Datasets:

kaupane
/

AstroAgentBench

+MIT License
+Copyright (c) 2026 [OpenMOSS-Team]
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md CHANGED Viewed

@@ -1,585 +1,40 @@
 ---
-license: mit
 language:
-- en
 tags:
-- aerospace
-- satellite-scheduling
-- operations-research
-- constraint-optimization
-- astrodynamics
-- benchmark
-configs:
-- config_name: aeossp_standard
-  data_files:
-  - split: test
-    path: aeossp_standard/test-*
-  - split: test_horizon_2022
-    path: aeossp_standard/test_horizon_2022-*
-  - split: test_easy
-    path: aeossp_standard/test_easy-*
-  - split: test_hard
-    path: aeossp_standard/test_hard-*
-  - split: train
-    path: aeossp_standard/train-*
-- config_name: regional_coverage
-  data_files:
-  - split: test
-    path: regional_coverage/test-*
-  - split: train
-    path: regional_coverage/train-*
-- config_name: relay_constellation
-  data_files:
-  - split: test
-    path: relay_constellation/test-*
-  - split: train
-    path: relay_constellation/train-*
-- config_name: revisit_constellation
-  data_files:
-  - split: test
-    path: revisit_constellation/test-*
-  - split: train
-    path: revisit_constellation/train-*
-- config_name: satnet
-  data_files:
-  - split: test
-    path: satnet/test-*
-- config_name: spot5
-  data_files:
-  - split: single_orbit
-    path: spot5/single_orbit-*
-  - split: multi_orbit
-    path: spot5/multi_orbit-*
-  - split: test
-    path: spot5/test-*
-  - split: train
-    path: spot5/train-*
-- config_name: stereo_imaging
-  data_files:
-  - split: test
-    path: stereo_imaging/test-*
-  - split: train
-    path: stereo_imaging/train-*
-dataset_info:
-- config_name: aeossp_standard
-  features:
-  - name: case_id
-    dtype: string
-  - name: split
-    dtype: string
-  - name: benchmark
-    dtype: string
-  - name: index_metadata
-    struct:
-    - name: case_id
-      dtype: string
-    - name: case_seed
-      dtype: int64
-    - name: celestrak_snapshot_epoch_utc
-      dtype: string
-    - name: horizon_hours
-      dtype: int64
-    - name: norad_catalog_ids
-      list: int64
-    - name: num_satellites
-      dtype: int64
-    - name: num_tasks
-      dtype: int64
-    - name: path
-      dtype: string
-    - name: satellite_sensor_mix
-      struct:
-      - name: infrared
-        dtype: int64
-      - name: visible
-        dtype: int64
-    - name: split
-      dtype: string
-    - name: task_sensor_mix
-      struct:
-      - name: infrared
-        dtype: int64
-      - name: visible
-        dtype: int64
-    - name: task_source_mix
-      struct:
-      - name: background
-        dtype: int64
-      - name: city
-        dtype: int64
-    - name: task_weight_summary
-      struct:
-      - name: max
-        dtype: float64
-      - name: mean
-        dtype: float64
-      - name: min
-        dtype: float64
-  - name: files
-    list:
-    - name: content
-      dtype: string
-    - name: path
-      dtype: string
-  splits:
-  - name: test
-    num_bytes: 2489505
-    num_examples: 5
-  - name: test_horizon_2022
-    num_bytes: 2489544
-    num_examples: 5
-  - name: test_easy
-    num_bytes: 1880560
-    num_examples: 5
-  - name: test_hard
-    num_bytes: 5035798
-    num_examples: 5
-  - name: train
-    num_bytes: 4807565
-    num_examples: 10
-  download_size: 16761038
-  dataset_size: 16702972
-- config_name: regional_coverage
-  features:
-  - name: case_id
-    dtype: string
-  - name: split
-    dtype: string
-  - name: benchmark
-    dtype: string
-  - name: index_metadata
-    struct:
-    - name: case_id
-      dtype: string
-    - name: horizon_hours
-      dtype: int64
-    - name: num_regions
-      dtype: int64
-    - name: num_satellites
-      dtype: int64
-    - name: path
-      dtype: string
-    - name: satellite_class_ids
-      list: string
-    - name: split
-      dtype: string
-    - name: total_region_area_m2
-      dtype: float64
-  - name: files
-    list:
-    - name: content
-      dtype: string
-    - name: path
-      dtype: string
-  splits:
-  - name: test
-    num_bytes: 15300881
-    num_examples: 5
-  - name: train
-    num_bytes: 26353791
-    num_examples: 10
-  download_size: 41667686
-  dataset_size: 41654672
-- config_name: relay_constellation
-  features:
-  - name: case_id
-    dtype: string
-  - name: split
-    dtype: string
-  - name: benchmark
-    dtype: string
-  - name: index_metadata
-    struct:
-    - name: case_id
-      dtype: string
-    - name: horizon_hours
-      dtype: int64
-    - name: max_added_satellites
-      dtype: int64
-    - name: num_backbone_satellites
-      dtype: int64
-    - name: num_demanded_windows
-      dtype: int64
-    - name: num_endpoint_pairs
-      dtype: int64
-    - name: num_ground_endpoints
-      dtype: int64
-    - name: path
-      dtype: string
-    - name: split
-      dtype: string
-  - name: files
-    list:
-    - name: content
-      dtype: string
-    - name: path
-      dtype: string
-  splits:
-  - name: test
-    num_bytes: 27101
-    num_examples: 5
-  - name: train
-    num_bytes: 52637
-    num_examples: 10
-  download_size: 112608
-  dataset_size: 79738
-- config_name: revisit_constellation
-  features:
-  - name: case_id
-    dtype: string
-  - name: split
-    dtype: string
-  - name: benchmark
-    dtype: string
-  - name: index_metadata
-    struct:
-    - name: case_id
-      dtype: string
-    - name: max_num_satellites
-      dtype: int64
-    - name: path
-      dtype: string
-    - name: split
-      dtype: string
-    - name: target_count
-      dtype: int64
-    - name: uniform_revisit_threshold_hours
-      dtype: float64
-  - name: files
-    list:
-    - name: content
-      dtype: string
-    - name: path
-      dtype: string
-  splits:
-  - name: test
-    num_bytes: 48155
-    num_examples: 5
-  - name: train
-    num_bytes: 95297
-    num_examples: 10
-  download_size: 155101
-  dataset_size: 143452
-- config_name: satnet
-  features:
-  - name: case_id
-    dtype: string
-  - name: split
-    dtype: string
-  - name: benchmark
-    dtype: string
-  - name: index_metadata
-    struct:
-    - name: case_id
-      dtype: string
-    - name: maintenance_window_count
-      dtype: int64
-    - name: path
-      dtype: string
-    - name: request_count
-      dtype: int64
-    - name: split
-      dtype: string
-    - name: week
-      dtype: int64
-    - name: year
-      dtype: int64
-  - name: files
-    list:
-    - name: content
-      dtype: string
-    - name: path
-      dtype: string
-  splits:
-  - name: test
-    num_bytes: 3248419
-    num_examples: 5
-  download_size: 3254244
-  dataset_size: 3248419
-- config_name: spot5
-  features:
-  - name: case_id
-    dtype: string
-  - name: split
-    dtype: string
-  - name: benchmark
-    dtype: string
-  - name: index_metadata
-    struct:
-    - name: case_id
-      dtype: string
-    - name: instance_file
-      dtype: string
-    - name: is_multi_orbit
-      dtype: bool
-    - name: path
-      dtype: string
-    - name: split
-      dtype: string
-  - name: files
-    list:
-    - name: content
-      dtype: string
-    - name: path
-      dtype: string
-  splits:
-  - name: single_orbit
-    num_bytes: 934024
-    num_examples: 14
-  - name: multi_orbit
-    num_bytes: 1766774
-    num_examples: 7
-  - name: test
-    num_bytes: 1147997
-    num_examples: 5
-  - name: train
-    num_bytes: 742083
-    num_examples: 10
-  download_size: 4608851
-  dataset_size: 4590878
-- config_name: stereo_imaging
-  features:
-  - name: case_id
-    dtype: string
-  - name: split
-    dtype: string
-  - name: benchmark
-    dtype: string
-  - name: index_metadata
-    struct:
-    - name: case_id
-      dtype: string
-    - name: horizon_end
-      dtype: string
-    - name: horizon_start
-      dtype: string
-    - name: norad_catalog_ids
-      list: int64
-    - name: num_satellites
-      dtype: int64
-    - name: num_targets
-      dtype: int64
-    - name: path
-      dtype: string
-    - name: satellite_ids
-      list: string
-    - name: split
-      dtype: string
-  - name: files
-    list:
-    - name: content
-      dtype: string
-    - name: path
-      dtype: string
-  splits:
-  - name: test
-    num_bytes: 138614
-    num_examples: 5
-  - name: train
-    num_bytes: 285950
-    num_examples: 10
-  download_size: 439361
-  dataset_size: 424564
 ---
-# AstroAgentBench Datasets
-This is the canonical Hugging Face Dataset repository for **AstroAgentBench**, a benchmark suite for evaluating AI agents and algorithms on space mission design and planning problems.
-Each benchmark is exposed as a separate **config** (subset) within this dataset. Splits within a config map transparently to the benchmark's own dataset splits (e.g., `test`, `single_orbit`, `multi_orbit`).
-## Dataset Summary
-| Config | Cases | Splits | Domain |
-|---|---|---|---|
-| `aeossp_standard` | 30 | `test`, `test_easy`, `test_hard`, `test_horizon_2022`, `train` | Agile Earth-observation satellite scheduling |
-| `regional_coverage` | 15 | `test`, `train` | SAR-like regional strip-observation planning |
-| `relay_constellation` | 15 | `test`, `train` | Relay satellite constellation augmentation |
-| `revisit_constellation` | 15 | `test`, `train` | Constellation design for uniform target revisit |
-| `satnet` | 5 | `test` | Deep Space Network (DSN) antenna scheduling |
-| `spot5` | 31 | `single_orbit`, `multi_orbit`, `test`, `train` | SPOT-5 daily photograph scheduling (DCKP) |
-| `stereo_imaging` | 15 | `test`, `train` | Optical stereo/tri-stereo imaging planning |
-## Dataset Structure
-Every example in every config follows the same schema:
-```json
-{
-  "case_id": "case_0001",
-  "split": "test",
-  "benchmark": "aeossp_standard",
-  "index_metadata": { ... case-specific metadata from index.json ... },
-  "files": [
-    {"path": "mission.yaml", "content": "..."},
-    {"path": "satellites.yaml", "content": "..."},
-    {"path": "tasks.yaml", "content": "..."}
-  ]
-}
-```
-- **`case_id`**: Unique identifier for the case within the benchmark.
-- **`split`**: The dataset split the case belongs to.
-- **`benchmark`**: The benchmark name.
-- **`index_metadata`**: The case-level entry from the benchmark's `dataset/index.json` (e.g., satellite counts, task counts, horizons, thresholds, provenance).
-- **`files`**: A list of all text files inside the case directory. Each entry has a `path` (relative to the case directory) and the full UTF-8 `content`.
-> **Note**: Because different cases contain different filenames, `files` is stored as a uniform list of objects rather than a dictionary with dynamic keys. This ensures consistent features across splits.
-## Quickstart
-### Loading a single benchmark
-```python
-from datasets import load_dataset
-# Load the aeossp_standard benchmark
-ds = load_dataset("kaupane/AstroAgentBench", "aeossp_standard")
-print(ds["test"][0]["case_id"])
-```
-### Loading a specific case's files
-```python
-case = ds["test"][0]
-for file in case["files"]:
-    print(file["path"])
-    # file["content"] contains the full text of the file
-```
-### Iterating all configs
-```python
-from datasets import get_dataset_config_names
-configs = get_dataset_config_names("kaupane/AstroAgentBench")
-for config in configs:
-    ds = load_dataset("kaupane/AstroAgentBench", config)
-    for split_name, split_ds in ds.items():
-        print(f"{config}/{split_name}: {len(split_ds)} cases")
 ```
-## Benchmark Descriptions
-### `aeossp_standard`
-A planning-oriented agile Earth-observation satellite scheduling benchmark. Each case provides a fixed constellation of real satellites (via frozen TLEs), time-windowed point-imaging tasks, and hard constraints on observation geometry, battery state, and slew feasibility. The solver submits a schedule of `observation` actions. Metrics include completion ratio (`CR`), weighted completion ratio (`WCR`), time-averaged tardiness (`TAT`), and power consumption (`PC`).
-**Case files**: `mission.yaml`, `satellites.yaml`, `tasks.yaml`
-### `regional_coverage`
-A SAR-like regional imaging benchmark. The solver must plan strip observations over polygonal regions of interest to maximize unique weighted coverage. Cases include real satellites with frozen TLEs, GeoJSON region definitions, and a benchmark-owned fine-grid scoring model. Hard constraints include roll-only strip geometry, same-satellite retargeting limits, battery feasibility, and optional per-region minimum coverage thresholds.
-**Case files**: `manifest.json`, `satellites.yaml`, `regions.geojson`, `coverage_grid.json`
-### `relay_constellation`
-A partial constellation-design benchmark for relay service augmentation. Given an immutable MEO relay backbone and ground endpoints, the solver adds a bounded number of lower-altitude relay satellites and schedules ground-link and inter-satellite-link actions. The verifier scores service fraction, latency percentiles, and the number of added satellites.
-**Case files**: `manifest.json`, `network.json`, `demands.json`
-### `revisit_constellation`
-A constellation-design and scheduling benchmark focused on revisit performance. The solver designs a satellite constellation (initial GCRF Cartesian states up to a case cap) and schedules `observation` actions to keep target revisit gaps as small as possible over a 48-hour horizon. Scoring is driven by `mean_revisit_gap_hours`, `max_revisit_gap_hours`, and `satellite_count`.
-**Case files**: `assets.json`, `mission.json`
-### `satnet`
-A reinforcement-learning benchmark derived from NASA/JPL Deep Space Network (DSN) operations. The task is to schedule ground-station antenna tracks for interplanetary spacecraft over one-week windows, respecting precomputed view periods, setup/teardown times, maintenance windows, and non-overlap constraints. The primary metrics are the mission-level unsatisfied-demand fairness metrics `U_rms` and `U_max`, with satisfied request count and total communication hours used as secondary service-volume indicators.
-**Case files**: `problem.json`, `maintenance.csv`, `metadata.json`
-### `spot5`
-A constraint optimization benchmark based on the ROADEF 2003 Challenge and CNES SPOT-5 operations. Cases are encoded in the DCKP (Disjunctively Constrained Knapsack Problem) format. The solver selects photographs and assigns cameras to maximize total profit while respecting binary/ternary disjunctive constraints and an onboard memory capacity constraint (for multi-orbit instances).
-**Case files**: `<case_id>.spot`
-### `stereo_imaging`
-An optical satellite stereo imaging benchmark. The solver schedules timed observations from real satellites to acquire same-pass stereo or tri-stereo products over ground targets. The verifier scores `coverage_ratio` (fraction of targets with a valid stereo product) and `normalized_quality` (mean best-per-target quality based on convergence angle, overlap, and pixel scale).
-**Case files**: `satellites.yaml`, `targets.yaml`, `mission.yaml`
-## Data Splits and Splits Policy
-- `aeossp_standard`, `regional_coverage`, `relay_constellation`, `revisit_constellation`, and `stereo_imaging`: expose benchmark-owned `train` splits for learning workflows and separate `test`-family splits for held-out evaluation.
-- `satnet`: exposes only the five published 2018 `test` cases; no `train` split is committed.
-- `spot5`: Exposes four splits:
-  - `single_orbit`: 14 cases without memory constraints.
-  - `multi_orbit`: 7 cases with a memory capacity of 200.
-  - `test`: A 5-case sample drawn with seed 42 (overlaps with `single_orbit` and `multi_orbit`).
-  - `train`: A 10-case sample drawn with seed 163 (overlaps with the full family splits).
-Future benchmark releases may add additional splits (e.g., `val`) transparently without changing the schema.
-## Dataset Creation
-All canonical datasets are generated or curated by the AstroAgentBench repository. Where generators exist, they are deterministic and tied to committed `splits.yaml` contracts. Canonical cases are committed to the repository and are the source of truth for evaluation.
-## Source Data
-| Config | Primary Sources |
-|---|---|
-| `aeossp_standard` | CelesTrak TLE snapshot; GeoNames cities; Natural Earth land polygons |
-| `regional_coverage` | CelesTrak TLE snapshot; GeoNames; Natural Earth |
-| `relay_constellation` | Synthetic case generator with deterministic seeds |
-| `revisit_constellation` | Kaggle world-cities dataset; CelesTrak TLE snapshot |
-| `satnet` | Derived from NASA/JPL Deep Space Network operations research (Chien et al., 2021) |
-| `spot5` | Mendeley Data DCKP abstraction (Wei & Hao, 2021) of CNES SPOT-5 ROADEF 2003 instances |
-| `stereo_imaging` | Kaggle world-cities; CelesTrak TLE snapshot |
-## Considerations for Using the Data
-- **Algorithm-agnostic**: Benchmarks define problems and verification, not preferred solving strategies.
-- **Standalone**: Each config is self-contained with no runtime dependencies on other configs.
-- **No solutions included**: This dataset contains only problem instances (cases). Solutions, baselines, and leaderboards belong in downstream repositories.
-- **Binary files skipped**: The upload script ingests only text-based case files. Any future binary artifacts would be excluded from this HF release.
-## Licensing Information
-This dataset repository aggregates multiple sources with different provenance:
-- **`spot5`**: The `.spot` instances are from the Mendeley Data release (DOI: 10.17632/2kbzg9nw3b.1) and are provided under **CC BY 4.0**.
-- **`satnet`**: Derived from NASA/JPL Deep Space Network operations research. Used for research and educational purposes.
-- **All other benchmarks** (`aeossp_standard`, `regional_coverage`, `relay_constellation`, `revisit_constellation`, `stereo_imaging`): Original benchmark materials created by the AstroAgentBench project.
-Please cite the appropriate references when using individual benchmarks (see Citation Information).
-## Citation Information
-If you use this dataset suite in your research, please cite the AstroAgentBench paper and the original benchmark sources:
-### Original preprint
-```bibtex
-@article{wang2026astroreason,
-  title={AstroReason-Bench: Evaluating Unified Agentic Planning across Heterogeneous Space Planning Problems},
-  author={Wang, Weiyi and Chen, Xinchi and Gong, Jingjing and Huang, Xuanjing and Qiu, Xipeng},
-  journal={arXiv preprint arXiv:2601.11354},
-  year={2026}
-}
-```
-### SatNet
-```bibtex
-@inproceedings{goh2021satnet,
-  title={SatNet: A benchmark for satellite scheduling optimization},
-  author={Goh, Edwin and Venkataram, Hamsa Shwetha and Balaji, Bharathan and Wilson, Brian D and Johnston, Mark D},
-  booktitle={AAAI-22 workshop on Machine Learning for Operations Research (ML4OR)},
-  year={2021}
-}
-```
-### SPOT-5 / DCKP
-```bibtex
-@article{wei2023responsive,
-  title={Responsive strategic oscillation for solving the disjunctively constrained knapsack problem},
-  author={Wei, Zequn and Hao, Jin-Kao and Ren, Jintong and Glover, Fred},
-  journal={European Journal of Operational Research},
-  volume={309},
-  number={3},
-  pages={993--1009},
-  year={2023},
-  publisher={Elsevier}
-}
-```
-## Contact and Links
-- **Repository**: https://github.com/Mtrya/AstroAgentBench
-- **Issue Tracker**: https://github.com/Mtrya/AstroAgentBench/issues

 ---
+license: other
+license_name: mixed-source-licenses
+license_link: https://huggingface.co/datasets/kaupane/AstroAgentBench/blob/v2.0.0/README.md#licensing-and-attribution
 language:
+  - en
 tags:
+  - rl-environment
+  - harbor
+  - aerospace
+  - satellite-scheduling
+  - astrodynamics
+  - benchmark
 ---
+# AstroAgentBench
+Harbor tasks for evaluating complete agent systems on space mission design. [GitHub](https://github.com/Mtrya/AstroAgentBench/tree/6f5b9d21b1efb2ca2ee6fcabdc338a9d077612cb) is the canonical source for benchmark definitions, generators, and source inputs. This release is `v2.0.0`, generated from Git commit `6f5b9d21b1efb2ca2ee6fcabdc338a9d077612cb`.
+## Run a taskset
+Install Harbor 0.23.0 with Python 3.13 and have Docker available. Run the seven reference checks, one per benchmark family:
+```bash
+harbor run --repo https://huggingface.co/datasets/kaupane/AstroAgentBench@v2.0.0 --dataset smoke@v2.0.0 --agent oracle -n 1 --jobs-dir results --job-name astroagentbench-smoke
 ```
+`registry.json` lists one dataset per benchmark and split, such as `regional_coverage-test@v2.0.0` and `spot5-single_orbit@v2.0.0`. Select one with `--dataset` and supply your Harbor agent adapter and model. Only the seven tasks in `smoke` include oracle solutions. Native scores have benchmark-specific units and directions; do not combine scores across families.
+## Contents and resources
+Each directory under `tasks/` contains a task brief, case inputs, environment Dockerfile, and independent verifier. The solving and verifier images share a public runtime pinned by digest. Tasks default to 8 CPUs, 16384 MiB memory, 7200 seconds of agent execution, 600 seconds of verification, public network access, and 10240 MiB requested storage. Docker does not enforce the requested storage as a disk quota. Harbor resource overrides are recorded with each run.
+`release-manifest.json` records the Git source, runtime image, byte sizes, and SHA-256 checksums. Dataset versions match the GitHub release tags. Releases from `v2.0.0` use this taskset layout; historical tags retain their original contents. The complete raw source tree remains on GitHub.
+## Licensing and attribution
+This release combines project code under the root [MIT license](LICENSE) with third-party inputs under their own terms. The MIT license does not replace those source licenses. See the [benchmark READMEs and source manifests at the release commit](https://github.com/Mtrya/AstroAgentBench/tree/6f5b9d21b1efb2ca2ee6fcabdc338a9d077612cb/benchmarks) for provenance.
+The SPOT5 `.spot` inputs are distributed under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/), from Zequn Wei and Jin-Kao Hao's [Mendeley Data release, version 1 (2021), DOI 10.17632/2kbzg9nw3b.1](https://data.mendeley.com/datasets/2kbzg9nw3b/1). The bundled source files are unchanged; benchmark case files are derived from them. Retain this attribution and indicate any further modifications when redistributing those data.

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+        "path": "tasks/regional_coverage-test-case_0001"
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+    "tasks": [
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+        "path": "tasks/relay_constellation-test-case_0001"
+      },
+      {
+        "name": "relay_constellation-test-case_0002",
+        "path": "tasks/relay_constellation-test-case_0002"
+      },
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+      },
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+        "path": "tasks/relay_constellation-test-case_0004"
+      },
+      {
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+        "path": "tasks/relay_constellation-test-case_0005"
+      }
+    ]
+  },
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+    "tasks": [
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+        "path": "tasks/relay_constellation-train-case_0001"
+      },
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+        "path": "tasks/revisit_constellation-test-case_0001"
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+        "path": "tasks/revisit_constellation-test-case_0005"
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+        "path": "tasks/revisit_constellation-train-case_0001"
+      },
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+        "path": "tasks/revisit_constellation-train-case_0010"
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+    "description": "AstroAgentBench satnet-test",
+    "tasks": [
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+        "name": "satnet-test-W10_2018",
+        "path": "tasks/satnet-test-W10_2018"
+      },
+      {
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+        "path": "tasks/satnet-test-W20_2018"
+      },
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+        "path": "tasks/satnet-test-W30_2018"
+      },
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+        "path": "tasks/satnet-test-W40_2018"
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+        "path": "tasks/spot5-multi_orbit-1021"
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+        "path": "tasks/spot5-single_orbit-5"
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+        "path": "tasks/stereo_imaging-test-case_0001"
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+        "name": "stereo_imaging-train-case_0006",
+        "path": "tasks/stereo_imaging-train-case_0006"
+      },
+      {
+        "name": "stereo_imaging-train-case_0007",
+        "path": "tasks/stereo_imaging-train-case_0007"
+      },
+      {
+        "name": "stereo_imaging-train-case_0008",
+        "path": "tasks/stereo_imaging-train-case_0008"
+      },
+      {
+        "name": "stereo_imaging-train-case_0009",
+        "path": "tasks/stereo_imaging-train-case_0009"
+      },
+      {
+        "name": "stereo_imaging-train-case_0010",
+        "path": "tasks/stereo_imaging-train-case_0010"
+      }
+    ]
+  },
+  {
+    "name": "smoke",
+    "version": "v2.0.0",
+    "description": "One oracle integration check per benchmark family",
+    "tasks": [
+      {
+        "name": "revisit_constellation-test-case_0001",
+        "path": "tasks/revisit_constellation-test-case_0001"
+      },
+      {
+        "name": "satnet-test-W10_2018",
+        "path": "tasks/satnet-test-W10_2018"
+      },
+      {
+        "name": "spot5-single_orbit-8",
+        "path": "tasks/spot5-single_orbit-8"
+      },
+      {
+        "name": "stereo_imaging-test-case_0001",
+        "path": "tasks/stereo_imaging-test-case_0001"
+      },
+      {
+        "name": "regional_coverage-test-case_0001",
+        "path": "tasks/regional_coverage-test-case_0001"
+      },
+      {
+        "name": "relay_constellation-test-case_0005",
+        "path": "tasks/relay_constellation-test-case_0005"
+      },
+      {
+        "name": "aeossp_standard-test-case_0001",
+        "path": "tasks/aeossp_standard-test-case_0001"
+      }
+    ]
+  }
+]

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tasks/aeossp_standard-test-case_0001/environment/Dockerfile ADDED Viewed

	@@ -0,0 +1,4 @@

+FROM ghcr.io/mtrya/astroagentbench-python@sha256:fe9733cad55519aa08dd0db9abb51444051ef5f53d6ac1ef0b4b6592491437d1
+WORKDIR /workspace
+COPY case /workspace/case
+RUN mkdir -p /workspace/solution

tasks/aeossp_standard-test-case_0001/environment/case/mission.yaml ADDED Viewed

	@@ -0,0 +1,24 @@

+mission:
+  case_id: case_0001
+  horizon_start: '2026-04-14T04:00:00Z'
+  horizon_end: '2026-04-14T16:00:00Z'
+  action_time_step_s: 5
+  geometry_sample_step_s: 5
+  resource_sample_step_s: 10
+  propagation:
+    model: sgp4
+    frame_inertial: gcrf
+    frame_fixed: itrf
+    earth_shape: wgs84
+  scoring:
+    ranking_order:
+    - valid
+    - WCR
+    - CR
+    - TAT
+    - PC
+    reported_metrics:
+    - CR
+    - WCR
+    - TAT
+    - PC

tasks/aeossp_standard-test-case_0001/environment/case/satellites.yaml ADDED Viewed

	@@ -0,0 +1,361 @@

+satellites:
+- satellite_id: sat_001
+  norad_catalog_id: 28051
+  tle_line1: 1 28051U 03046A   26103.92936350  .00000126  00000+0  55914-4 0  9994
+  tle_line2: 2 28051  98.1985 143.5711 0064246 173.9227 286.4737 14.36137850171300
+  sensor:
+    sensor_type: visible
+  attitude_model:
+    max_slew_velocity_deg_per_s: 1.8
+    max_slew_acceleration_deg_per_s2: 0.4
+    settling_time_s: 2.0
+    max_off_nadir_deg: 30.0
+  resource_model:
+    battery_capacity_wh: 1300.0
+    initial_battery_wh: 800.0
+    idle_power_w: 20.0
+    imaging_power_w: 420.0
+    slew_power_w: 360.0
+    sunlit_charge_power_w: 85.0
+- satellite_id: sat_002
+  norad_catalog_id: 32783
+  tle_line1: 1 32783U 08021A   26103.91837750  .00000562  00000+0  82530-4 0  9990
+  tle_line2: 2 32783  97.7709 154.8031 0010967 327.3165  32.7367 14.79161859969302
+  sensor:
+    sensor_type: visible
+  attitude_model:
+    max_slew_velocity_deg_per_s: 1.0
+    max_slew_acceleration_deg_per_s2: 0.25
+    settling_time_s: 3.0
+    max_off_nadir_deg: 25.0
+  resource_model:
+    battery_capacity_wh: 1600.0
+    initial_battery_wh: 1000.0
+    idle_power_w: 25.0
+    imaging_power_w: 480.0
+    slew_power_w: 280.0
+    sunlit_charge_power_w: 100.0
+- satellite_id: sat_003
+  norad_catalog_id: 33396
+  tle_line1: 1 33396U 08049A   26103.92431574  .00000228  00000+0  12693-3 0  9997
+  tle_line2: 2 33396  98.5635 163.2775 0001215  96.0005 264.1311 14.20124562908846
+  sensor:
+    sensor_type: visible
+  attitude_model:
+    max_slew_velocity_deg_per_s: 1.8
+    max_slew_acceleration_deg_per_s2: 0.4
+    settling_time_s: 2.0
+    max_off_nadir_deg: 30.0
+  resource_model:
+    battery_capacity_wh: 1300.0
+    initial_battery_wh: 800.0
+    idle_power_w: 20.0
+    imaging_power_w: 420.0
+    slew_power_w: 360.0
+    sunlit_charge_power_w: 85.0
+- satellite_id: sat_004
+  norad_catalog_id: 35681
+  tle_line1: 1 35681U 09041A   26103.88486025  .00000736  00000+0  11600-3 0  9996
+  tle_line2: 2 35681  97.7323 263.9278 0002534  65.1442 295.0031 14.75171584897400
+  sensor:
+    sensor_type: visible
+  attitude_model:
+    max_slew_velocity_deg_per_s: 1.0
+    max_slew_acceleration_deg_per_s2: 0.25
+    settling_time_s: 3.0
+    max_off_nadir_deg: 25.0
+  resource_model:
+    battery_capacity_wh: 1600.0
+    initial_battery_wh: 1000.0
+    idle_power_w: 25.0
+    imaging_power_w: 480.0
+    slew_power_w: 280.0
+    sunlit_charge_power_w: 100.0
+- satellite_id: sat_005
+  norad_catalog_id: 37387
+  tle_line1: 1 37387U 11015A   26103.89999973 -.00000252  00000+0 -94795-4 0  9999
+  tle_line2: 2 37387  98.7689 171.7738 0012401  84.9704 275.2889 14.21615505777047
+  sensor:
+    sensor_type: visible
+  attitude_model:
+    max_slew_velocity_deg_per_s: 1.0
+    max_slew_acceleration_deg_per_s2: 0.25
+    settling_time_s: 3.0
+    max_off_nadir_deg: 25.0
+  resource_model:
+    battery_capacity_wh: 1600.0
+    initial_battery_wh: 1000.0
+    idle_power_w: 25.0
+    imaging_power_w: 480.0
+    slew_power_w: 280.0
+    sunlit_charge_power_w: 100.0
+- satellite_id: sat_006
+  norad_catalog_id: 38012
+  tle_line1: 1 38012U 11076F   26103.92452051  .00000031  00000+0  16420-4 0  9999
+  tle_line2: 2 38012  98.1996 179.8836 0001241  74.0617  41.3226 14.58569444762624
+  sensor:
+    sensor_type: visible
+  attitude_model:
+    max_slew_velocity_deg_per_s: 1.0
+    max_slew_acceleration_deg_per_s2: 0.25
+    settling_time_s: 3.0
+    max_off_nadir_deg: 25.0
+  resource_model:
+    battery_capacity_wh: 1600.0
+    initial_battery_wh: 1000.0
+    idle_power_w: 25.0
+    imaging_power_w: 480.0
+    slew_power_w: 280.0
+    sunlit_charge_power_w: 100.0
+- satellite_id: sat_007
+  norad_catalog_id: 39019
+  tle_line1: 1 39019U 12068A   26103.93709536  .00000156  00000+0  43477-4 0  9993
+  tle_line2: 2 39019  98.1967 179.8664 0001151  77.9509 282.1820 14.58557094711482
+  sensor:
+    sensor_type: infrared
+  attitude_model:
+    max_slew_velocity_deg_per_s: 0.9
+    max_slew_acceleration_deg_per_s2: 0.15
+    settling_time_s: 3.5
+    max_off_nadir_deg: 20.0
+  resource_model:
+    battery_capacity_wh: 1800.0
+    initial_battery_wh: 1000.0
+    idle_power_w: 30.0
+    imaging_power_w: 680.0
+    slew_power_w: 320.0
+    sunlit_charge_power_w: 115.0
+- satellite_id: sat_008
+  norad_catalog_id: 39084
+  tle_line1: 1 39084U 13008A   26103.95632536  .00000202  00000+0  54735-4 0  9998
+  tle_line2: 2 39084  98.1863 175.0919 0001171  93.9204 266.2128 14.57117273688546
+  sensor:
+    sensor_type: visible
+  attitude_model:
+    max_slew_velocity_deg_per_s: 1.0
+    max_slew_acceleration_deg_per_s2: 0.25
+    settling_time_s: 3.0
+    max_off_nadir_deg: 25.0
+  resource_model:
+    battery_capacity_wh: 1600.0
+    initial_battery_wh: 1000.0
+    idle_power_w: 25.0
+    imaging_power_w: 480.0
+    slew_power_w: 280.0
+    sunlit_charge_power_w: 100.0
+- satellite_id: sat_009
+  norad_catalog_id: 40013
+  tle_line1: 1 40013U 14033D   26103.93736737  .00001307  00000+0  12918-3 0  9990
+  tle_line2: 2 40013  97.5922 340.6596 0001765 111.5119 248.6289 14.93547723628139
+  sensor:
+    sensor_type: visible
+  attitude_model:
+    max_slew_velocity_deg_per_s: 1.8
+    max_slew_acceleration_deg_per_s2: 0.4
+    settling_time_s: 2.0
+    max_off_nadir_deg: 30.0
+  resource_model:
+    battery_capacity_wh: 1300.0
+    initial_battery_wh: 800.0
+    idle_power_w: 20.0
+    imaging_power_w: 420.0
+    slew_power_w: 360.0
+    sunlit_charge_power_w: 85.0
+- satellite_id: sat_010
+  norad_catalog_id: 42063
+  tle_line1: 1 42063U 17013A   26103.94175150 -.00000047  00000+0 -13025-5 0  9999
+  tle_line2: 2 42063  98.5661 179.6296 0001235  93.6242 266.5083 14.30820285475457
+  sensor:
+    sensor_type: visible
+  attitude_model:
+    max_slew_velocity_deg_per_s: 1.0
+    max_slew_acceleration_deg_per_s2: 0.25
+    settling_time_s: 3.0
+    max_off_nadir_deg: 25.0
+  resource_model:
+    battery_capacity_wh: 1600.0
+    initial_battery_wh: 1000.0
+    idle_power_w: 25.0
+    imaging_power_w: 480.0
+    slew_power_w: 280.0
+    sunlit_charge_power_w: 100.0
+- satellite_id: sat_011
+  norad_catalog_id: 42988
+  tle_line1: 1 42988U 17068B   26103.65081329  .00006062  00000+0  18960-3 0  9999
+  tle_line2: 2 42988  97.4398 239.9634 0001252 115.0478 245.0894 15.33517382472468
+  sensor:
+    sensor_type: infrared
+  attitude_model:
+    max_slew_velocity_deg_per_s: 0.9
+    max_slew_acceleration_deg_per_s2: 0.15
+    settling_time_s: 3.5
+    max_off_nadir_deg: 20.0
+  resource_model:
+    battery_capacity_wh: 1800.0
+    initial_battery_wh: 1000.0
+    idle_power_w: 30.0
+    imaging_power_w: 680.0
+    slew_power_w: 320.0
+    sunlit_charge_power_w: 115.0
+- satellite_id: sat_012
+  norad_catalog_id: 42991
+  tle_line1: 1 42991U 17068E   26103.83844932  .00006341  00000+0  18525-3 0  9997
+  tle_line2: 2 42991  97.4427 240.6998 0005447 348.9947  11.1177 15.35651042472498
+  sensor:
+    sensor_type: visible
+  attitude_model:
+    max_slew_velocity_deg_per_s: 1.0
+    max_slew_acceleration_deg_per_s2: 0.25
+    settling_time_s: 3.0
+    max_off_nadir_deg: 25.0
+  resource_model:
+    battery_capacity_wh: 1600.0
+    initial_battery_wh: 1000.0
+    idle_power_w: 25.0
+    imaging_power_w: 480.0
+    slew_power_w: 280.0
+    sunlit_charge_power_w: 100.0
+- satellite_id: sat_013
+  norad_catalog_id: 43111
+  tle_line1: 1 43111U 18004A   26104.12260037  .00002784  00000+0  13508-3 0  9997
+  tle_line2: 2 43111  97.4095 164.6288 0002452 119.7879 240.3599 15.19306551457606
+  sensor:
+    sensor_type: visible
+  attitude_model:
+    max_slew_velocity_deg_per_s: 1.8
+    max_slew_acceleration_deg_per_s2: 0.4
+    settling_time_s: 2.0
+    max_off_nadir_deg: 30.0
+  resource_model:
+    battery_capacity_wh: 1300.0
+    initial_battery_wh: 800.0
+    idle_power_w: 20.0
+    imaging_power_w: 420.0
+    slew_power_w: 360.0
+    sunlit_charge_power_w: 85.0
+- satellite_id: sat_014
+  norad_catalog_id: 43259
+  tle_line1: 1 43259U 18031A   26104.11950488  .00000002  00000+0  76800-5 0  9992
+  tle_line2: 2 43259  98.0579 166.8090 0002685 187.3457 172.7713 14.76430187433244
+  sensor:
+    sensor_type: visible
+  attitude_model:
+    max_slew_velocity_deg_per_s: 1.0
+    max_slew_acceleration_deg_per_s2: 0.25
+    settling_time_s: 3.0
+    max_off_nadir_deg: 25.0
+  resource_model:
+    battery_capacity_wh: 1600.0
+    initial_battery_wh: 1000.0
+    idle_power_w: 25.0
+    imaging_power_w: 480.0
+    slew_power_w: 280.0
+    sunlit_charge_power_w: 100.0
+- satellite_id: sat_015
+  norad_catalog_id: 43260
+  tle_line1: 1 43260U 18031B   26104.16530807  .00000436  00000+0  70146-4 0  9995
+  tle_line2: 2 43260  98.0571 166.7195 0001054 283.4938  76.6154 14.76417197433241
+  sensor:
+    sensor_type: infrared
+  attitude_model:
+    max_slew_velocity_deg_per_s: 0.9
+    max_slew_acceleration_deg_per_s2: 0.15
+    settling_time_s: 3.5
+    max_off_nadir_deg: 20.0
+  resource_model:
+    battery_capacity_wh: 1800.0
+    initial_battery_wh: 1000.0
+    idle_power_w: 30.0
+    imaging_power_w: 680.0
+    slew_power_w: 320.0
+    sunlit_charge_power_w: 115.0
+- satellite_id: sat_016
+  norad_catalog_id: 43262
+  tle_line1: 1 43262U 18031D   26103.93793093  .00000573  00000+0  89849-4 0  9991
+  tle_line2: 2 43262  98.0583 166.6754 0000885  62.3940 297.7360 14.76451671433200
+  sensor:
+    sensor_type: visible
+  attitude_model:
+    max_slew_velocity_deg_per_s: 1.0
+    max_slew_acceleration_deg_per_s2: 0.25
+    settling_time_s: 3.0
+    max_off_nadir_deg: 25.0
+  resource_model:
+    battery_capacity_wh: 1600.0
+    initial_battery_wh: 1000.0
+    idle_power_w: 25.0
+    imaging_power_w: 480.0
+    slew_power_w: 280.0
+    sunlit_charge_power_w: 100.0
+- satellite_id: sat_017
+  norad_catalog_id: 48079
+  tle_line1: 1 48079U 21026A   26103.94185373  .00000257  00000+0  40677-4 0  9992
+  tle_line2: 2 48079  97.9928 102.3896 0006302  84.5923 275.6008 14.80244388272253
+  sensor:
+    sensor_type: infrared
+  attitude_model:
+    max_slew_velocity_deg_per_s: 0.9
+    max_slew_acceleration_deg_per_s2: 0.15
+    settling_time_s: 3.5
+    max_off_nadir_deg: 20.0
+  resource_model:
+    battery_capacity_wh: 1800.0
+    initial_battery_wh: 1000.0
+    idle_power_w: 30.0
+    imaging_power_w: 680.0
+    slew_power_w: 320.0
+    sunlit_charge_power_w: 115.0
+- satellite_id: sat_018
+  norad_catalog_id: 48268
+  tle_line1: 1 48268U 21034A   26103.96224166 -.00000034  00000+0  22549-5 0  9990
+  tle_line2: 2 48268  97.8933 179.6508 0001284  93.5777 266.5583 14.81672073268143
+  sensor:
+    sensor_type: visible
+  attitude_model:
+    max_slew_velocity_deg_per_s: 1.8
+    max_slew_acceleration_deg_per_s2: 0.4
+    settling_time_s: 2.0
+    max_off_nadir_deg: 30.0
+  resource_model:
+    battery_capacity_wh: 1300.0
+    initial_battery_wh: 800.0
+    idle_power_w: 20.0
+    imaging_power_w: 420.0
+    slew_power_w: 360.0
+    sunlit_charge_power_w: 85.0
+- satellite_id: sat_019
+  norad_catalog_id: 52912
+  tle_line1: 1 52912U 22069A   26103.95907240  .00000113  00000+0  21656-4 0  9994
+  tle_line2: 2 52912  97.8359 353.4264 0001854  52.2815 307.8565 14.79930234205115
+  sensor:
+    sensor_type: visible
+  attitude_model:
+    max_slew_velocity_deg_per_s: 1.8
+    max_slew_acceleration_deg_per_s2: 0.4
+    settling_time_s: 2.0
+    max_off_nadir_deg: 30.0
+  resource_model:
+    battery_capacity_wh: 1300.0
+    initial_battery_wh: 800.0
+    idle_power_w: 20.0
+    imaging_power_w: 420.0
+    slew_power_w: 360.0
+    sunlit_charge_power_w: 85.0
+- satellite_id: sat_020
+  norad_catalog_id: 60989
+  tle_line1: 1 60989U 24157A   26103.90679551  .00000060  00000+0  39456-4 0  9991
+  tle_line2: 2 60989  98.5642 179.6103 0001350 108.6675 251.4655 14.30813258 83797
+  sensor:
+    sensor_type: visible
+  attitude_model:
+    max_slew_velocity_deg_per_s: 1.0
+    max_slew_acceleration_deg_per_s2: 0.25
+    settling_time_s: 3.0
+    max_off_nadir_deg: 25.0
+  resource_model:
+    battery_capacity_wh: 1600.0
+    initial_battery_wh: 1000.0
+    idle_power_w: 25.0
+    imaging_power_w: 480.0
+    slew_power_w: 280.0
+    sunlit_charge_power_w: 100.0

tasks/aeossp_standard-test-case_0001/environment/case/tasks.yaml ADDED Viewed

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tasks/aeossp_standard-test-case_0001/instruction.md ADDED Viewed

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+# Agile Earth Observation Scheduling Problem
+This workspace contains one agile Earth-observation scheduling problem over a fixed mission horizon.
+You are given:
+- a mission description in `case/mission.yaml`
+- a fixed constellation with frozen orbital elements and subsystem limits in `case/satellites.yaml`
+- a set of time-windowed imaging tasks in `case/tasks.yaml`
+Your job is to produce `/workspace/solution/solution.json`, an event schedule of `observation` actions that completes as many high-value tasks as possible without violating hard timing, geometry, slew, or battery constraints.
+This problem is modeled as point-imaging scheduling on a fixed fleet. You are choosing when each satellite should spend a continuous interval observing a target, not redesigning the satellites, not changing their orbits, and not submitting low-level attitude trajectories. An action in the solution means "this satellite continuously observes this target over this interval," and the geometry, maneuver windows, and battery evolution are derived from that commitment during validation.
+## What Good Solutions Do
+A strong solution should:
+- satisfy all hard validity rules
+- complete as many high-weight tasks as possible
+- also improve overall completion rate when possible
+- avoid unnecessary lateness and wasteful power use when tie-breaking matters
+In practical terms, valid task completion matters first, especially on higher-weight tasks.
+## Files In This Workspace
+- `case/mission.yaml`: mission horizon, public time grids, and reported metric metadata
+- `case/satellites.yaml`: fixed satellites, TLEs, sensor limits, slew limits, and battery/power parameters
+- `case/tasks.yaml`: imaging requests with time windows, durations, sensor requirements, and weights
+## Expected Output
+Write one JSON object named `/workspace/solution/solution.json` in the solution directory.
+The required top-level field is:
+- `actions`
+Each action should represent one observation interval with:
+- `type`
+- `satellite_id`
+- `task_id`
+- `start_time`
+- `end_time`
+Do not submit visibility claims, maneuver windows, power traces, or completion claims. Those are derived during validation.
+## Modeling Contract
+Use SI units, degrees, and timezone-aware ISO 8601 timestamps. A trailing `Z` is the safest UTC form. `case/mission.yaml` is a top-level `mission` mapping. Let `H0 = mission.horizon_start`, `H1 = mission.horizon_end`, and `dt = mission.action_time_step_s`. Every action `start_time` and `end_time` must satisfy:
+```text
+H0 <= start_time < end_time <= H1
+(start_time - H0) / dt is an integer
+(end_time - H0) / dt is an integer
+```
+Each task in `case/tasks.yaml` has `release_time`, `due_time`, and `required_duration_s` on the same grid. A valid observation action must use `type: "observation"`, reference a known `satellite_id` and `task_id`, satisfy `release_time <= start_time` and `end_time <= due_time`, and have:
+```text
+end_time - start_time = required_duration_s
+```
+Longer or shorter observations do not partially complete the task. The satellite's `sensor.sensor_type` must exactly equal the task's `required_sensor_type`.
+The constellation is fixed by `case/satellites.yaml`. Satellite states are propagated only from each satellite's `tle_line1` and `tle_line2`; do not add satellites, change TLEs, or submit attitude trajectories. Inertial quantities use the case's GCRF convention, Earth-fixed geometry uses ITRF/ECEF, target coordinates use WGS84 geodetic `longitude_deg`, `latitude_deg`, and `altitude_m`, and Earth orientation is deterministic for a given case.
+Observation visibility is checked at `start_time`, `end_time`, and every `geometry_sample_step_s` grid instant strictly inside the action. At every checked instant, the target line of sight must be above the target local horizon and the off-nadir angle from satellite nadir to target line of sight must be no greater than `attitude_model.max_off_nadir_deg`, allowing only tiny numerical tolerance at the boundary.
+For a satellite, observation intervals are half-open for overlap purposes: `[start_time, end_time)`. Same-satellite actions must not overlap. For consecutive same-satellite observations, the required retargeting gap is computed from the angle `theta` between the previous target vector at the previous `end_time` and the next target vector at the next `start_time`, both in the inertial frame. With `omega = max_slew_velocity_deg_per_s` and `alpha = max_slew_acceleration_deg_per_s2`:
+```text
+if theta <= omega^2 / alpha:
+  slew_time_s = 2 * sqrt(theta / alpha)
+else:
+  slew_time_s = 2 * (omega / alpha) + (theta - omega^2 / alpha) / omega
+required_gap_s = slew_time_s + settling_time_s
+```
+The required gap is reserved immediately before the later observation. The solution is invalid if the available idle gap is shorter than `required_gap_s`.
+Battery feasibility is simulated for each satellite over the full mission horizon using `resource_sample_step_s` grid points plus all action and retargeting-window boundaries. Each segment uses its midpoint to decide whether an observation, retargeting window, and sunlight are active. Battery starts at `resource_model.initial_battery_wh`, is capped after each segment at `battery_capacity_wh`, and invalidates the solution if it drops below zero. Segment load is:
+```text
+load_power_w = idle_power_w
+             + imaging_power_w if the segment midpoint is inside an observation
+             + slew_power_w if the segment midpoint is inside a retargeting window
+battery_next_wh = battery_wh + (charge_power_w - load_power_w) * duration_s / 3600
+```
+`charge_power_w` is `sunlit_charge_power_w` in sunlight and `0` in eclipse. `PC` is gross consumed watt-hours summed over satellites that pass the battery check.
+Task completion is binary. For each `task_id`, the earliest valid completing observation by `end_time` counts once; duplicates do not add credit. For valid solutions:
+```text
+CR  = completed_task_count / total_task_count
+WCR = sum(weight for completed tasks) / sum(weight for all tasks)
+TAT = mean(completion_time - release_time) over completed tasks, in seconds, or null if none complete
+PC  = gross consumed watt-hours
+```
+Validity is the hard gate before these metrics matter. Residual ambiguity remains only for borderline propagation, geometry, and battery cases at numerical tolerances.

tasks/aeossp_standard-test-case_0001/solution/solution.json ADDED Viewed

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tasks/aeossp_standard-test-case_0001/solution/solve.sh ADDED Viewed

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+#!/bin/bash
+set -euo pipefail
+cp /solution/solution.json /workspace/solution/solution.json

tasks/aeossp_standard-test-case_0001/task.toml ADDED Viewed

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+schema_version = "1.3"
+artifacts = [{source = "/workspace/solution", destination = "solution"}]
+[task]
+name = "astroagentbench/aeossp_standard-test-case_0001"
+[metadata]
+benchmark = "aeossp_standard"
+split = "test"
+case_id = "case_0001"
+source_commit = "6f5b9d21b1efb2ca2ee6fcabdc338a9d077612cb"
+source_dirty = false
+case_sha256 = "81213315b8f4e84e07479e8048313c9102928c829bce1054cfad4ca58c84dcc4"
+verifier_sha256 = "a5372c13197394134bf55297a1d04ec8d0610f4fd22e2ec7b247e21c6fa0db9a"
+runtime_image = "ghcr.io/mtrya/astroagentbench-python@sha256:fe9733cad55519aa08dd0db9abb51444051ef5f53d6ac1ef0b4b6592491437d1"
+solution_filename = "solution.json"
+[environment]
+cpus = 8
+memory_mb = 16384
+storage_mb = 10240
+network_mode = "public"
+[agent]
+timeout_sec = 7200
+[verifier]
+environment_mode = "separate"
+timeout_sec = 600

tasks/aeossp_standard-test-case_0001/tests/Dockerfile ADDED Viewed

	@@ -0,0 +1,3 @@

+FROM ghcr.io/mtrya/astroagentbench-python@sha256:fe9733cad55519aa08dd0db9abb51444051ef5f53d6ac1ef0b4b6592491437d1
+COPY . /tests
+WORKDIR /tests

tasks/aeossp_standard-test-case_0001/tests/benchmarks/__init__.py ADDED Viewed

File without changes

tasks/aeossp_standard-test-case_0001/tests/benchmarks/aeossp_standard/__init__.py ADDED Viewed

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tasks/aeossp_standard-test-case_0001/tests/benchmarks/aeossp_standard/verifier/__init__.py ADDED Viewed

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+"""Public verifier helpers for aeossp_standard."""
+from .engine import analyze, analyze_solution, verify, verify_solution
+from .models import (
+    ActionFailure,
+    BatteryTraceSegment,
+    ManeuverWindow,
+    SolutionAnalysis,
+    TaskOutcome,
+    TimelineEvent,
+    ValidatedAction,
+    VerificationResult,
+)
+__all__ = [
+    "ActionFailure",
+    "BatteryTraceSegment",
+    "ManeuverWindow",
+    "SolutionAnalysis",
+    "TaskOutcome",
+    "TimelineEvent",
+    "ValidatedAction",
+    "VerificationResult",
+    "analyze",
+    "analyze_solution",
+    "verify",
+    "verify_solution",
+]

tasks/aeossp_standard-test-case_0001/tests/benchmarks/aeossp_standard/verifier/engine.py ADDED Viewed

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+"""Core verification logic for the aeossp_standard benchmark."""
+from __future__ import annotations
+from collections import defaultdict
+from datetime import UTC, datetime, timedelta
+import math
+from pathlib import Path
+from typing import Any
+import brahe
+import numpy as np
+from .io import load_case, load_solution
+from .models import (
+    AeosspCase,
+    AeosspSolution,
+    ActionFailure,
+    BatteryTraceSegment,
+    ManeuverWindow,
+    Mission,
+    NUMERICAL_EPS,
+    ObservationAction,
+    SolutionAnalysis,
+    TaskDef,
+    TaskOutcome,
+    TimelineEvent,
+    ValidatedAction,
+    VerificationResult,
+)
+_BRAHE_EOP_INITIALIZED = False
+class _PropagationContext:
+    def __init__(self, case: AeosspCase):
+        self.case = case
+        step_s = float(min(case.mission.action_time_step_s, case.mission.geometry_sample_step_s))
+        self.propagators = {
+            sat_id: brahe.SGPPropagator.from_tle(sat.tle_line1, sat.tle_line2, step_s)
+            for sat_id, sat in case.satellites.items()
+        }
+        self._eci_cache: dict[tuple[str, datetime], np.ndarray] = {}
+        self._ecef_cache: dict[tuple[str, datetime], np.ndarray] = {}
+    def state_eci(self, satellite_id: str, instant: datetime) -> np.ndarray:
+        key = (satellite_id, instant.astimezone(UTC))
+        state = self._eci_cache.get(key)
+        if state is None:
+            epoch = _datetime_to_epoch(key[1])
+            state = np.asarray(self.propagators[satellite_id].state_eci(epoch), dtype=float).reshape(6)
+            self._eci_cache[key] = state
+        return state
+    def state_ecef(self, satellite_id: str, instant: datetime) -> np.ndarray:
+        key = (satellite_id, instant.astimezone(UTC))
+        state = self._ecef_cache.get(key)
+        if state is None:
+            epoch = _datetime_to_epoch(key[1])
+            state = np.asarray(self.propagators[satellite_id].state_ecef(epoch), dtype=float).reshape(6)
+            self._ecef_cache[key] = state
+        return state
+def _ensure_brahe_ready() -> None:
+    global _BRAHE_EOP_INITIALIZED
+    if _BRAHE_EOP_INITIALIZED:
+        return
+    brahe.set_global_eop_provider_from_static_provider(
+        brahe.StaticEOPProvider.from_zero()
+    )
+    _BRAHE_EOP_INITIALIZED = True
+def _datetime_to_epoch(value: datetime) -> brahe.Epoch:
+    value = value.astimezone(UTC)
+    second = float(value.second) + (value.microsecond / 1_000_000.0)
+    return brahe.Epoch.from_datetime(
+        value.year,
+        value.month,
+        value.day,
+        value.hour,
+        value.minute,
+        second,
+        0.0,
+        brahe.TimeSystem.UTC,
+    )
+def _iso_z(value: datetime) -> str:
+    return value.astimezone(UTC).isoformat().replace("+00:00", "Z")
+def _default_metrics() -> dict[str, Any]:
+    return {"CR": 0.0, "WCR": 0.0, "TAT": None, "PC": 0.0}
+def _invalid_result(
+    violations: list[str], diagnostics: dict[str, Any] | None = None
+) -> VerificationResult:
+    return VerificationResult(
+        valid=False,
+        metrics=_default_metrics(),
+        violations=violations,
+        diagnostics=diagnostics or {},
+    )
+def _is_aligned(seconds: float, step_s: int) -> bool:
+    return abs((seconds / step_s) - round(seconds / step_s)) <= 1.0e-9
+def _action_sample_times(
+    mission: Mission,
+    start_time: datetime,
+    end_time: datetime,
+) -> list[datetime]:
+    if end_time <= start_time:
+        return [start_time]
+    points = [start_time]
+    step_s = mission.geometry_sample_step_s
+    start_offset_s = int(round((start_time - mission.horizon_start).total_seconds()))
+    end_offset_s = int(round((end_time - mission.horizon_start).total_seconds()))
+    next_grid_offset_s = ((start_offset_s // step_s) + 1) * step_s
+    while next_grid_offset_s < end_offset_s:
+        points.append(mission.horizon_start + timedelta(seconds=next_grid_offset_s))
+        next_grid_offset_s += step_s
+    if points[-1] != end_time:
+        points.append(end_time)
+    return points
+def _angle_between_deg(vector_a: np.ndarray, vector_b: np.ndarray) -> float:
+    norm_a = float(np.linalg.norm(vector_a))
+    norm_b = float(np.linalg.norm(vector_b))
+    if norm_a <= NUMERICAL_EPS or norm_b <= NUMERICAL_EPS:
+        return 0.0
+    cosine = float(np.dot(vector_a, vector_b) / (norm_a * norm_b))
+    cosine = max(-1.0, min(1.0, cosine))
+    return math.degrees(math.acos(cosine))
+def _off_nadir_deg(satellite_position_ecef_m: np.ndarray, target_ecef_m: np.ndarray) -> float:
+    return _angle_between_deg(
+        -satellite_position_ecef_m,
+        target_ecef_m - satellite_position_ecef_m,
+    )
+def _target_visible(
+    satellite_position_ecef_m: np.ndarray,
+    target_ecef_m: np.ndarray,
+) -> bool:
+    target_norm = float(np.linalg.norm(target_ecef_m))
+    if target_norm <= NUMERICAL_EPS:
+        return False
+    target_normal = target_ecef_m / target_norm
+    return float(np.dot(satellite_position_ecef_m - target_ecef_m, target_normal)) > 0.0
+def _target_vector_eci(
+    task: TaskDef,
+    propagation: _PropagationContext,
+    satellite_id: str,
+    instant: datetime,
+) -> np.ndarray:
+    epoch = _datetime_to_epoch(instant)
+    target_eci = np.asarray(
+        brahe.position_ecef_to_eci(epoch, np.asarray(task.target_ecef_m, dtype=float)),
+        dtype=float,
+    ).reshape(3)
+    sat_state_eci = propagation.state_eci(satellite_id, instant)
+    return target_eci - sat_state_eci[:3]
+def _is_sunlit(position_eci_m: np.ndarray, epoch: brahe.Epoch) -> bool:
+    sun_position = np.asarray(brahe.sun_position(epoch), dtype=float)
+    sun_hat = sun_position / np.linalg.norm(sun_position)
+    projection = float(np.dot(position_eci_m, sun_hat))
+    perpendicular = np.linalg.norm(position_eci_m - (projection * sun_hat))
+    return not (projection < 0.0 and perpendicular < brahe.R_EARTH)
+def _slew_time_s(
+    delta_angle_deg: float,
+    max_velocity_deg_per_s: float,
+    max_acceleration_deg_per_s2: float,
+) -> float:
+    delta_angle_deg = max(0.0, delta_angle_deg)
+    if delta_angle_deg <= NUMERICAL_EPS:
+        return 0.0
+    if max_velocity_deg_per_s <= 0.0 or max_acceleration_deg_per_s2 <= 0.0:
+        return math.inf
+    ramp_time = max_velocity_deg_per_s / max_acceleration_deg_per_s2
+    triangular_threshold = (
+        max_velocity_deg_per_s * max_velocity_deg_per_s / max_acceleration_deg_per_s2
+    )
+    if delta_angle_deg <= triangular_threshold:
+        return 2.0 * math.sqrt(delta_angle_deg / max_acceleration_deg_per_s2)
+    cruise_angle = delta_angle_deg - triangular_threshold
+    return (2.0 * ramp_time) + (cruise_angle / max_velocity_deg_per_s)
+def _make_failure(
+    *,
+    action_index: int,
+    satellite_id: str,
+    task_id: str,
+    reason: str,
+    stage: str,
+    time: datetime | None = None,
+) -> ActionFailure:
+    return ActionFailure(
+        action_index=action_index,
+        satellite_id=satellite_id,
+        task_id=task_id,
+        reason=reason,
+        stage=stage,
+        time=time.astimezone(UTC) if time is not None else None,
+    )
+def _validate_action_structure(
+    case: AeosspCase,
+    solution: AeosspSolution,
+) -> tuple[list[ValidatedAction], list[ActionFailure], list[str]]:
+    validated: list[ValidatedAction] = []
+    failures: list[ActionFailure] = []
+    violations: list[str] = []
+    for index, action in enumerate(solution.actions):
+        prefix = f"actions[{index}]"
+        if action.satellite_id not in case.satellites:
+            failures.append(
+                _make_failure(
+                    action_index=index,
+                    satellite_id=action.satellite_id,
+                    task_id=action.task_id,
+                    reason="unknown satellite_id",
+                    stage="structure",
+                    time=action.start_time,
+                )
+            )
+            violations.append(f"{prefix}: unknown satellite_id {action.satellite_id!r}")
+            continue
+        if action.task_id not in case.tasks:
+            failures.append(
+                _make_failure(
+                    action_index=index,
+                    satellite_id=action.satellite_id,
+                    task_id=action.task_id,
+                    reason="unknown task_id",
+                    stage="structure",
+                    time=action.start_time,
+                )
+            )
+            violations.append(f"{prefix}: unknown task_id {action.task_id!r}")
+            continue
+        task = case.tasks[action.task_id]
+        if action.end_time <= action.start_time:
+            reason = "end_time must be after start_time"
+            failures.append(
+                _make_failure(
+                    action_index=index,
+                    satellite_id=action.satellite_id,
+                    task_id=action.task_id,
+                    reason=reason,
+                    stage="structure",
+                    time=action.start_time,
+                )
+            )
+            violations.append(f"{prefix}: {reason}")
+            continue
+        if action.start_time < case.mission.horizon_start or action.end_time > case.mission.horizon_end:
+            reason = "action lies outside the mission horizon"
+            failures.append(
+                _make_failure(
+                    action_index=index,
+                    satellite_id=action.satellite_id,
+                    task_id=action.task_id,
+                    reason=reason,
+                    stage="structure",
+                    time=action.start_time,
+                )
+            )
+            violations.append(f"{prefix}: {reason}")
+            continue
+        misaligned = False
+        for field_name, instant in (("start_time", action.start_time), ("end_time", action.end_time)):
+            seconds = (instant - case.mission.horizon_start).total_seconds()
+            if not _is_aligned(seconds, case.mission.action_time_step_s):
+                reason = f"{field_name} must align to the {case.mission.action_time_step_s}s action grid"
+                failures.append(
+                    _make_failure(
+                        action_index=index,
+                        satellite_id=action.satellite_id,
+                        task_id=action.task_id,
+                        reason=reason,
+                        stage="structure",
+                        time=instant,
+                    )
+                )
+                violations.append(f"{prefix}: {reason}")
+                misaligned = True
+                break
+        if misaligned:
+            continue
+        if action.start_time < task.release_time or action.end_time > task.due_time:
+            reason = "action lies outside the task window"
+            failures.append(
+                _make_failure(
+                    action_index=index,
+                    satellite_id=action.satellite_id,
+                    task_id=action.task_id,
+                    reason=reason,
+                    stage="structure",
+                    time=action.start_time,
+                )
+            )
+            violations.append(f"{prefix}: {reason}")
+            continue
+        if action.duration_s != task.required_duration_s:
+            reason = (
+                f"action duration must equal required_duration_s "
+                f"({task.required_duration_s}s)"
+            )
+            failures.append(
+                _make_failure(
+                    action_index=index,
+                    satellite_id=action.satellite_id,
+                    task_id=action.task_id,
+                    reason=reason,
+                    stage="structure",
+                    time=action.start_time,
+                )
+            )
+            violations.append(f"{prefix}: {reason}")
+            continue
+        satellite = case.satellites[action.satellite_id]
+        if satellite.sensor.sensor_type != task.required_sensor_type:
+            reason = "satellite sensor_type does not match task required_sensor_type"
+            failures.append(
+                _make_failure(
+                    action_index=index,
+                    satellite_id=action.satellite_id,
+                    task_id=action.task_id,
+                    reason=reason,
+                    stage="structure",
+                    time=action.start_time,
+                )
+            )
+            violations.append(f"{prefix}: {reason}")
+            continue
+        validated.append(
+            ValidatedAction(
+                action_index=index,
+                satellite_id=action.satellite_id,
+                task_id=action.task_id,
+                start_time=action.start_time,
+                end_time=action.end_time,
+            )
+        )
+    return validated, failures, violations
+def _validate_observation_geometry(
+    case: AeosspCase,
+    propagation: _PropagationContext,
+    validated_actions: list[ValidatedAction],
+    failures: list[ActionFailure],
+    violations: list[str],
+) -> list[ValidatedAction]:
+    accepted: list[ValidatedAction] = []
+    for item in validated_actions:
+        satellite = case.satellites[item.satellite_id]
+        task = case.tasks[item.task_id]
+        sample_times = _action_sample_times(
+            case.mission,
+            item.start_time,
+            item.end_time,
+        )
+        bad_reason: str | None = None
+        bad_time: datetime | None = None
+        for sample_time in sample_times:
+            state_ecef = propagation.state_ecef(item.satellite_id, sample_time)
+            sat_pos_ecef = state_ecef[:3]
+            if not _target_visible(sat_pos_ecef, np.asarray(task.target_ecef_m, dtype=float)):
+                bad_reason = "target is not continuously visible"
+                bad_time = sample_time
+                break
+            off_nadir_deg = _off_nadir_deg(sat_pos_ecef, np.asarray(task.target_ecef_m, dtype=float))
+            if off_nadir_deg > satellite.attitude_model.max_off_nadir_deg + 1.0e-6:
+                bad_reason = "required pointing exceeds max_off_nadir_deg"
+                bad_time = sample_time
+                break
+        if bad_reason is not None:
+            failure_text = f"{bad_reason} at {_iso_z(bad_time)}" if bad_time is not None else bad_reason
+            failures.append(
+                _make_failure(
+                    action_index=item.action_index,
+                    satellite_id=item.satellite_id,
+                    task_id=item.task_id,
+                    reason=failure_text,
+                    stage="geometry",
+                    time=bad_time,
+                )
+            )
+            violations.append(f"actions[{item.action_index}]: {failure_text}")
+            continue
+        accepted.append(item)
+    return accepted
+def _validate_slew_and_build_maneuver_windows(
+    case: AeosspCase,
+    propagation: _PropagationContext,
+    actions_by_satellite: dict[str, list[ValidatedAction]],
+    failures: list[ActionFailure],
+    violations: list[str],
+) -> tuple[dict[str, list[ValidatedAction]], dict[str, list[ManeuverWindow]]]:
+    accepted_actions_by_satellite: dict[str, list[ValidatedAction]] = defaultdict(list)
+    maneuver_windows: dict[str, list[ManeuverWindow]] = defaultdict(list)
+    for satellite_id, actions in actions_by_satellite.items():
+        satellite = case.satellites[satellite_id]
+        actions.sort(key=lambda item: (item.start_time, item.end_time, item.action_index))
+        previous: ValidatedAction | None = None
+        for current in actions:
+            if previous is not None and previous.end_time > current.start_time:
+                reason = "observation actions overlap on the same satellite"
+                failures.append(
+                    _make_failure(
+                        action_index=current.action_index,
+                        satellite_id=satellite_id,
+                        task_id=current.task_id,
+                        reason=reason,
+                        stage="slew",
+                        time=current.start_time,
+                    )
+                )
+                violations.append(f"actions[{current.action_index}]: {reason}")
+                continue
+            current_task = case.tasks[current.task_id]
+            current_start_vec = _target_vector_eci(
+                current_task, propagation, satellite_id, current.start_time
+            )
+            if previous is None:
+                sat_state_eci = propagation.state_eci(satellite_id, current.start_time)
+                from_vector = -sat_state_eci[:3]
+                available_gap_s = (
+                    current.start_time - case.mission.horizon_start
+                ).total_seconds()
+                from_task_id = None
+                from_action_index = None
+            else:
+                previous_task = case.tasks[previous.task_id]
+                from_vector = _target_vector_eci(
+                    previous_task, propagation, satellite_id, previous.end_time
+                )
+                available_gap_s = (
+                    current.start_time - previous.end_time
+                ).total_seconds()
+                from_task_id = previous.task_id
+                from_action_index = previous.action_index
+            slew_angle_deg = _angle_between_deg(from_vector, current_start_vec)
+            slew_time_s = _slew_time_s(
+                slew_angle_deg,
+                satellite.attitude_model.max_slew_velocity_deg_per_s,
+                satellite.attitude_model.max_slew_acceleration_deg_per_s2,
+            )
+            required_gap_s = slew_time_s + satellite.attitude_model.settling_time_s
+            if available_gap_s + NUMERICAL_EPS < required_gap_s:
+                reason = (
+                    f"insufficient slew/settle time before observation "
+                    f"(need {required_gap_s:.3f}s, have {available_gap_s:.3f}s)"
+                )
+                failures.append(
+                    _make_failure(
+                        action_index=current.action_index,
+                        satellite_id=satellite_id,
+                        task_id=current.task_id,
+                        reason=reason,
+                        stage="slew",
+                        time=current.start_time,
+                    )
+                )
+                violations.append(f"actions[{current.action_index}]: {reason}")
+                continue
+            if required_gap_s > NUMERICAL_EPS:
+                window_start = current.start_time - timedelta(seconds=required_gap_s)
+                maneuver_windows[satellite_id].append(
+                    ManeuverWindow(
+                        action_index=current.action_index,
+                        satellite_id=satellite_id,
+                        start_time=window_start,
+                        end_time=current.start_time,
+                        required_gap_s=required_gap_s,
+                        slew_angle_deg=slew_angle_deg,
+                        from_action_index=from_action_index,
+                        from_task_id=from_task_id,
+                        to_task_id=current.task_id,
+                    )
+                )
+            accepted_actions_by_satellite[satellite_id].append(current)
+            previous = current
+    return accepted_actions_by_satellite, maneuver_windows
+def _interval_contains(instant: datetime, start: datetime, end: datetime) -> bool:
+    return start <= instant < end
+def _resource_time_points(
+    mission: Mission,
+    actions: list[ValidatedAction],
+    maneuver_windows: list[ManeuverWindow],
+) -> list[datetime]:
+    points: set[datetime] = {mission.horizon_start, mission.horizon_end}
+    current = mission.horizon_start
+    delta = timedelta(seconds=mission.resource_sample_step_s)
+    while current < mission.horizon_end:
+        points.add(current)
+        current = min(current + delta, mission.horizon_end)
+    points.add(mission.horizon_end)
+    for item in actions:
+        points.add(item.start_time)
+        points.add(item.end_time)
+    for window in maneuver_windows:
+        points.add(window.start_time)
+        points.add(window.end_time)
+    return sorted(points)
+def _segment_mode(
+    active_observation: ValidatedAction | None,
+    active_maneuver: ManeuverWindow | None,
+) -> str:
+    if active_observation is not None and active_maneuver is not None:
+        return "observation+slew"
+    if active_observation is not None:
+        return "observation"
+    if active_maneuver is not None:
+        return "slew"
+    return "idle"
+def _simulate_battery_and_power(
+    case: AeosspCase,
+    propagation: _PropagationContext,
+    actions_by_satellite: dict[str, list[ValidatedAction]],
+    maneuver_windows: dict[str, list[ManeuverWindow]],
+    failures: list[ActionFailure],
+    violations: list[str],
+) -> tuple[float, dict[str, Any], dict[str, tuple[BatteryTraceSegment, ...]]]:
+    total_pc_wh = 0.0
+    summaries: dict[str, Any] = {}
+    traces: dict[str, tuple[BatteryTraceSegment, ...]] = {}
+    for satellite_id, satellite in case.satellites.items():
+        actions = sorted(
+            actions_by_satellite.get(satellite_id, []),
+            key=lambda item: (item.start_time, item.end_time, item.action_index),
+        )
+        windows = maneuver_windows.get(satellite_id, [])
+        time_points = _resource_time_points(case.mission, actions, windows)
+        battery_wh = satellite.resource_model.initial_battery_wh
+        min_battery_wh = battery_wh
+        min_battery_time = case.mission.horizon_start
+        gross_consumption_wh = 0.0
+        total_charge_wh = 0.0
+        total_imaging_time_s = 0.0
+        total_slew_time_s = 0.0
+        failed = False
+        trace_segments: list[BatteryTraceSegment] = []
+        for start_time, end_time in zip(time_points, time_points[1:]):
+            duration_s = (end_time - start_time).total_seconds()
+            if duration_s <= 0.0:
+                continue
+            midpoint = start_time + ((end_time - start_time) / 2)
+            active_observation = next(
+                (
+                    item
+                    for item in actions
+                    if _interval_contains(midpoint, item.start_time, item.end_time)
+                ),
+                None,
+            )
+            active_maneuver = next(
+                (
+                    window
+                    for window in windows
+                    if _interval_contains(midpoint, window.start_time, window.end_time)
+                ),
+                None,
+            )
+            load_power_w = satellite.resource_model.idle_power_w
+            if active_observation is not None:
+                load_power_w += satellite.resource_model.imaging_power_w
+                total_imaging_time_s += duration_s
+            if active_maneuver is not None:
+                load_power_w += satellite.resource_model.slew_power_w
+                total_slew_time_s += duration_s
+            epoch = _datetime_to_epoch(midpoint)
+            state_eci = propagation.state_eci(satellite_id, midpoint)
+            charge_power_w = (
+                satellite.resource_model.sunlit_charge_power_w
+                if _is_sunlit(state_eci[:3], epoch)
+                else 0.0
+            )
+            battery_start_wh = battery_wh
+            gross_consumption_wh += (load_power_w * duration_s) / 3600.0
+            total_charge_wh += (charge_power_w * duration_s) / 3600.0
+            battery_wh += ((charge_power_w - load_power_w) * duration_s) / 3600.0
+            if battery_wh < -NUMERICAL_EPS:
+                reason = f"battery depletes below zero around {_iso_z(midpoint)}"
+                failing_index = active_observation.action_index if active_observation else -1
+                failing_task = active_observation.task_id if active_observation else ""
+                failures.append(
+                    _make_failure(
+                        action_index=failing_index,
+                        satellite_id=satellite_id,
+                        task_id=failing_task,
+                        reason=reason,
+                        stage="battery",
+                        time=midpoint,
+                    )
+                )
+                violations.append(f"Satellite {satellite_id}: {reason}")
+                failed = True
+                battery_end_wh = battery_wh
+            else:
+                battery_wh = min(satellite.resource_model.battery_capacity_wh, battery_wh)
+                battery_end_wh = battery_wh
+                if battery_wh < min_battery_wh:
+                    min_battery_wh = battery_wh
+                    min_battery_time = end_time
+            trace_segments.append(
+                BatteryTraceSegment(
+                    satellite_id=satellite_id,
+                    start_time=start_time,
+                    end_time=end_time,
+                    battery_start_wh=battery_start_wh,
+                    battery_end_wh=battery_end_wh,
+                    load_power_w=load_power_w,
+                    charge_power_w=charge_power_w,
+                    mode=_segment_mode(active_observation, active_maneuver),
+                    active_action_index=active_observation.action_index if active_observation else None,
+                    active_task_id=active_observation.task_id if active_observation else None,
+                    active_maneuver_to_action_index=active_maneuver.action_index if active_maneuver else None,
+                )
+            )
+            if failed:
+                break
+        summaries[satellite_id] = {
+            "initial_battery_wh": satellite.resource_model.initial_battery_wh,
+            "minimum_battery_wh": min_battery_wh,
+            "minimum_battery_time": _iso_z(min_battery_time),
+            "final_battery_wh": battery_wh,
+            "gross_consumption_wh": gross_consumption_wh,
+            "total_charge_wh": total_charge_wh,
+            "total_imaging_time_s": total_imaging_time_s,
+            "total_slew_time_s": total_slew_time_s,
+            "failed": failed,
+        }
+        traces[satellite_id] = tuple(trace_segments)
+        if not failed:
+            total_pc_wh += gross_consumption_wh
+    return total_pc_wh, summaries, traces
+def _compute_task_outcomes(
+    case: AeosspCase,
+    validated_actions: list[ValidatedAction],
+) -> dict[str, TaskOutcome]:
+    completed_by_task: dict[str, ValidatedAction] = {}
+    for item in sorted(
+        validated_actions,
+        key=lambda item: (item.end_time, item.start_time, item.action_index),
+    ):
+        current = completed_by_task.get(item.task_id)
+        if current is None or item.end_time < current.end_time:
+            completed_by_task[item.task_id] = item
+    outcomes: dict[str, TaskOutcome] = {}
+    for task_id, task in case.tasks.items():
+        completion = completed_by_task.get(task_id)
+        outcomes[task_id] = TaskOutcome(
+            task_id=task_id,
+            completed=completion is not None,
+            completion_time=completion.end_time if completion is not None else None,
+            completed_by_action_index=completion.action_index if completion is not None else None,
+            weight=task.weight,
+        )
+    return outcomes
+def _compute_metrics(
+    case: AeosspCase,
+    task_outcomes: dict[str, TaskOutcome],
+    total_pc_wh: float,
+) -> dict[str, Any]:
+    total_tasks = len(case.tasks)
+    completed = [outcome for outcome in task_outcomes.values() if outcome.completed]
+    total_weight = sum(task.weight for task in case.tasks.values())
+    completed_weight = sum(outcome.weight for outcome in completed)
+    tat_values_s = [
+        (
+            outcome.completion_time - case.tasks[outcome.task_id].release_time
+        ).total_seconds()
+        for outcome in completed
+        if outcome.completion_time is not None
+    ]
+    return {
+        "CR": len(completed) / total_tasks if total_tasks else 0.0,
+        "WCR": completed_weight / total_weight if total_weight > 0.0 else 0.0,
+        "TAT": (sum(tat_values_s) / len(tat_values_s)) if tat_values_s else None,
+        "PC": total_pc_wh,
+    }
+def _build_timeline_events(
+    validated_actions: list[ValidatedAction],
+    maneuver_windows: tuple[ManeuverWindow, ...],
+    failures: list[ActionFailure],
+) -> tuple[TimelineEvent, ...]:
+    events: list[TimelineEvent] = []
+    for action in validated_actions:
+        events.append(
+            TimelineEvent(
+                time=action.start_time,
+                satellite_id=action.satellite_id,
+                kind="action_start",
+                action_index=action.action_index,
+                task_id=action.task_id,
+            )
+        )
+        events.append(
+            TimelineEvent(
+                time=action.end_time,
+                satellite_id=action.satellite_id,
+                kind="action_end",
+                action_index=action.action_index,
+                task_id=action.task_id,
+            )
+        )
+    for window in maneuver_windows:
+        events.append(
+            TimelineEvent(
+                time=window.start_time,
+                satellite_id=window.satellite_id,
+                kind="maneuver_start",
+                action_index=window.action_index,
+                task_id=window.to_task_id,
+            )
+        )
+        events.append(
+            TimelineEvent(
+                time=window.end_time,
+                satellite_id=window.satellite_id,
+                kind="maneuver_end",
+                action_index=window.action_index,
+                task_id=window.to_task_id,
+            )
+        )
+    for failure in failures:
+        if failure.time is None:
+            continue
+        events.append(
+            TimelineEvent(
+                time=failure.time,
+                satellite_id=failure.satellite_id,
+                kind="failure",
+                action_index=failure.action_index if failure.action_index >= 0 else None,
+                task_id=failure.task_id or None,
+                detail=failure.reason,
+            )
+        )
+    events.sort(key=lambda item: (item.time, item.satellite_id, item.kind, item.action_index or -1))
+    return tuple(events)
+def _build_snapshot_candidates(
+    validated_actions: list[ValidatedAction],
+    failures: list[ActionFailure],
+    resource_summary: dict[str, Any],
+) -> tuple[datetime, ...]:
+    candidates: list[datetime] = []
+    for action in validated_actions:
+        candidates.extend((action.start_time, action.end_time))
+    for failure in failures:
+        if failure.time is not None:
+            candidates.append(failure.time)
+    for summary in resource_summary.values():
+        minimum_battery_time = summary.get("minimum_battery_time")
+        if isinstance(minimum_battery_time, str):
+            candidates.append(datetime.fromisoformat(minimum_battery_time.replace("Z", "+00:00")).astimezone(UTC))
+    unique = sorted({candidate.astimezone(UTC) for candidate in candidates})
+    return tuple(unique)
+def _build_diagnostics(
+    task_outcomes: dict[str, TaskOutcome],
+    failures: list[ActionFailure],
+    maneuver_windows: tuple[ManeuverWindow, ...],
+    resource_summary: dict[str, Any],
+) -> dict[str, Any]:
+    return {
+        "action_failures": [failure.as_dict() for failure in failures],
+        "maneuver_windows": [window.as_dict() for window in maneuver_windows],
+        "per_task": {
+            task_id: outcome.as_dict()
+            for task_id, outcome in task_outcomes.items()
+        },
+        "per_satellite_resource_summary": resource_summary,
+    }
+def analyze(case: AeosspCase, solution: AeosspSolution) -> SolutionAnalysis:
+    _ensure_brahe_ready()
+    propagation = _PropagationContext(case)
+    validated_actions, failures, violations = _validate_action_structure(case, solution)
+    validated_actions = _validate_observation_geometry(
+        case, propagation, validated_actions, failures, violations
+    )
+    actions_by_satellite: dict[str, list[ValidatedAction]] = defaultdict(list)
+    for item in validated_actions:
+        actions_by_satellite[item.satellite_id].append(item)
+    accepted_actions_by_satellite, maneuver_windows_by_satellite = _validate_slew_and_build_maneuver_windows(
+        case, propagation, actions_by_satellite, failures, violations
+    )
+    accepted_actions = [
+        item
+        for satellite_id in sorted(accepted_actions_by_satellite)
+        for item in accepted_actions_by_satellite[satellite_id]
+    ]
+    maneuver_windows = tuple(
+        window
+        for satellite_id in sorted(maneuver_windows_by_satellite)
+        for window in maneuver_windows_by_satellite[satellite_id]
+    )
+    total_pc_wh = 0.0
+    resource_summary: dict[str, Any] = {}
+    battery_traces: dict[str, tuple[BatteryTraceSegment, ...]] = {
+        sat_id: tuple() for sat_id in case.satellites
+    }
+    total_pc_wh, resource_summary, battery_traces = _simulate_battery_and_power(
+        case,
+        propagation,
+        accepted_actions_by_satellite,
+        maneuver_windows_by_satellite,
+        failures,
+        violations,
+    )
+    task_outcomes = _compute_task_outcomes(case, accepted_actions)
+    diagnostics = _build_diagnostics(task_outcomes, failures, maneuver_windows, resource_summary)
+    timeline_events = _build_timeline_events(accepted_actions, maneuver_windows, failures)
+    snapshot_candidates = _build_snapshot_candidates(accepted_actions, failures, resource_summary)
+    if violations:
+        result = VerificationResult(
+            valid=False,
+            metrics=_default_metrics(),
+            violations=violations,
+            diagnostics=diagnostics,
+        )
+    else:
+        result = VerificationResult(
+            valid=True,
+            metrics=_compute_metrics(case, task_outcomes, total_pc_wh),
+            violations=[],
+            diagnostics=diagnostics,
+        )
+    return SolutionAnalysis(
+        case=case,
+        solution=solution,
+        result=result,
+        validated_actions=tuple(
+            sorted(accepted_actions, key=lambda item: (item.start_time, item.end_time, item.action_index))
+        ),
+        action_failures=tuple(failures),
+        maneuver_windows=maneuver_windows,
+        task_outcomes=task_outcomes,
+        battery_traces=battery_traces,
+        per_satellite_resource_summary=resource_summary,
+        timeline_events=timeline_events,
+        snapshot_candidates=snapshot_candidates,
+    )
+def analyze_solution(case_dir: str | Path, solution_path: str | Path) -> SolutionAnalysis:
+    case = load_case(case_dir)
+    solution = load_solution(solution_path)
+    return analyze(case, solution)
+def verify(case: AeosspCase, solution: AeosspSolution) -> VerificationResult:
+    return analyze(case, solution).result
+def verify_solution(case_dir: str | Path, solution_path: str | Path) -> VerificationResult:
+    try:
+        return analyze_solution(case_dir, solution_path).result
+    except (FileNotFoundError, ValueError) as exc:
+        return _invalid_result([str(exc)], diagnostics={})

tasks/aeossp_standard-test-case_0001/tests/benchmarks/aeossp_standard/verifier/io.py ADDED Viewed

	@@ -0,0 +1,346 @@

+"""Case and solution loading for the aeossp_standard verifier."""
+from __future__ import annotations
+from datetime import UTC, datetime, timedelta
+from pathlib import Path
+from typing import Any
+import json
+import brahe
+import yaml
+from .models import (
+    AeosspCase,
+    AeosspSolution,
+    AttitudeModel,
+    Mission,
+    NUMERICAL_EPS,
+    ObservationAction,
+    ResourceModel,
+    SatelliteDef,
+    Sensor,
+    TaskDef,
+)
+def _load_yaml(path: Path) -> Any:
+    return yaml.safe_load(path.read_text(encoding="utf-8"))
+def _load_json(path: Path) -> Any:
+    return json.loads(path.read_text(encoding="utf-8"))
+def _parse_iso_utc(value: str, *, field_name: str) -> datetime:
+    if not isinstance(value, str):
+        raise ValueError(f"{field_name} must be an ISO 8601 timestamp string")
+    parsed = datetime.fromisoformat(value.replace("Z", "+00:00"))
+    if parsed.tzinfo is None:
+        raise ValueError(f"{field_name} must include timezone information")
+    return parsed.astimezone(UTC)
+def _require_mapping(payload: Any, context: str) -> dict[str, Any]:
+    if not isinstance(payload, dict):
+        raise ValueError(f"{context} must be a mapping/object")
+    return payload
+def _require_list(payload: Any, context: str) -> list[Any]:
+    if not isinstance(payload, list):
+        raise ValueError(f"{context} must be a list/array")
+    return payload
+def _require_str(mapping: dict[str, Any], key: str, context: str) -> str:
+    value = mapping.get(key)
+    if not isinstance(value, str) or not value:
+        raise ValueError(f"{context}.{key} must be a non-empty string")
+    return value
+def _require_int(mapping: dict[str, Any], key: str, context: str) -> int:
+    value = mapping.get(key)
+    if not isinstance(value, int):
+        raise ValueError(f"{context}.{key} must be an integer")
+    return value
+def _require_float(mapping: dict[str, Any], key: str, context: str) -> float:
+    value = mapping.get(key)
+    if not isinstance(value, (int, float)):
+        raise ValueError(f"{context}.{key} must be numeric")
+    return float(value)
+def _validate_positive_int(value: int, *, field_name: str) -> None:
+    if value <= 0:
+        raise ValueError(f"{field_name} must be > 0")
+def _validate_non_negative(value: float, *, field_name: str) -> None:
+    if value < -NUMERICAL_EPS:
+        raise ValueError(f"{field_name} must be >= 0")
+def _is_aligned(seconds: float, step_s: int) -> bool:
+    return abs((seconds / step_s) - round(seconds / step_s)) <= 1.0e-9
+def _validate_horizon_divisibility(mission: Mission) -> None:
+    for field_name, step_s in (
+        ("action_time_step_s", mission.action_time_step_s),
+        ("geometry_sample_step_s", mission.geometry_sample_step_s),
+        ("resource_sample_step_s", mission.resource_sample_step_s),
+    ):
+        if not _is_aligned(float(mission.horizon_seconds), step_s):
+            raise ValueError(
+                f"mission horizon must be exactly divisible by {field_name}"
+            )
+def _task_target_ecef_m(task: dict[str, Any], context: str):
+    return brahe.position_geodetic_to_ecef(
+        [
+            _require_float(task, "longitude_deg", context),
+            _require_float(task, "latitude_deg", context),
+            _require_float(task, "altitude_m", context),
+        ],
+        brahe.AngleFormat.DEGREES,
+    )
+def load_case(case_dir: str | Path) -> AeosspCase:
+    case_path = Path(case_dir).resolve()
+    mission_doc = _require_mapping(_load_yaml(case_path / "mission.yaml"), "mission.yaml")
+    satellites_doc = _require_mapping(
+        _load_yaml(case_path / "satellites.yaml"), "satellites.yaml"
+    )
+    tasks_doc = _require_mapping(_load_yaml(case_path / "tasks.yaml"), "tasks.yaml")
+    mission_raw = _require_mapping(mission_doc.get("mission"), "mission.yaml.mission")
+    satellites_raw = _require_list(
+        satellites_doc.get("satellites"), "satellites.yaml.satellites"
+    )
+    tasks_raw = _require_list(tasks_doc.get("tasks"), "tasks.yaml.tasks")
+    mission = Mission(
+        case_id=_require_str(mission_raw, "case_id", "mission.yaml.mission"),
+        horizon_start=_parse_iso_utc(
+            _require_str(mission_raw, "horizon_start", "mission.yaml.mission"),
+            field_name="mission.horizon_start",
+        ),
+        horizon_end=_parse_iso_utc(
+            _require_str(mission_raw, "horizon_end", "mission.yaml.mission"),
+            field_name="mission.horizon_end",
+        ),
+        action_time_step_s=_require_int(
+            mission_raw, "action_time_step_s", "mission.yaml.mission"
+        ),
+        geometry_sample_step_s=_require_int(
+            mission_raw, "geometry_sample_step_s", "mission.yaml.mission"
+        ),
+        resource_sample_step_s=_require_int(
+            mission_raw, "resource_sample_step_s", "mission.yaml.mission"
+        ),
+    )
+    if mission.horizon_end <= mission.horizon_start:
+        raise ValueError("mission.horizon_end must be after mission.horizon_start")
+    _validate_positive_int(mission.action_time_step_s, field_name="mission.action_time_step_s")
+    _validate_positive_int(
+        mission.geometry_sample_step_s, field_name="mission.geometry_sample_step_s"
+    )
+    _validate_positive_int(
+        mission.resource_sample_step_s, field_name="mission.resource_sample_step_s"
+    )
+    _validate_horizon_divisibility(mission)
+    propagation = _require_mapping(mission_raw.get("propagation"), "mission.yaml.mission.propagation")
+    if _require_str(propagation, "model", "mission.yaml.mission.propagation") != "sgp4":
+        raise ValueError("mission.propagation.model must be 'sgp4'")
+    satellites: dict[str, SatelliteDef] = {}
+    for index, payload in enumerate(satellites_raw):
+        context = f"satellites.yaml.satellites[{index}]"
+        sat_raw = _require_mapping(payload, context)
+        sat_id = _require_str(sat_raw, "satellite_id", context)
+        if sat_id in satellites:
+            raise ValueError(f"Duplicate satellite_id: {sat_id}")
+        tle_line1 = _require_str(sat_raw, "tle_line1", context)
+        tle_line2 = _require_str(sat_raw, "tle_line2", context)
+        if not brahe.validate_tle_lines(tle_line1, tle_line2):
+            raise ValueError(f"{context} contains an invalid TLE pair")
+        sensor_raw = _require_mapping(sat_raw.get("sensor"), f"{context}.sensor")
+        attitude_raw = _require_mapping(sat_raw.get("attitude_model"), f"{context}.attitude_model")
+        resource_raw = _require_mapping(sat_raw.get("resource_model"), f"{context}.resource_model")
+        sensor = Sensor(sensor_type=_require_str(sensor_raw, "sensor_type", f"{context}.sensor"))
+        if sensor.sensor_type not in {"visible", "infrared"}:
+            raise ValueError(f"{context}.sensor.sensor_type must be 'visible' or 'infrared'")
+        attitude = AttitudeModel(
+            max_slew_velocity_deg_per_s=_require_float(
+                attitude_raw, "max_slew_velocity_deg_per_s", f"{context}.attitude_model"
+            ),
+            max_slew_acceleration_deg_per_s2=_require_float(
+                attitude_raw,
+                "max_slew_acceleration_deg_per_s2",
+                f"{context}.attitude_model",
+            ),
+            settling_time_s=_require_float(
+                attitude_raw, "settling_time_s", f"{context}.attitude_model"
+            ),
+            max_off_nadir_deg=_require_float(
+                attitude_raw, "max_off_nadir_deg", f"{context}.attitude_model"
+            ),
+        )
+        resource = ResourceModel(
+            battery_capacity_wh=_require_float(
+                resource_raw, "battery_capacity_wh", f"{context}.resource_model"
+            ),
+            initial_battery_wh=_require_float(
+                resource_raw, "initial_battery_wh", f"{context}.resource_model"
+            ),
+            idle_power_w=_require_float(resource_raw, "idle_power_w", f"{context}.resource_model"),
+            imaging_power_w=_require_float(
+                resource_raw, "imaging_power_w", f"{context}.resource_model"
+            ),
+            slew_power_w=_require_float(resource_raw, "slew_power_w", f"{context}.resource_model"),
+            sunlit_charge_power_w=_require_float(
+                resource_raw, "sunlit_charge_power_w", f"{context}.resource_model"
+            ),
+        )
+        if resource.battery_capacity_wh <= 0:
+            raise ValueError(f"{context}.resource_model.battery_capacity_wh must be > 0")
+        if resource.initial_battery_wh < -NUMERICAL_EPS or (
+            resource.initial_battery_wh > resource.battery_capacity_wh + NUMERICAL_EPS
+        ):
+            raise ValueError(
+                f"{context}.resource_model.initial_battery_wh must lie within [0, battery_capacity_wh]"
+            )
+        for field_name, value in (
+            ("max_slew_velocity_deg_per_s", attitude.max_slew_velocity_deg_per_s),
+            ("max_slew_acceleration_deg_per_s2", attitude.max_slew_acceleration_deg_per_s2),
+            ("settling_time_s", attitude.settling_time_s),
+            ("max_off_nadir_deg", attitude.max_off_nadir_deg),
+            ("idle_power_w", resource.idle_power_w),
+            ("imaging_power_w", resource.imaging_power_w),
+            ("slew_power_w", resource.slew_power_w),
+            ("sunlit_charge_power_w", resource.sunlit_charge_power_w),
+        ):
+            _validate_non_negative(value, field_name=f"{context}.{field_name}")
+        satellites[sat_id] = SatelliteDef(
+            satellite_id=sat_id,
+            norad_catalog_id=_require_int(sat_raw, "norad_catalog_id", context),
+            tle_line1=tle_line1,
+            tle_line2=tle_line2,
+            sensor=sensor,
+            attitude_model=attitude,
+            resource_model=resource,
+        )
+    tasks: dict[str, TaskDef] = {}
+    for index, payload in enumerate(tasks_raw):
+        context = f"tasks.yaml.tasks[{index}]"
+        task_raw = _require_mapping(payload, context)
+        task_id = _require_str(task_raw, "task_id", context)
+        if task_id in tasks:
+            raise ValueError(f"Duplicate task_id: {task_id}")
+        release_time = _parse_iso_utc(
+            _require_str(task_raw, "release_time", context),
+            field_name=f"{context}.release_time",
+        )
+        due_time = _parse_iso_utc(
+            _require_str(task_raw, "due_time", context),
+            field_name=f"{context}.due_time",
+        )
+        required_duration_s = _require_int(task_raw, "required_duration_s", context)
+        weight_value = task_raw.get("weight", 1.0)
+        if not isinstance(weight_value, (int, float)):
+            raise ValueError(f"{context}.weight must be numeric")
+        weight = float(weight_value)
+        if release_time < mission.horizon_start or release_time > mission.horizon_end:
+            raise ValueError(f"{context}.release_time must lie inside the mission horizon")
+        if due_time < mission.horizon_start or due_time > mission.horizon_end:
+            raise ValueError(f"{context}.due_time must lie inside the mission horizon")
+        if due_time <= release_time:
+            raise ValueError(f"{context}.due_time must be after release_time")
+        if required_duration_s <= 0:
+            raise ValueError(f"{context}.required_duration_s must be > 0")
+        if weight <= 0.0:
+            raise ValueError(f"{context}.weight must be > 0")
+        for field_name, seconds in (
+            (f"{context}.release_time", (release_time - mission.horizon_start).total_seconds()),
+            (f"{context}.due_time", (due_time - mission.horizon_start).total_seconds()),
+            (f"{context}.required_duration_s", float(required_duration_s)),
+        ):
+            if not _is_aligned(seconds, mission.action_time_step_s):
+                raise ValueError(
+                    f"{field_name} must align to the {mission.action_time_step_s}s action grid"
+                )
+        if required_duration_s > int((due_time - release_time).total_seconds()):
+            raise ValueError(f"{context}.required_duration_s exceeds the task window length")
+        sensor_type = _require_str(task_raw, "required_sensor_type", context)
+        if sensor_type not in {"visible", "infrared"}:
+            raise ValueError(
+                f"{context}.required_sensor_type must be 'visible' or 'infrared'"
+            )
+        tasks[task_id] = TaskDef(
+            task_id=task_id,
+            name=_require_str(task_raw, "name", context),
+            latitude_deg=_require_float(task_raw, "latitude_deg", context),
+            longitude_deg=_require_float(task_raw, "longitude_deg", context),
+            altitude_m=_require_float(task_raw, "altitude_m", context),
+            release_time=release_time,
+            due_time=due_time,
+            required_duration_s=required_duration_s,
+            required_sensor_type=sensor_type,
+            weight=weight,
+            target_ecef_m=brahe.position_geodetic_to_ecef(
+                [
+                    _require_float(task_raw, "longitude_deg", context),
+                    _require_float(task_raw, "latitude_deg", context),
+                    _require_float(task_raw, "altitude_m", context),
+                ],
+                brahe.AngleFormat.DEGREES,
+            ),
+        )
+    return AeosspCase(
+        case_dir=case_path,
+        mission=mission,
+        satellites=satellites,
+        tasks=tasks,
+    )
+def load_solution(solution_path: str | Path) -> AeosspSolution:
+    path = Path(solution_path).resolve()
+    payload = _load_json(path)
+    if not isinstance(payload, dict):
+        raise ValueError("solution.json must be a JSON object")
+    actions_raw = payload.get("actions", [])
+    if not isinstance(actions_raw, list):
+        raise ValueError("solution.json.actions must be a list")
+    actions: list[ObservationAction] = []
+    for index, payload in enumerate(actions_raw):
+        context = f"solution.json.actions[{index}]"
+        action_raw = _require_mapping(payload, context)
+        action_type = _require_str(action_raw, "type", context)
+        if action_type != "observation":
+            raise ValueError(f"{context}.type {action_type!r} is unsupported")
+        actions.append(
+            ObservationAction(
+                satellite_id=_require_str(action_raw, "satellite_id", context),
+                task_id=_require_str(action_raw, "task_id", context),
+                start_time=_parse_iso_utc(
+                    _require_str(action_raw, "start_time", context),
+                    field_name=f"{context}.start_time",
+                ),
+                end_time=_parse_iso_utc(
+                    _require_str(action_raw, "end_time", context),
+                    field_name=f"{context}.end_time",
+                ),
+            )
+        )
+    return AeosspSolution(actions=actions)

tasks/aeossp_standard-test-case_0001/tests/benchmarks/aeossp_standard/verifier/models.py ADDED Viewed

	@@ -0,0 +1,286 @@

+"""Data models for the aeossp_standard verifier."""
+from __future__ import annotations
+from dataclasses import dataclass, field
+from datetime import UTC, datetime
+from pathlib import Path
+from typing import Any
+import json
+import numpy as np
+NUMERICAL_EPS = 1.0e-9
+@dataclass(frozen=True)
+class Mission:
+    case_id: str
+    horizon_start: datetime
+    horizon_end: datetime
+    action_time_step_s: int
+    geometry_sample_step_s: int
+    resource_sample_step_s: int
+    @property
+    def horizon_seconds(self) -> int:
+        seconds = (self.horizon_end - self.horizon_start).total_seconds()
+        if seconds < 0:
+            raise ValueError("mission horizon_end must be after horizon_start")
+        if abs(seconds - round(seconds)) > NUMERICAL_EPS:
+            raise ValueError("mission horizon must be an integer number of seconds")
+        return int(round(seconds))
+@dataclass(frozen=True)
+class Sensor:
+    sensor_type: str
+@dataclass(frozen=True)
+class AttitudeModel:
+    max_slew_velocity_deg_per_s: float
+    max_slew_acceleration_deg_per_s2: float
+    settling_time_s: float
+    max_off_nadir_deg: float
+@dataclass(frozen=True)
+class ResourceModel:
+    battery_capacity_wh: float
+    initial_battery_wh: float
+    idle_power_w: float
+    imaging_power_w: float
+    slew_power_w: float
+    sunlit_charge_power_w: float
+@dataclass(frozen=True)
+class SatelliteDef:
+    satellite_id: str
+    norad_catalog_id: int
+    tle_line1: str
+    tle_line2: str
+    sensor: Sensor
+    attitude_model: AttitudeModel
+    resource_model: ResourceModel
+@dataclass(frozen=True)
+class TaskDef:
+    task_id: str
+    name: str
+    latitude_deg: float
+    longitude_deg: float
+    altitude_m: float
+    release_time: datetime
+    due_time: datetime
+    required_duration_s: int
+    required_sensor_type: str
+    weight: float
+    target_ecef_m: np.ndarray
+@dataclass(frozen=True)
+class AeosspCase:
+    case_dir: Path
+    mission: Mission
+    satellites: dict[str, SatelliteDef]
+    tasks: dict[str, TaskDef]
+@dataclass(frozen=True)
+class ObservationAction:
+    satellite_id: str
+    task_id: str
+    start_time: datetime
+    end_time: datetime
+    @property
+    def duration_s(self) -> int:
+        seconds = (self.end_time - self.start_time).total_seconds()
+        if abs(seconds - round(seconds)) > NUMERICAL_EPS:
+            raise ValueError("Action duration must be an integer number of seconds")
+        return int(round(seconds))
+@dataclass(frozen=True)
+class AeosspSolution:
+    actions: list[ObservationAction]
+@dataclass(frozen=True)
+class ActionFailure:
+    action_index: int
+    satellite_id: str
+    task_id: str
+    reason: str
+    stage: str
+    time: datetime | None = None
+    def as_dict(self) -> dict[str, Any]:
+        return {
+            "action_index": self.action_index,
+            "satellite_id": self.satellite_id,
+            "task_id": self.task_id,
+            "reason": self.reason,
+            "stage": self.stage,
+            "time": self.time.astimezone(UTC).isoformat().replace("+00:00", "Z")
+            if self.time is not None
+            else None,
+        }
+@dataclass(frozen=True)
+class ManeuverWindow:
+    action_index: int
+    satellite_id: str
+    start_time: datetime
+    end_time: datetime
+    required_gap_s: float
+    slew_angle_deg: float
+    from_action_index: int | None
+    from_task_id: str | None
+    to_task_id: str
+    def as_dict(self) -> dict[str, Any]:
+        return {
+            "action_index": self.action_index,
+            "satellite_id": self.satellite_id,
+            "start_time": self.start_time.astimezone(UTC).isoformat().replace("+00:00", "Z"),
+            "end_time": self.end_time.astimezone(UTC).isoformat().replace("+00:00", "Z"),
+            "required_gap_s": self.required_gap_s,
+            "slew_angle_deg": self.slew_angle_deg,
+            "from_action_index": self.from_action_index,
+            "from_task_id": self.from_task_id,
+            "to_task_id": self.to_task_id,
+        }
+@dataclass(frozen=True)
+class ValidatedAction:
+    action_index: int
+    satellite_id: str
+    task_id: str
+    start_time: datetime
+    end_time: datetime
+    @property
+    def duration_s(self) -> int:
+        seconds = (self.end_time - self.start_time).total_seconds()
+        return int(round(seconds))
+    def as_dict(self) -> dict[str, Any]:
+        return {
+            "action_index": self.action_index,
+            "satellite_id": self.satellite_id,
+            "task_id": self.task_id,
+            "start_time": self.start_time.astimezone(UTC).isoformat().replace("+00:00", "Z"),
+            "end_time": self.end_time.astimezone(UTC).isoformat().replace("+00:00", "Z"),
+            "duration_s": self.duration_s,
+        }
+@dataclass(frozen=True)
+class TaskOutcome:
+    task_id: str
+    completed: bool
+    completion_time: datetime | None
+    completed_by_action_index: int | None
+    weight: float
+    def as_dict(self) -> dict[str, Any]:
+        return {
+            "task_id": self.task_id,
+            "completed": self.completed,
+            "completion_time": self.completion_time.astimezone(UTC).isoformat().replace("+00:00", "Z")
+            if self.completion_time is not None
+            else None,
+            "completed_by_action_index": self.completed_by_action_index,
+            "weight": self.weight,
+        }
+@dataclass(frozen=True)
+class BatteryTraceSegment:
+    satellite_id: str
+    start_time: datetime
+    end_time: datetime
+    battery_start_wh: float
+    battery_end_wh: float
+    load_power_w: float
+    charge_power_w: float
+    mode: str
+    active_action_index: int | None
+    active_task_id: str | None
+    active_maneuver_to_action_index: int | None
+    def as_dict(self) -> dict[str, Any]:
+        return {
+            "satellite_id": self.satellite_id,
+            "start_time": self.start_time.astimezone(UTC).isoformat().replace("+00:00", "Z"),
+            "end_time": self.end_time.astimezone(UTC).isoformat().replace("+00:00", "Z"),
+            "battery_start_wh": self.battery_start_wh,
+            "battery_end_wh": self.battery_end_wh,
+            "load_power_w": self.load_power_w,
+            "charge_power_w": self.charge_power_w,
+            "mode": self.mode,
+            "active_action_index": self.active_action_index,
+            "active_task_id": self.active_task_id,
+            "active_maneuver_to_action_index": self.active_maneuver_to_action_index,
+        }
+@dataclass(frozen=True)
+class TimelineEvent:
+    time: datetime
+    satellite_id: str
+    kind: str
+    action_index: int | None = None
+    task_id: str | None = None
+    detail: str | None = None
+    def as_dict(self) -> dict[str, Any]:
+        return {
+            "time": self.time.astimezone(UTC).isoformat().replace("+00:00", "Z"),
+            "satellite_id": self.satellite_id,
+            "kind": self.kind,
+            "action_index": self.action_index,
+            "task_id": self.task_id,
+            "detail": self.detail,
+        }
+@dataclass(frozen=True)
+class VerificationResult:
+    valid: bool
+    metrics: dict[str, Any]
+    violations: list[str]
+    diagnostics: dict[str, Any]
+    def to_dict(self) -> dict[str, Any]:
+        return {
+            "valid": self.valid,
+            "metrics": self.metrics,
+            "violations": self.violations,
+            "diagnostics": self.diagnostics,
+        }
+    def __str__(self) -> str:  # pragma: no cover - convenience helper
+        return json.dumps(self.to_dict(), indent=2, sort_keys=True)
+@dataclass(frozen=True)
+class SolutionAnalysis:
+    case: AeosspCase
+    solution: AeosspSolution
+    result: VerificationResult
+    validated_actions: tuple[ValidatedAction, ...]
+    action_failures: tuple[ActionFailure, ...]
+    maneuver_windows: tuple[ManeuverWindow, ...]
+    task_outcomes: dict[str, TaskOutcome]
+    battery_traces: dict[str, tuple[BatteryTraceSegment, ...]] = field(repr=False)
+    per_satellite_resource_summary: dict[str, Any]
+    timeline_events: tuple[TimelineEvent, ...]
+    snapshot_candidates: tuple[datetime, ...]

tasks/aeossp_standard-test-case_0001/tests/benchmarks/aeossp_standard/verifier/run.py ADDED Viewed

	@@ -0,0 +1,39 @@

+"""CLI entrypoint for the aeossp_standard verifier."""
+from __future__ import annotations
+import argparse
+import json
+from .engine import verify_solution
+def build_parser() -> argparse.ArgumentParser:
+    parser = argparse.ArgumentParser(
+        description="Verify aeossp_standard observation schedules against a canonical case.",
+    )
+    parser.add_argument("case_dir", help="Path to one canonical case directory")
+    parser.add_argument("solution_path", help="Path to a single-case solution JSON file")
+    return parser
+def main(argv: list[str] | None = None) -> int:
+    args = build_parser().parse_args(argv)
+    result = verify_solution(args.case_dir, args.solution_path)
+    print(
+        json.dumps(
+            {
+                "valid": result.valid,
+                "metrics": result.metrics,
+                "violations": result.violations,
+                "diagnostics": result.diagnostics,
+            },
+            indent=2,
+            sort_keys=True,
+        )
+    )
+    return 0 if result.valid else 1
+if __name__ == "__main__":
+    raise SystemExit(main())

tasks/aeossp_standard-test-case_0001/tests/case/mission.yaml ADDED Viewed

	@@ -0,0 +1,24 @@

+mission:
+  case_id: case_0001
+  horizon_start: '2026-04-14T04:00:00Z'
+  horizon_end: '2026-04-14T16:00:00Z'
+  action_time_step_s: 5
+  geometry_sample_step_s: 5
+  resource_sample_step_s: 10
+  propagation:
+    model: sgp4
+    frame_inertial: gcrf
+    frame_fixed: itrf
+    earth_shape: wgs84
+  scoring:
+    ranking_order:
+    - valid
+    - WCR
+    - CR
+    - TAT
+    - PC
+    reported_metrics:
+    - CR
+    - WCR
+    - TAT
+    - PC

tasks/aeossp_standard-test-case_0001/tests/case/satellites.yaml ADDED Viewed

	@@ -0,0 +1,361 @@

+satellites:
+- satellite_id: sat_001
+  norad_catalog_id: 28051
+  tle_line1: 1 28051U 03046A   26103.92936350  .00000126  00000+0  55914-4 0  9994
+  tle_line2: 2 28051  98.1985 143.5711 0064246 173.9227 286.4737 14.36137850171300
+  sensor:
+    sensor_type: visible
+  attitude_model:
+    max_slew_velocity_deg_per_s: 1.8
+    max_slew_acceleration_deg_per_s2: 0.4
+    settling_time_s: 2.0
+    max_off_nadir_deg: 30.0
+  resource_model:
+    battery_capacity_wh: 1300.0
+    initial_battery_wh: 800.0
+    idle_power_w: 20.0
+    imaging_power_w: 420.0
+    slew_power_w: 360.0
+    sunlit_charge_power_w: 85.0
+- satellite_id: sat_002
+  norad_catalog_id: 32783
+  tle_line1: 1 32783U 08021A   26103.91837750  .00000562  00000+0  82530-4 0  9990
+  tle_line2: 2 32783  97.7709 154.8031 0010967 327.3165  32.7367 14.79161859969302
+  sensor:
+    sensor_type: visible
+  attitude_model:
+    max_slew_velocity_deg_per_s: 1.0
+    max_slew_acceleration_deg_per_s2: 0.25
+    settling_time_s: 3.0
+    max_off_nadir_deg: 25.0
+  resource_model:
+    battery_capacity_wh: 1600.0
+    initial_battery_wh: 1000.0
+    idle_power_w: 25.0
+    imaging_power_w: 480.0
+    slew_power_w: 280.0
+    sunlit_charge_power_w: 100.0
+- satellite_id: sat_003
+  norad_catalog_id: 33396
+  tle_line1: 1 33396U 08049A   26103.92431574  .00000228  00000+0  12693-3 0  9997
+  tle_line2: 2 33396  98.5635 163.2775 0001215  96.0005 264.1311 14.20124562908846
+  sensor:
+    sensor_type: visible
+  attitude_model:
+    max_slew_velocity_deg_per_s: 1.8
+    max_slew_acceleration_deg_per_s2: 0.4
+    settling_time_s: 2.0
+    max_off_nadir_deg: 30.0
+  resource_model:
+    battery_capacity_wh: 1300.0
+    initial_battery_wh: 800.0
+    idle_power_w: 20.0
+    imaging_power_w: 420.0
+    slew_power_w: 360.0
+    sunlit_charge_power_w: 85.0
+- satellite_id: sat_004
+  norad_catalog_id: 35681
+  tle_line1: 1 35681U 09041A   26103.88486025  .00000736  00000+0  11600-3 0  9996
+  tle_line2: 2 35681  97.7323 263.9278 0002534  65.1442 295.0031 14.75171584897400
+  sensor:
+    sensor_type: visible
+  attitude_model:
+    max_slew_velocity_deg_per_s: 1.0
+    max_slew_acceleration_deg_per_s2: 0.25
+    settling_time_s: 3.0
+    max_off_nadir_deg: 25.0
+  resource_model:
+    battery_capacity_wh: 1600.0
+    initial_battery_wh: 1000.0
+    idle_power_w: 25.0
+    imaging_power_w: 480.0
+    slew_power_w: 280.0
+    sunlit_charge_power_w: 100.0
+- satellite_id: sat_005
+  norad_catalog_id: 37387
+  tle_line1: 1 37387U 11015A   26103.89999973 -.00000252  00000+0 -94795-4 0  9999
+  tle_line2: 2 37387  98.7689 171.7738 0012401  84.9704 275.2889 14.21615505777047
+  sensor:
+    sensor_type: visible
+  attitude_model:
+    max_slew_velocity_deg_per_s: 1.0
+    max_slew_acceleration_deg_per_s2: 0.25
+    settling_time_s: 3.0
+    max_off_nadir_deg: 25.0
+  resource_model:
+    battery_capacity_wh: 1600.0
+    initial_battery_wh: 1000.0
+    idle_power_w: 25.0
+    imaging_power_w: 480.0
+    slew_power_w: 280.0
+    sunlit_charge_power_w: 100.0
+- satellite_id: sat_006
+  norad_catalog_id: 38012
+  tle_line1: 1 38012U 11076F   26103.92452051  .00000031  00000+0  16420-4 0  9999
+  tle_line2: 2 38012  98.1996 179.8836 0001241  74.0617  41.3226 14.58569444762624
+  sensor:
+    sensor_type: visible
+  attitude_model:
+    max_slew_velocity_deg_per_s: 1.0
+    max_slew_acceleration_deg_per_s2: 0.25
+    settling_time_s: 3.0
+    max_off_nadir_deg: 25.0
+  resource_model:
+    battery_capacity_wh: 1600.0
+    initial_battery_wh: 1000.0
+    idle_power_w: 25.0
+    imaging_power_w: 480.0
+    slew_power_w: 280.0
+    sunlit_charge_power_w: 100.0
+- satellite_id: sat_007
+  norad_catalog_id: 39019
+  tle_line1: 1 39019U 12068A   26103.93709536  .00000156  00000+0  43477-4 0  9993
+  tle_line2: 2 39019  98.1967 179.8664 0001151  77.9509 282.1820 14.58557094711482
+  sensor:
+    sensor_type: infrared
+  attitude_model:
+    max_slew_velocity_deg_per_s: 0.9
+    max_slew_acceleration_deg_per_s2: 0.15
+    settling_time_s: 3.5
+    max_off_nadir_deg: 20.0
+  resource_model:
+    battery_capacity_wh: 1800.0
+    initial_battery_wh: 1000.0
+    idle_power_w: 30.0
+    imaging_power_w: 680.0
+    slew_power_w: 320.0
+    sunlit_charge_power_w: 115.0
+- satellite_id: sat_008
+  norad_catalog_id: 39084
+  tle_line1: 1 39084U 13008A   26103.95632536  .00000202  00000+0  54735-4 0  9998
+  tle_line2: 2 39084  98.1863 175.0919 0001171  93.9204 266.2128 14.57117273688546
+  sensor:
+    sensor_type: visible
+  attitude_model:
+    max_slew_velocity_deg_per_s: 1.0
+    max_slew_acceleration_deg_per_s2: 0.25
+    settling_time_s: 3.0
+    max_off_nadir_deg: 25.0
+  resource_model:
+    battery_capacity_wh: 1600.0
+    initial_battery_wh: 1000.0
+    idle_power_w: 25.0
+    imaging_power_w: 480.0
+    slew_power_w: 280.0
+    sunlit_charge_power_w: 100.0
+- satellite_id: sat_009
+  norad_catalog_id: 40013
+  tle_line1: 1 40013U 14033D   26103.93736737  .00001307  00000+0  12918-3 0  9990
+  tle_line2: 2 40013  97.5922 340.6596 0001765 111.5119 248.6289 14.93547723628139
+  sensor:
+    sensor_type: visible
+  attitude_model:
+    max_slew_velocity_deg_per_s: 1.8
+    max_slew_acceleration_deg_per_s2: 0.4
+    settling_time_s: 2.0
+    max_off_nadir_deg: 30.0
+  resource_model:
+    battery_capacity_wh: 1300.0
+    initial_battery_wh: 800.0
+    idle_power_w: 20.0
+    imaging_power_w: 420.0
+    slew_power_w: 360.0
+    sunlit_charge_power_w: 85.0
+- satellite_id: sat_010
+  norad_catalog_id: 42063
+  tle_line1: 1 42063U 17013A   26103.94175150 -.00000047  00000+0 -13025-5 0  9999
+  tle_line2: 2 42063  98.5661 179.6296 0001235  93.6242 266.5083 14.30820285475457
+  sensor:
+    sensor_type: visible
+  attitude_model:
+    max_slew_velocity_deg_per_s: 1.0
+    max_slew_acceleration_deg_per_s2: 0.25
+    settling_time_s: 3.0
+    max_off_nadir_deg: 25.0
+  resource_model:
+    battery_capacity_wh: 1600.0
+    initial_battery_wh: 1000.0
+    idle_power_w: 25.0
+    imaging_power_w: 480.0
+    slew_power_w: 280.0
+    sunlit_charge_power_w: 100.0
+- satellite_id: sat_011
+  norad_catalog_id: 42988
+  tle_line1: 1 42988U 17068B   26103.65081329  .00006062  00000+0  18960-3 0  9999
+  tle_line2: 2 42988  97.4398 239.9634 0001252 115.0478 245.0894 15.33517382472468
+  sensor:
+    sensor_type: infrared
+  attitude_model:
+    max_slew_velocity_deg_per_s: 0.9
+    max_slew_acceleration_deg_per_s2: 0.15
+    settling_time_s: 3.5
+    max_off_nadir_deg: 20.0
+  resource_model:
+    battery_capacity_wh: 1800.0
+    initial_battery_wh: 1000.0
+    idle_power_w: 30.0
+    imaging_power_w: 680.0
+    slew_power_w: 320.0
+    sunlit_charge_power_w: 115.0
+- satellite_id: sat_012
+  norad_catalog_id: 42991
+  tle_line1: 1 42991U 17068E   26103.83844932  .00006341  00000+0  18525-3 0  9997
+  tle_line2: 2 42991  97.4427 240.6998 0005447 348.9947  11.1177 15.35651042472498
+  sensor:
+    sensor_type: visible
+  attitude_model:
+    max_slew_velocity_deg_per_s: 1.0
+    max_slew_acceleration_deg_per_s2: 0.25
+    settling_time_s: 3.0
+    max_off_nadir_deg: 25.0
+  resource_model:
+    battery_capacity_wh: 1600.0
+    initial_battery_wh: 1000.0
+    idle_power_w: 25.0
+    imaging_power_w: 480.0
+    slew_power_w: 280.0
+    sunlit_charge_power_w: 100.0
+- satellite_id: sat_013
+  norad_catalog_id: 43111
+  tle_line1: 1 43111U 18004A   26104.12260037  .00002784  00000+0  13508-3 0  9997
+  tle_line2: 2 43111  97.4095 164.6288 0002452 119.7879 240.3599 15.19306551457606
+  sensor:
+    sensor_type: visible
+  attitude_model:
+    max_slew_velocity_deg_per_s: 1.8
+    max_slew_acceleration_deg_per_s2: 0.4
+    settling_time_s: 2.0
+    max_off_nadir_deg: 30.0
+  resource_model:
+    battery_capacity_wh: 1300.0
+    initial_battery_wh: 800.0
+    idle_power_w: 20.0
+    imaging_power_w: 420.0
+    slew_power_w: 360.0
+    sunlit_charge_power_w: 85.0
+- satellite_id: sat_014
+  norad_catalog_id: 43259
+  tle_line1: 1 43259U 18031A   26104.11950488  .00000002  00000+0  76800-5 0  9992
+  tle_line2: 2 43259  98.0579 166.8090 0002685 187.3457 172.7713 14.76430187433244
+  sensor:
+    sensor_type: visible
+  attitude_model:
+    max_slew_velocity_deg_per_s: 1.0
+    max_slew_acceleration_deg_per_s2: 0.25
+    settling_time_s: 3.0
+    max_off_nadir_deg: 25.0
+  resource_model:
+    battery_capacity_wh: 1600.0
+    initial_battery_wh: 1000.0
+    idle_power_w: 25.0
+    imaging_power_w: 480.0
+    slew_power_w: 280.0
+    sunlit_charge_power_w: 100.0
+- satellite_id: sat_015
+  norad_catalog_id: 43260
+  tle_line1: 1 43260U 18031B   26104.16530807  .00000436  00000+0  70146-4 0  9995
+  tle_line2: 2 43260  98.0571 166.7195 0001054 283.4938  76.6154 14.76417197433241
+  sensor:
+    sensor_type: infrared
+  attitude_model:
+    max_slew_velocity_deg_per_s: 0.9
+    max_slew_acceleration_deg_per_s2: 0.15
+    settling_time_s: 3.5
+    max_off_nadir_deg: 20.0
+  resource_model:
+    battery_capacity_wh: 1800.0
+    initial_battery_wh: 1000.0
+    idle_power_w: 30.0
+    imaging_power_w: 680.0
+    slew_power_w: 320.0
+    sunlit_charge_power_w: 115.0
+- satellite_id: sat_016
+  norad_catalog_id: 43262
+  tle_line1: 1 43262U 18031D   26103.93793093  .00000573  00000+0  89849-4 0  9991
+  tle_line2: 2 43262  98.0583 166.6754 0000885  62.3940 297.7360 14.76451671433200
+  sensor:
+    sensor_type: visible
+  attitude_model:
+    max_slew_velocity_deg_per_s: 1.0
+    max_slew_acceleration_deg_per_s2: 0.25
+    settling_time_s: 3.0
+    max_off_nadir_deg: 25.0
+  resource_model:
+    battery_capacity_wh: 1600.0
+    initial_battery_wh: 1000.0
+    idle_power_w: 25.0
+    imaging_power_w: 480.0
+    slew_power_w: 280.0
+    sunlit_charge_power_w: 100.0
+- satellite_id: sat_017
+  norad_catalog_id: 48079
+  tle_line1: 1 48079U 21026A   26103.94185373  .00000257  00000+0  40677-4 0  9992
+  tle_line2: 2 48079  97.9928 102.3896 0006302  84.5923 275.6008 14.80244388272253
+  sensor:
+    sensor_type: infrared
+  attitude_model:
+    max_slew_velocity_deg_per_s: 0.9
+    max_slew_acceleration_deg_per_s2: 0.15
+    settling_time_s: 3.5
+    max_off_nadir_deg: 20.0
+  resource_model:
+    battery_capacity_wh: 1800.0
+    initial_battery_wh: 1000.0
+    idle_power_w: 30.0
+    imaging_power_w: 680.0
+    slew_power_w: 320.0
+    sunlit_charge_power_w: 115.0
+- satellite_id: sat_018
+  norad_catalog_id: 48268
+  tle_line1: 1 48268U 21034A   26103.96224166 -.00000034  00000+0  22549-5 0  9990
+  tle_line2: 2 48268  97.8933 179.6508 0001284  93.5777 266.5583 14.81672073268143
+  sensor:
+    sensor_type: visible
+  attitude_model:
+    max_slew_velocity_deg_per_s: 1.8
+    max_slew_acceleration_deg_per_s2: 0.4
+    settling_time_s: 2.0
+    max_off_nadir_deg: 30.0
+  resource_model:
+    battery_capacity_wh: 1300.0
+    initial_battery_wh: 800.0
+    idle_power_w: 20.0
+    imaging_power_w: 420.0
+    slew_power_w: 360.0
+    sunlit_charge_power_w: 85.0
+- satellite_id: sat_019
+  norad_catalog_id: 52912
+  tle_line1: 1 52912U 22069A   26103.95907240  .00000113  00000+0  21656-4 0  9994
+  tle_line2: 2 52912  97.8359 353.4264 0001854  52.2815 307.8565 14.79930234205115
+  sensor:
+    sensor_type: visible
+  attitude_model:
+    max_slew_velocity_deg_per_s: 1.8
+    max_slew_acceleration_deg_per_s2: 0.4
+    settling_time_s: 2.0
+    max_off_nadir_deg: 30.0
+  resource_model:
+    battery_capacity_wh: 1300.0
+    initial_battery_wh: 800.0
+    idle_power_w: 20.0
+    imaging_power_w: 420.0
+    slew_power_w: 360.0
+    sunlit_charge_power_w: 85.0
+- satellite_id: sat_020
+  norad_catalog_id: 60989
+  tle_line1: 1 60989U 24157A   26103.90679551  .00000060  00000+0  39456-4 0  9991
+  tle_line2: 2 60989  98.5642 179.6103 0001350 108.6675 251.4655 14.30813258 83797
+  sensor:
+    sensor_type: visible
+  attitude_model:
+    max_slew_velocity_deg_per_s: 1.0
+    max_slew_acceleration_deg_per_s2: 0.25
+    settling_time_s: 3.0
+    max_off_nadir_deg: 25.0
+  resource_model:
+    battery_capacity_wh: 1600.0
+    initial_battery_wh: 1000.0
+    idle_power_w: 25.0
+    imaging_power_w: 480.0
+    slew_power_w: 280.0
+    sunlit_charge_power_w: 100.0

tasks/aeossp_standard-test-case_0001/tests/case/tasks.yaml ADDED Viewed

The diff for this file is too large to render. See raw diff

tasks/aeossp_standard-test-case_0001/tests/profile.json ADDED Viewed

	@@ -0,0 +1,34 @@

+{
+  "benchmark": "aeossp_standard",
+  "metrics": [
+    {
+      "name": "WCR",
+      "path": "metrics.WCR",
+      "direction": "maximize",
+      "role": "primary"
+    },
+    {
+      "name": "CR",
+      "path": "metrics.CR",
+      "direction": "maximize",
+      "role": "secondary"
+    },
+    {
+      "name": "TAT",
+      "path": "metrics.TAT",
+      "direction": "minimize",
+      "role": "secondary"
+    },
+    {
+      "name": "PC",
+      "path": "metrics.PC",
+      "direction": "minimize",
+      "role": "secondary"
+    }
+  ],
+  "solution_filename": "solution.json",
+  "verifier_command": [
+    "-m",
+    "benchmarks.aeossp_standard.verifier.run"
+  ]
+}

tasks/aeossp_standard-test-case_0001/tests/score.py ADDED Viewed

	@@ -0,0 +1,84 @@

+"""Call an unmodified benchmark verifier and expose its native metrics to Harbor."""
+from __future__ import annotations
+import argparse
+import json
+import math
+from pathlib import Path
+import re
+import shutil
+import subprocess
+import sys
+TEXT_METRICS = {
+    "spot5": {"computed_profit": "Computed Profit", "computed_weight": "Computed Weight", "computed_selected": "Selected Photos"},
+    "satnet": {"score_hours": "Total tracking hours", "n_tracks": "Tracks", "n_satisfied_requests": "Satisfied requests", "u_rms": "U_rms", "u_max": "U_max"},
+}
+def parse_report(benchmark: str, stdout: str, returncode: int) -> dict:
+    if returncode not in (0, 1):
+        raise RuntimeError(f"Verifier exited with {returncode}; inspect verifier.stderr")
+    if benchmark in TEXT_METRICS:
+        status = re.search(r"^Status:\s*(VALID|INVALID)\s*$", stdout, re.MULTILINE)
+        if status is None:
+            raise ValueError("Verifier output has no validity status")
+        metrics = {}
+        for name, label in TEXT_METRICS[benchmark].items():
+            match = re.search(rf"^{re.escape(label)}:\s*([-+\d.eE]+)", stdout, re.MULTILINE)
+            if match is None:
+                raise ValueError(f"Verifier output has no {label}")
+            metrics[name] = float(match.group(1))
+        report = {"valid": status.group(1) == "VALID", "metrics": metrics}
+    else:
+        report = json.loads(stdout)
+        if benchmark == "revisit_constellation":
+            report["valid"] = report["is_valid"]
+    if type(report.get("valid")) is not bool or not isinstance(report.get("metrics"), dict):
+        raise ValueError("Verifier output must contain valid and metrics")
+    if report["valid"] != (returncode == 0):
+        raise ValueError("Verifier validity and exit status disagree")
+    return report
+def score(task_tests: Path, solution_dir: Path, output: Path) -> dict:
+    profile = json.loads((task_tests / "profile.json").read_text())
+    benchmark = profile["benchmark"]
+    output.mkdir(parents=True, exist_ok=True)
+    shutil.copyfile(task_tests / "task-config.json", output / "task-config.json")
+    # One required filename makes missing/ambiguous submissions explicit.
+    solution = solution_dir / profile["solution_filename"]
+    if not solution.is_file():
+        report = {"valid": False, "metrics": {}, "errors": [f"Missing {solution.name}"], "status": "missing_solution"}
+    else:
+        command = [sys.executable, *profile["verifier_command"], str(task_tests / "case"), str(solution.resolve())]
+        if benchmark in TEXT_METRICS:
+            command.append("--verbose")
+        result = subprocess.run(command, cwd=task_tests, capture_output=True, text=True)
+        (output / "verifier.stdout").write_text(result.stdout)
+        (output / "verifier.stderr").write_text(result.stderr)
+        report = parse_report(benchmark, result.stdout, result.returncode)
+        report["status"] = "valid" if report["valid"] else "invalid"
+    (output / "report.json").write_text(json.dumps(report, indent=2, allow_nan=False) + "\n")
+    rewards = {"valid": float(report["valid"])}
+    for metric in profile["metrics"]:
+        value = report["metrics"].get(metric["name"])
+        if isinstance(value, (int, float)) and not isinstance(value, bool) and math.isfinite(value):
+            rewards[f"{benchmark}/{metric['name']}"] = value
+    (output / "reward.json").write_text(json.dumps(rewards, indent=2, allow_nan=False) + "\n")
+    return report
+def main() -> None:
+    parser = argparse.ArgumentParser(description=__doc__)
+    parser.add_argument("--tests", type=Path, default=Path("/tests"))
+    parser.add_argument("--solution", type=Path, default=Path("/workspace/solution"))
+    parser.add_argument("--output", type=Path, default=Path("/logs/verifier"))
+    args = parser.parse_args()
+    score(args.tests.resolve(), args.solution.resolve(), args.output.resolve())
+if __name__ == "__main__":
+    main()

tasks/aeossp_standard-test-case_0001/tests/task-config.json ADDED Viewed

	@@ -0,0 +1,36 @@

+{
+  "schema_version": "1.3",
+  "artifacts": [
+    {
+      "source": "/workspace/solution",
+      "destination": "solution"
+    }
+  ],
+  "task": {
+    "name": "astroagentbench/aeossp_standard-test-case_0001"
+  },
+  "metadata": {
+    "benchmark": "aeossp_standard",
+    "split": "test",
+    "case_id": "case_0001",
+    "source_commit": "6f5b9d21b1efb2ca2ee6fcabdc338a9d077612cb",
+    "source_dirty": false,
+    "case_sha256": "81213315b8f4e84e07479e8048313c9102928c829bce1054cfad4ca58c84dcc4",
+    "verifier_sha256": "a5372c13197394134bf55297a1d04ec8d0610f4fd22e2ec7b247e21c6fa0db9a",
+    "runtime_image": "ghcr.io/mtrya/astroagentbench-python@sha256:fe9733cad55519aa08dd0db9abb51444051ef5f53d6ac1ef0b4b6592491437d1",
+    "solution_filename": "solution.json"
+  },
+  "environment": {
+    "cpus": 8,
+    "memory_mb": 16384,
+    "storage_mb": 10240,
+    "network_mode": "public"
+  },
+  "agent": {
+    "timeout_sec": 7200
+  },
+  "verifier": {
+    "environment_mode": "separate",
+    "timeout_sec": 600
+  }
+}

tasks/aeossp_standard-test-case_0001/tests/test.sh ADDED Viewed

	@@ -0,0 +1,3 @@

+#!/bin/bash
+set -euo pipefail
+python /tests/score.py

tasks/aeossp_standard-test-case_0002/environment/Dockerfile ADDED Viewed

	@@ -0,0 +1,4 @@

+FROM ghcr.io/mtrya/astroagentbench-python@sha256:fe9733cad55519aa08dd0db9abb51444051ef5f53d6ac1ef0b4b6592491437d1
+WORKDIR /workspace
+COPY case /workspace/case
+RUN mkdir -p /workspace/solution

tasks/aeossp_standard-test-case_0002/environment/case/mission.yaml ADDED Viewed

	@@ -0,0 +1,24 @@

+mission:
+  case_id: case_0002
+  horizon_start: '2026-04-14T06:00:00Z'
+  horizon_end: '2026-04-14T18:00:00Z'
+  action_time_step_s: 5
+  geometry_sample_step_s: 5
+  resource_sample_step_s: 10
+  propagation:
+    model: sgp4
+    frame_inertial: gcrf
+    frame_fixed: itrf
+    earth_shape: wgs84
+  scoring:
+    ranking_order:
+    - valid
+    - WCR
+    - CR
+    - TAT
+    - PC
+    reported_metrics:
+    - CR
+    - WCR
+    - TAT
+    - PC

tasks/aeossp_standard-test-case_0002/environment/case/satellites.yaml ADDED Viewed

	@@ -0,0 +1,433 @@

+satellites:
+- satellite_id: sat_001
+  norad_catalog_id: 28051
+  tle_line1: 1 28051U 03046A   26103.92936350  .00000126  00000+0  55914-4 0  9994
+  tle_line2: 2 28051  98.1985 143.5711 0064246 173.9227 286.4737 14.36137850171300
+  sensor:
+    sensor_type: infrared
+  attitude_model:
+    max_slew_velocity_deg_per_s: 0.9
+    max_slew_acceleration_deg_per_s2: 0.15
+    settling_time_s: 3.5
+    max_off_nadir_deg: 20.0
+  resource_model:
+    battery_capacity_wh: 1800.0
+    initial_battery_wh: 1000.0
+    idle_power_w: 30.0
+    imaging_power_w: 680.0
+    slew_power_w: 320.0
+    sunlit_charge_power_w: 115.0
+- satellite_id: sat_002
+  norad_catalog_id: 28649
+  tle_line1: 1 28649U 05017A   26103.78459344  .00000718  00000+0  78137-4 0  9993
+  tle_line2: 2 28649  97.5369 129.7615 0000594  88.5323 271.5964 14.90885377134226
+  sensor:
+    sensor_type: visible
+  attitude_model:
+    max_slew_velocity_deg_per_s: 1.8
+    max_slew_acceleration_deg_per_s2: 0.4
+    settling_time_s: 2.0
+    max_off_nadir_deg: 30.0
+  resource_model:
+    battery_capacity_wh: 1300.0
+    initial_battery_wh: 800.0
+    idle_power_w: 20.0
+    imaging_power_w: 420.0
+    slew_power_w: 360.0
+    sunlit_charge_power_w: 85.0
+- satellite_id: sat_003
+  norad_catalog_id: 32783
+  tle_line1: 1 32783U 08021A   26103.91837750  .00000562  00000+0  82530-4 0  9990
+  tle_line2: 2 32783  97.7709 154.8031 0010967 327.3165  32.7367 14.79161859969302
+  sensor:
+    sensor_type: visible
+  attitude_model:
+    max_slew_velocity_deg_per_s: 1.0
+    max_slew_acceleration_deg_per_s2: 0.25
+    settling_time_s: 3.0
+    max_off_nadir_deg: 25.0
+  resource_model:
+    battery_capacity_wh: 1600.0
+    initial_battery_wh: 1000.0
+    idle_power_w: 25.0
+    imaging_power_w: 480.0
+    slew_power_w: 280.0
+    sunlit_charge_power_w: 100.0
+- satellite_id: sat_004
+  norad_catalog_id: 33396
+  tle_line1: 1 33396U 08049A   26103.92431574  .00000228  00000+0  12693-3 0  9997
+  tle_line2: 2 33396  98.5635 163.2775 0001215  96.0005 264.1311 14.20124562908846
+  sensor:
+    sensor_type: visible
+  attitude_model:
+    max_slew_velocity_deg_per_s: 1.0
+    max_slew_acceleration_deg_per_s2: 0.25
+    settling_time_s: 3.0
+    max_off_nadir_deg: 25.0
+  resource_model:
+    battery_capacity_wh: 1600.0
+    initial_battery_wh: 1000.0
+    idle_power_w: 25.0
+    imaging_power_w: 480.0
+    slew_power_w: 280.0
+    sunlit_charge_power_w: 100.0
+- satellite_id: sat_005
+  norad_catalog_id: 36795
+  tle_line1: 1 36795U 10035A   26103.91725973  .00000606  00000+0  89742-4 0  9999
+  tle_line2: 2 36795  98.0028 154.8560 0012216  44.0868 316.1314 14.78652641850354
+  sensor:
+    sensor_type: visible
+  attitude_model:
+    max_slew_velocity_deg_per_s: 1.0
+    max_slew_acceleration_deg_per_s2: 0.25
+    settling_time_s: 3.0
+    max_off_nadir_deg: 25.0
+  resource_model:
+    battery_capacity_wh: 1600.0
+    initial_battery_wh: 1000.0
+    idle_power_w: 25.0
+    imaging_power_w: 480.0
+    slew_power_w: 280.0
+    sunlit_charge_power_w: 100.0
+- satellite_id: sat_006
+  norad_catalog_id: 37387
+  tle_line1: 1 37387U 11015A   26103.89999973 -.00000252  00000+0 -94795-4 0  9999
+  tle_line2: 2 37387  98.7689 171.7738 0012401  84.9704 275.2889 14.21615505777047
+  sensor:
+    sensor_type: visible
+  attitude_model:
+    max_slew_velocity_deg_per_s: 1.8
+    max_slew_acceleration_deg_per_s2: 0.4
+    settling_time_s: 2.0
+    max_off_nadir_deg: 30.0
+  resource_model:
+    battery_capacity_wh: 1300.0
+    initial_battery_wh: 800.0
+    idle_power_w: 20.0
+    imaging_power_w: 420.0
+    slew_power_w: 360.0
+    sunlit_charge_power_w: 85.0
+- satellite_id: sat_007
+  norad_catalog_id: 39084
+  tle_line1: 1 39084U 13008A   26103.95632536  .00000202  00000+0  54735-4 0  9998
+  tle_line2: 2 39084  98.1863 175.0919 0001171  93.9204 266.2128 14.57117273688546
+  sensor:
+    sensor_type: visible
+  attitude_model:
+    max_slew_velocity_deg_per_s: 1.0
+    max_slew_acceleration_deg_per_s2: 0.25
+    settling_time_s: 3.0
+    max_off_nadir_deg: 25.0
+  resource_model:
+    battery_capacity_wh: 1600.0
+    initial_battery_wh: 1000.0
+    idle_power_w: 25.0
+    imaging_power_w: 480.0
+    slew_power_w: 280.0
+    sunlit_charge_power_w: 100.0
+- satellite_id: sat_008
+  norad_catalog_id: 39418
+  tle_line1: 1 39418U 13066C   26103.89800586  .00001935  00000+0  11389-3 0  9999
+  tle_line2: 2 39418  97.3884 155.3394 0021902 172.5671 187.5889 15.12606827678767
+  sensor:
+    sensor_type: visible
+  attitude_model:
+    max_slew_velocity_deg_per_s: 1.0
+    max_slew_acceleration_deg_per_s2: 0.25
+    settling_time_s: 3.0
+    max_off_nadir_deg: 25.0
+  resource_model:
+    battery_capacity_wh: 1600.0
+    initial_battery_wh: 1000.0
+    idle_power_w: 25.0
+    imaging_power_w: 480.0
+    slew_power_w: 280.0
+    sunlit_charge_power_w: 100.0
+- satellite_id: sat_009
+  norad_catalog_id: 40013
+  tle_line1: 1 40013U 14033D   26103.93736737  .00001307  00000+0  12918-3 0  9990
+  tle_line2: 2 40013  97.5922 340.6596 0001765 111.5119 248.6289 14.93547723628139
+  sensor:
+    sensor_type: infrared
+  attitude_model:
+    max_slew_velocity_deg_per_s: 0.9
+    max_slew_acceleration_deg_per_s2: 0.15
+    settling_time_s: 3.5
+    max_off_nadir_deg: 20.0
+  resource_model:
+    battery_capacity_wh: 1800.0
+    initial_battery_wh: 1000.0
+    idle_power_w: 30.0
+    imaging_power_w: 680.0
+    slew_power_w: 320.0
+    sunlit_charge_power_w: 115.0
+- satellite_id: sat_010
+  norad_catalog_id: 40053
+  tle_line1: 1 40053U 14034A   26103.93758432  .00000121  00000+0  34006-4 0  9997
+  tle_line2: 2 40053  98.0684 168.0716 0001643  85.6600 274.4789 14.60901965627756
+  sensor:
+    sensor_type: visible
+  attitude_model:
+    max_slew_velocity_deg_per_s: 1.8
+    max_slew_acceleration_deg_per_s2: 0.4
+    settling_time_s: 2.0
+    max_off_nadir_deg: 30.0
+  resource_model:
+    battery_capacity_wh: 1300.0
+    initial_battery_wh: 800.0
+    idle_power_w: 20.0
+    imaging_power_w: 420.0
+    slew_power_w: 360.0
+    sunlit_charge_power_w: 85.0
+- satellite_id: sat_011
+  norad_catalog_id: 40118
+  tle_line1: 1 40118U 14049A   26103.98557118 -.00000071  00000+0 -23137-5 0  9998
+  tle_line2: 2 40118  98.0162 168.2418 0008785  82.4719 277.7491 14.80823040629735
+  sensor:
+    sensor_type: visible
+  attitude_model:
+    max_slew_velocity_deg_per_s: 1.0
+    max_slew_acceleration_deg_per_s2: 0.25
+    settling_time_s: 3.0
+    max_off_nadir_deg: 25.0
+  resource_model:
+    battery_capacity_wh: 1600.0
+    initial_battery_wh: 1000.0
+    idle_power_w: 25.0
+    imaging_power_w: 480.0
+    slew_power_w: 280.0
+    sunlit_charge_power_w: 100.0
+- satellite_id: sat_012
+  norad_catalog_id: 41556
+  tle_line1: 1 41556U 16033A   26103.92916150  .00003508  00000+0  15880-3 0  9999
+  tle_line2: 2 41556  97.3856 180.9285 0014429 156.8761 203.3127 15.21454593548215
+  sensor:
+    sensor_type: visible
+  attitude_model:
+    max_slew_velocity_deg_per_s: 1.0
+    max_slew_acceleration_deg_per_s2: 0.25
+    settling_time_s: 3.0
+    max_off_nadir_deg: 25.0
+  resource_model:
+    battery_capacity_wh: 1600.0
+    initial_battery_wh: 1000.0
+    idle_power_w: 25.0
+    imaging_power_w: 480.0
+    slew_power_w: 280.0
+    sunlit_charge_power_w: 100.0
+- satellite_id: sat_013
+  norad_catalog_id: 42063
+  tle_line1: 1 42063U 17013A   26103.94175150 -.00000047  00000+0 -13025-5 0  9999
+  tle_line2: 2 42063  98.5661 179.6296 0001235  93.6242 266.5083 14.30820285475457
+  sensor:
+    sensor_type: visible
+  attitude_model:
+    max_slew_velocity_deg_per_s: 1.8
+    max_slew_acceleration_deg_per_s2: 0.4
+    settling_time_s: 2.0
+    max_off_nadir_deg: 30.0
+  resource_model:
+    battery_capacity_wh: 1300.0
+    initial_battery_wh: 800.0
+    idle_power_w: 20.0
+    imaging_power_w: 420.0
+    slew_power_w: 360.0
+    sunlit_charge_power_w: 85.0
+- satellite_id: sat_014
+  norad_catalog_id: 42767
+  tle_line1: 1 42767U 17036C   26104.09092135 -.00000035  00000+0  15208-5 0  9994
+  tle_line2: 2 42767  97.4333 164.9288 0003685 154.9538 205.1876 15.19227050488418
+  sensor:
+    sensor_type: visible
+  attitude_model:
+    max_slew_velocity_deg_per_s: 1.8
+    max_slew_acceleration_deg_per_s2: 0.4
+    settling_time_s: 2.0
+    max_off_nadir_deg: 30.0
+  resource_model:
+    battery_capacity_wh: 1300.0
+    initial_battery_wh: 800.0
+    idle_power_w: 20.0
+    imaging_power_w: 420.0
+    slew_power_w: 360.0
+    sunlit_charge_power_w: 85.0
+- satellite_id: sat_015
+  norad_catalog_id: 42991
+  tle_line1: 1 42991U 17068E   26103.83844932  .00006341  00000+0  18525-3 0  9997
+  tle_line2: 2 42991  97.4427 240.6998 0005447 348.9947  11.1177 15.35651042472498
+  sensor:
+    sensor_type: infrared
+  attitude_model:
+    max_slew_velocity_deg_per_s: 0.9
+    max_slew_acceleration_deg_per_s2: 0.15
+    settling_time_s: 3.5
+    max_off_nadir_deg: 20.0
+  resource_model:
+    battery_capacity_wh: 1800.0
+    initial_battery_wh: 1000.0
+    idle_power_w: 30.0
+    imaging_power_w: 680.0
+    slew_power_w: 320.0
+    sunlit_charge_power_w: 115.0
+- satellite_id: sat_016
+  norad_catalog_id: 43259
+  tle_line1: 1 43259U 18031A   26104.11950488  .00000002  00000+0  76800-5 0  9992
+  tle_line2: 2 43259  98.0579 166.8090 0002685 187.3457 172.7713 14.76430187433244
+  sensor:
+    sensor_type: visible
+  attitude_model:
+    max_slew_velocity_deg_per_s: 1.8
+    max_slew_acceleration_deg_per_s2: 0.4
+    settling_time_s: 2.0
+    max_off_nadir_deg: 30.0
+  resource_model:
+    battery_capacity_wh: 1300.0
+    initial_battery_wh: 800.0
+    idle_power_w: 20.0
+    imaging_power_w: 420.0
+    slew_power_w: 360.0
+    sunlit_charge_power_w: 85.0
+- satellite_id: sat_017
+  norad_catalog_id: 43262
+  tle_line1: 1 43262U 18031D   26103.93793093  .00000573  00000+0  89849-4 0  9991
+  tle_line2: 2 43262  98.0583 166.6754 0000885  62.3940 297.7360 14.76451671433200
+  sensor:
+    sensor_type: visible
+  attitude_model:
+    max_slew_velocity_deg_per_s: 1.8
+    max_slew_acceleration_deg_per_s2: 0.4
+    settling_time_s: 2.0
+    max_off_nadir_deg: 30.0
+  resource_model:
+    battery_capacity_wh: 1300.0
+    initial_battery_wh: 800.0
+    idle_power_w: 20.0
+    imaging_power_w: 420.0
+    slew_power_w: 360.0
+    sunlit_charge_power_w: 85.0
+- satellite_id: sat_018
+  norad_catalog_id: 43484
+  tle_line1: 1 43484U 18048A   26103.96554721  .00000418  00000+0  66848-4 0  9993
+  tle_line2: 2 43484  97.7811 168.9881 0012819  29.3816 330.8113 14.76556691423917
+  sensor:
+    sensor_type: visible
+  attitude_model:
+    max_slew_velocity_deg_per_s: 1.8
+    max_slew_acceleration_deg_per_s2: 0.4
+    settling_time_s: 2.0
+    max_off_nadir_deg: 30.0
+  resource_model:
+    battery_capacity_wh: 1300.0
+    initial_battery_wh: 800.0
+    idle_power_w: 20.0
+    imaging_power_w: 420.0
+    slew_power_w: 360.0
+    sunlit_charge_power_w: 85.0
+- satellite_id: sat_019
+  norad_catalog_id: 44622
+  tle_line1: 1 44622U 19066A   26103.98739708  .00000848  00000+0  11127-3 0  9997
+  tle_line2: 2 44622  98.0448  57.1255 0005574   1.4726 358.6503 14.82916452352865
+  sensor:
+    sensor_type: visible
+  attitude_model:
+    max_slew_velocity_deg_per_s: 1.0
+    max_slew_acceleration_deg_per_s2: 0.25
+    settling_time_s: 3.0
+    max_off_nadir_deg: 25.0
+  resource_model:
+    battery_capacity_wh: 1600.0
+    initial_battery_wh: 1000.0
+    idle_power_w: 25.0
+    imaging_power_w: 480.0
+    slew_power_w: 280.0
+    sunlit_charge_power_w: 100.0
+- satellite_id: sat_020
+  norad_catalog_id: 44804
+  tle_line1: 1 44804U 19081A   26103.94018655  .00001352  00000+0  67366-4 0  9991
+  tle_line2: 2 44804  97.4366 166.8204 0012500  22.3961 337.7817 15.19216469353714
+  sensor:
+    sensor_type: visible
+  attitude_model:
+    max_slew_velocity_deg_per_s: 1.0
+    max_slew_acceleration_deg_per_s2: 0.25
+    settling_time_s: 3.0
+    max_off_nadir_deg: 25.0
+  resource_model:
+    battery_capacity_wh: 1600.0
+    initial_battery_wh: 1000.0
+    idle_power_w: 25.0
+    imaging_power_w: 480.0
+    slew_power_w: 280.0
+    sunlit_charge_power_w: 100.0
+- satellite_id: sat_021
+  norad_catalog_id: 48079
+  tle_line1: 1 48079U 21026A   26103.94185373  .00000257  00000+0  40677-4 0  9992
+  tle_line2: 2 48079  97.9928 102.3896 0006302  84.5923 275.6008 14.80244388272253
+  sensor:
+    sensor_type: visible
+  attitude_model:
+    max_slew_velocity_deg_per_s: 1.0
+    max_slew_acceleration_deg_per_s2: 0.25
+    settling_time_s: 3.0
+    max_off_nadir_deg: 25.0
+  resource_model:
+    battery_capacity_wh: 1600.0
+    initial_battery_wh: 1000.0
+    idle_power_w: 25.0
+    imaging_power_w: 480.0
+    slew_power_w: 280.0
+    sunlit_charge_power_w: 100.0
+- satellite_id: sat_022
+  norad_catalog_id: 48268
+  tle_line1: 1 48268U 21034A   26103.96224166 -.00000034  00000+0  22549-5 0  9990
+  tle_line2: 2 48268  97.8933 179.6508 0001284  93.5777 266.5583 14.81672073268143
+  sensor:
+    sensor_type: infrared
+  attitude_model:
+    max_slew_velocity_deg_per_s: 0.9
+    max_slew_acceleration_deg_per_s2: 0.15
+    settling_time_s: 3.5
+    max_off_nadir_deg: 20.0
+  resource_model:
+    battery_capacity_wh: 1800.0
+    initial_battery_wh: 1000.0
+    idle_power_w: 30.0
+    imaging_power_w: 680.0
+    slew_power_w: 320.0
+    sunlit_charge_power_w: 115.0
+- satellite_id: sat_023
+  norad_catalog_id: 49070
+  tle_line1: 1 49070U 21073E   26103.92847993 -.00000361  00000+0 -39215-4 0  9991
+  tle_line2: 2 49070  97.8932 179.6137 0001280  92.8039 267.3320 14.81672472251852
+  sensor:
+    sensor_type: infrared
+  attitude_model:
+    max_slew_velocity_deg_per_s: 0.9
+    max_slew_acceleration_deg_per_s2: 0.15
+    settling_time_s: 3.5
+    max_off_nadir_deg: 20.0
+  resource_model:
+    battery_capacity_wh: 1800.0
+    initial_battery_wh: 1000.0
+    idle_power_w: 30.0
+    imaging_power_w: 680.0
+    slew_power_w: 320.0
+    sunlit_charge_power_w: 115.0
+- satellite_id: sat_024
+  norad_catalog_id: 52912
+  tle_line1: 1 52912U 22069A   26103.95907240  .00000113  00000+0  21656-4 0  9994
+  tle_line2: 2 52912  97.8359 353.4264 0001854  52.2815 307.8565 14.79930234205115
+  sensor:
+    sensor_type: visible
+  attitude_model:
+    max_slew_velocity_deg_per_s: 1.0
+    max_slew_acceleration_deg_per_s2: 0.25
+    settling_time_s: 3.0
+    max_off_nadir_deg: 25.0
+  resource_model:
+    battery_capacity_wh: 1600.0
+    initial_battery_wh: 1000.0
+    idle_power_w: 25.0
+    imaging_power_w: 480.0
+    slew_power_w: 280.0
+    sunlit_charge_power_w: 100.0

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+# Agile Earth Observation Scheduling Problem
+This workspace contains one agile Earth-observation scheduling problem over a fixed mission horizon.
+You are given:
+- a mission description in `case/mission.yaml`
+- a fixed constellation with frozen orbital elements and subsystem limits in `case/satellites.yaml`
+- a set of time-windowed imaging tasks in `case/tasks.yaml`
+Your job is to produce `/workspace/solution/solution.json`, an event schedule of `observation` actions that completes as many high-value tasks as possible without violating hard timing, geometry, slew, or battery constraints.
+This problem is modeled as point-imaging scheduling on a fixed fleet. You are choosing when each satellite should spend a continuous interval observing a target, not redesigning the satellites, not changing their orbits, and not submitting low-level attitude trajectories. An action in the solution means "this satellite continuously observes this target over this interval," and the geometry, maneuver windows, and battery evolution are derived from that commitment during validation.
+## What Good Solutions Do
+A strong solution should:
+- satisfy all hard validity rules
+- complete as many high-weight tasks as possible
+- also improve overall completion rate when possible
+- avoid unnecessary lateness and wasteful power use when tie-breaking matters
+In practical terms, valid task completion matters first, especially on higher-weight tasks.
+## Files In This Workspace
+- `case/mission.yaml`: mission horizon, public time grids, and reported metric metadata
+- `case/satellites.yaml`: fixed satellites, TLEs, sensor limits, slew limits, and battery/power parameters
+- `case/tasks.yaml`: imaging requests with time windows, durations, sensor requirements, and weights
+## Expected Output
+Write one JSON object named `/workspace/solution/solution.json` in the solution directory.
+The required top-level field is:
+- `actions`
+Each action should represent one observation interval with:
+- `type`
+- `satellite_id`
+- `task_id`
+- `start_time`
+- `end_time`
+Do not submit visibility claims, maneuver windows, power traces, or completion claims. Those are derived during validation.
+## Modeling Contract
+Use SI units, degrees, and timezone-aware ISO 8601 timestamps. A trailing `Z` is the safest UTC form. `case/mission.yaml` is a top-level `mission` mapping. Let `H0 = mission.horizon_start`, `H1 = mission.horizon_end`, and `dt = mission.action_time_step_s`. Every action `start_time` and `end_time` must satisfy:
+```text
+H0 <= start_time < end_time <= H1
+(start_time - H0) / dt is an integer
+(end_time - H0) / dt is an integer
+```
+Each task in `case/tasks.yaml` has `release_time`, `due_time`, and `required_duration_s` on the same grid. A valid observation action must use `type: "observation"`, reference a known `satellite_id` and `task_id`, satisfy `release_time <= start_time` and `end_time <= due_time`, and have:
+```text
+end_time - start_time = required_duration_s
+```
+Longer or shorter observations do not partially complete the task. The satellite's `sensor.sensor_type` must exactly equal the task's `required_sensor_type`.
+The constellation is fixed by `case/satellites.yaml`. Satellite states are propagated only from each satellite's `tle_line1` and `tle_line2`; do not add satellites, change TLEs, or submit attitude trajectories. Inertial quantities use the case's GCRF convention, Earth-fixed geometry uses ITRF/ECEF, target coordinates use WGS84 geodetic `longitude_deg`, `latitude_deg`, and `altitude_m`, and Earth orientation is deterministic for a given case.
+Observation visibility is checked at `start_time`, `end_time`, and every `geometry_sample_step_s` grid instant strictly inside the action. At every checked instant, the target line of sight must be above the target local horizon and the off-nadir angle from satellite nadir to target line of sight must be no greater than `attitude_model.max_off_nadir_deg`, allowing only tiny numerical tolerance at the boundary.
+For a satellite, observation intervals are half-open for overlap purposes: `[start_time, end_time)`. Same-satellite actions must not overlap. For consecutive same-satellite observations, the required retargeting gap is computed from the angle `theta` between the previous target vector at the previous `end_time` and the next target vector at the next `start_time`, both in the inertial frame. With `omega = max_slew_velocity_deg_per_s` and `alpha = max_slew_acceleration_deg_per_s2`:
+```text
+if theta <= omega^2 / alpha:
+  slew_time_s = 2 * sqrt(theta / alpha)
+else:
+  slew_time_s = 2 * (omega / alpha) + (theta - omega^2 / alpha) / omega
+required_gap_s = slew_time_s + settling_time_s
+```
+The required gap is reserved immediately before the later observation. The solution is invalid if the available idle gap is shorter than `required_gap_s`.
+Battery feasibility is simulated for each satellite over the full mission horizon using `resource_sample_step_s` grid points plus all action and retargeting-window boundaries. Each segment uses its midpoint to decide whether an observation, retargeting window, and sunlight are active. Battery starts at `resource_model.initial_battery_wh`, is capped after each segment at `battery_capacity_wh`, and invalidates the solution if it drops below zero. Segment load is:
+```text
+load_power_w = idle_power_w
+             + imaging_power_w if the segment midpoint is inside an observation
+             + slew_power_w if the segment midpoint is inside a retargeting window
+battery_next_wh = battery_wh + (charge_power_w - load_power_w) * duration_s / 3600
+```
+`charge_power_w` is `sunlit_charge_power_w` in sunlight and `0` in eclipse. `PC` is gross consumed watt-hours summed over satellites that pass the battery check.
+Task completion is binary. For each `task_id`, the earliest valid completing observation by `end_time` counts once; duplicates do not add credit. For valid solutions:
+```text
+CR  = completed_task_count / total_task_count
+WCR = sum(weight for completed tasks) / sum(weight for all tasks)
+TAT = mean(completion_time - release_time) over completed tasks, in seconds, or null if none complete
+PC  = gross consumed watt-hours
+```
+Validity is the hard gate before these metrics matter. Residual ambiguity remains only for borderline propagation, geometry, and battery cases at numerical tolerances.