diff options
Diffstat (limited to 'lib/model.py')
| -rw-r--r-- | lib/model.py | 88 |
1 files changed, 74 insertions, 14 deletions
diff --git a/lib/model.py b/lib/model.py index 58f05a4..4d1edd5 100644 --- a/lib/model.py +++ b/lib/model.py @@ -14,7 +14,14 @@ from .parameters import ( distinct_param_values, ) from .paramfit import ParamFit -from .utils import is_numeric, soft_cast_int, by_name_to_by_param, regression_measures +from .utils import ( + is_numeric, + soft_cast_int, + by_name_to_by_param, + by_param_to_by_name, + regression_measures, + param_eq_or_none, +) logger = logging.getLogger(__name__) @@ -79,6 +86,7 @@ class AnalyticModel: compute_stats=True, force_tree=False, max_std=None, + by_param=None, from_json=None, ): """ @@ -96,7 +104,7 @@ class AnalyticModel: - attributes: list of keys that should be analyzed, e.g. ['power', 'duration'] - for each attribute mentioned in 'attributes': A list with measurements. - All list except for 'attributes' must have the same length. + All lists except for 'attributes' must have the same length. For example: parameters = ['foo_count', 'irrelevant'] @@ -148,9 +156,18 @@ class AnalyticModel: for name, name_data in from_json["name"].items(): self.attr_by_name[name] = dict() for attr, attr_data in name_data.items(): - self.attr_by_name[name][attr] = ModelAttribute.from_json( - name, attr, attr_data - ) + if by_param: + self.attr_by_name[name][attr] = ModelAttribute.from_json( + name, + attr, + attr_data, + data_values=by_name[name][attr], + param_values=by_name[name]["param"], + ) + else: + self.attr_by_name[name][attr] = ModelAttribute.from_json( + name, attr, attr_data + ) self.fit_done = True return @@ -249,7 +266,7 @@ class AnalyticModel: return static_model_getter - def get_param_lut(self, use_mean=False, fallback=False): + def get_param_lut(self, use_mean=False, fallback=False, allow_none=False): """ Get parameter-look-up-table model function: name, attribute, parameter values -> model value. @@ -279,7 +296,16 @@ class AnalyticModel: try: return lut_model[name][key][param] except KeyError: - if fallback: + if allow_none: + keys = filter( + lambda p: param_eq_or_none(param, p), + lut_model[name][key].keys(), + ) + values = list(map(lambda p: lut_model[name][key][p], keys)) + if not values: + raise + return np.mean(values) + elif fallback: return static_model[name][key] raise params = kwargs["params"] @@ -643,7 +669,14 @@ class AnalyticModel: ret[f"xv/{name}/{attr_name}/{k}"] = np.mean(entry[k]) return ret - def to_json(self, **kwargs) -> dict: + def to_json( + self, + with_by_param=False, + lut_error=None, + static_error=None, + model_error=None, + **kwargs, + ) -> dict: """ Return JSON encoding of this AnalyticModel. """ @@ -653,21 +686,48 @@ class AnalyticModel: "paramValuesbyName": dict([[name, dict()] for name in self.names]), } + if with_by_param: + by_param = self.get_by_param() + ret["byParam"] = list() + for k, v in by_param.items(): + ret["byParam"].append((k, v)) + for name in self.names: for attr_name, attr in self.attr_by_name[name].items(): ret["name"][name][attr_name] = attr.to_json(**kwargs) + if lut_error: + ret["name"][name][attr_name]["lutError"] = lut_error[name][ + attr_name + ] + if static_error: + ret["name"][name][attr_name]["staticError"] = static_error[name][ + attr_name + ] + if model_error: + ret["name"][name][attr_name]["modelError"] = model_error[name][ + attr_name + ] attr_name = list(self.attributes(name))[0] for param_name in self.parameters: - ret["paramValuesbyName"][name][param_name] = self.attr_by_name[name][ - attr_name - ].stats.distinct_values_by_param_name[param_name] + if self.attr_by_name[name][attr_name].stats is not None: + ret["paramValuesbyName"][name][param_name] = self.attr_by_name[ + name + ][attr_name].stats.distinct_values_by_param_name[param_name] return ret @classmethod - def from_json(cls, data, by_name, parameters): - assert data["parameters"] == parameters - return cls(by_name, parameters, from_json=data) + def from_json(cls, data, by_name=None, parameters=None): + if by_name is None and parameters is None: + assert data["byParam"] is not None + by_param = dict() + for (nk, pk), v in data["byParam"]: + by_param[(nk, tuple(pk))] = v + by_name = by_param_to_by_name(by_param) + return cls(by_name, data["parameters"], by_param=by_param, from_json=data) + else: + assert data["parameters"] == parameters + return cls(by_name, parameters, from_json=data) def webconf_function_map(self) -> list: ret = list() |