Fix #101, bugfix parameter fitting

matthiaskoenig · Mar 21, 2021 · b3635b3 · b3635b3
1 parent 35843f6
commit b3635b3
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Showing 3 changed files with 14 additions and 1 deletion.
diff --git a/release-notes/next-release.md b/release-notes/next-release.md
@@ -2,6 +2,7 @@
 - breaking changes in units handling
 - bugfix plotting `dimensionless` units in labels
 - remove deprecated `distrib` and `sampling` functionality.
+- fixed typo in sensitivity
 
 **parameter fitting**
 - refactoring parameter fitting
@@ -18,3 +19,4 @@
   - ‘arctan’ : rho(z) = arctan(z). Limits a maximum loss on a single residual, has properties similar to ‘cauchy’.
 - figures closing in reports (#88)
 - improved parameter fitting plots and results (#32)
+- bugfix all NaN errors (#101)
diff --git a/src/sbmlsim/fit/optimization.py b/src/sbmlsim/fit/optimization.py
@@ -346,6 +346,7 @@ def initialize(
                     # Changes to baseline, which is the first point
                     y_ref = y_ref - y_ref[0]
 
+                # --- errors on data ---
                 # Use errors for weighting (tries SD and falls back on SE)
                 y_ref_err = None
                 if data_ref.y_sd is not None:
@@ -356,15 +357,25 @@ def initialize(
                     y_ref_err_type = "SE"
                 else:
                     y_ref_err_type = None
+                # handle special case of all NaN
+                if np.all(np.isnan(y_ref_err)):
+                    y_ref_err = None
+                    y_ref_err_type = None
 
                 # handle missing data (0.0 and NaN)
                 if y_ref_err is not None:
                     # remove 0.0 from y-error
                     y_ref_err[(y_ref_err == 0.0)] = np.NAN
                     if np.all(np.isnan(y_ref_err)):
                         # handle special case of all NaN errors
+                        logger.warning(
+                            f"Errors are all NaN '{sid}.{mapping_id}' y data: "
+                            f"'{y_ref_err}'"
+                        )
                         y_ref_err = None
+                        y_ref_err_type = None
                     else:
+                        # FIXME: this must be based on coefficient of variation
                         # some NaNs could exist (err is maximal error of all points)
                         y_ref_err[np.isnan(y_ref_err)] = np.nanmax(y_ref_err)
 

diff --git a/src/sbmlsim/serialization.py b/src/sbmlsim/serialization.py
@@ -57,7 +57,7 @@ def default(self, o):
 
         if hasattr(o, "to_dict"):
             # custom serializer
-            print(type(o))
+            # print(type(o))
             if isinstance(o, type):
                 print(o.__name__)
             return o.to_dict()