Hackathon

[XavierHubOcean]

Adding the WindEurope folder and notebooks to the Hackathons folder

[henriktorget]

Can we delete the DNB hackathon files?

[henriktorget]

Seaborn and mpl_toolkits are not installed by default in the workspaces.
Can we add a code block for pip installing them in the notebook?

[henriktorget]

The paths should be updated to work within the workspaces environment.

[henriktorget]

Can we update the examples to fetch the data from vestas? I have attached the json schemas for the endpoints and example code here:

aggregation_query_input.json
threshold_query_input.json
timeseries_area_query_input.json
timeseries_closestpoint_query_input.json

import requests
import json


################ POST Timeseries Query ######################
#############################################################
api_url = "https://public-dev.api.vestas.com/public/vestas-climate-library/v1/timeseriesquery"
headers =  {
    "Content-Type":"application/json",
    "api_key": "x5b13DOiwixsUPeCZfPTXTz26SEibL1y"
}
request = {
  "latitude": 46.90,
  "longitude": -78.286,
  "startDate": "2011-01-01T00:00:00.000Z",
  "endDate": "2024-01-30T15:11:51.021Z",
  "vars4D": [
    "wsp"
  ],
  "vars3D": [
    "t2"
  ],
  "heights": [
    21.3,
    80
  ]
}
response = requests.post(api_url, data=json.dumps(request), headers=headers)
print("Timeseries Query: ")
print(response.json())



################ POST Threshold Query ################################################################
#######################################################################################################
api_url = "https://public-dev.api.vestas.com/public/vestas-climate-library/v1/thresholdquery"
headers =  {
    "Content-Type":"application/json",
    "api_key": "x5b13DOiwixsUPeCZfPTXTz26SEibL1y"
}
request = {
    "maxxlat":50.1,
    "maxxlong":14.4,
    "minxlat":50.0,
    "minxlong":14.2,
    "starttime":"2022",
    "endtime":"2023",
    "zHeights":[20,30,40],
    "tc_min":-15,
    "tc_max":15
}
response = requests.post(api_url, data=json.dumps(request), headers=headers)
print("Threshold Query: ")
print(response.json())



################ POST Aggregation Query ################################################################
#######################################################################################################
api_url = "https://public-dev.api.vestas.com/public/vestas-climate-library/v1/aggregationquery"
headers =  {
    "Content-Type":"application/json",
    "api_key": "x5b13DOiwixsUPeCZfPTXTz26SEibL1y"
}
request = {
    "maxxlat":50.1,
    "maxxlong":14.4,
    "minxlat":50.0,
    "minxlong":14.2,
    "starttime":"20230101",
    "endtime":"20230131",
    "selectedFunction":{
        "MIN":{
            "3DVars":["t2"]
        }
    }
}
response = requests.post(api_url, data=json.dumps(request), headers=headers)
print("Aggregation Query: ")
print(response.json())


################ POST Time Series Area Query ##########################################################
#######################################################################################################
api_url = "https://public-dev.api.vestas.com/public/vestas-climate-library/v1/timeseriesareaquery"
headers =  {
    "Content-Type":"application/json",
    "api_key": "x5b13DOiwixsUPeCZfPTXTz26SEibL1y"
}
request = {
    "minxlat":41,
    "minxlong":-100,
    "maxxlat":42,
    "maxxlong":-99,
    "starttime":"20220501",
    "endtime":"20220831",
    "selectedVariables":{
        "4DVars":["wsp","wdir","tk"],
        "zHeights":[50,150]
    }
}
response = requests.post(api_url, data=json.dumps(request), headers=headers)
print("Timeseriea Area Query: ")
print(response.json())



################ Get Query Status ################################################################
##################################################################################################
api_url = "https://public-dev.api.vestas.com/public/vestas-climate-library/v1/querystatus/4d1cc6e3-e508-4e8c-9d6c-641adb4af0b6"
headers =  {
    "Content-Type":"application/json",
    "api_key": "x5b13DOiwixsUPeCZfPTXTz26SEibL1y"
}
response = requests.get(api_url, headers=headers)
print("Query Status: ")
print(response.json())



################ Get Paginated Query Result ######################################################
##################################################################################################
api_url = "https://public-dev.api.vestas.com/public/vestas-climate-library/v1/queryresult/4d1cc6e3-e508-4e8c-9d6c-641adb4af0b6/1"
headers =  {
    "Content-Type":"application/json",
    "api_key": "x5b13DOiwixsUPeCZfPTXTz26SEibL1y"
}
response = requests.get(api_url, headers=headers)
print("Query Result: ")
print(response.json())

[henriktorget]

The JSON for the data (the one between 50N8W – 60N12E is like this:

{
  "input_json": {
    "selectedFunction": {
      "AVG": {
        "4DVars": [
          "wsp",
          "tk"
        ],
        "3DVars": [
          "hgt",
          "t2",
          "sst",
          "pblh"
        ],
        "zHeights": [
          70,
          140,
          280
        ]
      },
      "MAX": {
        "4DVars": [
          "wsp"
        ],
        "3DVars": [
          "t2"
        ],
        "zHeights": [
          70,
          140,
          280
        ]
      },
      "MIN": {
        "3DVars": [
          "t2"
        ]
      }
    },
    "minxlat": 50,
    "minxlong": -8,
    "maxxlat": 60,
    "maxxlong": 12
  }
}

[henriktorget]

Great stuff!