jack
27 lines
1.3 KiB
Python
27 lines
1.3 KiB
Python
from pygui.backend.models.frame import Frame
|
||
from pygui.backend.models.session_model import SessionModel
|
||
from pygui.backend.models.threshold_classifier import BAND_HIGH, BAND_IN, BAND_LOW, ThresholdConfig
|
||
|
||
|
||
def test_manual_banding_and_stats():
|
||
model = SessionModel(ThresholdConfig(set_point=149.0, margin=1.0, auto=False))
|
||
update = model.process(Frame(seq=7, time=1.0, values=[151.0, 149.0, 147.0]))
|
||
assert update.seq == 7
|
||
assert update.bands == [BAND_HIGH, BAND_IN, BAND_LOW]
|
||
assert update.stats.avg == 149.0
|
||
assert (update.target, update.margin) == (149.0, 1.0)
|
||
assert update.state in ("idle", "ramp", "set")
|
||
|
||
def test_auto_banding_uses_mean_and_sigma():
|
||
model = SessionModel(ThresholdConfig(auto=True))
|
||
# Tight cluster around 149 -> small σ -> the 200.0 outlier reads HIGH
|
||
update = model.process(Frame(seq=0, time=0.0, values=[149.0, 149.0, 149.0, 200.0]))
|
||
assert update.bands[3] == BAND_HIGH
|
||
assert update.target == update.stats.avg
|
||
|
||
def test_set_thresholds_reband_on_next_frame():
|
||
m = SessionModel(ThresholdConfig(set_point=149.0, margin=1.0, auto=False))
|
||
m.set_thresholds(ThresholdConfig(set_point=149.0, margin=5.0, auto=False))
|
||
upd = m.process(Frame(seq=0, time=0.0, values=[151.0]))
|
||
assert upd.bands == [BAND_IN]
|