Datasets:

midwestern-simulation
/

boolean-networks

network_size int64	connectivity_modes int64	connectivity_mu sequence	connectivity_sigma sequence	connectivity_mode_weights sequence	initial_state sequence	function_keys sequence	function_values sequence	function_inputs sequence	trajectory sequence
51	4	[ 4.1, 7.68, 2.69, 1 ]	[ 0.8740278766434944, 0.2859912457681391, 0.28692021408805635, 1.2676098406028937 ]	[ 0.36726121895735225, 0.082046160377338, 0.32078062349207065, 0.229911997173239 ]	[1,0,0,0,0,0,1,0,0,1,0,0,1,1,0,0,0,1,1,1,1,1,1,0,1,0,1,1,0,1,0,0,0,1,1,0,1,0,0,1,1,1,0,1,1,0,0,0,0,0(...TRUNCATED)	[[[0,0,0],[0,0,1],[0,1,0],[0,1,1],[1,0,0],[1,0,1],[1,1,0],[1,1,1]],[[0,0,0],[0,0,1],[0,1,0],[0,1,1],(...TRUNCATED)	[[0,1,0,1,1,0,0,1],[0,1,1,1,1,1,0,1],[1,1,0,1,0,1,1,0,1,0,1,1,1,1,0,0,1,1,0,1,1,0,1,1,0,0,0,1,0,1,0,(...TRUNCATED)	[[12,47,43],[18,11,13],[33,42,4,30,41,14,34,16],[40,49,10,20,41],[29,3,47],[47],[1],[46,19,35,17,2],(...TRUNCATED)	[[0,1,1,0,0,1,1,0,0,0,0,0,1,0,0,0,1,1,1,0,0,0,0,1,1,1,0,1,1,1,0,1,0,1,0,1,0,0,0,1,1,0,0,0,0,0,0,1,1,(...TRUNCATED)
48	8	[ 1, 5.01, 6.1, 2.61, 3.79, 6.02, 5.71, 7.71 ]	[2.374736213362286,0.8926132175682255,0.39005795232499324,1.2635452561340186,1.008499994805906,2.029(...TRUNCATED)	[0.07310957024668147,0.12077466441387331,0.15065361839420363,0.10260316990577432,0.15159533366073594(...TRUNCATED)	[ 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 0, 1, 0, 1, 0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 0, 0, 1, 0 ]	[[[0,0,0,0,0,0],[0,0,0,0,0,1],[0,0,0,0,1,0],[0,0,0,0,1,1],[0,0,0,1,0,0],[0,0,0,1,0,1],[0,0,0,1,1,0],(...TRUNCATED)	[[1,1,0,0,1,0,0,0,1,0,1,0,0,1,1,0,1,1,1,1,0,1,1,1,0,1,1,0,0,1,0,1,0,0,1,0,0,0,1,1,0,1,1,0,1,0,0,0,0,(...TRUNCATED)	[[38,29,12,16,5,39],[25,36],[24,11,44,39,29],[21,19,5,31,33,40],[18,20,24,14,5],[16,12,24,5,18,4],[3(...TRUNCATED)	[[1,1,0,1,1,1,1,0,1,0,0,1,1,1,1,1,1,0,0,1,0,0,1,1,1,1,1,0,1,0,0,0,1,0,1,1,0,0,1,0,1,0,0,0,1,0,1,0],[(...TRUNCATED)
32	8	[ 5.04, 4.65, 6.4, 4.9, 5.67, 1, 1, 3.54 ]	[0.995700430990061,1.825915203391822,1.2753890202746985,0.7834807210060242,1.2934842175321444,1.5274(...TRUNCATED)	[0.0632318723293919,0.20248635885929472,0.17449910707688804,0.09016408233637997,0.08311782700375708,(...TRUNCATED)	[ 0, 0, 1, 1, 1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 1, 0, 1 ]	[[[0],[1]],[[0,0,0,0,0],[0,0,0,0,1],[0,0,0,1,0],[0,0,0,1,1],[0,0,1,0,0],[0,0,1,0,1],[0,0,1,1,0],[0,0(...TRUNCATED)	[[0,0],[0,1,1,1,1,0,0,1,1,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,0,1,1,1,1,0],[0,1,1,1,0,0,1,1],[0,1,0,1,(...TRUNCATED)	[[29],[9,28,22,14,7],[20,0,3],[24,17,5,9,13],[29,1,18,31],[27,21,24,15],[5],[14,22,16],[23,26,3,7,1,(...TRUNCATED)	[[0,1,1,0,1,0,1,1,1,1,0,1,1,1,1,0,1,1,0,0,0,1,1,0,0,0,0,1,1,0,1,1],[0,0,0,0,1,0,1,0,1,0,0,1,0,1,1,0,(...TRUNCATED)
47	5	[ 2.28, 4.21, 1, 1.18, 6.91 ]	[ 2.083861162258133, 1.222141112729336, 1.1635032699565266, 1.63770363167274, 1.9355039244937982 ]	[0.12743290435119317,0.33112971842237693,0.005722087317404222,0.38055550433776414,0.1551597855712615(...TRUNCATED)	[ 0, 0, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 1, 1, 1, 0, 1, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 1, 1, 0, 1, 1, 0, 0, 1, 1, 1, 1 ]	[[[0,0,0,0],[0,0,0,1],[0,0,1,0],[0,0,1,1],[0,1,0,0],[0,1,0,1],[0,1,1,0],[0,1,1,1],[1,0,0,0],[1,0,0,1(...TRUNCATED)	[[1,1,0,1,1,0,0,1,1,0,0,1,0,0,1,1],[0,1,0,1],[0,1,0,1],[1,1],[0,1,0,1,0,1,1,1,1,0,0,0,0,1,0,0],[0,1,(...TRUNCATED)	[[2,46,22,21],[40,30],[38,12],[3],[19,0,31,7],[35,32,7,43,24,15],[41,19,14],[36,13,10,22],[28,26,43](...TRUNCATED)	[[1,0,0,1,0,1,0,0,1,0,0,1,1,1,1,1,0,0,1,0,0,0,0,0,0,0,0,0,1,0,1,1,0,0,1,1,0,1,1,1,1,1,1,0,0,0,0],[1,(...TRUNCATED)
41	3	[ 1, 4.45, 4.82 ]	[ 1.9031128173886755, 1.4370254405959049, 0.44985491190213855 ]	[ 0.12844752917553107, 0.010771955105776936, 0.860780515718692 ]	[ 0, 1, 0, 1, 0, 0, 0, 0, 0, 1, 0, 1, 1, 0, 1, 0, 1, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0 ]	[[[0,0,0,0,0],[0,0,0,0,1],[0,0,0,1,0],[0,0,0,1,1],[0,0,1,0,0],[0,0,1,0,1],[0,0,1,1,0],[0,0,1,1,1],[0(...TRUNCATED)	[[0,0,0,0,1,1,1,1,0,1,1,1,1,0,0,0,0,1,0,0,0,1,0,0,0,0,0,1,1,0,1,0],[1,1,1,0,1,0,1,1,0,1,1,1,0,0,1,0,(...TRUNCATED)	[[11,10,25,40,8],[9,20,25,13,4],[14,40,25,8,10],[26,19,12,1,36],[24,13,22,28],[10,12,40,29,17],[14,1(...TRUNCATED)	[[0,1,0,1,0,1,1,0,1,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,1,0,0,0,0,1,1,1,0,1,1,1,1],[1,1,0,0,1,1,1,(...TRUNCATED)
49	8	[ 3.46, 6.94, 1, 5.45, 1, 4.43, 1.06, 3.96 ]	[2.2403304416095895,2.34947302416298,0.6894010188832647,1.3546603930155434,1.9403237186471234,0.3009(...TRUNCATED)	[0.039198463972332696,0.08588642858762426,0.1164140452942827,0.2619130599275291,0.050814331892911464(...TRUNCATED)	[ 0, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 0, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0, 0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 1, 1, 1, 0 ]	[[[0,0,0,0,0,0,0],[0,0,0,0,0,0,1],[0,0,0,0,0,1,0],[0,0,0,0,0,1,1],[0,0,0,0,1,0,0],[0,0,0,0,1,0,1],[0(...TRUNCATED)	[[0,0,0,1,0,0,1,1,0,0,0,0,1,1,1,0,1,0,0,0,1,0,0,1,0,1,1,0,1,1,1,1,0,0,0,1,0,1,1,1,1,1,1,0,0,1,0,0,0,(...TRUNCATED)	[[28,11,45,44,35,43,16],[24,2,14,41,16],[29,36,16,8,32,9],[48,33,40,43],[47,2,17,45],[37,1,10,41,9],(...TRUNCATED)	[[0,0,1,0,0,0,0,1,0,1,1,0,0,0,0,1,1,0,1,0,0,1,1,1,0,1,0,1,1,0,0,0,0,0,0,0,1,1,1,0,1,0,0,0,1,0,1,1,1](...TRUNCATED)
50	2	[ 5.81, 2.21 ]	[ 1.4509800219964628, 1.0405242752361306 ]	[ 0.6126457827251207, 0.3873542172748792 ]	[1,1,1,0,0,0,1,1,1,0,1,1,1,0,1,1,0,1,1,0,1,1,0,1,0,1,1,0,1,1,0,1,0,1,0,0,0,1,1,0,0,1,0,1,0,0,1,1,0,0(...TRUNCATED)	[[[0,0],[0,1],[1,0],[1,1]],[[0,0,0,0,0],[0,0,0,0,1],[0,0,0,1,0],[0,0,0,1,1],[0,0,1,0,0],[0,0,1,0,1],(...TRUNCATED)	[[1,0,0,0],[0,1,0,0,1,1,0,0,1,1,1,0,0,1,1,0,0,0,0,0,1,0,0,1,0,0,1,1,1,1,0,1],[1,1,1,1,0,1,0,0],[1,1,(...TRUNCATED)	[[28,24],[5,31,46,34,24],[47,44,33],[49,15,29,31,11,20,18,19],[34,18,10,29,20,30,4],[42,11,39,32,17,(...TRUNCATED)	[[0,0,1,1,1,1,1,0,0,0,0,0,1,0,0,0,1,0,1,1,1,0,0,0,0,1,0,1,1,0,1,0,0,1,0,1,0,0,0,0,0,1,1,0,1,0,0,1,1,(...TRUNCATED)
35	3	[ 1.86, 3.86, 2.25 ]	[ 2.2262735828525626, 1.2680669150284647, 2.474399163750311 ]	[ 0.07501273197957546, 0.2925006890587127, 0.6324865789617118 ]	[ 0, 0, 1, 0, 0, 1, 0, 1, 1, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1 ]	[[[0,0,0],[0,0,1],[0,1,0],[0,1,1],[1,0,0],[1,0,1],[1,1,0],[1,1,1]],[[0],[1]],[[0,0,0,0],[0,0,0,1],[0(...TRUNCATED)	[[0,0,1,0,1,0,0,1],[0,0],[0,0,1,1,0,0,0,1,1,0,1,0,0,1,1,1],[1,0,1,1,0,0,1,0,0,0,0,1,0,0,0,1,0,1,1,1,(...TRUNCATED)	[[34,7,25],[33],[5,26,29,24],[2,12,29,24,9,13],[8,34],[8,19],[3,10,16,9],[11,24],[20,3],[33,31,2,24](...TRUNCATED)	[[0,0,0,1,1,1,0,0,0,0,0,1,1,0,1,1,1,0,0,0,0,1,0,0,1,0,1,0,0,1,1,1,1,1,0],[0,0,1,1,1,0,1,0,1,1,0,0,1,(...TRUNCATED)
39	1	[ 4.6 ]	[ 1.3784549442209335 ]	[ 1 ]	[ 1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 1, 0, 1, 1, 0, 1, 0, 0, 1, 1, 1, 0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0 ]	[[[0,0,0,0,0],[0,0,0,0,1],[0,0,0,1,0],[0,0,0,1,1],[0,0,1,0,0],[0,0,1,0,1],[0,0,1,1,0],[0,0,1,1,1],[0(...TRUNCATED)	[[1,0,1,1,1,1,0,1,0,1,1,0,0,1,1,1,0,0,1,1,0,0,1,1,0,1,0,1,1,1,1,1],[0,1,1,0,0,1,0,1],[1,0,1,0,1,1,1,(...TRUNCATED)	[[27,33,30,10,14],[34,5,11],[21,17,23,12,37,36],[1,25,29],[35,15,26,21,19],[37,2,13,15,36,18],[13,3,(...TRUNCATED)	[[1,1,1,0,0,0,1,1,1,0,1,1,0,1,0,1,1,0,1,0,0,1,0,1,1,1,0,1,0,1,0,1,0,1,1,1,0,1,0],[0,1,1,0,0,1,0,1,0,(...TRUNCATED)
55	7	[ 4.28, 6.41, 2.01, 5.77, 2.81, 1, 6.52 ]	[2.4311297132887417,1.0370672070708584,0.4367906166320109,1.4604180038803063,1.6344755662821888,0.95(...TRUNCATED)	[0.20955165972521989,0.22850351972732078,0.06703973828088243,0.10022319084283716,0.11497058591393561(...TRUNCATED)	[0,1,0,0,1,1,0,1,0,0,0,1,0,1,1,0,1,1,1,1,0,1,1,1,0,1,0,1,0,1,0,1,1,0,1,0,1,0,1,0,0,1,1,0,0,1,1,1,1,1(...TRUNCATED)	[[[0,0,0,0,0,0,0],[0,0,0,0,0,0,1],[0,0,0,0,0,1,0],[0,0,0,0,0,1,1],[0,0,0,0,1,0,0],[0,0,0,0,1,0,1],[0(...TRUNCATED)	[[1,1,1,0,0,1,0,0,1,1,1,1,1,0,0,1,0,1,0,0,1,1,0,1,0,1,0,0,0,1,0,0,1,1,0,0,0,0,1,0,1,0,0,0,1,1,0,1,1,(...TRUNCATED)	[[5,45,27,16,46,9,19],[39,45],[52,42],[2,17],[16,4,2,13],[44,39,5,14],[0,54,36,45],[33,46],[47,35],[(...TRUNCATED)	[[0,1,1,1,1,1,0,1,0,1,0,0,1,0,0,1,1,0,0,0,1,1,1,1,1,1,0,1,1,0,0,0,1,0,0,1,1,1,0,0,1,1,0,1,1,0,0,1,0,(...TRUNCATED)

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boolean networks, each sampled over 8192 timesteps, ranging from network size 32-1024, with connectivities (sizes of functions) per item taken from random gaussian mixtures

features:

network_size              # number of nodes in the network
connectivity_modes        # gaussians that connectivities are sampled from
connectivity_mu
connectivity_sigma
connectivity_mode_weights
initial_state
function_keys             # think left (input) side of truth table
function_values           # think right (output) side of truth table
function_inputs           # the node indices that go into this function

for a tiny subset with 128 networks, for example if testing a pipeline, try:

from datasets import load_dataset

dataset = load_dataset(
  "parquet", data_files=[
    "https://huggingface.co/datasets/midwestern-simulation/boolean-networks/resolve/main/chunk_gUKO6HBS_128_8192_32-1024.parquet"
    # "chunk_{id}_{num_samples}_{min_network_size}_{max_network_size}.parquet"
  ]
)

Downloads last month: 3,185

Size of downloaded dataset files:

17.3 GB

Size of the auto-converted Parquet files:

17.3 GB

Number of rows:

116,864