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import datetime
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import time
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- import matplotlib as mpl
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import matplotlib .pyplot as plt
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import numpy as np
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import pandas as pd
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import seaborn as sns
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+ from graspologic .embed import AdjacencySpectralEmbed
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from pkg .data import load_split_connectome
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from pkg .io import OUT_PATH
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from pkg .io import glue as default_glue
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from pkg .io import savefig
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- from pkg .match import GraphMatchSolver
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- from pkg .plot import matched_stripplot , method_palette , set_theme
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+ from pkg .plot import set_theme
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from pkg .utils import get_hemisphere_indices
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- from scipy .stats import wilcoxon
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- from sklearn .covariance import log_likelihood
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- from tqdm import tqdm
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+
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FILENAME = "rdpg_sweep"
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@@ -42,9 +39,6 @@ def gluefig(name, fig, **kwargs):
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rng = np .random .default_rng (8888 )
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#%%
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- from graspologic .embed import AdjacencySpectralEmbed
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- from graspologic .utils import binarize
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-
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dataset = "maggot_subset"
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adj , nodes = load_split_connectome (dataset , weights = False )
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@@ -79,7 +73,7 @@ def compute_log_likelihood(adj, P):
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return log_likelihood
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- pad = 1 / (len (left_adj )** 3 )
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+ pad = 1 / (len (left_adj ) ** 3 )
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rows = []
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for rank in np .arange (1 , max_rank ):
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