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/dports/science/dakota/dakota-6.13.0-release-public.src-UI/packages/external/VPISparseGrid/test/
H A Dsandia_sgmgg_prb.out35 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
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/dports/finance/R-cran-plm/plm/man/
H A Dpseries.Rd11 \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)
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H A Dmodel.frame.pdata.frame.Rd6 \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)
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/dports/math/py-patsy/patsy-0.5.2/patsy/
H A Dcontrasts.py41 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)
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H A Dtest_build.py68 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()):
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/dports/science/openmx/openmx3.8/work/nbo_example/
H A DEC_NAO.std164 <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
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/dports/math/gap/gap-4.11.0/pkg/MonoidalCategories-2019.06.07/examples/
H A DVectorSpacesMonoidalCategory.gi100 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 ) )
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/dports/math/gap/gap-4.11.0/pkg/CAP-2019.06.07/examples/testfiles/
H A DVectorSpacesAllMethods.gi194 # 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 ) )
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/dports/math/ccmath/ccmath-2.2.1/manual/
H A DC04-cfit185 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) .
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/dports/math/gap/gap-4.11.0/pkg/CAP-2019.06.07/examples/
H A DVectorSpaces.gi93 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 ) );
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H A DGapDays2015FallHandsOn.gi75 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 ) );
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/dports/math/py-statsmodels/statsmodels-0.13.1/examples/python/
H A Dcontrasts.py70 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 Dscaling.fits.Rd5 \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 DINPUT_DYNMAT.def8 - 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 Dtable-margins.R6 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 Dtable-margins.R6 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 DNAMESPACE8 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)
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/dports/math/py-sympy/sympy-1.9/sympy/printing/tests/
H A Dtest_numpy.py2 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 DLinAlg.gi82 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,
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/dports/math/gap/gap-4.11.0/pkg/LinearAlgebraForCAP-2019.01.16/gap/
H A DLinearAlgebraForCAP.gi305 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;
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/dports/math/gap/gap-4.11.0/pkg/Thelma-1.02/lib/
H A Dste_realizability.gi59 # 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);
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/dports/math/gap/gap-4.11.0/pkg/ctbllib/tst/
H A Dhamilcyc.g77 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 );
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/dports/math/R-cran-robustbase/robustbase/man/
H A Dsummary.lts.Rd13 …\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 Drss.Rd8 \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
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/dports/science/gnudatalanguage/gdl-1.0.1/src/pro/
H A Dtrace.pro2 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
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