PointObservation

PointObservation(
    self,
    data,
    *,
    item=None,
    x=None,
    y=None,
    z=None,
    name=None,
    weight=1.0,
    quantity=None,
    aux_items=None,
    attrs=None,
)

Class for observations of fixed locations

Create a PointObservation from a dfs0 file or a pd.DataFrame.

Parameters

Name Type Description Default
data (str, Path, mikeio.Dataset, mikeio.DataArray, pd.DataFrame, pd.Series, xr.Dataset or xr.DataArray) filename (.dfs0 or .nc) or object with the data required
item (int, str) index or name of the wanted item/column, by default None if data contains more than one item, item must be given None
x float x-coordinate of the observation point, inferred from data if not given, else None None
y float y-coordinate of the observation point, inferred from data if not given, else None None
z float z-coordinate of the observation point, inferred from data if not given, else None None
name str user-defined name for easy identification in plots etc, by default file basename None
quantity Quantity The quantity of the observation, for validation with model results For MIKE dfs files this is inferred from the EUM information None
aux_items list list of names or indices of auxiliary items, by default None None
attrs dict additional attributes to be added to the data, by default None None
weight float weighting factor for skill scores, by default 1.0 1.0

Examples

>>> import modelskill as ms
>>> o1 = ms.PointObservation("klagshamn.dfs0", item=0, x=366844, y=6154291, name="Klagshamn")
>>> o2 = ms.PointObservation("klagshamn.dfs0", item="Water Level", x=366844, y=6154291)
>>> o3 = ms.PointObservation(df, item=0, x=366844, y=6154291, name="Klagshamn")
>>> o4 = ms.PointObservation(df["Water Level"], x=366844, y=6154291)

Attributes

Name Description
attrs Attributes of the observation
gtype Geometry type
n_points Number of data points
name Name of time series (value item name)
plot Plot using the ComparerPlotter
quantity Quantity of time series
time Time index
values Values as numpy array
weight Weighting factor for skill scores
x x-coordinate
y y-coordinate
z z-coordinate of observation point

Methods

Name Description
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

equals

PointObservation.equals(other)

Check if two TimeSeries are equal

sel

PointObservation.sel(**kwargs)

Select data by label

to_dataframe

PointObservation.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

PointObservation.trim(start_time=None, end_time=None, buffer='1s')

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'