diff options
Diffstat (limited to 'lib/model.py')
| -rw-r--r-- | lib/model.py | 31 |
1 files changed, 18 insertions, 13 deletions
diff --git a/lib/model.py b/lib/model.py index f01ae5d..f25e44f 100644 --- a/lib/model.py +++ b/lib/model.py @@ -6,6 +6,7 @@ import os from .automata import PTA, ModelAttribute from .functions import StaticFunction, SubstateFunction, SplitFunction from .parameters import ( + ParamType, ParallelParamStats, ParamStats, codependent_param_dict, @@ -127,10 +128,14 @@ class AnalyticModel: self._num_args = _num_args_from_by_name(by_name) self.distinct_param_values_by_name = dict() + self.param_type_by_name = dict() for name in self.names: self.distinct_param_values_by_name[name] = distinct_param_values( by_name[name]["param"] ) + self.param_type_by_name[name] = ParamType( + self.distinct_param_values_by_name[name], values_are_distinct=True + ) self.fit_done = False @@ -439,24 +444,20 @@ class AnalyticModel: "scalar": 0, "enum": 0, } - for param_index, param_values in enumerate( - self.distinct_param_values_by_name[name] - ): - if None in param_values: - none_adj = -1 - else: - none_adj = 0 - value_count = len(param_values) + none_adj - if value_count == 0: + for param_index in range(len(self.parameters)): + param_type = self.param_type_by_name[name][param_index] + if param_type == ParamType.UNSET: param_data["unset"] += 1 - elif value_count == 1: + elif param_type == ParamType.USELESS: param_data["useless"] += 1 - elif value_count == 2: + elif param_type == ParamType.BOOLEAN: param_data["boolean"] += 1 - elif all(map(lambda x: x is None or is_numeric(x), param_values)): + elif param_type == ParamType.SCALAR: param_data["scalar"] += 1 - else: + elif param_type == ParamType.ENUM: param_data["enum"] += 1 + else: + raise RuntimeError(f"Unknown param_type: {param_type}") ret[f"paramcount/{name}/useful"] = ( param_data["boolean"] + param_data["scalar"] + param_data["enum"] ) @@ -663,10 +664,14 @@ class PTAModel(AnalyticModel): self.ignore_trace_indexes = ignore_trace_indexes self.distinct_param_values_by_name = dict() + self.param_type_by_name = dict() for name in self.names: self.distinct_param_values_by_name[name] = distinct_param_values( by_name[name]["param"] ) + self.param_type_by_name[name] = ParamType( + self.distinct_param_values_by_name[name], values_are_distinct=True + ) self.fit_done = False |