WPS returns datasets : access band_data variable (#356)

In notebook 02 using the PAVICS beta image `stats_resp.get(asobj=True)` returns an `xr.Dataset` ... plotting requires accessing the `band_data` variable See Ouranosinc/pavics-jupyter-env-issues#7 Note this will break the notebook when using `current` image. Do not merge until all fixes are ready Fix for Ouranosinc/PAVICS-e2e-workflow-tests#121.
CSHS-CWRA · May 9, 2024 · 1f5be4e · 1f5be4e
2 parents 0676b1c + 6ff9f29
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diff --git a/docs/notebooks/02_Extract_geographical_watershed_properties.ipynb b/docs/notebooks/02_Extract_geographical_watershed_properties.ipynb
@@ -405,6 +405,13 @@
     "all_properties = {**shape_info, **land_use, **terrain}\n",
     "display(all_properties)"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
@@ -418,7 +425,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.16"
+   "version": "3.10.13"
   }
  },
  "nbformat": 4,

diff --git a/docs/notebooks/paper/Perform_a_climate_change_impact_study_on_a_watershed.ipynb b/docs/notebooks/paper/Perform_a_climate_change_impact_study_on_a_watershed.ipynb
@@ -77,6 +77,7 @@
     "import xclim.sdba as sdba\n",
     "from birdy import WPSClient\n",
     "from clisops.core import average, subset\n",
+    "from dask.diagnostics import ProgressBar\n",
     "\n",
     "from ravenpy import Emulator\n",
     "from ravenpy.config import commands as rc\n",
@@ -399,7 +400,7 @@
     "    ERA5_pr = ERA5_pr.mean({\"latitude\", \"longitude\"})\n",
     "\n",
     "    # Ensure that the precipitation is non-negative, which can happen with some reanalysis models.\n",
-    "    ERA5_pr[ERA5_pr < 0] = 0\n",
+    "    ERA5_pr = np.maximum(ERA5_pr, 0)\n",
     "\n",
     "    # Transform them to a dataset such that they can be written with attributes to netcdf\n",
     "    ERA5_tmin = ERA5_tmin.to_dataset(name=\"tmin\", promote_attrs=True)\n",
@@ -463,21 +464,20 @@
     "            col_subset = col.search(require_all_on=[\"source_id\"], **query)\n",
     "            mapper = fsCMIP.get_mapper(col_subset.df.zstore[0])\n",
     "\n",
-    "            # special case for precipitation, which does not have the \"height\" variable that we need to discard as for tasmax and tasmin.\n",
-    "            if variable == \"pr\":\n",
-    "                out[exp][variable] = average.average_shape(\n",
-    "                    xr.open_zarr(mapper, consolidated=True).sel(\n",
-    "                        time=slice(period_start, period_end)\n",
-    "                    )[variable],\n",
-    "                    basin_contour,\n",
-    "                ).chunk(-1)\n",
-    "            else:\n",
-    "                out[exp][variable] = average.average_shape(\n",
-    "                    xr.open_zarr(mapper, consolidated=True)\n",
-    "                    .sel(time=slice(period_start, period_end))\n",
-    "                    .reset_coords(\"height\", drop=True)[variable],\n",
-    "                    basin_contour,\n",
-    "                ).chunk(-1)\n",
+    "            ds = xr.open_zarr(mapper, consolidated=True).sel(\n",
+    "                time=slice(period_start, period_end)\n",
+    "            )\n",
+    "\n",
+    "            if \"height\" in ds.coords:\n",
+    "                ds = ds.drop_vars(\"height\")\n",
+    "\n",
+    "            out[exp][variable] = average.average_shape(\n",
+    "                ds,\n",
+    "                basin_contour,\n",
+    "            )[\n",
+    "                variable\n",
+    "            ].chunk(-1)\n",
+    "\n",
     "\n",
     "# We can now extract the variables that we will need later:\n",
     "historical_tasmax = out[\"historical\"][\"tasmax\"]\n",
@@ -633,15 +633,16 @@
     "    ]\n",
     ")\n",
     "# Write to temporary folder\n",
-    "fn_tmp_fut = tmp / \"future_dataset_tmp.nc\"\n",
-    "fut_dataset.to_netcdf(fn_tmp_fut)\n",
+    "with ProgressBar():\n",
+    "    fn_tmp_fut = tmp / \"future_dataset_tmp.nc\"\n",
+    "    fut_dataset.to_netcdf(fn_tmp_fut)\n",
     "\n",
-    "# Write the data to disk to a temporary location for future use.\n",
-    "ref_dataset = xr.open_dataset(fn_tmp_ref)\n",
-    "ref_dataset.isel(geom=0).squeeze().to_netcdf(tmp / \"reference_dataset.nc\")\n",
+    "    # Write the data to disk to a temporary location for future use.\n",
+    "    ref_dataset = xr.open_dataset(fn_tmp_ref)\n",
+    "    ref_dataset.isel(geom=0).squeeze().to_netcdf(tmp / \"reference_dataset.nc\")\n",
     "\n",
-    "fut_dataset = xr.open_dataset(fn_tmp_fut)\n",
-    "fut_dataset.isel(geom=0).squeeze().to_netcdf(tmp / \"future_dataset.nc\")"
+    "    fut_dataset = xr.open_dataset(fn_tmp_fut)\n",
+    "    fut_dataset.isel(geom=0).squeeze().to_netcdf(tmp / \"future_dataset.nc\")"
    ]
   },
   {
@@ -826,11 +827,10 @@
    "source": [
     "# Copy the configuration of the previous model that we will modify for our validation:\n",
     "model_validation = model_config.duplicate(\n",
-    "    params=optimized_parameters,\n",
     "    StartDate=dt.datetime(1986, 1, 1),\n",
     "    EndDate=dt.datetime(1990, 12, 31),\n",
     "    SuppressOutput=False,\n",
-    ")\n",
+    ").set_params(optimized_parameters)\n",
     "\n",
     "sim_output = Emulator(config=model_validation).run()\n",
     "\n",
@@ -1007,7 +1007,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.16"
+   "version": "3.11.6"
   }
  },
  "nbformat": 4,