v0.5.1

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: v0.4.1...v0.5.1

v0.5.0

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: v0.4.1...v0.5.0

v0.4.1

What's Changed

• Update README.rst by @ekbrown in #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 #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: v0.3.0...v0.4.0

v0.4.0

What's Changed

• Add utility to plot empirical voc-D curve (#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: v0.3.0...v0.4.0

v0.3.1

What's Changed

• Add workflow to test package from notebook by @LSYS in #54
• Add details of measures into docs by @LSYS in #55
• Fix path to images in docs by @LSYS in #56

Full Changelog: v0.3.0...v0.3.1

LexicalRichness v0.3.0

What's Changed

• Disallow string input if tokenizer =None (closes #12) by @LSYS in #38
• fix tokenizing of lists by @LSYS in #39
• add .gitignore and make by @LSYS in #41
• Linkify references and add papers in readme #43 solved by @Sreetama2001 in #46
• Added an example use case of the LexicalRichness tool by @g-hurst in #48
• Add voc-D measure (#42) by @LSYS in #49
• Update docs by @LSYS in #51

New Contributors

• @Sreetama2001 made their first contribution in #46
• @g-hurst made their first contribution in #48

Full Changelog: v0.2.0...v0.3.0

bump to v0.2.0

Fix inputs with strings and lists.

Fix-#12

Fix gotcha where str input is still allowed when tokenizer=None (#38).

Fixes #26

Fixes packaging error (#26 )

bumping to v0.1.7

bumping