/dports/science/py-phono3py/phono3py-1.22.3/phono3py/phonon3/ |
H A D | spectral_function.py | 68 for sigma_i, sigma in enumerate(spf.sigmas): 93 spf.spectral_functions[sigma_i, i], 94 spf.shifts[sigma_i, i], 95 spf.half_linewidths[sigma_i, i], 173 for sigma_i, sigma in enumerate(self._sigmas): 175 self._run_delta(self._gp_index, sigma_i) 216 def _run_gamma(self, ise, i, sigma, sigma_i): argument 225 self._gammas[sigma_i, i], 229 def _run_delta(self, i, sigma_i): argument 264 gammas = self._gammas[sigma_i, i, j, k] [all …]
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/dports/math/py-statsmodels/statsmodels-0.13.1/statsmodels/sandbox/panel/ |
H A D | panel_short.py | 112 sigma_i = self.get_within_cov(res_pooled.resid) 113 self.cholsigmainv_i = np.linalg.cholesky(np.linalg.pinv(sigma_i)).T 129 def __init__(self, endog, exog, group, sigma_i=None): argument 139 if sigma_i is None: 140 sigma_i = np.eye(int(nobs_i)) 141 self.cholsigmainv_i = np.linalg.cholesky(np.linalg.pinv(sigma_i)).T 164 sigma_i = self.get_within_cov(res_pooled.resid) 165 self.cholsigmainv_i = np.linalg.cholesky(np.linalg.pinv(sigma_i)).T 226 sigma_i = self.get_within_cov(results.resid) 227 self.cholsigmainv_i = np.linalg.cholesky(np.linalg.pinv(sigma_i)).T
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/dports/games/libtmcg/libTMCG-1.3.18/src/ |
H A D | PedersenVSS.cc | 104 in >> sigma_i >> tau_i; in PedersenVSS() 345 mpz_add(sigma_i, sigma_i, foo); in Share() 346 mpz_mod(sigma_i, sigma_i, q); in Share() 351 mpz_add_ui(sigma_i, sigma_i, 1L); in Share() 412 mpz_add_ui(sigma_i, sigma_i, 1L); in Share() 421 mpz_add(sigma_i, sigma_i, foo); in Share() 422 mpz_mod(sigma_i, sigma_i, q); in Share() 432 mpz_set_ui(sigma_i, 0L); in Share() 441 mpz_add(sigma_i, sigma_i, foo); in Share() 442 mpz_mod(sigma_i, sigma_i, q); in Share() [all …]
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/dports/science/dakota/dakota-6.13.0-release-public.src-UI/packages/external/acro/packages/scolib/src/libs/ |
H A D | EP.notes | 5 x_i += x_i + N(0,\sigma_i), 7 where $N(0,\sigma_i)$ is a normally distributed random variable with 8 standard deviation $\sigma_i$. If we assume that all of the dimensions 9 have been scaled properly, then the initial values for the $\sigma_i$ will 15 \sum_{i=1}^n N(0,\sigma_i) \equiv \sigma \sum_{i=1}^n N(0,1) \equiv \sigma \Chi^2(n). 24 E\left[ \sqrt{\sum_{i=1}^n N(0,\sigma_i) \right] = \sigma 2^(1/2) \Gamma[(n+1)/2] \Gamma[n/2].
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/dports/science/py-cirq-aqt/Cirq-0.12.0/examples/ |
H A D | direct_fidelity_estimation.py | 100 sigma_i = p.estimated_energy() 101 assert np.isclose(sigma_i.imag, 0.0, atol=1e-6) 102 sigma_i = sigma_i.real 104 return sigma_i 322 sigma_i: float 443 sigma_i = asyncio.get_event_loop().run_until_complete( 449 sigma_i, _ = compute_characteristic_function( 453 trial_results.append(Result(pauli_trace=pauli_trace, sigma_i=sigma_i)) 455 fidelity += sigma_i / rho_i
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/dports/science/py-cirq-ionq/Cirq-0.13.1/examples/ |
H A D | direct_fidelity_estimation.py | 99 sigma_i = p.estimated_energy() 100 assert np.isclose(sigma_i.imag, 0.0, atol=1e-6) 101 sigma_i = sigma_i.real 103 return sigma_i 321 sigma_i: float 445 sigma_i = duet.run( 453 sigma_i, _ = compute_characteristic_function( 457 trial_results.append(Result(pauli_trace=pauli_trace, sigma_i=sigma_i)) 459 fidelity += sigma_i / rho_i
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/dports/science/py-cirq-pasqal/Cirq-0.13.1/examples/ |
H A D | direct_fidelity_estimation.py | 99 sigma_i = p.estimated_energy() 100 assert np.isclose(sigma_i.imag, 0.0, atol=1e-6) 101 sigma_i = sigma_i.real 103 return sigma_i 321 sigma_i: float 445 sigma_i = duet.run( 453 sigma_i, _ = compute_characteristic_function( 457 trial_results.append(Result(pauli_trace=pauli_trace, sigma_i=sigma_i)) 459 fidelity += sigma_i / rho_i
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/dports/science/py-cirq-core/Cirq-0.13.1/examples/ |
H A D | direct_fidelity_estimation.py | 99 sigma_i = p.estimated_energy() 100 assert np.isclose(sigma_i.imag, 0.0, atol=1e-6) 101 sigma_i = sigma_i.real 103 return sigma_i 321 sigma_i: float 445 sigma_i = duet.run( 453 sigma_i, _ = compute_characteristic_function( 457 trial_results.append(Result(pauli_trace=pauli_trace, sigma_i=sigma_i)) 459 fidelity += sigma_i / rho_i
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/dports/science/py-cirq-google/Cirq-0.13.0/examples/ |
H A D | direct_fidelity_estimation.py | 99 sigma_i = p.estimated_energy() 100 assert np.isclose(sigma_i.imag, 0.0, atol=1e-6) 101 sigma_i = sigma_i.real 103 return sigma_i 321 sigma_i: float 445 sigma_i = duet.run( 453 sigma_i, _ = compute_characteristic_function( 457 trial_results.append(Result(pauli_trace=pauli_trace, sigma_i=sigma_i)) 459 fidelity += sigma_i / rho_i
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/dports/science/libvdwxc/libvdwxc-b1e0dd854310410012d05daf4c6661b49f31b2ab/src/ |
H A D | radial_test.c | 37 double potential(int N, double dr, double* rho_i, double* sigma_i, double* dedn_i, double* dedsigma… in potential() argument 41 double E = vdwxc_calculate_radial(data, N, dr, rho_i, sigma_i, in potential() 100 double* sigma_i = fftw_malloc(sizeof(double) * N); in main() local 108 read_data(N, sigma_i, "testdata/sigma.txt"); in main() 114 for (i=N/2; i<N; i++) sigma_i[i] = 0; in main() 117 double E1 = potential(N, dr, rho_i, sigma_i, dedn_i, dedsigma_i); in main()
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H A D | q0test.c | 140 double* sigma_i = (double*)malloc(ngpts * sizeof(double)); in main() local 146 sigma_i[ii] = 0.0; in main() 165 sigma_i[k + ldim[2] * (j + ldim[1] * i)] = 2. + cos((j0 - k0) / 5.0); in main() 171 double energy = vdwxc_calculate(vdw, rho_i, sigma_i, v_i, dedsigma_i); in main() 214 printf("sigma = %24.18f %24.18f\n", sigma_i[0], sigma_i[1]); in main() 253 free(sigma_i); in main()
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/dports/science/liggghts/LIGGGHTS-PUBLIC-3.8.0-26-g6e873439/doc/Eqs/ |
H A D | pair_eim2.tex | 7 \sigma_i & = & \sum_{j=i_1}^{i_N} q_j \cdot \psi_{ij} \left(r_{ij}\right) \\ 8 E_i\left(q_i,\sigma_i\right) & = & \frac{1}{2} \cdot q_i \cdot \sigma_i
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H A D | pair_eim1.tex | 6 …}^{N} \sum_{j=i_1}^{i_N} \phi_{ij} \left(r_{ij}\right) + \sum_{i=1}^{N}E_i\left(q_i,\sigma_i\right)
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/dports/textproc/texi2html/texi2html-5.0/test/formatting/res/tex_l2h_mediawiki/ |
H A D | tex | 12 \over \sigma_i\right)^2 16 \over \sigma_i\right)^2 \end{displaymath}]]</div>
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/dports/textproc/texi2html/texi2html-5.0/test/formatting/res_all/tex_l2h_mediawiki/ |
H A D | tex | 12 \over \sigma_i\right)^2 16 \over \sigma_i\right)^2 \end{displaymath}]]</div>
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/dports/math/openturns/openturns-1.18/python/doc/theory/reliability_sensitivity/ |
H A D | taylor_importance_factors.rst | 41 \Var Z = \sum_{i=1}^{n_X} \left(\frac{\partial h}{\partial x_i} (\muX)\right)^2 \sigma_i^2 47 - :math:`\sigma_i^2 = \Var X_i` is the variance of the i-th input variable. 54 \cF_i = \frac{\left(\frac{\partial h}{\partial x_i} (\muX)\right)^2 \sigma_i^2}{\Var Z}
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/dports/science/lammps/lammps-stable_29Sep2021/doc/src/ |
H A D | pair_eim.rst | 37 …}^{N} \sum_{j=i_1}^{i_N} \phi_{ij} \left(r_{ij}\right) + \sum_{i=1}^{N}E_i\left(q_i,\sigma_i\right) 42 q_i and the electrical potential :math:`\sigma_i` at its location. E_i, q_i, 43 and :math:`sigma_i` are calculated as 48 \sigma_i = & \sum_{j=i_1}^{i_N} q_j \cdot \psi_{ij} \left(r_{ij}\right) \\ 49 E_i\left(q_i,\sigma_i\right) = & \frac{1}{2} \cdot q_i \cdot \sigma_i
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/dports/science/lammps/lammps-stable_29Sep2021/src/DPD-REACT/ |
H A D | fix_shardlow.cpp | 192 double *cut_i, *cut2_i, *sigma_i; in ssa_update_dpd() local 222 sigma_i = pairDPD->sigma[itype]; in ssa_update_dpd() 267 double halfsigma_ij = 0.5*sigma_i[jtype]; in ssa_update_dpd() 357 double *cut_i, *cut2_i, *sigma_i, *kappa_i, *alpha_i; in ssa_update_dpde() local 389 sigma_i = pairDPDE->sigma[itype]; in ssa_update_dpde() 440 double halfsigma_ij = 0.5*sigma_i[jtype]; in ssa_update_dpde()
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/dports/math/openturns/openturns-1.18/python/src/ |
H A D | FractionalBrownianMotionModel_doc.i.in | 39 …C_{i,j}(s, t)=&\dfrac{\sigma_i\sigma_j}{2}\left\{\rho_{i,j}\left(\left|\dfrac{s}{\theta}\right|^{H… 46 …\forall s, t\in \Rset, C_{i,j}(s, t)=&\dfrac{\sigma_i\sigma_j}{2}\left\{\rho_{i,j}\left(\left|\dfr… 49 :math:`i`-th component and :math:`\sigma_i` its amplitude. Note that the scale
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/dports/math/openturns/openturns-1.18/python/doc/usecases/ |
H A D | use_case_chaboche.rst | 72 \sigma_i = G(\epsilon_i,R,C,\gamma) + (\epsilon_\sigma)_i, 76 The observations are the pairs :math:`\{(\epsilon_i,\sigma_i)\}_{i=1,...,n}`, i.e. each observation…
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/dports/science/gromacs/gromacs-2021.4/docs/reference-manual/topologies/ |
H A D | parameter-files.rst | 71 \mbox{V}_{ii} & = & C^{(6)}_{i} & = & 4\,\epsilon_i\sigma_i^{6} & 73 \mbox{W}_{ii} & = & C^{(12)}_{i} & = & 4\,\epsilon_i\sigma_i^{12} & 79 \mbox{V}_{ii} & = & \sigma_i & \mbox{[ nm ]} \\ 99 \sigma_{ij} & = & \frac{1}{2}(\sigma_i+\sigma_j) \\
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/dports/print/texinfo/texinfo-6.8/tp/tests/many_input_files/tex_t4ht_res/ |
H A D | tex_tex4ht_tex.tex | 7 \over \sigma_i\right)^2 $$
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/dports/print/texinfo/texinfo-6.8/tp/tests/tex_html/res_parser/tex_httex/ |
H A D | tex_tex4ht_tex.tex | 7 \over \sigma_i\right)^2 $$
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/dports/graphics/pcl-pointclouds/pcl-pcl-1.12.0/2d/include/pcl/2d/ |
H A D | keypoint.h | 61 const float sigma_i,
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/dports/textproc/texi2html/texi2html-5.0/test/many_input_files/tex_t4ht_res/ |
H A D | tex_tex4ht_tex.tex | 8 \over \sigma_i\right)^2 $$
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