Add petab.v2.reparametrize_log

PEtab v2 has no `parameterScale`. To estimate a parameter `p` on log
scale (and to specify priors for `log10(p)`), `p` has to be replaced by
a new parameter `log10_p` with `p = 10^log10_p`.

`reparametrize_log` does this for a given set of parameters on a copy
of the problem and returns the copy and the mapping of old to new IDs:

* parameter table: log-transformed bounds and nominal values (a lower
  bound of 0 becomes -inf); priors given explicitly, or derived from
  `log-normal`, `log-laplace` and `log-uniform` priors
* SBML model: new parameter `log10_p` and initial assignment
  `p = 10^log10_p`
* observable/noise formulas and condition table target values:
  `p` -> `10^log10_p`
* measurement table overrides: `p` -> `log10_p`, numeric overrides are
  log-transformed, and the placeholder `ph` -> `10^ph` in the formulas

Base e is supported as well.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>

Author: dweindl

CHANGELOG.md

@@ -72,6 +72,9 @@
 * `petab.v1.math.petab_symbol` (also in `petab.v2.math`) creates sympy
   symbols with the same assumptions as `sympify_petab`
   (by @dweindl in https://github.com/PEtab-dev/libpetab-python/pull/563)
+* `petab.v2.reparametrize_log` estimates parameters on log scale by replacing
+  them with new log-transformed parameters
+  (by @dweindl in https://github.com/PEtab-dev/libpetab-python/pull/560)
 
 ## 0.9 series
 

doc/modules.rst

@@ -40,3 +40,4 @@ API Reference
    petab.v2.models
    petab.v2.options
    petab.v2.petab1to2
+   petab.v2.reparametrize

petab/v2/__init__.py

@@ -38,3 +38,4 @@
 from .lint import lint_problem  # noqa: F401
 from .models import MODEL_TYPE_PYSB, MODEL_TYPE_SBML, Model  # noqa: F401
 from .options import *
+from .reparametrize import reparametrize_log  # noqa: F401

petab/v2/converters.py

@@ -17,7 +17,11 @@
     ExperimentPeriod,
     Problem,
 )
-from .models._sbml_utils import add_sbml_parameter, check
+from .models._sbml_utils import (
+    add_sbml_parameter,
+    check,
+    set_initial_assignment,
+)
 from .models.sbml_model import SbmlModel
 
 __all__ = ["ExperimentsToSbmlConverter", "assignments_to_experiments"]
@@ -351,13 +355,7 @@ def _create_initial_assignments(
                     (default, True),
                 )
 
-                # Create a new initial assignment if necessary, otherwise
-                #  overwrite the existing one.
-                if ia is None:
-                    ia = model.createInitialAssignment()
-                    ia.setSymbol(target_id)
-
-                set_math(ia, expr)
+                set_initial_assignment(model, target_id, expr)
                 free_symbols_in_assignments |= expr.free_symbols
 
         # the target value may depend on parameters that are only

petab/v2/models/_sbml_utils.py

@@ -1,6 +1,8 @@
 """Private utility functions for SBML handling."""
 
 import libsbml
+import sympy as sp
+from sbmlmath.mathml_printer import SBMLMathMLPrinter
 
 retval_to_str = {
     getattr(libsbml, attr): attr
@@ -49,3 +51,32 @@ def add_sbml_parameter(
         check(param.setConstant(constant))
 
     return param
+
+
+def set_initial_assignment(
+    model: libsbml.Model,
+    symbol_id: str,
+    expr: sp.Expr,
+    literals_dimensionless: bool = True,
+) -> libsbml.InitialAssignment:
+    """Set the initial assignment for the given symbol.
+
+    Overwrites any existing initial assignment for that symbol.
+
+    :param literals_dimensionless:
+        Whether to annotate numeric literals as dimensionless.
+        (`sbmlmath` can't read back, e.g., ``10^x`` with a dimensionless
+        base.)
+    """
+    if (ia := model.getInitialAssignmentBySymbol(symbol_id)) is None:
+        ia = model.createInitialAssignment()
+        check(ia.setSymbol(symbol_id))
+    mathml = SBMLMathMLPrinter(
+        sbml_level=model.getLevel(),
+        sbml_version=model.getVersion(),
+        literals_dimensionless=literals_dimensionless,
+    ).doprint(expr)
+    if (ast := libsbml.readMathMLFromString(mathml)) is None:
+        raise ValueError(f"Failed to convert `{expr}' to MathML.")
+    check(ia.setMath(ast))
+    return ia