TrackModelResult

TrackModelResult(
    data,
    *,
    name=None,
    item=None,
    quantity=None,
    x_item=0,
    y_item=1,
    keep_duplicates='first',
    aux_items=None,
)

Model result for a track.

Construct a TrackModelResult from a dfs0 file, mikeio.Dataset, pandas.DataFrame or a xarray.Datasets

Parameters

Name	Type	Description	Default
data	types.TrackType	The input data or file path	required
name	str | None	The name of the model result, by default None (will be set to file name or item name)	None
item	str | int | None	If multiple items/arrays are present in the input an item must be given (as either an index or a string), by default None	None
x_item	str | int | None	Item of the first coordinate of positions, by default None	0
y_item	str | int | None	Item of the second coordinate of positions, by default None	1
quantity	Quantity	Model quantity, for MIKE files this is inferred from the EUM information	None
keep_duplicates	(str, bool)	Strategy for handling duplicate timestamps (wraps xarray.Dataset.drop_duplicates) “first” to keep first occurrence, “last” to keep last occurrence, False to drop all duplicates, “offset” to add milliseconds to consecutive duplicates, by default “first”	'first'
aux_items	list[int | str] | None	Auxiliary items, by default None	None

Attributes

Name	Description
gtype	Geometry type
n_points	Number of data points
name	Name of time series (value item name)
node	node-coordinate
plot	Plot using the ComparerPlotter
quantity	Quantity of time series
time	Time index
values	Values as numpy array
x	x-coordinate
y	y-coordinate

Methods

Name	Description
copy	Create a deep copy of the TimeSeries.
equals	Check if two TimeSeries are equal
sel	Select data by label
to_dataframe	Convert matched data to pandas DataFrame
trim	Trim observation data to a given time interval

copy

TrackModelResult.copy()

Create a deep copy of the TimeSeries.

Returns

Name	Type	Description
	TimeSeries	Deep copy of the TimeSeries object

equals

TrackModelResult.equals(other)

Check if two TimeSeries are equal

sel

TrackModelResult.sel(**kwargs)

Select data by label

to_dataframe

TrackModelResult.to_dataframe()

Convert matched data to pandas DataFrame

Include x, y coordinates only if gtype=track

Returns

Name	Type	Description
	pd.DataFrame	data as a pandas DataFrame

trim

TrackModelResult.trim(
    start_time=None,
    end_time=None,
    buffer='1s',
    no_overlap='error',
)

Trim observation data to a given time interval

Parameters

Name	Type	Description	Default
start_time	pd.Timestamp	start time	None
end_time	pd.Timestamp	end time	None
buffer	str	buffer time around start and end time, by default “1s”	'1s'
no_overlap	Literal['ignore', 'error', 'warn']	Empty data handling.	'error'