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[pre-commit.ci] pre-commit autoupdate #3

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80515cd
[pre-commit.ci] pre-commit autoupdate
pre-commit-ci[bot] Apr 20, 2026
1ac6ee2
[pre-commit.ci] auto fixes from pre-commit.com hooks
pre-commit-ci[bot] Apr 20, 2026
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2 changes: 1 addition & 1 deletion .gitignore
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Original file line number Diff line number Diff line change
Expand Up @@ -162,4 +162,4 @@ ciccada/


*.csv
*.png
*.png
4 changes: 2 additions & 2 deletions .pre-commit-config.yaml
100755 → 100644
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Expand Up @@ -2,7 +2,7 @@
# See https://pre-commit.com/hooks.html for more hooks
repos:
- repo: https://github.com/pre-commit/pre-commit-hooks
rev: v5.0.0
rev: v6.0.0
hooks:
- id: trailing-whitespace
- id: end-of-file-fixer
Expand All @@ -11,7 +11,7 @@ repos:
exclude: ^uv.lock$
- repo: https://github.com/astral-sh/ruff-pre-commit
# Ruff version.
rev: v0.8.2
rev: v0.15.11
hooks:
# Run the linter.
- id: ruff
Expand Down
45 changes: 23 additions & 22 deletions BOM_NCI/Get_ALL_postcodes_ABS.ipynb
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Expand Up @@ -8,12 +8,14 @@
"outputs": [],
"source": [
"import sys\n",
"sys.path.append('../') \n",
"from visualisation import *\n",
"import xarray as xr\n",
"\n",
"sys.path.append(\"../\")\n",
"import dask\n",
"import geopandas as gpd\n",
"import xarray as xr\n",
"from shapely.geometry import Point\n",
"\n",
"from visualisation import *\n",
"# crs = EPSG:4326 (WGS 84)"
]
},
Expand All @@ -36,7 +38,7 @@
],
"source": [
"bom_path = \"/home/hossein/CICCADA/BOM_NCI/2023/01/01/\"\n",
"files = glob(bom_path+\"*.nc\")\n",
"files = glob(bom_path + \"*.nc\")\n",
"len(files)"
]
},
Expand All @@ -57,13 +59,13 @@
"source": [
"df = [xr.open_dataset(file).to_dataframe() for file in files[:15]]\n",
"df = pd.concat(df, axis=0).reset_index(drop=False)\n",
"df = df.dropna(subset='direct_normal_irradiance').reset_index(drop=True)\n",
"df['julian_date'] = pd.to_datetime(df['julian_date'], origin='julian', unit='D')\n",
"df = df[['latitude', 'longitude']].drop_duplicates().reset_index(drop=True)\n",
"df = df.dropna(subset=\"direct_normal_irradiance\").reset_index(drop=True)\n",
"df[\"julian_date\"] = pd.to_datetime(df[\"julian_date\"], origin=\"julian\", unit=\"D\")\n",
"df = df[[\"latitude\", \"longitude\"]].drop_duplicates().reset_index(drop=True)\n",
"# df = df.query(f\"latitude >= -35 & latitude <= -34.6 & longitude >= 138.5 & longitude <= 138.8\").reset_index(drop=True)\n",
"df['geometry'] = [Point(x,y) for x,y in zip(df['longitude'], df['latitude'])]\n",
"geo_list = df['geometry'].unique()\n",
"print('len(geo_list): ', len(geo_list))"
"df[\"geometry\"] = [Point(x, y) for x, y in zip(df[\"longitude\"], df[\"latitude\"])]\n",
"geo_list = df[\"geometry\"].unique()\n",
"print(\"len(geo_list): \", len(geo_list))"
]
},
{
Expand All @@ -73,7 +75,9 @@
"metadata": {},
"outputs": [],
"source": [
"gdf = gpd.GeoDataFrame(df[['longitude', 'latitude', 'geometry']], geometry='geometry', crs='EPSG:4326') # assuming WGS84"
"gdf = gpd.GeoDataFrame(\n",
" df[[\"longitude\", \"latitude\", \"geometry\"]], geometry=\"geometry\", crs=\"EPSG:4326\"\n",
") # assuming WGS84"
]
},
{
Expand All @@ -83,8 +87,8 @@
"metadata": {},
"outputs": [],
"source": [
"gdf_postcodes = gpd.read_file('POA_2021_AUST_GDA2020_SHP/POA_2021_AUST_GDA2020.shp')\n",
"gdf_postcodes = gdf_postcodes.to_crs('EPSG:4326') # Ensure same CRS"
"gdf_postcodes = gpd.read_file(\"POA_2021_AUST_GDA2020_SHP/POA_2021_AUST_GDA2020.shp\")\n",
"gdf_postcodes = gdf_postcodes.to_crs(\"EPSG:4326\") # Ensure same CRS"
]
},
{
Expand Down Expand Up @@ -153,10 +157,7 @@
"outputs": [],
"source": [
"gdf_joined = gpd.sjoin(\n",
" gdf,\n",
" gdf_postcodes[['POA_CODE21', 'geometry']],\n",
" how='left',\n",
" predicate='within'\n",
" gdf, gdf_postcodes[[\"POA_CODE21\", \"geometry\"]], how=\"left\", predicate=\"within\"\n",
")"
]
},
Expand All @@ -167,7 +168,7 @@
"metadata": {},
"outputs": [],
"source": [
"gdf_joined.drop(columns=['index_right'], inplace=True)\n",
"gdf_joined.drop(columns=[\"index_right\"], inplace=True)\n",
"gdf_joined = gdf_joined.dropna().reset_index(drop=True)"
]
},
Expand All @@ -178,7 +179,7 @@
"metadata": {},
"outputs": [],
"source": [
"gdf_joined.to_csv('bom_postcodes_points.csv', index=False)"
"gdf_joined.to_csv(\"bom_postcodes_points.csv\", index=False)"
]
},
{
Expand All @@ -188,7 +189,7 @@
"metadata": {},
"outputs": [],
"source": [
"gdf_postcodes['geometry'][0]"
"gdf_postcodes[\"geometry\"][0]"
]
},
{
Expand Down Expand Up @@ -265,7 +266,7 @@
],
"source": [
"fig, ax = plt.subplots()\n",
"gdf_postcodes.plot(ax=ax, facecolor='none', edgecolor='black')\n"
"gdf_postcodes.plot(ax=ax, facecolor=\"none\", edgecolor=\"black\")"
]
},
{
Expand All @@ -275,7 +276,7 @@
"metadata": {},
"outputs": [],
"source": [
"gdf.plot(ax=ax, color='red', markersize=2)\n",
"gdf.plot(ax=ax, color=\"red\", markersize=2)\n",
"plt.show()"
]
}
Expand Down
60 changes: 38 additions & 22 deletions BOM_NCI/Get_ALL_postcodes_GNAF.ipynb
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Expand Up @@ -8,13 +8,15 @@
"outputs": [],
"source": [
"import sys\n",
"sys.path.append('../') \n",
"from visualisation import *\n",
"import xarray as xr\n",
"\n",
"sys.path.append(\"../\")\n",
"import dask\n",
"import geopandas as gpd\n",
"import xarray as xr\n",
"from shapely.geometry import Point\n",
"from sklearn.neighbors import KDTree\n",
"\n",
"from visualisation import *\n",
"# crs = EPSG:4326 (WGS 84)"
]
},
Expand All @@ -37,7 +39,7 @@
],
"source": [
"bom_path = \"/home/hossein/CICCADA/BOM_NCI/2023/01/01/\"\n",
"files = glob(bom_path+\"*.nc\")\n",
"files = glob(bom_path + \"*.nc\")\n",
"len(files)"
]
},
Expand All @@ -50,9 +52,9 @@
"source": [
"df = [xr.open_dataset(file).to_dataframe() for file in files[:15]]\n",
"df = pd.concat(df, axis=0).reset_index(drop=False)\n",
"df = df.dropna(subset='direct_normal_irradiance').reset_index(drop=True)\n",
"df['julian_date'] = pd.to_datetime(df['julian_date'], origin='julian', unit='D')\n",
"df = df[['latitude', 'longitude']].drop_duplicates().reset_index(drop=True)"
"df = df.dropna(subset=\"direct_normal_irradiance\").reset_index(drop=True)\n",
"df[\"julian_date\"] = pd.to_datetime(df[\"julian_date\"], origin=\"julian\", unit=\"D\")\n",
"df = df[[\"latitude\", \"longitude\"]].drop_duplicates().reset_index(drop=True)"
]
},
{
Expand Down Expand Up @@ -113,9 +115,13 @@
"metadata": {},
"outputs": [],
"source": [
"SA_STREET_LOCALITY_POINT_psv = pd.read_csv(glob(f\"{naf_path}SA_STREET_LOCALITY_POINT_psv.psv\")[0], sep='|', low_memory=False).dropna(axis=1)\n",
"SA_ADDRESS_DETAIL_psv = pd.read_csv(glob(f\"{naf_path}SA_ADDRESS_DETAIL_psv.psv\")[0], sep='|', low_memory=False).dropna(axis=1)\n",
"# SA_ADDRESS_DETAIL_psv\n"
"SA_STREET_LOCALITY_POINT_psv = pd.read_csv(\n",
" glob(f\"{naf_path}SA_STREET_LOCALITY_POINT_psv.psv\")[0], sep=\"|\", low_memory=False\n",
").dropna(axis=1)\n",
"SA_ADDRESS_DETAIL_psv = pd.read_csv(\n",
" glob(f\"{naf_path}SA_ADDRESS_DETAIL_psv.psv\")[0], sep=\"|\", low_memory=False\n",
").dropna(axis=1)\n",
"# SA_ADDRESS_DETAIL_psv"
]
},
{
Expand Down Expand Up @@ -292,7 +298,9 @@
"metadata": {},
"outputs": [],
"source": [
"a = pd.read_csv(glob(f\"{naf_path}SA_ADDRESS_DETAIL_psv.psv\")[0], sep='|', low_memory=False)"
"a = pd.read_csv(\n",
" glob(f\"{naf_path}SA_ADDRESS_DETAIL_psv.psv\")[0], sep=\"|\", low_memory=False\n",
")"
]
},
{
Expand Down Expand Up @@ -334,7 +342,7 @@
"metadata": {},
"outputs": [],
"source": [
"5035 in SA_ADDRESS_DETAIL_psv['POSTCODE'].unique()"
"5035 in SA_ADDRESS_DETAIL_psv[\"POSTCODE\"].unique()"
]
},
{
Expand All @@ -344,7 +352,7 @@
"metadata": {},
"outputs": [],
"source": [
"SA_ADDRESS_DETAIL_psv['POSTCODE'].unique().shape"
"SA_ADDRESS_DETAIL_psv[\"POSTCODE\"].unique().shape"
]
},
{
Expand All @@ -365,8 +373,14 @@
}
],
"source": [
"locaility_points = SA_STREET_LOCALITY_POINT_psv[['STREET_LOCALITY_PID', 'LONGITUDE', 'LATITUDE']].merge(SA_ADDRESS_DETAIL_psv[['STREET_LOCALITY_PID', 'POSTCODE']].drop_duplicates(), on='STREET_LOCALITY_PID', how='left')\n",
"locaility_points.drop(columns=['STREET_LOCALITY_PID'], inplace=True)\n",
"locaility_points = SA_STREET_LOCALITY_POINT_psv[\n",
" [\"STREET_LOCALITY_PID\", \"LONGITUDE\", \"LATITUDE\"]\n",
"].merge(\n",
" SA_ADDRESS_DETAIL_psv[[\"STREET_LOCALITY_PID\", \"POSTCODE\"]].drop_duplicates(),\n",
" on=\"STREET_LOCALITY_PID\",\n",
" how=\"left\",\n",
")\n",
"locaility_points.drop(columns=[\"STREET_LOCALITY_PID\"], inplace=True)\n",
"locaility_points.dropna(inplace=True)\n",
"locaility_points.columns"
]
Expand All @@ -388,8 +402,8 @@
"metadata": {},
"outputs": [],
"source": [
"postcode_coords = locaility_points[['LATITUDE', 'LONGITUDE']].to_numpy()\n",
"kdtree = KDTree(postcode_coords, metric='euclidean')"
"postcode_coords = locaility_points[[\"LATITUDE\", \"LONGITUDE\"]].to_numpy()\n",
"kdtree = KDTree(postcode_coords, metric=\"euclidean\")"
]
},
{
Expand All @@ -414,9 +428,11 @@
"metadata": {},
"outputs": [],
"source": [
"df['nearest_postcode'] = locaility_points.iloc[nearest_indices]['POSTCODE'].values\n",
"df[\"nearest_postcode\"] = locaility_points.iloc[nearest_indices][\"POSTCODE\"].values\n",
"\n",
"df['distance_km'] = nearest_distances*111 # Rough conversion factor for degrees to kilometers"
"df[\"distance_km\"] = (\n",
" nearest_distances * 111\n",
") # Rough conversion factor for degrees to kilometers"
]
},
{
Expand Down Expand Up @@ -447,7 +463,7 @@
}
],
"source": [
"df0['nearest_postcode'].unique().shape"
"df0[\"nearest_postcode\"].unique().shape"
]
},
{
Expand All @@ -468,7 +484,7 @@
}
],
"source": [
"5035 in df0['nearest_postcode'].unique()"
"5035 in df0[\"nearest_postcode\"].unique()"
]
},
{
Expand All @@ -478,7 +494,7 @@
"metadata": {},
"outputs": [],
"source": [
"df0.to_csv('bom_postcodes_points.csv', index=False)"
"df0.to_csv(\"bom_postcodes_points.csv\", index=False)"
]
}
],
Expand Down
19 changes: 11 additions & 8 deletions BOM_NCI/describe_bom_data.ipynb
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Expand Up @@ -7,10 +7,13 @@
"outputs": [],
"source": [
"import sys\n",
"sys.path.append('../') \n",
"from visualisation import *\n",
"\n",
"sys.path.append(\"../\")\n",
"import concurrent.futures\n",
"\n",
"import xarray as xr\n",
"import concurrent.futures"
"\n",
"from visualisation import *"
]
},
{
Expand All @@ -31,7 +34,7 @@
],
"source": [
"bom_path = \"/home/hossein/CICCADA/BOM_NCI/2023/01/01/\"\n",
"files = glob(bom_path+\"*.nc\")\n",
"files = glob(bom_path + \"*.nc\")\n",
"len(files)"
]
},
Expand All @@ -47,7 +50,7 @@
"# print(ds)\n",
"\n",
"# List all variables\n",
"# print(ds.variables)\n"
"# print(ds.variables)"
]
},
{
Expand All @@ -64,7 +67,7 @@
}
],
"source": [
"print(ds['latitude'].attrs)\n"
"print(ds[\"latitude\"].attrs)"
]
},
{
Expand Down Expand Up @@ -201,12 +204,12 @@
}
],
"source": [
"for key in ('quality_mask','cloud_type'):\n",
"for key in (\"quality_mask\", \"cloud_type\"):\n",
" print(ds[key].long_name)\n",
" print(ds[key].flag_meanings)\n",
" print(ds[key].flag_values)\n",
" print(ds[key].comment)\n",
" print('---------------------------------')"
" print(\"---------------------------------\")"
]
}
],
Expand Down
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