Tengo un conjunto de datos de millones de segmentos de línea dirigida. Los segmentos de línea son secuenciales: es una variable climática (calor sensible), con valores observados y simulados a intervalos de media hora. Estoy tratando de buscar patrones en el rendimiento de la simulación. Estoy viendo un diagrama de dispersión de valores de obs vs simulación, y vinculándolos con segmentos de línea (las flechas indican la dirección del tiempo). Si los trazo, me sale un desorden borroso que es imposible de interpretar, así:
Este es un subconjunto de 10000 líneas, trazadas bien y con baja opacidad:
ggplot(d, aes(x=Qh_obs, xend=lead(Qh_obs), y=Qh_sim, yend=lead(Qh_sim))) +
geom_segment(size=0.1, alpha=0.2, arrow=arrow(length=unit(2, units='mm')))
dput() de las primeras 700 filas de datos (limitado por la longitud de la publicación):
structure(
list(
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Estoy interesado en tratar de resumir visualmente el flujo de estas líneas. ¿Hay alguna forma común de resumir este tipo de información? Simplemente podría hacer un diagrama de campo vectorial, pero creo que perdería información relevante, en particular, algunas de las áreas más densas probablemente tienen múltiples grupos de segmentos. Estoy considerando agrupar los segmentos (usando las cuatro variables como características) y luego trazar los promedios, o tal vez hacer un campo vectorial de rosas de viento, pero quería ver si había alguna forma mejor de hacerlo.
Respuestas:
También podría dividirse en fragmentos de tiempo y hacer trazados facetados. Esto ayudaría si el flujo retrocede y avanza sobre sí mismo varias veces.
Es posible suavizar los segmentos para tener una idea del flujo también, pero creo que el facetado sería un primer paso.
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Una posibilidad sería promediar los días, obtener uno o unos pocos ciclos diarios "promedio" en lugar de más de 1,000 días individuales.
Otra idea podría ser una representación en 3D como en Tominski, Schumann, Andrienko y Andrienko (2012) .
Referencia:
Tominski, C., Schumann, H., Andrienko, G., Andrienko, N. (2012). Visualización basada en apilamiento de datos de atributos de trayectoria. Visualization and Computer Graphics, IEEE Transactions on , vol.18, no.12, pp.2565,2574, Dec. 2012. doi: 10.1109 / TVCG.2012.265. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6327262&isnumber=6327196
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