Mercurial > octave
view scripts/general/interp2.m @ 29949:f254c302bb9c
remove JIT compiler from Octave sources
As stated in the NEWS file entry added with this changeset, no one
has ever seriously taken on further development of the JIT compiler in
Octave since it was first added as part of a Google Summer of Code
project in 2012 and it still does nothing significant. It is out of
date with the default interpreter that walks the parse tree. Even
though we have fixed the configure script to disable it by default,
people still ask questions about how to build it, but it doesn’t seem
that they are doing that to work on it but because they think it will
make Octave code run faster (it never did, except for some extremely
simple bits of code as examples for demonstration purposes only).
* NEWS: Note change.
* configure.ac, acinclude.m4: Eliminate checks and macros related to
the JIT compiler and LLVM.
* basics.txi, install.txi, octave.texi, vectorize.txi: Remove mention
of JIT compiler and LLVM.
* jit-ir.cc, jit-ir.h, jit-typeinfo.cc, jit-typeinfo.h, jit-util.cc,
jit-util.h, pt-jit.cc, pt-jit.h: Delete.
* libinterp/parse-tree/module.mk: Update.
* Array-jit.cc: Delete.
* libinterp/template-inst/module.mk: Update.
* test/jit.tst: Delete.
* test/module.mk: Update.
* interpreter.cc (interpreter::interpreter): Don't check options for
debug_jit or jit_compiler.
* toplev.cc (F__octave_config_info__): Remove JIT compiler and LLVM
info from struct.
* ov-base.h (octave_base_value::grab, octave_base_value::release):
Delete.
* ov-builtin.h, ov-builtin.cc (octave_builtin::to_jit,
octave_builtin::stash_jit): Delete.
(octave_builtin::m_jtype): Delete data member and all uses.
* ov-usr-fcn.h, ov-usr-fcn.cc (octave_user_function::m_jit_info):
Delete data member and all uses.
(octave_user_function::get_info, octave_user_function::stash_info): Delete.
* options.h (DEBUG_JIT_OPTION, JIT_COMPILER_OPTION): Delete macro
definitions and all uses.
* octave.h, octave.cc (cmdline_options::cmdline_options): Don't handle
DEBUG_JIT_OPTION, JIT_COMPILER_OPTION): Delete.
(cmdline_options::debug_jit, cmdline_options::jit_compiler): Delete
functions and all uses.
(cmdline_options::m_debug_jit, cmdline_options::m_jit_compiler): Delete
data members and all uses.
(octave_getopt_options long_opts): Remove "debug-jit" and
"jit-compiler" from the list.
* pt-eval.cc (tree_evaluator::visit_simple_for_command,
tree_evaluator::visit_complex_for_command,
tree_evaluator::visit_while_command,
tree_evaluator::execute_user_function): Eliminate JIT compiler code.
* pt-loop.h, pt-loop.cc (tree_while_command::get_info,
tree_while_command::stash_info, tree_simple_for_command::get_info,
tree_simple_for_command::stash_info): Delete functions and all uses.
(tree_while_command::m_compiled, tree_simple_for_command::m_compiled):
Delete member variable and all uses.
* usage.h (usage_string, octave_print_verbose_usage_and_exit): Remove
[--debug-jit] and [--jit-compiler] from the message.
* Array.h (Array<T>::Array): Remove constructor that was only intended
to be used by the JIT compiler.
(Array<T>::jit_ref_count, Array<T>::jit_slice_data,
Array<T>::jit_dimensions, Array<T>::jit_array_rep): Delete.
* Marray.h (MArray<T>::MArray): Remove constructor that was only
intended to be used by the JIT compiler.
* NDArray.h (NDArray::NDarray): Remove constructor that was only
intended to be used by the JIT compiler.
* dim-vector.h (dim_vector::to_jit): Delete.
(dim_vector::dim_vector): Remove constructor that was only intended to
be used by the JIT compiler.
* codeql-analysis.yaml, make.yaml: Don't require llvm-dev.
* subst-config-vals.in.sh, subst-cross-config-vals.in.sh: Don't
substitute OCTAVE_CONF_LLVM_CPPFLAGS, OCTAVE_CONF_LLVM_LDFLAGS, or
OCTAVE_CONF_LLVM_LIBS.
* Doxyfile.in: Don't define HAVE_LLVM.
* aspell-octave.en.pws: Eliminate jit, JIT, and LLVM from the list of
spelling exceptions.
* build-env.h, build-env.in.cc (LLVM_CPPFLAGS, LLVM_LDFLAGS,
LLVM_LIBS): Delete variables and all uses.
* libinterp/corefcn/module.mk (%canon_reldir%_libcorefcn_la_CPPFLAGS):
Remove $(LLVM_CPPFLAGS) from the list.
* libinterp/parse-tree/module.mk (%canon_reldir%_libparse_tree_la_CPPFLAGS):
Remove $(LLVM_CPPFLAGS) from the list.
author | John W. Eaton <jwe@octave.org> |
---|---|
date | Tue, 10 Aug 2021 16:42:29 -0400 |
parents | 7854d5752dd2 |
children | 01de0045b2e3 |
line wrap: on
line source
######################################################################## ## ## Copyright (C) 2000-2021 The Octave Project Developers ## ## See the file COPYRIGHT.md in the top-level directory of this ## distribution or <https://octave.org/copyright/>. ## ## This file is part of Octave. ## ## Octave is free software: you can redistribute it and/or modify it ## under the terms of the GNU General Public License as published by ## the Free Software Foundation, either version 3 of the License, or ## (at your option) any later version. ## ## Octave is distributed in the hope that it will be useful, but ## WITHOUT ANY WARRANTY; without even the implied warranty of ## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the ## GNU General Public License for more details. ## ## You should have received a copy of the GNU General Public License ## along with Octave; see the file COPYING. If not, see ## <https://www.gnu.org/licenses/>. ## ######################################################################## ## -*- texinfo -*- ## @deftypefn {} {@var{zi} =} interp2 (@var{x}, @var{y}, @var{z}, @var{xi}, @var{yi}) ## @deftypefnx {} {@var{zi} =} interp2 (@var{z}, @var{xi}, @var{yi}) ## @deftypefnx {} {@var{zi} =} interp2 (@var{z}, @var{n}) ## @deftypefnx {} {@var{zi} =} interp2 (@var{z}) ## @deftypefnx {} {@var{zi} =} interp2 (@dots{}, @var{method}) ## @deftypefnx {} {@var{zi} =} interp2 (@dots{}, @var{method}, @var{extrap}) ## ## Two-dimensional interpolation. ## ## Interpolate reference data @var{x}, @var{y}, @var{z} to determine @var{zi} ## at the coordinates @var{xi}, @var{yi}. The reference data @var{x}, @var{y} ## can be matrices, as returned by @code{meshgrid}, in which case the sizes of ## @var{x}, @var{y}, and @var{z} must be equal. If @var{x}, @var{y} are ## vectors describing a grid then @code{length (@var{x}) == columns (@var{z})} ## and @code{length (@var{y}) == rows (@var{z})}. In either case the input ## data must be strictly monotonic. ## ## If called without @var{x}, @var{y}, and just a single reference data matrix ## @var{z}, the 2-D region ## @code{@var{x} = 1:columns (@var{z}), @var{y} = 1:rows (@var{z})} is assumed. ## This saves memory if the grid is regular and the distance between points is ## not important. ## ## If called with a single reference data matrix @var{z} and a refinement ## value @var{n}, then perform interpolation over a grid where each original ## interval has been recursively subdivided @var{n} times. This results in ## @code{2^@var{n}-1} additional points for every interval in the original ## grid. If @var{n} is omitted a value of 1 is used. As an example, the ## interval [0,1] with @code{@var{n}==2} results in a refined interval with ## points at [0, 1/4, 1/2, 3/4, 1]. ## ## The interpolation @var{method} is one of: ## ## @table @asis ## @item @qcode{"nearest"} ## Return the nearest neighbor. ## ## @item @qcode{"linear"} (default) ## Linear interpolation from nearest neighbors. ## ## @item @qcode{"pchip"} ## Piecewise cubic Hermite interpolating polynomial---shape-preserving ## interpolation with smooth first derivative. ## ## @item @qcode{"cubic"} ## Cubic interpolation (same as @qcode{"pchip"}). ## ## @item @qcode{"spline"} ## Cubic spline interpolation---smooth first and second derivatives ## throughout the curve. ## @end table ## ## @var{extrap} is a scalar number. It replaces values beyond the endpoints ## with @var{extrap}. Note that if @var{extrap} is used, @var{method} must ## be specified as well. If @var{extrap} is omitted and the @var{method} is ## @qcode{"spline"}, then the extrapolated values of the @qcode{"spline"} are ## used. Otherwise the default @var{extrap} value for any other @var{method} ## is @qcode{"NA"}. ## @seealso{interp1, interp3, interpn, meshgrid} ## @end deftypefn function ZI = interp2 (varargin) narginchk (1, 7); nargs = nargin; Z = X = Y = XI = YI = n = []; method = "linear"; extrap = []; ## Check for method and extrap if (nargs > 1 && ischar (varargin{end-1})) if (! isnumeric (varargin{end}) || ! isscalar (varargin{end})) error ("interp2: EXTRAP must be a numeric scalar"); endif extrap = varargin{end}; method = varargin{end-1}; nargs -= 2; elseif (ischar (varargin{end})) method = varargin{end}; nargs -= 1; endif if (method(1) == "*") warning ("interp2: ignoring unsupported '*' flag to METHOD"); method(1) = []; endif method = validatestring (method, ... {"nearest", "linear", "pchip", "cubic", "spline"}); ## Read numeric input switch (nargs) case 1 Z = varargin{1}; n = 1; case 2 [Z, n] = deal (varargin{1:nargs}); case 3 [Z, XI, YI] = deal (varargin{1:nargs}); case 5 [X, Y, Z, XI, YI] = deal (varargin{1:nargs}); otherwise print_usage (); endswitch ## Type checking if (! isnumeric (Z) || isscalar (Z) || ! ismatrix (Z)) error ("interp2: Z must be a 2-D matrix"); endif if (! isempty (n) && ! (isscalar (n) && n >= 0 && n == fix (n))) error ("interp2: N must be an integer >= 0"); endif ## Define X, Y, XI, YI if needed [zr, zc] = size (Z); if (isempty (X)) X = 1:zc; Y = 1:zr; endif if (! isnumeric (X) || ! isnumeric (Y)) error ("interp2: X, Y must be numeric matrices"); endif if (! isempty (n)) ## Calculate the interleaved input vectors. p = 2^n; XI = (p:p*zc)/p; YI = (p:p*zr)'/p; endif if (! isnumeric (XI) || ! isnumeric (YI)) error ("interp2: XI, YI must be numeric"); endif if (isvector (X) && isvector (Y)) X = X(:); Y = Y(:); elseif (size_equal (X, Y)) X = X(1,:).'; Y = Y(:,1); else error ("interp2: X and Y must be matrices of equal size"); endif if (columns (Z) != length (X) || rows (Z) != length (Y)) error ("interp2: X and Y size must match the dimensions of Z"); endif dx = diff (X); if (all (dx < 0)) X = flipud (X); Z = fliplr (Z); elseif (any (dx <= 0)) error ("interp2: X must be strictly monotonic"); endif dy = diff (Y); if (all (dy < 0)) Y = flipud (Y); Z = flipud (Z); elseif (any (dy <= 0)) error ("interp2: Y must be strictly monotonic"); endif if (any (strcmp (method, {"nearest", "linear", "pchip", "cubic"}))) ## If Xi and Yi are vectors of different orientation build a grid if ((isrow (XI) && iscolumn (YI)) || (iscolumn (XI) && isrow (YI))) [XI, YI] = meshgrid (XI, YI); elseif (! size_equal (XI, YI)) error ("interp2: XI and YI must be matrices of equal size"); endif ## if XI, YI are vectors, X and Y should share their orientation. if (isrow (XI)) if (rows (X) != 1) X = X.'; endif if (rows (Y) != 1) Y = Y.'; endif elseif (iscolumn (XI)) if (columns (X) != 1) X = X.'; endif if (columns (Y) != 1) Y = Y.'; endif endif xidx = lookup (X, XI, "lr"); yidx = lookup (Y, YI, "lr"); if (strcmp (method, "linear")) ## each quad satisfies the equation z(x,y)=a+b*x+c*y+d*xy ## ## a-b ## | | ## c-d a = Z(1:(zr - 1), 1:(zc - 1)); b = Z(1:(zr - 1), 2:zc) - a; c = Z(2:zr, 1:(zc - 1)) - a; d = Z(2:zr, 2:zc) - a - b - c; ## scale XI, YI values to a 1-spaced grid Xsc = (XI - X(xidx)) ./ (diff (X)(xidx)); Ysc = (YI - Y(yidx)) ./ (diff (Y)(yidx)); ## Get 2D index. idx = sub2ind (size (a), yidx, xidx); ## Dispose of the 1D indices at this point to save memory. clear xidx yidx; ## Apply plane equation ## Handle case where idx and coefficients are both vectors and resulting ## coeff(idx) follows orientation of coeff, rather than that of idx. forient = @(x) reshape (x, size (idx)); ZI = forient (a(idx)) ... + forient (b(idx)) .* Xsc ... + forient (c(idx)) .* Ysc ... + forient (d(idx)) .* Xsc.*Ysc; elseif (strcmp (method, "nearest")) ii = (XI - X(xidx) >= X(xidx + 1) - XI); jj = (YI - Y(yidx) >= Y(yidx + 1) - YI); idx = sub2ind (size (Z), yidx+jj, xidx+ii); ZI = Z(idx); elseif (strcmp (method, "pchip") || strcmp (method, "cubic")) if (length (X) < 2 || length (Y) < 2) error ("interp2: %s requires at least 2 points in each dimension", method); endif ## first order derivatives DX = __pchip_deriv__ (X, Z, 2); DY = __pchip_deriv__ (Y, Z, 1); ## Compute mixed derivatives row-wise and column-wise, use the average. DXY = (__pchip_deriv__ (X, DY, 2) + __pchip_deriv__ (Y, DX, 1))/2; ## do the bicubic interpolation hx = diff (X); hx = hx(xidx); hy = diff (Y); hy = hy(yidx); tx = (XI - X(xidx)) ./ hx; ty = (YI - Y(yidx)) ./ hy; ## construct the cubic hermite base functions in x, y ## formulas: ## b{1,1} = ( 2*t.^3 - 3*t.^2 + 1); ## b{2,1} = h.*( t.^3 - 2*t.^2 + t ); ## b{1,2} = (-2*t.^3 + 3*t.^2 ); ## b{2,2} = h.*( t.^3 - t.^2 ); ## optimized equivalents of the above: t1 = tx.^2; t2 = tx.*t1 - t1; xb{2,2} = hx.*t2; t1 = t2 - t1; xb{2,1} = hx.*(t1 + tx); t2 += t1; xb{1,2} = -t2; xb{1,1} = t2 + 1; t1 = ty.^2; t2 = ty.*t1 - t1; yb{2,2} = hy.*t2; t1 = t2 - t1; yb{2,1} = hy.*(t1 + ty); t2 += t1; yb{1,2} = -t2; yb{1,1} = t2 + 1; ZI = zeros (size (XI)); for i = 1:2 for j = 1:2 zidx = sub2ind (size (Z), yidx+(j-1), xidx+(i-1)); ZI += xb{1,i} .* yb{1,j} .* Z(zidx); ZI += xb{2,i} .* yb{1,j} .* DX(zidx); ZI += xb{1,i} .* yb{2,j} .* DY(zidx); ZI += xb{2,i} .* yb{2,j} .* DXY(zidx); endfor endfor endif else ## Check dimensions of XI and YI if (isvector (XI) && isvector (YI) && ! size_equal (XI, YI)) XI = XI(:).'; YI = YI(:); elseif (! size_equal (XI, YI)) error ("interp2: XI and YI must be matrices of equal size"); endif if (strcmp (method, "spline")) if (isgriddata (XI) && isgriddata (YI')) ZI = __splinen__ ({Y, X}, Z, {YI(:,1), XI(1,:)}, extrap, "spline"); else error ("interp2: XI, YI must have uniform spacing ('meshgrid' format)"); endif endif return; # spline doesn't need NA extrapolation value (MATLAB compatibility) endif ## extrapolation 'extrap' if (isempty (extrap)) extrap = NA; endif if (X(1) < X(end)) if (Y(1) < Y(end)) ZI(XI < X(1,1) | XI > X(end) | YI < Y(1,1) | YI > Y(end)) = extrap; else ZI(XI < X(1) | XI > X(end) | YI < Y(end) | YI > Y(1)) = extrap; endif else if (Y(1) < Y(end)) ZI(XI < X(end) | XI > X(1) | YI < Y(1) | YI > Y(end)) = extrap; else ZI(XI < X(1,end) | XI > X(1) | YI < Y(end) | YI > Y(1)) = extrap; endif endif endfunction function b = isgriddata (X) d1 = diff (X, 1, 1); b = ! any (d1(:) != 0); endfunction %!demo %! clf; %! colormap ("default"); %! A = [13,-1,12;5,4,3;1,6,2]; %! x = [0,1,4]; y = [10,11,12]; %! xi = linspace (min (x), max (x), 17); %! yi = linspace (min (y), max (y), 26)'; %! mesh (xi,yi,interp2 (x,y,A,xi,yi, "linear")); %! [x,y] = meshgrid (x,y); %! hold on; plot3 (x,y,A,"b*"); hold off; %!demo %! clf; %! colormap ("default"); %! [x,y,A] = peaks (10); %! x = x(1,:)'; y = y(:,1); %! xi = linspace (min (x), max (x), 41); %! yi = linspace (min (y), max (y), 41)'; %! mesh (xi,yi,interp2 (x,y,A,xi,yi, "linear")); %! [x,y] = meshgrid (x,y); %! hold on; plot3 (x,y,A,"b*"); hold off; %!demo %! clf; %! colormap ("default"); %! A = [13,-1,12;5,4,3;1,6,2]; %! x = [0,1,4]; y = [10,11,12]; %! xi = linspace (min (x), max (x), 17); %! yi = linspace (min (y), max (y), 26)'; %! mesh (xi,yi,interp2 (x,y,A,xi,yi, "nearest")); %! [x,y] = meshgrid (x,y); %! hold on; plot3 (x,y,A,"b*"); hold off; %!demo %! clf; %! colormap ("default"); %! [x,y,A] = peaks (10); %! x = x(1,:)'; y = y(:,1); %! xi = linspace (min (x), max (x), 41); %! yi = linspace (min (y), max (y), 41)'; %! mesh (xi,yi,interp2 (x,y,A,xi,yi, "nearest")); %! [x,y] = meshgrid (x,y); %! hold on; plot3 (x,y,A,"b*"); hold off; ## 'pchip' commented out since it is the same as 'cubic' %!#demo %! clf; %! colormap ("default"); %! A = [13,-1,12;5,4,3;1,6,2]; %! x = [0,1,2]; y = [10,11,12]; %! xi = linspace (min (x), max (x), 17); %! yi = linspace (min (y), max (y), 26)'; %! mesh (xi,yi,interp2 (x,y,A,xi,yi, "pchip")); %! [x,y] = meshgrid (x,y); %! hold on; plot3 (x,y,A,"b*"); hold off; ## 'pchip' commented out since it is the same as 'cubic' %!#demo %! clf; %! colormap ("default"); %! [x,y,A] = peaks (10); %! x = x(1,:)'; y = y(:,1); %! xi = linspace (min (x), max (x), 41); %! yi = linspace (min (y), max (y), 41)'; %! mesh (xi,yi,interp2 (x,y,A,xi,yi, "pchip")); %! [x,y] = meshgrid (x,y); %! hold on; plot3 (x,y,A,"b*"); hold off; %!demo %! clf; %! colormap ("default"); %! A = [13,-1,12;5,4,3;1,6,2]; %! x = [0,1,2]; y = [10,11,12]; %! xi = linspace (min (x), max (x), 17); %! yi = linspace (min (y), max (y), 26)'; %! mesh (xi,yi,interp2 (x,y,A,xi,yi, "cubic")); %! [x,y] = meshgrid (x,y); %! hold on; plot3 (x,y,A,"b*"); hold off; %!demo %! clf; %! colormap ("default"); %! [x,y,A] = peaks (10); %! x = x(1,:)'; y = y(:,1); %! xi = linspace (min (x), max (x), 41); %! yi = linspace (min (y), max (y), 41)'; %! mesh (xi,yi,interp2 (x,y,A,xi,yi, "cubic")); %! [x,y] = meshgrid (x,y); %! hold on; plot3 (x,y,A,"b*"); hold off; %!demo %! clf; %! colormap ("default"); %! A = [13,-1,12;5,4,3;1,6,2]; %! x = [0,1,2]; y = [10,11,12]; %! xi = linspace (min (x), max (x), 17); %! yi = linspace (min (y), max (y), 26)'; %! mesh (xi,yi,interp2 (x,y,A,xi,yi, "spline")); %! [x,y] = meshgrid (x,y); %! hold on; plot3 (x,y,A,"b*"); hold off; %!demo %! clf; %! colormap ("default"); %! [x,y,A] = peaks (10); %! x = x(1,:)'; y = y(:,1); %! xi = linspace (min (x), max (x), 41); %! yi = linspace (min (y), max (y), 41)'; %! mesh (xi,yi,interp2 (x,y,A,xi,yi, "spline")); %! [x,y] = meshgrid (x,y); %! hold on; plot3 (x,y,A,"b*"); hold off; %!test # simple test %! x = [1,2,3]; %! y = [4,5,6,7]; %! [X, Y] = meshgrid (x, y); %! orig = X.^2 + Y.^3; %! xi = [1.2,2, 1.5]; %! yi = [6.2, 4.0, 5.0]'; %! %! expected = ... %! [243, 245.4, 243.9; %! 65.6, 68, 66.5; %! 126.6, 129, 127.5]; %! result = interp2 (x,y,orig, xi, yi); %! %! assert (result, expected, 1000*eps); %!test # 2^n refinement form %! x = [1,2,3]; %! y = [4,5,6,7]; %! [X, Y] = meshgrid (x, y); %! orig = X.^2 + Y.^3; %! xi = [1:0.25:3]; yi = [4:0.25:7]'; %! expected = interp2 (x,y,orig, xi, yi); %! result = interp2 (orig, 2); %! %! assert (result, expected, 10*eps); %!test # matrix slice %! A = eye (4); %! assert (interp2 (A,[1:4],[1:4]), [1,1,1,1]); %!test # non-gridded XI,YI %! A = eye (4); %! assert (interp2 (A,[1,2;3,4],[1,3;2,4]), [1,0;0,1]); %!test # for values outside of boundaries %! x = [1,2,3]; %! y = [4,5,6,7]; %! [X, Y] = meshgrid (x,y); %! orig = X.^2 + Y.^3; %! xi = [0,4]; %! yi = [3,8]'; %! assert (interp2 (x,y,orig, xi, yi), [NA,NA;NA,NA]); %! assert (interp2 (x,y,orig, xi, yi,"linear", 0), [0,0;0,0]); %! assert (interp2 (x,y,orig, xi, yi,"linear", 2), [2,2;2,2]); %! assert (interp2 (x,y,orig, xi, yi,"spline", 2), [2,2;2,2]); %! assert (interp2 (x,y,orig, xi, yi,"linear", 0+1i), [0+1i,0+1i;0+1i,0+1i]); %! assert (interp2 (x,y,orig, xi, yi,"spline"), [27,43;512,528]); %!test # for values at boundaries %! A = [1,2;3,4]; %! x = [0,1]; %! y = [2,3]'; %! assert (interp2 (x,y,A,x,y,"linear"), A); %! assert (interp2 (x,y,A,x,y,"nearest"), A); %!test # for Matlab-compatible rounding for 'nearest' %! X = meshgrid (1:4); %! assert (interp2 (X, 2.5, 2.5, "nearest"), 3); ## re-order monotonically decreasing %!assert <*41838> (interp2 ([1 2 3], [3 2 1], magic (3), 2.5, 3), 3.5) %!assert <*41838> (interp2 ([3 2 1], [1 2 3], magic (3), 1.5, 1), 3.5) ## Linear interpretation with vector XI doesn't lead to matrix output %!assert <*49506> (interp2 ([2 3], [2 3 4], [1 2; 3 4; 5 6], [2 3], 3, "linear"), [3 4]) %!shared z, zout, tol %! z = [1 3 5; 3 5 7; 5 7 9]; %! zout = [1 2 3 4 5; 2 3 4 5 6; 3 4 5 6 7; 4 5 6 7 8; 5 6 7 8 9]; %! tol = 2 * eps; %! %!assert (interp2 (z), zout, tol) %!assert (interp2 (z, "linear"), zout, tol) %!assert (interp2 (z, "pchip"), zout, tol) %!assert (interp2 (z, "cubic"), zout, 10 * tol) %!assert (interp2 (z, "spline"), zout, tol) %!assert (interp2 (z, [2 3 1], [2 2 2]', "linear"), repmat ([5, 7, 3], [3, 1]), tol) %!assert (interp2 (z, [2 3 1], [2 2 2]', "pchip"), repmat ([5, 7, 3], [3, 1]), tol) %!assert (interp2 (z, [2 3 1], [2 2 2]', "cubic"), repmat ([5, 7, 3], [3, 1]), 10 * tol) %!assert (interp2 (z, [2 3 1], [2 2 2]', "spline"), repmat ([5, 7, 3], [3, 1]), tol) %!assert (interp2 (z, [2 3 1], [2 2 2], "linear"), [5 7 3], tol) %!assert (interp2 (z, [2 3 1], [2 2 2], "pchip"), [5 7 3], tol) %!assert (interp2 (z, [2 3 1], [2 2 2], "cubic"), [5 7 3], 10 * tol) %!assert (interp2 (z, [2 3 1], [2 2 2], "spline"), [5 7 3], tol) ## Test input validation %!error interp2 (1, 1, 1, 1, 1, 2) # only 5 numeric inputs %!error interp2 (1, 1, 1, 1, 1, 2, 2) # only 5 numeric inputs %!error <Z must be a 2-D matrix> interp2 ({1}) %!error <Z must be a 2-D matrix> interp2 (1,1,1) %!error <Z must be a 2-D matrix> interp2 (ones (2,2,2)) %!error <N must be an integer .= 0> interp2 (ones (2), ones (2)) %!error <N must be an integer .= 0> interp2 (ones (2), -1) %!error <N must be an integer .= 0> interp2 (ones (2), 1.5) %!warning <ignoring unsupported '\*' flag> interp2 (rand (3,3), 1, "*linear"); %!error <EXTRAP must be a numeric scalar> interp2 (1, 1, 1, 1, 1, 'linear', {1}) %!error <EXTRAP must be a numeric scalar> interp2 (1, 1, 1, 1, 1, 'linear', ones (2,2)) %!error <EXTRAP must be a numeric scalar> interp2 (1, 1, 1, 1, 1, 'linear', "abc") %!error <EXTRAP must be a numeric scalar> interp2 (1, 1, 1, 1, 1, 'linear', "extrap") %!error <X, Y must be numeric matrices> interp2 ({1}, 1, ones (2), 1, 1) %!error <X, Y must be numeric matrices> interp2 (1, {1}, ones (2), 1, 1) %!error <XI, YI must be numeric> interp2 (1, 1, ones (2), {1}, 1) %!error <XI, YI must be numeric> interp2 (1, 1, ones (2), 1, {1}) %!error <X and Y must be matrices of equal size> interp2 (ones (2,2), 1, ones (2), 1, 1) %!error <X and Y must be matrices of equal size> interp2 (ones (2,2), ones (2,3), ones (2), 1, 1) %!error <X and Y size must match the dimensions of Z> interp2 (1:3, 1:3, ones (3,2), 1, 1) %!error <X and Y size must match the dimensions of Z> interp2 (1:2, 1:2, ones (3,2), 1, 1) %!error <X must be strictly monotonic> interp2 ([1 0 2], 1:3, ones (3,3), 1, 1) %!error <Y must be strictly monotonic> interp2 (1:3, [1 0 2], ones (3,3), 1, 1) %!error <XI and YI must be matrices of equal size> interp2 (1:2, 1:2, ones (2), ones (2,2), 1) %!error <XI and YI must be matrices of equal size> interp2 (1:2, 1:2, ones (2), 1, ones (2,2)) %!error <XI, YI must have uniform spacing> interp2 (1:2, 1:2, ones (2), [1 2 4], [1 2 3], "spline") %!error <XI, YI must have uniform spacing> interp2 (1:2, 1:2, ones (2), [1 2 3], [1 2 4], "spline") %!error interp2 (1, 1, 1, 1, 1, "foobar")