Metadata-Version: 2.1
Name: python-TAMER
Version: 0.2.14
Summary: Toolkit for Analysis and Maps of Exposure Risk
Home-page: https://github.com/tch521/python-TAMER
Author: Todd C. Harris
Author-email: todd.harris@meteoswiss.ch
License: BSD-3-Clause license
Description: ============================
        Introduction to python-TAMER
        ============================
        
        The Toolkit for Analysis and Maps of Exposure Risk (TAMER) is designed to calculate estimates of individual and
        population exposure across a geographic area. Currently, the project is focused on erythemal UV radiation 
        exposure, but the tools provided by TAMER could be used in a variety of contexts provided there is appropriate
        source data. In addition to providing a simple methods for basic exposure calculations, (such as mean, median,
        and maximum intensities over certain time periods,) TAMER allows users to calculate daily doses by integrating
        the exposure over time. 
        
        In the context of UV, the dose received by an exposed individual is far more relevant to their corresponding 
        health risk than the ambient level of UV. Usually, these doses are measured by wearable devices. Harris et al.
        2021 (https://doi.org/10.3390/atmos12020268) explains the various benefits of instead estimating such doses
        based on satellite-derived data with sufficiently high spatial and temporal resolution. The Swiss UV 
        climatology provided by Vuilleumier et al. 2020 (https://doi.org/10.1016/j.envint.2020.106177) is Currently
        the most appropriate source data for TAMER as it provides erythemal UV at an approximately 1.5km spatial
        resolution and an hourly temporal resolution. Harris et al. 2021 shows that with location, date, and time
        information, reasonable ambient doses can be calculated. However, to calculate personal doses, the Exposure
        Ratio (ER) must also be known, that being the ratio between the ambient dose and the personal dose received
        by a certain body part. Different body parts have varying ERs which also depend on body posture, for example
        the ER of the forehead is lower when bowing down than when standing normally. TAMER includes a model from
        Vernez et al. 2015 (https://doi.org/10.1038/jes.2014.6) to calculate ERs according to anatomic zone, posture,
        and time of year. python-tamer.SpecificDoses is a table-like class designed to take location, date, time, 
        posture, and anatomic zone information to calculate specific ambient and personal doses of the described
        individuals. 
        
        A large part of TAMER is dedicated to producing high quality maps of a variety of exposure metrics. 
        
        
        * Free software: BSD-3-Clause license
        
        
        Features
        --------
        
        * Calculate doses rapidly with custom exposure schedules
        * Analyse exposure distributions per pixel and calculate a variety of metrics to describe exposure
        * Produce maps to represent chronic and acute exposure 
        * Replicate dosimetry measurements using Exposure Ratio modelling
        
        
        =======
        History
        =======
        
        0.2 Alpha (2021-03-11)
        -----------------------
        
        * Added documentation
        * Added basic unit tests for each class (SpecificDoses and ExposureMap)
        * Added histogram descriptor calculator functions to subroutines.
        * Added map making functionality for ExposureMap class, limited consideration of map_options at this stage
        * Fixed errors when working with single day test data (but anticipate further issues with this, to be fixed in a later release)
        
        
        0.1 (2021-03-02)
        ------------------
        
        * Alpha release on github only, no documentation and limited functionality
        
Keywords: python-TAMER UV
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3
Provides-Extra: test
