histwords | building diachronic/historical word vectors
kandi X-RAY | histwords Summary
kandi X-RAY | histwords Summary
histwords is a Python library. histwords has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.
An eclectic collection of tools for analyzing historical language change using vector space semantics.
An eclectic collection of tools for analyzing historical language change using vector space semantics.
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Quality
Security
License
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Support
histwords has a low active ecosystem.
It has 369 star(s) with 88 fork(s). There are 22 watchers for this library.
It had no major release in the last 6 months.
There are 7 open issues and 6 have been closed. On average issues are closed in 3 days. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of histwords is current.
Quality
histwords has 0 bugs and 0 code smells.
Security
histwords has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
histwords code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.
License
histwords is licensed under the Apache-2.0 License. This license is Permissive.
Permissive licenses have the least restrictions, and you can use them in most projects.
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histwords releases are not available. You will need to build from source code and install.
Build file is available. You can build the component from source.
It has 3686 lines of code, 228 functions and 80 files.
It has high code complexity. Code complexity directly impacts maintainability of the code.
Top functions reviewed by kandi - BETA
kandi has reviewed histwords and discovered the below as its top functions. This is intended to give you an instant insight into histwords implemented functionality, and help decide if they suit your requirements.
- Create an embedding object
- Load vocabulary
- Load a sparse matrix
- Load word vocabulary from file
- Read counts matrix
- Load count vocabulary
- Load a dictionary of year index dictionaries
- Return a dict of the year index for each year
- Compute the deviation of a year
- Makes a matplotlib matrix
- Calculate mean stderr for a time series
- Compute the orthogonal matrix of two embeds
- Alcrustes two embeddings
- Compute similarity between two vectors
- Calculate the median of a words time series
- Returns the indices of the closest contexts in the graph
- Compute the mean standard deviation of a words time series
- Return the indices of the closest node
- Load year index
- Compute the probability density matrix
- Load the target words from a word file
- Calculate the pmi matrix
- Process a single lemma line
- Calculate the mean deviation of a series
- Read vectors from file
- Return a SequentialEmbedding
Get all kandi verified functions for this library.
histwords Key Features
No Key Features are available at this moment for histwords.
histwords Examples and Code Snippets
No Code Snippets are available at this moment for histwords.
Community Discussions
No Community Discussions are available at this moment for histwords.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install histwords
You can download it from GitHub.
You can use histwords like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
You can use histwords like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
Support
For any new features, suggestions and bugs create an issue on GitHub.
If you have any questions check and ask questions on community page Stack Overflow .
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