distance_histogram seems to be broken

Bug reports:

When I calculate the all pairs shortest path distances of a graph using shortest_distance() and histogram them using np.histogram, there is a hefty mismatch to distance_histogram()'s output just for larger graphs.

Please follow the general troubleshooting steps first:

Are you running the latest graph-tool version?
Do you observe the problem with the current git version?
Are you using Macports or Homebrew? If yes, please submit an issue there instead: https://github.com/Homebrew/brew/issues and https://trac.macports.org/newticket
Did you compile graph-tool manually?

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Do not forget to supply the following information:

A minimal and self-contained example that shows the problem.
Your operating system.
The Python version you are using.
If you compiled graph-tool manually: Your compiler version, as well as the version of Boost being used.

Setup

gt.__version__ == 2.43 (commit 5778eb10, )
Python version: 3.9.7
uname -a Linux hostname 5.11.0-38-generic #42~20.04.1-Ubuntu SMP Tue Sep 28 20:41:07 UTC 2021 x86_64 x86_64 x86_64 GNU/Linux
Installed / automatically compiled via conda-forge

MWE

import graph_tool.all as gt
import numpy as np

G = gt.random_graph(300, lambda: np.random.randint(1,10,2))
G_weight = G.new_edge_property('float')
for e in G.edges():
    G_weight[e] = 100 * np.random.random()

apsp_true = [ d for l in gt.shortest_distance(G, weights=G_weight) for d in l if 0 < d <= 1e50 ]

counts, bins = gt.distance_histogram(G, G_weight)
counts_np, _ = np.histogram(apsp_true, bins=bins)

print(np.where(counts!=counts_np))

Up to 300 nodes, this returns (array([], dtype=int64),) as expected. From 301 onward there is a great mismatch:

(array([  2,   3,   4,   6,   9,  12,  13,  14,  16,  17,  20,  22,  23,
         24,  25,  26,  27,  28,  29,  30,  31,  33,  35,  36,  37,  41,
         42,  43,  44,  45,  46,  47,  48,  49,  50,  51,  52,  54,  56,
         57,  61,  62,  65,  66,  67,  68,  69,  70,  71,  72,  73,  75,
         76,  77,  78,  79,  80,  81,  83,  84,  85,  86,  87,  88,  89,
         90,  91,  92,  94,  95,  96,  97,  98, 100, 101, 102, 103, 104,
        105, 106, 107, 108, 110, 111, 112, 113, 114, 115, 116, 117, 118,
        119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131,
        132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144,
        145, 146, 147, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158,
        159, 161, 162, 163, 166, 167, 168, 169, 170, 171, 172, 173, 174,
        175, 176, 177, 180, 181, 182, 183, 184, 185, 187, 188, 189, 190,
        191, 192, 193, 194, 195, 196, 197, 199, 200, 201, 202, 203, 205,
        206, 207, 208, 209, 210, 211, 212, 213, 214, 215, 216, 217, 218,
        219, 220, 221, 222, 223, 224, 225, 226, 228, 229, 230, 231, 233,
        234, 236, 237, 238, 240, 241, 242, 243, 245, 246, 247, 248, 249,
        250, 253, 254, 255, 256, 257, 258, 259, 261, 262, 263, 265, 266,
        267, 268, 271, 272, 273, 275, 276, 277, 279, 281, 284, 288, 305,
        306, 308, 310, 313, 321, 326, 333, 334, 348, 361, 365, 424]),)

For some graphs even sum(counts) != sum(counts_np).

What's happening here?

P.s. I made a quick chart:

Edited Nov 17, 2021 by suuuehgi