glucopy.Gframe.conga#

Gframe.conga(per_day: bool = False, m: int = 1, slack: int = 0, ignore_na: bool = True, ddof: int = 1)[source]#

Calculates the Continuous Overall Net Glycaemic Action (CONGA).

\[CONGA = \sqrt{\frac{1}{k-ddof} \sum_{t=t1} (D_t - \bar D)^2}\]

\(ddof\) is the Delta Degrees of Freedom.
\(D_t\) is the difference between glycaemia at time t and t minus m hours ago.
\(\bar D\) is the mean of the differences (\(D_t\)).
\(k\) is the number of differences.

Parameters:

per_day (bool, default False) – If True, returns the CONGA for each day separately. If False, returns the CONGA for the entire dataset.
m (int, default 1) – Number of hours to use for the CONGA calculation.
slack (int, default 0) – Maximum number of minutes that the given time can differ from the actual time in the data.
ignore_na (bool, default True) – If True, ignores missing values (not found within slack). If False, raises an error if there are missing values.
ddof (int, default 1) – Delta Degrees of Freedom. The divisor used in calculations of standard deviation is N - ddof, where N represents the number of elements.

Returns:

conga – List of CONGA for each day.

Return type:

list

Examples

Calculating the CONGA for the entire dataset (default):

In [1]: import glucopy as gp

In [2]: gf = gp.data('prueba_1')

In [3]: gf.conga()
Out[3]: 45.718116219771694

Calculating the CONGA for each day with a 5 minutes slack:

In [4]: gf.conga(per_day=True, slack=5)
Out[4]: 
Day
2020-11-27    39.420203
2020-11-28    48.749528
2020-11-29    42.539827
2020-11-30    38.670023
2020-12-01    43.761159
                ...    
2021-03-14    39.162393
2021-03-15    55.081212
2021-03-16    41.223525
2021-03-17    40.082720
2021-03-18    38.906165
Name: CONGA, Length: 112, dtype: float64