/dports/graphics/enblend/enblend-enfuse-4.2/doc/ |
H A D | exposure-weights.gp | 11 gaussian(y, y_opt, width) = exp(-0.5 * ((y - y_opt) / width)**2) 12 lorentzian(y, y_opt, width) = 1.0 / (1.0 + ((y - y_opt) / (width * fwhm_gaussian / fwhm_lorentzian)… 13 halfsine(y, y_opt, width) = \ 14 abs((y - y_opt) / (width * fwhm_gaussian / fwhm_halfsinusodial)) <= pi / 2.0 ? \ 15 cos((y - y_opt) / (width * fwhm_gaussian / fwhm_halfsinusodial)) : \ 17 fullsine(y, y_opt, width) = \ 18 abs((y - y_opt) / (width * fwhm_gaussian / fwhm_fullsinusodial)) <= pi ? \ 19 (1.0 + cos((y - y_opt) / (width * fwhm_gaussian / fwhm_fullsinusodial))) / 2.0 : \ 21 power(y, y_opt, width) = \ 22 abs((y - y_opt) / (width * fwhm_gaussian / fwhm_power)) <= 1.0 ? \ [all …]
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H A D | power.gp | 6 power(y, y_opt, width) = \ 7 abs((y - y_opt) / (width * fwhm_gaussian / fwhm_power)) <= 1.0 ? \ 8 1.0 - (abs(y - y_opt) / (width * fwhm_gaussian / fwhm_power))**4 : \
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H A D | fullsine.gp | 7 fullsine(y, y_opt, width) = \ 8 abs((y - y_opt) / (width * fwhm_gaussian / fwhm_fullsinusodial)) <= pi ? \ 9 (1.0 + cos((y - y_opt) / (width * fwhm_gaussian / fwhm_fullsinusodial))) / 2.0 : \
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H A D | halfsine.gp | 7 halfsine(y, y_opt, width) = \ 8 abs((y - y_opt) / (width * fwhm_gaussian / fwhm_halfsinusodial)) <= pi / 2.0 ? \ 9 cos((y - y_opt) / (width * fwhm_gaussian / fwhm_halfsinusodial)) : \
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H A D | lorentzian.gp | 6 lorentzian(y, y_opt, width) = 1.0 / (1.0 + ((y - y_opt) / (width * fwhm_gaussian / fwhm_lorentzian)…
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H A D | gaussian.gp | 7 gaussian(y, y_opt, width) = exp(-0.5 * ((y - y_opt) / width)**2)
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/dports/science/py-scikit-optimize/scikit-optimize-0.9.0/skopt/ |
H A D | acquisition.py | 7 def gaussian_acquisition_1D(X, model, y_opt=None, acq_func="LCB", 15 model, y_opt, acq_func=acq_func, 20 def _gaussian_acquisition(X, model, y_opt=None, acq_func="LCB", 51 func_and_grad = gaussian_ei(X, model, y_opt, xi, return_grad) 53 func_and_grad = gaussian_pi(X, model, y_opt, xi, return_grad) 149 def gaussian_pi(X, model, y_opt=0.0, xi=0.01, return_grad=False): 214 improve = y_opt - xi - mu[mask] 232 def gaussian_ei(X, model, y_opt=0.0, xi=0.01, return_grad=False): 297 improve = y_opt - xi - mu[mask]
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H A D | plots.py | 236 y_opt=np.min(curr_func_vals),
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/dports/math/py-algopy/algopy-0.5.7/documentation/sphinx/examples/ |
H A D | preferred_nucleotide.py | 237 y_opt = result[0] 238 log_mu_opt, d_opt = y_opt[0], y_opt[1] 240 cov = scipy.linalg.inv(numdifftools.Hessian(eval_f_partial)(y_opt)) 248 print(numdifftools.Gradient(eval_f_partial)(y_opt)) 269 y_opt = result[0] 270 log_mu_opt, d_opt = y_opt[0], y_opt[1] 272 cov = scipy.linalg.inv(eval_hess_f_partial(y_opt)) 280 print(eval_grad_f_partial(y_opt))
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/dports/security/gwee/gwee-1.36/ |
H A D | gwee.c | 115 char *y_opt = ""; variable 1829 y_opt, TMPFILE, z_opt); 1838 url, y_opt, TMPFILE, z_opt); 1871 y_opt, imprefix, TMPFILE, wgeturl, z_opt); 1875 url, y_opt, imprefix, TMPFILE, wgeturl, z_opt); 2070 y_opt, TMPFILE, z_opt); 2074 url, y_opt, TMPFILE, z_opt); 2098 y_opt, TMPFILE, z_opt); 2107 url, y_opt, TMPFILE, z_opt); 2430 y_opt = (char *)strdup(optarg); [all …]
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/dports/science/py-scikit-optimize/scikit-optimize-0.9.0/doc/modules/ |
H A D | acquisition.rst | 25 where ``u(f(x)) = 1``, if ``f(x) < y_opt`` and ``u(f(x)) = 0``, 26 if ``f(x) > y_opt``. 44 where ``u(f(x)) = 0``, if ``f(x) > y_opt`` and ``u(f(x)) = y_opt - f(x)``, 45 if ``f(x) < y_opt``.
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/dports/multimedia/aegisub/aegisub-3.2.2/src/ |
H A D | persist_location.cpp | 30 , y_opt(OPT_SET(options_prefix + "/Last/Y")) in PersistLocation() 37 int y = y_opt->GetInt(); in PersistLocation() 85 y_opt->SetInt(pos.y); in OnMove()
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H A D | persist_location.h | 37 agi::OptionValue *y_opt; variable
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/dports/math/py-osqp/osqp-0.6.2.post0/module/tests/ |
H A D | warm_start_test.py | 49 y_opt = res.y 58 self.model.warm_start(x=x_opt, y=y_opt)
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/dports/math/casadi/casadi-3.5.5/docs/examples/cplusplus/ |
H A D | chain_qp.cpp | 167 DM y_opt = x_opt(Slice(0, x_opt.size1(), 2)); in main() local 180 file << "y_opt = " << y_opt << ";" << endl; in main()
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/dports/databases/grass7/grass-7.8.6/display/d.linegraph/ |
H A D | main.c | 210 struct Option *dir_opt, *x_opt, *y_opt; in main() local 242 y_opt = G_define_option(); in main() 243 y_opt->key = "y_file"; in main() 244 y_opt->description = _("Name of data file(s) for Y axis of graph"); in main() 245 y_opt->type = TYPE_STRING; in main() 246 y_opt->required = YES; in main() 247 y_opt->multiple = YES; in main() 421 for (i = 0, j = 1; (name = y_opt->answers[i]); i++, j++) { in main()
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/dports/comms/liquid-dsp/liquid-dsp-1.3.2/src/filter/src/ |
H A D | rkaiser.c | 382 float y_opt = 0.0f; in liquid_firdes_rkaiser_quadratic() local 413 if (p==0 || y1 < y_opt) { in liquid_firdes_rkaiser_quadratic() 415 y_opt = y1; in liquid_firdes_rkaiser_quadratic()
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/dports/devel/ncurses/ncurses-6.3/test/ |
H A D | demo_termcap.c | 84 static bool y_opt = FALSE; variable 370 if (x_opt && (my_blob == 0) && y_opt) { in demo_termcap() 827 y_opt = TRUE; in main()
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H A D | demo_terminfo.c | 75 static bool y_opt = FALSE; variable 367 if (y_opt) { in demo_terminfo() 852 y_opt = TRUE; in main()
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/dports/science/p5-Chemistry-File-Mopac/Chemistry-File-Mopac-0.15/ |
H A D | Mopac.pm | 165 my ($symbol, $x_val, $x_opt, $y_val, $y_opt,
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/dports/science/p5-PerlMol/PerlMol-0.3500/inc/BUNDLES/Chemistry-File-Mopac-0.15/ |
H A D | Mopac.pm | 165 my ($symbol, $x_val, $x_opt, $y_val, $y_opt,
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/dports/science/py-scipy/scipy-1.7.1/scipy/signal/ |
H A D | signaltools.py | 3867 y_opt = y_fb 3869 y_opt += wic 3871 y_opt[..., :m] += wic[..., :m] 3872 y_opt[..., -m:] += wic[..., -m:] 3880 y_opt = np.swapaxes(y_opt, axis, x.ndim - 1) 3882 return y_opt, x0, x1
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/dports/science/py-scikit-optimize/scikit-optimize-0.9.0/skopt/optimizer/ |
H A D | optimizer.py | 558 X=X, model=est, y_opt=np.min(self.yi),
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