Document new Span.to_array() method
@@ -145,6 +145,35 @@ p
+cell float
+cell A scalar similarity score. Higher is more similar.
++h(2, "to_array") Span.to_array
+ +tag method
+ +tag-new(2)
+
+p
+ | Given a list of #[code M] attribute IDs, export the tokens to a numpy
+ | #[code ndarray] of shape #[code (N, M)], where #[code N] is the length of
+ | the document. The values will be 32-bit integers.
+
++aside-code("Example").
+ from spacy.attrs import LOWER, POS, ENT_TYPE, IS_ALPHA
+ doc = nlp(u'I like New York in Autumn.')
+ span = doc[2:3]
+ # All strings mapped to integers, for easy export to numpy
+ np_array = span.to_array([LOWER, POS, ENT_TYPE, IS_ALPHA])
+
++table(["Name", "Type", "Description"])
+ +row
+ +cell #[code attr_ids]
+ +cell list
+ +cell A list of attribute ID ints.
+
+ +footrow
+ +cell returns
+ +cell #[code.u-break numpy.ndarray[long, ndim=2]]
+ +cell
+ | A feature matrix, with one row per word, and one column per
+ | attribute indicated in the input #[code attr_ids].
+
+h(2, "merge") Span.merge
+tag method
