import sys
sys.path.append('.')
import disaggregator as da
from pandas.tseries.offsets import DateOffset
import numpy as np
db_url = "postgresql://*****:*****@db.wiki-energy.org:5432/postgres"
psda = da.PecanStreetDatasetAdapter(db_url)
dataids = psda.get_unique_dataids("curated", 2013, 1, group=1)
traces = psda.get_month_traces("curated", 2013, 1, dataids[-1], group=1)
instances = [da.ApplianceInstance([trace], {}) for trace in traces]
usage_order = np.argsort([i.traces[0].get_total_usage()
for i in instances])[::-1]
top_5_instances = [instances[i] for i in usage_order[1:6]]
print[inst.traces[0].series.name for inst in top_5_instances]
print da.aggregate_traces(traces, {"name": "aggregated"}).series
import sys
sys.path.append('.')
import disaggregator as da
from pandas.tseries.offsets import DateOffset
import numpy as np
db_url = "postgresql://*****:*****@db.wiki-energy.org:5432/postgres"
psda = da.PecanStreetDatasetAdapter(db_url)
dataids = psda.get_unique_dataids("curated",2013,1,group=1)
traces = psda.get_month_traces("curated",2013,1,dataids[-1],group=1)
instances = [da.ApplianceInstance([trace],{}) for trace in traces]
usage_order = np.argsort([i.traces[0].get_total_usage() for i in instances])[::-1]
top_5_instances = [instances[i] for i in usage_order[1:6]]
print [inst.traces[0].series.name for inst in top_5_instances]
print da.aggregate_traces(traces, {"name":"aggregated"}).series
def test_aggregate_traces_aligned(self):
aligned_traces = da.align_traces(self.consecutive_traces)
da.aggregate_traces(aligned_traces, {})
def test_aggregate_traces_aligned(self):
aligned_traces = da.align_traces(self.consecutive_traces)
da.aggregate_traces(aligned_traces,{})
