Time Series

Hydra supports three types of time series: “normal” time series, equally spaced time series and seasonal time series. The SOAP interface provides methods to store data on the server and to retrieve them from the server.

Saving time series data to the server

“Normal” time series and seasonal time series

Time series are sent to the server as TimeSeries objects. Every element of the time series added to the TimeSeries object as a TimeSeriesData object.

A TimeSeries object only has the field ts_values which holds an array of TimeSeriesData objects. A TimeSeriesData object has the fields ts_time and ts_value. While the value can be anything, a string, a number or an array, the time needs to follow a certain pattern:

'%Y-%m-%d %H:%M:%S.%f%z'

following these specifications

%Y	year, four digits	2013
%m	month, two digits	10
%d	day, two digits	03
%H	hour, two digits	00
%M	minute, two digits	49
%S	seconds, two digits	17
%f	fractional seconds	568
%z	time zone offset, sign and four digits	-0400

for example:

'2013-10-03 00:49:17.568-0400'

A time stamp can take any value from January 1st, year 2 (year 1 in reserved for seasonal time series). In a time stamp for a seasonal time series the year is replaced by either '0001' or 'XXXX'. We recommend to use the latter, since using year 1 explicitly might not be supported in future versions of Hydra.

An example in Python

In Python the code to generate a complete time series object could look like this:

from suds import Client

url = 'http://localhost:8000?wsdl'
client = Client(url)

#These should obviously be valid IDs
scenario_id = AAA
resource_attribute_id = BBB

dataset = [(datetime(2002, 1, 1), 4.0), (datetime(2002, 1, 2), 4.5)]

#In general, data sent to the server must be contained in a 'dataset' obhect
dataset = self.client.factory.create('ns1:Dataset')
dataset.type      = 'timeseries'
dataset.name      = 'Max Capacity'
dataset.unit      = 'metres cubed'
dataset.dimension = 'Volume'


#Create the timeseries object
timeseries = {"Header": {}}
for time, value in dataset:
     t = PluginLib.date_to_string(time)
     timeseries["0"][t] = value

timeseries.ts_values = json.dumps(timeseries)

dataset.value = timeseries

client.service.add_data_to_attribute(scenario_id, resource_attribute_id, dataset)

If you would like to save a seasonal time series to the server an optional parameter to PluginLib.date_to_string() should to the trick:

tsdata.ts_time = PluginLib.date_to_string(time, seasonal=True)

Retrieving time series from the server