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fix up predictions

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This commit is contained in:
Michaela 2021-03-22 19:29:37 +11:00
parent cc61cc7010
commit 8995e6249b
2 changed files with 27 additions and 10 deletions
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28
predict/lambda_function.py
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@ -29,7 +29,7 @@ def predict(event, context):
"3": {
"date_histogram": {
"field": "datetime",
"fixed_interval": "30s"
"fixed_interval": "5s"
},
"aggs": {
"1": {
@ -52,7 +52,9 @@ def predict(event, context):
},
"4": {
"serial_diff": {
"buckets_path": "4-metric"
"buckets_path": "4-metric",
"gap_policy": "skip",
"lag": 5
}
},
"5": {
@ -135,7 +137,13 @@ def predict(event, context):
}
],
"should": [],
"must_not": []
"must_not": [
{
"match_phrase": {
"software_name": "SondehubV1"
}
}
]
}
}
}
@ -158,7 +166,7 @@ def predict(event, context):
serials[x['key']] = {
"alt": sorted(x['3']['buckets'], key=lambda k: k['key_as_string'])[-1]['1']['hits']['hits'][0]['fields']['alt'][0],
"position": sorted(x['3']['buckets'], key=lambda k: k['key_as_string'])[-1]['5']['hits']['hits'][0]['fields']['position'][0].split(","),
"rate": sorted(x['3']['buckets'], key=lambda k: k['key_as_string'])[-1]['4']['value']/30, # as we bucket for every 30 seconds at the moment,
"rate": sorted(x['3']['buckets'], key=lambda k: k['key_as_string'])[-1]['4']['value']/25, # as we bucket for every 5 seconds with a lag of 5
"time": sorted(x['3']['buckets'], key=lambda k: k['key_as_string'])[-1]['key_as_string']
}
except:
@ -176,7 +184,7 @@ def predict(event, context):
burst_altitude = (value['alt']+0.05) if value['alt'] > 26000 else 26000
conn.request("GET",
f"/api/v1/?launch_latitude={value['position'][0].strip()}&launch_longitude={float(value['position'][1].strip())+180}&launch_datetime={value['time']}&launch_altitude={value['alt']}&ascent_rate={ascent_rate}&burst_altitude={burst_altitude}&descent_rate={descent_rate}"
f"/api/v1/?launch_latitude={value['position'][0].strip()}&launch_longitude={float(value['position'][1].strip())+ 180}&launch_datetime={value['time']}&launch_altitude={value['alt']}&ascent_rate={ascent_rate}&burst_altitude={burst_altitude}&descent_rate={descent_rate}"
)
res = conn.getresponse()
data = res.read()
@ -197,7 +205,7 @@ def predict(event, context):
data.append({
"time": int(datetime.fromisoformat(item['datetime'].split(".")[0].replace("Z","")).timestamp()),
"lat": item['latitude'],
"lon": item['longitude'] -180,
"lon": item['longitude']-180,
"alt": item['altitude'],
})
@ -205,7 +213,7 @@ def predict(event, context):
"vehicle": serial,
"time": value['request']['launch_datetime'],
"latitude": value['request']['launch_latitude'],
"longitude": value['request']['launch_longitude']-180,
"longitude": value['request']['launch_longitude'],
"altitude": value['request']['launch_altitude'],
"ascent_rate":value['request']['ascent_rate'],
"descent_rate":value['request']['descent_rate'],
@ -241,8 +249,10 @@ if __name__ == "__main__":
# position_id: 0
# vehicles: RS_*;*chase
print(
get_sondes_in_air_rates(
{},{}
predict(
{"queryStringParameters" : {
"vehicles": ""
}},{}
)
)

9
query/lambda_function.py
View File

@ -264,7 +264,14 @@ def datanew(event, context):
"lt": lt.isoformat()
}
}
},
}
],
"must_not": [
{
"match_phrase": {
"software_name": "SondehubV1"
}
}
]
}
},