Enable programmatic interaction with 'Notion' pages,
    databases, blocks, comments, and users through the 'Notion API'
    <https://developers.notion.com/>.  Provides both synchronous and
    asynchronous client interfaces for building workflows and automations
    that integrate with 'Notion' workspaces. Supports all 'Notion API'
    endpoints including content creation, data retrieval, and workspace
    management.

Provides functions to query databases and notes in 'Notion', using the official REST API. To learn more about the functionality of the 'Notion' API, see <https://developers.notion.com/>.

A comprehensive toolkit for analyzing and visualizing neural data 
    outputs, including Principal Component Analysis (PCA) trajectory plotting, 
    Multi-Electrode Array (MEA) heatmap generation, and variable importance 
    analysis. Provides publication-ready visualizations with flexible 
    customization options for neuroscience research applications.

Computes the probability density function, the cumulative density function, quantile function, random numbers and measures of inference for the following families exponentiated generalized gull alpha power family, exponentiated gull alpha powerfamily, gull alpha power family.

The raw dataset and model used in Lai et al. (2021) 
    Decoupled responses of native and exotic tree diversities to 
    distance from old-growth forest and soil phosphorous in 
    novel secondary forests. Applied Vegetation Science, 24, e12548.

In semi-structured interviews that use the 'framework' method, it
    is not always clear how refinements to interview questions affect the
    decision of when to stop interviews. The trend of 'novel' and 'duplicate'
    interview codes (novel codes are information that other interviewees have
    not previously mentioned) provides insight into the richness of qualitative
    information. This package provides tools to visualise when refinements occur
    and how that affects the trends of novel and duplicate codes. These
    visualisations, when used progressively as new interviews are finished, can
    help the researcher to decide on a stopping point for their interviews. For
    context, see Wong et al., (2023) <doi:10.1177/16094069231220773>.