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github | mazhar-ansari-ardeh/BenchmarkFcns-master | keanefcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/keanefcn.m | 778 | utf_8 | 475b30973a903c14ec69b043132b14bb | % Computes the value of the Keane function.
% SCORES = KEANEFCN(X) computes the value of the Keane function at point X.
% KEANEFCN accepts a matrix of size M-by-2 and returns a vetor SCORES of
% size M-by-1 in which each row contains the function value for the
% corresponding row of X.
%
% Author: Mazhar Ansari Arde... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | schaffern1fcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/schaffern1fcn.m | 839 | utf_8 | 85dcb77c1cc0df4ea9afa0f684a0e779 | % Computes the value of the Schaffer N. 1 function.
% SCORES = SCHAFFERN1FCN(X) computes the value of the Schaffer N. 1
% function at point X. SCHAFFERN1FCN accepts a matrix of size M-by-2 and
% returns a vetor SCORES of size M-by-1 in which each row contains the
% function value for the corresponding row of X.
%
%... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | shubert4fcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/shubert4fcn.m | 674 | utf_8 | 9a223d89b2e4ce79dab73ab03e90332b | % Computes the value of the Shubert 4 function.
% SCORES = SHUBEERT4FCN(X) computes the value of the Shubert 4
% function at point X. SHUBEERT4FCN accepts a matrix of size M-by-N and
% returns a vetor SCORES of size M-by-1 in which each row contains the
% function value for the corresponding row of X.
%
% Author: Ma... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | qingfcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/qingfcn.m | 693 | utf_8 | b0e9cb9b1bbb5a3a7397bead70643148 | % Computes the value of the Qing function.
% SCORES = QINGFCN(X) computes the value of the Qing
% function at point X. QINGFCN accepts a matrix of size M-by-N and
% returns a vetor SCORES of size M-by-1 in which each row contains the
% function value for the corresponding row of X.
% For more information, please visi... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | schwefel222fcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/schwefel222fcn.m | 596 | utf_8 | 1672e251ca10c2d918c04515d06b01bb | % Computes the value of the Schwefel 2.22 function.
% SCORES = SCHWEFEL222FCN(X) computes the value of the Schwefel 2.22
% function at point X. SCHWEFEL222FCN accepts a matrix of size M-by-N and
% returns a vetor SCORES of size M-by-1 in which each row contains the
% function value for the corresponding row of X.
% ... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | ackleyn2fcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/ackleyn2fcn.m | 717 | utf_8 | 0faa9e763116ba967dbda3a39a537c2f | % Computes the value of the Ackley N. 2 function.
% SCORES = ACKLEYN2FCN(X) computes the value of the Ackley N. 2
% function at point X. ACKLEYN2FCN accepts a matrix of size M-by-2 and
% returns a vetor SCORES of size M-by-1 in which each row contains the
% function value for the corresponding row of X.
%
% Author: ... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | powellsumfcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/powellsumfcn.m | 667 | utf_8 | 3d9bf2ea28f7943ada98aaae33b240b8 | % Computes the value of the Powell Sum benchmark function.
% SCORES = POWELLSUMFCN(X) computes the value of the Powell Sum function at
% point X. POWELLSUMFCN accepts a matrix of size M-by-N and returns a vetor
% SCORES of size M-by-1 in which each row contains the
% function value for the corresponding row of X.
%... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | happycatfcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/happycatfcn.m | 881 | utf_8 | c654870b8aa609394b482e3e68307886 | % Computes the value of the Happy Cat benchmark function.
% SCORES = HAPPYCATFCN(X) computes the value of the Happy Cat function at
% point X. HAPPYCATFCN accepts a matrix of size M-by-N and returns a vetor
% SCORES of size M-by-1 in which each row contains the function value for
% the corresponding row of X.
% SCO... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | schwefel223fcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/schwefel223fcn.m | 562 | utf_8 | f17da97d48ef3b94697cfe93f2e0b3fa | % Computes the value of the Schwefel 2.23 function.
% SCORES = SCHWEFEL223FCN(X) computes the value of the Schwefel 2.23
% function at point X. SCHWEFEL223FCN accepts a matrix of size M-by-N and
% returns a vetor SCORES of size M-by-1 in which each row contains the
% function value for the corresponding row of X.
% ... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | rosenbrockfcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/rosenbrockfcn.m | 859 | utf_8 | d84361c62c39689f384227ad47326955 | % Computes the value of the Rosenbrock benchmark function.
% SCORES = ROSENBROCKFCN(X) computes the value of the Rosenbrock function
% at point X. ROSENBROCKFCN accepts a matrix of size M-by-N and returns a
% vetor SCORES of size M-by-1 in which each row contains the function value
% for the corresponding row of X... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | xinsheyangn2fcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/xinsheyangn2fcn.m | 681 | utf_8 | 854ee863ca43d8c71d4d0584840c633b | % Computes the value of the Xin-She Yang N. 2 function.
% SCORES = XINSHEYANGN2FCN(X) computes the value of the Xin-She Yang N. 2
% function at point X. XINSHEYANGN2FCN accepts a matrix of size M-by-N and
% returns a vetor SCORES of size M-by-1 in which each row contains the
% function value for the corresponding row... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | bartelsconnfcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/bartelsconnfcn.m | 758 | utf_8 | 85cf39da9f00dad8c9c96a7533fe2c40 | % Computes the value of the Bartels Conn benchmark function.
% SCORES = BARTELSCONNFCN(X) computes the value of the Bartels Conn
% function at point X. BARTELSCONNFCN accepts a matrix of size M-by-2 and
% returns a vetor SCORES of size M-by-1 in which each row contains the
% function value for the corresponding row ... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | meshfcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/meshfcn.m | 1,885 | utf_8 | b539ec4915956585571477a598d6cbe2 | % Draws mesh of a functionon the 3-dimensional space
%
% meshfcn(FCN, X, Y) draws the mesh of the function given by the
% handle FCN in the x-y plane defined over the intervals specified by X
% and Y
%
% meshfcn(FCN, X, Y, X_LABEL) draws the mesh and uses X_LABEL as the
% label of x-axis
%
% meshfcn(FCN, X, Y, X_... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | matyasfcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/matyasfcn.m | 801 | utf_8 | 441461aec82c3b08e65859ed94c0a38b | % Computes the value of the Matyas benchmark function.
% SCORES = MATYASFCN(X) computes the value of the Matyas function at
% point X. MATYASFCN accepts a matrix of size M-by-2 and returns a
% vetor SCORES of size M-by-1 in which each row contains the function value
% for the corresponding row of X.
% For more info... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | brownfcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/brownfcn.m | 767 | utf_8 | 100a40afdaa26f503a4b3acd7bc7e0b6 | % Computes the value of the Brown benchmark function.
% SCORES = BROWNFCN(X) computes the value of the Brown function at point X.
% BROWNFCN accepts a matrix of size M-by-N and returns a vetor SCORES of
% size M-by-1 in which each row contains the function value for the
% corresponding row of X. For more information ... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | schwefel221fcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/schwefel221fcn.m | 566 | utf_8 | a9cb938e99518253f201df232efca299 | % Computes the value of the Schwefel 2.21 function.
% SCORES = SCHWEFEL221FCN(X) computes the value of the Schwefel 2.21
% function at point X. SCHWEFEL221FCN accepts a matrix of size M-by-N and
% returns a vetor SCORES of size M-by-1 in which each row contains the
% function value for the corresponding row of X.
% ... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | shubertfcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/shubertfcn.m | 776 | utf_8 | d8705e1a29d879ac69d7afff09b2dc09 | % Computes the value of the Shubert function.
% SCORES = SHUBEERTFCN(X) computes the value of the Shubert
% function at point X. SHUBEERTFCN accepts a matrix of size M-by-N and
% returns a vetor SCORES of size M-by-1 in which each row contains the
% function value for the corresponding row of X.
% See also: shubert3... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | bealefcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/bealefcn.m | 879 | utf_8 | dc652ca954e0b5a335942c5856e0d65b | % Computes the value of the Beale benchmark function.
% SCORES = BEALEFCN(X) computes the value of the Beale function at
% point X. BEALEFCN accepts a matrix of size M-by-2 and returns a
% vetor SCORES of size M-by-1 in which each row contains the function value
% for the corresponding row of X.
% For more informat... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | ackleyfcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/ackleyfcn.m | 799 | utf_8 | 646e68c2adbf7529a42cd6a791ac3088 | % Computes the value of Ackley benchmark function.
% SCORES = ACKLEYFCN(X) computes the value of the Ackey function at point
% X. ACKLEYFCN accepts a matrix of size M-by-N and returns a vetor SCORES
% of size M-by-1 in which each row contains the function value for each row
% of X.
% For more information please visit: ... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | xinsheyangn3fcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/xinsheyangn3fcn.m | 1,466 | utf_8 | e95446e2505bc5490bceabbdaddc5727 | % Computes the value of the Xin-She Yang N. 3 function.
% The Xin-She Yang N. 3 function is a parametric function and it is
% behaviour can be controlled with two additional parameters 'beta' and
% 'm'. In this implementation, the parameters are optional and when not
% given, their default value will be used.
% SCORE... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | gramacyleefcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/gramacyleefcn.m | 804 | utf_8 | d1a44e600343026a2993482ed9f22ab9 | % Computes the value of the Gramacy & Lee benchmark function.
% SCORES = GRAMACYLEEFCN(X) computes the value of the Gramacy & Lee
% function at point X. GRAMACYLEEFCN accepts a matrix of size M-by-2 and
% returns a vetor SCORES of size M-by-1 in which each row contains the
% function value for the corresponding row ... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | schwefelfcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/schwefelfcn.m | 645 | utf_8 | 83f989653fd14d1882417d895a3f67f5 | % Computes the value of the Schwefel benchmark function.
% SCORES = SCHWEFELFCN(X) computes the value of the Schwefel function at
% point X. SCHWEFELFCN accepts a matrix of size M-by-2 and returns a
% vetor SCORES of size M-by-1 in which each row contains the function value
% for the corresponding row of X.
% For m... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | ridgefcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/ridgefcn.m | 982 | utf_8 | d9009761f470b475261cd43c68022545 | % Computes the value of the Ridge benchmark function.
% SCORES = RIDGEFCN(X) computes the value of the Ridge function at point X.
% RIDGEFCN accepts a matrix of size M-by-N and returns a vetor SCORES of
% size M-by-1 in which each row contains the function value for the
% corresponding row of X.
% SCORES = RIDGEFCN(... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | leonfcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/leonfcn.m | 672 | utf_8 | 05de416bc34be69902c5ab1b479c82d3 | % Computes the value of the Leon function.
% SCORES = LEONFCN(X) computes the value of the Leon function at point X.
% LEONFCN accepts a matrix of size M-by-2 and returns a vetor SCORES of
% size M-by-1 in which each row contains the function value for the
% corresponding row of X.
%
% Author: Mazhar Ansari Ardeh
% ... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | spherefcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/spherefcn.m | 616 | utf_8 | 3a9f5fa748f2dd837328661fe0555fbd | % Computes the value of Sphere benchmark function.
% SCORES = SPHEREFCN(X) computes the value of the Ackey function at
% point X. SPHEREFCN accepts a matrix of size M-by-N and returns a vetor
% SCORES of size M-by-1 in which each row contains the function value for
% each row of X.
% For more information please visit... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | alpinen1fcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/alpinen1fcn.m | 669 | utf_8 | a3bfdcc570752e5ccac0268fc86049ea | % Computes the value of the Alpine N. 1 function.
% SCORES = ALPINEN1FCN(X) computes the value of the Alpine N. 1
% function at point X. ALPINEN1FCN accepts a matrix of size M-by-N and
% returns a vetor SCORES of size M-by-1 in which each row contains the
% function value for the corresponding row of X.
% For more in... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | birdfcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/birdfcn.m | 745 | utf_8 | 70817648f5c53cfccfe36ebd3193dc06 | % Computes the value of the Bird function.
% SCORES = BIRDFCN(X) computes the value of the Bird
% function at point X. BIRDFCN accepts a matrix of size M-by-2 and
% returns a vetor SCORES of size M-by-1 in which each row contains the
% function value for the corresponding row of X.
%
% Author: Mazhar Ansari Ardeh
%... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | brentfcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/brentfcn.m | 778 | utf_8 | 2eedbed762fe962bf6fefb1178058990 | % Computes the value of the Egg Crate function.
% SCORES = BRENTFCN(X) computes the value of the Brent
% function at point X. BRENTFCN accepts a matrix of size M-by-2 and
% returns a vetor SCORES of size M-by-1 in which each row contains the
% function value for the corresponding row of X.
% For more information, pl... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | eggcratefcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/eggcratefcn.m | 789 | utf_8 | 8b1333d8669e31417c9de379bf45dc2c | % Computes the value of the Egg Crate function.
% SCORES = EGGCRATEFCN(X) computes the value of the Egg Crate
% function at point X. EGGCRATEFCN accepts a matrix of size M-by-2 and
% returns a vetor SCORES of size M-by-1 in which each row contains the
% function value for the corresponding row of X.
% For more infor... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | deckkersaartsfcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/deckkersaartsfcn.m | 855 | utf_8 | a97206fe28d156c5bee1dd4db5d117b2 | % Computes the value of the Deckkers-Aarts function.
% SCORES = DECKKERSAARTSFCN(X) computes the value of the Deckkers-Aarts
% function at point X. DECKKERSAARTSFCN accepts a matrix of size M-by-2 and
% returns a vetor SCORES of size M-by-1 in which each row contains the
% function value for the corresponding row o... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | contourfcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/contourfcn.m | 1,937 | utf_8 | 2b3a9cfe82443b20135e308ed9ecb3d8 | % Draws contour of a functionon the 3-dimensional space
%
% contourfcn(FCN, X, Y) draws the contour of the function given by the
% handle FCN in the x-y plane defined over the intervals specified by X
% and Y
%
% contourfcn(FCN, X, Y, X_LABEL) draws the contour and uses X_LABEL as the
% label of x-axis
%
% contou... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | salomonfcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/salomonfcn.m | 761 | utf_8 | edebc0c0f380908fdd195e6fd3f64a54 | % Computes the value of the Salomon's benchmark function.
% SCORES = SALOMONFCN(X) computes the value of the Salomon's
% function at point X. SALOMONFCN accepts a matrix of size M-by-N
% and returns a vetor SCORES of size M-by-1 in which each row contains the
% function value for the corresponding row of X.
% For... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | bohachevskyn2fcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/bohachevskyn2fcn.m | 776 | utf_8 | 049ed83636414da3751cfa917b98e1c6 | % Computes the value of Bohachevsky N. 2 benchmark function.
% SCORES = BOHACHEVSKYN2FCN(X) computes the value of the Bohachevsky N. 2
% function at point X. BOHACHEVSKYN2FCN accepts a matrix of size M-by-N and
% returns a vetor SCORES of size M-by-1 in which each row contains the
% function value for each row of X.
... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | styblinskitankfcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/styblinskitankfcn.m | 827 | utf_8 | e71e6037101592313dd41638278daa58 | % Computes the value of the Styblinski-Tank benchmark function.
% SCORES = STYBLINSKITANKFCN(X) computes the value of the Styblinski-Tank
% function at point X. STYBLINSKITANKFCN accepts a matrix of size M-by-2
% and returns a vetor SCORES of size M-by-1 in which each row contains the
% function value for the corre... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | bukinn6fcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/bukinn6fcn.m | 855 | utf_8 | 6ad3bf61ba232a8b9a27b184a8c42cfa | % Computes the value of the Bukin N. 6 benchmark function.
% SCORES = BUKINN6FCN(X) computes the value of the Bukin N. 6 function at
% point X. BUKINN6FCN accepts a matrix of size M-by-2 and returns a
% vetor SCORES of size M-by-1 in which each row contains the function value
% for the corresponding row of X.
% For... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | quarticfcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/quarticfcn.m | 646 | utf_8 | af5c5228f263df6e28dc9d8f444cc7a4 | % Computes the value of Quartic benchmark function.
% SCORES = QUARTICFCN(X) computes the value of the Quartic function at
% point X. QUARTICFCN accepts a matrix of size M-by-N and returns a vetor
% SCORES of size M-by-1 in which each row contains the function value for
% each row of X.
%
% Author: Mazhar Ansari Ard... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | rastriginfcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/rastriginfcn.m | 697 | utf_8 | 9e570db9f3799df65e0be82d20138340 | % Computes the value of Rastrigin benchmark function.
% SCORES = RASTRIGINFCN(X) computes the value of the Rastrigin function at
% point X. RASTRIGINFCN accepts a matrix of size M-by-N and returns a vetor
% SCORES of size M-by-1 in which each row contains the function value for
% the corresponding row of X.
% For mor... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | periodicfcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/periodicfcn.m | 626 | utf_8 | 079cd6af275165a53b214dfe4e508ca7 | % Computes the value of the Sum Square function.
% SCORES = SUMSQUAREFCN(X) computes the value of the Periodic
% function at point X. PERIODICFCN accepts a matrix of size M-by-N and
% returns a vetor SCORES of size M-by-1 in which each row contains the
% function value for the corresponding row of X.
%
% Author: Ma... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | sumsquaresfcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/sumsquaresfcn.m | 625 | utf_8 | 04f2c7f02ba5a6dfdfa8ed26b679f590 | % Computes the value of the Sum Squares function.
% SCORES = SUMSQUARESFCN(X) computes the value of the Sum Squares
% function at point X. SUMSQUARESFCN accepts a matrix of size M-by-N and
% returns a vetor SCORES of size M-by-1 in which each row contains the
% function value for the corresponding row of X.
%
% Auth... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | himmelblaufcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/himmelblaufcn.m | 830 | utf_8 | 2747f2f34bb2b4444d05bd5cce5f2282 | % Computes the value of the Himmelblau's benchmark function.
% SCORES = HIMMELBLAUFCN(X) computes the value of the Himmelblau's
% function at point X. HIMMELBLAUFCN accepts a matrix of size M-by-2
% and returns a vetor SCORES of size M-by-1 in which each row contains the
% function value for the corresponding row of ... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | dropwavefcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/dropwavefcn.m | 853 | utf_8 | f45070e4a0a781d22d61306c391df8eb | % Computes the value of the Drop-Wave benchmark function.
% SCORES = DROPWAVEFCN(X) computes the value of the Drop-Wave function at
% point X. DROPWAVEFCN accepts a matrix of size M-by-2 and returns a
% vetor SCORES of size M-by-1 in which each row contains the function value
% for the corresponding row of X.
% For... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | schaffern2fcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/schaffern2fcn.m | 921 | utf_8 | bb18ac35e7e4d8bb8f7e976b0b818506 | % Computes the value of the Schaffer N. 2 benchmark function.
% SCORES = SCHAFFERN2FCN(X) computes the value of the Schaffer N. 2 function
% at point X. SCHAFFERN2FCN accepts a matrix of size M-by-2 and returns a
% vetor SCORES of size M-by-1 in which each row contains the function value
% for the corresponding row ... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | griewankfcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/griewankfcn.m | 771 | utf_8 | 51e92b4cf255700c13aaff33109fe0c5 | % Computes the value of the Griewank benchmark function.
% SCORES = GRIEWANKFCN(X) computes the value of the Griewank's
% function at point X. GRIEWANKFCN accepts a matrix of size M-by-N
% and returns a vetor SCORES of size M-by-1 in which each row contains the
% function value for the corresponding row of X.
%
% Au... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | threehumpcamelfcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/threehumpcamelfcn.m | 891 | utf_8 | 589c50493978f953f42dc6d56d3b5225 | % Computes the value of the Three-hump camel benchmark function.
% SCORES = THREEHUMPCAMELFCN(X) computes the value of the Three-hump camel
% function at point X. THREEHUMPCAMELFCN accepts a matrix of size M-by-2
% and returns a vetor SCORES of size M-by-1 in which each row contains the
% function value for the c... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | boothfcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/boothfcn.m | 808 | utf_8 | e3fd2896eb05fa3a42a53d7414979fe8 | % Computes the value of the Booth benchmark function.
% SCORES = BOOTHFCN(X) computes the value of the Booth's function at
% point X. BOOTHFCN accepts a matrix of size M-by-2 and returns a
% vetor SCORES of size M-by-1 in which each row contains the function value
% for the corresponding row of X.
% For more inform... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | mccormickfcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/mccormickfcn.m | 835 | utf_8 | bcb0d8005c082fc7a319f4c87654a4db | % Computes the value of the McCormick benchmark function.
% SCORES = MCCORMICKFCN(X) computes the value of the McCormick function
% at point X. MCCORMICKFCN accepts a matrix of size M-by-2 and returns a
% vetor SCORES of size M-by-1 in which each row contains the function value
% for the corresponding row of X. For ... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | exponentialfcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/exponentialfcn.m | 584 | utf_8 | a9aed04b633f200a6d4cd25736eaf1b3 | % Computes the value of the Exponential function.
% SCORES = EXPONENTIALFCN(X) computes the value of the Exponential
% function at point X. EXPONENTIALFCN accepts a matrix of size M-by-N and
% returns a vetor SCORES of size M-by-1 in which each row contains the
% function value for the corresponding row of X.
%
% Au... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | abc.m | .m | BenchmarkFcns-master/optimiser/matlab/abc/abc.m | 6,250 | utf_8 | cdd9dacc1b0a969c50efd42766baaad5 | % Optimizes a given function with the Artificial Bee Colony algorithm (ABC).
% [X] = ABC(FITNESSFCN, NVARS) finds a local unconstrained minimum X to the
% FITNESSFCN using abc. NVARS is the dimension (number of design variables)
% of the FITNESSFCN. FITNESSFCN accepts a vector X of size 1-by-NVARS, and
% returns a sc... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | abcoptions.m | .m | BenchmarkFcns-master/optimiser/matlab/abc/abcoptions.m | 2,254 | utf_8 | fd4dc359e8764cdbe5a36f6d29d2e0bd | % AROOPTIONS Creates an option structure for Artificial Bee Colony
% algorithm.
% ABCOPTIONS will print the list of available options and their
% values.
% OPTIONS = ABCOPTIONS('default') will return an option structure that
% contains default values for the algorithm parameters.
% OPTIONS = ABCOPTIONS('list') will pr... |
github | trieutuanvnu/CLM-framework-master | demo.m | .m | CLM-framework-master/matlab_version/face_detection/face_detection_yu/demo.m | 2,293 | utf_8 | a03fbb6302d44b6640ec7a0045c77dea | % Function:
% demo
%
% Usage:
% This function demonstrates how to call the functions we provided to
% detect facial landmarks and get pose information. In the demo version,
% we only choose the largest face ROI detected to further localize its
% landmraks. And the current version is only suitable for wi... |
github | trieutuanvnu/CLM-framework-master | detect.m | .m | CLM-framework-master/matlab_version/face_detection/face_detection_yu/face_detect_64/detect.m | 5,497 | utf_8 | 8056df5cc27320fd2ab86a86bf4c3868 | function boxes = detect(input, model, thresh)
% Keep track of detected boxes and features
BOXCACHESIZE = 1000;
cnt = 0;
boxes.s = 0;
boxes.c = 0;
boxes.xy = 0;
boxes.level = 0;
boxes(BOXCACHESIZE) = boxes;
% Compute the feature pyramid and prepare filters
pyra = featpyramid(input,model);
[components,filters,resp] ... |
github | trieutuanvnu/CLM-framework-master | detect.m | .m | CLM-framework-master/matlab_version/face_detection/face_detection_yu/face_detect_32/detect.m | 5,497 | utf_8 | 8056df5cc27320fd2ab86a86bf4c3868 | function boxes = detect(input, model, thresh)
% Keep track of detected boxes and features
BOXCACHESIZE = 1000;
cnt = 0;
boxes.s = 0;
boxes.c = 0;
boxes.xy = 0;
boxes.level = 0;
boxes(BOXCACHESIZE) = boxes;
% Compute the feature pyramid and prepare filters
pyra = featpyramid(input,model);
[components,filters,resp] ... |
github | trieutuanvnu/CLM-framework-master | detect.m | .m | CLM-framework-master/matlab_version/face_detection/face_detection_zhu/face-release1.0-basic/detect.m | 5,142 | utf_8 | cd759876abb45da1a5be34a1237acd0a | function boxes = detect(input, model, thresh)
% Keep track of detected boxes and features
BOXCACHESIZE = 100000;
cnt = 0;
boxes.s = 0;
boxes.c = 0;
boxes.xy = 0;
boxes.level = 0;
boxes(BOXCACHESIZE) = boxes;
% Compute the feature pyramid and prepare filters
pyra = featpyramid(input,model);
[components,filters,resp... |
github | trieutuanvnu/CLM-framework-master | visualizemodel.m | .m | CLM-framework-master/matlab_version/face_detection/face_detection_zhu/face-release1.0-basic/visualizemodel.m | 3,577 | utf_8 | 251d5578a4c745e11ce795c8a8a4e1ed | function visualizemodel(model,compid)
if nargin<2
compid = 1:length(model.components);
end
pad = 2;
bs = 20;
for i = compid
c = model.components{i};
numparts = length(c);
Nmix = zeros(1,numparts);
for k = 1:numparts
Nmix(k) = length(c(k).filterid);
end
for k = 2:numparts... |
github | trieutuanvnu/CLM-framework-master | Fitting_from_bb.m | .m | CLM-framework-master/matlab_version/fitting/Fitting_from_bb.m | 10,736 | utf_8 | 45746313845759df5516fb5d4b9934b7 | function [ shape2D, global_params, local_params, final_lhood, landmark_lhoods, view_used ] = Fitting_from_bb( Image, DepthImage, bounding_box, PDM, patchExperts, clmParams, varargin)
%FITTING Summary of this function goes here
% Detailed explanation goes here
% the bounding box format is [minX, minY, maxX, maxY]... |
github | trieutuanvnu/CLM-framework-master | interp2_mine.m | .m | CLM-framework-master/matlab_version/fitting/interp2_mine.m | 20,801 | utf_8 | 220aa792ce5b22e812b4bad3b375b329 | function zi = interp2_mine(varargin)
%INTERP2 2-D interpolation (table lookup).
% ZI = INTERP2(X,Y,Z,XI,YI) interpolates to find ZI, the values of the
% underlying 2-D function Z at the points in matrices XI and YI.
% Matrices X and Y specify the points at which the data Z is given.
%
% XI can be a row vector, ... |
github | trieutuanvnu/CLM-framework-master | CalcJacobian.m | .m | CLM-framework-master/matlab_version/fitting/CalcJacobian.m | 1,333 | utf_8 | 1b62f9a4104c629ff80049c1bfea9567 | % This calculates the combined rigid with non-rigid Jacobian (non-rigid can
% eiher be expression or identity one)
function J = CalcJacobian(M, V, p_local, p_global)
n = size(M, 1)/3;
non_rigid_modes = size(V,2);
J = zeros(n*2, 6 + non_rigid_modes);
% now the layour is
% ---... |
github | trieutuanvnu/CLM-framework-master | PatchResponseCCNF.m | .m | CLM-framework-master/matlab_version/fitting/PatchResponseCCNF.m | 2,740 | utf_8 | 566d48e8656f756ae9af7d31d8b2ac55 | function [ responses ] = PatchResponseCCNF(patches, patch_experts_class, visibilities, patchExperts, window_size)
%PATCHRESPONSESVM Summary of this function goes here
% Detailed explanation goes here
normalisationOptions = patchExperts.normalisationOptionsCol;
patchSize = normalisationOptions.patchSize;
... |
github | trieutuanvnu/CLM-framework-master | NU_RLMS.m | .m | CLM-framework-master/matlab_version/fitting/NU_RLMS.m | 9,547 | utf_8 | 313ae3c571133af4a520db68eb97435f | function [ final_global, final_local, final_lhood, landmark_lhoods ] = NU_RLMS( ...
init_global, init_local, PDM, patchResponses, visibilities,...
view, reliabilities, baseShape, OrigToRefTransform, rigid, ...
clmParams, gauss_resp)
%RLMS Summary of this function goes here
% Detailed explanation goes here... |
github | trieutuanvnu/CLM-framework-master | PatchResponseSVM_multi_modal.m | .m | CLM-framework-master/matlab_version/fitting/PatchResponseSVM_multi_modal.m | 5,129 | utf_8 | e736ddb434521d9608edc3f3fc7b188d | function [ responses ] = PatchResponseSVM_multi_modal( patches, patch_experts, visibilities, normalisationOptions, clmParameters, window_size)
%PATCHRESPONSESVM Summary of this function goes here
% Detailed explanation goes here
patchSize = normalisationOptions.patchSize;
responses = ce... |
github | trieutuanvnu/CLM-framework-master | Collect_wild_imgs.m | .m | CLM-framework-master/matlab_version/experiments_iccv_300w/Collect_wild_imgs.m | 5,507 | utf_8 | 5b43676289f81ab146b99199ae89a6df | function [images, detections, labels] = Collect_wild_imgs(root_test_data)
use_afw = true;
use_lfpw = true;
use_helen = true;
use_ibug = true;
use_68 = true;
images = [];
labels = [];
detections = [];
if(use_afw)
[img, det, lbl] = Collect_AFW(... |
github | trieutuanvnu/CLM-framework-master | writeMatrix.m | .m | CLM-framework-master/matlab_version/PDM_helpers/writeMatrix.m | 428 | utf_8 | 3a2c87a966a8dc0f296d992d85f7d445 | % for easier readibility write them row by row
function writeMatrix(fileID, M, type)
fprintf(fileID, '%d\r\n', size(M,1));
fprintf(fileID, '%d\r\n', size(M,2));
fprintf(fileID, '%d\r\n', type);
for i=1:size(M,1)
if(type == 4 || type == 0)
fprintf(fileID, '%d ', M(i,:));
... |
github | trieutuanvnu/CLM-framework-master | fit_PDM_ortho_proj_to_2D_no_reg.m | .m | CLM-framework-master/matlab_version/PDM_helpers/fit_PDM_ortho_proj_to_2D_no_reg.m | 9,726 | utf_8 | a7d2a08fb6a085786ca26efe54c2241b | function [ a, R, T, T3D, params, error, shapeOrtho ] = fit_PDM_ortho_proj_to_2D_no_reg( M, E, V, shape2D)
%FITPDMTO2DSHAPE Summary of this function goes here
% Detailed explanation goes here
hidden = false;
% if some of the points are unavailable modify M, V, and shape2D (can
% later infer the actual sh... |
github | trieutuanvnu/CLM-framework-master | writeMatrixBin.m | .m | CLM-framework-master/matlab_version/PDM_helpers/writeMatrixBin.m | 911 | utf_8 | 636b1a9c9f27421bfde056250858f51e | % for easier readibility write them row by row
function writeMatrixBin(fileID, M, type)
% 4 bytes each for the description
fwrite(fileID, size(M,1), 'uint');
fwrite(fileID, size(M,2), 'uint');
fwrite(fileID, type, 'uint');
% Convert the matrix to OpenCV format (row minor as opposed to column
... |
github | trieutuanvnu/CLM-framework-master | fit_PDM_ortho_proj_to_2D.m | .m | CLM-framework-master/matlab_version/PDM_helpers/fit_PDM_ortho_proj_to_2D.m | 9,871 | utf_8 | 7accc2b0fee769eecc059448c7e69b26 | function [ a, R, T, T3D, params, error, shapeOrtho ] = fit_PDM_ortho_proj_to_2D( M, E, V, shape2D, f, cx, cy)
%FITPDMTO2DSHAPE Summary of this function goes here
% Detailed explanation goes here
params = zeros(size(E));
hidden = false;
% if some of the points are unavailable modify M, V, and shape2D (c... |
github | trieutuanvnu/CLM-framework-master | Collect_wild_imgs.m | .m | CLM-framework-master/matlab_version/bounding_box_mapping/Collect_wild_imgs.m | 5,461 | utf_8 | 69afbb7f409efa978b4ecfdea73220ee | function [images, detections, labels] = Collect_wild_imgs(root_test_data, use_afw, use_lfpw, use_helen, use_ibug)
use_68 = true;
images = [];
labels = [];
detections = [];
if(use_afw)
[img, det, lbl] = Collect_AFW(root_test_data, use_68);
images = cat... |
github | trieutuanvnu/CLM-framework-master | Create_data_66.m | .m | CLM-framework-master/matlab_version/face_validation/Create_data_66.m | 11,874 | utf_8 | 674e8b488296e88975ab8869f8db5d9b | function Create_data_66()
load '../models/pdm/pdm_66_multi_pie';
load '../models/tri_66.mat';
% This script uses the same format used for patch expert training, and
% expects the data to be there
dataset_loc = '../../../CCNF experiments/clnf/patch training/data_preparation/prepared_data/';
addpath('../PDM_helpers/');... |
github | trieutuanvnu/CLM-framework-master | Create_data_68.m | .m | CLM-framework-master/matlab_version/face_validation/Create_data_68.m | 11,691 | utf_8 | 9569c6c8664f9edea1584a02a1349028 | function Create_data_68()
load '../models/pdm/pdm_68_multi_pie';
load '../models/tri_68.mat';
% This script uses the same format used for patch expert training, and
% expects the data to be there
dataset_loc = '../../../CCNF experiments/clnf/patch_training/data_preparation/prepared_data/';
addpath('../PDM_helpers/');... |
github | trieutuanvnu/CLM-framework-master | Create_data_68_large.m | .m | CLM-framework-master/matlab_version/face_validation/Create_data_68_large.m | 12,397 | utf_8 | 53b5fd86000c1be10aa5f2ad2d32529e | function Create_data_68_large()
load '../models/pdm/pdm_68_aligned_wild';
load '../models/tri_68.mat';
% This script uses the same format used for patch expert training, and
% expects the data to be there (this can be found in
% https://github.com/TadasBaltrusaitis/CCNF)
% Replace with your location of training data... |
github | trieutuanvnu/CLM-framework-master | Collect_wild_imgs.m | .m | CLM-framework-master/matlab_version/face_validation/Collect_wild_imgs.m | 5,454 | utf_8 | e0042374523fb6085a4a7afb9ec734cb | function [images, detections, labels] = Collect_wild_imgs(root_test_data)
use_afw = true;
use_lfpw = true;
use_helen = true;
use_ibug = true;
use_68 = true;
images = [];
labels = [];
detections = [];
if(use_afw)
[img, det, lbl] = Collect_AFW(... |
github | trieutuanvnu/CLM-framework-master | InitialisePieceWiseAffine.m | .m | CLM-framework-master/matlab_version/face_validation/InitialisePieceWiseAffine.m | 2,628 | utf_8 | b9968dd94a35da481cbae3dec1e73e48 | function [ alphas, betas, triX, mask, xmin, ymin, npix ] = InitialisePieceWiseAffine( triangulation, sourcePoints )
%INITIALISEPIECEWICEAFFINE Summary of this function goes here
% Detailed explanation goes here
triangulation = triangulation + 1;
numPoints = size(sourcePoints, 1);
numTris = size(triangul... |
github | trieutuanvnu/CLM-framework-master | Create_data_66_large.m | .m | CLM-framework-master/matlab_version/face_validation/Create_data_66_large.m | 12,039 | utf_8 | 88cdd3874830743c782ad3eafd52867d | function Create_data_66_large()
load '../models/pdm/pdm_66_multi_pie';
load '../models/tri_66.mat';
% This script uses the same format used for patch expert training, and
% expects the data to be there (this can be found in
% https://github.com/TadasBaltrusaitis/CCNF)
% Replace with your location of training data
da... |
github | trieutuanvnu/CLM-framework-master | myOctaveVersion.m | .m | CLM-framework-master/matlab_version/face_validation/DeepLearnToolbox/util/myOctaveVersion.m | 169 | utf_8 | d4603482a968c496b66a4ed4e7c72471 | % return OCTAVE_VERSION or 'undefined' as a string
function result = myOctaveVersion()
if isOctave()
result = OCTAVE_VERSION;
else
result = 'undefined';
end
|
github | trieutuanvnu/CLM-framework-master | isOctave.m | .m | CLM-framework-master/matlab_version/face_validation/DeepLearnToolbox/util/isOctave.m | 108 | utf_8 | 4695e8d7c4478e1e67733cca9903f9ef | %detects if we're running Octave
function result = isOctave()
result = exist('OCTAVE_VERSION') ~= 0;
end |
github | trieutuanvnu/CLM-framework-master | makeLMfilters.m | .m | CLM-framework-master/matlab_version/face_validation/DeepLearnToolbox/util/makeLMfilters.m | 1,895 | utf_8 | 21950924882d8a0c49ab03ef0681b618 | function F=makeLMfilters
% Returns the LML filter bank of size 49x49x48 in F. To convolve an
% image I with the filter bank you can either use the matlab function
% conv2, i.e. responses(:,:,i)=conv2(I,F(:,:,i),'valid'), or use the
% Fourier transform.
SUP=49; % Support of the largest filter (must be... |
github | trieutuanvnu/CLM-framework-master | caenumgradcheck.m | .m | CLM-framework-master/matlab_version/face_validation/DeepLearnToolbox/CAE/caenumgradcheck.m | 3,618 | utf_8 | 6c481fc15ab7df32e0f476514100141a | function cae = caenumgradcheck(cae, x, y)
epsilon = 1e-4;
er = 1e-6;
disp('performing numerical gradient checking...')
for i = 1 : numel(cae.o)
p_cae = cae; p_cae.c{i} = p_cae.c{i} + epsilon;
m_cae = cae; m_cae.c{i} = m_cae.c{i} - epsilon;
[m_cae, p_cae] = caerun(m_cae, p_cae, x... |
github | trieutuanvnu/CLM-framework-master | Collect_wild_imgs.m | .m | CLM-framework-master/matlab_version/experiments_in_the_wild/Collect_wild_imgs.m | 5,507 | utf_8 | 5b43676289f81ab146b99199ae89a6df | function [images, detections, labels] = Collect_wild_imgs(root_test_data)
use_afw = true;
use_lfpw = true;
use_helen = true;
use_ibug = true;
use_68 = true;
images = [];
labels = [];
detections = [];
if(use_afw)
[img, det, lbl] = Collect_AFW(... |
github | trieutuanvnu/CLM-framework-master | compute_error_point_to_line_right_eye.m | .m | CLM-framework-master/matlab_version/experiments_in_the_wild/compute_error_point_to_line_right_eye.m | 2,807 | utf_8 | 8a3340813a8f382b8cbc66193d881e21 | function [ error_per_image ] = compute_error_point_to_line_right_eye( ground_truth_all, detected_points_all, occluded )
%compute_error
% compute the average point-to-point Euclidean error normalized by the
% inter-ocular distance (measured as the Euclidean distance between the
% outer corners of the eyes)
%
% I... |
github | trieutuanvnu/CLM-framework-master | compute_error_point_to_line_left_eye.m | .m | CLM-framework-master/matlab_version/experiments_in_the_wild/compute_error_point_to_line_left_eye.m | 2,806 | utf_8 | 7ee0c021e10837321563b4801cb8b499 | function [ error_per_image ] = compute_error_point_to_line_left_eye( ground_truth_all, detected_points_all, occluded )
%compute_error
% compute the average point-to-point Euclidean error normalized by the
% inter-ocular distance (measured as the Euclidean distance between the
% outer corners of the eyes)
%
% In... |
github | trieutuanvnu/CLM-framework-master | compute_brow_error_to_line.m | .m | CLM-framework-master/matlab_version/experiments_in_the_wild/compute_brow_error_to_line.m | 2,804 | utf_8 | 7039aa3de0164e4ea5bfa788c174dd85 | function [ error_per_image ] = compute_brow_error( ground_truth_all, detected_points_all, occluded )
%compute_error
% compute the average point-to-point Euclidean error of right eye normalized by the
% inter-ocular distance (measured as the Euclidean distance between the
% outer corners of the eyes)
%
% Inputs:... |
github | trieutuanvnu/CLM-framework-master | plotcov2.m | .m | CLM-framework-master/matlab_version/experiments_in_the_wild/hierarch_checks/plotcov2.m | 5,217 | utf_8 | 6c070f75d902dd37b4ccc0311074d4c6 | % PLOTCOV2 - Plots a covariance ellipse with major and minor axes
% for a bivariate Gaussian distribution.
%
% Usage:
% h = plotcov2(mu, Sigma[, OPTIONS]);
%
% Inputs:
% mu - a 2 x 1 vector giving the mean of the distribution.
% Sigma - a 2 x 2 symmetric positive semi-definite matrix giving
% ... |
github | trieutuanvnu/CLM-framework-master | compute_error_point_to_line_right_eye.m | .m | CLM-framework-master/matlab_version/experiments_in_the_wild/hierarch_checks/compute_error_point_to_line_right_eye.m | 2,830 | utf_8 | 0e29578273daec0c8d6c342eb53ae62c | function [ error_per_image ] = compute_error_point_to_line_right_eye( ground_truth_all, detected_points_all, occluded )
%compute_error
% compute the average point-to-point Euclidean error normalized by the
% inter-ocular distance (measured as the Euclidean distance between the
% outer corners of the eyes)
%
% I... |
github | trieutuanvnu/CLM-framework-master | compute_error_point_to_line_left_eye.m | .m | CLM-framework-master/matlab_version/experiments_in_the_wild/hierarch_checks/compute_error_point_to_line_left_eye.m | 2,829 | utf_8 | b0705a2c432d9be2f31536de4fa3b537 | function [ error_per_image ] = compute_error_point_to_line_left_eye( ground_truth_all, detected_points_all, occluded )
%compute_error
% compute the average point-to-point Euclidean error normalized by the
% inter-ocular distance (measured as the Euclidean distance between the
% outer corners of the eyes)
%
% In... |
github | trieutuanvnu/CLM-framework-master | writeMatrix.m | .m | CLM-framework-master/matlab_version/pdm_generation/PDM_helpers/writeMatrix.m | 428 | utf_8 | 3a2c87a966a8dc0f296d992d85f7d445 | % for easier readibility write them row by row
function writeMatrix(fileID, M, type)
fprintf(fileID, '%d\r\n', size(M,1));
fprintf(fileID, '%d\r\n', size(M,2));
fprintf(fileID, '%d\r\n', type);
for i=1:size(M,1)
if(type == 4 || type == 0)
fprintf(fileID, '%d ', M(i,:));
... |
github | trieutuanvnu/CLM-framework-master | fit_PDM_ortho_proj_to_2D.m | .m | CLM-framework-master/matlab_version/pdm_generation/PDM_helpers/fit_PDM_ortho_proj_to_2D.m | 9,871 | utf_8 | 7accc2b0fee769eecc059448c7e69b26 | function [ a, R, T, T3D, params, error, shapeOrtho ] = fit_PDM_ortho_proj_to_2D( M, E, V, shape2D, f, cx, cy)
%FITPDMTO2DSHAPE Summary of this function goes here
% Detailed explanation goes here
params = zeros(size(E));
hidden = false;
% if some of the points are unavailable modify M, V, and shape2D (c... |
github | trieutuanvnu/CLM-framework-master | findG.m | .m | CLM-framework-master/matlab_version/pdm_generation/nrsfm-em/findG.m | 1,188 | utf_8 | c81e58ce3f1a6f9066f2ecb4cb4dac67 | function G = findG(Rhat)
[F,D] = size(Rhat); F = F/2;
% Build matrix Q such that Q * v = [1,...,1,0,...,0] where v is a six
% element vector containg all six distinct elements of the Matrix C
%clear Q
for f = 1:F,
g = f + F;
h = g + F;
Q(f,:) = zt2(Rhat(f,:), Rhat(f,:));
Q(g,:) = zt2(Rhat(g,:), Rhat(g,:));
... |
github | trieutuanvnu/CLM-framework-master | prune_observations.m | .m | CLM-framework-master/matlab_version/pdm_generation/Wild_data_pdm/prune_observations.m | 1,145 | utf_8 | a9667d8c30c83debfac87a02012109cf | function [ observations ] = prune_observations( observations, percentage_to_keep )
%PRUNE_OBSERVATIONS Summary of this function goes here
% Detailed explanation goes here
distances = pdist(observations, @euclid_dist);
distances = squareform(distances);
m = max(distances(:));
distances(log... |
github | trieutuanvnu/CLM-framework-master | writePDM.m | .m | CLM-framework-master/matlab_version/pdm_generation/Wild_data_pdm/writePDM.m | 1,235 | utf_8 | b0e7f7dff0c7231a80b75e35435d0828 | function writePDM( V, E, M, outputFile, Vmorph, Emorph )
%WRITEPDM Summary of this function goes here
% Detailed explanation goes here
fId = fopen(outputFile,'w');
% number of elements
% Comment
fprintf(fId, '# The mean values of the components (in mm)\n');
writeMatrix(fId, M, 6);
... |
github | stephenjia/bmvc16_face-master | register_face_based_on_eyes.m | .m | bmvc16_face-master/image_crop/register_face_based_on_eyes.m | 5,983 | utf_8 | 5994339ba692b044e2c1d6ff60cae359 | % Extracts the face region from an image based on provided eye coordinates
%
% PROTOTYPE
% Y = register_face_based_on_eyes(X,eyes,size1)
%
% USAGE EXAMPLE(S)
%
% Example 1:
% eyes.x(1)=160; %These coordinates were obtained using getpts(),
% eyes.y(1)=184; %but could also be read from a fil... |
github | SIMOGroup/SIMO-Package-master | MPInterfaceScalar3D.m | .m | SIMO-Package-master/PreProcessing/MultiPatches/MPInterfaceScalar3D.m | 4,891 | utf_8 | cd36347f001732152b4d9087955c5c00 | % MP_INTERFACE_3D: create a global numbering of basis functions in three-dimensional multipatch geometries.
%
% [glob_num, glob_ndof] = mp_interface_3d (interfaces, sp);
%
% INPUT:
%
% interfaces: structure with the information of the interfaces between patches (see mp_geo_read_file)
% sp: object representi... |
github | SIMOGroup/SIMO-Package-master | MPInterfaceVector2D.m | .m | SIMO-Package-master/PreProcessing/MultiPatches/MPInterfaceVector2D.m | 4,611 | utf_8 | d31fe00262e4db47e2b3a06216dec926 | % MP_INTERFACE_VECTOR_2D: create a global numbering of vectorial basis functions in two-dimensional multipatch geometries.
%
% [GNum, GNDof] = mp_interface_vector_2d (Interfaces, sp);
%
% INPUT:
%
% Interfaces: structure with the information of the Interfaces between patches (see mp_geo_read_file)
% sp: obj... |
github | SIMOGroup/SIMO-Package-master | MPInterfaceVector3D.m | .m | SIMO-Package-master/PreProcessing/MultiPatches/MPInterfaceVector3D.m | 6,100 | utf_8 | 320650dcc02c23b7178e7449d2d27910 | function [GNum, GNDof] = MPInterfaceVector3D (Interfaces, Mesh, gluedFaces)
% function [GNum, GNDof] = MPInterfaceVector3D (Interfaces, Mesh, gluedFaces)
% modified from GeoPDEs code
if (~isempty(Interfaces))
GNum = cell(numel(Mesh), 1);
patchIntrfc = cell(numel(Mesh), 1);
ttform = cell(numel(Mesh), n... |
github | SIMOGroup/SIMO-Package-master | MPInterfaceScalar2D.m | .m | SIMO-Package-master/PreProcessing/MultiPatches/MPInterfaceScalar2D.m | 4,580 | utf_8 | b8a1cd998a90e0232fd117cf9e248eb8 | % MP_INTERFACE_2D: create a global numbering of basis functions in two-dimensional multipatch geometries.
%
% [glob_num, glob_ndof] = mp_interface_2d (interfaces, sp);
%
% INPUT:
%
% interfaces: structure with the information of the interfaces between patches (see mp_geo_read_file)
% sp: object representing... |
github | SIMOGroup/SIMO-Package-master | MPInterfaceScalar1D.m | .m | SIMO-Package-master/PreProcessing/MultiPatches/MPInterfaceScalar1D.m | 3,199 | utf_8 | aeab802ae30341f7dcf2afc61f87baa2 | function [GNum, GNDof] = MPInterfaceScalar1D(Interfaces, Mesh)
% function [GNum, GNDof] = MPInterfaceScalar1D(Interfaces, Mesh)
if (~isempty(Interfaces))
GNum = cell(numel(Mesh), 1);
patch_intrfc = cell(numel(Mesh), 1);
ttform = cell(numel(Mesh), numel(Interfaces));
ppnum = cell(numel(Interfaces), 1);
... |
github | SIMOGroup/SIMO-Package-master | exportToVTK.m | .m | SIMO-Package-master/PostProcessing/exportToVTK.m | 2,854 | utf_8 | 789cb7a5bdeccea92c112574e7dc1303 | % MSH_TO_VTK: Export to VTK format for plotting.
%
% MSH_to_vtk (pts, values, filename, fieldname)
%
% INPUT:
%
% pts: points at which the field was computed
% values: values of the field at the selected point
% filename: name of the output file
% fieldname: how to name the saved variable in ... |
github | SIMOGroup/SIMO-Package-master | applyNewmannBdryVals.m | .m | SIMO-Package-master/Processing/ImposeBC/applyNewmannBdryVals.m | 12,970 | utf_8 | 9235dc60e8bd1a2bb119311abf430be0 | function [Vals, GDofs] = applyNewmannBdryVals(NURBS, Mesh, g, Refs, LAB, varargin)
% [Vals, GDofs] = applyNewmannBdryVals(NURBS, Mesh, g, Refs, LAB, varargin)
% Evaluate values for applying Newmann boundary condition
% ------------------------------------------------------------
% Input:
% NURBS: NURBS struc... |
github | SIMOGroup/SIMO-Package-master | projDrchltBdryVals.m | .m | SIMO-Package-master/Processing/ImposeBC/projDrchltBdryVals.m | 10,076 | utf_8 | a62f4b176f0a2ac70e78708516eae499 | function [Coeffs, GDofs] = projDrchltBdryVals(NURBS, Mesh, h, Refs, LAB, varargin)
% function [Coeffs, GDofs] = projDrchltBdryVals(NURBS, Mesh, h, Refs, LAB, varargin)
% Evaluate coefficent values for imposing Dirichlet boundary condition of
% 2D and 3D problem (project Dirichlet Boundary Values)
% --------------------... |
github | SIMOGroup/SIMO-Package-master | DegreeElevateCurv.m | .m | SIMO-Package-master/NURBSToolbox/Refine/Bases/DegreeElevateCurv.m | 6,353 | utf_8 | 51472e57b9f70eb9cf3c66b434dc3948 | function [OKntVect, OCtrlPts] = DegreeElevateCurv(p, IKntVect, ICtrlPts, t)
% function [OKntVect, OCtrlPts] = DegreeElevateCurv(p, IKntVect, ICtrlPts, t)
% ---------------------------------------------------------------
% Degree elevate a curve t times
% ---------------------------------------------------------------
%... |
github | CyclotronResearchCentre/MRIquality-master | tbx_scfg_mriq_epi_qa.m | .m | MRIquality-master/tbx_scfg_mriq_epi_qa.m | 10,965 | utf_8 | 5a835112cac38460bd403179ea0eefa4 | function epiqa = tbx_scfg_mriq_epi_qa
% (Sub)configuration file for the MRIquality toolbox, partim EPI/QA.
% Quality assurance includes SNR and stability estimates.
%
% Warning and disclaimer: This software is for research use only.
% Do not use it for clinical or diagnostic purposes.
%
%===============================... |
github | CyclotronResearchCentre/MRIquality-master | tbx_scfg_mriq_epi_qareport.m | .m | MRIquality-master/tbx_scfg_mriq_epi_qareport.m | 8,567 | utf_8 | 6a73a2e436f458341f1e8219df3c1f9e | function epiqareport = tbx_scfg_mriq_epi_qareport
% (Sub)configuration file for the MRIquality toolbox, partim EPI/QA Report.
% The report generates a series of figures summarizing the results
% collected over time from QA runs, in order to visualize any evolution,
% drift, outliers, etc...
%
% Warning and disclaimer: ... |
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