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)