dfsu.Dfsu2DH

dfsu.Dfsu2DH(self, filename)

Attributes

Name	Description
deletevalue	File delete value
end_time	File end time
items	List of items
n_items	Number of items
n_timesteps	Number of time steps
start_time	File start time
timestep	Time step size in seconds

Methods

Name	Description
extract_track	Extract track data from a dfsu file
get_overset_grid	get a 2d grid that covers the domain by specifying spacing or shape
read	Read data from a dfsu file

extract_track

dfsu.Dfsu2DH.extract_track(track, items=None, method='nearest', dtype=np.float32)

Extract track data from a dfsu file

Parameters

Name	Type	Description	Default
track		with DatetimeIndex and (x, y) of track points as first two columns x,y coordinates must be in same coordinate system as dfsu	required
track		filename of csv or dfs0 file containing t,x,y	required
items		Extract only selected items, by number (0-based), or by name	None
method		Spatial interpolation method (‘nearest’ or ‘inverse_distance’) default=‘nearest’	'nearest'

Returns

Type	Description
mikeio.dataset.Dataset	A dataset with data dimension t The first two items will be x- and y- coordinates of track

Examples

>>> dfsu = mikeio.open("tests/testdata/NorthSea_HD_and_windspeed.dfsu")
>>> ds = dfsu.extract_track("tests/testdata/altimetry_NorthSea_20171027.csv")
>>> ds
<mikeio.Dataset>
dims: (time:1115)
time: 2017-10-26 04:37:37 - 2017-10-30 20:54:47 (1115 non-equidistant records)
geometry: GeometryUndefined()
items:
  0:  Longitude <Undefined> (undefined)
  1:  Latitude <Undefined> (undefined)
  2:  Surface elevation <Surface Elevation> (meter)
  3:  Wind speed <Wind speed> (meter per sec)

get_overset_grid

dfsu.Dfsu2DH.get_overset_grid(dx=None, dy=None, nx=None, ny=None, buffer=0.0)

get a 2d grid that covers the domain by specifying spacing or shape

Parameters

Name	Type	Description	Default
dx	float	grid resolution in x-direction (or in x- and y-direction)	None
dy	float	grid resolution in y-direction	None
nx	int	number of points in x-direction, by default None (the value will be inferred)	None
ny	int	number of points in y-direction, by default None (the value will be inferred)	None
buffer	float	positive to make the area larger, default=0 can be set to a small negative value to avoid NaN values all around the domain.	0.0

Returns

Type	Description
<mikeio.Grid2D>	2d grid

read

dfsu.Dfsu2DH.read(items=None, time=None, elements=None, area=None, x=None, y=None, keepdims=False, dtype=np.float32, error_bad_data=True, fill_bad_data_value=np.nan)

Read data from a dfsu file

Parameters

Name	Type	Description	Default
items	str | int | typing.Sequence[str | int] | None	Read only selected items, by number (0-based), or by name	None
time	int | str | slice | None	Read only selected time steps, by default None (=all)	None
keepdims	bool	When reading a single time step only, should the time-dimension be kept in the returned Dataset? by default: False	False
area	typing.Tuple[float, float, float, float] | None	Read only data inside (horizontal) area given as a bounding box (tuple with left, lower, right, upper) or as list of coordinates for a polygon, by default None	None
x	float | None	Read only data for elements containing the (x,y) points(s), by default None	None
y	float | None	Read only data for elements containing the (x,y) points(s), by default None	None
elements	typing.Collection[int] | None	Read only selected element ids, by default None	None
error_bad_data	bool	raise error if data is corrupt, by default True,	True
fill_bad_data_value	float	fill value for to impute corrupt data, used in conjunction with error_bad_data=False default np.nan	np.nan

Returns

Type	Description
mikeio.dataset.Dataset	A Dataset with data dimensions [t,elements]