Esempio n. 1
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    def _LMC_Gordon03(self, wave):
        """
        Gordon et al. (2003, ApJ, 594,279)
        """

        x = 1e4 / np.asarray([wave])  # inv microns

        X_tab = np.loadtxt(execution_path('LMC_Gordon.txt'))
        Xx = self.R_V * np.interp(x, X_tab[:, 0], X_tab[:, 1])
        return np.squeeze(Xx)
Esempio n. 2
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    def _Gal_SM79(self, wave):
        """
        from Savage & Mathis (1979, ARA&A, 17, 73)
        """

        x = 1e4 / np.asarray([wave])  # inv microns

        X_tab = np.loadtxt(execution_path('Gal_SM79.txt'))
        Xx = np.interp(x, X_tab[:, 0], X_tab[:, 1])
        return np.squeeze(Xx)
Esempio n. 3
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    def _LMC_Gordon03(self, wave):
        """
        Gordon et al. (2003, ApJ, 594,279)
        """
        
        x = 1e4 / np.asarray([wave]) # inv microns

        X_tab = np.loadtxt(execution_path('LMC_Gordon.txt'))
        Xx = self.R_V * np.interp(x, X_tab[:,0], X_tab[:,1])
        return np.squeeze(Xx)
Esempio n. 4
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    def _Gal_SM79(self, wave):
        """
        from Savage & Mathis (1979, ARA&A, 17, 73)
        """
        
        x = 1e4 / np.asarray([wave]) # inv microns

        X_tab = np.loadtxt(execution_path('Gal_SM79.txt'))
        Xx = np.interp(x, X_tab[:,0], X_tab[:,1])
        return np.squeeze(Xx)
Esempio n. 5
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    def _K76(self, wave):
        """
        from Kaler (1976, ApJS, 31, 517).
        This function returns the correction relative to Hbeta, not usable for absolute correction.
        """

        w = np.asarray([wave])  # inv microns

        f_tab = np.loadtxt(execution_path('Gal_Kaler.txt'))
        f = np.interp(w, f_tab[:, 0], f_tab[:, 1])
        return np.squeeze(f * self.cHbeta / 0.4 / self.E_BV)
Esempio n. 6
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    def _K76(self, wave):
        """
        from Kaler (1976, ApJS, 31, 517).
        This function returns the correction relative to Hbeta, not usable for absolute correction.
        """
        
        w = np.asarray([wave]) # inv microns

        f_tab = np.loadtxt(execution_path('Gal_Kaler.txt'))
        f = np.interp(w, f_tab[:,0], f_tab[:,1])
        return np.squeeze(f * self.cHbeta / 0.4 / self.E_BV)