scientimate.swanwaterlevelspvariedgrid#

swanwaterlevel = scientimate.swanwaterlevelspvariedgrid(xgrid, ygrid, xpointgrid, ypointgrid, waterlevelgrid, savedata='no', outfilename='swanwaterlevel.wl', outfilelocation=None, CalcMethod='linear')

Description#

Generate SWAN water level file for spatially varied water level from gridded input data

This function can be used for any other scalar variable as well

Inputs#

xgrid: x (longitude) of output grid points as a [M*N] array
ygrid: y (latitude) of output grid points as a [M*N] array
xpointgrid: x (longitude) of the locations that water level (or any scalar variable) is known in those locations as a [K*L] array
ypointgrid: y (latitude) of the locations that water level (or any scalar variable) is known in those locations as a [K*L] array
waterlevelgrid: Water level (or any scalar variable) at (xpointgrid,ypointgrid) as a [K*L*P] array

P is number of time steps for a time series
savedata=’no’: Define if save data in a file or not

‘no’: does not save

‘yes’: save data as ascii file
outfilename=’swanwaterlevel.wl’: Name of output file between ‘ ‘ mark, example: ‘swanwaterlevel.wl’

outfilename should have ‘.wl’ extension

In case of using other scalar varable than water level, use proper name and extension
outfilelocation=pwd: Location of output file between ‘ ‘ mark, example: ‘C:' in MATLAB, or ‘C:/’ in Python
CalcMethod=’linear’: Interpolation method

‘linear’: Use default or ‘linear’ method to interpolate

‘nearest’: Use nearest neighbor method to interpolate

Outputs#

swanwaterlevel: Spatially varied water level data (or any scalar variable) formated for SWAN

Water level data at each time step is assigned into the grid points

Examples#

import scientimate as sm
import numpy as np

xgrid,ygrid=np.meshgrid(np.linspace(-91,-90,100),np.linspace(28,30,100))
xpointgrid,ypointgrid=np.meshgrid(np.linspace(-92,-89,100),np.linspace(27,31,100))
waterlevelgrid=0.5+(0.6-0.5)*np.random.rand(100,100,4) #Data for 4 time steps
savedata='no'
outfilename='swanwaterlevel.wl'
outfilelocation=None
CalcMethod='linear'
swanwaterlevel=sm.swanwaterlevelspvariedgrid(xgrid,ygrid,xpointgrid,ypointgrid,waterlevelgrid,savedata,outfilename,outfilelocation,CalcMethod)


xgrid,ygrid=np.meshgrid(np.linspace(-91,-90,100),np.linspace(28,30,100))
xpointgrid,ypointgrid=np.meshgrid(np.linspace(-92,-89,100),np.linspace(27,31,100))
waterlevelgrid=0.5+(0.6-0.5)*np.random.rand(100,100) #Data for 1 time step
savedata='no'
outfilename='swanwaterlevel.wl'
outfilelocation=None
CalcMethod='linear'
swanwaterlevel=sm.swanwaterlevelspvariedgrid(xgrid,ygrid,xpointgrid,ypointgrid,waterlevelgrid,savedata,outfilename,outfilelocation,CalcMethod)

References#

Booij, N. R. R. C., Ris, R. C., & Holthuijsen, L. H. (1999). A third‐generation wave model for coastal regions: 1. Model description and validation. Journal of geophysical research: Oceans, 104(C4), 7649-7666.

SWAN Team. (2007). S WAN user manual. Delft University of Technology. The Netherlands.

scientimate.swanwaterlevelspvariedgrid

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