1 # Created by Octave 3.6.1, Fri Mar 30 22:42:15 2012 UTC <root@t61>
13 # name: <cell-element>
17 Example program of the optimal interpolation toolbox
21 # name: <cell-element>
25 Example program of the optimal interpolation toolbox
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37 # name: <cell-element>
41 -- Loadable Function: [FI,VARI] = optiminterp1(X,F,VAR,LENX,M,XI)
42 Performs a local 1D-optimal interpolation (objective analysis).
44 Every elements in F corresponds to a data point (observation) at
45 location X,Y with the error variance VAR.
47 LENX is correlation length in x-direction. M represents the
48 number of influential points.
50 XI is the data points where the field is interpolated. FI is the
51 interpolated field and VARI is its error variance.
53 The background field of the optimal interpolation is zero. For a
54 different background field, the background field must be
55 subtracted from the observation, the difference is mapped by OI
56 onto the background grid and finally the background is added back
57 to the interpolated field.
62 # name: <cell-element>
66 Performs a local 1D-optimal interpolation (objective analysis).
70 # name: <cell-element>
77 # name: <cell-element>
81 -- Loadable Function: [FI,VARI] =
82 optiminterp2(X,Y,F,VAR,LENX,LENY,M,XI,YI)
83 Performs a local 2D-optimal interpolation (objective analysis).
85 Every elements in F corresponds to a data point (observation) at
86 location X,Y with the error variance VAR.
88 LENX and LENY are correlation length in x-direction and
89 y-direction respectively. M represents the number of influential
92 XI and YI are the data points where the field is interpolated. FI
93 is the interpolated field and VARI is its error variance.
95 The background field of the optimal interpolation is zero. For a
96 different background field, the background field must be
97 subtracted from the observation, the difference is mapped by OI
98 onto the background grid and finally the background is added back
99 to the interpolated field. The error variance of the background
100 field is assumed to have a error variance of one.
105 # name: <cell-element>
109 Performs a local 2D-optimal interpolation (objective analysis).
113 # name: <cell-element>
120 # name: <cell-element>
124 -- Loadable Function: [FI,VARI] =
125 optiminterp3(X,Y,Z,F,VAR,LENX,LENY,LENZ,M,XI,YI,ZI)
126 Performs a local 3D-optimal interpolation (objective analysis).
128 Every elements in F corresponds to a data point (observation) at
129 location X, Y, Z with the error variance var
131 LENX,LENY and LENZ are correlation length in x-,y- and z-direction
132 respectively. M represents the number of influential points.
134 XI,YI and ZI are the data points where the field is interpolated.
135 FI is the interpolated field and VARI is its error variance.
137 The background field of the optimal interpolation is zero. For a
138 different background field, the background field must be
139 subtracted from the observation, the difference is mapped by OI
140 onto the background grid and finally the background is added back
141 to the interpolated field.
143 The error variance of the background field is assumed to have a
144 error variance of one.
149 # name: <cell-element>
153 Performs a local 3D-optimal interpolation (objective analysis).
157 # name: <cell-element>
164 # name: <cell-element>
168 -- Loadable Function: [FI,VARI] =
169 optiminterp4(X,Y,Z,T,F,VAR,LENX,LENY,LENZ,LENT,M,XI,YI,ZI,TI)
170 Performs a local 4D-optimal interpolation (objective analysis).
172 Every elements in F corresponds to a data point (observation) at
173 location X, Y, Z, T with the error variance var
175 LENX,LENY,LENZ and LENT are correlation length in
176 x-,y-,z-direction and time, respectively. M represents the number
177 of influential points.
179 XI,YI,ZI and TI are the data points where the field is
180 interpolated. FI is the interpolated field and VARI is its error
183 The background field of the optimal interpolation is zero. For a
184 different background field, the background field must be
185 subtracted from the observation, the difference is mapped by OI
186 onto the background grid and finally the background is added back
187 to the interpolated field.
189 The error variance of the background field is assumed to have a
190 error variance of one.
195 # name: <cell-element>
199 Performs a local 4D-optimal interpolation (objective analysis).
203 # name: <cell-element>
210 # name: <cell-element>
214 -- Loadable Function: [FI,VARI] =
215 optiminterpn(X,Y,...,F,VAR,LENX,LENY,...,M,XI,YI,...)
216 Performs a local nD-optimal interpolation (objective analysis).
218 Every elements in F corresponds to a data point (observation) at
219 location X,Y,... with the error variance VAR.
221 LENX,LENY,... are correlation length in x-direction
222 y-direction,... respectively. M represents the number of
225 XI,YI,... are the data points where the field is interpolated. FI
226 is the interpolated field and VARI is its error variance.
228 The background field of the optimal interpolation is zero. For a
229 different background field, the background field must be
230 subtracted from the observation, the difference is mapped by OI
231 onto the background grid and finally the background is added back
232 to the interpolated field. The error variance of the background
233 field is assumed to have a error variance of one.
238 # name: <cell-element>
242 Performs a local nD-optimal interpolation (objective analysis).
246 # name: <cell-element>
253 # name: <cell-element>
257 Tests 1D, 2D and 3D optimal interpolation.
258 All tests should pass; any error indicates that either
259 there is a bug in the optimal interpolation package or
260 that it is incrorrectly installed.
264 # name: <cell-element>
268 Tests 1D, 2D and 3D optimal interpolation.
272 # name: <cell-element>
276 test_optiminterp_mult
279 # name: <cell-element>
283 Tests 1D, 2D and 3D optimal interpolation.
284 All tests should pass; any error indicates that either
285 there is a bug in the optimal interpolation package or
286 that it is incrorrectly installed.
290 # name: <cell-element>
294 Tests 1D, 2D and 3D optimal interpolation.