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,{})