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FIX: fix recipe4.ipynb, try always have 24 fitting volumes #96

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Nov 6, 2024
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FIX: fix recipe4.ipynb, try always have 24 fitting volumes #96

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28 changes: 21 additions & 7 deletions notebooks/workflow/recipe4.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -18,9 +18,9 @@
"source": [
"# Load ODIM_H5 Volume data from German Weather Service\n",
"\n",
"In this example, we obtain and read the latest 30 minutes of available volumetric radar data from German Weather Service available at [opendata.dwd.de](https://opendata.dwd.de). Finally we do some plotting.\n",
"In this example, we obtain and read the last 2 hours of available volumetric radar data from German Weather Service available at [opendata.dwd.de](https://opendata.dwd.de). Finally we do some plotting.\n",
"\n",
"This retrieves 6 timesteps of the 10 sweeps (moments DBZH and VRADH) of the DWD volume scan of a distinct radar. This amounts to 120 data files which are combined into one volumetric Cf/Radial2 like xarray powered structure.\n",
"This retrieves 24 timesteps of the 10 sweeps (moments DBZH and VRADH) of the DWD volume scan of a distinct radar. This amounts to 480 data files which are combined into one volumetric Cf/Radial2 like xarray powered structure.\n",
"\n",
"Exports to single file Odim_H5 and Cf/Radial2 format are shown at the end of this tutorial.\n",
"\n",
Expand Down Expand Up @@ -162,13 +162,13 @@
"metadata": {},
"outputs": [],
"source": [
"for f in filelist1[: 10 * 24]:\n",
"for f in filelist1[: 10 * 25]:\n",
" with http.request(\n",
" \"GET\", os.path.join(opendata_url1, f), preload_content=False\n",
" ) as r, open(f, \"wb\") as out:\n",
" shutil.copyfileobj(r, out)\n",
"\n",
"for f in filelist2[: 10 * 24]:\n",
"for f in filelist2[: 10 * 25]:\n",
" with http.request(\n",
" \"GET\", os.path.join(opendata_url2, f), preload_content=False\n",
" ) as r, open(f, \"wb\") as out:\n",
Expand All @@ -194,8 +194,7 @@
"volume_reflectivity = np.array(\n",
" sorted(volume_reflectivity, key=lambda x: x.split(\"-\")[2])\n",
")\n",
"volume_velocity = np.array(sorted(volume_velocity, key=lambda x: x.split(\"-\")[2]))\n",
"volume_reflectivity[:15]"
"volume_velocity = np.array(sorted(volume_velocity, key=lambda x: x.split(\"-\")[2]))"
]
},
{
Expand All @@ -208,6 +207,15 @@
"volume_velocity = volume_velocity.reshape(-1, 10).T"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"volume_reflectivity"
]
},
{
"cell_type": "code",
"execution_count": null,
Expand Down Expand Up @@ -282,7 +290,13 @@
"metadata": {},
"outputs": [],
"source": [
"dsl[0]"
"vt_min = np.array([dsl[i].volume_time.min().values for i in range(10)])\n",
"vt_max = np.array([dsl[i].volume_time.max().values for i in range(10)])\n",
"if not all((vt_min == vt_min[0])):\n",
" dsl = [ds.sel(volume_time=slice(vt_min.max(), vt_max.min())) for ds in dsl]\n",
"else:\n",
" dsl = [ds.isel(volume_time=slice(1, -1)) for ds in dsl]\n",
"dsl = sorted(dsl, key=lambda ds: ds.time.min().values)"
]
},
{
Expand Down
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