def main():
"""
This is the main function
Returns:
None
"""
import hbAnalysis as hb # Assuming we named the file 'heartbeat.py'
import filehander
import json
from jsonEncoder import NumpyAwareJSONEncoder
# get data
filename = filehander.open_file_dialog()
df = hb.get_data(filename)
# Todo: clean the data
# signal processing
# calc interested info using the chosen data, and store in metrics
hb.process(df, metrics)
# plot the interested value
plotter(df, "test_data1")
# store the interested value into file
j = json.dumps(metrics, cls=NumpyAwareJSONEncoder)
f = open("data.json", "w")
f.write(j)
f.close()
def get_num_beats(test_input, expected):
df = get_data(test_input)
peaks, _ = fit_peaks(df)
beats = get_beats(df, peaks)
num_beats = get_num_beats(beats)
minimum, maximum = expected
print("num of beats is {}".format(num_beats))
assert (minimum <= num_beats <= maximum)
def test_fit_peaks(test_input, expected):
df = get_data(test_input)
peaks, w_best = fit_peaks(df)
num_peaks = len(peaks)
minimum, maximum = expected
print("num of peaks is {}".format(num_peaks))
print("best weight is {}".format(w_best))
assert (minimum <= num_peaks <= maximum)
def test_detect_peaks(test_input, expected):
df = get_data(test_input)
fs = calc_fs(df)
rolling_mean = calc_rolling_mean(df, 0.25, fs)
num_peaks = len(detect_peaks(df, 60, rolling_mean))
minimum, maximum = expected
print("fs is {}".format(fs))
print("num of peaks is {}".format(num_peaks))
assert (minimum <= num_peaks <= maximum)
def test_calc_rolling_mean(test_input, expected):
df = get_data(test_input)
hrw = 1
fs = 2
rolling_mean = calc_rolling_mean(df, hrw, fs)
print("rolling_mean is :{}".format(rolling_mean))
is_close = np.std(np.array(rolling_mean) - np.array(expected))
print("isClose is :{}".format(is_close))
assert (is_close <= 0.001)
def test_calc_rrsd(test_input, expected):
df = get_data(test_input)
fs = calc_fs(df)
rolling_mean = calc_rolling_mean(df, 0.25, fs)
peaks = detect_peaks(df, 100, rolling_mean)
rr_list = calc_rr(df, peaks)
rrsd = calc_rrsd(rr_list)
minimum, maximum = expected
print("rrsd is {}".format(rrsd))
assert (minimum <= rrsd <= maximum)
def test_calc_rr(test_input, expected):
df = get_data(test_input)
fs = calc_fs(df)
rolling_mean = calc_rolling_mean(df, 0.25, fs)
peaks = detect_peaks(df, 100, rolling_mean)
rr_list = calc_rr(df, peaks)
minimum, maximum = expected
rr_list_invalid = list(
filter(lambda rr: rr <= minimum or rr >= maximum, rr_list))
print("num of peaks is {}".format(len(peaks)))
print("num of rr_invalid is {}".format(len(rr_list_invalid)))
assert (len(rr_list_invalid) <= 5)
def get_mean_hr_bpm(test_input, expected):
raw_input = input('Enter your input:')
input_duration = float(raw_input)
df = get_data(test_input)
duration = get_duration(df)
fs = calc_fs(df)
rolling_mean = calc_rolling_mean(df, 0.25, fs)
peaks = detect_peaks(df, 100, rolling_mean)
rr_list = calc_rr(df, peaks)
bpm = calc_bpm(rr_list)
mean_hr_bpm = get_mean_hr_bpm(duration, bpm, input_duration)
minimum, maximum = expected
print("mean_hr_bpm is {}".format(mean_hr_bpm))
assert (minimum <= mean_hr_bpm <= maximum)
def test_calc_fs(test_input, expected):
df = get_data(test_input)
fs = calc_fs(df)
assert (fs == expected)
def test_get_voltage_extremes(test_input, expected):
df = get_data(test_input)
extremes = get_voltage_extremes(df)
assert (extremes == expected)
def test_get_duration(test_input, expected):
df = get_data(test_input)
duration = get_duration(df)
assert (duration == expected)
def test_get_data(test_input, expected):
df = get_data(test_input)
assert (list(df.time) == expected)
