51 lines
1.9 KiB
Python
51 lines
1.9 KiB
Python
"""Tests for scroll generator."""
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from __future__ import annotations
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import json
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from pathlib import Path
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import torch
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import pytest
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from ai_mouse.scroll.generator import generate_scroll
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from tools.scroll.models import ScrollCVAE
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@pytest.fixture
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def scroll_model_dir(tmp_path):
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model = ScrollCVAE(seq_len=32)
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torch.save(model.state_dict(), tmp_path / "scroll_model.pt")
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config = {"seq_len": 32, "epochs": 100}
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(tmp_path / "scroll_config.json").write_text(json.dumps(config))
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return tmp_path
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class TestGenerateScroll:
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def test_returns_list_of_dicts(self, scroll_model_dir):
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result = generate_scroll(1000, 3000, mode="target", model_dir=str(scroll_model_dir))
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assert isinstance(result, list)
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assert len(result) > 0
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assert all("deltaY" in e and "t" in e and "deltaMode" in e for e in result)
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def test_timestamps_monotonic(self, scroll_model_dir):
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result = generate_scroll(1000, 3000, mode="target", model_dir=str(scroll_model_dir))
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times = [e["t"] for e in result]
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for i in range(1, len(times)):
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assert times[i] >= times[i - 1]
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def test_total_scroll_approximately_matches_distance(self, scroll_model_dir):
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result = generate_scroll(1000, 3000, mode="target", model_dir=str(scroll_model_dir))
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total = sum(e["deltaY"] for e in result)
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# Should be within 30% of target distance (2000px)
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assert abs(total - 2000) < 2000 * 0.4
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def test_deltaY_are_integers(self, scroll_model_dir):
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result = generate_scroll(1000, 3000, mode="target", model_dir=str(scroll_model_dir))
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assert all(isinstance(e["deltaY"], int) for e in result)
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def test_direction_up(self, scroll_model_dir):
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result = generate_scroll(3000, 1000, mode="target", model_dir=str(scroll_model_dir))
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total = sum(e["deltaY"] for e in result)
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# Negative total for scrolling up
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assert total < 0
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