标题： 用户界面软件的开发，用于安装在马约拉天文台的天文学光谱仪COLORES 显示英文标题

标题： Desarrollo del software de interfaz de usuario para el espectrógrafo astronómico COLORES instalado en el observatorio de la Mayora

摘要： 本论文项目源于将位于La Mayora并属于Burst Observer and Optical Transient Exploring System (BOOTES)望远镜网络的光谱仪（COLORES）投入运行的需求。 位于BOOTES 2的机器人望远镜具有许多优点，其中包括能够以非常低的反应时间执行大量观测。 这使得可以获得大量关于天体定位和特征的数据。 有了这个工具的运行，现在可以从观测中提取大量新参数，使该站拥有一个更完整和多功能的仪器，以获得更有意思的科学信息。 为此，将执行一系列脚本。 具体来说有两个，一个用于光谱仪的校准，另一个负责图像处理和光谱提取。 这将使用Spyder软件（Python）来完成，在此软件中，还将进行大量测试以验证软件是否正常工作。 一旦完成这些测试，它将被实施到望远镜的网页上供使用。 为此将使用一些库，包括Astropy，它包含一个完整的Python天文数据处理包，以及Matplotlib，它允许使用从数组中的数据生成的图形。 此外，还将使用多种图像采集技术，如：过滤、高斯调整和干扰区域的使用。 通过所有这些，将优化从望远镜提取的数据以达到预期的结果。 显示英文摘要

摘要： This thesis project arises from the need to put into operation the spectrograph (COLORES) of the station (BOOTES 2), located in La Mayora and belonging to the network of Burst Observer and Optical Transient Exploring System (BOOTES) telescopes. A robotic telescope such as the one located at BOOTES 2 has, among its many virtues, the ability to perform a multitude of observations with a very low reaction time. This makes it possible to obtain a large amount of data on the positioning and characterization of astronomical bodies. With this tool in operation, it will now be possible to extract a multitude of new parameters from the observations, providing this station with a more complete and versatile instrument with which to obtain more interesting scientific information. For this task, a series of scripts will be performed. Specifically two, one for the calibration of the spectrograph and another one in charge of the image processing and the extraction of its spectrum. This will be carried out using Spyder software (Python), in which, in addition, numerous tests will be carried out to verify that the software works perfectly. Once these tests have been carried out, it will be implemented in the telescope's Web page for its use. Several libraries will be used for this purpose, including Astropy, which includes a complete package for handling astronomical data in Python, and Matplotlib, which allows the use of graphics generated from data contained in arrays. In addition, several image acquisition techniques will be used, such as: filtering, Gaussian adjustment, and use of regions of interferences. With all this, the data extracted from the telescope will be optimized to achieve the desired results.