pytuflow.INFO.time_series

pytuflow.INFO.time_series#

INFO.time_series(locations, data_types, time_fmt='relative', *args, **kwargs)#

Returns a time-series DataFrame for the given location(s) and data type(s).

It’s possible to pass in a well known shorthand for the data type e.g. q for flow.

The location can also be a filter string, e.g. channel to extract the time-series values for all channels. The following filters are available for the INFO class:

  • None: returns all locations

  • 1d: returns all locations (same as passing in None for locations)

  • node

  • channel

The returned column names will be in the format obj/data_type/location e.g. channel/flow/FC01.1_R. The data_type name in the column heading will be identical to the data type name passed into the function e.g. if h is used instead of water level, then the return will be node/h/FC01.1_R.1.

Parameters:

  • locations (str | list[str]) – The location to extract the time series data for. If None is passed in, all locations will be returned for the given data_types.

  • data_types (str | list[str]) – The data type to extract the time series data for. If None is passed in, all data types will be returned for the given locations.

  • time_fmt (str, optional) – The format for the time column. Options are relative or absolute.

Returns:

The time series data.

Return type:

pd.DataFrame

Examples

Extracting flow for a given channel.

>>> res = ...  # Assume res is loaded result class
>>> res.time_series('ds1', 'q')
Time (h)   channel/q/ds1
0.000000           0.000
0.016667           0.000
...                  ...
2.983334           8.670
3.000000           8.391

Extracting all data types for a given location

>>> res.time_series('ds1', None)
Time (h)  channel/Flow/ds1  channel/Velocity/ds1
0.000000             0.000                 0.000
0.016667             0.000                 0.000
...                    ...                   ...
2.983334             8.670                 1.348
3.000000             8.391                 1.333

Extracting all flow results

>>> res.time_series(None, 'flow')
Time (h)  channel/flow/ds1  ...  channel/flow/FC_weir1
0.000000             0.000  ...                    0.0
0.016667             0.000  ...                    0.0
...                    ...  ...                    ...
2.983334             8.670  ...                    0.0
3.000000             8.391  ...                    0.0
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