Aggregating Instances: Aggregate and Histogram¶

We assume that you have generated a SDK for the WindTurbine model and have a client ready to go.

pygen automatically generates an aggregate and a histogram method for the properties in the views.

In [2]:

from wind_turbine import WindTurbineClient

from wind_turbine import WindTurbineClient

In [3]:

pygen = WindTurbineClient.from_toml("config.toml")

pygen = WindTurbineClient.from_toml("config.toml")

In [5]:

result = pygen.generating_unit.aggregate("avg", property="capacity")
result

result = pygen.generating_unit.aggregate("avg", property="capacity") result

Out[5]:

[AvgValue(property='capacity', value=6.857142857142857)]

The aggregatemethods combines all the aggrgagations and properties pased in

In [7]:

result = pygen.wind_turbine.aggregate(
    "count",
    property=["name", "windfarm", "capacity"],
)
result

result = pygen.wind_turbine.aggregate( "count", property=["name", "windfarm", "capacity"], ) result

Out[7]:

[CountValue(property='capacity', value=5),
 CountValue(property='windfarm', value=5),
 CountValue(property='name', value=5)]

Typically, you have to specify which properties you want to aggregate on, however, for count you can skip the properties and pygen will just take the first property it finds.

In [8]:

result = pygen.generating_unit.aggregate("count")
result

result = pygen.generating_unit.aggregate("count") result

Out[8]:

[CountValue(property='externalId', value=7)]

You can also group by when you aggregate

In [9]:

result = pygen.wind_turbine.aggregate("avg", property="capacity", group_by="windfarm")
result

result = pygen.wind_turbine.aggregate("avg", property="capacity", group_by="windfarm") result

Out[9]:

	aggregates	group
0	[{'aggregate': 'avg', 'property': 'capacity', ...	{'windfarm': 'Hornsea 1'}

In [10]:

result[0].group, result[0].aggregates

result[0].group, result[0].aggregates

Out[10]:

({'windfarm': 'Hornsea 1'}, [AvgValue(property='capacity', value=7.0)])

In addition, we have histogram aggregation on a separate method

In [11]:

result = pygen.sensor_position.histogram("position", interval=5.0)
result

result = pygen.sensor_position.histogram("position", interval=5.0) result

Out[11]:

HistogramValue(property='position', interval=5.0, buckets=[])

In [30]:

import matplotlib.pyplot as plt

import matplotlib.pyplot as plt

In [31]:

plt.bar([b.start for b in result.buckets], [b.count for b in result.buckets])
plt.xlabel("Sensor position")
plt.ylabel("Sensor count");

plt.bar([b.start for b in result.buckets], [b.count for b in result.buckets]) plt.xlabel("Sensor position") plt.ylabel("Sensor count");

Next section: Querying

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