emoji-math computes the given python expression and returns either the value or the nearest 5 emojis as measured by cosine similarity.

Overview

Emoji Math

Open In Colab

Because why not? I put a minimal effort into this project, so please have low expectations.

pip install [email protected]+git://github.com/whitead/emoji-math.git

Usage

emoji-math computes the given python expression and returns either the value or the nearest 5 emojis as measured by cosine similarity.

>emoji-math ๐Ÿ‘‘ - ๐Ÿšน + ๐Ÿšบ
Best Matches:
  ๐Ÿ‘‘-๐Ÿšน+๐Ÿšบ = ๐Ÿ‘ธ
  ๐Ÿ‘‘-๐Ÿšน+๐Ÿšบ = ๐Ÿ‘‘
  ๐Ÿ‘‘-๐Ÿšน+๐Ÿšบ = ๐Ÿคด
>emoji-math ๐Ÿšน @ ๐Ÿšบ
๐Ÿšน @ ๐Ÿšบ = 0.32784234338655205
>emoji-math np.sin(๐Ÿฐ)
Best Matches:
  np.sin(๐Ÿฐ) = ๐Ÿฏ
  np.sin(๐Ÿฐ) = ๐Ÿฐ
  np.sin(๐Ÿฐ) = ๐Ÿ‘ธ
>emoji-math ๐Ÿšน + ๐Ÿšบ
Best Matches:
  ๐Ÿšน+๐Ÿšบ = ๐Ÿšป
  ๐Ÿšน+๐Ÿšบ = ๐Ÿšบ
  ๐Ÿšน+๐Ÿšบ = ๐Ÿšน

Options

You can choose between using the Euclidean distance or cosine similarity for reporting results. Cosine works better for multiplication/division because it only cares about direction. Default is Euclidean.

>emoji-math --cosine ๐Ÿšน + ๐Ÿšบ
Best Matches:
  ๐Ÿšน+๐Ÿšบ = ๐Ÿ‘š
  ๐Ÿšน+๐Ÿšบ = ๐Ÿšบ
  ๐Ÿšน+๐Ÿšบ = ๐Ÿšน

Google Colab

Start using emoji math with Open In Colab

Credit

Made by @andrewwhite01

Vector embeddings from emoji2vec as described in

@misc{eisner2016emoji2vec,
      title={emoji2vec: Learning Emoji Representations from their Description},
      author={Ben Eisner and Tim Rocktรคschel and Isabelle Augenstein and Matko Boลกnjak and Sebastian Riedel},
      year={2016},
      eprint={1609.08359},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}
Owner
Andrew White
Andrew White
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