X-Git-Url: https://git.creatis.insa-lyon.fr/pubgit/?p=CreaPhase.git;a=blobdiff_plain;f=octave_packages%2Foptiminterp-0.3.3%2Fdoc-cache;fp=octave_packages%2Foptiminterp-0.3.3%2Fdoc-cache;h=6e1c6eb8a3fa27b7f4651fd323f3cb6c7af7a891;hp=0000000000000000000000000000000000000000;hb=c880e8788dfc484bf23ce13fa2787f2c6bca4863;hpb=1705066eceaaea976f010f669ce8e972f3734b05 diff --git a/octave_packages/optiminterp-0.3.3/doc-cache b/octave_packages/optiminterp-0.3.3/doc-cache new file mode 100644 index 0000000..6e1c6eb --- /dev/null +++ b/octave_packages/optiminterp-0.3.3/doc-cache @@ -0,0 +1,299 @@ +# Created by Octave 3.6.1, Fri Mar 30 22:42:15 2012 UTC +# name: cache +# type: cell +# rows: 3 +# columns: 8 +# name: +# type: sq_string +# elements: 1 +# length: 19 +example_optiminterp + + +# name: +# type: sq_string +# elements: 1 +# length: 54 + Example program of the optimal interpolation toolbox + + + +# name: +# type: sq_string +# elements: 1 +# length: 54 + Example program of the optimal interpolation toolbox + + + + +# name: +# type: sq_string +# elements: 1 +# length: 12 +optiminterp1 + + +# name: +# type: sq_string +# elements: 1 +# length: 790 + -- 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. + + + + +# name: +# type: sq_string +# elements: 1 +# length: 63 +Performs a local 1D-optimal interpolation (objective analysis). + + + +# name: +# type: sq_string +# elements: 1 +# length: 12 +optiminterp2 + + +# name: +# type: sq_string +# elements: 1 +# length: 955 + -- 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. + + + + +# name: +# type: sq_string +# elements: 1 +# length: 63 +Performs a local 2D-optimal interpolation (objective analysis). + + + +# name: +# type: sq_string +# elements: 1 +# length: 12 +optiminterp3 + + +# name: +# type: sq_string +# elements: 1 +# length: 971 + -- 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. + + + + +# name: +# type: sq_string +# elements: 1 +# length: 63 +Performs a local 3D-optimal interpolation (objective analysis). + + + +# name: +# type: sq_string +# elements: 1 +# length: 12 +optiminterp4 + + +# name: +# type: sq_string +# elements: 1 +# length: 1008 + -- 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. + + + + +# name: +# type: sq_string +# elements: 1 +# length: 63 +Performs a local 4D-optimal interpolation (objective analysis). + + + +# name: +# type: sq_string +# elements: 1 +# length: 12 +optiminterpn + + +# name: +# type: sq_string +# elements: 1 +# length: 971 + -- 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. + + + + +# name: +# type: sq_string +# elements: 1 +# length: 63 +Performs a local nD-optimal interpolation (objective analysis). + + + +# name: +# type: sq_string +# elements: 1 +# length: 16 +test_optiminterp + + +# name: +# type: sq_string +# elements: 1 +# length: 194 + 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. + + + +# name: +# type: sq_string +# elements: 1 +# length: 43 + Tests 1D, 2D and 3D optimal interpolation. + + + +# name: +# type: sq_string +# elements: 1 +# length: 21 +test_optiminterp_mult + + +# name: +# type: sq_string +# elements: 1 +# length: 194 + 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. + + + +# name: +# type: sq_string +# elements: 1 +# length: 43 + Tests 1D, 2D and 3D optimal interpolation. + + + + +