Every time you run hyppo, you get nreps* of a warning about @jit being deprecated. It looks like:
/usr/local/lib/python3.9/site-packages/umap_learn-0.5.3-py3.9.egg/umap/distances.py:1063: NumbaDeprecationWarning: The 'nopython' keyword argument was not supplied to the 'numba.jit' decorator. The implicit default value for this argument is currently False, but it will be changed to True in Numba 0.59.0. See https://numba.readthedocs.io/en/stable/reference/deprecation.html#deprecation-of-object-mode-fall-back-behaviour-when-using-jit for details.
@numba.jit()
For instance:
import numpy as np
from graspologic.simulations import sbm
from graphbook_code import dcsbm
from copy import deepcopy
# the block matrix for the neurons before learning
B0 = 0.05*np.ones((3, 3))
np.fill_diagonal(B0, 0.4)
B_learned = deepcopy(B0)
B_learned[0,1] = B_learned[1,0] = 0.3
nk = 30
ns = np.repeat(nk, 3)
theta = np.tile(np.linspace(np.sqrt(2), np.sqrt(2) - 1, nk), 3)
zs = np.repeat([1,2,3], nk)
T = 12
networks = np.array([sbm(ns, B0) if (t < 6 or t > 8) else dcsbm(zs, theta, B0) for t in range(T)])
and:
from graspologic.inference import latent_position_test
#import warnings
#warnings.filterwarnings('ignore')
pvalues = [latent_position_test(networks[t], networks[t + 1], n_components=3, n_bootstraps=1000, workers=-1)[1] for t in range(T-1)]
Every time you run hyppo, you get
nreps*of a warning about@jitbeing deprecated. It looks like:For instance:
and:
produces the error.
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