LexicalRichness Versions Save

:smile_cat: :speech_balloon: A module to compute textual lexical richness (aka lexical diversity).

v0.5.1

9 months ago

What's Changed

Pass through within_sample parameter in vocd (fixes #80, @xhulianoThe1)
Fix CTTR equation (fixes #77)
Minor doc fixes
Fixed path to vocd image

`LexicalRichness`

To install: pip install lexicalrichness

Example usage

from lexicalrichness import LexicalRichness

# text example
text = """Measure of textual lexical diversity, computed as the mean length of sequential words in
                a text that maintains a minimum threshold TTR score.

                Iterates over words until TTR scores falls below a threshold, then increase factor
                counter by 1 and start over. McCarthy and Jarvis (2010, pg. 385) recommends a factor
                threshold in the range of [0.660, 0.750].
                (McCarthy 2005, McCarthy and Jarvis 2010)"""

lex = LexicalRichness(text)

lex.vocd_fig(
    ntokens=50,  # Maximum number for the token/word size in the random samplings
    within_sample=100,  # Number of samples
    seed=42,  # Seed for reproducibility
)

Full Changelog: https://github.com/LSYS/LexicalRichness/compare/v0.4.1...v0.5.1

v0.5.0

1 year ago

What's Changed

Add new measures #65
- Yule's K
- Yule's I
- Herdan's Vm
- Simpson's D
Add new measures to example notebook (example.ipynb) #70
Add new measures to docs #71
Add the example.ipynb to the docs #72
Tidy up imports using isort #69

`LexicalRichness`

To install: pip install lexicalrichness

Example usage

from lexicalrichness import LexicalRichness

# text example
text = """Measure of textual lexical diversity, computed as the mean length of sequential words in
                a text that maintains a minimum threshold TTR score.

                Iterates over words until TTR scores falls below a threshold, then increase factor
                counter by 1 and start over. McCarthy and Jarvis (2010, pg. 385) recommends a factor
                threshold in the range of [0.660, 0.750].
                (McCarthy 2005, McCarthy and Jarvis 2010)"""

lex = LexicalRichness(text)

lex.vocd_fig(
    ntokens=50,  # Maximum number for the token/word size in the random samplings
    within_sample=100,  # Number of samples
    seed=42,  # Seed for reproducibility
)

Full Changelog: https://github.com/LSYS/LexicalRichness/compare/v0.4.1...v0.5.0

v0.4.1

1 year ago

What's Changed

Update README.rst by @ekbrown in https://github.com/LSYS/LexicalRichness/pull/62
@LSYS Add useful links (#61)
@LSYS Add links to docs in Section 7 of README.rst to reference details in docs (#64)
@LSYS Remove LGTM (#66)
@LSYS Fix Sphinx autodoc on RTD (#67)

New Contributors

@ekbrown made their first contribution in https://github.com/LSYS/LexicalRichness/pull/62

`LexicalRichness`

To install: pip install lexicalrichness

Example usage

from lexicalrichness import LexicalRichness

# text example
text = """Measure of textual lexical diversity, computed as the mean length of sequential words in
                a text that maintains a minimum threshold TTR score.

                Iterates over words until TTR scores falls below a threshold, then increase factor
                counter by 1 and start over. McCarthy and Jarvis (2010, pg. 385) recommends a factor
                threshold in the range of [0.660, 0.750].
                (McCarthy 2005, McCarthy and Jarvis 2010)"""

lex = LexicalRichness(text)

lex.vocd_fig(
    ntokens=50,  # Maximum number for the token/word size in the random samplings
    within_sample=100,  # Number of samples
    seed=42,  # Seed for reproducibility
)

GitHub: https://github.com/LSYS/LexicalRichness Example notebook: https://nbviewer.org/github/LSYS/LexicalRichness/blob/master/docs/example.ipynb Docs: http://lexicalrichness.readthedocs.io/

Full Changelog: https://github.com/LSYS/LexicalRichness/compare/v0.3.0...v0.4.0

v0.4.0

1 year ago

What's Changed

Add utility to plot empirical voc-D curve (https://github.com/LSYS/LexicalRichness/issues/60)
matplotlib is now a requirement (from setup.py)
Update docs

To install: pip install lexicalrichness

Example usage

from lexicalrichness import LexicalRichness

# text example
text = """Measure of textual lexical diversity, computed as the mean length of sequential words in
                a text that maintains a minimum threshold TTR score.

                Iterates over words until TTR scores falls below a threshold, then increase factor
                counter by 1 and start over. McCarthy and Jarvis (2010, pg. 385) recommends a factor
                threshold in the range of [0.660, 0.750].
                (McCarthy 2005, McCarthy and Jarvis 2010)"""

lex = LexicalRichness(text)

lex.vocd_fig(
    ntokens=50,  # Maximum number for the token/word size in the random samplings
    within_sample=100,  # Number of samples
    seed=42,  # Seed for reproducibility
)

GitHub: https://github.com/LSYS/LexicalRichness Example notebook: https://nbviewer.org/github/LSYS/LexicalRichness/blob/master/docs/example.ipynb Docs: https://www.lucasshen.com/software/lexicalrichness/doc

Full Changelog: https://github.com/LSYS/LexicalRichness/compare/v0.3.0...v0.4.0