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• position of the detector w.r.t. interaction point (IP) is not well known,
• in some cases detector consists of a few sub-detectors,
• sometimes sub-detectors may move w.r.t. each other,
• sub-detectors (different in general) consist of precisely engineered sensors which positions are not well known and need to be calibrated. 

To solve problem for this type of geometry description describe such a geometry we may consider a variable length series of hierarchical objects like pixel → sensor → sub-detector → detector → setup, where each low-level child object is included in its higher-level parent object. For each node of this hierarchical model low-level objects form the tree, which is convenient for recursions. Each child object position and orientation can be described in the parent frame. Tree-like structure can be kept in form of table , saved in and retrieved from the file. The last feature is practically convenient for calibration purpose; all constants for detector/experiment geometry description can be saved in a single file. Whenever new geometry information is available, for example from optical measurement or dedicated runs with bright diffraction rings, particular part of the hierarchical table can be updated.

This note contains description of the hierarchical geometry model, implemented coordinate transformation algorithms, parametrization of the hierarchical geometry through the in table, description of software interface in C++ and Python, details of calibration, etc.

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