Fix notebooks

GeoscienceAustralia · Oct 15, 2024 · 4bae3cb · 4bae3cb
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diff --git a/docs/notebooks/Case_study_intertidal.ipynb b/docs/notebooks/Case_study_intertidal.ipynb
diff --git a/docs/notebooks/Tide_statistics.ipynb b/docs/notebooks/Tide_statistics.ipynb
@@ -344,7 +344,11 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Calculate biases for multiple satellite sensors"
+    "## Calculate biases for multiple satellite sensors\n",
+    "At our location, Sentinel-2 optical satellites are biased towards high tide observations, while Sentinel-1 radar satellites are biased towards low tide observations. \n",
+    "Could combining data from multiple EO sensors help us capture a more complete view of tides at this location?\n",
+    "\n",
+    "To test this theory, we can combine Sentinel-2 and Sentinel-1 data into a single `xarray.Dataset`, recording the name of each sensor using a new `satellite_name` coordinate in our data:"
    ]
   },
   {
@@ -379,7 +383,16 @@
     "\n",
     "# Combine both Sentinel-1 and Sentinel-2 data into a single dataset\n",
     "ds_all = xr.concat([ds_s1, ds_s2], dim=\"time\")\n",
-    "print(ds_all)\n"
+    "print(ds_all)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can now run `tide_stats` again.\n",
+    "This time, we pass our satellite name coordinate to the function using the `plot_col=\"satellite_name\"` parameter.\n",
+    "This will plot data from each of our satellites using a different symbol."
    ]
   },
   {
@@ -429,6 +442,27 @@
     "    directory=\"../../tests/data/tide_models\",\n",
     ")\n"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can see that at this location, combining Sentinel-2 and Sentinel-1 data greatly improves our biases: our satellite data now covers ~85% of the modelled astronomical tide range, and only fails to observe 10% of the highest tides and 6% of the lowest tides!"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Next steps\n",
+    "\n",
+    "We have explored calculating tide statistics and biases in EO data. Now we can learn how to validate modelled tides against [measured tide gauge data](../Validating_tides) to ensure the tides we are modelling are accurate."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": []
   }
  ],
  "metadata": {
@@ -447,7 +481,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.0"
+   "version": "3.12.1"
   }
  },
  "nbformat": 4,

diff --git a/docs/notebooks/Validating_tides.ipynb b/docs/notebooks/Validating_tides.ipynb
@@ -141,9 +141,6 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/workspaces/eo-tides/.venv/lib/python3.12/site-packages/geopandas/array.py:403: UserWarning: Geometry is in a geographic CRS. Results from 'sjoin_nearest' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n",
-      "\n",
-      "  warnings.warn(\n",
       "/workspaces/eo-tides/eo_tides/validation.py:157: FutureWarning: Support for nested sequences for 'parse_dates' in pd.read_csv is deprecated. Combine the desired columns with pd.to_datetime after parsing instead.\n",
       "  pd.read_csv(\n"
      ]
@@ -194,19 +191,11 @@
     "joined_df.plot.scatter(x=\"sea_level\", y=\"tide_height\")\n",
     "eval_metrics(x=joined_df.sea_level, y=joined_df.tide_height)"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "9427ee6f-0db7-47a5-86e1-1617f9372c6c",
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": ".venv",
    "language": "python",
    "name": "python3"
   },
@@ -220,7 +209,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.1"
+   "version": "3.12.0"
   }
  },
  "nbformat": 4,

diff --git a/eo_tides/validation.py b/eo_tides/validation.py
@@ -267,7 +267,9 @@ def load_gauge_gesla(
 
     # If x and y are single numbers, select nearest row
     elif isinstance(x, Number) & isinstance(y, Number):
-        site_code = _nearest_row(metadata_gdf, x, y, max_distance).site_code
+        with warnings.catch_warnings():
+            warnings.simplefilter("ignore")
+            site_code = _nearest_row(metadata_gdf, x, y, max_distance).site_code
 
         # Raise exception if no valid tide gauges are found
         if site_code.isnull().all():