From 574b8a1a1dd9a6ffdf18cc2e500a4de1a834ff21 Mon Sep 17 00:00:00 2001
From: radek_poleski <radek.poleski@gmail.com>
Date: Mon, 20 Jun 2022 20:07:57 +0200
Subject: [PATCH] ex16: _get_example_parameters() - moving fixed parameters to
 begin in order to prepare future commits

---
 examples/example_16/TO_DO.md           |  1 +
 examples/example_16/ulens_model_fit.py | 19 ++++++++++---------
 2 files changed, 11 insertions(+), 9 deletions(-)

diff --git a/examples/example_16/TO_DO.md b/examples/example_16/TO_DO.md
index c03ebc04..839e311b 100644
--- a/examples/example_16/TO_DO.md
+++ b/examples/example_16/TO_DO.md
@@ -12,6 +12,7 @@
 - posterior files
 - print model
 - example with add_2450000: False
+- yaml output in README.md
 
 # NOW - plot trajectory:
 - test if works in ulens_model_plot.py
diff --git a/examples/example_16/ulens_model_fit.py b/examples/example_16/ulens_model_fit.py
index 4a571ba9..e545fbd4 100644
--- a/examples/example_16/ulens_model_fit.py
+++ b/examples/example_16/ulens_model_fit.py
@@ -38,7 +38,7 @@
 except Exception:
     raise ImportError('\nYou have to install MulensModel first!\n')
 
-__version__ = '0.30.0'
+__version__ = '0.30.1'
 
 
 class UlensModelFit(object):
@@ -1498,19 +1498,24 @@ def _get_example_parameters(self):
         Generate parameters *dict* according to provided starting and fixed
         parameters.
         """
+        if self._fixed_parameters is None:
+            parameters = dict()
+        else:
+            parameters = {**self._fixed_parameters}
+
         if self._task == 'plot':
-            parameters = dict(zip(
+            parameters.update(dict(zip(
                 self._model_parameters['parameters'],
-                self._model_parameters['values']))
+                self._model_parameters['values'])))
             # XXX this is some kind of a hack:
             self._best_model_theta = []
             self._fit_parameters = []
         elif self._task == 'fit':
             if self._fit_method == 'EMCEE':
-                parameters = self._get_example_parameters_EMCEE()
+                parameters.update(self._get_example_parameters_EMCEE())
             elif self._fit_method == 'MultiNest':
                 means = 0.5 * (self._max_values + self._min_values)
-                parameters = dict(zip(self._fit_parameters, means))
+                parameters.update(dict(zip(self._fit_parameters, means)))
                 if "x_caustic_in" in self._fit_parameters:
                     index = self._fit_parameters.index("x_caustic_in")
                     parameters["x_caustic_in"] = (
@@ -1521,10 +1526,6 @@ def _get_example_parameters(self):
         else:
             raise ValueError('internal value')
 
-        if self._fixed_parameters is not None:
-            for (key, value) in self._fixed_parameters.items():
-                parameters[key] = value
-
         return parameters
 
     def _get_example_parameters_EMCEE(self):