Python open_rri Examples

Example #1

File: rri_to_hrv.py Project: zuotie/Watching-Video-Emotion

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)

Example #2

File: fd_calc.py Project: marcusjzw/HeartAlert-neural-network

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')

Example #3

File: rri_to_hrv_script.py Project: marcusjzw/HeartAlert-neural-network

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()

Example #4

 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)

Example #5

 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)

Example #6

 def setUp(self):
     self.real_rri = open_rri('tests/test_files/real_rri.txt')

Example #7

 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)