lexical_diversity_example.py

#Copyright <YEAR> <COPYRIGHT HOLDER>
#
#Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
#
#The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
#
#THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

from lexical_diversity import mtld, hdd

academic_sample = 'In sum, all textual analyses are fraught with difficulty and disagreement, and LD is no exception. There is no agreement in the field as to the form of processing (sequential or nonsequential) or the composition of lexical terms (e.g., words, lemmas, bigrams, etc.); and even a common position with regard to the distinction between the terms lexical diversity, vocabulary diversity, and lexical richness remains unclear (Malvern et al., 2004). In this study, we do not attempt to remedy these issues. Instead, we argue that the field is sufficiently young to be still in need of exploring its potential to inform substantially. Thus, we include in our analyses the most sophisticated indices of LD that are currently available.'

print('Sample MTLD:', mtld(academic_sample.split()))
print('Sample HD-D:', hdd(academic_sample.split()))