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-# Miscellaneous
-
-A collection of unrelated quality check functions.
-
-## Index
-
-- [flagRange](#flagrange)
-- [flagSeasonalRange](#flagseasonalrange)
-- [flagIsolated](#flagisolated)
-- [flagPattern](#flagpattern)
-- [flagMissing](#flagmissing)
-- [clearFlags](#clearflags)
-- [forceFlags](#forceflags)
-
-
-
-## flagRange
-
-```
-flagRange(min, max)
-```
-| parameter | data type | default value | description |
-| --------- | --------- | ------------- | ----------- |
-| min | float | | The upper bound for valid values |
-| max | float | | The lower bound for valid values |
-
-
-The function flags all values outside the closed interval
-$`[`$`min`, `max`$`]`$.
-
-## flagSeasonalRange
-
-```
-flagSeasonalRange(min, max, startmonth=1, endmonth=12, startday=1, endday=31)
-```
-
-| parameter | data type | default value | description |
-| --------- | ----------- | ---- | ----------- |
-| min | float | | The upper bound for valid values |
-| max | float | | The lower bound for valid values |
-| startmonth | integer | `1` | The interval start month |
-| endmonth | integer | `12` | The interval end month |
-| startday | integer | `1` | The interval start day |
-| endday | integer | `31` | The interval end day |
-
-The function does the same as `flagRange`, but only if the timestamp of the
-data-point lies in a defined interval, which is build from days and months only.
-In particular, the *year* is not considered in the Interval.
-
-The left
-boundary is defined by `startmonth` and `startday`, the right boundary by `endmonth`
-and `endday`. Both boundaries are inclusive. If the left side occurs later
-in the year than the right side, the interval is extended over the change of
-year (e.g. an interval of [01/12, 01/03], will flag values in December,
-January and February).
-
-NOTE: Only works for time-series-like datasets.
-
-
-## flagIsolated
-
-```
-flagIsolated(window, gap_window, group_window)
-
-```
-
-| parameter | data type | default value | description |
-|--------------|---------------------------------------------------------------|---------------|------------------------------------------------------------------------------------------------------------------------------------------------|
-| gap_window | [offset string](docs/ParameterDescriptions.md#offset-strings) | | The minimum size of the gap before and after a group of valid values, which makes this group considered as isolated. See condition (2) and (3) |
-| group_window | [offset string](docs/ParameterDescriptions.md#offset-strings) | | The maximum size of an isolated group of valid data. See condition (1). |
-
-The function flags arbitrary large groups of values, if they are surrounded by sufficiently
-large data gaps. A gap is defined as group of missing and/or flagged values.
-
-A continuous group of values
-$`x_{k}, x_{k+1},...,x_{k+n}`$ with timestamps $`t_{k}, t_{k+1}, ..., t_{k+n}`$
-is considered to be isolated, if:
-1. $` t_{k+n} - t_{k} \le `$ `group_window`
-2. None of the values $` x_i, ..., x_{k-1} `$, with $`t_{k-1} - t_{i} \ge `$ `gap_window` is valid or unflagged
-3. None of the values $` x_{k+n+1}, ..., x_{j} `$, with $`t_{j} - t_{k+n+1} \ge `$ `gap_window` is valid or unflagged
-
-
-## flagMissing
-
-```
-flagMissing(nodata=NaN)
-```
-
-| parameter | data type | default value | description |
-| --------- | ---------- | -------------- | ----------- |
-| nodata | any | `NAN` | A value that defines missing data |
-
-The function flags all values indicating missing data.
-
-
-
-
-## flagPattern
-
-```
-flagPattern(ref_datafield, sample_freq = '15 Min', method = 'dtw', min_distance = None)
-```
-
-
-| parameter | data type | default value | description |
-|-----------------------|---------------------------------------------------------------|---------------|------------------------------------------------------------------------------------------------------------------------------------------------------------|
-| ref_datafield | string | |Name of the reference datafield = "pattern" |
-| sample_freq | string | `"15 Min"` |Sample frequency to harmonize the data |
-| method | string | `"dtw "` |"dtw" for Dynamic Time Warping (DTW), "wavelet" for Wavelet Pattern Recognition Algorithm |
-| min_distance | float | `None` |For DTW - alogrithm: the minimum distance of two graphs in order to be classified as "different" |
-
-
-Implementation of the pattern recognition algorithms introduced in [Pattern Recognition](https://git.ufz.de/rdm-software/saqc/-/wikis/Pattern-Recognition).
-
-
-
-
-
-## clearFlags
-
-```
-clearFlags()
-```
-
-The funcion removes all previously set flags.
-
-## forceFlags
-
-```
-forceFlags(flag)
-```
-| parameter | data type | default value | description |
-| --------- | ----------- | ---- | ----------- |
-| flag | float/[flagging constant](docs/ParameterDescriptions.md#flagging-constants) | GOOD | The flag that is set unconditionally |
-
-The functions overwrites all previous set flags with the given flag.
-
-
-## flagDummy
-
-```
-flagDummy()
-```
-
-Identity function, i.e. the function does nothing.