Copybara-Service
3ec09f7296
PiperOrigin-RevId: 868229512 Change-Id: I790bc08fc8b0745583a2f92d9ee2c5a19ba558ea
114 lines
3.3 KiB
Python
114 lines
3.3 KiB
Python
# Copyright 2026 DeepMind Technologies Limited
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ==============================================================================
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"""Automated insights report section."""
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from typing import Any
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from mujoco.sysid._src import parameter
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from mujoco.sysid.report.sections.base import ReportSection
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class AutomatedInsights(ReportSection):
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"""Analyzes identification results and generates automated insights/suggestions.
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Currently checks for parameters stuck at boundaries.
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"""
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def __init__(
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self,
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title: str,
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parameter_dict: parameter.ParameterDict,
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anchor: str = "insights",
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collapsible: bool = True,
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):
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# Default to collapsed
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super().__init__(collapsible=collapsible, is_open=False)
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self._anchor = anchor
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self._parameter_dict = parameter_dict
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self._x_hat = parameter_dict.as_vector()
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self._insights = self._generate_insights()
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self._n_warnings = len(
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[i for i in self._insights if i["type"] == "warning"]
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)
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self._title = f"Log - {self._n_warnings} warnings"
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def _generate_insights(self) -> list[dict[str, Any]]:
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insights = []
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# Logic: Check for boundary hits
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param_names = self._parameter_dict.get_non_frozen_parameter_names()
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bounds = self._parameter_dict.get_bounds()
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lower_bounds, upper_bounds = bounds
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if len(self._x_hat) != len(param_names):
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raise ValueError("Parameter count mismatch")
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for i, name in enumerate(param_names):
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val = self._x_hat[i]
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lb = lower_bounds[i]
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ub = upper_bounds[i]
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rng = max(ub - lb, 1e-9)
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# Threshold: 0.1% of range or 1e-6 absolute
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threshold = rng * 1e-3
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if threshold < 1e-8:
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threshold = 1e-8
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if abs(val - lb) < threshold:
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insights.append({
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"type": "warning",
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"title": "Lower Bound Hit",
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"message": (
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f"Parameter <b>{name}</b> ({val:.4g}) is at its lower bound"
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f" ({lb:.4g})."
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),
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})
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elif abs(val - ub) < threshold:
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insights.append({
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"type": "warning",
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"title": "Upper Bound Hit",
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"message": (
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f"Parameter <b>{name}</b> ({val:.4g}) is at its upper bound"
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f" ({ub:.4g})."
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),
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})
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if not insights:
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insights.append({
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"type": "success",
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"title": "No Issues Detected",
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"message": "All parameters are within their bounds.",
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})
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return insights
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@property
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def template_filename(self) -> str:
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return "insights.html"
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@property
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def title(self) -> str:
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return self._title
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@property
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def anchor(self) -> str:
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return self._anchor
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def get_context(self) -> dict[str, Any]:
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return {"title": self._title, "insights": self._insights}
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