Fork-safe, raw access to the 'Amazon Web Services' ('AWS') 'SDK' via the 'boto3' 'Python' module, and convenient helper functions to query the 'Simple Storage Service' ('S3') and 'Key Management Service' ('KMS'), partial support for 'IAM', the 'Systems Manager Parameter Store' and 'Secrets Manager'.

Analysis workflow for finding geographic boundaries of ecological or landscape traits and comparing the placement of geographic boundaries of two traits. If data are trait values, trait data are transformed to boundary intensities based on approximate first derivatives across latitude and longitude. The package includes functions to create custom null models based on the input data. The boundary statistics are described in: Fortin, Drapeau, and Jacquez (1996) <doi:10.2307/3545584>.

Computes uniform bounds on the distance between
  the cumulative distribution function of a standardized sum
  of random variables and its first-order Edgeworth expansion,
  following the article Derumigny, Girard, Guyonvarch (2023)
  <doi:10.1007/s13171-023-00320-y>.

Implements unit root tests for bounded time series following
    Cavaliere and Xu (2014) <doi:10.1016/j.jeconom.2013.08.012>. Standard 
    unit root tests (ADF, Phillips-Perron) have non-standard limiting 
    distributions when the time series is bounded. This package provides 
    modified ADF and M-type tests (MZ-alpha, MZ-t, MSB) with p-values computed 
    via Monte Carlo simulation of bounded Brownian motion. Supports one-sided 
    (lower bound only) and two-sided bounds, with automatic lag selection 
    using the MAIC criterion of Ng and Perron (2001) 
    <doi:10.1111/1468-0262.00256>.

Generate ground truth cases for object localization algorithms. 
    Cycle through a list of images, select points around which to generate bounding 
    boxes and assign classifiers. Output the coordinates, and images annotated with 
    boxes and labels. For an example study that uses bounding boxes for image 
    localization and classification see Ibrahim, Badr, Abdallah, and Eissa (2012)
    "Bounding Box Object Localization Based on Image Superpixelization"
    <doi:10.1016/j.procs.2012.09.119>.