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pysersic · Jan 8, 2024 · a7de9f6 · a7de9f6
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diff --git a/examples/API-Summary.ipynb b/examples/API-Summary.ipynb
@@ -154,7 +154,7 @@
     "- `set_prior(parameter,distribution)`: directly set the prior of a parameter using a numpyro distribution. \n",
     "- `sample()`: sample; see api for all args. sets the `sampling_results` attribute. \n",
     "- `find_MAP()`: use optimizer to find \"best fit\" model. \n",
-    "-  `estimate_posterior()`: non-sampling methods of estimating posterior, uaing methods `laplace` or `svi-flow`; see the paper for more details. \n",
+    "-  `estimate_posterior()`: non-sampling methods of estimating posterior, uaing methods `laplace`, `svi-mvn` or `svi-flow`; see the paper for more details. \n",
     "- \n",
     "\n",
     "### FitSingle(BaseFitter)\n",
@@ -195,7 +195,6 @@
     "\n",
     "#### Methods Summary \n",
     "- `summary()`: returns `az.summary(self.idata)`; i.e., the summary data frame. \n",
-    "- `get_median_model()`: get the median model of the posterior draw. Returns a tuple of the params of that model, plus the actual model image. \n",
     "- `corner()`: wrapper around `corner.py` for plotting a corner plot of the results. (returns the corner fig).\n",
     "- `retrieve_param_quantiles(quantiles,return_dataframe)`: returns a dict, or if specified, dataframe of the quantiles on each parameter. Quantiles are provided as a list-like, in decimal form (e.g., by default [0.16,0.5,0.84]). \n",
     "- `retrieve_med_std()`: similar but for returning the median and std around the median for the properties. \n",

diff --git a/examples/example-fit.ipynb b/examples/example-fit.ipynb
diff --git a/examples/manual-priors.ipynb b/examples/manual-priors.ipynb
diff --git a/examples/multi-source-fitting.ipynb b/examples/multi-source-fitting.ipynb
diff --git a/examples/multiband-example.ipynb b/examples/multiband-example.ipynb
diff --git a/pysersic/priors.py b/pysersic/priors.py
@@ -214,7 +214,6 @@ def __init__(self, sky_type = 'none',sky_guess=None,sky_guess_err=None, suffix =
         elif self.sky_type == 'tilted-plane':
             self.sky_prior = TiltedPlaneSkyPrior(sky_guess=sky_guess, sky_guess_err=sky_guess_err, suffix = suffix)
 
-
     @property
     def param_names(self):
         return list(self.dist_dict.keys())
@@ -469,14 +468,14 @@ def check_vars(self, verbose = False) -> bool:
             True if all variable for given type are present with no extra, False otherwise
         """
         missing = []
-
-        for var in self.param_names:
+        param_names = base_profile_params[self.profile_type]
+        for var in param_names:
             if not var in self.dist_dict.keys():
                 missing.append(var)
 
         extra = []
-        for (name, descrip) in self.repr_dict.items():
-            if (name not in self.param_names) and ('sky' not in name):
+        for (name, descrip) in self.dist_dict.items():
+            if (name not in param_names) and ('sky' not in name):
                 extra.append(name)
         if verbose:
             print ("Missing params for profile: ", missing)