Merge pull request #467 from HajimeKawahara/refact2

self merge. Refact2

src/exojax/spec/api.py

@@ -195,70 +195,6 @@ def activate(self, df, mask=None):
         if self.gpu_transfer:
             self.generate_jnp_arrays()
 
-    def compute_broadening_(
-        self, jlower, jupper, alpha_ref_def=None, n_Texp_def=None, output=None
-    ):
-        """computing broadening parameters
-
-        Parameters
-        ----------
-        jlower: jlower array
-        jupper: jupper array
-        alpha_ref: set default alpha_ref and apply it. None=use self.alpha_ref_def
-        n_Texp_def: set default n_Texp and apply it. None=use self.n_Texp_def
-
-        Returns
-        -------
-        None. Store values in self.n_Texp and self.alpha_ref.
-
-        """
-        if alpha_ref_def:
-            self.alpha_ref_def = alpha_ref_def
-        if n_Texp_def:
-            self.n_Texp_def = n_Texp_def
-
-        if self.broadf:
-            try:
-                print(".broad is used.")
-                bdat = read_broad(self.broad_file)
-                codelv = check_bdat(bdat)
-                print("Broadening code level=", codelv)
-                if codelv == "a0":
-                    j2alpha_ref, j2n_Texp = make_j2b(
-                        bdat,
-                        alpha_ref_default=self.alpha_ref_def,
-                        n_Texp_default=self.n_Texp_def,
-                        jlower_max=np.max(jlower),
-                    )
-                    self.alpha_ref = np.array(j2alpha_ref[jlower])
-                    self.n_Texp = np.array(j2n_Texp[jlower])
-                elif codelv == "a1":
-                    j2alpha_ref, j2n_Texp = make_j2b(
-                        bdat,
-                        alpha_ref_default=self.alpha_ref_def,
-                        n_Texp_default=self.n_Texp_def,
-                        jlower_max=np.max(jlower),
-                    )
-                    jj2alpha_ref, jj2n_Texp = make_jj2b(
-                        bdat,
-                        j2alpha_ref_def=j2alpha_ref,
-                        j2n_Texp_def=j2n_Texp,
-                        jupper_max=np.max(jupper),
-                    )
-                    self.alpha_ref = np.array(jj2alpha_ref[jlower, jupper])
-                    self.n_Texp = np.array(jj2n_Texp[jlower, jupper])
-            except FileNotFoundError:
-                print(
-                    "Warning: Cannot load .broad. The default broadening parameters are used."
-                )
-                self.alpha_ref = np.array(self.alpha_ref_def * np.ones_like(jlower))
-                self.n_Texp = np.array(self.n_Texp_def * np.ones_like(jlower))
-
-        else:
-            print("The default broadening parameters are used.")
-            self.alpha_ref = np.array(self.alpha_ref_def * np.ones_like(jlower))
-            self.n_Texp = np.array(self.n_Texp_def * np.ones_like(jlower))
-
     def compute_load_mask(self, df):
         # wavelength
         print(df)