CQARCHAEO: A PYTHON']PYTHON PACKAGE FOR COSINE QUANTOGRAM ANALYSIS AND MONTE CARLO SIMULATIONS

被引:0
|
作者
Lago, Giancarlo [1 ,2 ]
Cardarelli, Lorenzo [3 ,4 ]
Ialongo, Nicola [5 ]
机构
[1] Univ Salento, Dipartimento Beni Culturali, Lecce, Italy
[2] Univ Bologna, Dipartimento Sci Econ DSE, Bologna, Italy
[3] Sapienza Univ Roma, Dipartimento Sci Antichita, Rome, Italy
[4] CNR, Ist Sci Patrimonio Culturale, Naples, Italy
[5] Georg August Univ, Seminar Ur & Fruhgeschichte, Gottingen, Germany
来源
ARCHEOLOGIA E CALCOLATORI | 2024年 / 35卷 / 01期
关键词
WEIGHTS;
D O I
10.19282/ac.35.1.2024.15
中图分类号
K85 [文物考古];
学科分类号
0601 ;
摘要
Cosine Quantogram Analysis (CQA) is a statistical analysis employed in archaeology for the study of numerical datasets with hypothesized quantal distribution. To verify thesignificance of the results, the analysis is often combined with the execution of Monte Carlo simulations. In this article, we present a freely downloadable Python package (CQArchaeo) that integrates CQA and Monte Carlo simulations in the same environment, making the analysis customizable in the main parameters. We provide a guide that enables the use of this tool even for researchers with limited experience in Python programming and demonstrate the applicability, functioning, and main limitations of the analysis on some archaeological datasets.
引用
收藏
页码:215 / 232
页数:18
相关论文
共 50 条
  • [1] Asymmetric Uncertainties in Measurements: SOAD A Python']Python Package Based on Monte Carlo Simulations
    Erdim, M. Kiyami
    Hudaverdi, Murat
    TURKISH PHYSICAL SOCIETY 35TH INTERNATIONAL PHYSICS CONGRESS (TPS35), 2019, 2178
  • [2] A Python']Python program for the implementation of the Γ-method for Monte Carlo simulations
    De Palma, Barbara
    Erba, Marco
    Mantovani, Luca
    Mosco, Nicola
    COMPUTER PHYSICS COMMUNICATIONS, 2019, 234 : 294 - 301
  • [3] Pytim: A Python']Python Package for the Interfacial Analysis of Molecular Simulations
    Sega, Marcello
    Hantal, Gyoergy
    Fabian, Balazs
    Jedlovszky, Pal
    JOURNAL OF COMPUTATIONAL CHEMISTRY, 2018, 39 (25) : 2118 - 2125
  • [4] kMCpy: A python']python package to simulate transport properties in solids with kinetic Monte Carlo
    Deng, Zeyu
    Mishra, Tara P.
    Xie, Weihang
    Saeed, Daanyal Ahmed
    Gautam, Gopalakrishnan Sai
    Canepa, Pieremanuele
    COMPUTATIONAL MATERIALS SCIENCE, 2023, 229
  • [5] HOOMD-blue: A Python']Python package for high-performance molecular dynamics and hard particle Monte Carlo simulations
    Anderson, Joshua A.
    Glaser, Jens
    Glotzer, Sharon C.
    COMPUTATIONAL MATERIALS SCIENCE, 2020, 173 (173)
  • [6] Teaching Monte Carlo Simulation with Python']Python
    Holman, Justin O.
    Hacherl, Allie
    JOURNAL OF STATISTICS AND DATA SCIENCE EDUCATION, 2023, 31 (01): : 33 - 44
  • [7] SOURSOP: A Python']Python Package for the Analysis of Simulations of Intrinsically Disordered Proteins
    Lalmansingh, Jared M.
    Keeley, Alex T.
    Ruff, Kiersten M.
    Pappu, Rohit V.
    Holehouse, Alex S.
    JOURNAL OF CHEMICAL THEORY AND COMPUTATION, 2023, 19 (16) : 5609 - 5620
  • [8] pyerrors: A python']python framework for error analysis of Monte Carlo data
    Joswig, Fabian
    Kuberski, Simon
    Kuhlmann, Justus T.
    Neuendorf, Jan
    COMPUTER PHYSICS COMMUNICATIONS, 2023, 288
  • [9] MontePython']Python: Implementing quantum Monte Carlo using python']python
    Nilsen, Jon Kristian
    COMPUTER PHYSICS COMMUNICATIONS, 2007, 177 (10) : 799 - 814
  • [10] ZOSPy, a python']python package for ray tracing simulations
    van Vught, Luc
    Haasjes, Corne
    Beenakker, Jan-Willem
    ACTA OPHTHALMOLOGICA, 2024, 102