"""
TestSPH: accomplished
subsampling: NOT tested
"""
import shutil
from pathlib import Path
import numpy as np
import pytest
from torch_ecg.databases import SPH, DataBaseInfo
from torch_ecg.utils.download import http_get
###############################################################################
# set paths
_CWD = Path(__file__).absolute().parents[2] / "tmp" / "test-db" / "sph"
try:
shutil.rmtree(_CWD)
except FileNotFoundError:
pass
_CWD.mkdir(parents=True, exist_ok=True)
http_get(
url="https://www.dropbox.com/s/og877l6d4bh4vew/SPH-Mini.tar.gz?dl=1",
dst_dir=_CWD,
extract=True,
)
###############################################################################
reader = SPH(_CWD)
class TestSPH:
def test_len(self):
assert len(reader) == 100
def test_subsample(self):
ss_ratio = 0.3
reader_ss = SPH(_CWD, subsample=ss_ratio, verbose=0)
assert len(reader_ss) == pytest.approx(len(reader) * ss_ratio, abs=1)
ss_ratio = 0.1 / len(reader)
reader_ss = SPH(_CWD, subsample=ss_ratio)
assert len(reader_ss) == 1
with pytest.raises(AssertionError, match="`subsample` must be in \\(0, 1\\], but got `.+`"):
SPH(_CWD, subsample=0.0)
with pytest.raises(AssertionError, match="`subsample` must be in \\(0, 1\\], but got `.+`"):
SPH(_CWD, subsample=1.01)
with pytest.raises(AssertionError, match="`subsample` must be in \\(0, 1\\], but got `.+`"):
SPH(_CWD, subsample=-0.1)
def test_load_data(self):
for rec in reader:
data = reader.load_data(rec)
data_1 = reader.load_data(rec, leads=[1, 7])
assert data.shape[0] == 12
assert data_1.shape[0] == 2
assert np.allclose(data[[1, 7], :], data_1)
data_1 = reader.load_data(rec, units="uV")
assert np.allclose(data_1, data * 1000)
data_1 = reader.load_data(rec, data_format="lead_last")
assert data.shape == data_1.T.shape
data_1, data_1_fs = reader.load_data(rec, return_fs=True)
assert data_1_fs == reader.fs
with pytest.raises(AssertionError, match="Invalid data_format: `flat`"):
reader.load_data(rec, data_format="flat")
with pytest.raises(AssertionError, match="Invalid units: `kV`"):
reader.load_data(rec, units="kV")
def test_load_ann(self):
for rec in reader:
ann = reader.load_ann(rec, ann_format="c")
ann_1 = reader.load_ann(rec, ann_format="f")
assert isinstance(ann, list) and isinstance(ann_1, list)
assert len(ann) == len(ann_1)
ann_1 = reader.load_ann(rec, ann_format="c", ignore_modifier=False)
assert len(ann) == len(ann_1)
ann_1 = reader.load_ann(rec, ann_format="f", ignore_modifier=False)
assert len(ann) == len(ann_1)
with pytest.raises(ValueError, match="Unknown annotation format: `flat`"):
reader.load_ann(rec, ann_format="flat")
with pytest.raises(NotImplementedError, match="Abbreviations are not supported yet"):
reader.load_ann(rec, ann_format="a")
def test_get_subject_info(self):
for rec in reader:
info = reader.get_subject_info(rec)
assert isinstance(info, dict)
assert info.keys() == {"age", "sex"}
def test_get_subject_id(self):
for rec in reader:
sid = reader.get_subject_id(rec)
assert isinstance(sid, str)
def test_get_age(self):
for rec in reader:
age = reader.get_age(rec)
assert isinstance(age, int)
assert age > 0
def test_get_sex(self):
for rec in reader:
sex = reader.get_sex(rec)
assert isinstance(sex, str)
assert sex in ["M", "F"]
def test_get_siglen(self):
for rec in reader:
siglen = reader.get_siglen(rec)
data = reader.load_data(rec)
assert isinstance(siglen, int)
assert siglen == data.shape[1]
def test_meta_data(self):
assert isinstance(reader.url, dict)
assert reader.get_citation() is None # printed
isinstance(reader.database_info, DataBaseInfo)
def test_plot(self):
waves = {
"p_onsets": [100, 1100],
"p_offsets": [110, 1110],
"q_onsets": [115, 1115],
"s_offsets": [130, 1130],
"t_onsets": [150, 1150],
"t_offsets": [190, 1190],
}
reader.plot(0, leads="II", ticks_granularity=2, waves=waves)
waves = {
"p_peaks": [105, 1105],
"q_peaks": [120, 1120],
"s_peaks": [125, 1125],
"t_peaks": [170, 1170],
}
reader.plot(0, leads=["II", 7], ticks_granularity=1, waves=waves)
waves = {
"p_peaks": [105, 1105],
"r_peaks": [122, 1122],
"t_peaks": [170, 1170],
}
data = reader.load_data(0)
reader.plot(0, data=data, ticks_granularity=0, waves=waves)
Datasets
Models
