mirror of https://github.com/explosion/spaCy.git
142 lines
4.6 KiB
Python
142 lines
4.6 KiB
Python
# coding: utf-8
|
|
from __future__ import unicode_literals
|
|
|
|
from numpy.testing import assert_almost_equal, assert_array_almost_equal
|
|
import pytest
|
|
from pytest import approx
|
|
from spacy.gold import GoldParse
|
|
from spacy.scorer import Scorer, ROCAUCScore
|
|
from spacy.scorer import _roc_auc_score, _roc_curve
|
|
from .util import get_doc
|
|
|
|
test_ner_cardinal = [
|
|
["100 - 200", {"entities": [[0, 3, "CARDINAL"], [6, 9, "CARDINAL"]]}]
|
|
]
|
|
|
|
test_ner_apple = [
|
|
[
|
|
"Apple is looking at buying U.K. startup for $1 billion",
|
|
{"entities": [(0, 5, "ORG"), (27, 31, "GPE"), (44, 54, "MONEY")]},
|
|
]
|
|
]
|
|
|
|
|
|
def test_ner_per_type(en_vocab):
|
|
# Gold and Doc are identical
|
|
scorer = Scorer()
|
|
for input_, annot in test_ner_cardinal:
|
|
doc = get_doc(
|
|
en_vocab,
|
|
words=input_.split(" "),
|
|
ents=[[0, 1, "CARDINAL"], [2, 3, "CARDINAL"]],
|
|
)
|
|
gold = GoldParse(doc, entities=annot["entities"])
|
|
scorer.score(doc, gold)
|
|
results = scorer.scores
|
|
|
|
assert results["ents_p"] == 100
|
|
assert results["ents_f"] == 100
|
|
assert results["ents_r"] == 100
|
|
assert results["ents_per_type"]["CARDINAL"]["p"] == 100
|
|
assert results["ents_per_type"]["CARDINAL"]["f"] == 100
|
|
assert results["ents_per_type"]["CARDINAL"]["r"] == 100
|
|
|
|
# Doc has one missing and one extra entity
|
|
# Entity type MONEY is not present in Doc
|
|
scorer = Scorer()
|
|
for input_, annot in test_ner_apple:
|
|
doc = get_doc(
|
|
en_vocab,
|
|
words=input_.split(" "),
|
|
ents=[[0, 1, "ORG"], [5, 6, "GPE"], [6, 7, "ORG"]],
|
|
)
|
|
gold = GoldParse(doc, entities=annot["entities"])
|
|
scorer.score(doc, gold)
|
|
results = scorer.scores
|
|
|
|
assert results["ents_p"] == approx(66.66666)
|
|
assert results["ents_r"] == approx(66.66666)
|
|
assert results["ents_f"] == approx(66.66666)
|
|
assert "GPE" in results["ents_per_type"]
|
|
assert "MONEY" in results["ents_per_type"]
|
|
assert "ORG" in results["ents_per_type"]
|
|
assert results["ents_per_type"]["GPE"]["p"] == 100
|
|
assert results["ents_per_type"]["GPE"]["r"] == 100
|
|
assert results["ents_per_type"]["GPE"]["f"] == 100
|
|
assert results["ents_per_type"]["MONEY"]["p"] == 0
|
|
assert results["ents_per_type"]["MONEY"]["r"] == 0
|
|
assert results["ents_per_type"]["MONEY"]["f"] == 0
|
|
assert results["ents_per_type"]["ORG"]["p"] == 50
|
|
assert results["ents_per_type"]["ORG"]["r"] == 100
|
|
assert results["ents_per_type"]["ORG"]["f"] == approx(66.66666)
|
|
|
|
|
|
def test_roc_auc_score():
|
|
# Binary classification, toy tests from scikit-learn test suite
|
|
y_true = [0, 1]
|
|
y_score = [0, 1]
|
|
tpr, fpr, _ = _roc_curve(y_true, y_score)
|
|
roc_auc = _roc_auc_score(y_true, y_score)
|
|
assert_array_almost_equal(tpr, [0, 0, 1])
|
|
assert_array_almost_equal(fpr, [0, 1, 1])
|
|
assert_almost_equal(roc_auc, 1.0)
|
|
|
|
y_true = [0, 1]
|
|
y_score = [1, 0]
|
|
tpr, fpr, _ = _roc_curve(y_true, y_score)
|
|
roc_auc = _roc_auc_score(y_true, y_score)
|
|
assert_array_almost_equal(tpr, [0, 1, 1])
|
|
assert_array_almost_equal(fpr, [0, 0, 1])
|
|
assert_almost_equal(roc_auc, 0.0)
|
|
|
|
y_true = [1, 0]
|
|
y_score = [1, 1]
|
|
tpr, fpr, _ = _roc_curve(y_true, y_score)
|
|
roc_auc = _roc_auc_score(y_true, y_score)
|
|
assert_array_almost_equal(tpr, [0, 1])
|
|
assert_array_almost_equal(fpr, [0, 1])
|
|
assert_almost_equal(roc_auc, 0.5)
|
|
|
|
y_true = [1, 0]
|
|
y_score = [1, 0]
|
|
tpr, fpr, _ = _roc_curve(y_true, y_score)
|
|
roc_auc = _roc_auc_score(y_true, y_score)
|
|
assert_array_almost_equal(tpr, [0, 0, 1])
|
|
assert_array_almost_equal(fpr, [0, 1, 1])
|
|
assert_almost_equal(roc_auc, 1.0)
|
|
|
|
y_true = [1, 0]
|
|
y_score = [0.5, 0.5]
|
|
tpr, fpr, _ = _roc_curve(y_true, y_score)
|
|
roc_auc = _roc_auc_score(y_true, y_score)
|
|
assert_array_almost_equal(tpr, [0, 1])
|
|
assert_array_almost_equal(fpr, [0, 1])
|
|
assert_almost_equal(roc_auc, 0.5)
|
|
|
|
# same result as above with ROCAUCScore wrapper
|
|
score = ROCAUCScore()
|
|
score.score_set(0.5, 1)
|
|
score.score_set(0.5, 0)
|
|
assert_almost_equal(score.score, 0.5)
|
|
|
|
# check that errors are raised in undefined cases and score is -inf
|
|
y_true = [0, 0]
|
|
y_score = [0.25, 0.75]
|
|
with pytest.raises(ValueError):
|
|
_roc_auc_score(y_true, y_score)
|
|
|
|
score = ROCAUCScore()
|
|
score.score_set(0.25, 0)
|
|
score.score_set(0.75, 0)
|
|
assert score.score == -float("inf")
|
|
|
|
y_true = [1, 1]
|
|
y_score = [0.25, 0.75]
|
|
with pytest.raises(ValueError):
|
|
_roc_auc_score(y_true, y_score)
|
|
|
|
score = ROCAUCScore()
|
|
score.score_set(0.25, 1)
|
|
score.score_set(0.75, 1)
|
|
assert score.score == -float("inf")
|