File size: 2,292 Bytes
9721937 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 | """Tests for dashboard summary-stats helpers in utils/utils.py."""
import numpy as np
import pytest
from utils.utils import mean_rt_per_choice
def _make_sim_output(rts, choices):
"""Build a sim-output-shaped dict with rts/choices arrays."""
rts = np.asarray(rts, dtype=np.float32).reshape(-1, 1, 1)
choices = np.asarray(choices, dtype=np.float32).reshape(-1, 1, 1)
return {"rts": rts, "choices": choices}
def test_mean_rt_per_choice_basic_two_choice():
sim = _make_sim_output(
rts=[0.4, 0.5, 0.6, 0.8, 1.0],
choices=[1, 1, 1, -1, -1],
)
out = mean_rt_per_choice(sim)
assert set(out.keys()) == {-1, 1}
assert out[1] == pytest.approx(0.5)
assert out[-1] == pytest.approx(0.9)
def test_mean_rt_per_choice_filters_deadline_timeouts():
sim = _make_sim_output(
rts=[0.4, -999, 0.6, -999, 1.0],
choices=[1, -999, 1, -999, -1],
)
out = mean_rt_per_choice(sim)
# Only valid samples count.
assert out[1] == pytest.approx(0.5)
assert out[-1] == pytest.approx(1.0)
def test_mean_rt_per_choice_one_sided():
"""All responses on one boundary — only that choice appears in the dict."""
sim = _make_sim_output(
rts=[0.3, 0.4, 0.5],
choices=[1, 1, 1],
)
out = mean_rt_per_choice(sim)
assert out == {1: pytest.approx(0.4)}
def test_mean_rt_per_choice_all_invalid():
sim = _make_sim_output(
rts=[-999, -999, -999],
choices=[-999, -999, -999],
)
assert mean_rt_per_choice(sim) == {}
def test_mean_rt_per_choice_n_choice():
sim = _make_sim_output(
rts=[0.4, 0.5, 0.6, 0.7, 0.8],
choices=[0, 1, 2, 0, 3],
)
out = mean_rt_per_choice(sim)
assert set(out.keys()) == {0, 1, 2, 3}
assert out[0] == pytest.approx(0.55) # mean of 0.4 and 0.7
assert out[1] == pytest.approx(0.5)
assert out[2] == pytest.approx(0.6)
assert out[3] == pytest.approx(0.8)
def test_mean_rt_per_choice_keys_are_int_when_integer_valued():
"""Choice keys should be int when integer-valued so DataFrame column names are clean."""
sim = _make_sim_output(rts=[0.4, 0.5], choices=[-1, 1])
out = mean_rt_per_choice(sim)
for key in out:
assert isinstance(key, int), f"expected int key, got {type(key)}"
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