more work on loggaussian
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@ -34,10 +34,10 @@ AppDir:
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include:
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# for /usr/bin/env
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- coreutils
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- dash
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- zsync
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- hicolor-icon-theme
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# - coreutils
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# - dash
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# - zsync
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# - hicolor-icon-theme
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- libatlas3-base
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- python3.9-minimal
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- python3-numpy
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@ -55,7 +55,6 @@ AppDir:
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- libqt5test5
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- libqt5xml5
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- qtbase5-dev-tools
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- qtchooser
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- pyqt5-dev-tools
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- qtchooser
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- libavahi-client3
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@ -63,10 +62,18 @@ AppDir:
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- libavahi-common3
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- libwacom2
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- libwacom-common
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after_bundle: |
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echo "MONSTER SED FOLLOWING...(uncomment if needed for mpl-data)"
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# sed -i s,\'/usr/share/matplotlib/mpl-data\',"f\"\{os.environ.get\('APPDIR'\,'/'\)\}/usr/share/matplotlib/mpl-data\"", ${TARGET_APPDIR}/usr/lib/python3/dist-packages/matplotlib/__init__.py
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files:
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exclude:
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- usr/share/man
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- usr/share/doc/*/README.*
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- usr/share/doc/*/changelog.*
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- usr/share/doc/*/NEWS.*
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- usr/share/doc/*/TODO.}*
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runtime:
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# if needed, apparently replaces hardcoded location with APPDIR location
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# path_mappings:
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# - /usr/share/matplotlib/mpl-data:$APPDIR/usr/share/matplotlib/mpl-data
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version: "continuous"
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env:
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PATH: '${APPDIR}/usr/bin:${PATH}'
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@ -23,7 +23,7 @@ double logNormalDist(double tau, double tau0, double sigma) {
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return exp(- pow((log(tau/tau0) / sigma), 2) / 2.) / sqrt(2*M_PI)/sigma;
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}
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double logGaussianSD_high(double u, void *user_data) {
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double logGaussian_imag_high(double u, void *user_data) {
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double *c = (double *)user_data;
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double omega = c[0];
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@ -36,7 +36,7 @@ double logGaussianSD_high(double u, void *user_data) {
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return dist * omega * uu / (pow(uu, 2) + pow(omega, 2));
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}
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double logGaussianSD_low(double u, void *user_data) {
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double logGaussian_imag_low(double u, void *user_data) {
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double *c = (double *)user_data;
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double omega = c[0];
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@ -50,6 +50,33 @@ double logGaussianSD_low(double u, void *user_data) {
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return dist * omega * uu / (1. + pow(omega*uu, 2));
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}
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double logGaussian_real_high(double u, void *user_data) {
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double *c = (double *)user_data;
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double omega = c[0];
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double tau = c[1];
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double sigma = c[2];
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double uu = exp(-2.*u);
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double dist = logNormalDist(exp(uu), tau, sigma);
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return dist * uu / (uu + pow(omega, 2));
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}
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double logGaussian_real_low(double u, void *user_data) {
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double *c = (double *)user_data;
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double omega = c[0];
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double tau = c[1];
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double sigma = c[2];
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double uu = exp(u);
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double dist = logNormalDist(uu, tau, sigma);
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return dist / (1. + pow(omega*uu, 2));
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}
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double logGaussianCorrelation(double x, void *user_data) {
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double *c = (double *)user_data;
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@ -52,8 +52,8 @@ class LogGaussian(Distribution):
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res_real = _integration_parallel(_omega, _tau, sigma, _integrate_process_imag)
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res_imag = _integration_parallel(_omega, _tau, sigma, _integrate_process_real)
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else:
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res_real = None
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res_imag = None
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res_real = _integration_parallel(_omega, _tau, sigma, _integrate_process_imag)
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res_imag = _integration_parallel(_omega, _tau, sigma, _integrate_process_real)
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return (res_real + 1j * res_imag).squeeze()
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@ -95,8 +95,8 @@ def _integrate_specdens_c(omega: np.ndarray, tau: np.ndarray, sigma: float) -> n
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c = (ctypes.c_double * 3)(o, t, sigma)
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user_data = ctypes.cast(ctypes.pointer(c), ctypes.c_void_p)
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area = quad(LowLevelCallable(lib.logGaussianSD_high, user_data), 0, np.infty)[0]
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area += quad(LowLevelCallable(lib.logGaussianSD_low, user_data), -np.infty, 0)[0]
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area = quad(LowLevelCallable(lib.logGaussianSD_high, user_data), 0, np.infty, epsabs=1e-12, epsrel=1e-12)[0]
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area += quad(LowLevelCallable(lib.logGaussianSD_low, user_data), -np.infty, 0, epsabs=1e-12, epsrel=1e-12)[0]
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res.append(area)
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@ -105,9 +105,10 @@ def _integrate_specdens_c(omega: np.ndarray, tau: np.ndarray, sigma: float) -> n
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return res
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def _integrate_process_imag(omega_i, tau_j, sigma):
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area = quad(_integrand_freq_imag_high, 0, 50, args=(omega_i, tau_j, sigma))[0]
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area += quad(_integrand_freq_imag_low, -50, 0, args=(omega_i, tau_j, sigma))[0]
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def _integrate_process_imag(args):
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omega_i, tau_j, sigma = args
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area = quad(_integrand_freq_imag_high, 0, 50, args=(omega_i, tau_j, sigma), epsabs=1e-12, epsrel=1e-12)[0]
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area += quad(_integrand_freq_imag_low, -50, 0, args=(omega_i, tau_j, sigma), epsabs=1e-12, epsrel=1e-12)[0]
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return area
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@ -166,10 +167,3 @@ def _integrand_freq_real_low(u, omega, tau, sigma):
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def _integrand_freq_real_high(u, omega, tau, sigma):
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uu = np.exp(-2*u)
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return LogGaussian.distribution(np.exp(u), tau, sigma) * uu / (uu + omega**2)
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if __name__ == '__main__':
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import matplotlib.pyplot as plt
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xx = np.logspace(-5, 5)
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plt.loglog(xx, LogGaussian.specdens(xx, 1, 2))
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plt.show()
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