def test_make_2d_no_freq(self):
filepath = Path(__file__).parent.parent
data_file_path = (filepath / "fixtures" / "data_transforms" /
"timeseries_standardized.csv")
data = pd.read_csv(data_file_path, index_col=0, parse_dates=True)
expected_data_file_path = (filepath / "fixtures" / "data_transforms" /
"power_mat.csv")
with open(expected_data_file_path) as file:
expected_output = np.genfromtxt(file, delimiter=",")
key = data.columns[0]
actual_output = make_2d(data, key=key, trim_start=True, trim_end=True)
np.testing.assert_array_almost_equal(expected_output, actual_output)
def test_make_2d_no_freq(self):
data_file_path = os.path.abspath(
os.path.join(
os.path.dirname(__file__),
"../fixtures/data_transforms/timeseries_standardized.csv"))
data = pd.read_csv(data_file_path, index_col=0, parse_dates=True)
expected_data_file_path = os.path.abspath(
os.path.join(os.path.dirname(__file__),
"../fixtures/data_transforms/power_mat.csv"))
with open(expected_data_file_path) as file:
expected_output = np.genfromtxt(file, delimiter=',')
key = data.columns[0]
actual_output = make_2d(data, key=key, trim_start=True, trim_end=True)
np.testing.assert_array_almost_equal(expected_output, actual_output)
def _make_2d_list(self, standardized_data_frame_list):
return [make_2d(standardized_data_frame, key='ac_power_01',
zero_nighttime=True, interp_missing=True) for
standardized_data_frame in standardized_data_frame_list]