def test_hjorth(self):
ans_activity, ans_morbidity, ans_complexity= univariate.hjorth(white_noise)
ref_complexity = 1.2311281218979759
ref_morbidity = 1.4009964711379468
ref_activity = 1.0152445860000012
self.assertAlmostEqual(ref_complexity, ans_complexity)
self.assertAlmostEqual(ref_morbidity, ans_morbidity)
self.assertAlmostEqual(ref_activity, ans_activity)
def test_hjorth(self):
ans_activity, ans_morbidity, ans_complexity = univariate.hjorth(
white_noise)
ref_complexity = 1.2311281218979759
ref_morbidity = 1.4009964711379468
ref_activity = 1.0152445860000012
self.assertAlmostEqual(ref_complexity, ans_complexity)
self.assertAlmostEqual(ref_morbidity, ans_morbidity)
self.assertAlmostEqual(ref_activity, ans_activity)
import numpy as np
import sys
MIN_EPOCH_N = 256 * 5
MAX_EPOCH_N = 256 * 30
EPOCH_STEP = 256 * 5
N_REPLICATES = 5
SPECT_ENT_BANDS = 2 ** np.arange(0,8)/2
fun_to_test = [
{"times":100,"name":"hfd", "is_original":True,"fun": lambda x: pyeeg.hfd(x,2**3)},
{"times":100,"name":"hfd", "is_original":False,"fun": lambda x: univ.hfd(x,2**3)},
{"times":100,"name":"hjorth", "is_original":True,"fun": lambda x: pyeeg.hjorth(x)},
{"times":100,"name":"hjorth", "is_original":False,"fun": lambda x: univ.hjorth(x)},
{"times":100,"name":"pfd", "is_original":True, "fun":lambda x: pyeeg.pfd(x)},
{"times":100,"name":"pfd", "is_original":False, "fun":lambda x: pyeeg.pfd(x)},
{"times":2,"name":"samp_ent", "is_original":True, "fun":lambda x: pyeeg.samp_entropy(x,2,1.5)},
{"times":10,"name":"samp_ent", "is_original":False, "fun":lambda x: univ.samp_entropy(x,2,1.5,relative_r=False)},
{"times":2,"name":"ap_ent", "is_original":True, "fun":lambda x: pyeeg.ap_entropy(x,2,1.5)},
{"times":10,"name":"ap_ent", "is_original":False, "fun":lambda x: univ.ap_entropy(x,2,1.5)},
{"times":10,"name":"svd_ent", "is_original":True, "fun":lambda x: pyeeg.svd_entropy(x,2,3)},
{"times":100,"name":"svd_ent", "is_original":False, "fun":lambda x: univ.svd_entropy(x,2,3)},
{"times":10,"name":"fisher_info", "is_original":True, "fun":lambda x: pyeeg.fisher_info(x,2,3)},
{"times":100, "name":"fisher_info", "is_original":False, "fun":lambda x: univ.fisher_info(x,2,3)},
{"times":100,"name":"spectral_entropy", "is_original":True, "fun":lambda x: pyeeg.spectral_entropy(x,SPECT_ENT_BANDS,256)},
{"times":100, "name":"spectral_entropy", "is_original":False, "fun":lambda x: univ.spectral_entropy(x,256, SPECT_ENT_BANDS)},
]
"times": 100,
"name": "hfd",
"is_original": False,
"fun": lambda x: univ.hfd(x, 2**3)
},
{
"times": 100,
"name": "hjorth",
"is_original": True,
"fun": lambda x: pyeeg.hjorth(x)
},
{
"times": 100,
"name": "hjorth",
"is_original": False,
"fun": lambda x: univ.hjorth(x)
},
{
"times": 100,
"name": "pfd",
"is_original": True,
"fun": lambda x: pyeeg.pfd(x)
},
{
"times": 100,
"name": "pfd",
"is_original": False,
"fun": lambda x: pyeeg.pfd(x)
},
{
"times": 2,
