|
17 | 17 | num_edges: [20, 20, 20, 20, 20] |
18 | 18 | num_snapshots: 5 |
19 | 19 | tgdata: |
20 | | - x = 4-element Vector{Float64}</code></pre></div><a class="docs-sourcelink" target="_blank" href="https://github.com/JuliaGraphs/GraphNeuralNetworks.jl/blob/78935125575cafe78001aad29952052e841c2774/GNNGraphs/src/temporalsnapshotsgnngraph.jl#L1-L37">source</a></section></article><article class="docstring"><header><a class="docstring-article-toggle-button fa-solid fa-chevron-down" href="javascript:;" title="Collapse docstring"></a><a class="docstring-binding" id="GNNGraphs.add_snapshot-Tuple{TemporalSnapshotsGNNGraph, Int64, GNNGraph}" href="#GNNGraphs.add_snapshot-Tuple{TemporalSnapshotsGNNGraph, Int64, GNNGraph}"><code>GNNGraphs.add_snapshot</code></a> — <span class="docstring-category">Method</span><span class="is-flex-grow-1 docstring-article-toggle-button" title="Collapse docstring"></span></header><section><div><pre><code class="language-julia hljs">add_snapshot(tg::TemporalSnapshotsGNNGraph, t::Int, g::GNNGraph)</code></pre><p>Return a <code>TemporalSnapshotsGNNGraph</code> created starting from <code>tg</code> by adding the snapshot <code>g</code> at time index <code>t</code>.</p><p><strong>Examples</strong></p><pre><code class="language-julia-repl hljs">julia> using GNNGraphs |
| 20 | + x = 4-element Vector{Float64}</code></pre></div><a class="docs-sourcelink" target="_blank" href="https://github.com/JuliaGraphs/GraphNeuralNetworks.jl/blob/7bd58c6812b1a81debae0543e3a5c90369aefae1/GNNGraphs/src/temporalsnapshotsgnngraph.jl#L1-L37">source</a></section></article><article class="docstring"><header><a class="docstring-article-toggle-button fa-solid fa-chevron-down" href="javascript:;" title="Collapse docstring"></a><a class="docstring-binding" id="GNNGraphs.add_snapshot-Tuple{TemporalSnapshotsGNNGraph, Int64, GNNGraph}" href="#GNNGraphs.add_snapshot-Tuple{TemporalSnapshotsGNNGraph, Int64, GNNGraph}"><code>GNNGraphs.add_snapshot</code></a> — <span class="docstring-category">Method</span><span class="is-flex-grow-1 docstring-article-toggle-button" title="Collapse docstring"></span></header><section><div><pre><code class="language-julia hljs">add_snapshot(tg::TemporalSnapshotsGNNGraph, t::Int, g::GNNGraph)</code></pre><p>Return a <code>TemporalSnapshotsGNNGraph</code> created starting from <code>tg</code> by adding the snapshot <code>g</code> at time index <code>t</code>.</p><p><strong>Examples</strong></p><pre><code class="language-julia-repl hljs">julia> using GNNGraphs |
21 | 21 |
|
22 | 22 | julia> snapshots = [rand_graph(10, 20) for i in 1:5]; |
23 | 23 |
|
|
31 | 31 | TemporalSnapshotsGNNGraph: |
32 | 32 | num_nodes: [10, 10, 10, 10, 10, 10] |
33 | 33 | num_edges: [20, 20, 16, 20, 20, 20] |
34 | | - num_snapshots: 6</code></pre></div><a class="docs-sourcelink" target="_blank" href="https://github.com/JuliaGraphs/GraphNeuralNetworks.jl/blob/78935125575cafe78001aad29952052e841c2774/GNNGraphs/src/temporalsnapshotsgnngraph.jl#L73-L97">source</a></section></article><article class="docstring"><header><a class="docstring-article-toggle-button fa-solid fa-chevron-down" href="javascript:;" title="Collapse docstring"></a><a class="docstring-binding" id="GNNGraphs.remove_snapshot-Tuple{TemporalSnapshotsGNNGraph, Int64}" href="#GNNGraphs.remove_snapshot-Tuple{TemporalSnapshotsGNNGraph, Int64}"><code>GNNGraphs.remove_snapshot</code></a> — <span class="docstring-category">Method</span><span class="is-flex-grow-1 docstring-article-toggle-button" title="Collapse docstring"></span></header><section><div><pre><code class="language-julia hljs">remove_snapshot(tg::TemporalSnapshotsGNNGraph, t::Int)</code></pre><p>Return a <a href="#TemporalSnapshotsGNNGraph"><code>TemporalSnapshotsGNNGraph</code></a> created starting from <code>tg</code> by removing the snapshot at time index <code>t</code>.</p><p><strong>Examples</strong></p><pre><code class="language-julia-repl hljs">julia> using GNNGraphs |
| 34 | + num_snapshots: 6</code></pre></div><a class="docs-sourcelink" target="_blank" href="https://github.com/JuliaGraphs/GraphNeuralNetworks.jl/blob/7bd58c6812b1a81debae0543e3a5c90369aefae1/GNNGraphs/src/temporalsnapshotsgnngraph.jl#L73-L97">source</a></section></article><article class="docstring"><header><a class="docstring-article-toggle-button fa-solid fa-chevron-down" href="javascript:;" title="Collapse docstring"></a><a class="docstring-binding" id="GNNGraphs.remove_snapshot-Tuple{TemporalSnapshotsGNNGraph, Int64}" href="#GNNGraphs.remove_snapshot-Tuple{TemporalSnapshotsGNNGraph, Int64}"><code>GNNGraphs.remove_snapshot</code></a> — <span class="docstring-category">Method</span><span class="is-flex-grow-1 docstring-article-toggle-button" title="Collapse docstring"></span></header><section><div><pre><code class="language-julia hljs">remove_snapshot(tg::TemporalSnapshotsGNNGraph, t::Int)</code></pre><p>Return a <a href="#TemporalSnapshotsGNNGraph"><code>TemporalSnapshotsGNNGraph</code></a> created starting from <code>tg</code> by removing the snapshot at time index <code>t</code>.</p><p><strong>Examples</strong></p><pre><code class="language-julia-repl hljs">julia> using GNNGraphs |
35 | 35 |
|
36 | 36 | julia> snapshots = [rand_graph(10,20), rand_graph(10,14), rand_graph(10,22)]; |
37 | 37 |
|
|
45 | 45 | TemporalSnapshotsGNNGraph: |
46 | 46 | num_nodes: [10, 10] |
47 | 47 | num_edges: [20, 22] |
48 | | - num_snapshots: 2</code></pre></div><a class="docs-sourcelink" target="_blank" href="https://github.com/JuliaGraphs/GraphNeuralNetworks.jl/blob/78935125575cafe78001aad29952052e841c2774/GNNGraphs/src/temporalsnapshotsgnngraph.jl#L133-L157">source</a></section></article><h2 id="Random-Generators"><a class="docs-heading-anchor" href="#Random-Generators">Random Generators</a><a id="Random-Generators-1"></a><a class="docs-heading-anchor-permalink" href="#Random-Generators" title="Permalink"></a></h2><article class="docstring"><header><a class="docstring-article-toggle-button fa-solid fa-chevron-down" href="javascript:;" title="Collapse docstring"></a><a class="docstring-binding" id="GNNGraphs.rand_temporal_radius_graph" href="#GNNGraphs.rand_temporal_radius_graph"><code>GNNGraphs.rand_temporal_radius_graph</code></a> — <span class="docstring-category">Function</span><span class="is-flex-grow-1 docstring-article-toggle-button" title="Collapse docstring"></span></header><section><div><pre><code class="language-julia hljs">rand_temporal_radius_graph(number_nodes::Int, |
| 48 | + num_snapshots: 2</code></pre></div><a class="docs-sourcelink" target="_blank" href="https://github.com/JuliaGraphs/GraphNeuralNetworks.jl/blob/7bd58c6812b1a81debae0543e3a5c90369aefae1/GNNGraphs/src/temporalsnapshotsgnngraph.jl#L133-L157">source</a></section></article><h2 id="Random-Generators"><a class="docs-heading-anchor" href="#Random-Generators">Random Generators</a><a id="Random-Generators-1"></a><a class="docs-heading-anchor-permalink" href="#Random-Generators" title="Permalink"></a></h2><article class="docstring"><header><a class="docstring-article-toggle-button fa-solid fa-chevron-down" href="javascript:;" title="Collapse docstring"></a><a class="docstring-binding" id="GNNGraphs.rand_temporal_radius_graph" href="#GNNGraphs.rand_temporal_radius_graph"><code>GNNGraphs.rand_temporal_radius_graph</code></a> — <span class="docstring-category">Function</span><span class="is-flex-grow-1 docstring-article-toggle-button" title="Collapse docstring"></span></header><section><div><pre><code class="language-julia hljs">rand_temporal_radius_graph(number_nodes::Int, |
49 | 49 | number_snapshots::Int, |
50 | 50 | speed::AbstractFloat, |
51 | 51 | r::AbstractFloat; |
|
57 | 57 | TemporalSnapshotsGNNGraph: |
58 | 58 | num_nodes: [10, 10, 10, 10, 10] |
59 | 59 | num_edges: [90, 90, 90, 90, 90] |
60 | | - num_snapshots: 5</code></pre></div><a class="docs-sourcelink" target="_blank" href="https://github.com/JuliaGraphs/GraphNeuralNetworks.jl/blob/78935125575cafe78001aad29952052e841c2774/GNNGraphs/src/generate.jl#L224-L264">source</a></section></article><article class="docstring"><header><a class="docstring-article-toggle-button fa-solid fa-chevron-down" href="javascript:;" title="Collapse docstring"></a><a class="docstring-binding" id="GNNGraphs.rand_temporal_hyperbolic_graph" href="#GNNGraphs.rand_temporal_hyperbolic_graph"><code>GNNGraphs.rand_temporal_hyperbolic_graph</code></a> — <span class="docstring-category">Function</span><span class="is-flex-grow-1 docstring-article-toggle-button" title="Collapse docstring"></span></header><section><div><pre><code class="language-julia hljs">rand_temporal_hyperbolic_graph(number_nodes::Int, |
| 60 | + num_snapshots: 5</code></pre></div><a class="docs-sourcelink" target="_blank" href="https://github.com/JuliaGraphs/GraphNeuralNetworks.jl/blob/7bd58c6812b1a81debae0543e3a5c90369aefae1/GNNGraphs/src/generate.jl#L224-L264">source</a></section></article><article class="docstring"><header><a class="docstring-article-toggle-button fa-solid fa-chevron-down" href="javascript:;" title="Collapse docstring"></a><a class="docstring-binding" id="GNNGraphs.rand_temporal_hyperbolic_graph" href="#GNNGraphs.rand_temporal_hyperbolic_graph"><code>GNNGraphs.rand_temporal_hyperbolic_graph</code></a> — <span class="docstring-category">Function</span><span class="is-flex-grow-1 docstring-article-toggle-button" title="Collapse docstring"></span></header><section><div><pre><code class="language-julia hljs">rand_temporal_hyperbolic_graph(number_nodes::Int, |
61 | 61 | number_snapshots::Int; |
62 | 62 | α::Real, |
63 | 63 | R::Real, |
|
70 | 70 | TemporalSnapshotsGNNGraph: |
71 | 71 | num_nodes: [10, 10, 10, 10, 10] |
72 | 72 | num_edges: [44, 46, 48, 42, 38] |
73 | | - num_snapshots: 5</code></pre><p><strong>References</strong></p><p>Section D of the paper <a href="https://arxiv.org/pdf/2101.00414.pdf">Dynamic Hidden-Variable Network Models</a> and the paper <a href="https://arxiv.org/pdf/1006.5169.pdf">Hyperbolic Geometry of Complex Networks</a></p></div><a class="docs-sourcelink" target="_blank" href="https://github.com/JuliaGraphs/GraphNeuralNetworks.jl/blob/78935125575cafe78001aad29952052e841c2774/GNNGraphs/src/generate.jl#L299-L339">source</a></section></article></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../heterograph/">« GNNHeteroGraph</a><a class="docs-footer-nextpage" href="../samplers/">Samplers »</a><div class="flexbox-break"></div><p class="footer-message">Powered by <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> and the <a href="https://julialang.org/">Julia Programming Language</a>.</p></nav></div><div class="modal" id="documenter-settings"><div class="modal-background"></div><div class="modal-card"><header class="modal-card-head"><p class="modal-card-title">Settings</p><button class="delete"></button></header><section class="modal-card-body"><p><label class="label">Theme</label><div class="select"><select id="documenter-themepicker"><option value="auto">Automatic (OS)</option><option value="documenter-light">documenter-light</option><option value="documenter-dark">documenter-dark</option><option value="catppuccin-latte">catppuccin-latte</option><option value="catppuccin-frappe">catppuccin-frappe</option><option value="catppuccin-macchiato">catppuccin-macchiato</option><option value="catppuccin-mocha">catppuccin-mocha</option></select></div></p><hr/><p>This document was generated with <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> version 1.8.0 on <span class="colophon-date" title="Friday 6 December 2024 23:26">Friday 6 December 2024</span>. Using Julia version 1.10.5.</p></section><footer class="modal-card-foot"></footer></div></div></div></body><div data-docstringscollapsed="true"></div></html> |
| 73 | + num_snapshots: 5</code></pre><p><strong>References</strong></p><p>Section D of the paper <a href="https://arxiv.org/pdf/2101.00414.pdf">Dynamic Hidden-Variable Network Models</a> and the paper <a href="https://arxiv.org/pdf/1006.5169.pdf">Hyperbolic Geometry of Complex Networks</a></p></div><a class="docs-sourcelink" target="_blank" href="https://github.com/JuliaGraphs/GraphNeuralNetworks.jl/blob/7bd58c6812b1a81debae0543e3a5c90369aefae1/GNNGraphs/src/generate.jl#L299-L339">source</a></section></article></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../heterograph/">« GNNHeteroGraph</a><a class="docs-footer-nextpage" href="../samplers/">Samplers »</a><div class="flexbox-break"></div><p class="footer-message">Powered by <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> and the <a href="https://julialang.org/">Julia Programming Language</a>.</p></nav></div><div class="modal" id="documenter-settings"><div class="modal-background"></div><div class="modal-card"><header class="modal-card-head"><p class="modal-card-title">Settings</p><button class="delete"></button></header><section class="modal-card-body"><p><label class="label">Theme</label><div class="select"><select id="documenter-themepicker"><option value="auto">Automatic (OS)</option><option value="documenter-light">documenter-light</option><option value="documenter-dark">documenter-dark</option><option value="catppuccin-latte">catppuccin-latte</option><option value="catppuccin-frappe">catppuccin-frappe</option><option value="catppuccin-macchiato">catppuccin-macchiato</option><option value="catppuccin-mocha">catppuccin-mocha</option></select></div></p><hr/><p>This document was generated with <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> version 1.8.0 on <span class="colophon-date" title="Saturday 7 December 2024 08:42">Saturday 7 December 2024</span>. Using Julia version 1.10.5.</p></section><footer class="modal-card-foot"></footer></div></div></div></body><div data-docstringscollapsed="true"></div></html> |
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