# Path: tests/data.py
# class DummyData(object):
#     def __init__(self):
#         self.attrs = {
#                 'datetime': datetime(2016,6,4),
#                 'LATITUDE': 15, 'LONGITUDE': -38}
#         self.data = {
#                 'PRES': ma.fix_invalid(
#                     [2, 6, 10, 21, 44, 79, 100, 150,
#                         200, 400, 410, 650, 1000, 2000, 5000]),
#                 'TEMP': ma.fix_invalid(
#                     [25.32, 25.34, 25.34, 25.31, 24.99, 23.46, 21.85, 17.95,
#                         15.39, 11.08, 6.93, 7.93, 5.71, 3.58, np.nan]),
#                 'PSAL': ma.fix_invalid(
#                     [36.49, 36.51, 36.52, 36.53, 36.59, 36.76, 36.81, 36.39,
#                         35.98, 35.30, 35.28, 34.93, 34.86, np.nan, np.nan])}
# 
#     def __getitem__(self, key):
#         return self.data[key]
# 
#     def keys(self):
#         return self.data.keys()
# 
#     @property
#     def attributes(self):
#         print('attributes will be removed. Use attrs instead!')
#         return self.attrs


from hypothesis import given
from numpy import ma
from ..data import DummyData
import hypothesis.strategies as st
import numpy as np
    import pandas as pd
    import xarray as xr
        assert type(kwargs[x]) != type(da_kwargs[da])
    assert isinstance(y, np.ndarray)
    assert np.allclose(y, y2, equal_nan=True)


def compare_compound_feature_dataset(feature, data, *args, **kwargs):
    if not XARRAY_AVAILABLE:
        return

    ds = xr.Dataset({v:("N", data[v]) for v in data})

    y = feature(data, *args, **kwargs)
    y2 = feature(ds, *args, **kwargs)


def compare_feature_input_types(feature, *args, **kwargs):
    compare_feature_tuple(feature, *args, **kwargs)
    compare_feature_series(feature, *args, **kwargs)
    compare_feature_dataarray(feature, *args, **kwargs)


def compare_compound_feature_input_types(feature, *args, **kwargs):
    compare_compound_feature_tuple(feature, *args, **kwargs)
    compare_compound_feature_dataframe(feature, *args, **kwargs)
    compare_compound_feature_dataset(feature, *args, **kwargs)


def compare_tuple(Procedure, cfg):
    """Validate the results using a tuple
    """

# Path: tests/data.py
# class DummyData(object):
#     def __init__(self):
#         self.attrs = {
#                 'datetime': datetime(2016,6,4),
#                 'LATITUDE': 15, 'LONGITUDE': -38}
#         self.data = {
#                 'PRES': ma.fix_invalid(
#                     [2, 6, 10, 21, 44, 79, 100, 150,
#                         200, 400, 410, 650, 1000, 2000, 5000]),
#                 'TEMP': ma.fix_invalid(
#                     [25.32, 25.34, 25.34, 25.31, 24.99, 23.46, 21.85, 17.95,
#                         15.39, 11.08, 6.93, 7.93, 5.71, 3.58, np.nan]),
#                 'PSAL': ma.fix_invalid(
#                     [36.49, 36.51, 36.52, 36.53, 36.59, 36.76, 36.81, 36.39,
#                         35.98, 35.30, 35.28, 34.93, 34.86, np.nan, np.nan])}
# 
#     def __getitem__(self, key):
#         return self.data[key]
# 
#     def keys(self):
#         return self.data.keys()
# 
#     @property
#     def attributes(self):
#         print('attributes will be removed. Use attrs instead!')
#         return self.attrs


# Path: tests/qctests/compare.py
from hypothesis import given
from numpy import ma
from ..data import DummyData
import hypothesis.strategies as st
import numpy as np
    import pandas as pd
    import xarray as xr

        assert type(kwargs[x]) != type(da_kwargs[da])
    assert isinstance(y, np.ndarray)
    assert np.allclose(y, y2, equal_nan=True)


def compare_compound_feature_dataset(feature, data, *args, **kwargs):
    if not XARRAY_AVAILABLE:
        return

    ds = xr.Dataset({v:("N", data[v]) for v in data})

    y = feature(data, *args, **kwargs)
    y2 = feature(ds, *args, **kwargs)


def compare_feature_input_types(feature, *args, **kwargs):
    compare_feature_tuple(feature, *args, **kwargs)
    compare_feature_series(feature, *args, **kwargs)
    compare_feature_dataarray(feature, *args, **kwargs)


def compare_compound_feature_input_types(feature, *args, **kwargs):
    compare_compound_feature_tuple(feature, *args, **kwargs)
    compare_compound_feature_dataframe(feature, *args, **kwargs)
    compare_compound_feature_dataset(feature, *args, **kwargs)


def compare_tuple(Procedure, cfg):
    """Validate the results using a tuple
    """

    profile = DummyData()