Release 0.1.21

Author: dilpath

CHANGELOG.md

@@ -2,6 +2,15 @@
 
 ## 0.1 series
 
+### 0.1.21
+
+* PEtab spec compliance: measurements must now be not null, and numeric (#76)
+  * Users who relied on null measurements for simulation/plotting are
+    recommended to store these dummy simulation-only measurements in an
+    additional file, separate to real measurements used for calibration
+* Improve Unicode support (#79, fixes #77)
+* Convenience methods to scale or unscale a parameter vector (#78)
+
 ### 0.1.20
 
 * Visualization: plot additional simulation points (not only at measurements) (#62), bugfix (#68)

petab/conditions.py

@@ -51,8 +51,7 @@ def write_condition_df(df: pd.DataFrame, filename: str) -> None:
         df: PEtab condition table
         filename: Destination file name
     """
-    with open(filename, 'w') as fh:
-        df.to_csv(fh, sep='\t', index=True)
+    df.to_csv(filename, sep='\t', index=True)
 
 
 def create_condition_df(parameter_ids: Iterable[str],

petab/core.py

@@ -40,8 +40,7 @@ def write_simulation_df(df: pd.DataFrame, filename: str) -> None:
         df: PEtab simulation table
         filename: Destination file name
     """
-    with open(filename, 'w') as fh:
-        df.to_csv(fh, sep='\t', index=False)
+    df.to_csv(filename, sep='\t', index=False)
 
 
 def get_visualization_df(visualization_file: str) -> pd.DataFrame:
@@ -70,8 +69,7 @@ def write_visualization_df(df: pd.DataFrame, filename: str) -> None:
         df: PEtab visualization table
         filename: Destination file name
     """
-    with open(filename, 'w') as fh:
-        df.to_csv(fh, sep='\t', index=False)
+    df.to_csv(filename, sep='\t', index=False)
 
 
 def get_notnull_columns(df: pd.DataFrame, candidates: Iterable):

petab/lint.py

@@ -20,6 +20,8 @@
 __all__ = ['assert_all_parameters_present_in_parameter_df',
            'assert_measured_observables_defined',
            'assert_measurement_conditions_present_in_condition_table',
+           'assert_measurements_not_null',
+           'assert_measurements_numeric',
            'assert_model_parameters_in_condition_or_parameter_table',
            'assert_no_leading_trailing_whitespace',
            'assert_noise_distributions_valid',
@@ -177,6 +179,9 @@ def check_measurement_df(df: pd.DataFrame,
         measurements.assert_overrides_match_parameter_count(
             df, observable_df)
 
+    assert_measurements_not_null(df)
+    assert_measurements_numeric(df)
+
 
 def check_parameter_df(
         df: pd.DataFrame,
@@ -906,6 +911,51 @@ def assert_measurement_conditions_present_in_condition_table(
                              + str(missing_conditions))
 
 
+def assert_measurements_not_null(
+    measurement_df: pd.DataFrame,
+) -> None:
+    """Check whether all measurements are not null.
+
+    Arguments:
+        measurement_df:
+            PEtab measurement table.
+
+    Raises:
+        AssertionError:
+            Some measurement value(s) are null (missing).
+    """
+    if measurement_df[MEASUREMENT].isnull().any():
+        raise AssertionError('Some measurement(s) are null (missing).')
+
+
+def assert_measurements_numeric(
+    measurement_df: pd.DataFrame,
+) -> None:
+    """Check whether all measurements are numeric.
+
+    Note that null (missing) measurements are ignored.
+
+    Arguments:
+        measurement_df:
+            PEtab measurement table.
+
+    Raises:
+        AssertionError:
+            Some measurement value(s) are not numeric.
+    """
+    not_null_measurement_values = measurement_df[MEASUREMENT].dropna()
+    all_measurements_are_numeric = (
+        pd.to_numeric(not_null_measurement_values, errors='coerce')
+        .notnull()
+        .all()
+    )
+    if not all_measurements_are_numeric:
+        raise AssertionError(
+            'Some values in the `petab.C.MEASUREMENT` column of the PEtab '
+            'measurements table are not numeric.'
+        )
+
+
 def is_valid_identifier(x: str) -> bool:
     """Check whether `x` is a valid identifier
 

petab/measurements.py

@@ -57,8 +57,7 @@ def write_measurement_df(df: pd.DataFrame, filename: str) -> None:
         df: PEtab measurement table
         filename: Destination file name
     """
-    with open(filename, 'w') as fh:
-        df.to_csv(fh, sep='\t', index=False)
+    df.to_csv(filename, sep='\t', index=False)
 
 
 def get_noise_distributions(measurement_df: pd.DataFrame) -> dict:

petab/observables.py

@@ -60,8 +60,7 @@ def write_observable_df(df: pd.DataFrame, filename: str) -> None:
         df: PEtab observable table
         filename: Destination file name
     """
-    with open(filename, 'w') as fh:
-        df.to_csv(fh, sep='\t', index=True)
+    df.to_csv(filename, sep='\t', index=True)
 
 
 def get_output_parameters(

petab/parameters.py

@@ -89,8 +89,7 @@ def write_parameter_df(df: pd.DataFrame, filename: str) -> None:
         df: PEtab parameter table
         filename: Destination file name
     """
-    with open(filename, 'w') as fh:
-        df.to_csv(fh, sep='\t', index=True)
+    df.to_csv(filename, sep='\t', index=True)
 
 
 def get_optimization_parameters(parameter_df: pd.DataFrame) -> List[str]:

petab/problem.py

@@ -727,6 +727,54 @@ def sample_parameter_startpoints(self, n_starts: int = 100):
         return sampling.sample_parameter_startpoints(
             self.parameter_df, n_starts=n_starts)
 
+    def unscale_parameters(
+        self,
+        x_dict: Dict[str, float],
+    ) -> Dict[str, float]:
+        """Unscale parameter values.
+
+        Parameters
+        ----------
+        x_dict:
+            Keys are parameter IDs in the PEtab problem, values are scaled
+            parameter values.
+
+        Returns
+        -------
+        The unscaled parameter values.
+        """
+        return {
+            parameter_id: parameters.unscale(
+                parameter_value,
+                self.parameter_df[PARAMETER_SCALE][parameter_id],
+            )
+            for parameter_id, parameter_value in x_dict.items()
+        }
+
+    def scale_parameters(
+        self,
+        x_dict: Dict[str, float],
+    ) -> Dict[str, float]:
+        """Scale parameter values.
+
+        Parameters
+        ----------
+        x_dict:
+            Keys are parameter IDs in the PEtab problem, values are unscaled
+            parameter values.
+
+        Returns
+        -------
+        The scaled parameter values.
+        """
+        return {
+            parameter_id: parameters.scale(
+                parameter_value,
+                self.parameter_df[PARAMETER_SCALE][parameter_id],
+            )
+            for parameter_id, parameter_value in x_dict.items()
+        }
+
 
 def get_default_condition_file_name(model_name: str, folder: str = ''):
     """Get file name according to proposed convention"""

petab/version.py

@@ -1,2 +1,2 @@
 """PEtab library version"""
-__version__ = '0.1.20'
+__version__ = '0.1.21'

tests/test_parameters.py

@@ -112,7 +112,8 @@ def test_write_parameter_df():
     """Test parameters.write_parameter_df."""
     parameter_df = pd.DataFrame(data={
         PARAMETER_ID: ['par1', 'par2'],
-        PARAMETER_NAME: ['parname1', 'parname2'],
+        # Test utf8 characters
+        PARAMETER_NAME: ['ɑ', 'β'],
     }).set_index(PARAMETER_ID)
 
     with tempfile.NamedTemporaryFile(mode='w', delete=True) as fh: