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:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 | 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)