Cleanup old nlp code

Author: metab0t

src/pyoptinterface/_src/ipopt.py

@@ -14,10 +14,6 @@
 from .nlfunc import (
  ExpressionGraphContext,
  convert_to_expressionhandle,
- trace_function,
- FunctionTracingResult,
- Vars,
- Params,
 )
 
 from .core_ext import (
@@ -212,42 +208,6 @@ def get_constraint_dual(model, constraint):
 constraint_attribute_set_func_map = {}
 
 
-def match_variable_values(
- tracing_result: FunctionTracingResult, vars_dict: Dict[str, any]
-):
- nx = tracing_result.n_variables()
- variable_indices_map = tracing_result.variable_indices_map
- var_values = [None for _ in range(nx)]
- for v_name, value in vars_dict.items():
- index = variable_indices_map.get(v_name, None)
- if index is None:
- raise ValueError(f"Unknown variable name: {v_name}")
- var_values[index] = value
- for i, value in enumerate(var_values):
- if value is None:
- missing_name = tracing_result.variable_names[i]
- raise ValueError(f"Missing initial value for variable {missing_name}")
- return var_values
-
-
-def match_parameter_values(
- tracing_result: FunctionTracingResult, params_dict: Dict[str, any]
-):
- np = tracing_result.n_parameters()
- parameter_indices_map = tracing_result.parameter_indices_map
- param_values = [None for _ in range(np)]
- for p_name, value in params_dict.items():
- index = parameter_indices_map.get(p_name, None)
- if index is None:
- raise ValueError(f"Unknown parameter name: {p_name}")
- param_values[index] = value
- for i, value in enumerate(param_values):
- if value is None:
- missing_name = tracing_result.parameter_names[i]
- raise ValueError(f"Missing initial value for parameter {missing_name}")
- return param_values
-
-
 class Model(RawModel):
  def __init__(self, jit: str = "LLVM"):
  super().__init__()

src/pyoptinterface/_src/nlfunc.py

@@ -184,81 +184,3 @@ def ifelse(condition, true_expr, false_expr):
  TernaryOperator.IfThenElse, condition, true_expr, false_expr
  )
  return new_expression
-
-
-class DynamicTable:
- def __init__(self):
- self._data = {}
-
- def __getattr__(self, name):
- if name not in self._data:
- self._data[name] = self._create()
- return self._data[name]
-
- def __len__(self):
- return len(self._data)
-
- def _names(self):
- return list(self._data.keys())
-
- def _create(self):
- pass
-
-
-class VariableTable(DynamicTable):
- def _create(self):
- graph = ExpressionGraphContext.current_graph()
- variable = graph.add_variable(len(self))
- return variable
-
-
-class ParameterTable(DynamicTable):
- def _create(self):
- graph = ExpressionGraphContext.current_graph()
- parameter = graph.add_parameter(len(self))
- return parameter
-
-
-class FunctionTracingResult:
- def __init__(self, graph, results, variable_names, parameter_names):
- self.graph = graph
- self.results = results
- self.variable_names = variable_names
- self.parameter_names = parameter_names
-
- # record the inverse mapping from name to index
- self.variable_indices_map = {name: i for i, name in enumerate(variable_names)}
- self.parameter_indices_map = {name: i for i, name in enumerate(parameter_names)}
-
- def n_variables(self):
- return len(self.variable_names)
-
- def n_parameters(self):
- return len(self.parameter_names)
-
- def n_outputs(self):
- return len(self.results)
-
-
-def trace_function(f):
- with ExpressionGraphContext() as graph:
- vars = VariableTable()
- params = ParameterTable()
-
- # detect the number of arguments f receives
- # 1: f(vars)
- # 2: f(vars, params)
- # >2: error
- n_args = len(inspect.signature(f).parameters)
- if n_args == 1:
- results = f(vars)
- elif n_args == 2:
- results = f(vars, params)
- else:
- raise ValueError("Function to trace must receive either 1 or 2 arguments")
-
- # The results might be a scalar expressions or a list of scalar expressions
- if isinstance(results, ExpressionHandle):
- results = [results]
-
- return FunctionTracingResult(graph, results, vars._names(), params._names())