def get_inline_variables(signals: [api.Signal], include_wt: bool) -> {}:
variables = {}
for signal in signals:
if (signal.value_type == 'Numeric'):
variable = api.NumericVariable(
kind="numeric",
# https://docs.microsoft.com/en-us/rest/api/time-series-insights/reference-time-series-expression-syntax#other-functions
value=api.Tsx(
tsx=
f'coalesce($event.{signal._property}.Double, toDouble($event.{signal._property}.Long))'
),
aggregation=api.Tsx(tsx="it doesn't matter"))
variables[signal._property] = variable
else:
logger.info(
f'Not adding signal {signal._property} with value type {signal.value_type}'
)
if include_wt:
variables["wt"] = variable = api.NumericVariable(
kind="numeric",
value=api.Tsx(tsx='$event.wt'),
aggregation=api.Tsx(tsx="avg($value)"))
return variables
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="$event.temperature"),
aggregation=a10a.Tsx(tsx="it doesn't matter"))
get_series = a10a.GetSeries(
[id],
search_span=time_range,
inline_variables={"temperature": temperatureVariable})
time_series_data = ts_api.time_series_query_time_series(
a10a.QueryRequest(get_series=get_series))
print(
f'Got {len(time_series_data.timestamps)} datapoints and {len(time_series_data.properties)} properties'
)
# access the data in time_series_data.properties
print("-----------")
# get average of tomorrow's rainfall probablility, filtered by description = Possible shower or Mostly cloudy
amphora_api = a10a.AmphoraeApi(client.apiClient)
print(f'Getting signals for: {amphora_api.amphorae_read(id).name}')
print("-----------")
signals = amphora_api.amphorae_signals_get_signals(id)
properties = list((s._property for s in signals))
ts_api = a10a.TimeSeriesApi(
client.apiClient) # the API for interacting with time series
one_hour_ago = datetime.utcnow() + timedelta(hours=-1)
# Create a DateTimeRange to describe over what period we want data.
time_range = a10a.DateTimeRange(_from=one_hour_ago, to=datetime.utcnow())
# let's get the maximum write time for the period
maxWtVar = a10a.AggregateVariable(kind="aggregate",
aggregation=a10a.Tsx("max($event.wt)"))
minWtVar = a10a.AggregateVariable(kind="aggregate",
aggregation=a10a.Tsx("min($event.wt)"))
get_aggregate = a10a.AggregateSeries(
[id],
search_span=time_range,
interval="PT4H",
projected_variables=["maxWt", "minWt"],
inline_variables={
"maxWt": maxWtVar,
"minWt": minWtVar
})
agg_data = ts_api.time_series_query_time_series(
a10a.QueryRequest(aggregate_series=get_aggregate))
maxWt = max(agg_data.properties[0].values) # max value from max list
importCsv("dates_of_interest.csv")
amphora_id = 'fca8998a-2d0e-4afa-a9aa-1467759a8d9a'
T = 60
## Get the data
ts_api = a10a.TimeSeriesApi(client.apiClient)
time_range = a10a.DateTimeRange(_from=datetime.utcnow() + timedelta(days=-T),
to=datetime.utcnow())
variables = {
"confirmedCases":
a10a.NumericVariable(kind="numeric",
value=a10a.Tsx(tsx="$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",
value=a10a.Tsx(tsx="$event.deaths"),
aggregation=a10a.Tsx(tsx="it doesn't matter"))
}
labels=labels)
amphora_id = amphora.amphora_id
amphora_api = a10a.AmphoraeApi(client.apiClient)
T = 25
for i in range(len(country_stor)):
sep = ""
# Pull beta signal
## Get the data
ts_api = a10a.TimeSeriesApi(client.apiClient)
time_range = a10a.DateTimeRange(_from=datetime.utcnow() +
timedelta(days=-T),
to=datetime.utcnow() + timedelta(days=-5))
variables = {
"beta":
a10a.NumericVariable(kind="numeric",
value=a10a.Tsx(tsx="$event.beta"),
aggregation=a10a.Tsx(tsx="it doesn't matter"))
}
get_series_query = a10a.GetSeries(
[country_stor[i][0]],
search_span=time_range,
inline_variables=variables) # the complete query
time_series_data = ts_api.time_series_query_time_series(
a10a.QueryRequest(get_series=get_series_query))
data_array, unique_dt, data_name = flatten_time_series_data(
time_series_data)
unique_dt_list = list(unique_dt)
beta = data_array[0]