一维到三维密度分布函数及其可视化在大数据分析中的应用——以苦橄质玄武岩等为例

One-dimensional to three-dimensional density distribution functions and their applications in visualized big data analysis:Exemplified by picritic basalt and some other rocks

提出不同维度的密度分布函数的计算方法和可视化方案,以解决不同数量级和不同测量误差的岩石样本数据分析对比困难的问题。通过SiO2、全碱和MgO指标的三维密度分布函数和t-分布随机邻域嵌入可视化方法对GEOROC和PETDB数据库进行发掘,发现大洋岩(oceanite)和富辉橄玄岩(ankaramite)与苦橄质玄武岩(basalt,picritic)成分相近,而铁质苦橄岩(picrite,ferro)与侵入的橄榄辉长岩和苦橄岩(picrite)成分相似。利用二维密度分布函数和可视化技术,对比分析了不同岩石在TAS图解和硅镁图上的数据分布状态和数据集中核心区域。发现总体分布上,更富镁的苦橄岩的SiO2含量高于苦橄质玄武岩,超基性的苦橄岩(picrate)核心区域主要分布在TAS图解的B区,这与以SiO2=45%划分基性岩和超基性岩界线的观点矛盾。

In this paper,the calculation methods and visualization schemes of density distribution functions of different dimensions are proposed to solve the problem of difficulties in analysis and comparison of rock sample data with different orders of magnitude and different measurement errors.Data mining based on the GEOROC and PETDB databases by using the three-dimensional density distribution function of SiO2,total alkali and MgO index as well as the t-distribution random neighborhood embedding visualization method revealed that picritic basalt is similar to oceanite and ankaramite,while picrate is similar to intrusive olivine gabbro and ferropicrate.Comparisons between two-dimensional density distribution function and cumulative density contour visualization were used to analyze the data distribution of different rocks on TAS and Si-Mg maps and the core area of data concentration.It is found that the SiO2 content of magnesium-rich picrite is higher than that of picrite basalt in general distribution.The core area of picrite is mainly located in the B area of TAS diagram,which is contrary to the traditional view that SiO2=45%is used as the boundary between basic and ultramafic rocks.