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Merge remote-tracking branch 'origin/argo' into argo
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RomiP committed Dec 6, 2023
2 parents 089f71e + 79ecc27 commit 377d3c0
Showing 1 changed file with 23 additions and 11 deletions.
34 changes: 23 additions & 11 deletions doc/source/example_notebooks/QUEST_argo_data_access.ipynb
Original file line number Diff line number Diff line change
@@ -325,7 +325,7 @@
"source": [
"filename = 'processed_ATL03_20220419002753_04111506_006_02.h5'\n",
"\n",
"reader = ipx.Read(source=path+filename)"
"reader = ipx.Read(data_source=path+filename)"
]
},
{
@@ -361,19 +361,31 @@
"user_expressions": []
},
"source": [
"To make the data more easily plottable, let's convert the data into a Pandas DataFrame. Note that this method is memory-intensive for ATL03 data, so users are suggested to look at small spatial domains to prevent the notebook from crashing."
"To make the data more easily plottable, let's convert the data into a Pandas DataFrame. Note that this method is memory-intensive for ATL03 data, so users are suggested to look at small spatial domains to prevent the notebook from crashing. Here, since we only have data from one granule and ground track, we have sped up the conversion to a dataframe by first removing extra xarray dimensions we don't need for our plots. Several of the other steps completed below have analogous operations in xarray that would further reduce memory requirements and computation times."
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "bc086db7-f5a1-4ba7-ba90-5b19afaf6808",
"metadata": {
"tags": []
},
"id": "50d23a8e",
"metadata": {},
"outputs": [],
"source": [
"is2_pd =(ds.squeeze()\n",
" .reset_coords()\n",
" .drop_vars([\"source_file\",\"data_start_utc\",\"data_end_utc\",\"gran_idx\"])\n",
" .to_dataframe()\n",
" )"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "01bb5a12",
"metadata": {},
"outputs": [],
"source": [
"is2_pd = ds.to_dataframe()"
"is2_pd"
]
},
{
@@ -385,9 +397,9 @@
},
"outputs": [],
"source": [
"# Rearrange the data to only include \"ocean\" photons\n",
"is2_pd = is2_pd.reset_index(level=[0,1,2])\n",
"is2_pd_ocean = is2_pd[is2_pd.index==1]\n",
"# Create a new dataframe with only \"ocean\" photons, as indicated by the \"ds_surf_type\" flag\n",
"is2_pd = is2_pd.reset_index(level=[0,1])\n",
"is2_pd_ocean = is2_pd[is2_pd.ds_surf_type==1].drop(columns=\"photon_idx\")\n",
"is2_pd_ocean"
]
},
@@ -446,7 +458,7 @@
"outputs": [],
"source": [
"# Drop time variables that would cause errors in explore() function\n",
"is2_gdf = is2_gdf.drop(['data_start_utc','data_end_utc','delta_time','atlas_sdp_gps_epoch'], axis=1)"
"is2_gdf = is2_gdf.drop(['delta_time','atlas_sdp_gps_epoch'], axis=1)"
]
},
{

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