def check_for_discontinuity(df, tolerance):
""" Returns a DataFrame object containing only rows and columns with values of <df>
at which there is an outlier first-order partial derivative along row axis.
Normal values are set to NaN.
tolerance: used in outlier test for first-order derivative, how many sigmas?
"""
if isinstance(df.index, DatetimeIndex):
# doesn't matter what value, this is just for allowing the division to occur
# result of is_outlier does not depend on index_unit
index_unit = np.timedelta64(365, 'D')
else:
index_unit = 1
der = derivative(df, index_unit)
return df[is_outlier(der, tolerance)].dropna(axis=0, how="all").dropna(axis=1, how="all")
def test_derivative__DataFrame(self):
result = calculator.derivative(pd.DataFrame({'a': [3, 2, 8], 'b': [3, 2, 11]}, index=[0, 1, 4]))
self.assertFrameEqual(result, pd.DataFrame({'a': [-1, 2], 'b': [-1, 3]}), check_dtype=False)
def test_derivative__Series(self):
result = calculator.derivative(pd.Series([3, 2, 8], index=[0, 1, 4]))
self.assertFrameEqual(result, pd.Series([-1, 2]), check_dtype=False)
result = calculator.derivative(pd.Series([3, 2, 8], index=[0, 1, 4]), index_unit=2)
self.assertFrameEqual(result, pd.Series([-2, 4]), check_dtype=False)