/dports/science/dakota/dakota-6.13.0-release-public.src-UI/packages/external/VPISparseGrid/test/ |
H A D | sandia_sgmgg_prb.out | 35 Sum: 1 86 Sum: 1 115 Sum: 1 144 Sum: 1 329 Sum: 1 344 Sum: 1 361 Sum: 1 380 Sum: 1 401 Sum: 1 504 Sum: 1 1 [all …]
|
/dports/finance/R-cran-plm/plm/man/ |
H A D | pseries.Rd | 11 \alias{Sum} 12 \alias{Sum.default} 13 \alias{Sum.pseries} 14 \alias{Sum.matrix} 49 Sum(x, ...) 55 \method{Sum}{matrix}(x, effect, ...) 104 \code{as.matrix}, which returns a matrix. 123 called demeaned data. \code{Sum} returns a vector/matrix with sum per individual 146 as.matrix(z) 154 Sum(z) [all …]
|
H A D | model.frame.pdata.frame.Rd | 6 \alias{model.matrix.plm} 7 \alias{model.matrix.pdata.frame} 8 \title{model.frame and model.matrix for panel data} 21 \method{model.matrix}{plm}(object, ...) 23 \method{model.matrix}{pdata.frame}( 25 model = c("pooling", "within", "Between", "Sum", "between", "mean", "random", "fd"), 52 \item{model}{one of \code{"pooling"}, \code{"within"}, \code{"Sum"}, \code{"Between"}, 64 \code{model.matrix} methods return a \code{matrix}. 73 \code{model.matrix}.\cr The \code{model.matrix} methods builds a model matrix 91 # then construct the (transformed) model matrix (design matrix) [all …]
|
/dports/math/py-patsy/patsy-0.5.2/patsy/ |
H A D | contrasts.py | 41 self.matrix = np.asarray(matrix) 298 print(matrix.matrix) 303 print(matrix.matrix) 304 assert np.allclose(matrix.matrix, 312 print(matrix.matrix) 323 print(matrix.matrix) 339 class Sum(object): class 404 t1 = Sum() 415 t2 = Sum(omit=1) 425 t3 = Sum(omit=-3) [all …]
|
H A D | test_build.py | 68 matrix = matrices[0] 70 == matrix.design_info.term_slices) 72 == matrix.design_info.column_names) 73 assert matrix.design_info is design_infos[0] 74 check_design_matrix(matrix, expected_rank, termlist, 76 return matrix 597 from patsy.contrasts import ContrastMatrix, Sum 609 for s in (Sum, Sum()): 618 m = make_matrix({"a": C(values, Sum(omit=0))}, 3, [["a"]], 635 for s in (Sum, Sum()): [all …]
|
/dports/science/openmx/openmx3.8/work/nbo_example/ |
H A D | EC_NAO.std | 164 <MD= 1> Calculation of the overlap matrix 165 <MD= 1> Calculation of the nonlocal matrix 166 <MD= 1> Calculation of the VNA projector matrix 180 Sum of MulP: up = 17.00000 down = 17.00000 201 Sum of MulP: up = 17.00000 down = 17.00000 222 Sum of MulP: up = 17.00000 down = 17.00000 243 Sum of MulP: up = 17.00000 down = 17.00000 264 Sum of MulP: up = 17.00000 down = 17.00000 285 Sum of MulP: up = 17.00000 down = 17.00000 306 Sum of MulP: up = 17.00000 down = 17.00000 [all …]
|
/dports/math/gap/gap-4.11.0/pkg/MonoidalCategories-2019.06.07/examples/ |
H A D | VectorSpacesMonoidalCategory.gi | 100 function( source, matrix, range ) 103 if not IsHomalgMatrix( matrix ) then 109 morphism := matrix; 148 Print( "A rational vector space homomorphism with matrix: \n" ); 354 dim := Sum( components, c -> Dimension( c ) ); 472 dim := Sum( components, c -> Dimension( c ) ); 644 local matrix; 650 matrix := morphism!.morphism; 652 return IsHomalgMatrix( matrix ) 653 and NrRows( matrix ) = Dimension( Source( morphism ) ) [all …]
|
/dports/math/gap/gap-4.11.0/pkg/CAP-2019.06.07/examples/testfiles/ |
H A D | VectorSpacesAllMethods.gi | 194 # dim := Sum( List( object_product_list, c -> Dimension( c ) ) ); 211 dim := Sum( components, c -> Dimension( c ) ); 270 dim := Sum( components, c -> Dimension( Source( c ) ) ); 312 dim := Sum( List( object_product_list, c -> Dimension( c ) ) ); 329 dim := Sum( components, c -> Dimension( c ) ); 387 dim := Sum( components, c -> Dimension( Range( c ) ) ); 501 local matrix; 507 matrix := morphism!.morphism; 509 return IsHomalgMatrix( matrix ) 510 and NrRows( matrix ) = Dimension( Source( morphism ) ) [all …]
|
/dports/math/ccmath/ccmath-2.2.1/manual/ |
H A D | C04-cfit | 185 f = {Sum(i=0 to m) a[i]*Ti(x)}/{1+Sum(j=1 to m) b[i]Ti(x))} . 201 f = {Sum(i=0 to m) a[i]*Ti(x)}/{1+Sum(j=1 to m) b[i]Ti(x))} . 329 ssq = Sum(i=n to m-1){b~[i]^2} . 416 ssq = Sum(i=n to m-1){b'[i]^2} + Sum([k]){b'[k]^2} 519 h[k] = Sum(i=0 to n-1){(opk(x[i]))^2} and 521 f[k] = Sum(i=0 to n-1){x[i]*opk(x[i])^2} . 529 ssq = Sum(i=0 to n-1) e[i]^2 575 fit_n(x) = Sum(k=0 to n){c[k]*opk(x)} 599 fit(x) = Sum(i=0 to m-1) bc[i]*x^i . 617 fit(x) = Sum(i=0 to m-1) c[k]*opk(x) . [all …]
|
/dports/math/gap/gap-4.11.0/pkg/CAP-2019.06.07/examples/ |
H A D | VectorSpaces.gi | 93 function( source, matrix, range ) 96 if not IsHomalgMatrix( matrix ) then 102 morphism := matrix; 316 dim := Sum( components, c -> Dimension( c ) ); 446 dim := Sum( components, c -> Dimension( c ) ); 609 local matrix; 615 matrix := morphism!.morphism; 617 return IsHomalgMatrix( matrix ) 618 and NrRows( matrix ) = Dimension( Source( morphism ) ) 619 and NrColumns( matrix ) = Dimension( Range( morphism ) ); [all …]
|
H A D | GapDays2015FallHandsOn.gi | 75 function( source, matrix, range ) 78 if not IsHomalgMatrix( matrix ) then 80 … morphism := HomalgMatrix( matrix, Dimension( source ), Dimension( range ), VECTORSPACES_FIELD ); 84 morphism := matrix; 121 Print( "A rational vector space homomorphism with matrix: \n" ); 317 dim := Sum( List( object_product_list, c -> Dimension( c ) ) ); 333 dim := Sum( components, c -> Dimension( c ) ); 335 dim_pre := Sum( components{ [ 1 .. injection_number - 1 ] }, c -> Dimension( c ) ); 363 dim := Sum( components, c -> Dimension( Source( c ) ) ); 389 dim := Sum( components, c -> Dimension( c ) ); [all …]
|
/dports/math/py-statsmodels/statsmodels-0.13.1/examples/python/ |
H A D | contrasts.py | 70 print(contrast.matrix) 80 print(contrast.matrix[hsb2.race - 1, :][:20]) 136 print(contrast.matrix) 150 from patsy.contrasts import Sum 152 contrast = Sum().code_without_intercept(levels) 153 print(contrast.matrix) 175 print(contrast.matrix) 200 print(contrast.matrix) 240 print(contrast.matrix)
|
/dports/math/R-cran-psych/psych/man/ |
H A D | scaling.fits.Rd | 5 \description{Given a matrix of choices and a vector of scale values, how well do the scale values c… 13 \item{data}{ A matrix or dataframe of choice frequencies } 18 …ics. One fit statistic for scaling is the just the size of the residual matrix compared to the or… 22 \item{original }{Sum of squares for original data} 23 \item{resid }{Sum of squares for residuals given the data and the model} 24 \item{residual }{Residual matrix}
|
/dports/science/quantum-espresso/q-e-qe-6.7.0/PHonon/Doc/ |
H A D | INPUT_DYNMAT.def | 8 - reads a dynamical matrix file produced by the phonon code 11 file), applies the chosen Acoustic Sum Rule (if q=0) 13 - diagonalise the dynamical matrix 34 input file containing the dynamical matrix 57 Indicates the type of Acoustic Sum Rule imposed. 62 no Acoustic Sum Rules imposed @b (default) 67 the diagonal elements of the dynamical matrix) 71 correction of the dyn. matrix (projection) 135 of the dynamical matrix (they are orthogonal)
|
/dports/math/R/R-4.1.2/src/library/stats/tests/ |
H A D | table-margins.R | 6 mB <- matrix(c(16, 26, 27, 20, 15 mB1 <- addmargins(mB, 1, list(list(Sum = sum, sqS = sqsm))) nameattr 16 mB2 <- addmargins(mB, 1, list(list(Sum = sum, sqS = function(x) sum(x)^2/100))) nameattr
|
/dports/math/libRmath/R-4.1.1/src/library/stats/tests/ |
H A D | table-margins.R | 6 mB <- matrix(c(16, 26, 27, 20, 15 mB1 <- addmargins(mB, 1, list(list(Sum = sum, sqS = sqsm))) nameattr 16 mB2 <- addmargins(mB, 1, list(list(Sum = sum, sqS = function(x) sum(x)^2/100))) nameattr
|
/dports/finance/R-cran-plm/plm/ |
H A D | NAMESPACE | 8 S3method(Between,matrix) 13 S3method(Sum,default) 14 S3method(Sum,matrix) 15 S3method(Sum,pseries) 17 S3method(Within,matrix) 24 S3method(as.matrix,pseries) 26 S3method(between,matrix) 78 S3method(model.matrix,pcce) 80 S3method(model.matrix,plm) 147 S3method(pvar,matrix) [all …]
|
/dports/math/py-sympy/sympy-1.9/sympy/printing/tests/ |
H A D | test_numpy.py | 2 Piecewise, lambdify, Equality, Unequality, Sum, Mod, sqrt, 47 s = Sum(x ** i, (i, a, b)) 54 s = Sum(i * x, (i, a, b)) 66 s = Sum((x + j) * i, (i, a, b), (j, c, d)) 86 ma = np.matrix([[1, 2], [3, 4]]) 87 mb = np.matrix([[1,-2], [-1, 3]]) 99 ma = np.matrix([[1, 2], [3, 4]]) 100 mb = np.matrix([[1,-2], [-1, 3]]) 101 mc = np.matrix([[2, 0], [1, 2]]) 102 md = np.matrix([[1,-1], [4, 7]])
|
/dports/math/gap/gap-4.11.0/pkg/MajoranaAlgebras-1.4/gap/ |
H A D | LinAlg.gi | 82 local B, # input matrix 83 n, # size of matrix 85 D, # output diagonal matrix 86 i, # loop over rows of matrix 87 j, # loop over columns of matrix 99 D[i, i] := B[i, i] - Sum(sum); 107 if B[j, i] - Sum(sum) = 0 then 120 L[j, i] := (B[j, i] - Sum(sum))/D[i, i]; 211 ## Takes a matrix <mat> and a row vector <row>, both in sparse matrix format. 295 iter := rec( matrix := M, [all …]
|
/dports/math/gap/gap-4.11.0/pkg/LinearAlgebraForCAP-2019.01.16/gap/ |
H A D | LinearAlgebraForCAP.gi | 305 dimension := Sum( List( object_list, object -> Dimension( object ) ) ); 328 dim_pre := Sum( object_list{ [ 1 .. projection_number - 1 ] }, c -> Dimension( c ) ); 371 dim_pre := Sum( object_list{ [ 1 .. injection_number - 1 ] }, c -> Dimension( c ) ); 412 start := Sum( List( summands{[ 1 .. nr-1 ]}, Dimension ) ) + 1; 427 start := Sum( List( summands{[ 1 .. nr-1 ]}, Dimension ) ) + 1; 801 local matrix, m, new_matrix, c; 803 matrix := UnderlyingMatrix( alpha ); 805 m := NrRows( matrix ); 809 …new_matrix := UnionOfColumns( List( [ 1 .. NrRows( matrix ) ], n -> CertainRows( matrix, [ n ] ) )… 828 local matrix, m, n, new_matrix; [all …]
|
/dports/math/gap/gap-4.11.0/pkg/Thelma-1.02/lib/ |
H A D | ste_realizability.gi | 59 # Arguments: mat - a matrix over GF(2); 70 # Arguments: ker - a matrix over GF(2); 87 mout:=[]; #tolerance matrix L 253 # Output: a tolerance matrix. 550 Add(w,Sum(w)-1); 626 Add(w,Sum(w)-1); 644 Add(w,Sum(w)-1); 659 Add(w,Sum(w)-1); 779 Add(w,Sum(w)-1); 796 Add(w,Sum(w)-1); [all …]
|
/dports/math/gap/gap-4.11.0/pkg/ctbllib/tst/ |
H A D | hamilcyc.g | 77 matrix:= []; 86 matrix[i][j]:= matrix[ powers[i] ][j]; 87 matrix[j][i]:= matrix[j][ powers[i] ]; 99 matrix[i][j]:= matrix[i][ powers[j] ]; 100 matrix[j][i]:= matrix[ powers[j] ][i]; 134 return matrix; 206 j -> Maximum( 0, classlengths[j] - Sum( prim, 226 delta:= List( bounds, Sum ); 228 size:= Sum( classlengths ); 281 size:= Sum( classlengths ); [all …]
|
/dports/math/R-cran-robustbase/robustbase/man/ |
H A D | summary.lts.Rd | 13 …\item{correlation}{logical; if \code{TRUE}, the correlation matrix of the estimated parameters is … 38 \item{coefficients}{a \eqn{p \times 4}{p x 4} matrix with columns for 43 sigma^2 = 1/(n-p) Sum(R[i]^2),} 53 R^2 = 1 - Sum(R[i]^2) / Sum((y[i]- y*)^2),} 58 \item{cov.unscaled}{a \eqn{p \times p}{p x p} matrix of (unscaled) 60 \item{correlation}{the correlation matrix corresponding to the above
|
/dports/math/R-cran-NMF/NMF/man/ |
H A D | rss.Rd | 8 \alias{rss,matrix-method} 10 \title{Residual Sum of Squares and Explained Variance} 14 \S4method{rss}{matrix}(object, target) 27 \item{target}{target matrix} 34 respectively computes the Residual Sum of Squares (RSS) 46 accurately reproduce the original target matrix. Note, 62 the RSS between a target matrix and its estimate 63 \code{object}, which must be a matrix of the same 102 # rss,matrix-method 113 # RSS between an NMF model and a target matrix [all …]
|
/dports/science/gnudatalanguage/gdl-1.0.1/src/pro/ |
H A D | trace.pro | 2 function trace, matrix,double=double_keyword 12 ; Calculates the trace of the input matrix 'matrix' 19 ; result = trace(matrix) 28 ; Result is the trace of the matrix 33 ; The input matrix must be n x n 37 ; Sum over the diagonal elements of the input matrix, return the result 40 ; i=identity(4) ; 4 x 4 identity matrix 62 s=size(matrix) 73 ;real matrix 82 ;complex matrix [all …]
|