Skip to content

Commit

Permalink
Onboard Iris wind model (#146)
Browse files Browse the repository at this point in the history 
Signed-off-by: Joe Moorhouse <joe.moorhouse@gmail.com>
  • Loading branch information
@joemoorhouse
joemoorhouse authored Sep 17, 2023
1 parent 0c15a19 commit f118bb1
Show file tree
Hide file tree
Showing 18 changed files with 427 additions and 112 deletions.
2 changes: 1 addition & 1 deletion README.md
View file
Original file line number Diff line number Diff line change
Expand Up @@ -9,7 +9,7 @@ pip install physrisk-lib
Access to hazard event data requires setting of environment variables specifying the S3 Bucket, for example:

```
OSC_S3_BUCKET=redhat-osc-physical-landing-647521352890
OSC_S3_BUCKET=physrisk-hazard-indicators
OSC_S3_ACCESS_KEY=**********6I
OSC_S3_SECRET_KEY=**********mS
```
Expand Down
2 changes: 1 addition & 1 deletion docs/handbook/onboarding.rst
View file
Original file line number Diff line number Diff line change
Expand Up @@ -55,7 +55,7 @@ Specific types of model also exist for common modelling approaches. In particula
On-boarding a model based on a damage/disruption curve
------------------------------------------------------

A vulnerability distribition can be inferred directly from a damage/disruption curve:
A vulnerability distribution can be inferred directly from a damage/disruption curve:

.. image:: onboarding/disruption_curve.png
:width: 500
Expand Down
193 changes: 174 additions & 19 deletions ...U JRC global flood depth-damage functions/EU JRC global flood depth-damage functions.json
View file
Original file line number Diff line number Diff line change
Expand Up @@ -256,47 +256,142 @@
{
"asset_type": "Buildings/Commercial",
"event_type": "RiverineInundation",
"impact_mean": [],
"impact_mean": [
0.0,
0.15,
0.3,
0.45,
0.55,
0.75,
0.9,
1.0,
1.0
],
"impact_std": [],
"impact_type": "Damage",
"intensity": [],
"intensity": [
0.0,
0.5,
1.0,
1.5,
2.0,
3.0,
4.0,
5.0,
6.0
],
"intensity_units": "m",
"location": "Europe"
},
{
"asset_type": "Buildings/Commercial",
"event_type": "RiverineInundation",
"impact_mean": [
0.0
],
"impact_std": [
0.0
0.0,
0.018404908,
0.239263804,
0.374233129,
0.466257669,
0.552147239,
0.687116564,
0.82208589,
0.90797546,
1.0
],
"impact_std": [],
"impact_type": "Damage",
"intensity": [
0.0,
0.01
0.01,
0.5,
1.0,
1.5,
2.0,
3.0,
4.0,
5.0,
6.0
],
"intensity_units": "m",
"location": "North America"
},
{
"asset_type": "Buildings/Commercial",
"event_type": "RiverineInundation",
"impact_mean": [],
"impact_std": [],
"impact_mean": [
0.0,
0.611477587,
0.839531094,
0.923588457,
0.991972477,
1.0,
1.0,
1.0,
1.0
],
"impact_std": [
0.0,
0.077023435,
0.035924027,
0.026876525,
0.016055046,
0.0,
0.0,
0.0,
0.0
],
"impact_type": "Damage",
"intensity": [],
"intensity": [
0.0,
0.5,
1.0,
1.5,
2.0,
3.0,
4.0,
5.0,
6.0
],
"intensity_units": "m",
"location": "South America"
},
{
"asset_type": "Buildings/Commercial",
"event_type": "RiverineInundation",
"impact_mean": [],
"impact_std": [],
"impact_mean": [
0.0,
0.376789623,
0.537681619,
0.659336684,
0.762845232,
0.883348656,
0.941854895,
0.98075938,
1.0
],
"impact_std": [
0.0,
0.240462285,
0.240596279,
0.243605156,
0.250253511,
0.171703625,
0.11240992,
0.052781064,
0.0
],
"impact_type": "Damage",
"intensity": [],
"intensity": [
0.0,
0.5,
1.0,
1.5,
2.0,
3.0,
4.0,
5.0,
6.0
],
"intensity_units": "m",
"location": "Asia"
},
Expand All @@ -306,27 +401,87 @@
"impact_mean": [],
"impact_std": [],
"impact_type": "Damage",
"intensity": [],
"intensity": [
0.0,
0.5,
1.0,
1.5,
2.0,
3.0,
4.0,
5.0,
6.0
],
"intensity_units": "m",
"location": "Africa"
},
{
"asset_type": "Buildings/Commercial",
"event_type": "RiverineInundation",
"impact_mean": [],
"impact_std": [],
"impact_mean": [
0.0,
0.238953575,
0.481199682,
0.673795091,
0.864583333,
1.0,
1.0,
1.0,
1.0
],
"impact_std": [
0.0,
0.142878204,
0.204113206,
0.190903594,
0.178000078,
0.0,
0.0,
0.0,
0.0
],
"impact_type": "Damage",
"intensity": [],
"intensity": [
0.0,
0.5,
1.0,
1.5,
2.0,
3.0,
4.0,
5.0,
6.0
],
"intensity_units": "m",
"location": "Oceania"
},
{
"asset_type": "Buildings/Commercial",
"event_type": "RiverineInundation",
"impact_mean": [],
"impact_mean": [
0.0,
0.323296918,
0.506529105,
0.63459558,
0.744309656,
0.864093044,
0.932788157,
0.977746968,
1.0
],
"impact_std": [],
"impact_type": "Damage",
"intensity": [],
"intensity": [
0.0,
0.5,
1.0,
1.5,
2.0,
3.0,
4.0,
5.0,
6.0
],
"intensity_units": "m",
"location": "Global"
},
Expand Down
6 changes: 3 additions & 3 deletions notebooks/vulnerability_onboarding/EU JRC global flood depth-damage functions/onboard.ipynb
View file
Original file line number Diff line number Diff line change
Expand Up @@ -18,7 +18,7 @@
},
{
"cell_type": "code",
"execution_count": 6,
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -31,7 +31,7 @@
"# consistent with physrisk continent definition\n",
"location_mappings = { \"Europe\": \"Europe\", \"North America\": \"North America\", \"Central & South America\": \"South America\", \"Asia\": \"Asia\", \"Africa\": \"Africa\", \"Oceania\": \"Oceania\", \"Global\": \"Global\" }\n",
"type_mappings = { \"Residential buildings\": \"Buildings/Residential\",\n",
" \"Commerical buildings\": \"Buildings/Commercial\",\n",
" \"Commercial buildings\": \"Buildings/Commercial\",\n",
" \"Industrial buildings\": \"Buildings/Industrial\"\n",
"}\n",
"\n",
Expand Down Expand Up @@ -89,7 +89,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.10"
"version": "3.8.13"
},
"orig_nbformat": 4
},
Expand Down
22 changes: 18 additions & 4 deletions src/physrisk/data/hazard_data_provider.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -67,7 +67,14 @@ def __init__(
super().__init__(get_source_path, store=store, zarr_reader=zarr_reader, interpolation=interpolation)

def get_intensity_curves(
self, longitudes: List[float], latitudes: List[float], *, indicator_id: str, scenario: str, year: int
self,
longitudes: List[float],
latitudes: List[float],
*,
indicator_id: str,
scenario: str,
year: int,
hint: Optional[HazardDataHint] = None,
):
"""Get intensity curve for each latitude and longitude coordinate pair.
Expand All @@ -83,7 +90,7 @@ def get_intensity_curves(
return_periods: return periods in years.
"""

path = self._get_source_path(indicator_id=indicator_id, scenario=scenario, year=year)
path = self._get_source_path(indicator_id=indicator_id, scenario=scenario, year=year, hint=hint)
curves, return_periods = self._reader.get_curves(
path, longitudes, latitudes, self._interpolation
) # type: ignore
Expand All @@ -104,7 +111,14 @@ def __init__(
super().__init__(get_source_path, store=store, zarr_reader=zarr_reader, interpolation=interpolation)

def get_parameters(
self, longitudes: List[float], latitudes: List[float], *, indicator_id: str, scenario: str, year: int
self,
longitudes: List[float],
latitudes: List[float],
*,
indicator_id: str,
scenario: str,
year: int,
hint: Optional[HazardDataHint] = None,
):
"""Get hazard parameters for each latitude and longitude coordinate pair.
Expand All @@ -119,6 +133,6 @@ def get_parameters(
parameters: numpy array of parameters
"""

path = self._get_source_path(indicator_id=indicator_id, scenario=scenario, year=year)
path = self._get_source_path(indicator_id=indicator_id, scenario=scenario, year=year, hint=hint)
parameters, _ = self._reader.get_curves(path, longitudes, latitudes, self._interpolation)
return parameters[:, 0]
2 changes: 1 addition & 1 deletion src/physrisk/data/image_creator.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -95,7 +95,7 @@ def _to_image(
# (from zarr 2.16.0 we can also use block indexing)
data = data[index, 256 * tile.y : 256 * (tile.y + 1), 256 * tile.x : 256 * (tile.x + 1)]

if any(dim > 1500 for dim in data.shape):
if any(dim > 4000 for dim in data.shape):
raise Exception("dimension too large (over 1500).")
map_defn = colormap_provider.colormap(colormap)

Expand Down
20 changes: 12 additions & 8 deletions src/physrisk/data/pregenerated_hazard_model.py
View file
Original file line number Diff line number Diff line change
@@ -1,6 +1,8 @@
from collections import defaultdict
from typing import Dict, List, Mapping, MutableMapping, Optional, cast

import numpy as np

from physrisk.data.zarr_reader import ZarrReader
from physrisk.kernel.hazards import Hazard, HazardKind

Expand Down Expand Up @@ -40,24 +42,26 @@ def get_hazard_events(self, requests: List[HazardDataRequest]) -> Mapping[Hazard
responses: MutableMapping[HazardDataRequest, HazardDataResponse] = {}
for key in batches.keys():
batch: List[HazardDataRequest] = batches[key]
event_type, indicator_id, scenario, year = (
hazard_type, indicator_id, scenario, year, hint = (
batch[0].hazard_type,
batch[0].indicator_id,
batch[0].scenario,
batch[0].year,
batch[0].hint,
)
longitudes = [req.longitude for req in batch]
latitudes = [req.latitude for req in batch]
if event_type.kind == HazardKind.acute: # type: ignore
intensities, return_periods = self.acute_hazard_data_providers[event_type].get_intensity_curves(
longitudes, latitudes, indicator_id=indicator_id, scenario=scenario, year=year
if hazard_type.kind == HazardKind.acute: # type: ignore
intensities, return_periods = self.acute_hazard_data_providers[hazard_type].get_intensity_curves(
longitudes, latitudes, indicator_id=indicator_id, scenario=scenario, year=year, hint=hint
)

for i, req in enumerate(batch):
responses[req] = HazardEventDataResponse(return_periods, intensities[i, :])
elif event_type.kind == HazardKind.chronic: # type: ignore
parameters = self.chronic_hazard_data_providers[event_type].get_parameters(
longitudes, latitudes, indicator_id=indicator_id, scenario=scenario, year=year
valid = ~np.isnan(intensities[i, :])
responses[req] = HazardEventDataResponse(return_periods[valid], intensities[i, :][valid])
elif hazard_type.kind == HazardKind.chronic: # type: ignore
parameters = self.chronic_hazard_data_providers[hazard_type].get_parameters(
longitudes, latitudes, indicator_id=indicator_id, scenario=scenario, year=year, hint=hint
)

for i, req in enumerate(batch):
Expand Down
Loading

0 comments on commit f118bb1

Please sign in to comment.