| sample_freq | string | | Offset String. Determining the intended sampling rate of the data-to-be aggregated |
| agg_freq | string | | Offset String. Determining the frequency to aggregate to. |
| sample_func | func or Nonetype | np.mean | Function to gather/aggregate data within every sampling interval. If `None` is passed, data is expected to already match a sampling grid of `sample_freq` |
| agg_func | func | np.mean | Aggregation function, used to downsample data from `sample_freq` to `agg_freq`. |
| invalid_flags | list or Nonetype | None | List of flags, to be regarded as signifying invalid values. By default (=`None`), `NaN` data and `BAD`-flagged data is considered invalid. See description below.|
| max_invalid | integer | `Inf` | Maximum number of invalid data points allowed for an aggregation interval to not get assigned `NaN` |
The function downsamples the data-to-be flagged from its intended sampling rate, assumed to be `sample_freq`, to a lower
sampling rate of `agg_freq`, by applying `agg_func` onto intervals of size `agg_freq`.
If `sample_func` is not `None`, in a preceeding step the data, contained in a sampling interval of `sample_freq`,
gets aggregated with `sample_func` to a `sampling_freq` sized grid.
The parameter `invalid_flags` allows for marking data values, flagged with a flag listed in `invalid_flags` as invalid.
By setting `max_invalid` to a value < `inf`, you can determine the aggregation of aggregation intervals containing
more than `max_invalid` invalid values to get assigned `NaN` value.
By default, `BAD` - flagged, as well as missing/ `NaN` data is considered invalid.
Although, the function is a wrapper around `harmonize` - the deharmonization of "real"
downsamples (`sample_freq` < `agg_freq`) is not recommended, since, the backtracking of flags would result in really
unexpected results.(BAD - flagging of all the values contained in an invalid aggregate)
(an option to just regain initial data frame shape with initial flags is to be implemented)
