/dports/converters/p5-String-Multibyte/String-Multibyte-1.12/t/ |
H A D | arylist.t | 14 $n = "\cM\cJ"; 16 $str = "[a1]\cM\cM[b2]\cM\cJ[c3]\cJ\cM[d4]\cJ\cJ[e5]\cJ\cM\cJ\cM"; 17 $ret = "[a1]\cJ\cJ[b2]\cM\cJ[c3]\cM\cJ[d4]\cM\cM[e5]\cM\cM\cJ\cJ"; 25 print $ret eq $crlf->strtr($str, ["\cM", "\cJ"], "\cJ\cM") 29 # \cJ to \cM\cJ and \cM to \cM\cJ 31 print $ret2 eq $crlf->strtr($str, "\cJ\cM", "\cM\cJ") 37 print $str eq $crlf->strtr($str, "\cM\cJ", "\cM\cJ") 40 $str = "\cM\cJ\cM\cJ\cM\cJ\cM"; 48 $str = "\cM\cM\cM\cM\cM\cM\cJ"; 62 $str = "\cJ\cM\cM\cM\cM\cM\cM"; [all …]
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H A D | grapheme.t | 28 print "\cM\cJ" =~ /^${reDGC}\z/ 29 && "\cM\cJ" !~ /^${reDGC}{2}\z/ 32 print "\cM\cM" !~ /^${reDGC}\z/ 33 && "\cM\cM" =~ /^${reDGC}{2}\z/ 40 print "\cJ\cM" !~ /^${reDGC}\z/ 41 && "\cJ\cM" =~ /^${reDGC}{2}\z/
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/dports/www/webtrees/webtrees-1.7.18/webtrees/app/Report/ |
H A D | ReportPdfTextbox.php | 141 $cM = $renderer->getMargins(); 144 if (is_array($cM['cell'])) { 145 $cWT = $cW - ($cM['padding_left'] + $cM['padding_right']); 147 $cWT = $cW - ($cM['cell'] * 2); 200 if (is_array($cM['cell'])) { 201 $cHT += ($cM['padding_bottom'] + $cM['padding_top']); 259 if (is_array($cM['cell'])) { 269 if (is_array($cM['cell'])) { 281 if (is_array($cM['cell'])) { 306 $renderer->SetLeftMargin($cM['left']); [all …]
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H A D | ReportPdfCell.php | 103 $cM = $renderer->getMargins(); 105 if (is_array($cM['cell'])) { 106 $cHT += ($cM['padding_bottom'] + $cM['padding_top']); 108 $cHT += ($cM['cell'] * 2);
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/dports/www/webtrees20/webtrees-2.0.19/webtrees/app/Report/ |
H A D | ReportPdfTextBox.php | 150 $cM = $renderer->tcpdf->getMargins(); 153 if (is_array($cM['cell'])) { 154 $cWT = $cW - ($cM['padding_left'] + $cM['padding_right']); 156 $cWT = $cW - $cM['cell'] * 2; 209 if (is_array($cM['cell'])) { 210 $cHT += $cM['padding_bottom'] + $cM['padding_top']; 212 $cHT += $cM['cell'] * 2; 266 if (is_array($cM['cell'])) { 276 if (is_array($cM['cell'])) { 288 if (is_array($cM['cell'])) { [all …]
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H A D | ReportPdfCell.php | 122 $cM = $renderer->tcpdf->getMargins(); 124 if (is_array($cM['cell'])) { 125 $cHT += $cM['padding_bottom'] + $cM['padding_top']; 127 $cHT += $cM['cell'] * 2;
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/dports/math/openturns/openturns-1.18/python/src/ |
H A D | ConditionedGaussianProcess_doc.i.in | 12 Mesh :math:`\cM` over which the domain :math:`\cD` is discretized. 31 …cM)` and the covariance evaluation on the mesh vertices :math:`\cC^{stat}_{\theta}(\cM)` condition… 33 …ta}(\cM)` of the covariance matrix :math:`\cC^{stat}_{\theta}(\cM)` such as :math:`\cC^{stat}_{\th… 34 …realizations are obtained as following : :math:`realization = Y(\cM) + \cL_{\theta}(\cM) W` with :…
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H A D | GeneralLinearModelResult_doc.i.in | 9 The meta model: :math:`\tilde{\cM}: \Rset^d \rightarrow \Rset^p`, defined in :eq:metaModel. 28 The meta model :math:`\tilde{\cM}: \Rset^d \rightarrow \Rset^p` is defined by: 33 \tilde{\cM}(\vect{x}) = \left( 48 \tilde{\cM}(\vect{x}) = \left( 58 Create the model :math:`\cM: \Rset \mapsto \Rset` and the samples: 133 The meta model :math:`\tilde{\cM}: \Rset^d \rightarrow \Rset^p`, defined in :eq:'metaModel'.
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H A D | NonStationaryCovarianceModelFactory_doc.i.in | 9 We denote :math:`(\vect{t}_0, \dots, \vect{t}_{N-1})` the vertices of the mesh :math:`\cM \in \cD`. 13 …math:`(\vect{x}_0^k, \dots, \vect{x}_{N-1}^k)` the values of the field *k* on the mesh :math:`\cM`. 29 First, we estimate the covariance function *C* on the vertices of the mesh :math:`\cM` using the em… 35 …& \forall \vect{t}_i \in \cM, \quad m(\vect{t}_i) \simeq \frac{1}{K} \sum_{k=1}^{K} \vect{x}_i^k \\ 46 where *k* is such that :math:`\vect{t}_k` is the vertex of :math:`\cM` the nearest to :math:`\vect{…
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/dports/x11-toolkits/p5-Tk/Tk-804.035/ |
H A D | Tk.xs | 691 XClientMessageEvent cM; in SendClientMessage() local 695 len = sizeof(cM.data); in SendClientMessage() 697 cM.serial = 0; in SendClientMessage() 698 cM.send_event = 0; in SendClientMessage() 700 cM.window = xid; in SendClientMessage() 702 cM.format = format; in SendClientMessage() 704 if ((RETVAL = XSendEvent(cM.display, cM.window, False, NoEventMask, (XEvent *) & cM))) in SendClientMessage() 744 cM.serial = 0; 745 cM.send_event = 0; 747 cM.window = xid; [all …]
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/dports/science/kim-api/kim-api-2.2.1/cpp/src/ |
H A D | KIM_ModelImplementation.cpp | 2398 cM.p = &M; in ModelDestroy() 2404 cM.p = &M; in ModelDestroy() 2474 cM.p = &M; in ModelComputeArgumentsCreate() 2482 cM.p = &M; in ModelComputeArgumentsCreate() 2558 cM.p = &M; in ModelComputeArgumentsDestroy() 2566 cM.p = &M; in ModelComputeArgumentsDestroy() 2639 cM.p = &M; in ModelCompute() 2648 cM.p = &M; in ModelCompute() 2718 cM.p = &M; in ModelExtension() 2724 cM.p = &M; in ModelExtension() [all …]
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/dports/news/fidogate/fidogate-5.10-3-g1c1fd41/scripts/areas/ |
H A D | areassucksync.in | 95 $resp =~ s/\cM?\cJ?$//; 103 $resp =~ s/\cM?\cJ?$//; 108 $resp =~ s/\cM?\cJ?$//; 127 s/\cM?\cJ?$//; 145 s/\cM?\cJ?$//; 164 s/\cM?\cJ?$//;
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/dports/math/geogram/geogram-1.7.7/src/lib/geogram/NL/ |
H A D | nl_cholmod.c | 412 cholmod_sparse_ptr cM= NULL; in nlMatrixFactorize_CHOLMOD() local 460 cM = CHOLMOD()->cholmod_allocate_sparse( in nlMatrixFactorize_CHOLMOD() 469 rowptr = (int*)cM->p; in nlMatrixFactorize_CHOLMOD() 470 colind = (int*)cM->i; in nlMatrixFactorize_CHOLMOD() 471 val = (double*)cM->x; in nlMatrixFactorize_CHOLMOD() 487 LLt->L = CHOLMOD()->cholmod_analyze(cM, &CHOLMOD()->cholmod_common); in nlMatrixFactorize_CHOLMOD() 488 if(!CHOLMOD()->cholmod_factorize(cM, LLt->L, &CHOLMOD()->cholmod_common)) { in nlMatrixFactorize_CHOLMOD() 493 CHOLMOD()->cholmod_free_sparse(&cM, &CHOLMOD()->cholmod_common); in nlMatrixFactorize_CHOLMOD()
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/dports/devel/p5-Term-ReadLine-Gnu/Term-ReadLine-Gnu-1.42/t/ |
H A D | readline.t | 596 $INSTR = "abcdefgh\cM"; 620 $INSTR = "1234\e?i\eoB\cM\cM"; 623 $INSTR = "\cM"; 628 $INSTR = "one\cMtwo\cMthree\cM\cP\cP\cP\cO\cO\cO\cM"; 656 $INSTR = "!1\cM"; 662 $INSTR = "!!\cM"; 666 $INSTR = "1234\cM"; 668 $INSTR = "!!\cM"; 848 $INSTR = "insert\cM"; 854 $INSTR = "insert\cM"; [all …]
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/dports/math/grace/grace-5.1.25/auxiliary/ |
H A D | fdf2fit | 30 s/\(.+?\)|\cM//g; 39 s/\(.+?\)|\cM//g; 48 s/\(.+?\)|\cM//g; 57 s/\(.+?\)|\cM//g;
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/dports/editors/abiword/abiword-3.0.5/src/text/fmt/xp/ |
H A D | fp_DirectionMarkerRun.cpp | 114 UT_UCS4Char cM = m_iMarker == UCS_LRM ? (UT_UCS4Char)'>' : (UT_UCS4Char)'<'; in _lookupProperties() local 115 m_iDrawWidth = pG->measureString(&cM, 0, 1, NULL); in _lookupProperties() 273 UT_UCS4Char cM = m_iMarker == UCS_LRM ? (UT_UCS4Char)'>' : (UT_UCS4Char)'<'; in _draw() local 274 m_iDrawWidth = getGraphics()->measureString(&cM, 0, 1, NULL); in _draw() 304 painter.drawChars(&cM, 0, 1, m_iXoffText, m_iYoffText); in _draw()
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/dports/lang/go-devel/go-becaeea1199b875bc24800fa88f2f4fea119bf78/test/fixedbugs/ |
H A D | issue46234.go | 42 cM *CM 58 cA, err := r.cM.NewA(ctx, cN, nn, WEA(), WEA()) 69 r := R{cM: &c}
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/dports/math/py-pynleq2/pysces-0.9.8/pysces/ |
H A D | PyscesScan.py | 107 cM = ModeList.index('elasticity') 108 if cM > MaxMode: 110 MaxMode = cM 112 cM = ModeList.index('mca') 113 if cM > MaxMode: 115 MaxMode = cM 117 cM = ModeList.index('stability') 118 if cM > MaxMode: 120 MaxMode = cM
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/dports/biology/py-PySCeS/pysces-1.0.0/pysces/ |
H A D | PyscesScan.py | 104 cM = ModeList.index('elasticity') 105 if cM > MaxMode: 107 MaxMode = cM 109 cM = ModeList.index('mca') 110 if cM > MaxMode: 112 MaxMode = cM 114 cM = ModeList.index('stability') 115 if cM > MaxMode: 117 MaxMode = cM
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/dports/math/openturns/openturns-1.18/python/doc/theory/probabilistic_modeling/ |
H A D | estimate_non_stationary_covariance_model.rst | 12 the common mesh :math:`\cM` and 30 vertices of the mesh :math:`\cM`. At each vertex 31 :math:`\vect{t}_i \in \cM`, we use the empirical mean estimator applied 39 …\displaystyle \forall \vect{t}_i \in \cM, \quad m(\vect{t}_i) \simeq \frac{1}{K} \sum_{k=1}^{K} \… 59 :math:`\cM` the nearest to :math:`\vect{s}` and :math:`\vect{t}_l` the
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H A D | field_function.rst | 28 :math:`\cM` into the multivariate stochastic process: 43 the :math:`\cM'`. 47 (:math:`\cD \neq \cD'` or :math:`\cM \neq \cM'`). 69 dimension of the vertices of the mesh :math:`\cM`. This data is
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/dports/math/viennacl/ViennaCL-1.7.1/examples/benchmarks/ |
H A D | dense_blas.cpp | 34 std::vector<T> cM(M.internal_size()); in init_random() local 37 cM[F::mem_index(i, j, M.internal_size1(), M.internal_size2())] = T(rand())/T(RAND_MAX); in init_random() 38 viennacl::fast_copy(&cM[0],&cM[0] + cM.size(),M); in init_random()
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H A D | dense_blas.cu | 34 std::vector<T> cM(M.internal_size()); in init_random() local 37 cM[F::mem_index(i, j, M.internal_size1(), M.internal_size2())] = T(rand())/T(RAND_MAX); in init_random() 38 viennacl::fast_copy(&cM[0],&cM[0] + cM.size(),M); in init_random()
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/dports/misc/libxdf/libxdf-0.991/smarc/ |
H A D | multi_stage.c | 528 const int cM = current->M[s]; in build_fast_ratios() local 531 bands[2] = (cL>cM) ? (fs-fstop) / fmax : (fs*cL/cM - fstop) / fmax; in build_fast_ratios() 534 int k=(flen-1)/(2*cM); in build_fast_ratios() 535 while (2*k*cM+1 < flen) in build_fast_ratios() 537 flen = 2*k*cM+1; in build_fast_ratios() 545 double stage_ops = flen*fs / cM; in build_fast_ratios() 548 fs = (fs * cL) / cM; in build_fast_ratios()
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/dports/math/pari/pari-2.13.3/src/basemath/ |
H A D | matperm.c | 44 GEN cM; in matpermanent() local 45 M = Q_primitive_part(M, &cM); in matpermanent() 47 if (cM) p = gerepileupto(av, gmul(p, gpowgs(cM,n))); in matpermanent()
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