client = AmphoraDataRepositoryClient(credentials)
# https://beta.amphoradata.com/Amphorae/Detail?id=57d6593f-1889-410a-b1fb-631b6f9c9c85
id = "57d6593f-1889-410a-b1fb-631b6f9c9c85"
try:
amphora_api = a10a.AmphoraeApi(client.apiClient)
print(f'Getting signals for: {amphora_api.amphorae_read(id).name}')
signals = amphora_api.amphorae_signals_get_signals(id)
properties = list((s._property for s in signals))
ts_api = a10a.TimeSeriesApi(
client.apiClient) # the API for interacting with time series
tomorrow = datetime.now() + timedelta(hours=24)
# Create a DateTimeRange to describe over what period we want data.
time_range = a10a.DateTimeRange(_from=datetime.now(), to=tomorrow)
# Create a variable object for getting temperature data
temperatureVariable = a10a.NumericVariable(
kind="numeric",
value=a10a.Tsx(tsx="$event.temperature"),
aggregation=a10a.Tsx(tsx="it doesn't matter"))
get_series = a10a.GetSeries(
[id],
search_span=time_range,
inline_variables={"temperature": temperatureVariable})
time_series_data = ts_api.time_series_query_time_series(
a10a.QueryRequest(get_series=get_series))
print(
f'Got {len(time_series_data.timestamps)} datapoints and {len(time_series_data.properties)} properties'
)
return [i for i in a_list if i]
try:
amphora_api = a10a.AmphoraeApi(client.apiClient)
print(f'Getting signals for: {amphora_api.amphorae_read(id).name}')
print("-----------")
signals = amphora_api.amphorae_signals_get_signals(id)
properties = list((s._property for s in signals))
ts_api = a10a.TimeSeriesApi(
client.apiClient) # the API for interacting with time series
one_hour_ago = datetime.utcnow() + timedelta(hours=-1)
# Create a DateTimeRange to describe over what period we want data.
time_range = a10a.DateTimeRange(_from=one_hour_ago, to=datetime.utcnow())
# let's get the maximum write time for the period
maxWtVar = a10a.AggregateVariable(kind="aggregate",
aggregation=a10a.Tsx("max($event.wt)"))
minWtVar = a10a.AggregateVariable(kind="aggregate",
aggregation=a10a.Tsx("min($event.wt)"))
get_aggregate = a10a.AggregateSeries(
[id],
search_span=time_range,
interval="PT4H",
projected_variables=["maxWt", "minWt"],
inline_variables={
"maxWt": maxWtVar,
"minWt": minWtVar
})
##############################################################
# parameters and details
credentials = Credentials(username=os.getenv('username'),
password=os.getenv('password'))
client = AmphoraDataRepositoryClient(credentials)
Electricity_Amphora_id = '89c2e30d-78c8-46ef-b591-140edd84ddb6'
Weather_Amphora_id = '2866d34f-fe2b-4c07-acdd-28fe2d6d9194'
Forecast_amphora_id = '78831a6b-de49-454e-9e5c-7c757478e783'
name = 'South_Australia_Electricity_Price.json'
#############################################################
# Publish raw data on microprediction
mw = MicroWriter(write_key="bdfd44affd28e6c5b45329d6d4df7729")
time_range = a10a.DateTimeRange(_from=datetime.utcnow() + timedelta(hours=-1),
to=datetime.utcnow())
electricity_amphora = client.get_amphora(Electricity_Amphora_id)
electricity_signals = electricity_amphora.get_signals()
df = electricity_signals.pull(date_time_range=time_range).to_pandas()
price = df['price']
mw.set(name=name, value=price[-1])
##########################################################
# Create a prediction and publish on microprediction
# length = mw.num_predictions
# data_time_range = a10a.DateTimeRange(_from = datetime.utcnow() + timedelta(hours=-length/2) , to= datetime.utcnow() )
# pdf = electricity_signals.pull(date_time_range=data_time_range).to_pandas()
# price = pdf['price']
# prices_of_interest = price[-length-1:-1]
# elec_prices_diff = np.zeros(length-1)
element_of_interest = non_none_indicies[t]
data_array[i - 1][t] = time_series_data.properties[i].values[
element_of_interest]
return data_array, unique_dt, data_name
importCsv("dates_of_interest.csv")
amphora_id = 'fca8998a-2d0e-4afa-a9aa-1467759a8d9a'
T = 60
## Get the data
ts_api = a10a.TimeSeriesApi(client.apiClient)
time_range = a10a.DateTimeRange(_from=datetime.utcnow() + timedelta(days=-T),
to=datetime.utcnow())
variables = {
"confirmedCases":
a10a.NumericVariable(kind="numeric",
value=a10a.Tsx(tsx="$event.confirmedCases"),
aggregation=a10a.Tsx(tsx="it doesn't matter")),
"activeCases":
a10a.NumericVariable(kind="numeric",
value=a10a.Tsx(tsx="$event.activeCases"),
aggregation=a10a.Tsx(tsx="it doesn't matter")),
"recoveredCases":
a10a.NumericVariable(kind="numeric",
value=a10a.Tsx(tsx="$event.recoveredCases"),
aggregation=a10a.Tsx(tsx="it doesn't matter")),
"deaths":
a10a.NumericVariable(kind="numeric",
def default_date_time_range() -> api.DateTimeRange:
yesterday = datetime.utcnow() + timedelta(hours=-24)
return api.DateTimeRange(_from=yesterday, to=datetime.utcnow())