| inter_method | [shift](#shift-methods)/[aggregation](#aggregation-methods)/[interpolation](#interpolation-methods) method string | | Method used to project values to the target grid |
| inter_method | [shift](#shift-methods)/[aggregation](#aggregation-methods)/[interpolation](#interpolation-methods) method string | | Method used to project values to the target grid |
| reshape_method | [shift](#shift-methods)/[aggregation](#aggregation-methods) method string | | Method used to project flags to the target grid |
| reshape_method | [shift](#shift-methods)/[aggregation](#aggregation-methods) method string | | Method used to project flags to the target grid |
| inter_agg | [aggregation function string](#aggregation-functions) | `"mean"` | Function used for aggregation, if an `inter_method` is given |
| inter_agg | [aggregation function string](#aggregation-functions) | `"mean"` | Function used for aggregation, if an `inter_method` is given |
| inter_order | int | `1` | The order of interpolation applied, if an an `inter_method` is given |
| inter_order | int | `1` | The order of interpolation applied, if an `inter_method` is given |
| inter_downcast | boolean | `False` | `True`: Decrease interpolation order if data chunks that are too short to be interpolated with order `inter_order`. <br/>`False`: Project those data chunks to `NAN`. <br/> Option only relevant if `inter_method` supports an `inter_order` |
| inter_downcast | bool | `False` | `True`: Decrease interpolation order if data chunks that are too short to be interpolated with order `inter_order`. <br/>`False`: Project those data chunks to `NAN`. <br/> Option only relevant if `inter_method` supports an `inter_order` |
| reshape_agg | [aggregation function string](#aggregation-functions) | `"max"` | Function used for the aggregation of flags. By default (`"max"`) the worst/highest flag is assigned |
| reshape_agg | [aggregation function string](#aggregation-functions) | `"max"` | Function used for the aggregation of flags. By default (`"max"`) the worst/highest flag is assigned |
| reshape_missing_flag | string | `None` | Valid flag value, that will be used for empty harmonization intervals. By default (`None`) such intervals are set to `BAD` |
| reshape_missing_flag | string | `None` | Valid flag value, that will be used for empty harmonization intervals. By default (`None`) such intervals are set to `BAD` |
| reshape_shift_comment | boolean | `True` | `True`: Shifted flags will be reset, other fields associated with a flag might get lost. <br/>`False`: Shifted flags will not be reset. <br/><br/> Only relevant for multi-column flagger and a given `inter_method` |
| reshape_shift_comment | bool | `True` | `True`: Shifted flags will be reset, other fields associated with a flag might get lost. <br/>`False`: Shifted flags will not be reset. <br/><br/> Only relevant for multi-column flagger and a given `inter_method` |
| data_missing_value | Any | `np.nan` | The value, indicating missing data |
| data_missing_value | Any | `np.nan` | The value, indicating missing data |
...
@@ -224,53 +224,55 @@ NOTE:
...
@@ -224,53 +224,55 @@ NOTE:
deharmonize(co_flagging)
deharmonize(co_flagging)
```
```
| parameter | data type | default value | description |
| parameter | data type | default value | description |
| co_flagging | boolean | | `False`: depending on the harmonization method applied, only overwrite ultimately preceeding, first succeeding or nearest flag to a harmonized flag. <br/>`True`: Depending on the harmonization method applied, overwrite all the values covered by the succeeding or preceeding sampling intervall, or, all the values in the range of a harmonic flags timestamp. |
| co_flagging | boolean | | Control the bahviour of the flag reprojection, see description |
After having calculated flags on an equidistant frequency grid, generated by
This functions projects harmonized datasets back to there original time stamps
a call to a harmonization function, you may want to project
and thereby restores the original data shape.
that new flags on to the original data index, or just restore the
original data shape. Then a call to `deharmonize` will do exactly that.
A combination of calls to one of the `harmonize*` functions and `deharmonize`,
allows to leverage information from data sets with differing timestamps/frequencies
`deharmonize` will check for harmonization information for the variable it is
and bring the generated information back to the original dataset.
applied on (automatically generated by any call to a harmonization function of that variable)
and than:
`deharmonize` will implicitly revert the methods and functions applied during
harmonization. I.e.:
1. Overwrite the harmonized data series with the original dataseries and its timestamps.
- The harmonized time series will be dropped in favor of the original one
2. Project the calculated flags onto the original index, by inverting the
- Flags are projected to the original time stamps if the are 'worse'/higher
flag projection method used for harmonization, meaning, that:
than the original. The direction of this projection is invert to the
* if the flags got shifted or aggregated forward, either the flag associated with the ultimatly preceeding
shift/aggregation direction in `harmonize*`, i.e. a forward shift in
original timestamp, to the harmonized flag (`co_flagging`=`False`),
`harmonize*` will result in a backward shift in `deharmonize` and vice
or all the flags, coverd by the harmonized flags preceeding sampling intervall (`co_flagging`=`True`)
versa.
get overwritten with the harmonized flag - if they are "better" than this harmonized flag.
- The projection behavior is controlled by the value of `co_flagging`:
(According to the flagging order of the current flagger.)
+`False`: Project a flag from the harmonized time series to a single
* if the flags got shifted or aggregated backwards, either the flag associated with the first succeeding
flag in the deharmonized data set
original timestamp, to the harmonized flag (`co_flagging`=`False`),
+`True`: Project a flag in the harmonized time series to all flags
or all the flags, coverd by the harmonized flags succeeding sampling intervall (`co_flagging`=`True`)
in the respective projection interval.
get overwritten with the harmonized flag - if they are "better" than this harmonized flag.
(According to the flagging order of the current flagger.)
Let's say during harmonization a dataset was aggregated to a lower
* if the flags got shifted or aggregated to the nearest harmonic index,
frequency (e.g. a time series with a frequency of 10 minutes was
either the flag associated with the flag, nearest, to the harmonized flag (`co_flagging`=`False`),
resampled to one with a frequency of 1 hour) and needs to be deharmonized.
or all the flags, covered by the harmonized flags range (`co_flagging`=`True`)
If `co_flagging` is `True`, the flags from the harmonized dataset
get overwritten with the harmonized flag - if they are "better" than this harmonized flag.
will be projected to all the six values within the aggregation period,
(According to the flagging order of the current flagger.)
if `co_flagging` is False, only the next/last/nearest value in the
deharmonized dataset will inherit the flag from the harmonized
