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88 changes: 75 additions & 13 deletions docs/notebooks/1_hazard_indicators.ipynb
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Expand Up @@ -66,17 +66,61 @@
"request = {\n",
" \"items\": [\n",
" {\n",
" \"longitudes\": [69.4787, 68.71, 20.1047, 19.8936, 19.6359, 0.5407, 6.9366, 6.935, 13.7319, 13.7319],\n",
" \"latitudes\": [34.556, 35.9416, 39.9116, 41.6796, 42.0137, 35.7835, 36.8789, 36.88, -12.4706, -12.4706],\n",
" \"longitudes\": [\n",
" 69.4787,\n",
" 68.71,\n",
" 20.1047,\n",
" 19.8936,\n",
" 19.6359,\n",
" 0.5407,\n",
" 6.9366,\n",
" 6.935,\n",
" 13.7319,\n",
" 13.7319,\n",
" ],\n",
" \"latitudes\": [\n",
" 34.556,\n",
" 35.9416,\n",
" 39.9116,\n",
" 41.6796,\n",
" 42.0137,\n",
" 35.7835,\n",
" 36.8789,\n",
" 36.88,\n",
" -12.4706,\n",
" -12.4706,\n",
" ],\n",
" \"request_item_id\": \"my_flood_request\",\n",
" \"hazard_type\": \"RiverineInundation\",\n",
" \"indicator_id\": \"flood_depth\",\n",
" \"scenario\": \"historical\",\n",
" \"year\": 1980,\n",
" },\n",
" {\n",
" \"longitudes\": [69.4787, 68.71, 20.1047, 19.8936, 19.6359, 0.5407, 6.9366, 6.935, 13.7319, 13.7319],\n",
" \"latitudes\": [34.556, 35.9416, 39.9116, 41.6796, 42.0137, 35.7835, 36.8789, 36.88, -12.4706, -12.4706],\n",
" \"longitudes\": [\n",
" 69.4787,\n",
" 68.71,\n",
" 20.1047,\n",
" 19.8936,\n",
" 19.6359,\n",
" 0.5407,\n",
" 6.9366,\n",
" 6.935,\n",
" 13.7319,\n",
" 13.7319,\n",
" ],\n",
" \"latitudes\": [\n",
" 34.556,\n",
" 35.9416,\n",
" 39.9116,\n",
" 41.6796,\n",
" 42.0137,\n",
" 35.7835,\n",
" 36.8789,\n",
" 36.88,\n",
" -12.4706,\n",
" -12.4706,\n",
" ],\n",
" \"request_item_id\": \"my_flood_request\",\n",
" \"hazard_type\": \"RiverineInundation\",\n",
" \"indicator_id\": \"flood_depth\",\n",
Expand Down Expand Up @@ -202,36 +246,50 @@
"fig1 = make_subplots(rows=1, cols=2)\n",
"fig1.add_trace(\n",
" go.Scatter(\n",
" x=flood_results_baseline[0][\"index_values\"], y=flood_results_baseline[0][\"intensities\"], name=\"baseline flood\"\n",
" x=flood_results_baseline[0][\"index_values\"],\n",
" y=flood_results_baseline[0][\"intensities\"],\n",
" name=\"baseline flood\",\n",
" ),\n",
" row=1,\n",
" col=1,\n",
")\n",
"fig1.add_trace(\n",
" go.Scatter(\n",
" x=flood_results_rcp585[0][\"index_values\"], y=flood_results_rcp585[0][\"intensities\"], name=\"flood RCP 8.5 2050\"\n",
" x=flood_results_rcp585[0][\"index_values\"],\n",
" y=flood_results_rcp585[0][\"intensities\"],\n",
" name=\"flood RCP 8.5 2050\",\n",
" ),\n",
" row=1,\n",
" col=1,\n",
")\n",
"fig1.update_xaxes(title=\"Return period (years)\", title_font={\"size\": 14}, row=1, col=1, type=\"log\")\n",
"fig1.update_xaxes(\n",
" title=\"Return period (years)\", title_font={\"size\": 14}, row=1, col=1, type=\"log\"\n",
")\n",
"fig1.update_yaxes(title=\"Flood depth (m)\", title_font={\"size\": 14}, row=1, col=1)\n",
"fig1.add_trace(\n",
" go.Scatter(\n",
" x=wind_results_baseline[0][\"index_values\"], y=wind_results_baseline[0][\"intensities\"], name=\"baseline wind\"\n",
" x=wind_results_baseline[0][\"index_values\"],\n",
" y=wind_results_baseline[0][\"intensities\"],\n",
" name=\"baseline wind\",\n",
" ),\n",
" row=1,\n",
" col=2,\n",
")\n",
"fig1.add_trace(\n",
" go.Scatter(\n",
" x=wind_results_ssp585[0][\"index_values\"], y=wind_results_ssp585[0][\"intensities\"], name=\"wind SSP585 2050\"\n",
" x=wind_results_ssp585[0][\"index_values\"],\n",
" y=wind_results_ssp585[0][\"intensities\"],\n",
" name=\"wind SSP585 2050\",\n",
" ),\n",
" row=1,\n",
" col=2,\n",
")\n",
"fig1.update_xaxes(title=\"Return period (years)\", title_font={\"size\": 14}, row=1, col=2, type=\"log\")\n",
"fig1.update_yaxes(title=\"Max (1 minute) wind speed (m/s)\", title_font={\"size\": 14}, row=1, col=2)"
"fig1.update_xaxes(\n",
" title=\"Return period (years)\", title_font={\"size\": 14}, row=1, col=2, type=\"log\"\n",
")\n",
"fig1.update_yaxes(\n",
" title=\"Max (1 minute) wind speed (m/s)\", title_font={\"size\": 14}, row=1, col=2\n",
")"
]
},
{
Expand Down Expand Up @@ -353,11 +411,15 @@
"hazard_types = set(r[\"hazard_type\"] for r in hazard_resources)\n",
"print(f\"Hazards: {hazard_types}\")\n",
"wind_resources = [r for r in hazard_resources if r[\"hazard_type\"] == \"Wind\"]\n",
"print(f\"{len(hazard_resources)} hazard resources in the inventory, of which {len(wind_resources)} are Wind resources.\")\n",
"print(\n",
" f\"{len(hazard_resources)} hazard resources in the inventory, of which {len(wind_resources)} are Wind resources.\"\n",
")\n",
"iris_model_resource = next(r for r in wind_resources if \"iris\" in r[\"path\"])\n",
"# pp.pprint(iris_model_resource[0])\n",
"path = iris_model_resource[\"path\"]\n",
"print(f\"The resource 'path' is a unique identifier. For the IRIS Wind resource, for example, this is: '{path}'.\")\n",
"print(\n",
" f\"The resource 'path' is a unique identifier. For the IRIS Wind resource, for example, this is: '{path}'.\"\n",
")\n",
"print(\n",
" \"Where resources are multi-dimensional arrays (as opposed to an external API), this is also the path of the array.\"\n",
")\n",
Expand Down
33 changes: 27 additions & 6 deletions docs/notebooks/2_asset_level_impacts.ipynb
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Expand Up @@ -174,19 +174,34 @@
"\n",
"fig1 = make_subplots(rows=1, cols=2)\n",
"fig1.add_trace(\n",
" go.Scatter(x=exceedance_histo[\"exceed_probabilities\"], y=exceedance_histo[\"values\"], name=\"baseline wind\"),\n",
" go.Scatter(\n",
" x=exceedance_histo[\"exceed_probabilities\"],\n",
" y=exceedance_histo[\"values\"],\n",
" name=\"baseline wind\",\n",
" ),\n",
" row=1,\n",
" col=1,\n",
")\n",
"fig1.add_trace(\n",
" go.Scatter(x=exceedance_ssp585[\"exceed_probabilities\"], y=exceedance_ssp585[\"values\"], name=\"wind SSP585\"),\n",
" go.Scatter(\n",
" x=exceedance_ssp585[\"exceed_probabilities\"],\n",
" y=exceedance_ssp585[\"values\"],\n",
" name=\"wind SSP585\",\n",
" ),\n",
" row=1,\n",
" col=1,\n",
")\n",
"fig1.update_xaxes(\n",
" title=\"Annual exceedance probability\", title_font={\"size\": 14}, row=1, col=1, type=\"log\", autorange=\"reversed\"\n",
" title=\"Annual exceedance probability\",\n",
" title_font={\"size\": 14},\n",
" row=1,\n",
" col=1,\n",
" type=\"log\",\n",
" autorange=\"reversed\",\n",
")\n",
"fig1.update_yaxes(title=\"Damage as fraction of insurable value\", title_font={\"size\": 14}, row=1, col=1)"
"fig1.update_yaxes(\n",
" title=\"Damage as fraction of insurable value\", title_font={\"size\": 14}, row=1, col=1\n",
")"
]
},
{
Expand Down Expand Up @@ -231,7 +246,9 @@
"asset_measures_dict = {}\n",
"for i in asset_measures:\n",
" key = i[\"key\"]\n",
" asset_measures_dict[Key(key[\"hazard_type\"], key[\"measure_id\"], key[\"scenario_id\"], key[\"year\"])] = i\n",
" asset_measures_dict[\n",
" Key(key[\"hazard_type\"], key[\"measure_id\"], key[\"scenario_id\"], key[\"year\"])\n",
" ] = i\n",
"\n",
"wind_impact_scores = asset_measures_dict[Key(\"Wind\", \"measure_set_0\", \"ssp585\", \"2050\")]\n",
"\n",
Expand Down Expand Up @@ -282,7 +299,11 @@
}
],
"source": [
"pp.pprint(response[\"risk_measures\"][\"score_based_measure_set_defn\"][\"score_definitions\"][\"measure_1\"])"
"pp.pprint(\n",
" response[\"risk_measures\"][\"score_based_measure_set_defn\"][\"score_definitions\"][\n",
" \"measure_1\"\n",
" ]\n",
")"
]
},
{
Expand Down
27 changes: 21 additions & 6 deletions methodology/plots/interp_pixel_is_area.ipynb
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Expand Up @@ -6,7 +6,8 @@
"metadata": {},
"outputs": [],
"source": [
"import os, sys\n",
"import os\n",
"import sys\n",
"from affine import Affine\n",
"import matplotlib.pyplot as plt\n",
"import s3fs\n",
Expand All @@ -17,7 +18,11 @@
"\n",
"os.environ[\"CREDENTIAL_DOTENV_DIR\"] = os.path.dirname(os.getcwd())\n",
"zarr_utilities.set_credential_env_variables()\n",
"s3 = s3fs.S3FileSystem(anon=False, key=os.environ[\"OSC_S3_ACCESS_KEY\"], secret=os.environ[\"OSC_S3_SECRET_KEY\"])"
"s3 = s3fs.S3FileSystem(\n",
" anon=False,\n",
" key=os.environ[\"OSC_S3_ACCESS_KEY\"],\n",
" secret=os.environ[\"OSC_S3_SECRET_KEY\"],\n",
")"
]
},
{
Expand All @@ -28,7 +33,9 @@
"source": [
"longitude = 2.293\n",
"latitude = 48.855\n",
"transform = Affine(0.008333333333333333, 0.0, -180.0, 0.0, -0.008333333333333333, 90.0, 0.0, 0.0, 1.0)"
"transform = Affine(\n",
" 0.008333333333333333, 0.0, -180.0, 0.0, -0.008333333333333333, 90.0, 0.0, 0.0, 1.0\n",
")"
]
},
{
Expand Down Expand Up @@ -72,7 +79,8 @@
"source": [
"delta = 0.02\n",
"plt1 = da.sel(\n",
" latitude=slice(latitude + delta, latitude - delta), longitude=slice(longitude - delta, longitude + delta)\n",
" latitude=slice(latitude + delta, latitude - delta),\n",
" longitude=slice(longitude - delta, longitude + delta),\n",
")[8, :, :].plot.pcolormesh(cmap=\"Blues\", cbar_kwargs={\"label\": \"flood depth (m)\"})"
]
},
Expand All @@ -97,10 +105,17 @@
"# the point falls in pixel 21875, 4937\n",
"\n",
"plt1.axes.set_title(\"\")\n",
"surrounding_points = [[21874.5, 4936.5], [21874.5, 4937.5], [21875.5, 4936.5], [21875.5, 4937.5]]\n",
"surrounding_points = [\n",
" [21874.5, 4936.5],\n",
" [21874.5, 4937.5],\n",
" [21875.5, 4936.5],\n",
" [21875.5, 4937.5],\n",
"]\n",
"for point in surrounding_points:\n",
" pointt = transform * point\n",
" plt1.axes.plot([pointt[0], longitude], [pointt[1], latitude], \"--\", color=\"grey\", zorder=1)\n",
" plt1.axes.plot(\n",
" [pointt[0], longitude], [pointt[1], latitude], \"--\", color=\"grey\", zorder=1\n",
" )\n",
" plt1.axes.scatter([pointt[0]], [pointt[1]], c=\"black\", marker=\"o\", zorder=2)\n",
"plt1.axes.scatter([longitude], [latitude], c=\"black\", marker=\"x\", zorder=2)\n",
"plt1.axes.figure"
Expand Down
6 changes: 5 additions & 1 deletion notebooks/vulnerability_onboarding/EU JRC global flood depth-damage functions/onboard.ipynb
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Expand Up @@ -54,7 +54,11 @@
" # whether zero depth is considered really zero or a flood event with smallest depth\n",
" zero_as_minimum = True if location == \"North America\" else False\n",
" # for North America, the 0 depth damage is for flooding of any depth. We consider that a 1 cm inundation.\n",
" depth = np.concatenate([[0, 0.01], flood_depth[1:]]) if zero_as_minimum else flood_depth\n",
" depth = (\n",
" np.concatenate([[0, 0.01], flood_depth[1:]])\n",
" if zero_as_minimum\n",
" else flood_depth\n",
" )\n",
"\n",
" mean = type_df[location + \"_Mean\"].to_numpy()\n",
" std = type_df[location + \"_Std\"].to_numpy()\n",
Expand Down
19 changes: 14 additions & 5 deletions ...y_onboarding/WRI thermal power plant physical climate vulnerability factors/onboard.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -22,7 +22,8 @@
"metadata": {},
"outputs": [],
"source": [
"import json, pandas\n",
"import json\n",
"import pandas\n",
"\n",
"data = {\"items\": []}\n",
"\n",
Expand Down Expand Up @@ -53,15 +54,23 @@
" \"event_type\": hazard_type.replace(\" \", \"\"),\n",
" \"location\": \"Global\",\n",
" \"intensity\": list(item[\"Threshold\"].values),\n",
" \"intensity_units\": item[\"Threshold Unit\"].values[0].replace(\" \", \"\"),\n",
" \"impact_type\": item[\"Vulnerability Type\"].values[0].replace(\" \", \"\"),\n",
" \"impact_units\": item[\"Vulnerability Unit\"].values[0].replace(\" \", \"\"),\n",
" \"intensity_units\": item[\"Threshold Unit\"]\n",
" .values[0]\n",
" .replace(\" \", \"\"),\n",
" \"impact_type\": item[\"Vulnerability Type\"]\n",
" .values[0]\n",
" .replace(\" \", \"\"),\n",
" \"impact_units\": item[\"Vulnerability Unit\"]\n",
" .values[0]\n",
" .replace(\" \", \"\"),\n",
" \"impact_mean\": list(item[\"Vulnerability\"].values),\n",
" \"impact_std\": [],\n",
" }\n",
" )\n",
"\n",
"with open(\"WRI thermal power plant physical climate vulnerability factors.json\", \"w\") as f:\n",
"with open(\n",
" \"WRI thermal power plant physical climate vulnerability factors.json\", \"w\"\n",
") as f:\n",
" vulnerability_json = json.dumps(data, sort_keys=True, indent=4)\n",
" f.write(vulnerability_json)"
]
Expand Down

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