# Created by Octave 3.2.4, Tue Nov 23 12:52:45 2010 EST <mockbuild@jetta.math.Princeton.EDU.private>
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example_optiminterp
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 Example program of the optimal interpolation toolbox

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 Example program of the optimal interpolation toolbox


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optiminterp1
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 -- Loadable Function: [FI,VARI] = optiminterp1(X,F,VAR,LENX,M,XI)
     Performs a local 1D-optimal interpolation (objective analysis).

     Every elements in F corresponds to a data point (observation) at
     location X,Y with the error variance VAR.

     LENX is correlation length in x-direction.  M represents the
     number of influential points.

     XI is the data points where the field is interpolated. FI is the
     interpolated field and VARI is its error variance.

     The background field of the optimal interpolation is zero.  For a
     different background field, the background field must be
     subtracted from the observation, the difference is mapped by OI
     onto the background grid and finally the background is added back
     to the interpolated field.


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Performs a local 1D-optimal interpolation (objective analysis).

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optiminterp2
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 -- Loadable Function: [FI,VARI] =
          optiminterp2(X,Y,F,VAR,LENX,LENY,M,XI,YI)
     Performs a local 2D-optimal interpolation (objective analysis).

     Every elements in F corresponds to a data point (observation) at
     location X,Y with the error variance VAR.

     LENX and LENY are correlation length in x-direction and
     y-direction respectively.  M represents the number of influential
     points.

     XI and YI are the data points where the field is interpolated. FI
     is the interpolated field and VARI is its error variance.

     The background field of the optimal interpolation is zero.  For a
     different background field, the background field must be
     subtracted from the observation, the difference is mapped by OI
     onto the background grid and finally the background is added back
     to the interpolated field.  The error variance of the background
     field is assumed to have a error variance of one.


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Performs a local 2D-optimal interpolation (objective analysis).

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# length: 12
optiminterp3
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 -- Loadable Function: [FI,VARI] =
          optiminterp3(X,Y,Z,F,VAR,LENX,LENY,LENZ,M,XI,YI,ZI)
     Performs a local 3D-optimal interpolation (objective analysis).

     Every elements in F corresponds to a data point (observation) at
     location  X, Y, Z with the error variance var

     LENX,LENY and LENZ are correlation length in x-,y- and z-direction
     respectively.  M represents the number of influential points.

     XI,YI and ZI are the data points where the field is interpolated.
     FI is the interpolated field and VARI is its error variance.

     The background field of the optimal interpolation is zero.  For a
     different background field, the background field must be
     subtracted from the observation, the difference is mapped by OI
     onto the background grid and finally the background is added back
     to the interpolated field.

     The error variance of the background field is assumed to have a
     error variance of one.


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Performs a local 3D-optimal interpolation (objective analysis).

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optiminterp4
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 -- Loadable Function: [FI,VARI] =
          optiminterp4(X,Y,Z,T,F,VAR,LENX,LENY,LENZ,LENT,M,XI,YI,ZI,TI)
     Performs a local 4D-optimal interpolation (objective analysis).

     Every elements in F corresponds to a data point (observation) at
     location  X, Y, Z, T with the error variance var

     LENX,LENY,LENZ and LENT are correlation length in
     x-,y-,z-direction and time, respectively.  M represents the number
     of influential points.

     XI,YI,ZI and TI are the data points where the field is
     interpolated. FI is the interpolated field and VARI is its error
     variance.

     The background field of the optimal interpolation is zero.  For a
     different background field, the background field must be
     subtracted from the observation, the difference is mapped by OI
     onto the background grid and finally the background is added back
     to the interpolated field.

     The error variance of the background field is assumed to have a
     error variance of one.


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Performs a local 4D-optimal interpolation (objective analysis).

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# length: 12
optiminterpn
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 -- Loadable Function: [FI,VARI] =
          optiminterpn(X,Y,...,F,VAR,LENX,LENY,...,M,XI,YI,...)
     Performs a local nD-optimal interpolation (objective analysis).

     Every elements in F corresponds to a data point (observation) at
     location X,Y,... with the error variance VAR.

     LENX,LENY,... are correlation length in x-direction
     y-direction,... respectively.  M represents the number of
     influential points.

     XI,YI,... are the data points where the field is interpolated. FI
     is the interpolated field and VARI is its error variance.

     The background field of the optimal interpolation is zero.  For a
     different background field, the background field must be
     subtracted from the observation, the difference is mapped by OI
     onto the background grid and finally the background is added back
     to the interpolated field.  The error variance of the background
     field is assumed to have a error variance of one.


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Performs a local nD-optimal interpolation (objective analysis).

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test_optiminterp
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 Tests 1D, 2D and 3D optimal interpolation.
 All tests should pass; any error indicates that either 
 there is a bug in the optimal interpolation package or 
 that it is incrorrectly installed.

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 Tests 1D, 2D and 3D optimal interpolation.

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test_optiminterp_mult
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 Tests 1D, 2D and 3D optimal interpolation.
 All tests should pass; any error indicates that either 
 there is a bug in the optimal interpolation package or 
 that it is incrorrectly installed.

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# type: string
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 Tests 1D, 2D and 3D optimal interpolation.

