Automatic visual analysis method and system for celestial body spectral data

Abstract

The invention discloses an automatic visual analysis method and system for celestial body spectral data, and belongs to the technical field of astronomical spectral analysis and big data processing and analysis. The problems that many tedious screening, drawing and other work are needed during spectral analysis, and a large number of unknown types of spectrum clustering and outlier spectrum searching and analysis are lack of automation are solved. According to the technical scheme, the method comprises the following steps: acquiring spectral data and preprocessing the spectral data; reducing the preprocessed spectral data to two dimensions by using an SP-tSNE dimension reduction algorithm; projecting the data after dimension reduction to an interactive two-dimensional plane for visualization; carrying out frame selection on points on the interactive two-dimensional plane by using a mouse, and automatically displaying a mean value spectrum of spectrums corresponding to the points in the region by the system; a user marks an emitting ray and an absorbing ray on the spectrum according to own needs, and the position of the ray can be adjusted by adjusting the red shift; the system provides a function of storing the spectrum of the frame selection area; the method is applied to celestial body spectrum analysis.

Description

technical field [0001] The invention relates to an automatic visual analysis method and system for astronomical spectral data, belonging to the technical fields of astronomical spectral analysis, big data processing and analysis. Background technique [0002] Astronomy is a discipline with a long history. In recent years, with the implementation of a large number of sky survey projects, we have obtained a large amount of astronomical data to help us analyze celestial bodies and the universe. The spectra of celestial bodies contain a lot of physical information. It is of great significance to study galaxy evolution and star formation. Classifying spectra is the primary task of spectral analysis, and the discovery of outlier spectra may be of great help to the study of rare celestial objects. [0003] There are already many excellent methods for spectral classification and anomalous spectral search. These methods provide great help for the classification of a large number of ...

AI Technical Summary

Problems solved by technology

[0003] Nowadays, there are many excellent methods for spectral classification and finding abnormal spectra. These methods have provided great help for the classification of a large number of spectra. However, for rigorous consideration, the final results of some rare types of spectra still need to be determined by astronomers based on experience. , and these methods lack automation in the links that require manual intervention, and are often manually screened and observed, which will waste a lot of energy

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