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6 results for “Simplicial Complexes”
Experimental validation of simplicial complexes in multivariable coupled oscillators. Coupling: Lineal (Class III) vs NoLineal (Class III)
<p>The data sets correspond to the experimental implementation of synchronization phenomenon in <strong>simplicial complexes</strong>. In this particular case, the simplicial complex consists of 3-node network, where each node is an electronic Rössler-like oscillator whose parameters were fixed to operate in <strong>chaotic regime</strong>. In simplicial complexes, it is possible to model two types of interactions among nodes: <strong>pair-wise interactions (linear interactions)</strong> and <strong>high-order interactions (non-linear interactions)</strong>.</p> <p>The complete experiment consists of coupling simultaneously by means of linear and non-linear interactions the simplicial complex, the coupling occurs in state variables x (class III) and y (class II). The full data sets are organized in four Dataset, whose name explicitly indicates in which state variable occurs each coupling. In these case, Linearx-nonlinearx means that the linear coupling occurs in variable <em><strong>x</strong></em> (class III) whereas the non-linear coupling occurs in variable<em><strong> x</strong></em> (class III).</p> <p>Now, each folder contains 10000 files which come from varying the linear coupling and the nonlinear coupling 100 times each one. The file name is composed as follows: rootname XX YY, where XX corresponds to the variation number in linear coupling, whereas YY corresponds to the variation number in non-linear coupling.</p> <p>Internally in each file we can find 6 columns and 30,000 rows. Each pair of columns corresponds to the<strong><em> x</em></strong> and <strong><em>y</em></strong> variables of each oscillator and the rows correspond to time-varying samples.</p>
Experimental validation of simplicial complexes in multivariable coupled oscillators. Coupling: Lineal (Class III) vs NoLineal (Class II)
<p>The data sets correspond to the experimental implementation of synchronization phenomenon in<strong> simplicial complexe</strong>s. In this particular case, the simplicial complex consists of 3-node network, where each node is an electronic Rössler-like oscillator whose parameters were fixed to operate in <strong>chaotic regime</strong>. In simplicial complexes, it is possible to model two types of interactions among nodes: <strong>pair-wise interactions</strong> (linear interactions) and <strong>high-order interactions</strong> (non-linear interactions).</p> <p>The complete experiment consists of coupling simultaneously by means of linear and non-linear interactions the simplicial complex, the coupling occurs in state variables x (class III) and y (class II). The full data sets are organized in four Dataset (second), whose name explicitly indicates in which state variable occurs each coupling. In these case, Linearx-nonlineary means that the linear coupling occurs in variable <em><strong>x</strong></em> (class III) whereas the non-linear coupling occurs in variable <em><strong>y</strong></em> (class II).</p> <p>Now, each folder contains 10000 files which come from varying the linear coupling and the nonlinear coupling 100 times each one. The file name is composed as follows: rootname XX YY, where XX corresponds to the variation number in linear coupling, whereas YY corresponds to the variation number in non-linear coupling.</p> <p>Internally in each file we can find 6 columns and 30,000 rows. Each pair of columns corresponds to the <em><strong>x</strong></em> and <em><strong>y</strong></em> variables of each oscillator and the rows correspond to time-varying samples.</p>
Experimental validation of simplicial complexes in multivariable coupled oscillators. Coupling: Lineal (Class II) vs NoLineal (Class III)
<p>The data sets correspond to the experimental implementation of synchronization phenomenon in <strong>simplicial complexes</strong>. In this particular case, the simplicial complex consists of 3-node network, where each node is an electronic Rössler-like oscillator whose parameters were fixed to operate in <strong>chaotic regime</strong>. In simplicial complexes, it is possible to model two types of interactions among nodes: <strong>pair-wise interactions</strong> (linear interactions) and <strong>high-order interactions</strong> (non-linear interactions).</p> <p>The complete experiment consists of coupling simultaneously by means of linear and non-linear interactions the simplicial complex, the coupling occurs in state variables x (class III) and y (class II). The full data sets are organized in four Dataset (third), whose name explicitly indicates in which state variable occurs each coupling. In these case, Lineary-nonlinearx means that the linear coupling occurs in <strong>variable y</strong> (class II) whereas the non-linear coupling occurs in <strong>variable x</strong> (class III).</p> <p>Now, each folder contains 10000 files which come from varying the linear coupling and the nonlinear coupling 100 times each one. The file name is composed as follows: rootname XX YY, where XX corresponds to the variation number in linear coupling, whereas YY corresponds to the variation number in non-linear coupling.</p> <p>Internally in each file we can find 6 columns and 30,000 rows. Each pair of columns corresponds to the x and y variables of each oscillator and the rows correspond to time-varying samples.</p>
Experimental validation of simplicial complexes in multivariable coupled oscillators. Coupling: Lineal (Class II) vs NoLineal (Class II)
<p>The data sets correspond to the experimental implementation of synchronization phenomenon in <strong>simplicial complexes</strong>. In this particular case, the simplicial complex consists of 3-node network, where each node is an electronic Rössler-like oscillator whose parameters were fixed to operate in <strong>chaotic regime</strong>. In simplicial complexes, it is possible to model two types of interactions among nodes: <strong>pair-wise interactions</strong> (linear interactions) and<strong> high-order interaction</strong>s (non-linear interactions).</p> <p>The complete experiment consists of coupling simultaneously by means of linear and non-linear interactions the simplicial complex, the coupling occurs in state variables x (class III) and y (class II). The full data sets are organized in four Dataset (fourth), whose name explicitly indicates in which state variable occurs each coupling. In these case, Linearx-nonlinearx means that the linear coupling occurs in variable <strong>y</strong> (class II) whereas the non-linear coupling occurs in variable <strong>y</strong> (class II).</p> <p>Now, each folder contains 10000 files which come from varying the linear coupling and the nonlinear coupling 100 times each one. The file name is composed as follows: rootname XX YY, where XX corresponds to the variation number in linear coupling, whereas YY corresponds to the variation number in non-linear coupling.</p> <p>Internally in each file we can find 6 columns and 30,000 rows. Each pair of columns corresponds to the x and y variables of each oscillator and the rows correspond to time-varying samples.</p>
Data for: Capturing complex interactions in disease ecology with simplicial sets
<p>Here we provide archived code for: Code for Capturing Complex Interactions in Disease Ecology with Simplicial Sets. Ecology Letters. The code provided can be used to generate the figures used in the manuscript as well as to generate appendix 3 in the supplementary materials. In the paper, we describe how higher-order network approaches can be applied in disease ecology research. We explain <em>what</em> simplicial sets are; <em>why</em> their use would be beneficial in different subject areas; <em>where</em> these areas are: social, transmission, movement/spatial and ecological networks; and <em>when</em> using them would help most in each context. To demonstrate their application, we develop a novel approach to identify how pathogens persist within a host population (see code for Appendix 3 in this repository). We also provide an overview of <em>how</em> to use simplicial sets, highlighting specific metrics, generative models and software. Finally, we <em>synthesize</em> key research questions simplicial sets will help us answer and highlight the methodological developments required.</p>
Data for: Capturing complex interactions in disease ecology with simplicial sets
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