Methods for generating matrices from Paper objects and other data.
| dfr | Methods for generating Numpy data objects from JSTOR Data-for-Research datasets. | 
Methods for generating Numpy data objects from JSTOR Data-for-Research datasets.
| array(data[, normalize, verbose]) | Yields a Numpy array, along with feature-index and document-index mappings. | 
| matrix(data[, normalize, verbose]) | Yields a Numpy matrix, along with feature-index and document-index mappings. | 
Yields a Numpy array, along with feature-index and document-index mappings.
Usage
>>> import tethne.readers as rd
>>> import tethne.matrices as mt
>>> data = rd.dfr.ngrams("/Path/to/DfR/data")
>>> A, doc_index, feat_index = mt.dfr.array(data, normalize=True)
| Parameters : | data : dict 
 normalize : bool 
  | 
|---|---|
| Returns : | A : Numpy array 
 document_index : class:.Map 
 feature_index : Map 
  | 
Yields a Numpy matrix, along with feature-index and document-index mappings.
Usage
>>> import tethne.readers as rd
>>> import tethne.matrices as mt
>>> data = rd.dfr.ngrams("/Path/to/DfR/data")
>>> M, doc_index, feat_index = mt.dfr.matrix(data, normalize=True)
| Parameters : | data : dict 
 normalize : bool 
  | 
|---|---|
| Returns : | M : Numpy matrix 
 document_index : class:.Map 
 feature_index : Map 
  |