def test_downsample_hourly_frequency():
records = [{
"start": datetime(2015, 1, 1, tzinfo=pytz.UTC) + timedelta(seconds=i*900),
"value": np.nan if i % 30 == 0 or 1000 < i < 2000 else 0.1,
"estimated": i % 3 == 0 or 2000 < i < 3000,
} for i in range(10000)]
cd = ConsumptionData(records, "electricity", "kWh", record_type="arbitrary_start")
cd_down = cd.downsample('H')
assert np.isnan(cd.data["2015-01-01 00:00:00"])
assert_allclose(cd.data["2015-01-01 00:15:00"], 0.1)
assert cd.data.shape == (10000,)
assert cd.estimated["2015-01-01 00:00:00"] == True
assert cd.estimated["2015-01-01 00:15:00"] == False
assert cd.estimated.shape == (10000,)
assert_allclose(cd_down.data["2015-01-01 00:00"], 0.3)
assert_allclose(cd_down.data["2015-01-01 01:00"], 0.4)
assert cd_down.data.shape == (2500,)
assert cd_down.estimated["2015-01-01 00:00"] == True
assert cd_down.estimated["2015-01-01 01:00"] == False
assert cd_down.estimated.shape == (2500,)
def test_downsample_hourly_frequency():
records = [{
"start":
datetime(2015, 1, 1, tzinfo=pytz.UTC) + timedelta(seconds=i * 900),
"value":
np.nan if i % 30 == 0 or 1000 < i < 2000 else 0.1,
"estimated":
i % 3 == 0 or 2000 < i < 3000,
} for i in range(10000)]
cd = ConsumptionData(records,
"electricity",
"kWh",
record_type="arbitrary_start")
cd_down = cd.downsample('H')
assert np.isnan(cd.data["2015-01-01 00:00:00"])
assert_allclose(cd.data["2015-01-01 00:15:00"], 0.1)
assert cd.data.shape == (10000, )
assert cd.estimated["2015-01-01 00:00:00"] == True
assert cd.estimated["2015-01-01 00:15:00"] == False
assert cd.estimated.shape == (10000, )
assert_allclose(cd_down.data["2015-01-01 00:00"], 0.3)
assert_allclose(cd_down.data["2015-01-01 01:00"], 0.4)
assert cd_down.data.shape == (2500, )
assert cd_down.estimated["2015-01-01 00:00"] == True
assert cd_down.estimated["2015-01-01 01:00"] == False
assert cd_down.estimated.shape == (2500, )
def test_downsample_empty():
records = []
cd = ConsumptionData(records, "electricity", "kWh", record_type="arbitrary_start")
cd_down = cd.downsample('D')
assert_allclose(cd.data, cd_down.data)
assert_allclose(cd.estimated, cd_down.estimated)
def test_downsample_empty():
records = []
cd = ConsumptionData(records,
"electricity",
"kWh",
record_type="arbitrary_start")
cd_down = cd.downsample('D')
assert_allclose(cd.data, cd_down.data)
assert_allclose(cd.estimated, cd_down.estimated)
def test_downsample_single_record():
records = [{
"start": datetime(2015, 1, 1, tzinfo=pytz.UTC),
"value": 0,
"estimated": False
}]
cd = ConsumptionData(records, "electricity", "kWh", record_type="arbitrary_start")
cd_down = cd.downsample('D')
assert_allclose(cd.data, cd_down.data)
assert_allclose(cd.estimated, cd_down.estimated)
def test_downsample_two_day():
records = [{
"start": datetime(2015, 1, 1, tzinfo=pytz.UTC) + timedelta(days=2*i),
"value": 1.0,
"estimated": False,
} for i in range(100)]
cd = ConsumptionData(records, "electricity", "kWh", record_type="arbitrary_start")
cd_down = cd.downsample('D')
assert_allclose(cd.data, cd_down.data)
assert_allclose(cd.estimated, cd_down.estimated)
def test_downsample_single_record():
records = [{
"start": datetime(2015, 1, 1, tzinfo=pytz.UTC),
"value": 0,
"estimated": False
}]
cd = ConsumptionData(records,
"electricity",
"kWh",
record_type="arbitrary_start")
cd_down = cd.downsample('D')
assert_allclose(cd.data, cd_down.data)
assert_allclose(cd.estimated, cd_down.estimated)
def test_downsample_two_day():
records = [{
"start":
datetime(2015, 1, 1, tzinfo=pytz.UTC) + timedelta(days=2 * i),
"value":
1.0,
"estimated":
False,
} for i in range(100)]
cd = ConsumptionData(records,
"electricity",
"kWh",
record_type="arbitrary_start")
cd_down = cd.downsample('D')
assert_allclose(cd.data, cd_down.data)
assert_allclose(cd.estimated, cd_down.estimated)
