diff --git a/gsf/fitting.py b/gsf/fitting.py
index 5872383..8089683 100644
--- a/gsf/fitting.py
+++ b/gsf/fitting.py
@@ -791,15 +791,16 @@ def update_input(self, inputs, c:float=3e18, Mpc_cm:float=3.08568025e+24, m0set:
             elif self.dust_model == 4:
                 self.dust_model_name = 'KriekConroy'
             else:
-                self.logger.warning('Unknown index number for dust attenuation. Setting to Calzetti.')
+                self.logger.warning('Unknown index number for dust model. Setting to Calzetti.')
                 self.dust_model = 0
                 self.dust_model_name = 'Calz'
         except:
+            self.logger.warning('Index number for dust model (DUST_MODEL) cannot be found. Setting to Calzetti.')
             self.dust_model = 0
             self.dust_model_name = 'Calz'
 
         if self.verbose:
-            self.logger.info('Dust attenuation is set to %s\n'%self.dust_model_name)
+            self.logger.info('Dust model is set to %s\n'%self.dust_model_name)
 
         # If FIR data;
         try:
diff --git a/gsf/function.py b/gsf/function.py
index c9eed43..67ec8fc 100644
--- a/gsf/function.py
+++ b/gsf/function.py
@@ -739,7 +739,7 @@ def apply_dust(yy, xx, nr, Av, dust_model=0):
 	elif dust_model == 2: # LMC
 		yyd, xxd, nrd = dust_gen(xx, yy, Av, nr, Rv=4.05, gamma=-0.06, Eb=2.8)
 	elif dust_model == 3: # SMC
-		yyd, xxd, nrd = dust_smc(xx, yy, Av, nr, Rv=2.74, x0=4.703, gamma=1.212, lmlimu=3.115, f_Alam=False)
+		yyd, xxd, nrd = dust_smc(xx, yy, Av, nr, Rv=2.74, x0=4.703, gamma=1.212, f_Alam=False)
 	elif dust_model == 4: # Kriek&Conroy with gamma=-0.2
 		yyd, xxd, nrd = dust_kc(xx, yy, Av, nr, Rv=4.05, gamma=-0.2)
 	else:
@@ -747,16 +747,14 @@ def apply_dust(yy, xx, nr, Av, dust_model=0):
 	return yyd, xxd, nrd
 
 
-def dust_smc(lm, fl, Av, nr, Rv=2.74, x0=4.703, gamma=1.212, lmlimu=3.115, f_Alam=False):
+def dust_smc(lm, fl, Av, nr, Rv=2.74, x0=4.6, gamma=1.0, f_Alam=False):
     '''
-    For general purpose (Noll+09).
-    This function is much better than previous, but is hard to impliment for the current version.
-    A difference from dust_gen is Eb is defined as a function of gamma.
+    Dust law for SMC (Gordon+03).
 
     Parameters
     ----------
     lm : float array
-        wavelength, at RF.
+        wavelength in AA, at RF.
     fl : float array
         fnu
     Av : float
@@ -772,42 +770,42 @@ def dust_smc(lm, fl, Av, nr, Rv=2.74, x0=4.703, gamma=1.212, lmlimu=3.115, f_Ala
     # if any(np.diff(lm)<0):
     #     print('Something is wrong in lm: dust_smc of function.py')
 
-    lmm  = lm/10000. # in micron
-    con1 = (lmm<=0.63)
-    con2 = (lmm>0.63)  & (lmm<=lmlimu)
-    con3 = (lmm>lmlimu)
-
-    #nr0 = nr[con0]
-    nr1 = nr[con1]
-    nr2 = nr[con2]
-    nr3 = nr[con3]
-
-    #lmm0 = lmm[con0]
-    lmm1 = lmm[con1]
-    lmm2 = lmm[con2]
-    lmm3 = lmm[con3]
-
-    #fl0 = fl[con0]
-    fl1 = fl[con1]
-    fl2 = fl[con2]
-    fl3 = fl[con3]
-
-    nrd  = np.concatenate([nr1,nr2,nr3])
-    lmmc = np.concatenate([lmm1,lmm2,lmm3])
-    flc  = np.concatenate([fl1,fl2,fl3])
+    lmm  = lm/10000. # into micron
+    nrd = nr #np.concatenate([nr1,nr2,nr3])
+    lmmc = lmm #np.concatenate([lmm1,lmm2,lmm3])
+    flc = fl #np.concatenate([fl1,fl2,fl3])
 
     # Using average for SMC;
-    c1,c2,c3,c4 = -0.856, 1.038, 3.215, 0.107
+    c1,c2,c3,c4 = -4.959, 2.264, 0.389, 0.461
+    # SMC Wing Sample;
+    # c1,c2,c3,c4 = -0.856, 1.038, 3.215, 0.107
+
     x = 1./lmmc
-    Dx = x**2 / ((x**2-x0**2)**2 +x**2*gamma**2)
-    Fx = 0.5329 * (x - 5.9)**2 + 0.05644 * (x-5.9)**3
+    Dx = x**2 / ((x**2-x0**2)**2 + x**2*gamma**2)
+    Fx = 0.5392 * (x - 5.9)**2 + 0.05644 * (x-5.9)**3
     con_fx = (x<5.9)
     Fx[con_fx] = 0
 
-    EBlam_to_EB = c1+c2*x+c3*Dx+c4*Fx
+    EBlam_to_EB = c1 + c2*x + c3*Dx + c4*Fx
     Alam = Av / Rv * EBlam_to_EB
     fl_cor = flc[:] * 10**(-0.4*Alam[:])
 
+    if False:
+        import matplotlib.pyplot as plt
+        plt.close()
+        xs = np.arange(0.5, 10, 0.01)
+        x = xs
+        Dx = x**2 / ((x**2-x0**2)**2 + x**2*gamma**2)
+        Fx = 0.5392 * (x - 5.9)**2 + 0.05644 * (x-5.9)**3
+        con_fx = (x<5.9)
+        Fx[con_fx] = 0
+        EBlam_to_EB = c1 + c2*x + c3*Dx + c4*Fx
+        Av = 2.0
+        Alam = Av / Rv * EBlam_to_EB
+        plt.scatter(x, EBlam_to_EB, )
+        plt.show()
+        hoge
+
     if f_Alam:
         return fl_cor, lmmc*10000., nrd, Alam
     else:
diff --git a/gsf/plot_sed.py b/gsf/plot_sed.py
index 92ebf75..9b561fd 100644
--- a/gsf/plot_sed.py
+++ b/gsf/plot_sed.py
@@ -1077,6 +1077,8 @@ def plot_sed(MB, flim=0.01, fil_path='./', scale=None, f_chind=True, figpdf=Fals
         hdr['library'] = LIBRARY
         hdr['nimf'] = nimf
         hdr['scale'] = scale
+        hdr['dust model'] = MB.dust_model_name
+        hdr['ndust model'] = MB.dust_model
 
         try:
             # Chi square:
@@ -1184,7 +1186,6 @@ def plot_sed(MB, flim=0.01, fil_path='./', scale=None, f_chind=True, figpdf=Fals
                     tree_spec['header'].update({'%s'%key: hdr[key] * u.solMass / u.yr})
                 else:
                     tree_spec['header'].update({'%s'%key: hdr[key]})
-
         # BB;
         Cnu_to_Jy = 10**((23.9-m0set)) # fnu_mzpset to microJy. So the final output SED library has uJy.
         # tree_spec['model'].update({'wave_bb': lbb * u.AA})