cleanup

bopen · Apr 9, 2024 · 996f169 · 996f169
1 parent 9946700
commit 996f169
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Showing 2 changed files with 36 additions and 6 deletions.
diff --git a/notebooks/wp4/extreme_indices.ipynb b/notebooks/wp4/extreme_indices.ipynb
@@ -41,7 +41,7 @@
     "import icclim\n",
     "import matplotlib.pyplot as plt\n",
     "import xarray as xr\n",
-    "from c3s_eqc_automatic_quality_control import diagnostics, download, plot\n",
+    "from c3s_eqc_automatic_quality_control import diagnostics, download, plot, utils\n",
     "from xarrayMannKendall import Mann_Kendall_test\n",
     "\n",
     "plt.style.use(\"seaborn-v0_8-notebook\")\n",
@@ -96,6 +96,9 @@
     "# Interpolation method\n",
     "interpolation_method = \"bilinear\"\n",
     "\n",
+    "# Area to show\n",
+    "area = [72, -22, 27, 45]\n",
+    "\n",
     "# Chunks for download\n",
     "chunks = {\"year\": 1}"
    ]
@@ -187,7 +190,6 @@
    },
    "outputs": [],
    "source": [
-    "area = [72, -22, 27, 45]\n",
     "request_era = (\n",
     "    \"reanalysis-era5-single-levels\",\n",
     "    {\n",
@@ -556,8 +558,21 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Mask\n",
     "lsm = download.download_and_transform(*request_lsm)[\"lsm\"].squeeze(drop=True)\n",
+    "\n",
+    "# Cutout\n",
+    "regionalise_kwargs = {\n",
+    "    \"lon_slice\": slice(area[1], area[3]),\n",
+    "    \"lat_slice\": slice(area[0], area[2]),\n",
+    "}\n",
+    "lsm = utils.regionalise(lsm, **regionalise_kwargs)\n",
+    "ds_interpolated = utils.regionalise(ds_interpolated, **regionalise_kwargs)\n",
+    "model_datasets = {\n",
+    "    model: utils.regionalise(ds, **regionalise_kwargs)\n",
+    "    for model, ds in model_datasets.items()\n",
+    "}\n",
+    "\n",
+    "# Mask\n",
     "ds_era5 = ds_era5.where(lsm)\n",
     "ds_interpolated = ds_interpolated.where(lsm)\n",
     "model_datasets = {\n",

diff --git a/notebooks/wp4/extreme_indices_future.ipynb b/notebooks/wp4/extreme_indices_future.ipynb
@@ -41,7 +41,7 @@
     "import icclim\n",
     "import matplotlib.pyplot as plt\n",
     "import xarray as xr\n",
-    "from c3s_eqc_automatic_quality_control import diagnostics, download, plot\n",
+    "from c3s_eqc_automatic_quality_control import diagnostics, download, plot, utils\n",
     "from xarrayMannKendall import Mann_Kendall_test\n",
     "\n",
     "plt.style.use(\"seaborn-v0_8-notebook\")\n",
@@ -96,6 +96,9 @@
     "# Interpolation method\n",
     "interpolation_method = \"bilinear\"\n",
     "\n",
+    "# Area to show\n",
+    "area = [72, -22, 27, 45]\n",
+    "\n",
     "# Chunks for download\n",
     "chunks = {\"year\": 1}"
    ]
@@ -182,7 +185,6 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "area = [72, -22, 27, 45]\n",
     "request_lsm = (\n",
     "    \"reanalysis-era5-single-levels\",\n",
     "    {\n",
@@ -602,8 +604,21 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Mask\n",
     "lsm = download.download_and_transform(*request_lsm)[\"lsm\"].squeeze(drop=True)\n",
+    "\n",
+    "# Cutout\n",
+    "regionalise_kwargs = {\n",
+    "    \"lon_slice\": slice(area[1], area[3]),\n",
+    "    \"lat_slice\": slice(area[0], area[2]),\n",
+    "}\n",
+    "lsm = utils.regionalise(lsm, **regionalise_kwargs)\n",
+    "ds_interpolated = utils.regionalise(ds_interpolated, **regionalise_kwargs)\n",
+    "model_datasets = {\n",
+    "    model: utils.regionalise(ds, **regionalise_kwargs)\n",
+    "    for model, ds in model_datasets.items()\n",
+    "}\n",
+    "\n",
+    "# Mask\n",
     "ds_interpolated = ds_interpolated.where(\n",
     "    diagnostics.regrid(lsm, ds_interpolated, method=\"bilinear\")\n",
     ")\n",