Classes
class	EncodeProcessDecode

class	MLPGraphIndependent

class	MLPGraphNetwork

class	SofieGNN

Functions
	CopyData (input_data)

	GenerateData ()

	get_graph_data_dict (num_nodes, num_edges, NODE_FEATURE_SIZE=2, EDGE_FEATURE_SIZE=2, GLOBAL_FEATURE_SIZE=1)

	make_mlp_model ()

	PrintSofie (output, printShape=False)

	RunGNet (inputGraphData)

Variables
	c0 = ROOT.TCanvas()

	c1 = c0.cd(1)

	c2 = c0.cd(2)

	core = ROOT.TMVA.Experimental.SOFIE.RModel_GNN.ParseFromMemory(ep_model._core._network, CoreGraphData, filename = "core")

	CoreGraphData = get_graph_data_dict(num_nodes, num_edges, 2LATENT_SIZE, 2LATENT_SIZE, 2*LATENT_SIZE)

	data = GenerateData()

list	dataSet = []

	DecodeGraphData = get_graph_data_dict(num_nodes,num_edges, LATENT_SIZE, LATENT_SIZE, LATENT_SIZE)

	decoder = ROOT.TMVA.Experimental.SOFIE.RModel_GraphIndependent.ParseFromMemory(ep_model._decoder._network, DecodeGraphData, filename = "decoder")

	edge_data

int	edge_size = 4

	edgesG = outGnet[1].edges.numpy()

	edgesS = np.asarray(outSofie[1].edge_data)

	encoder = ROOT.TMVA.Experimental.SOFIE.RModel_GraphIndependent.ParseFromMemory(ep_model._encoder._network, GraphData, filename = "encoder")

	end = time.time()

	endSC = time.time()

	ep_model = EncodeProcessDecode()

	g = out[1].globals.numpy()

	global_data

int	global_size = 1

	globG = outGnet[1].globals.numpy()

	globS = np.asarray(outSofie[1].global_data)

	gnet_data_i = utils_tf.data_dicts_to_graphs_tuple([graphData])

list	gnetData = []

	gnn = SofieGNN()

	GraphData = get_graph_data_dict(num_nodes,num_edges, node_size, edge_size, global_size)

list	graphData = dataSet[i]

	hDe = ROOT.TH1D("hDe","Difference for edge data",100,1,0)

	hDg = ROOT.TH1D("hDg","Difference for global data",100,1,0)

	hDn = ROOT.TH1D("hDn","Difference for node data",100,1,0)

	hG = ROOT.TH1D("hG","Result from graphnet",100,1,0)

	hS = ROOT.TH1D("hS","Result from SOFIE",100,1,0)

	input_core_graph_data = utils_tf.data_dicts_to_graphs_tuple([CoreGraphData])

	input_data = ROOT.TMVA.Experimental.SOFIE.GNN_Data()

	input_graph_data = utils_tf.data_dicts_to_graphs_tuple([GraphData])

int	LATENT_SIZE = 100

	node_data

int	node_size = 4

	nodesG = outGnet[1].nodes.numpy()

	nodesS = np.asarray(outSofie[1].node_data)

int	num_edges = 20

int	NUM_LAYERS = 4

int	num_nodes = 5

int	numevts = 100

	out = RunGNet(gnetData[i])

	outGnet = RunGNet(gnetData[i])

	output_gn = ep_model(input_graph_data, processing_steps)

	output_transform = ROOT.TMVA.Experimental.SOFIE.RModel_GraphIndependent.ParseFromMemory(ep_model._output_transform._network, DecodeGraphData, filename = "output_transform")

	outSofie = gnn.infer(sofieData[i])

int	processing_steps = 5

	rec = np.array([0,0,0,0,1,1,1,2,2,3,1,2,3,4,2,3,4,3,4,4], dtype='int32')

	receivers

	senders

	snd = np.array([1,2,3,4,2,3,4,3,4,4,0,0,0,0,1,1,1,2,2,3], dtype='int32')

list	sofieData = []

	start = time.time()

	start0 = time.time()

Function Documentation

◆ CopyData()

TMVA_SOFIE_GNN.CopyData ( input_data )

Definition at line 143 of file TMVA_SOFIE_GNN.py.

◆ GenerateData()

TMVA_SOFIE_GNN.GenerateData ( )

Definition at line 176 of file TMVA_SOFIE_GNN.py.

◆ get_graph_data_dict()

TMVA_SOFIE_GNN.get_graph_data_dict	(	num_nodes,
		num_edges,
		NODE_FEATURE_SIZE = `2`,
		EDGE_FEATURE_SIZE = `2`,
		GLOBAL_FEATURE_SIZE = `1`
	)

Definition at line 22 of file TMVA_SOFIE_GNN.py.

◆ make_mlp_model()

TMVA_SOFIE_GNN.make_mlp_model ( )

Definition at line 32 of file TMVA_SOFIE_GNN.py.

◆ PrintSofie()

TMVA_SOFIE_GNN.PrintSofie	(	output,
		printShape = `False`
	)

Definition at line 133 of file TMVA_SOFIE_GNN.py.

◆ RunGNet()

TMVA_SOFIE_GNN.RunGNet ( inputGraphData )

Definition at line 195 of file TMVA_SOFIE_GNN.py.

Variable Documentation

◆ c0

TMVA_SOFIE_GNN.c0 = ROOT.TCanvas()

Definition at line 243 of file TMVA_SOFIE_GNN.py.

◆ c1

TMVA_SOFIE_GNN.c1 = c0.cd(1)

Definition at line 245 of file TMVA_SOFIE_GNN.py.

◆ c2

TMVA_SOFIE_GNN.c2 = c0.cd(2)

Definition at line 278 of file TMVA_SOFIE_GNN.py.

◆ core

TMVA_SOFIE_GNN.core = ROOT.TMVA.Experimental.SOFIE.RModel_GNN.ParseFromMemory(ep_model._core._network, CoreGraphData, filename = "core")

Definition at line 113 of file TMVA_SOFIE_GNN.py.

◆ CoreGraphData

TMVA_SOFIE_GNN.CoreGraphData = get_graph_data_dict(num_nodes, num_edges, 2*LATENT_SIZE, 2*LATENT_SIZE, 2*LATENT_SIZE)

Definition at line 96 of file TMVA_SOFIE_GNN.py.

◆ data

TMVA_SOFIE_GNN.data = GenerateData()

Definition at line 183 of file TMVA_SOFIE_GNN.py.

◆ dataSet

list TMVA_SOFIE_GNN.dataSet = []

Definition at line 181 of file TMVA_SOFIE_GNN.py.

◆ DecodeGraphData

TMVA_SOFIE_GNN.DecodeGraphData = get_graph_data_dict(num_nodes,num_edges, LATENT_SIZE, LATENT_SIZE, LATENT_SIZE)

Definition at line 100 of file TMVA_SOFIE_GNN.py.

◆ decoder

TMVA_SOFIE_GNN.decoder = ROOT.TMVA.Experimental.SOFIE.RModel_GraphIndependent.ParseFromMemory(ep_model._decoder._network, DecodeGraphData, filename = "decoder")

Definition at line 117 of file TMVA_SOFIE_GNN.py.

◆ edge_data

TMVA_SOFIE_GNN.edge_data

Definition at line 215 of file TMVA_SOFIE_GNN.py.

◆ edge_size

int TMVA_SOFIE_GNN.edge_size = 4

Definition at line 15 of file TMVA_SOFIE_GNN.py.

◆ edgesG

TMVA_SOFIE_GNN.edgesG = outGnet[1].edges.numpy()

Definition at line 259 of file TMVA_SOFIE_GNN.py.

◆ edgesS

TMVA_SOFIE_GNN.edgesS = np.asarray(outSofie[1].edge_data)

Definition at line 260 of file TMVA_SOFIE_GNN.py.

◆ encoder

TMVA_SOFIE_GNN.encoder = ROOT.TMVA.Experimental.SOFIE.RModel_GraphIndependent.ParseFromMemory(ep_model._encoder._network, GraphData, filename = "encoder")

Definition at line 109 of file TMVA_SOFIE_GNN.py.

◆ end

TMVA_SOFIE_GNN.end = time.time()

Definition at line 206 of file TMVA_SOFIE_GNN.py.

◆ endSC

TMVA_SOFIE_GNN.endSC = time.time()

Definition at line 226 of file TMVA_SOFIE_GNN.py.

◆ ep_model

TMVA_SOFIE_GNN.ep_model = EncodeProcessDecode()

Definition at line 86 of file TMVA_SOFIE_GNN.py.

◆ g

TMVA_SOFIE_GNN.g = out[1].globals.numpy()

Definition at line 203 of file TMVA_SOFIE_GNN.py.

◆ global_data

TMVA_SOFIE_GNN.global_data

Definition at line 216 of file TMVA_SOFIE_GNN.py.

◆ global_size

int TMVA_SOFIE_GNN.global_size = 1

Definition at line 16 of file TMVA_SOFIE_GNN.py.

◆ globG

TMVA_SOFIE_GNN.globG = outGnet[1].globals.numpy()

Definition at line 272 of file TMVA_SOFIE_GNN.py.

◆ globS

TMVA_SOFIE_GNN.globS = np.asarray(outSofie[1].global_data)

Definition at line 273 of file TMVA_SOFIE_GNN.py.

◆ gnet_data_i

TMVA_SOFIE_GNN.gnet_data_i = utils_tf.data_dicts_to_graphs_tuple([graphData])

Definition at line 191 of file TMVA_SOFIE_GNN.py.

◆ gnetData

list TMVA_SOFIE_GNN.gnetData = []

Definition at line 188 of file TMVA_SOFIE_GNN.py.

◆ gnn

TMVA_SOFIE_GNN.gnn = SofieGNN()

Definition at line 231 of file TMVA_SOFIE_GNN.py.

◆ GraphData

TMVA_SOFIE_GNN.GraphData = get_graph_data_dict(num_nodes,num_edges, node_size, edge_size, global_size)

Definition at line 89 of file TMVA_SOFIE_GNN.py.

◆ graphData

list TMVA_SOFIE_GNN.graphData = dataSet[i]

Definition at line 190 of file TMVA_SOFIE_GNN.py.

◆ hDe

TMVA_SOFIE_GNN.hDe = ROOT.TH1D("hDe","Difference for edge data",100,1,0)

Definition at line 252 of file TMVA_SOFIE_GNN.py.

◆ hDg

TMVA_SOFIE_GNN.hDg = ROOT.TH1D("hDg","Difference for global data",100,1,0)

Definition at line 254 of file TMVA_SOFIE_GNN.py.

◆ hDn

TMVA_SOFIE_GNN.hDn = ROOT.TH1D("hDn","Difference for node data",100,1,0)

Definition at line 253 of file TMVA_SOFIE_GNN.py.

◆ hG

TMVA_SOFIE_GNN.hG = ROOT.TH1D("hG","Result from graphnet",100,1,0)

Definition at line 200 of file TMVA_SOFIE_GNN.py.

◆ hS

TMVA_SOFIE_GNN.hS = ROOT.TH1D("hS","Result from SOFIE",100,1,0)

Definition at line 229 of file TMVA_SOFIE_GNN.py.

◆ input_core_graph_data

TMVA_SOFIE_GNN.input_core_graph_data = utils_tf.data_dicts_to_graphs_tuple([CoreGraphData])

Definition at line 97 of file TMVA_SOFIE_GNN.py.

◆ input_data

TMVA_SOFIE_GNN.input_data = ROOT.TMVA.Experimental.SOFIE.GNN_Data()

Definition at line 213 of file TMVA_SOFIE_GNN.py.

◆ input_graph_data

TMVA_SOFIE_GNN.input_graph_data = utils_tf.data_dicts_to_graphs_tuple([GraphData])

Definition at line 92 of file TMVA_SOFIE_GNN.py.

◆ LATENT_SIZE

int TMVA_SOFIE_GNN.LATENT_SIZE = 100

Definition at line 17 of file TMVA_SOFIE_GNN.py.

◆ node_data

TMVA_SOFIE_GNN.node_data

Definition at line 214 of file TMVA_SOFIE_GNN.py.

◆ node_size

int TMVA_SOFIE_GNN.node_size = 4

Definition at line 14 of file TMVA_SOFIE_GNN.py.

◆ nodesG

TMVA_SOFIE_GNN.nodesG = outGnet[1].nodes.numpy()

Definition at line 266 of file TMVA_SOFIE_GNN.py.

◆ nodesS

TMVA_SOFIE_GNN.nodesS = np.asarray(outSofie[1].node_data)

Definition at line 267 of file TMVA_SOFIE_GNN.py.

◆ num_edges

int TMVA_SOFIE_GNN.num_edges = 20

Definition at line 11 of file TMVA_SOFIE_GNN.py.

◆ NUM_LAYERS

int TMVA_SOFIE_GNN.NUM_LAYERS = 4

Definition at line 18 of file TMVA_SOFIE_GNN.py.

◆ num_nodes

int TMVA_SOFIE_GNN.num_nodes = 5

Definition at line 10 of file TMVA_SOFIE_GNN.py.

◆ numevts

int TMVA_SOFIE_GNN.numevts = 100

Definition at line 180 of file TMVA_SOFIE_GNN.py.

◆ out

TMVA_SOFIE_GNN.out = RunGNet(gnetData[i])

Definition at line 202 of file TMVA_SOFIE_GNN.py.

◆ outGnet

TMVA_SOFIE_GNN.outGnet = RunGNet(gnetData[i])

Definition at line 258 of file TMVA_SOFIE_GNN.py.

◆ output_gn

TMVA_SOFIE_GNN.output_gn = ep_model(input_graph_data, processing_steps)

Definition at line 103 of file TMVA_SOFIE_GNN.py.

◆ output_transform

TMVA_SOFIE_GNN.output_transform = ROOT.TMVA.Experimental.SOFIE.RModel_GraphIndependent.ParseFromMemory(ep_model._output_transform._network, DecodeGraphData, filename = "output_transform")

Definition at line 121 of file TMVA_SOFIE_GNN.py.

◆ outSofie

TMVA_SOFIE_GNN.outSofie = gnn.infer(sofieData[i])

Definition at line 257 of file TMVA_SOFIE_GNN.py.

◆ processing_steps

int TMVA_SOFIE_GNN.processing_steps = 5

Definition at line 19 of file TMVA_SOFIE_GNN.py.

◆ rec

TMVA_SOFIE_GNN.rec = np.array([0,0,0,0,1,1,1,2,2,3,1,2,3,4,2,3,4,3,4,4], dtype='int32')

Definition at line 13 of file TMVA_SOFIE_GNN.py.

◆ receivers

TMVA_SOFIE_GNN.receivers

Definition at line 218 of file TMVA_SOFIE_GNN.py.

◆ senders

TMVA_SOFIE_GNN.senders

Definition at line 219 of file TMVA_SOFIE_GNN.py.

◆ snd

TMVA_SOFIE_GNN.snd = np.array([1,2,3,4,2,3,4,3,4,4,0,0,0,0,1,1,1,2,2,3], dtype='int32')

Definition at line 12 of file TMVA_SOFIE_GNN.py.

◆ sofieData

list TMVA_SOFIE_GNN.sofieData = []

Definition at line 210 of file TMVA_SOFIE_GNN.py.

◆ start

TMVA_SOFIE_GNN.start = time.time()

Definition at line 199 of file TMVA_SOFIE_GNN.py.

◆ start0

TMVA_SOFIE_GNN.start0 = time.time()

Definition at line 230 of file TMVA_SOFIE_GNN.py.

Classes

Functions

Variables