from hrv.filters import moving_median
import numpy as np
# def _moving_function(rri, order, func):
# offset = int(order / 2)
# filt_rri = np.array(rri.copy(), dtype=np.float64)
# for i in range(offset, len(rri) - offset, 1):
# filt_rri[i] = func(rri[i-offset:i+offset+1])
# return filt_rri
# def moving_median(rri, order=3):
# return _moving_function(rri, order, np.median)
rri = open_rri('./data/test/extracted/Iris_kangxi_peyin_RRI.txt')
filt_rri = moving_median(rri, order=3)
results = time_domain(filt_rri)
print(results)
results = frequency_domain(rri=filt_rri,
fs=4.0,
method='welch',
interp_method='cubic',
detrend='linear')
print(results)
results = non_linear(filt_rri)
print(results)
from hrv.classical import frequency_domain
from hrv.utils import open_rri
import csv
for name in range(1, 106):
rri = open_rri(str(name) + '_.txt')
results = frequency_domain(rri=rri,
fs=4.0,
method='welch',
interp_method='cubic',
detrend='linear')
print("For data sample: " + str(name))
print(results)
output_csv_name = str(name) + '_hrvfd.csv'
with open(output_csv_name, 'wb') as f: # Just use 'w' mode in 3.x
w = csv.DictWriter(f, results.keys())
w.writeheader()
w.writerow(results)
print(str(name) + ' rri file has been written to csv')
from hrv.utils import open_rri
# uses hrv package and converts dict output to csv format
import csv
# how to use: td specifies td analysis and nl specifies NL analysis.
# change it depending on which one you want output
specifier = 'td'
# this script is GENERAL purpose. you need to change some of these to match the filenames
for i in range(1, 55): # change range
filename_header = 'nsr' + str(i).zfill(3) # change name possibly
filename = filename_header + 'rri.txt'
classifier = ''
try:
rri = open_rri(filename)
except:
continue
if specifier == 'td':
results = time_domain(rri) # output is dict
elif specifier == 'nl':
results = non_linear(rri)
else:
print("Invalid argument!")
output_csv_name = filename_header + 'hrv_' + specifier + '.csv'
with open(output_csv_name, 'wb') as f: # Just use 'w' mode in 3.x
w = csv.DictWriter(f, results.keys())
w.writeheader()
def test_open_hrm_file(self):
rri_file_name = 'tests/test_files/test_file_2.hrm'
response = open_rri(rri_file_name)
expected = FAKE_RRI
np.testing.assert_equal(response, expected)
def test_open_rri_text_file(self):
rri_file_name = 'tests/test_files/test_file_1.txt'
expected = FAKE_RRI
response = open_rri(rri_file_name)
np.testing.assert_equal(response, expected)
def setUp(self):
self.real_rri = open_rri('tests/test_files/real_rri.txt')
def test_open_rri_from_hrm_fileobj(self):
rri_file_name = 'tests/test_files/test_file_2.hrm'
file_obj = open(rri_file_name, 'r')
expected = FAKE_RRI
response = open_rri(file_obj)
np.testing.assert_equal(response, expected)