smrf.spatial package

smrf.spatial.grid module

2016-03-07 Scott Havens

Distributed forcing data over a grid using interpolation

class smrf.spatial.grid.GRID(config, mx, my, GridX, GridY, mz=None, GridZ=None, mask=None, metadata=None)[source]

Bases: object

Inverse distance weighting class - Standard IDW - Detrended IDW

calculateInterpolation(data, grid_method='linear')[source]

Interpolate over the grid

Parameters:
  • data – data to interpolate
  • mx – x locations for the points
  • my – y locations for the points
  • X – x locations in grid to interpolate over
  • Y – y locations in grid to interpolate over
detrendedInterpolation(data, flag=0, grid_method='linear')[source]

Interpolate using a detrended approach

Parameters:
  • data – data to interpolate
  • grid_method – scipy.interpolate.griddata interpolation method
detrendedInterpolationLocal(data, flag=0, grid_method='linear')[source]

Interpolate using a detrended approach

Parameters:
  • data – data to interpolate
  • grid_method – scipy.interpolate.griddata interpolation method
detrendedInterpolationMask(data, flag=0, grid_method='linear')[source]

Interpolate using a detrended approach

Parameters:
  • data – data to interpolate
  • grid_method – scipy.interpolate.griddata interpolation method

smrf.spatial.idw module

2015-11-30 Scott Havens updated 2015-12-31 Scott Havens

  • start using panda dataframes to help keep track of stations

Distributed forcing data over a grid using different methods

class smrf.spatial.idw.IDW(mx, my, GridX, GridY, mz=None, GridZ=None, power=2, zeroVal=-1)[source]

Bases: object

Inverse distance weighting class for distributing input data. Availables options are:

  • Standard IDW
  • Detrended IDW
calculateDistances()[source]

Calculate the distances from the measurement locations to the grid locations

calculateIDW(data, local=False)[source]

Calculate the IDW of the data at mx,my over GridX,GridY Inputs: data - is the same size at mx,my

calculateWeights()[source]

Calculate the weights for

detrendData(data, flag=0, zeros=None)[source]

Detrend the data in val using the heights zmeas data - is the same size at mx,my flag - 1 for positive, -1 for negative, 0 for any trend imposed

detrendedIDW(data, flag=0, zeros=None, local=False)[source]

Calculate the detrended IDW of the data at mx,my over GridX,GridY Inputs: data - is the same size at mx,my

retrendData(idw)[source]

Retrend the IDW values

Module contents