generate_q

This function generates a matrix of Dynamic Error values (q) for the DLO simulation.

Implements sentiment analysis using huggingface <https://huggingface.co> transformer zero-shot classification model pipelines for text and image data. The default text pipeline is Cross-Encoder's DistilRoBERTa <https://huggingface.co/cross-encoder/nli-distilroberta-base> and default image/video pipeline is Open AI's CLIP <https://huggingface.co/openai/clip-vit-base-patch32>. All other zero-shot classification model pipelines can be implemented using their model name from <https://huggingface.co/models?pipeline_tag=zero-shot-classification>.

Aleksandar Tomašević

transforEmotion

Sentiment Analysis for Text, Image and Video using Transformer
Models

Alexander Christensen

Hudson Golino

generate_q function

<dl><dt>num_steps</dt>
<dd>Numeric integer.
The number of time steps used in the simulation.</dd>
<dt>sigma_q</dt>
<dd>Numeric. 
Standard deviation of the Dynamic Error/</dd></dl>

Arguments

Generate a matrix of Dynamic Error values for the DLO simulation — generate_q

<dl>

<dt>num_steps</dt>
<dd>Numeric integer.
The number of time steps used in the simulation.</dd>


<dt>sigma_q</dt>
<dd>Numeric. 
Standard deviation of the Dynamic Error/</dd>

</dl>

generate_q: Generate a matrix of Dynamic Error values for the DLO simulation

Description

Usage

Value

Arguments