full_wideband_designmatrix

nanograv · Feb 14, 2025 · aa07a51 · aa07a51
1 parent 8289c76
commit aa07a51
Showing 1 changed file with 5 additions and 51 deletions.
diff --git a/src/pint/fitter.py b/src/pint/fitter.py
@@ -1468,12 +1468,11 @@ def M_params_units_norm(self):
         )
 
         if not self.full_cov:
-            Mn = DesignMatrixMaker("toa_noise", u.s)(self.fitter.toas, self.model)
+            # Mn = DesignMatrixMaker("toa_noise", u.s)(self.fitter.toas, self.model)
             phiinv = 1 / self.model.full_basis_weight(self.fitter.toas)
-            if Mn is not None:
-                M, params, units, _ = self.model.full_wideband_designmatrix(
-                    self.fitter.toas
-                )
+            M, params, units, _ = self.model.full_wideband_designmatrix(
+                self.fitter.toas
+            )
 
         M, norm = normalize_designmatrix(M, params)
         self.fac = norm
@@ -1506,14 +1505,7 @@ def mtcm_mtcy_mtcmplain(self):
 
         # compute covariance matrices
         if self.full_cov:
-            cov = combine_covariance_matrix(
-                [
-                    CovarianceMatrixMaker("toa", u.s)(self.fitter.toas, self.model),
-                    CovarianceMatrixMaker("dm", u.pc / u.cm**3)(
-                        self.fitter.toas, self.model
-                    ),
-                ]
-            ).matrix
+            cov = self.model.wideband_covariance_matrix(self.fitter.toas)
             cf = scipy.linalg.cho_factor(cov)
             cm = scipy.linalg.cho_solve(cf, self.M)
             mtcm = np.dot(self.M.T, cm)
@@ -1568,44 +1560,6 @@ def step(self):
         # compute absolute estimates, normalized errors, covariance matrix
         return self.xhat / self.norm
 
-    @cached_property
-    def step1(self):
-        residuals = self.resids.calc_wideband_resids()
-
-        # compute covariance matrices
-        if self.full_cov:
-            M, params, units, _ = self.model.wideband_designmatrix(self.fitter.toas)
-            M, norm = normalize_designmatrix(M, params)
-            cov = self.model.wideband_covariance_matrix(self.fitter.toas)
-            mtcm, mtcy = get_gls_mtcm_mtcy_fullcov(cov, M, residuals)
-        else:
-            M, params, units, _ = self.model.full_wideband_designmatrix(
-                self.fitter.toas
-            )
-            M, norm = normalize_designmatrix(M, params)
-            phiinv = 1 / self.model.full_basis_weight(self.fitter.toas) / norm**2
-            self.phiinv = phiinv
-            Nvec = self.model.scaled_wideband_uncertainty(self.fitter.toas) ** 2
-            mtcm, mtcy = get_gls_mtcm_mtcy(phiinv, Nvec, M, residuals)
-
-        self.params = params
-        self.units = units
-        self.M = M
-        self.fac = norm
-
-        # TODO: seems like doing this on every iteration is wasteful, and we should just do it once and then update the matrix
-        covariance_matrix_labels = {
-            param: (i, i + 1, unit)
-            for i, (param, unit) in enumerate(zip(params, units))
-        }
-        # covariance matrix is 2D and symmetric
-        self.parameter_covariance_matrix_labels = [covariance_matrix_labels] * 2
-
-        self.xvar, self.xhat = _solve_svd(mtcm, mtcy, self.threshold, params)
-        self.norm = norm
-
-        return self.xhat / norm
-
     def take_step(self, step, lambda_=1):
         return WidebandState(
             self.fitter, self.take_step_model(step, lambda_), threshold=self.threshold