75 lines
2.3 KiB
Python
75 lines
2.3 KiB
Python
import pandas as pd
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import pytest
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from data_processing import classify_treatments, glucose_status, summarize_time_in_range
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@pytest.fixture
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def sample_glucose():
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return pd.DataFrame(
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{
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"timestamp": pd.to_datetime(
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["2026-07-25 08:00", "2026-07-25 09:00", "2026-07-25 10:00", "2026-07-25 11:00"]
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),
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"mmol": [3.5, 6.0, 11.0, 7.0], # laag, in bereik, hoog, in bereik
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}
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)
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@pytest.fixture
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def sample_treatments():
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return pd.DataFrame(
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{
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"timestamp": pd.to_datetime(
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[
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"2026-07-25 08:00",
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"2026-07-25 12:00",
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"2026-07-24 09:00",
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"2026-07-20 09:00",
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]
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),
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"eventType": ["Meal Bolus", "Correction Bolus", "Site Change", "Sensor Change"],
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"insulin": [4.0, 1.5, None, None],
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"carbs": [45.0, None, None, None],
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}
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)
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def test_glucose_status_classifies_correctly():
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assert glucose_status(3.5) == "low"
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assert glucose_status(6.0) == "in_range"
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assert glucose_status(11.0) == "high"
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def test_summarize_time_in_range(sample_glucose):
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result = summarize_time_in_range(sample_glucose)
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assert result == {"low": 25.0, "in_range": 50.0, "high": 25.0}
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def test_summarize_time_in_range_handles_empty_input():
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empty = pd.DataFrame(columns=["timestamp", "mmol"])
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result = summarize_time_in_range(empty)
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assert result == {"low": 0.0, "in_range": 0.0, "high": 0.0}
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def test_classify_treatments_splits_into_expected_subsets(sample_treatments):
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events = classify_treatments(sample_treatments)
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assert len(events["insulin"]) == 2
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assert set(events["insulin"]["insulin"]) == {4.0, 1.5}
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assert len(events["carbs"]) == 1
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assert events["carbs"].iloc[0]["carbs"] == 45.0
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assert len(events["site_changes"]) == 1
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assert events["site_changes"].iloc[0]["eventType"] == "Site Change"
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assert len(events["sensor_changes"]) == 1
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assert events["sensor_changes"].iloc[0]["eventType"] == "Sensor Change"
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def test_classify_treatments_handles_empty_input():
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empty = pd.DataFrame(columns=["timestamp", "eventType", "insulin", "carbs"])
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events = classify_treatments(empty)
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assert all(df.empty for df in events.values())
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