def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
util.configure_logging()
self.test1 = {
'A':
np.array([[0, 0, 0, 0], [0, 0, 0, 1], [0, 0, 0, 1], [0, 1, 1, 0]]),
'RSP_true':
np.array([[0.00000, np.inf, np.inf, np.inf],
[np.inf, 0.00000, 2.14516, 1.07258],
[np.inf, 2.14516, 0.00000, 1.07258],
[np.inf, 1.07258, 1.07258, 0.00000]]),
'FE_true':
np.array([[0.00000, np.inf, np.inf, np.inf],
[np.inf, 0.00000, 2.62308, 1.31154],
[np.inf, 2.62308, 0.00000, 1.31154],
[np.inf, 1.31154, 1.31154, 0.00000]])
}
self.test2 = {
'A':
np.array([[.5, .25, .25], [.25, .0, .75], [.25, .75, .0]]),
'RSP_true':
np.array([[0.00000, 4.34699, 4.34699], [4.34699, 0.00000, 1.33429],
[4.34699, 1.33429, 0.00000]]),
'FE_true':
np.array([[0.00000, 5.15091, 5.15091], [5.15091, 0.00000, 1.62088],
[5.15091, 1.62088, 0.00000]])
}
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
util.configure_logging()
self.A = np.array([[1, 1, 0, 0, 1, 0], [1, 0, 1, 0, 1, 0],
[0, 1, 0, 1, 0, 0], [0, 0, 1, 0, 1, 1],
[1, 1, 0, 1, 0, 0], [0, 0, 0, 1, 0, 0]])
self.D = np.array([[3, 0, 0, 0, 0, 0], [0, 3, 0, 0, 0, 0],
[0, 0, 2, 0, 0, 0], [0, 0, 0, 3, 0, 0],
[0, 0, 0, 0, 3, 0], [0, 0, 0, 0, 0, 1]])
self.L = np.array([[2, -1, 0, 0, -1, 0], [-1, 3, -1, 0, -1, 0],
[0, -1, 2, -1, 0, 0], [0, 0, -1, 3, -1, -1],
[-1, -1, 0, -1, 3, 0], [0, 0, 0, -1, 0, 1]])
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
util.configure_logging()
self.etalon = { # CCT, FE, logFor, RSP, SCT, SP
'football': (.7928, .9061, .9028, .9092, .8115, .8575),
'karate': (1., 1., 1., 1., 1., 1.),
'polblogs': (.5525, .5813, .5811, .5815, .5757, .5605),
'news_2cl_1': (.7944, .8050, .8381, .7966, .8174, .6540),
'news_2cl_2': (.5819, .5909, .5844, .5797, .5523, .5159),
'news_2cl_3': (.7577, .8107, .7482, .7962, .7857, .8592),
'news_3cl_1': (.7785, .7810, .7530, .7810, .7730, .7426),
'news_3cl_2': (.7616, .7968, .7585, .7761, .7282, .6246),
'news_3cl_3': (.7455, .7707, .7487, .7300, .7627, .7203),
'news_5cl_1': (.6701, .6922, .6143, .7078, .6658, .6815),
'news_5cl_2': (.6177, .6401, .5977, .6243, .6154, .5970),
'news_5cl_3': (.6269, .6065, .5729, .5750, .5712, .4801)
}
self.datasets = Datasets()
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
util.configure_logging()
self.etalon = { # SCT CCT FE RSP SP Com For Heat Walk lCom lFor lHeat lWalk LVN
'football': (0.908, 0.889, 0.884, 0.884, 0.812, 0.545, 0.293,
0.492, 0.749, 0.598, 0.424, 0.583, 0.249, 0.698),
'lfr1': (0.976, 0.990, 0.981, 0.983, 0.890, 0.052, 0.027, 0.051,
0.003, 0.475, 0.500, 0.511, 0.485, 0.962),
'lfr2': (1.000, 1.000, 1.000, 1.000, 0.986, 0.147, 0.164, 0.266,
0.694, 0.481, 0.478, 0.449, 0.682, 0.823),
'lfr3': (1.000, 0.997, 1.000, 1.000, 0.989, 0.087, 0.130, 0.159,
0.502, 0.520, 0.379, 0.376, 0.729, 0.827),
'news_2cl_1': (0.608, 0.638, 0.584, 0.581, 0.434, 0.018, 0.032,
0.032, 0.249, 0.291, 0.243, 0.253, 0.462, 0.573),
'news_2cl_2': (0.356, 0.396, 0.359, 0.346, 0.296, 0.008, 0.027,
0.100, 0.394, 0.584, 0.123, 0.207, 0.233, 0.432),
'news_2cl_3': (0.579, 0.584, 0.590, 0.598, 0.616, 0.333, 0.053,
0.117, 0.357, 0.682, 0.553, 0.611, 0.496, 0.586),
'news_3cl_1': (0.697, 0.706, 0.702, 0.696, 0.660, 0.096, 0.032,
0.125, 0.245, 0.489, 0.471, 0.478, 0.748, 0.699),
'news_3cl_2': (0.656, 0.689, 0.711, 0.706, 0.572, 0.068, 0.035,
0.040, 0.294, 0.345, 0.343, 0.281, 0.572, 0.661),
'news_3cl_3': (0.642, 0.605, 0.681, 0.678, 0.720, 0.067, 0.031,
0.033, 0.380, 0.295, 0.255, 0.248, 0.423, 0.673),
'news_5cl_1': (0.641, 0.643, 0.648, 0.651, 0.614, 0.087, 0.019,
0.032, 0.284, 0.259, 0.273, 0.291, 0.504, 0.684),
'news_5cl_2': (0.616, 0.630, 0.643, 0.633, 0.596, 0.185, 0.026,
0.024, 0.291, 0.345, 0.214, 0.234, 0.374, 0.634),
'news_5cl_3': (0.573, 0.624, 0.615, 0.571, 0.480, 0.034, 0.021,
0.021, 0.369, 0.300, 0.337, 0.281, 0.383, 0.572),
'polblogs': (0.556, 0.556, 0.567, 0.568, 0.549, 0.423, 0.322,
0.641, 0.298, 0.511, 0.550, 0.527, 0.577, 0.597),
'karate': (0.832, 0.724, 0.838, 0.832, 1.000, 0.262, 0.395, 1.000,
0.875, 1.000, 0.866, 1.000, 0.697, 0.982)
}
self.datasets = Datasets()
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
util.configure_logging()
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
util.configure_logging()
self.graph = Samples.triangle_graph
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
self.graph = Samples.chain_graph
util.configure_logging()
import logging
import sys
import warnings
import matplotlib.pyplot as plt
import numpy as np
warnings.filterwarnings("ignore")
sys.path.append('../..')
from _datasets_kward import datasets_kward
from pygraphs.measure import kernels
from pygraphs.scenario import d3_colors
from pygraphs.util import configure_logging
configure_logging()
logger = logging.getLogger()
dataset_names = [
'dolphins',
'',
# 'eu-core',
'football',
'karate',
'polbooks',
'',
'news_2cl_1',
# 'news_2cl_1_numpy',
'news_2cl_2',
'news_2cl_3',
'news_3cl_1',
'news_3cl_2',
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
util.configure_logging()
self.graph = Samples.diploma_matrix
def __init__(self, *args, **kwargs):
super().__init__(0.002, *args, **kwargs) # error bars in paper: 0.002
util.configure_logging()
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
util.configure_logging()
self.get_CT = lambda A: SPCT_D(A).get_D(0)
self.get_SP = lambda A: SPCT_D(A).get_D(1)
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
util.configure_logging()
graph, _, info = Datasets().karate
self.graph, self.y_true = graph[0]
