# NCGOCR
[](https://travis-ci.org/jeroyang/ncgocr)
[](https://pypi.python.org/pypi/ncgocr)
- Named Concept Gene Ontology Concept Recognition
- Automatic recognize Gene Ontology (GO) concepts from context.
## Installation
Using 'pip' to install the Python module
```bash
$ pip install -U ncgocr
```
## Usage
```python
from ncgocr import Craft, GoData, NCGOCR, Corpus, evaluate
craft = Craft('data')
corpus = craft.get_corpus()
goldstandard = craft.get_goldstandard()
print('Loading GO...')
godata = GoData('data/craft-1.0/ontologies/GO.obo')
print('Initiating NCGOCR...')
ncgocr = NCGOCR(godata)
print('Training the model...')
ncgocr.train(corpus, goldstandard)
print('Loading the testing corpus...')
corpus_name = 'testing corpus'
testing_corpus = Corpus.from_dir('data/craft-1.0/articles/txt/', corpus_name)
print('predicting the results...')
result = ncgocr.process(testing_corpus)
print('Show the first 10 results...')
print(result.to_list()[:10])
print('Evaluate the results...')
report = evaluate(result, goldstandard, 'Using the training corpus as the testing corpus')
print(report)
```
## License
* Free software: MIT license
[](https://travis-ci.org/jeroyang/ncgocr)
[](https://pypi.python.org/pypi/ncgocr)
- Named Concept Gene Ontology Concept Recognition
- Automatic recognize Gene Ontology (GO) concepts from context.
## Installation
Using 'pip' to install the Python module
```bash
$ pip install -U ncgocr
```
## Usage
```python
from ncgocr import Craft, GoData, NCGOCR, Corpus, evaluate
craft = Craft('data')
corpus = craft.get_corpus()
goldstandard = craft.get_goldstandard()
print('Loading GO...')
godata = GoData('data/craft-1.0/ontologies/GO.obo')
print('Initiating NCGOCR...')
ncgocr = NCGOCR(godata)
print('Training the model...')
ncgocr.train(corpus, goldstandard)
print('Loading the testing corpus...')
corpus_name = 'testing corpus'
testing_corpus = Corpus.from_dir('data/craft-1.0/articles/txt/', corpus_name)
print('predicting the results...')
result = ncgocr.process(testing_corpus)
print('Show the first 10 results...')
print(result.to_list()[:10])
print('Evaluate the results...')
report = evaluate(result, goldstandard, 'Using the training corpus as the testing corpus')
print(report)
```
## License
* Free software: MIT license
Metadata
Release files for ncgocr 1.0.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| ncgocr-1.0.2.tar.gz | 3.7 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| ncgocr-1.0.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 3.8 MB
Release files / ncgocr-1.0.2.tar.gz
| Download URL | ncgocr-1.0.2.tar.gz |
|---|---|
| Size | 3.7 MB |
| Tags | Source |
|
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Release files / ncgocr-1.0.2-py3-none-any.whl
| Download URL | ncgocr-1.0.2-py3-none-any.whl |
|---|---|
| Size | 78.8 kB |
| Tags | Python 3 |
|
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