399b2d8c..13de9f1a 100644 --- a/.github/workflows/dea-coastlines-image.yaml +++ b/.github/workflows/dea-coastlines-image.yaml @@ -117,7 +117,64 @@ jobs: For full integration test results, refer to the [Tests directory README](https://github.com/GeoscienceAustralia/dea-coastlines/tree/${{ github.head_ref }}/tests). + # Upload code coverage results - name: Upload coverage reports to Codecov uses: codecov/codecov-action@v3 env: - CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }} \ No newline at end of file + CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }} + + # Add output GeoPackage data to Actions artifact so it can be downloaded + - uses: actions/upload-artifact@v3 + with: + name: output_geopackage + path: ./data/processed/tests/coastlines_tests.gpkg + + # Add output ESRI Shapefile data to Actions artifact so it can be downloaded + - uses: actions/upload-artifact@v3 + with: + name: output_shps + path: ./data/processed/tests/coastlines_tests.shp.zip + + push_ecr: + needs: [test] + runs-on: ubuntu-latest + + # Only run on a push to the main branch OR a release + if: (github.event_name == 'push' && github.ref == 'refs/heads/main') || (github.event_name == 'release') + + steps: + - name: Checkout code + uses: actions/checkout@v3 + + - name: Configure AWS credentials + uses: aws-actions/configure-aws-credentials@v1 + with: + role-to-assume: arn:aws:iam::538673716275:role/github-actions-role + aws-region: ap-southeast-2 + + - name: Get tag for this build if it exists + if: github.event_name == 'release' + run: | + echo "RELEASE=${GITHUB_REF/refs\/tags\/}" >> $GITHUB_ENV + + - name: Push release image to ECR + uses: whoan/docker-build-with-cache-action@master + if: github.event_name == 'release' + with: + registry: 538673716275.dkr.ecr.ap-southeast-2.amazonaws.com + image_name: ${{ env.IMAGE_NAME }} + image_tag: ${{ env.RELEASE }} + + - name: Get git commit hash for push to main + if: github.event_name != 'release' + run: | + echo "TAG=dev$(git rev-parse --short HEAD)" \ + >> $GITHUB_ENV + + - name: Push unstable image to ECR + uses: whoan/docker-build-with-cache-action@master + if: github.event_name != 'release' + with: + registry: 538673716275.dkr.ecr.ap-southeast-2.amazonaws.com + image_name: ${{ env.IMAGE_NAME }} + image_tag: latest,${{ env.TAG }} \ No newline at end of file diff --git a/.github/workflows/docker.yaml b/.github/workflows/docker.yaml deleted file mode 100644 index 13d7a611..00000000 --- a/.github/workflows/docker.yaml +++ /dev/null @@ -1,59 +0,0 @@ -# name: Build and push image - -# # Run action on both a push to the "develop" branch, -# # and when a Github release is created/edited/published -# on: -# push: -# branches: -# - develop -# paths: -# - 'coastlines/**' -# - '.github/workflows/docker.yaml' -# - 'Dockerfile' - -# release: -# types: [created, edited, published] - -# permissions: -# id-token: write # This is required for requesting the JWT -# contents: read # This is required for actions/checkout - -# env: -# IMAGE_NAME: geoscienceaustralia/dea-coastlines - -# jobs: -# push_ecr: -# runs-on: ubuntu-latest -# steps: -# - name: Checkout code -# uses: actions/checkout@v3 - -# # If action is triggered by a release, push image to -# # Dockerhub using custom image tag extracted from the release -# - name: Get current version tag from release to use as image tag -# if: github.event_name == 'release' -# run: | -# echo "RELEASE=${GITHUB_REF/refs\/tags\/}" >> $GITHUB_ENV - -# # If action is trigged by a push (not release), push a -# # latest/unstable image to Dockerhub using image tag based -# # on the most recent Github tag and commit hash -# - name: Get git commit hash for push to branch to use as image tag -# if: github.event_name != 'release' -# run: | -# git fetch --all --tags -# echo "RELEASE=$(git describe --tags)" >> $GITHUB_ENV - -# - name: Configure AWS credentials -# uses: aws-actions/configure-aws-credentials@v1 -# with: -# role-to-assume: arn:aws:iam::538673716275:role/github-actions-role -# aws-region: ap-southeast-2 - -# - name: Push image to ECR -# uses: whoan/docker-build-with-cache-action@master -# with: -# context: ./ -# registry: 538673716275.dkr.ecr.ap-southeast-2.amazonaws.com -# image_name: ${{ env.IMAGE_NAME }} -# image_tag: latest,${{ env.RELEASE }} diff --git a/.github/workflows/test.yaml b/.github/workflows/test.yaml deleted file mode 100644 index 8bfb4560..00000000 --- a/.github/workflows/test.yaml +++ /dev/null @@ -1,109 +0,0 @@ - -# --- -# name: Tests - -# on: -# pull_request: -# branches: -# - 'develop' -# - 'tests_validation' -# paths: -# - '**' -# - '.github/workflows/test.yml' -# - '!docs/**' -# - '!*.rst' -# - '!*.md' -# workflow_dispatch: - -# push: -# branches: -# - 'develop' -# - 'tests_validation' -# paths: -# - '**' -# - '.github/workflows/test.yml' -# - '!docs/**' -# - '!*.rst' -# - '!*.md' - -# permissions: -# id-token: write # This is required for requesting the JWT -# contents: write # This is required for actions/checkout - -# jobs: -# integration-tests: -# runs-on: ubuntu-latest - -# steps: -# - uses: actions/checkout@v2 -# with: -# fetch-depth: 0 - -# - name: Configure AWS credentials from Test account -# uses: aws-actions/configure-aws-credentials@v1 -# with: -# role-to-assume: arn:aws:iam::538673716275:role/github-actions-dea-coastlines-s3-role -# aws-region: ap-southeast-2 - -# - name: Copy files to the test website with the AWS CLI -# run: | -# aws s3 sync s3://dea-non-public-data/tide_models/tide_models/fes2014 tide_models/fes2014 -# aws s3 sync s3://dea-non-public-data/tide_models/tide_models/hamtide tide_models/hamtide - -# - name: Run dockerized integration tests and copy outputs -# run: | -# # Set up artifacts directory to house outputs from integration tests, -# # giving all users read and write permissions -# mkdir artifacts -# chmod a+rw artifacts - -# # Run integration tests using Docker -# docker-compose up -d -# docker-compose exec -T coastline /bin/sh -c "sh ./docker/coastline/run_tests" -# docker-compose down - -# # Copy out validation outputs produced by the integration tests and place them -# # in correct output locations so they can be committed back into the repository -# cp ./artifacts/stats_tests.png ./tests/stats_tests.png -# cp ./artifacts/stats_tests.csv ./data/validation/processed/stats_tests.csv -# cp ./artifacts/README.md ./tests/README.md - -# # - name: Setup upterm session -# # uses: lhotari/action-upterm@v1 - -# # Commit validation results produced by integration tests back into repo -# - uses: stefanzweifel/git-auto-commit-action@v4 -# with: -# commit_message: Automatically update integration test validation results -# file_pattern: 'tests/stats_tests.png data/validation/processed/stats_tests.csv tests/README.md' - -# # Add output GeoPackage data to Actions artifact so it can be downloaded -# - uses: actions/upload-artifact@v3 -# with: -# name: output_geopackage -# path: ./artifacts/coastlines_tests.gpkg - -# # Add output ESRI Shapefile data to Actions artifact so it can be downloaded -# - uses: actions/upload-artifact@v3 -# with: -# name: output_shps -# path: ./artifacts/coastlines_tests.shp.zip - -# # Add output test results 1 -# - uses: actions/upload-artifact@v3 -# with: -# name: test_results -# path: ./artifacts/stats_tests.png - -# # Add output test results 2 -# - uses: actions/upload-artifact@v3 -# with: -# name: test_results -# path: ./artifacts/stats_tests.csv - -# # Update code coverage -# - name: Upload coverage to Codecov -# uses: codecov/codecov-action@v3 -# with: -# directory: ./artifacts/ -# fail_ci_if_error: false From b9a9cd3d68a7d40d1119652c135861f29f50ea88 Mon Sep 17 00:00:00 2001 From: robbibt Date: Fri, 2 Aug 2024 00:36:08 +0000 Subject: [PATCH 43/45] Automatically update integration test validation results --- tests/README.md | 10 +++++----- tests/stats_tests.csv | 1 + tests/stats_tests.png | Bin 96061 -> 96357 bytes 3 files changed, 6 insertions(+), 5 deletions(-) diff --git a/tests/README.md b/tests/README.md index 9df406bc..538565e0 100644 --- a/tests/README.md +++ b/tests/README.md @@ -15,11 +15,11 @@ In addition to testing whether the code runs without errors, we also run a small ## Latest integration test validation results -The latest integration test completed at **2024-08-02 10:15**. Compared to the previous run, it had an: -- RMSE accuracy of **6.15 m (:heavy_minus_sign: no change)** -- MAE accuracy of **4.85 m (:heavy_minus_sign: no change)** -- Bias of **-2.65 m (:heavy_minus_sign: no change)** -- Pearson correlation of **0.975 (:heavy_minus_sign: no change)** +The latest integration test completed at **2024-08-02 10:36**. Compared to the previous run, it had an: +- RMSE accuracy of **6.15 m ( :heavy_minus_sign: no change)** +- MAE accuracy of **4.85 m ( :heavy_minus_sign: no change)** +- Bias of **-2.65 m ( :heavy_minus_sign: no change)** +- Pearson correlation of **0.975 ( :heavy_minus_sign: no change)** \ No newline at end of file diff --git a/tests/stats_tests.csv b/tests/stats_tests.csv index 2c1e5313..ceb35018 100644 --- a/tests/stats_tests.csv +++ b/tests/stats_tests.csv @@ -37,3 +37,4 @@ time,n,mae,rmse,stdev,corr,bias,name 2024-08-01 06:58:39.701964,2669.0,4.85,6.15,5.57,0.975,-2.65,tests 2024-08-01 10:41:29.546023,2669.0,4.85,6.15,5.57,0.975,-2.65,tests 2024-08-02 00:15:55.377300,2669.0,4.85,6.15,5.57,0.975,-2.65,tests +2024-08-02 00:36:06.849345,2669.0,4.85,6.15,5.57,0.975,-2.65,tests diff --git a/tests/stats_tests.png b/tests/stats_tests.png index dc6ff66b1333d9df426dcba6321dd9e217a61af1..1ef6f747ff45152bde28d45c8b4c19de21659910 100644 GIT binary patch literal 96357 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Update vector.py --- coastlines/vector.py | 2 -- 1 file changed, 2 deletions(-) diff --git a/coastlines/vector.py b/coastlines/vector.py index c6ef9e8a..949fd9df 100644 --- a/coastlines/vector.py +++ b/coastlines/vector.py @@ -11,8 +11,6 @@ # * Compute rates of coastal change at every 30 m of coastline # using linear regression -# Test tests - import glob import os import sys From d26754264c3c72257d4dc180c208e68084816527 Mon Sep 17 00:00:00 2001 From: robbibt Date: Fri, 2 Aug 2024 00:58:44 +0000 Subject: [PATCH 45/45] Automatically update integration test validation results --- tests/README.md | 2 +- tests/stats_tests.csv | 1 + tests/stats_tests.png | Bin 96357 -> 96346 bytes 3 files changed, 2 insertions(+), 1 deletion(-) diff --git a/tests/README.md b/tests/README.md index 538565e0..13d07f65 100644 --- a/tests/README.md +++ b/tests/README.md @@ -15,7 +15,7 @@ In addition to testing whether the code runs without errors, we also run a small ## Latest integration test validation results -The latest integration test completed at **2024-08-02 10:36**. Compared to the previous run, it had an: +The latest integration test completed at **2024-08-02 10:58**. Compared to the previous run, it had an: - RMSE accuracy of **6.15 m ( :heavy_minus_sign: no change)** - MAE accuracy of **4.85 m ( :heavy_minus_sign: no change)** - Bias of **-2.65 m ( :heavy_minus_sign: no change)** diff --git a/tests/stats_tests.csv b/tests/stats_tests.csv index ceb35018..cbe61aa8 100644 --- a/tests/stats_tests.csv +++ b/tests/stats_tests.csv @@ -38,3 +38,4 @@ time,n,mae,rmse,stdev,corr,bias,name 2024-08-01 10:41:29.546023,2669.0,4.85,6.15,5.57,0.975,-2.65,tests 2024-08-02 00:15:55.377300,2669.0,4.85,6.15,5.57,0.975,-2.65,tests 2024-08-02 00:36:06.849345,2669.0,4.85,6.15,5.57,0.975,-2.65,tests +2024-08-02 00:58:41.932746,2669.0,4.85,6.15,5.57,0.975,-2.65,tests diff --git a/tests/stats_tests.png b/tests/stats_tests.png index 1ef6f747ff45152bde28d45c8b4c19de21659910..1018d2382fd993f01ebf172aabee6267ac5c1997 100644 GIT binary patch delta 65189 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