def setup_class_methods(request):
"""
Fixture to setup class to test EcgBatch methods separately.
"""
path = os.path.join(os.path.dirname(os.path.realpath(__file__)), 'data/')
ind = ds.FilesIndex(path=os.path.join(path, 'A*.hea'), no_ext=True, sort=True)
batch_loaded = (EcgBatch(ind, unique_labels=["A", "O", "N"])
.load(fmt="wfdb", components=["signal", "annotation", "meta"]))
def teardown_class_methods():
"""
Teardown class
"""
request.addfinalizer(teardown_class_methods)
return batch_loaded
def test_load_wav(self, setup_module_load): #pylint: disable=redefined-outer-name
"""
Testing EDF loader.
"""
# Arrange
path = setup_module_load[1]
ind = ds.FilesIndex(path=os.path.join(path, 'sample*.wav'), no_ext=True, sort=True)
batch = EcgBatch(ind)
# Act
batch = batch.load(fmt="wav", components=["signal", "annotation", "meta"])
# Assert
assert isinstance(batch.signal, np.ndarray)
assert isinstance(batch.meta, np.ndarray)
assert isinstance(batch.annotation, np.ndarray)
assert batch.signal.shape == (1,)
assert batch.annotation.shape == (1,)
assert batch.meta.shape == (1,)
assert isinstance(batch.signal[0], np.ndarray)
assert isinstance(batch.annotation[0], dict)
assert isinstance(batch.meta[0], dict)
del batch
def test_load_wfdb_annotation(self, setup_module_load): #pylint: disable=redefined-outer-name
"""
Testing wfdb loader for annotation.
"""
# Arrange
path = setup_module_load[1]
ind = ds.FilesIndex(path=os.path.join(path, 'sel100.hea'), no_ext=True, sort=True)
batch = EcgBatch(ind)
# Act
batch = batch.load(fmt="wfdb", components=["signal", "annotation", "meta"], ann_ext="pu1")
# Assert
assert isinstance(batch.signal, np.ndarray)
assert isinstance(batch.meta, np.ndarray)
assert isinstance(batch.annotation, np.ndarray)
assert batch.signal.shape == (1,)
assert batch.annotation.shape == (1,)
assert batch.meta.shape == (1,)
assert isinstance(batch.signal[0], np.ndarray)
assert isinstance(batch.annotation[0], dict)
assert isinstance(batch.meta[0], dict)
assert 'annsamp' in batch.annotation[0]
assert 'anntype' in batch.annotation[0]
del batch
def setup_module_load(request):
"""
Fixture to setup module. Performs check for presence of test files,
creates initial batch object.
"""
path = os.path.join(os.path.dirname(os.path.realpath(__file__)), 'data')
files = ["A00001.hea", "A00001.mat", "A00002.hea", "A00002.mat",
"A00004.hea", "A00004.mat", "A00005.hea", "A00005.mat",
"A00008.hea", "A00008.mat", "A00013.hea", "A00013.mat", "REFERENCE.csv"]
# TODO: make better test for presence of files .hea and
# REFERENCE.csv
if np.all([os.path.isfile(os.path.join(path, file)) for file in files]):
ind = ds.FilesIndex(path=os.path.join(path, 'A*.hea'), no_ext=True, sort=True)
else:
raise FileNotFoundError("Test files not found in 'tests/data/'!")
def teardown_module_load():
"""
Teardown module
"""
request.addfinalizer(teardown_module_load)
return ind, path
import sys
import numpy as np
from matplotlib import pyplot as plt
sys.path.append('..')
import cardio
import cardio.dataset as ds
index = ds.FilesIndex(path='C:/training2017/A*.hea', no_ext=True, sort=True)
#print(index.indices)
from cardio import EcgBatch
eds = ds.Dataset(index, batch_class=EcgBatch)
batch = eds.next_batch(batch_size=6, unique_labels=['A', 'N', 'O'])
batch_with_data = batch.load(fmt='wfdb', components=['signal', 'meta'])
batch_with_data = batch.load(src='C:/training2017/REFERENCE.csv',
fmt='csv',
components='target')
#print(batch_with_data['A00001'].target)
## now trying different actions
original_batch = batch_with_data.deepcopy()
changed_batch = batch_with_data.deepcopy()
## CONVOLUTION to remove noise from Ecg
kernel = cardio.kernels.gaussian(
size=10) # will convolute signal with gaussian curve to remove noise
length = original_batch["A00001"].signal.shape[1]