def start_analyze_climate(request, format=None):
"""
Start a job to calculate the monthly climate (precipitation
and mean temperature) of a given area.
Source PRISM Climate Group
For more information, see
the [technical documentation](https://wikiwatershed.org/
documentation/mmw-tech/#overlays-tab-coverage)
## Response
You can use the url provided in the response's `location`
header to poll for the job's results.
<summary>
**Example of a completed job's `result`**
</summary>
<details>
{
"survey": {
"displayName": "Climate",
"name": "climate",
"categories": [
{
"ppt": 66.84088134765625,
"tmean": -2.4587886333465576,
"monthidx": 1,
"month": "January"
},
{
"ppt": 59.17946434020996,
"tmean": -1.8310737609863281,
"monthidx": 2,
"month": "February"
}, ...
]
}
}
</details>
---
type:
job:
required: true
type: string
status:
required: true
type: string
omit_serializer: true
parameters:
- name: body
description: A valid single-ringed Multipolygon GeoJSON
representation of the shape to analyze.
See the GeoJSON spec
https://tools.ietf.org/html/rfc7946#section-3.1.7
paramType: body
type: object
- name: wkaoi
paramType: query
description: The table and ID for a well-known area of interest,
such as a HUC.
Format "table__id", eg. "huc12__55174" will analyze
the HUC-12 City of Philadelphia-Schuylkill River.
- name: Authorization
paramType: header
description: Format "Token YOUR_API_TOKEN_HERE". When using
Swagger you may wish to set this for all requests via
the field at the top right of the page.
consumes:
- application/json
produces:
- application/json
"""
user = request.user if request.user.is_authenticated() else None
wkaoi = request.query_params.get('wkaoi', None)
area_of_interest = load_area_of_interest(request.data, wkaoi)
validate_aoi(area_of_interest)
geotasks = []
ppt_raster = settings.GEOP['json']['ppt']['input']['targetRaster']
tmean_raster = settings.GEOP['json']['tmean']['input']['targetRaster']
for i in xrange(1, 13):
ppt_input = {
'polygon': [area_of_interest],
'targetRaster': ppt_raster.format(i)
}
tmean_input = {
'polygon': [area_of_interest],
'targetRaster': tmean_raster.format(i)
}
geotasks.extend([
geoprocessing.run.s('ppt', ppt_input, wkaoi, i)
| tasks.analyze_climate.s('ppt', i),
geoprocessing.run.s('tmean', tmean_input, wkaoi, i)
| tasks.analyze_climate.s('tmean', i)
])
return start_celery_job([
group(geotasks),
tasks.collect_climate.s(),
],
area_of_interest,
user,
link_error=False)
def start_analyze_catchment_water_quality(request, format=None):
"""
Starts a job to calculate the calibrated GWLF-E (MapShed) model
estimates for a given area
(Delaware River Basin only)
Source Stream Reach Tool Assessment (SRAT)
For more information, see
the [technical documentation](https://wikiwatershed.org/
documentation/mmw-tech/#overlays-tab-coverage)
## Response
you can use the url provided in the response's `location`
header to poll for the job's results.
<summary>
**example of a completed job's `result`**
</summary>
<details>
{
"survey": {
"displayname": "water quality",
"name": "catchment_water_quality",
"categories": [
{
"tss_urban_": 49.115354321566734,
"tn_riparia": 0.3730090214,
"tn_pt_kgyr": null,
"tp_urban_k": 0.5043825,
"tss_tot_kg": 336.49653266840215,
"geom": {
"type": "multipolygon",
"coordinates": [
[
[
[
-74.9780151302813,
40.0646039341582
], ...
], ...
]
]
},
"nord": 4793,
"tss_concmg": 124.5634,
"tp_ag_kgyr": 0.493174,
"tp_yr_avg_": 0.0929,
"tn_yr_avg_": 1.461,
"tn_ag_kgyr": 8.74263,
"tss_natura": 3.912097242622951,
"tp_pt_kgyr": null,
"tn_natural": 2.622789,
"areaha": 375.27,
"tp_tot_kgy": 0.51148576021895,
"tn_urban_k": 8.428792,
"tp_natural": 0.0560425,
"tp_riparia": 0.1240888899,
"tn_tot_kgy": 7.745244945328085,
"tss_ag_kgy": 66.71350648852459,
"tss_rip_kg": 545.9289658316266
}
]
}
}
</details>
---
type:
job:
required: true
type: string
status:
required: true
type: string
omit_serializer: true
parameters:
- name: body
description: A valid single-ringed Multipolygon GeoJSON
representation of the shape to analyze.
See the GeoJSON spec
https://tools.ietf.org/html/rfc7946#section-3.1.7
paramType: body
type: object
- name: wkaoi
paramType: query
description: The table and ID for a well-known area of interest,
such as a HUC.
Format "table__id", eg. "huc12__55174" will analyze
the HUC-12 City of Philadelphia-Schuylkill River.
- name: Authorization
paramType: header
description: Format "Token YOUR_API_TOKEN_HERE". When using
Swagger you may wish to set this for all requests via
the field at the top right of the page.
consumes:
- application/json
produces:
- application/json
"""
user = request.user if request.user.is_authenticated() else None
wkaoi = request.query_params.get('wkaoi', None)
area_of_interest = load_area_of_interest(request.data, wkaoi)
validate_aoi(area_of_interest)
return start_celery_job(
[tasks.analyze_catchment_water_quality.s(area_of_interest)],
area_of_interest, user)
def start_analyze_pointsource(request, format=None):
"""
Starts a job to analyze the discharge monitoring report annual
averages for a given area.
Source EPA NPDES
For more information, see the
[technical documentation](https://wikiwatershed.org/
documentation/mmw-tech/#additional-data-layers)
## Response
You can use the URL provided in the response's `Location`
header to poll for the job's results.
<summary>
**Example of a completed job's `result`**
</summary>
<details>
{
"survey": {
"displayName": "Point Source",
"name": "pointsource",
"categories": [
{
"city": "PHILADELPHIA",
"kgp_yr": 16937.8,
"mgd": 4.0835,
"npdes_id": "0011533",
"longitude": -75.209722,
"state": "PA",
"facilityname": "GIRARD POINT PROCESSING AREA",
"latitude": 39.909722,
"kgn_yr": 1160.76
}
], ...
}
}
</details>
---
type:
job:
required: true
type: string
status:
required: true
type: string
omit_serializer: true
parameters:
- name: body
description: A valid single-ringed Multipolygon GeoJSON
representation of the shape to analyze.
See the GeoJSON spec
https://tools.ietf.org/html/rfc7946#section-3.1.7
paramType: body
type: object
- name: wkaoi
description: The table and ID for a well-known area of interest,
such as a HUC.
Format "table__id", eg. "huc12__55174" will analyze
the HUC-12 City of Philadelphia-Schuylkill River.
- name: Authorization
paramType: header
description: Format "Token YOUR_API_TOKEN_HERE". When using
Swagger you may wish to set this for all requests via
the field at the top right of the page.
consumes:
- application/json
produces:
- application/json
"""
user = request.user if request.user.is_authenticated() else None
wkaoi = request.query_params.get('wkaoi', None)
area_of_interest = load_area_of_interest(request.data, wkaoi)
validate_aoi(area_of_interest)
return start_celery_job([tasks.analyze_pointsource.s(area_of_interest)],
area_of_interest, user)
def start_analyze_animals(request, format=None):
"""
Starts a job to produce counts for animals in a given area.
Source USDA
For more information, see
the [technical documentation](https://wikiwatershed.org/documentation/
mmw-tech/#additional-data-layers)
## Response
You can use the URL provided in the response's `Location` header
to poll for the job's results.
<summary>
**Example of a completed job's `result`**
</summary>
<details>
{
"survey": {
"displayName": "Animals",
"name": "animals",
"categories": [
{
"aeu": 0,
"type": "Sheep"
},
{
"aeu": 0,
"type": "Horses"
},
{
"aeu": 0,
"type": "Turkeys"
},
{
"aeu": 0,
"type": "Chickens, Layers"
},
{
"aeu": 0,
"type": "Cows, Beef"
},
{
"aeu": 0,
"type": "Pigs/Hogs/Swine"
},
{
"aeu": 0,
"type": "Cows, Dairy"
},
{
"aeu": 0,
"type": "Chickens, Broilers"
}
]
}
}
</details>
---
type:
job:
required: true
type: string
status:
required: true
type: string
omit_serializer: true
parameters:
- name: body
description: A valid single-ringed Multipolygon GeoJSON
representation of the shape to analyze.
See the GeoJSON spec
https://tools.ietf.org/html/rfc7946#section-3.1.7
paramType: body
type: object
- name: wkaoi
paramType: query
description: The table and ID for a well-known area of interest,
such as a HUC.
Format "table__id", eg. "huc12__55174" will analyze
the HUC-12 City of Philadelphia-Schuylkill River.
- name: Authorization
paramType: header
description: Format "Token YOUR_API_TOKEN_HERE". When using
Swagger you may wish to set this for all requests via
the field at the top right of the page.
consumes:
- application/json
produces:
- application/json
"""
user = request.user if request.user.is_authenticated() else None
wkaoi = request.query_params.get('wkaoi', None)
area_of_interest = load_area_of_interest(request.data, wkaoi)
validate_aoi(area_of_interest)
return start_celery_job([tasks.analyze_animals.s(area_of_interest)],
area_of_interest, user)
def start_analyze_soil(request, format=None):
"""
Starts a job to produce a soil-type histogram for a given area.
Uses the Hydrologic Soil Groups From USDA gSSURGO 2016
For more information, see the
[technical documentation](https://wikiwatershed.org/
documentation/mmw-tech/#overlays-tab-coverage).
## Response
You can use the URL provided in the response's `Location`
header to poll for the job's results.
<summary>
**Example of a completed job's `result`**
</summary>
<details>
{
"survey": {
"displayName": "Soil",
"name": "soil",
"categories": [
{
"code": "a",
"type": "A - High Infiltration",
"coverage": 0.000010505194818837915,
"area": 897.253981351988
},
{
"code": "b",
"type": "B - Moderate Infiltration",
"coverage": 0.036474036411005245,
"area": 3115265.8232541024
},
{
"code": "c",
"type": "C - Slow Infiltration",
"coverage": 0.9465810843462092,
"area": 80847967.24370223
},
{
"code": "d",
"type": "D - Very Slow Infiltration",
"coverage": 0.00012606233782605497,
"area": 10767.047776223857
},
{
"code": "ad",
"type": "A/D - High/Very Slow Infiltration",
"coverage": 0,
"area": 0
},
{
"code": "bd",
"type": "B/D - Medium/Very Slow Infiltration",
"coverage": 0.0017753779243836077,
"area": 151635.92284848596
},
{
"code": "cd",
"type": "C/D - Medium/Very Slow Infiltration",
"coverage": 0.015032933785757057,
"area": 1283970.4473146948
}
]
}
}
</details>
---
type:
job:
required: true
type: string
status:
required: true
type: string
omit_serializer: true
parameters:
- name: body
description: A valid single-ringed Multipolygon GeoJSON
representation of the shape to analyze.
See the GeoJSON spec
https://tools.ietf.org/html/rfc7946#section-3.1.7
paramType: body
type: object
- name: wkaoi
description: The table and ID for a well-known area of interest,
such as a HUC.
Format "table__id", eg. "huc12__55174" will analyze
the HUC-12 City of Philadelphia-Schuylkill River.
type: string
paramType: query
- name: Authorization
paramType: header
description: Format "Token YOUR_API_TOKEN_HERE". When using
Swagger you may wish to set this for all requests via
the field at the top right of the page.
consumes:
- application/json
produces:
- application/json
"""
user = request.user if request.user.is_authenticated() else None
wkaoi = request.query_params.get('wkaoi', None)
area_of_interest = load_area_of_interest(request.data, wkaoi)
validate_aoi(area_of_interest)
geop_input = {'polygon': [area_of_interest]}
return start_celery_job([
geoprocessing.run.s('soil', geop_input, wkaoi),
tasks.analyze_soil.s(area_of_interest)
], area_of_interest, user)
def start_analyze_land(request, format=None):
"""
Starts a job to produce a land-use histogram for a given area.
Uses the National Land Cover Database (NLCD 2011)
For more information, see the
[technical documentation](https://wikiwatershed.org/
documentation/mmw-tech/#overlays-tab-coverage).
## Response
You can use the URL provided in the response's `Location`
header to poll for the job's results.
<summary>
**Example of a completed job's `result`**
</summary>
<details>
{
"survey": {
"displayName": "Land",
"name": "land",
"categories": [
{
"nlcd": 43,
"code": "mixed_forest",
"type": "Mixed Forest",
"coverage": 0,
"area": 0
},
{
"nlcd": 71,
"code": "grassland",
"type": "Grassland/Herbaceous",
"coverage": 0,
"area": 0
},
{
"nlcd": 41,
"code": "deciduous_forest",
"type": "Deciduous Forest",
"coverage": 0,
"area": 0
},
{
"nlcd": 42,
"code": "evergreen_forest",
"type": "Evergreen Forest",
"coverage": 0,
"area": 0
},
{
"nlcd": 11,
"code": "open_water",
"type": "Open Water",
"coverage": 0,
"area": 0
},
{
"nlcd": 12,
"code": "perennial_ice",
"type": "Perennial Ice/Snow",
"coverage": 0,
"area": 0
},
{
"nlcd": 81,
"code": "pasture",
"type": "Pasture/Hay",
"coverage": 0,
"area": 0
},
{
"nlcd": 82,
"code": "cultivated_crops",
"type": "Cultivated Crops",
"coverage": 0,
"area": 0
},
{
"nlcd": 52,
"code": "shrub",
"type": "Shrub/Scrub",
"coverage": 0,
"area": 0
},
{
"nlcd": 21,
"code": "developed_open",
"type": "Developed, Open Space",
"coverage": 0.030303030303030304,
"area": 2691.709835265247
},
{
"nlcd": 22,
"code": "developed_low",
"type": "Developed, Low Intensity",
"coverage": 0.18181818181818182,
"area": 16150.259011591483
},
{
"nlcd": 23,
"code": "developed_med",
"type": "Developed, Medium Intensity",
"coverage": 0.5151515151515151,
"area": 45759.0671995092
},
{
"nlcd": 24,
"code": "developed_high",
"type": "Developed, High Intensity",
"coverage": 0.2727272727272727,
"area": 24225.388517387222
},
{
"nlcd": 90,
"code": "woody_wetlands",
"type": "Woody Wetlands",
"coverage": 0,
"area": 0
},
{
"nlcd": 95,
"code": "herbaceous_wetlands",
"type": "Emergent Herbaceous Wetlands",
"coverage": 0,
"area": 0
},
{
"nlcd": 31,
"code": "barren_land",
"type": "Barren Land (Rock/Sand/Clay)",
"coverage": 0,
"area": 0
}
]
}
}
</details>
---
type:
job:
required: true
type: string
status:
required: true
type: string
omit_serializer: true
parameters:
- name: body
description: A valid single-ringed Multipolygon GeoJSON
representation of the shape to analyze.
See the GeoJSON spec
https://tools.ietf.org/html/rfc7946#section-3.1.7
paramType: body
type: object
- name: wkaoi
description: The table and ID for a well-known area of interest,
such as a HUC.
Format "table__id", eg. "huc12__55174" will analyze
the HUC-12 City of Philadelphia-Schuylkill River.
type: string
paramType: query
- name: Authorization
paramType: header
description: Format "Token YOUR_API_TOKEN_HERE". When using
Swagger you may wish to set this for all requests via
the field at the top right of the page.
consumes:
- application/json
produces:
- application/json
"""
user = request.user if request.user.is_authenticated() else None
wkaoi = request.query_params.get('wkaoi', None)
area_of_interest = load_area_of_interest(request.data, wkaoi)
validate_aoi(area_of_interest)
geop_input = {'polygon': [area_of_interest]}
return start_celery_job([
geoprocessing.run.s('nlcd', geop_input, wkaoi),
tasks.analyze_nlcd.s(area_of_interest)
], area_of_interest, user)