Wording edits

Co-authored-by: Daniel J. Egger <[email protected]>

Author: nkanazawa1989

qiskit_experiments/curve_analysis/curve_analysis.py

@@ -244,11 +244,11 @@ def __init_subclass__(cls, **kwargs):
 
         super().__init_subclass__(**kwargs)
 
-        # Create fit model:
-        # The fit model is created only once when the sub-class, i.e. type, is initialized.
-        # This removes overhead of instantiating the same fit model object multiple times.
-        # Its impact is significant especially when user creates a parallel experiment instance,
-        # where the curve analysis subclass is instantiated multiple times along with fit model.
+        # Create the fit model, i.e. the function(s) to which the data is fit:
+        # The fit model is created only once when the sub-class is initialized.
+        # This removes the overhead of instantiating the same fit model object multiple times.
+        # This may occur in, e.g., parallel experiments where the curve analysis subclass is 
+        # instantiated multiple times.
         model_source = collections.defaultdict(list)
         for series in cls.__series__:
             model_source["fit_functions"].append(series.fit_func)
@@ -313,7 +313,7 @@ def curve_fit(
 
         This is the scipy curve fit wrapper to manage named fit parameters and
         return outcomes as ufloat objects with parameter correlation computed based on the
-        covariance matrix obtained from the fitting. Result is returned as
+        covariance matrix obtained from the fitting. The result is returned as
         :class:`~qiskit_experiments.curve_analysis.FitData` which is a special data container
         for curve analysis. This method can perform multi-objective optimization with
         multiple data series with related fit models.

qiskit_experiments/curve_analysis/curve_data.py

@@ -52,10 +52,10 @@ class SeriesDef:
     signature: List[str] = dataclasses.field(init=False)
 
     def __post_init__(self):
-        """Parse the fit function signature to extract the names of the variables."""
-        # Parse parameter names defiend in the fit function.
-        # Note that fit function usually takes arguments F(x, p0, p1, p2, ...)
-        # thus the first value should be excluded.
+        """Parse the fit function signature to extract the names of the variables.
+        
+        Fit functions take arguments F(x, p0, p1, p2, ...) thus the first value should be excluded.
+        """
         signature = list(inspect.signature(self.fit_func).parameters.keys())
         fitparams = signature[1:]
 

qiskit_experiments/curve_analysis/fit_models.py

@@ -28,7 +28,7 @@ class FitModel(ABC):
 
     This class ties together the fit function and associated parameter names to
     perform correct parameter mapping among multiple objective functions with different signatures,
-    in which some parameters may be excluded from the fitting when they are fixed.
+    in which some parameters may be excluded from the fitting when their values are fixed.
 
     Examples:
 

releasenotes/notes/add-fit-model-and-remove-curve_fitter-arg-4a0effb5f9b88ba9.yaml

@@ -18,7 +18,7 @@ features:
 upgrade:
   - |
     Analysis option `curve_fitter` of the :class:`CurveAnalysis` has been removed
-    because of the serialization problem. To use custom curve fitting library,
+    because callable lambda functions are not serializable. To use a custom curve fitting library,
     one must directly override the class method :meth:`CurveAnalysis.curve_fit`.
 developer:
   - |

test/curve_analysis/test_curve_analysis_base_class.py

@@ -253,7 +253,7 @@ class MyCurveFit(CurveAnalysis):
 
         instance = MyCurveFit()
 
-        # both par0 and par1 is excluded
+        # both par0 and par1 are included
         self.assertListEqual(instance.parameters, ["par0", "par1"])
 
         # par1 is excluded