76 lines
2.5 KiB
Python
76 lines
2.5 KiB
Python
import unittest
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import numpy as np
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import pandas as pd
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from numpy.random import default_rng
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from pandas.testing import assert_series_equal
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from features.communication import count_comms, enumerate_contacts, get_call_data
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rng = default_rng()
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class CallsFeatures(unittest.TestCase):
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@classmethod
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def setUpClass(cls) -> None:
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call_rows = 10
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callers = np.concatenate(
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(
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np.repeat("caller1", 2),
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np.repeat("caller2", 3),
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np.repeat("caller3", 4),
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np.repeat("caller4", 1),
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),
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axis=None,
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)
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rng.shuffle(callers)
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cls.calls = pd.DataFrame(
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{
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"id": np.linspace(0, call_rows - 1, num=call_rows, dtype="u4") + 100,
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"_id": np.linspace(0, call_rows - 1, num=call_rows, dtype="u4"),
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"timestamp": np.sort(
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rng.integers(1612169903000, 1614556703000, size=call_rows)
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),
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"device_id": "device1",
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"call_type": rng.integers(1, 3, size=call_rows, endpoint=True),
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"call_duration": rng.integers(0, 600, size=call_rows),
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"trace": callers,
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"participant_id": 29,
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}
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)
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@classmethod
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def assertSeriesEqual(cls, a, b, msg=None, **optional):
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try:
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assert_series_equal(a, b, **optional)
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except AssertionError as e:
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raise cls.failureException(msg) from e
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def setUp(self):
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self.addTypeEqualityFunc(pd.DataFrame, self.assertSeriesEqual)
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def test_get_calls_data(self):
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calls_from_db = get_call_data(["nokia_0000003"])
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self.assertIsNotNone(calls_from_db)
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def test_enumeration(self):
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self.calls["contact_id_manual"] = self.calls["trace"].astype("category")
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self.calls["contact_id_manual"] = self.calls[
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"contact_id_manual"
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].cat.rename_categories(
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{"caller1": 2, "caller2": 1, "caller3": 0, "caller4": 3}
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)
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# Enumerate callers manually by their frequency as set in setUpClass.
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self.calls = enumerate_contacts(self.calls)
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self.assertSeriesEqual(
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self.calls["contact_id_manual"],
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self.calls["contact_id"].astype("category"),
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check_names=False,
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check_category_order=False,
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)
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def test_count_comms(self):
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self.features = count_comms(self.calls)
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print(self.features)
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self.assertIsInstance(self.features, pd.DataFrame)
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