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In this paper, we present CALSAGOS : Clustering ALgorithmS Applied to Galaxies in Overdense Systems which is a PYTHON package developed to select cluster members and to search, find, and identify substructures. CALSAGOS is based on clustering algorithms, and was developed to be used in spectroscopic and photometric samples. To test the performance of CALSAGOS , we use the S-PLUS's mock catalogues, and we found an error of 1–6 per cent on member selection depending on the function that is used. Besides, CALSAGOS has a F 1-score of 0.8, a precision of 85 per cent and a completeness of 100 per cent in the identification of substructures in the outer regions of galaxy clusters (r > r 200). The F 1-score, precision, and completeness of CALSAGOS fall to 0.5, 75, and 40 per cent when we consider all substructure identifications (inner and outer) due to the function that searches, finds, and identifies the substructures works in 2D, and cannot resolve the substructures projected over others. [ABSTRACT FROM AUTHOR]

Although trivial in principle, direct comparison of galaxy clusters X-ray observations to numerical hydro– N-body simulations is not always simple, because of many possible artefacts introduced by the instrument response, sky background and instrumental noise. To address these problems, we constructed the software package x-mas (X-ray Map Simulator), a tool devoted to simulate X-ray observations of galaxy clusters obtained from hydro– N-body simulations. One of the main features of x-mas is the ability to generate event files following the same standards used for real observations. This implies that its simulated observations can be analysed in the same way as – and with the same tools of – real observations. In this paper we present how the x-mas package works, and discuss its application to the simulation of Chandra ACIS-S3 observations. Using the results of high-resolution hydro– N-body simulations, we generate fake Chandra observations of a number of simulated clusters. We then compare some of the main physical properties of the input data to those derived from the simulated observations after performing a standard imaging and spectral analysis. We find that, because of the sky background, the lower surface brightness spatial substructures, which can be easily identified in the simulations, are no longer detected in the simulated observations. We also show that, when a cluster has a complex (i.e. not isothermal) thermal structure along the line of sight, then the projected spectroscopic temperature obtained from the observation is significantly lower than the emission-weighed value inferred directly from hydrodynamical simulation. This implies that much attention should be paid in the theoretical interpretation of observed temperatures. [ABSTRACT FROM AUTHOR]