| plot {panelPomp} | R Documentation |
Diagnostic plots for each unit in a panelPomp
## S4 method for signature 'panelPomp_plottable'
plot(
x,
variables,
panel = lines,
nc = NULL,
yax.flip = FALSE,
mar = c(0, 5.1, 0, if (yax.flip) 5.1 else 2.1),
oma = c(6, 0, 5, 0),
axes = TRUE,
...
)
x |
the object to plot |
variables |
optional character; names of variables to be displayed |
panel |
function of prototype |
nc |
the number of columns to use. Defaults to 1 for up to 4 series, otherwise to 2. |
yax.flip |
logical; if TRUE, the y-axis (ticks and numbering) should flip from side 2 (left) to 4 (right) from series to series. |
mar, oma |
the |
axes |
logical; indicates if x- and y- axes should be drawn |
... |
ignored or passed to low-level plotting functions |
No return value (the function returns NULL
).
Edward L. Ionides
plot(panelRandomWalk())


SUBROUTINE DGGEVX( BALANC, JOBVL, JOBVR, SENSE, N, A, LDA, B, LDB, $ ALPHAR, ALPHAI, BETA, VL, LDVL, VR, LDVR, ILO, $ IHI, LSCALE, RSCALE, ABNRM, BBNRM, RCONDE, $ RCONDV, WORK, LWORK, IWORK, BWORK, INFO ) * * -- LAPACK driver routine (version 3.1) -- * Univ. of Tennessee, Univ. of California Berkeley and NAG Ltd.. * November 2006 * * .. Scalar Arguments .. CHARACTER BALANC, JOBVL, JOBVR, SENSE INTEGER IHI, ILO, INFO, LDA, LDB, LDVL, LDVR, LWORK, N DOUBLE PRECISION ABNRM, BBNRM * .. * .. Array Arguments .. LOGICAL BWORK( * ) INTEGER IWORK( * ) DOUBLE PRECISION A( LDA, * ), ALPHAI( * ), ALPHAR( * ), $ B( LDB, * ), BETA( * ), LSCALE( * ), $ RCONDE( * ), RCONDV( * ), RSCALE( * ), $ VL( LDVL, * ), VR( LDVR, * ), WORK( * ) * .. * * Purpose * ======= * * DGGEVX computes for a pair of N-by-N real nonsymmetric matrices (A,B) * the generalized eigenvalues, and optionally, the left and/or right * generalized eigenvectors. * * Optionally also, it computes a balancing transformation to improve * the conditioning of the eigenvalues and eigenvectors (ILO, IHI, * LSCALE, RSCALE, ABNRM, and BBNRM), reciprocal condition numbers for * the eigenvalues (RCONDE), and reciprocal condition numbers for the * right eigenvectors (RCONDV). * * A generalized eigenvalue for a pair of matrices (A,B) is a scalar * lambda or a ratio alpha/beta = lambda, such that A - lambda*B is * singular. It is usually represented as the pair (alpha,beta), as * there is a reasonable interpretation for beta=0, and even for both * being zero. * * The right eigenvector v(j) corresponding to the eigenvalue lambda(j) * of (A,B) satisfies * * A * v(j) = lambda(j) * B * v(j) . * * The left eigenvector u(j) corresponding to the eigenvalue lambda(j) * of (A,B) satisfies * * u(j)**H * A = lambda(j) * u(j)**H * B. * * where u(j)**H is the conjugate-transpose of u(j). * * * Arguments * ========= * * BALANC (input) CHARACTER*1 * Specifies the balance option to be performed. * = 'N': do not diagonally scale or permute; * = 'P': permute only; * = 'S': scale only; * = 'B': both permute and scale. * Computed reciprocal condition numbers will be for the * matrices after permuting and/or balancing. Permuting does * not change condition numbers (in exact arithmetic), but * balancing does. * * JOBVL (input) CHARACTER*1 * = 'N': do not compute the left generalized eigenvectors; * = 'V': compute the left generalized eigenvectors. * * JOBVR (input) CHARACTER*1 * = 'N': do not compute the right generalized eigenvectors; * = 'V': compute the right generalized eigenvectors. * * SENSE (input) CHARACTER*1 * Determines which reciprocal condition numbers are computed. * = 'N': none are computed; * = 'E': computed for eigenvalues only; * = 'V': computed for eigenvectors only; * = 'B': computed for eigenvalues and eigenvectors. * * N (input) INTEGER * The order of the matrices A, B, VL, and VR. N >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA, N) * On entry, the matrix A in the pair (A,B). * On exit, A has been overwritten. If JOBVL='V' or JOBVR='V' * or both, then A contains the first part of the real Schur * form of the "balanced" versions of the input A and B. * * LDA (input) INTEGER * The leading dimension of A. LDA >= max(1,N). * * B (input/output) DOUBLE PRECISION array, dimension (LDB, N) * On entry, the matrix B in the pair (A,B). * On exit, B has been overwritten. If JOBVL='V' or JOBVR='V' * or both, then B contains the second part of the real Schur * form of the "balanced" versions of the input A and B. * * LDB (input) INTEGER * The leading dimension of B. LDB >= max(1,N). * * ALPHAR (output) DOUBLE PRECISION array, dimension (N) * ALPHAI (output) DOUBLE PRECISION array, dimension (N) * BETA (output) DOUBLE PRECISION array, dimension (N) * On exit, (ALPHAR(j) + ALPHAI(j)*i)/BETA(j), j=1,...,N, will * be the generalized eigenvalues. If ALPHAI(j) is zero, then * the j-th eigenvalue is real; if positive, then the j-th and * (j+1)-st eigenvalues are a complex conjugate pair, with * ALPHAI(j+1) negative. * * Note: the quotients ALPHAR(j)/BETA(j) and ALPHAI(j)/BETA(j) * may easily over- or underflow, and BETA(j) may even be zero. * Thus, the user should avoid naively computing the ratio * ALPHA/BETA. However, ALPHAR and ALPHAI will be always less * than and usually comparable with norm(A) in magnitude, and * BETA always less than and usually comparable with norm(B). * * VL (output) DOUBLE PRECISION array, dimension (LDVL,N) * If JOBVL = 'V', the left eigenvectors u(j) are stored one * after another in the columns of VL, in the same order as * their eigenvalues. If the j-th eigenvalue is real, then * u(j) = VL(:,j), the j-th column of VL. If the j-th and * (j+1)-th eigenvalues form a complex conjugate pair, then * u(j) = VL(:,j)+i*VL(:,j+1) and u(j+1) = VL(:,j)-i*VL(:,j+1). * Each eigenvector will be scaled so the largest component have * abs(real part) + abs(imag. part) = 1. * Not referenced if JOBVL = 'N'. * * LDVL (input) INTEGER * The leading dimension of the matrix VL. LDVL >= 1, and * if JOBVL = 'V', LDVL >= N. * * VR (output) DOUBLE PRECISION array, dimension (LDVR,N) * If JOBVR = 'V', the right eigenvectors v(j) are stored one * after another in the columns of VR, in the same order as * their eigenvalues. If the j-th eigenvalue is real, then * v(j) = VR(:,j), the j-th column of VR. If the j-th and * (j+1)-th eigenvalues form a complex conjugate pair, then * v(j) = VR(:,j)+i*VR(:,j+1) and v(j+1) = VR(:,j)-i*VR(:,j+1). * Each eigenvector will be scaled so the largest component have * abs(real part) + abs(imag. part) = 1. * Not referenced if JOBVR = 'N'. * * LDVR (input) INTEGER * The leading dimension of the matrix VR. LDVR >= 1, and * if JOBVR = 'V', LDVR >= N. * * ILO (output) INTEGER * IHI (output) INTEGER * ILO and IHI are integer values such that on exit * A(i,j) = 0 and B(i,j) = 0 if i > j and * j = 1,...,ILO-1 or i = IHI+1,...,N. * If BALANC = 'N' or 'S', ILO = 1 and IHI = N. * * LSCALE (output) DOUBLE PRECISION array, dimension (N) * Details of the permutations and scaling factors applied * to the left side of A and B. If PL(j) is the index of the * row interchanged with row j, and DL(j) is the scaling * factor applied to row j, then * LSCALE(j) = PL(j) for j = 1,...,ILO-1 * = DL(j) for j = ILO,...,IHI * = PL(j) for j = IHI+1,...,N. * The order in which the interchanges are made is N to IHI+1, * then 1 to ILO-1. * * RSCALE (output) DOUBLE PRECISION array, dimension (N) * Details of the permutations and scaling factors applied * to the right side of A and B. If PR(j) is the index of the * column interchanged with column j, and DR(j) is the scaling * factor applied to column j, then * RSCALE(j) = PR(j) for j = 1,...,ILO-1 * = DR(j) for j = ILO,...,IHI * = PR(j) for j = IHI+1,...,N * The order in which the interchanges are made is N to IHI+1, * then 1 to ILO-1. * * ABNRM (output) DOUBLE PRECISION * The one-norm of the balanced matrix A. * * BBNRM (output) DOUBLE PRECISION * The one-norm of the balanced matrix B. * * RCONDE (output) DOUBLE PRECISION array, dimension (N) * If SENSE = 'E' or 'B', the reciprocal condition numbers of * the eigenvalues, stored in consecutive elements of the array. * For a complex conjugate pair of eigenvalues two consecutive * elements of RCONDE are set to the same value. Thus RCONDE(j), * RCONDV(j), and the j-th columns of VL and VR all correspond * to the j-th eigenpair. * If SENSE = 'N or 'V', RCONDE is not referenced. * * RCONDV (output) DOUBLE PRECISION array, dimension (N) * If SENSE = 'V' or 'B', the estimated reciprocal condition * numbers of the eigenvectors, stored in consecutive elements * of the array. For a complex eigenvector two consecutive * elements of RCONDV are set to the same value. If the * eigenvalues cannot be reordered to compute RCONDV(j), * RCONDV(j) is set to 0; this can only occur when the true * value would be very small anyway. * If SENSE = 'N' or 'E', RCONDV is not referenced. * * WORK (workspace/output) DOUBLE PRECISION array, dimension (MAX(1,LWORK)) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The dimension of the array WORK. LWORK >= max(1,2*N). * If BALANC = 'S' or 'B', or JOBVL = 'V', or JOBVR = 'V', * LWORK >= max(1,6*N). * If SENSE = 'E' or 'B', LWORK >= max(1,10*N). * If SENSE = 'V' or 'B', LWORK >= 2*N*N+8*N+16. * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * IWORK (workspace) INTEGER array, dimension (N+6) * If SENSE = 'E', IWORK is not referenced. * * BWORK (workspace) LOGICAL array, dimension (N) * If SENSE = 'N', BWORK is not referenced. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value. * = 1,...,N: * The QZ iteration failed. No eigenvectors have been * calculated, but ALPHAR(j), ALPHAI(j), and BETA(j) * should be correct for j=INFO+1,...,N. * > N: =N+1: other than QZ iteration failed in DHGEQZ. * =N+2: error return from DTGEVC. * * Further Details * =============== * * Balancing a matrix pair (A,B) includes, first, permuting rows and * columns to isolate eigenvalues, second, applying diagonal similarity * transformation to the rows and columns to make the rows and columns * as close in norm as possible. The computed reciprocal condition * numbers correspond to the balanced matrix. Permuting rows and columns * will not change the condition numbers (in exact arithmetic) but * diagonal scaling will. For further explanation of balancing, see * section <IP_ADDRESS> of LAPACK Users' Guide. * * An approximate error bound on the chordal distance between the i-th * computed generalized eigenvalue w and the corresponding exact * eigenvalue lambda is * * chord(w, lambda) <= EPS * norm(ABNRM, BBNRM) / RCONDE(I) * * An approximate error bound for the angle between the i-th computed * eigenvector VL(i) or VR(i) is given by * * EPS * norm(ABNRM, BBNRM) / DIF(i). * * For further explanation of the reciprocal condition numbers RCONDE * and RCONDV, see section 4.11 of LAPACK User's Guide. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0 ) * .. * .. Local Scalars .. LOGICAL ILASCL, ILBSCL, ILV, ILVL, ILVR, LQUERY, NOSCL, $ PAIR, WANTSB, WANTSE, WANTSN, WANTSV CHARACTER CHTEMP INTEGER I, ICOLS, IERR, IJOBVL, IJOBVR, IN, IROWS, $ ITAU, IWRK, IWRK1, J, JC, JR, M, MAXWRK, $ MINWRK, MM DOUBLE PRECISION ANRM, ANRMTO, BIGNUM, BNRM, BNRMTO, EPS, $ SMLNUM, TEMP * .. * .. Local Arrays .. LOGICAL LDUMMA( 1 ) * .. * .. External Subroutines .. EXTERNAL DGEQRF, DGGBAK, DGGBAL, DGGHRD, DHGEQZ, DLABAD, $ DLACPY, DLASCL, DLASET, DORGQR, DORMQR, DTGEVC, $ DTGSNA, XERBLA * .. * .. External Functions .. LOGICAL LSAME INTEGER ILAENV DOUBLE PRECISION DLAMCH, DLANGE EXTERNAL LSAME, ILAENV, DLAMCH, DLANGE * .. * .. Intrinsic Functions .. INTRINSIC ABS, MAX, SQRT * .. * .. Executable Statements .. * * Decode the input arguments * IF( LSAME( JOBVL, 'N' ) ) THEN IJOBVL = 1 ILVL = .FALSE. ELSE IF( LSAME( JOBVL, 'V' ) ) THEN IJOBVL = 2 ILVL = .TRUE. ELSE IJOBVL = -1 ILVL = .FALSE. END IF * IF( LSAME( JOBVR, 'N' ) ) THEN IJOBVR = 1 ILVR = .FALSE. ELSE IF( LSAME( JOBVR, 'V' ) ) THEN IJOBVR = 2 ILVR = .TRUE. ELSE IJOBVR = -1 ILVR = .FALSE. END IF ILV = ILVL .OR. ILVR * NOSCL = LSAME( BALANC, 'N' ) .OR. LSAME( BALANC, 'P' ) WANTSN = LSAME( SENSE, 'N' ) WANTSE = LSAME( SENSE, 'E' ) WANTSV = LSAME( SENSE, 'V' ) WANTSB = LSAME( SENSE, 'B' ) * * Test the input arguments * INFO = 0 LQUERY = ( LWORK.EQ.-1 ) IF( .NOT.( LSAME( BALANC, 'N' ) .OR. LSAME( BALANC, $ 'S' ) .OR. LSAME( BALANC, 'P' ) .OR. LSAME( BALANC, 'B' ) ) ) $ THEN INFO = -1 ELSE IF( IJOBVL.LE.0 ) THEN INFO = -2 ELSE IF( IJOBVR.LE.0 ) THEN INFO = -3 ELSE IF( .NOT.( WANTSN .OR. WANTSE .OR. WANTSB .OR. WANTSV ) ) $ THEN INFO = -4 ELSE IF( N.LT.0 ) THEN INFO = -5 ELSE IF( LDA.LT.MAX( 1, N ) ) THEN INFO = -7 ELSE IF( LDB.LT.MAX( 1, N ) ) THEN INFO = -9 ELSE IF( LDVL.LT.1 .OR. ( ILVL .AND. LDVL.LT.N ) ) THEN INFO = -14 ELSE IF( LDVR.LT.1 .OR. ( ILVR .AND. LDVR.LT.N ) ) THEN INFO = -16 END IF * * Compute workspace * (Note: Comments in the code beginning "Workspace:" describe the * minimal amount of workspace needed at that point in the code, * as well as the preferred amount for good performance. * NB refers to the optimal block size for the immediately * following subroutine, as returned by ILAENV. The workspace is * computed assuming ILO = 1 and IHI = N, the worst case.) * IF( INFO.EQ.0 ) THEN IF( N.EQ.0 ) THEN MINWRK = 1 MAXWRK = 1 ELSE IF( NOSCL .AND. .NOT.ILV ) THEN MINWRK = 2*N ELSE MINWRK = 6*N END IF IF( WANTSE .OR. WANTSB ) THEN MINWRK = 10*N END IF IF( WANTSV .OR. WANTSB ) THEN MINWRK = MAX( MINWRK, 2*N*( N + 4 ) + 16 ) END IF MAXWRK = MINWRK MAXWRK = MAX( MAXWRK, $ N + N*ILAENV( 1, 'DGEQRF', ' ', N, 1, N, 0 ) ) MAXWRK = MAX( MAXWRK, $ N + N*ILAENV( 1, 'DORMQR', ' ', N, 1, N, 0 ) ) IF( ILVL ) THEN MAXWRK = MAX( MAXWRK, N + $ N*ILAENV( 1, 'DORGQR', ' ', N, 1, N, 0 ) ) END IF END IF WORK( 1 ) = MAXWRK * IF( LWORK.LT.MINWRK .AND. .NOT.LQUERY ) THEN INFO = -26 END IF END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DGGEVX', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * IF( N.EQ.0 ) $ RETURN * * * Get machine constants * EPS = DLAMCH( 'P' ) SMLNUM = DLAMCH( 'S' ) BIGNUM = ONE / SMLNUM CALL DLABAD( SMLNUM, BIGNUM ) SMLNUM = SQRT( SMLNUM ) / EPS BIGNUM = ONE / SMLNUM * * Scale A if max element outside range [SMLNUM,BIGNUM] * ANRM = DLANGE( 'M', N, N, A, LDA, WORK ) ILASCL = .FALSE. IF( ANRM.GT.ZERO .AND. ANRM.LT.SMLNUM ) THEN ANRMTO = SMLNUM ILASCL = .TRUE. ELSE IF( ANRM.GT.BIGNUM ) THEN ANRMTO = BIGNUM ILASCL = .TRUE. END IF IF( ILASCL ) $ CALL DLASCL( 'G', 0, 0, ANRM, ANRMTO, N, N, A, LDA, IERR ) * * Scale B if max element outside range [SMLNUM,BIGNUM] * BNRM = DLANGE( 'M', N, N, B, LDB, WORK ) ILBSCL = .FALSE. IF( BNRM.GT.ZERO .AND. BNRM.LT.SMLNUM ) THEN BNRMTO = SMLNUM ILBSCL = .TRUE. ELSE IF( BNRM.GT.BIGNUM ) THEN BNRMTO = BIGNUM ILBSCL = .TRUE. END IF IF( ILBSCL ) $ CALL DLASCL( 'G', 0, 0, BNRM, BNRMTO, N, N, B, LDB, IERR ) * * Permute and/or balance the matrix pair (A,B) * (Workspace: need 6*N if BALANC = 'S' or 'B', 1 otherwise) * CALL DGGBAL( BALANC, N, A, LDA, B, LDB, ILO, IHI, LSCALE, RSCALE, $ WORK, IERR ) * * Compute ABNRM and BBNRM * ABNRM = DLANGE( '1', N, N, A, LDA, WORK( 1 ) ) IF( ILASCL ) THEN WORK( 1 ) = ABNRM CALL DLASCL( 'G', 0, 0, ANRMTO, ANRM, 1, 1, WORK( 1 ), 1, $ IERR ) ABNRM = WORK( 1 ) END IF * BBNRM = DLANGE( '1', N, N, B, LDB, WORK( 1 ) ) IF( ILBSCL ) THEN WORK( 1 ) = BBNRM CALL DLASCL( 'G', 0, 0, BNRMTO, BNRM, 1, 1, WORK( 1 ), 1, $ IERR ) BBNRM = WORK( 1 ) END IF * * Reduce B to triangular form (QR decomposition of B) * (Workspace: need N, prefer N*NB ) * IROWS = IHI + 1 - ILO IF( ILV .OR. .NOT.WANTSN ) THEN ICOLS = N + 1 - ILO ELSE ICOLS = IROWS END IF ITAU = 1 IWRK = ITAU + IROWS CALL DGEQRF( IROWS, ICOLS, B( ILO, ILO ), LDB, WORK( ITAU ), $ WORK( IWRK ), LWORK+1-IWRK, IERR ) * * Apply the orthogonal transformation to A * (Workspace: need N, prefer N*NB) * CALL DORMQR( 'L', 'T', IROWS, ICOLS, IROWS, B( ILO, ILO ), LDB, $ WORK( ITAU ), A( ILO, ILO ), LDA, WORK( IWRK ), $ LWORK+1-IWRK, IERR ) * * Initialize VL and/or VR * (Workspace: need N, prefer N*NB) * IF( ILVL ) THEN CALL DLASET( 'Full', N, N, ZERO, ONE, VL, LDVL ) IF( IROWS.GT.1 ) THEN CALL DLACPY( 'L', IROWS-1, IROWS-1, B( ILO+1, ILO ), LDB, $ VL( ILO+1, ILO ), LDVL ) END IF CALL DORGQR( IROWS, IROWS, IROWS, VL( ILO, ILO ), LDVL, $ WORK( ITAU ), WORK( IWRK ), LWORK+1-IWRK, IERR ) END IF * IF( ILVR ) $ CALL DLASET( 'Full', N, N, ZERO, ONE, VR, LDVR ) * * Reduce to generalized Hessenberg form * (Workspace: none needed) * IF( ILV .OR. .NOT.WANTSN ) THEN * * Eigenvectors requested -- work on whole matrix. * CALL DGGHRD( JOBVL, JOBVR, N, ILO, IHI, A, LDA, B, LDB, VL, $ LDVL, VR, LDVR, IERR ) ELSE CALL DGGHRD( 'N', 'N', IROWS, 1, IROWS, A( ILO, ILO ), LDA, $ B( ILO, ILO ), LDB, VL, LDVL, VR, LDVR, IERR ) END IF * * Perform QZ algorithm (Compute eigenvalues, and optionally, the * Schur forms and Schur vectors) * (Workspace: need N) * IF( ILV .OR. .NOT.WANTSN ) THEN CHTEMP = 'S' ELSE CHTEMP = 'E' END IF * CALL DHGEQZ( CHTEMP, JOBVL, JOBVR, N, ILO, IHI, A, LDA, B, LDB, $ ALPHAR, ALPHAI, BETA, VL, LDVL, VR, LDVR, WORK, $ LWORK, IERR ) IF( IERR.NE.0 ) THEN IF( IERR.GT.0 .AND. IERR.LE.N ) THEN INFO = IERR ELSE IF( IERR.GT.N .AND. IERR.LE.2*N ) THEN INFO = IERR - N ELSE INFO = N + 1 END IF GO TO 130 END IF * * Compute Eigenvectors and estimate condition numbers if desired * (Workspace: DTGEVC: need 6*N * DTGSNA: need 2*N*(N+2)+16 if SENSE = 'V' or 'B', * need N otherwise ) * IF( ILV .OR. .NOT.WANTSN ) THEN IF( ILV ) THEN IF( ILVL ) THEN IF( ILVR ) THEN CHTEMP = 'B' ELSE CHTEMP = 'L' END IF ELSE CHTEMP = 'R' END IF * CALL DTGEVC( CHTEMP, 'B', LDUMMA, N, A, LDA, B, LDB, VL, $ LDVL, VR, LDVR, N, IN, WORK, IERR ) IF( IERR.NE.0 ) THEN INFO = N + 2 GO TO 130 END IF END IF * IF( .NOT.WANTSN ) THEN * * compute eigenvectors (DTGEVC) and estimate condition * numbers (DTGSNA). Note that the definition of the condition * number is not invariant under transformation (u,v) to * (Q*u, Z*v), where (u,v) are eigenvectors of the generalized * Schur form (S,T), Q and Z are orthogonal matrices. In order * to avoid using extra 2*N*N workspace, we have to recalculate * eigenvectors and estimate one condition numbers at a time. * PAIR = .FALSE. DO 20 I = 1, N * IF( PAIR ) THEN PAIR = .FALSE. GO TO 20 END IF MM = 1 IF( I.LT.N ) THEN IF( A( I+1, I ).NE.ZERO ) THEN PAIR = .TRUE. MM = 2 END IF END IF * DO 10 J = 1, N BWORK( J ) = .FALSE. 10 CONTINUE IF( MM.EQ.1 ) THEN BWORK( I ) = .TRUE. ELSE IF( MM.EQ.2 ) THEN BWORK( I ) = .TRUE. BWORK( I+1 ) = .TRUE. END IF * IWRK = MM*N + 1 IWRK1 = IWRK + MM*N * * Compute a pair of left and right eigenvectors. * (compute workspace: need up to 4*N + 6*N) * IF( WANTSE .OR. WANTSB ) THEN CALL DTGEVC( 'B', 'S', BWORK, N, A, LDA, B, LDB, $ WORK( 1 ), N, WORK( IWRK ), N, MM, M, $ WORK( IWRK1 ), IERR ) IF( IERR.NE.0 ) THEN INFO = N + 2 GO TO 130 END IF END IF * CALL DTGSNA( SENSE, 'S', BWORK, N, A, LDA, B, LDB, $ WORK( 1 ), N, WORK( IWRK ), N, RCONDE( I ), $ RCONDV( I ), MM, M, WORK( IWRK1 ), $ LWORK-IWRK1+1, IWORK, IERR ) * 20 CONTINUE END IF END IF * * Undo balancing on VL and VR and normalization * (Workspace: none needed) * IF( ILVL ) THEN CALL DGGBAK( BALANC, 'L', N, ILO, IHI, LSCALE, RSCALE, N, VL, $ LDVL, IERR ) * DO 70 JC = 1, N IF( ALPHAI( JC ).LT.ZERO ) $ GO TO 70 TEMP = ZERO IF( ALPHAI( JC ).EQ.ZERO ) THEN DO 30 JR = 1, N TEMP = MAX( TEMP, ABS( VL( JR, JC ) ) ) 30 CONTINUE ELSE DO 40 JR = 1, N TEMP = MAX( TEMP, ABS( VL( JR, JC ) )+ $ ABS( VL( JR, JC+1 ) ) ) 40 CONTINUE END IF IF( TEMP.LT.SMLNUM ) $ GO TO 70 TEMP = ONE / TEMP IF( ALPHAI( JC ).EQ.ZERO ) THEN DO 50 JR = 1, N VL( JR, JC ) = VL( JR, JC )*TEMP 50 CONTINUE ELSE DO 60 JR = 1, N VL( JR, JC ) = VL( JR, JC )*TEMP VL( JR, JC+1 ) = VL( JR, JC+1 )*TEMP 60 CONTINUE END IF 70 CONTINUE END IF IF( ILVR ) THEN CALL DGGBAK( BALANC, 'R', N, ILO, IHI, LSCALE, RSCALE, N, VR, $ LDVR, IERR ) DO 120 JC = 1, N IF( ALPHAI( JC ).LT.ZERO ) $ GO TO 120 TEMP = ZERO IF( ALPHAI( JC ).EQ.ZERO ) THEN DO 80 JR = 1, N TEMP = MAX( TEMP, ABS( VR( JR, JC ) ) ) 80 CONTINUE ELSE DO 90 JR = 1, N TEMP = MAX( TEMP, ABS( VR( JR, JC ) )+ $ ABS( VR( JR, JC+1 ) ) ) 90 CONTINUE END IF IF( TEMP.LT.SMLNUM ) $ GO TO 120 TEMP = ONE / TEMP IF( ALPHAI( JC ).EQ.ZERO ) THEN DO 100 JR = 1, N VR( JR, JC ) = VR( JR, JC )*TEMP 100 CONTINUE ELSE DO 110 JR = 1, N VR( JR, JC ) = VR( JR, JC )*TEMP VR( JR, JC+1 ) = VR( JR, JC+1 )*TEMP 110 CONTINUE END IF 120 CONTINUE END IF * * Undo scaling if necessary * IF( ILASCL ) THEN CALL DLASCL( 'G', 0, 0, ANRMTO, ANRM, N, 1, ALPHAR, N, IERR ) CALL DLASCL( 'G', 0, 0, ANRMTO, ANRM, N, 1, ALPHAI, N, IERR ) END IF * IF( ILBSCL ) THEN CALL DLASCL( 'G', 0, 0, BNRMTO, BNRM, N, 1, BETA, N, IERR ) END IF * 130 CONTINUE WORK( 1 ) = MAXWRK * RETURN * * End of DGGEVX * END


Located on the west coast of Cotentin Peninsula and just 25nm east of Guernsey, this is an attractive little port surrounded by sandy beaches.
Position 49° 33'15"N, 01° 51'54"W (harbour entrance)
This port has tidal access with a cill into the inner harbour/marina. Access is at chart datum +5m.
Last updated April 2016.


Before Change
// Recursively search superclasses to swap in the right Keras class.
cls.__bases__ = tuple(
swap_class(base, v2_cls, v1_cls, use_v2) for base in cls.__bases__)
return cls
After Change
// Recursively search superclasses to swap in the right Keras class.
new_bases = []
for base in cls.__bases__:
if ((use_v2 and issubclass(base, v1_cls)
// `v1_cls` often extends `v2_cls`, so it may still call `swap_class`
// even if it doesn"t need to. That being said, it may be the safest
// not to over optimize this logic for the sake of correctness,
// especially if we swap v1 & v2 classes that don"t extend each other,


{% load staticfiles %}
Some text that people will think is awesome! Some text that people will think is awesome! Some text that people will think is awesome!


A
Ariel, Beatrice and Cassandra — three brilliant game theorists — were bored at a game theory conference (shocking, we know) and devised the following game to pass the time. They drew a number line and placed $1 on the 1, $2 on the 2, $3 on the 3 and so on to $10 on the 10.
Each player has a personalized token. They take turns — Ariel first, Beatrice second and Cassandra third — placing their tokens on one of the money stacks (only one token is allowed per space). Once the tokens are all placed, each player gets to take every stack that her token is on or is closest to. If a stack is midway between two tokens, the players split that cash.
And now you can play a crappy but functional JavaScript version of this game! Simply select a space for each token and see what everyone's payout is.
Player A's token:
Player B's token:
Player C's token:


Enter a sequence of figures and listen.
{{ $parent.$parent.getPrimeNumberForCell(cell.row, cell.col) }}
How is a melody generated from numbers?
The goal is to create a melody from the prime decomposition of the number.
To make it short, the melody lasts n beats (between 1 and 32), so the given number is decomposed in n numbers of equals length. Each number is decomposed in prime factors. Each cell represents a prime number. The row on which the prime factor is located determines which note will be played (from D5 to D6).
The melody is generated by playing one beat (column) after the other.
Here are some numbers you can try for yourself :
-<PHONE_NUMBER>03000017000500 (with 12 beats)
-<PHONE_NUMBER>1117050205021902190700 (with 16 beats)
-<PHONE_NUMBER>00190019001700130000050300 (with 18 beats)


Source code for module_add_to_queries
#!/usr/bin/env python3
# Copyright 2018 Lael D. Barlow
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
"""Module for script: amoebae.
"""
# Import built-in modules.
#import argparse
import sys
import os
import subprocess
#import re
#import settings
#import shutil
#import glob
import time
import pandas as pd
# Import modules from installed libraries/packages.
from Bio import SeqIO
#from Bio import AlignIO
#from Bio.Alphabet import IUPAC, Gapped
import module_amoebae
from module_amoebae_get_datatype import get_dbtype
# Define functions to be used in amoebae.
[docs]def get_query_file_type(query_file):
"""Takes an input query file and determines whether it is a FASTA file or
an HMM file. Returns either "FASTA" or "HMM".
"""
file_type = None
with open(query_file) as infh:
first_line = infh.readline().strip()
if first_line.startswith('>'):
file_type = 'FASTA'
elif first_line.startswith('HMM'):
file_type = 'HMM'
# Check that it worked.
assert file_type is not None, """Error: Input file type could not be
determined: %s""" % query_file
# Return file type.
return file_type
[docs]def get_hmm_datatype(query_file):
"""Takes an HMM file (HMMer3 software package) and determines what data
type it has (i.e., generated from an amino acid or nucleic acid alignment).
Returns either "prot" or "nucl".
"""
datatype = None
with open(query_file) as infh:
for i in infh:
if i.startswith('ALPH'):
dname = i.strip().split(' ')[1]
if dname == 'amino':
datatype = 'prot'
elif dname == 'DNA':
datatype = 'nucl'
break
# Check that it worked.
assert datatype is not None, """Error: Data type could not be
determined for input file: %s""" % query_file
# Return the data type.
return datatype
[docs]def get_mod_query_path(query_file, filetype, datatype, query_dir):
"""Define a new query path.
"""
exten = None
if filetype == 'fa':
if datatype == 'prot':
exten = 'faa'
elif datatype == 'nucl':
exten = 'fna'
elif filetype == 'afa':
if datatype == 'prot':
exten = 'afaa'
elif datatype == 'nucl':
extenn = 'afna'
# Check that it worked.
assert exten is not None, """Error: New extension could not be
determined for input file: %s""" % query_file
# Define basename with new extension.
query_file_new_exten = os.path.basename(query_file).rsplit('.', 1)[0] +\
'.' + exten
# Get new path.
new_query_file_path = os.path.join(query_dir, query_file_new_exten)
# Return the new path.
return new_query_file_path
[docs]def is_single_fasta(query_file):
"""Return True if the given fasta file contains only one sequence.
"""
single = False
num_seqs = 0
with open(query_file) as infh:
for seq in SeqIO.parse(query_file, 'fasta'):
num_seqs += 1
if num_seqs == 1:
single = True
return single
[docs]def fasta_seqs_all_same_len(query_file):
"""Returns True if the sequences in a given fasta file are all the same
length.
"""
seq_lengths = []
with open(query_file) as infh:
for seq in SeqIO.parse(infh, 'fasta'):
seq_lengths.append(len(seq))
# If the sequences are the same length, then a nonredundant list of
# sequence lengths will only contain one element.
if len(set(seq_lengths)) == 1:
return True
else:
return False
[docs]def update_query_csv(csv_file, mod_query_path, datatype):
"""Appends a line to the given spreadsheet with info about the given fasta
file added to a directory.
"""
# Define column headers.
headers = ['Filename',
'Query title',
'Query source description',
'Query taxon (species if applicable)',
'Query database filename (if applicable)',
'File type',
'Data type',
'Date added',
'Citation'
]
# Make new csv file if necessary.
if not os.path.isfile(csv_file):
#df = pd.DataFrame(columns=headers)
#df.to_csv(csv_file) #, index_label='Filename')
with open(csv_file, 'w') as o:
o.write(','.join(headers)) # + '\n')
# Load dataframe from csv file.
df = pd.read_csv(csv_file) #, index_col='Filename')
# Get current date.
cur_date = time.strftime("%Y/%m/%d")
# Get query filename and extension.
full = os.path.basename(mod_query_path).rsplit('.', 1)
filename = full[0]
exten = full[1]
# Get query basename.
query_basename = os.path.basename(mod_query_path)
# Get query title name.
query_title = query_basename.split('_')[0]
# Get query taxon name.
# Assumes that there is an accession or something else after the "taxon" in
# the query file name.
taxon = module_amoebae.get_query_taxon_from_filename(query_basename)
# Initiate dataframe for line to append.
new_row = pd.DataFrame(columns=headers)
# Add info to new row.
new_row.loc[0] = ['???'] * len(headers)
new_row.loc[0]['Filename'] = query_basename
new_row.loc[0]['Query title'] = query_title
new_row.loc[0]['Query source description'] = taxon
new_row.loc[0]['Query taxon (species if applicable)'] = module_amoebae.get_species_from_db_csv(taxon)
new_row.loc[0]['Data type'] = datatype
new_row.loc[0]['File type'] = exten
new_row.loc[0]['Date added'] = cur_date
new_row.loc[0]['Citation'] = '?'
new_row.loc[0]['Query database filename (if applicable)'] =\
module_amoebae.get_db_filename_for_query_from_db_csv(taxon)
# Check that it worked.
assert not '???' in new_row.loc[0], """Could not add all the necessary info
to the query info spreadsheet for query file:\n\t%s""" % mod_query_path
# Append new row to dataframe.
df = df.append(new_row, ignore_index=True)
# Re-order columns in output dataframe.
df = df[new_row.columns]
# Write updated dataframe to csv file.
#df[1:].to_csv(csv_file)
df.to_csv(csv_file, index=False)


- getAliveNeighborCount(int, int) - Method in interface golad.lib.Board
-
Returns the current number of alive neighbors of a specified cell.
- getAliveNeighborCount(int, int) - Method in class golad.lib.impl.AbstractBoard
-
- getAliveNeighborCount(int, int) - Method in class golad.lib.impl.DelegateBoard
-
- getAuthor() - Method in interface golad.bot.BotFactory
-
Returns the name of the author of the Bots created by this BotFactory.
- getBoard() - Method in class golad.lib.impl.DefaultAbstractMoveFactory
-
- getBoard() - Method in interface golad.lib.MoveFactory
-
Returns the Board used for the validation of
Move
s.
- getCellStateAt(int, int) - Method in interface golad.lib.Board
-
Returns the current state of the cell at the specified coordinates.
- getCellStateAt(int, int) - Method in class golad.lib.impl.DefaultBoard
-
- getCellStateAt(int, int) - Method in class golad.lib.impl.DelegateBoard
-
- getHeight() - Method in interface golad.lib.Board
-
Returns the height of this Board.
- getHeight() - Method in class golad.lib.impl.DefaultBoard
-
- getHeight() - Method in class golad.lib.impl.DelegateBoard
-
- getMoveType() - Method in interface golad.lib.Move
-
Returns the Type of this move.
- getName() - Method in interface golad.bot.BotFactory
-
Returns the name of the Bots created by this BotFactory, or "Human" if the created Bots are human interfaces.
- getNeighborCellCount(int, int, Set<CellState>) - Method in interface golad.lib.Board
-
Returns the current number of neighbors of a specified cell, that are in any of the specified
CellState
s.
- getNeighborCellCount(int, int, Set<CellState>) - Method in class golad.lib.impl.AbstractBoard
-
- getNeighborCellCount(int, int, Set<CellState>) - Method in class golad.lib.impl.DelegateBoard
-
- getNewState() - Method in interface golad.lib.Move
-
Returns the state this board is/will be in after this move.
- getNextMove(MoveFactory, Move) - Method in interface golad.bot.Bot
-
Obtains the next move this bot will make in the given situation.
- getOriginalState() - Method in interface golad.lib.Move
-
Returns the state this board was/is in before this move.
- getPlayerColor() - Method in class golad.lib.impl.DefaultAbstractMoveFactory
-
- getPlayerColor() - Method in interface golad.lib.MoveFactory
-
Returns the CellState representing an alive cell owned by the player that is given this MoveFactory.
- getSacrificeX(int) - Method in interface golad.lib.Move
-
Returns the X coordinate of the n-th sacrificed cell.
- getSacrificeY(int) - Method in interface golad.lib.Move
-
Returns the Y coordinate of the n-th sacrificed cell.
- getTargetX() - Method in interface golad.lib.Move
-
Returns the X coordinate of the targeted cell.
- getTargetY() - Method in interface golad.lib.Move
-
Returns the Y coordinate of the targeted cell.
- getTotalCellCount(Set<CellState>) - Method in interface golad.lib.Board
-
Returns the current number of cells in any of the specified
CellState
s.
- getTotalCellCount(Set<CellState>) - Method in class golad.lib.impl.AbstractBoard
-
- getTotalCellCount(Set<CellState>) - Method in class golad.lib.impl.DelegateBoard
-
- getVersion() - Method in interface golad.bot.BotFactory
-
Returns the version of the Bots created by this BotFactory.
- getWidth() - Method in interface golad.lib.Board
-
Returns the width of this Board.
- getWidth() - Method in class golad.lib.impl.DefaultBoard
-
- getWidth() - Method in class golad.lib.impl.DelegateBoard
-
- golad.bot - package golad.bot
-
This package provides bot related classes and interfaces.
- golad.lib - package golad.lib
-
This package provides classes and interfaces for observation and manipulation of GOLAD boards.
- golad.lib.impl - package golad.lib.impl
-
This package provides abstract and concrete implementations of the concepts defined in
golad.lib


The content of this listing item goes here.
The content of this listing item goes here.
The content of this listing item goes here.
This one has more text than the other items.
Quite a lot more
Perhaps we could do something different with it?
The content of this listing item goes here.
The content of this listing item goes here.


Dover NH Real Estate | New Hampshire Homes For Sale | Top Agents
CENTURY 21 Central Falls Realty 242 Central Avenue Dover, NH 03820. CENTURY 21 Central Falls Realty is conveniently located in historic Dover, New .
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Treatment for Herniated or Bulging Discs
our team - Century 21 Central Falls Realty
Contact Central Falls Realty for information on Concord NH Real Estate, . CENTURY 21 Central Falls Realty, located at 242 Central Avenue, is right in the .
http://century21central.com/ourteam/team.html
Homes For Sale In NH & VT - Littleton NH - Northeast Kingdom VT ...
Call a Real Estate Agent in Littleton NH with CENTURY 21 Winn Associates for any . White Mountain NH Real Estate - Littleton NH Real Estate - CENTURY 21 Winn Associates, . Foreclosure Help: 5 Pros You Need on Your Team .
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century 21 team new hampshire Herniated or Bulging Discs
Loon Mountain Real Estate, New Hampshire, White Mountains ...
CENTURY 21 Mountainside Realty is located in the heart of the beautiful White Mountains of New Hampshire. We're your source for Loon Mountain Area Real .
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New Hampshire Real Estate | Find Houses & Homes ... - Century 21
Search New Hampshire real estate property listings to find homes for sale in New Hampshire. Browse houses for sale in New Hampshire today!
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Contact Central Falls Realty for information on New Hampshire Real Estate, New Hampshire Foreclosures, New . Century 21 Central Falls logo dwellNh logo .
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CENTURY 21 McLennan & Company
CENTURY 21 McLennan & Company is a Real Estate Agency serving both home buyers and sellers in New Hampshire and Massachusetts.
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- basic subunit of sucrose (narrowing of the spine)
Paula Forbes - Century 21 Central Falls Realty
When Paula says she's one of the best realtors in New Hampshire, she has the record to prove it. Paula has been a Number One Century 21 Sales Associate in .
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CENTURY 21 Barbara Patterson has many great agents that have been . CENTURY 21 Barbara Patterson is a full service real estate brokerage agency serving the Southern Maine and New Hampshire areas since 1986. . Meet the Team .
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Century 21 HBS Realty, NH Real Estate, NH Realty, NH Realtor, Londonderry . About CENTURY 21 HBS Realty · Our Team of New Hampshire Realtors .
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Claremont NH homes for sale, Sunapee NH lake front, land, Realtors buying and selling real estate, . CENTURY 21 Highview Realty Means High Quality.
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You can learn about Century 21 North Shore in Windham, NH by visiting REALTOR.com®. Discover agent profiles and listings provided by Century 21 North .
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Century 21, Circa '72 and Thompson Real Estate. Our Realtors have been serving the Concord and greater Central New Hampshire area with all types of Real .
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Lake Winnipesaukee Real Estate | NH Lakes Region Real Estate
We cover all NH Lakes such as Lake Winnisquam and Squam Lake. . We are the source for New Hampshire Lakes Region Real Estate! . Lake Winnipesaukee [213]Lake Winnisquam [15]Squam Lake [21]Ossipee Lake [15] Lake Waukewan .
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Sara Mitchell Team are Hampshire Real Estate agents from CENTURY 21 New Heritage located in Hampshire, IL. Contact Sara Mitchell Team today!
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Preparation time
less than 30 mins
Cooking time
10 to 30 mins
Serves
Serves 1
For the shrimp butter, place the orange juice and scallop muscles in a small saucepan and bring to the boil. Skim off any foam, then stir in the sugar.
Blend two tablespoons of the shrimps in a food processor to form a paste, then add this to the pan with the orange juice, and continue to heat for a further 2-3 minutes. Pass the sauce through a sieve to remove the scallop muscles, return the liquid to the pan, and season to taste with salt and freshly ground black pepper.
Stir in the butter and the remaining tablespoon of shrimps and continue cooking for 1-2 minutes until the butter has melted and the shrimps have warmed through.
For the black pudding, combine the mace, paprika, flour and seasoning in a bowl and press the black pudding slices into this mixture to coat, shaking off any excess. Heat the oil in a frying pan over a medium heat and fry the coated black pudding for 2-3 minutes on each side.
For the scallops, season the scallops with salt and freshly ground black pepper. Heat the oil and butter in a separate frying pan over a high heat. When the butter is foaming, add the scallops and cook for 1-2 minutes on each side, or until they are golden brown and crisp.
For the pea and radish shoot salad, mix the orange and lemon juice, olive oil and seasoning in a bowl until well combined. Add the pea shoots and radish sprouts and toss them in the vinaigrette to coat.
To serve, pile the shoot salad onto a serving plate and alternate the scallops and black pudding slices around the edge of the plate. Drizzle the shrimp butter over the scallops and black pudding, then garnish with fresh chives.


Wilder vs. Ortiz 2 results: Deontay Wilder loses most of fight, then KOs Luis Ortiz in seventh
by Harry DaviesDeontay Wilder (42-0-21, 42 KOs) remained undefeated and defended his WBC heavyweight title for the tenth time with a seventh-round KO of Luis Ortiz (31-2-2 NCs, 26 KOs).
It was a fairly slow start to the fight, with not much action taking place in the first two rounds. Ortiz did a good job of using his jab and setting up a big overhand left which he landed in the first. A cut opened up on the right side of the Cuban’s head which seemed to be from a elbow by Wilder.
Ortiz continued for the next two rounds trying to force Wilder up into the corner and land his left hand. “The Bronze Bomber” was let to land anything meaningful, instead pacing himself and clearly showing a lot of respect for the power of Ortiz.
It was much the same up until round seven. Wilder didn’t even land a punch in the fifth round as Ortiz fought very well off of his jab, troubling Wilder and making the knockout artist throw virtually no power punches at all.
Suddenly come the seventh round, it all changed out of nowhere. As wilder began to measure Ortiz with his left hand, he fired a short right hand straight down the middle which dropped Ortiz. Although it looked like he would get back to his feet when the count came to eight, he couldn’t and referee Kenny Bayless rightfully stopped the fight.
It’s likely that Wilder will rematch Tyson Fury in his next fight in early 2020 following his KO win over Ortiz. Fury picked up two wins in 2019, a stoppage win over Tom Schwarz and a decision against Otto Wallin.
Official result: Deontay Wilder def. Luis Ortiz by KO in the seventh round


Mayor William B. Judge
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The Rf/φ method is made to analyse strain on objects which were already elliptical before deformation.The method was establshed by R. Lisle (1985).
The finite ellipticity (Rf), seen on deformed objects, and the orientation of the finite ellipse are a result from the primary (initial) ellipticity (Ri), the orientation of the initial ellipse, and the ellipticity of the strain ellipse (Rs), and its orientation.. Objects with the same Ri and various orientation show uniform pattern after affine deformation. These patterns can be described with curves (Ri-curves) in which Rf is plotted vs. the finite orientation φ. An affine deformation of objects with various ellipticity but identical orientation also results in defined curves (Rf/φ–curves,Θ-curves).


The Ohio State University
Teaching Assistant
August 2015-Current
Java
- Responsibilities include grading, assisting with lab, and answering questions
Siemens PLM Software
Software Development Co-op
January 2015-August 2015
Java | XML | .NET
- Worked more than 35 hours per week for 8 months
- Within several hours and a few dozen lines of code, reduced the run time for an inherited .NET utility by over 99% from more than 40 minutes to less than 5 seconds
- Developed an application to automate and streamline a task that took up to 40% of Product Manager's time by integrating issue tracking software with scrum management software
- Added functionality to a Google Web Toolkit widget while reducing the number of server calls made by the widget
- Maintained and improved several utilities involved in importing data from excel files to a database
Franklin County Emergency Management and Homeland Security
Assistant to the IT Manager
May 2014-August 2014
Java | PHP | MySQL
- Automated the work of hundreds of volunteers
- Developed an application to direct staff through the flood management procedure
- Developed software to monitor water levels throughout central Ohio for automated tracking of floods
- Set up a server to run automated data logging


Apache Security References
Below is a list of useful references on keeping an Apache Web Server secure.
- Aphache Software Foundation Standards - Adhering to standards is the first step in preventing security vulnerablities.
- Apache Security Best Prectices & Apache Security Best Prectices - A couple lists of things that can be done to increase the security on an Apache web server
- Known Apache Vulnerabilities - CVE Details is a website that keeps a database of known security vulnerabilities. For each vulnerablity to provide the number of known exploits, dates, vulnerability score, access level gained, acces, complexity, and a few more details. Linked above is a direct link to the Apache page.


◆ AddPopulatedConnection()
| void MoveToCode.MazeManager.AddPopulatedConnection |
( |
Connection |
connection | ) |
|
◆ GetClosestKuriMazePiece()
| MazePiece MoveToCode.MazeManager.GetClosestKuriMazePiece |
( |
| ) |
|
◆ GetMazeConnectorRelBKInDir()
◆ GetMazeObject()
| GameObject MoveToCode.MazeManager.GetMazeObject |
( |
string |
name | ) |
|
◆ GetMisalignedPiece()
| MazePiece MoveToCode.MazeManager.GetMisalignedPiece |
( |
| ) |
|
◆ GetMissingPiecesFromMaze()
| MazePiece MoveToCode.MazeManager.GetMissingPiecesFromMaze |
( |
| ) |
|
◆ GetPotentialNextMP()
◆ IsBKAtTheGoalNow()
| bool MoveToCode.MazeManager.IsBKAtTheGoalNow |
( |
| ) |
|
◆ IsSameAsSolutionMaze()
| bool MoveToCode.MazeManager.IsSameAsSolutionMaze |
( |
| ) |
|
◆ LockMaze()
| void MoveToCode.MazeManager.LockMaze |
( |
| ) |
|
Lock and unlock should only be called by SwitchModeButton.cs
because it is the holder of the state
◆ LogMaze()
| void MoveToCode.MazeManager.LogMaze |
( |
| ) |
|
◆ MarkMazeDirty()
| void MoveToCode.MazeManager.MarkMazeDirty |
( |
| ) |
|
◆ ReturnOpenConnectionToPool()
| void MoveToCode.MazeManager.ReturnOpenConnectionToPool |
( |
Connection |
connection | ) |
|
◆ UnlockMaze()
| void MoveToCode.MazeManager.UnlockMaze |
( |
| ) |
|
Lock and unlock should only be called by SwitchModeButton.cs
because it is the holder of the state
◆ _allMazePieces
| HashSet<MazePiece> MoveToCode.MazeManager._allMazePieces |
◆ BKCurrentMP
| MazePiece MoveToCode.MazeManager.BKCurrentMP = null |
◆ containsSolCol
| string MoveToCode.MazeManager.containsSolCol = "containsSol" |
|
static |
◆ mazeLockCol
| string MoveToCode.MazeManager.mazeLockCol = "mazeLock" |
|
static |
◆ mazeLogCol
| string MoveToCode.MazeManager.mazeLogCol = "UserMaze" |
|
static |
◆ OnBKGoalEnter
| UnityEvent MoveToCode.MazeManager.OnBKGoalEnter |
◆ OnBKGoalExit
| UnityEvent MoveToCode.MazeManager.OnBKGoalExit |
◆ OnMazeLocked
| UnityEvent MoveToCode.MazeManager.OnMazeLocked |
◆ OnMazeUnlocked
| UnityEvent MoveToCode.MazeManager.OnMazeUnlocked |
◆ AllMazePieces
| HashSet<MazePiece> MoveToCode.MazeManager.AllMazePieces |
|
get |
◆ BKMazePiece
◆ ExerciseInFullyCompleteState
| bool MoveToCode.MazeManager.ExerciseInFullyCompleteState |
|
get |
◆ GoalMazePiece
| MazePiece MoveToCode.MazeManager.GoalMazePiece |
|
get |
◆ IsLocked
| bool MoveToCode.MazeManager.IsLocked |
|
get |
◆ MyMazeGraph
The documentation for this class was generated from the following file:
- /Users/tgroeche/scripts/UnityProjects/MoveToCode/Assets/Scripts/MazeManager.cs


--- layout: index title: Error the page doesn't exist tagline: You're lost in the space of Fullit make your landing page a fullpage sliding tool usefull for web marketing. 404 error img : 1.jpg img-mobile : 1-mobile.jpg css: cover.css js: keywords: gradient, html, css, landing page, jekyll, ruby, web marketing, advertising canonical: https://grads.github.io --- {% include JB/setup %}


The help inline component creates a small button beside that triggers an action to display more information for users.
Use the help inline component to provide information about a field or section such as how a value is calculated. Use this option when persistent inline help is not necessary.
You can open the content in a popover or the help panel, depending on how extensive the information is.


• University of Queensland
• Ibrahim Medical College
• Southern Medical University
• Kun Ming Medical University
• Sun Yat-sen University
• Zhejiang University
• Tanjungpura University
• Airlangga University
• Universitas Gadjah Mada
• Hang Tuah University
• Diponegoro University
• Brawijaya University
• Andalas University
• Lambung Mangurat University
• Universitas Padjadjaran
• Osaka Medical College
• Taipei Medical University
• Chung Shan Medical University
• Tzu Chi University
• Chiang Mai University
• Faculty of Medicine Ramathibodi Hospital, Mahidol University
• Faculty of Medicine Siriraj Hospital, Mahidol University
• Khon Kaen University
• Mahasarakam University
• Navamindradhiraj University
• Princess of Naradhiwas University
• Prince of Songkla University
• Srinakharinwirot University
• Medical Education Center, Maharaj Nakhon Ratchasima Hospital,Mahidol University
• Ubon Ratchathani University
• Walailak University
• Pham Ngoc Thach University
• Sydney Medical School
• Khwaja Yunus Ali Medical College
• Ibrahim Medical College
• Soochow University
• Southern Medical University
• Kun Ming Medical University
• Zhejiang University
• Airlangga University
• Universitas Gadjah Mada
• Universitas Indonesia
• Hang Tuah University
• Diponegoro University
• Brawijaya University
• Andalas University
• University of Sumatera Utara
• Lambung Mangurat University
• Universitas Padjadjaran
• Sriwijaya University
• Christian University of Indonesia
• Osaka Medical College
• Perdana University Graduate School Of Medicine
• University Putra Malaysia
• School Of Medical Sciences, Universiti Sains Malaysia
• Mongolian National University of Medical Science
• University of Medicine, Mandalay
• Taipei Medical University
• Chung Shan Medical University
• Siriraj Hospital, Mahidol University
• Prince of Songkhla University
• Chiang Mai University
• Naresuan University
• Vajira Hospital, Navamindradhiraj University
• Princess of Naradhiwas University
• School of Medicine, Walailak University
• Ubonratchathani University
• Phramongkutklao College of Medicine
• Khwaja Yunus Ali Medical College
• Ibrahim Medical College
• International University
• Soochow University
• Southern Medical University
• Zhejiang University
• Airlangga University
• Universitas Gadjah Mada
• Universitas Indonesia
• Hang Tuah University
• Diponegoro University
• Brawijaya University
• Andalas University
• University of Sumatera Utara
• Lambung Mangurat University
• Universitas Padjadjaran
• Faculty of Medicine, State islamic university syarif hidayatullah jakarta
• Faculty of Medicine, Mulawarman University
• Osaka Medical College
• University of Malaya Medical School
• University Putra Malaysia
• Mongolian National University of Medical Science
• College of Medicine, De La Salle Health Sciences Institute
• Chung Shan Medical University
• Siriraj Hospital, Mahidol University
• Prince of Songkhla University
• Chiang Mai University
• Naresuan University
• Vajira Hospital, Navamindradhiraj University
• Princess of Naradhiwas University
• School of Medicine, Walailak University
• Ubonratchathani University
• Phramongkutklao College of Medicine
• Faculty of Medicine, Thammasat University
• Khon Kaen University


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Move the colourwheel pointer to generate a sentence!
The closer to the center,
the more similar the result will
is supposed to be to the original sentence.


Akron faces Youngstown St.
by EndPlayAKRON, Ohio - Youngstown State (2-2) vs. Akron (3-1)
James A. Rhodes Arena, Akron, Ohio; Thursday, 7 p.m. EST
BOTTOM LINE: Youngstown State and Akron both look to put winning streaks together . Both teams are coming off of home victories in their last game. Akron earned a 76-45 win over South Carolina Upstate on Monday, while Youngstown State won 66-60 over NC Central on Tuesday.
LEADING THE CHARGE: The dynamic Xeyrius Williams has averaged 16.3 points, 9.3 rebounds and 2.8 blocks to lead the way for the Zips. Loren Cristian Jackson has paired with Williams and is maintaining an average of 14 points, four rebounds and four assists per game. The Penguins are led by Darius Quisneberry, who is averaging 15.5 points.DOMINANT DARIUS: Quisneberry has connected on 30 percent of the 20 3-pointers he's attempted and has gone 5 for 15 over his last three games. He's also converted 80 percent of his free throws this season.
STREAK SCORING: Akron has won its last three home games, scoring an average of 71.3 points while giving up 52.
PASSING FOR POINTS: The Zips have recently created baskets via assists more often than the Penguins. Akron has 33 assists on 60 field goals (55 percent) over its previous three contests while Youngstown State has assists on 22 of 68 field goals (32.4 percent) during its past three games.
DID YOU KNOW: Youngstown State has committed a turnover on just 16.5 percent of its possessions this season, which is the lowest rate among all Horizon teams. The Penguins have turned the ball over only 11.5 times per game this season.
___
For more AP college basketball coverage: https://apnews.com/Collegebasketball and http://twitter.com/AP_Top25
___
This was generated by Automated Insights, http://www.automatedinsights.com/ap, using data from STATS LLC, https://www.stats.com


Aldus Corporation, which later merged with Adobe Systems, helped bring Lorem Ipsum into the information age with its 1985 flagship software Aldus PageMaker. The program came bundled with Lorem Ipsum dummy text to help with laying out page content, and other word processors like Microsoft Word followed suit
Aldus Corporation, which later merged with Adobe Systems, helped bring Lorem Ipsum into the information age with its 1985 flagship software Aldus PageMaker. The program came bundled with Lorem Ipsum dummy text to help with laying out page content, and other word processors like Microsoft Word followed suit
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About DocketMinder
DocketMinder is an application designed for attorneys handling criminal cases in New Orleans. Once you register and type in your client’s case number, DocketMinder will check Orleans Parish’s Docket Master daily for updates to your client’s case. You will then receive an email highlighting the changes. DocketMinder is optimized for viewing on your desktop computer, tablet, or phone.
DocketMinder was designed by third year law students Nicholas Zotti and Michael Tassin of the Litigation and Technology section of the Loyola Law Clinic in the 2013 Spring Semester. The Litigation and Technology section is headed by Assistant Clinical Professor Judson Mitchell and seeks to discover and implement new ways for lawyers to use technology in daily practice. DocketMinder is open source software offered free of charge under the MIT license. The source code is available on Github.
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A class for multiple animation: a slideshow. More...
Public Member Functions | |
| SlideShow () | |
| A constructor. More... | |
| void | addAnimatedObject (AnimatedObject animatedObject) |
| Adds an animated object (animation). More... | |
| void | update (float elapsed) |
| Updates the current animation. More... | |
| void | next () |
| Activates the next animation in the slideshow. | |
| void | autoUpdate (float elapsed) |
| Updates the slideshow and changes the animation automatically once the animation has been shown completely. More... | |
| void | draw (SpriteBatch sb) |
| Draws the current frame of the current animation. More... | |
| void | stop () |
| Stops the slideshow. More... | |
| void | resume () |
| Resumes the slideshow. More... | |
A class for multiple animation: a slideshow.
The idea is that a slideshow contains multiple animations and the animation that is displayed can be changed by an event.
Part of the animation partition.
|
inline |
A constructor.
Sets the variables to default values.
|
inline |
Adds an animated object (animation).
| animatedObject | the AnimatedObject containing the animation you wish to add |
|
inline |
Updates the slideshow and changes the animation automatically once the animation has been shown completely.
| elapsed | elapsed time |
|
inline |
Draws the current frame of the current animation.
| sb | the spritebatch of the game |
|
inline |
Resumes the slideshow.
Resumes autoUpdate(), and the current animation. Enables next() function.
|
inline |
Stops the slideshow.
Stops autoUpdate(), and the current animation. Disables next() function.
|
inline |
Updates the current animation.
| elapsed | elapsed time |


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The no1. guide with everything you need to know.
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