Commit ⋅ snorkel-team/snorkel

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snorkel/analysis/error_analysis.py changed.

@@ -61,7 +61,7 @@

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def get_label_instances(
    bucket: Tuple[int, ...], x: np.ndarray, *y: np.ndarray
) -> np.ndarray:
    """Return instances in x with the specified combination of labels
    """Return instances in x with the specified combination of labels.

    Parameters
    ----------

@@ -89,13 +89,13 @@

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    >>> Y_gold = np.array([1, 1, 1])
    >>> Y_pred = np.array([1, 0, 0])
    >>> bucket = (1, 0)
    
    The returned NumPy array of data instances from ``x`` will correspond to 
    the rows where the first list had a 1 and the second list had a 0. 

    The returned NumPy array of data instances from ``x`` will correspond to
    the rows where the first list had a 1 and the second list had a 0.
    >>> get_label_instances(bucket, x.to_numpy(), Y_gold, Y_pred)
    array([['a second string', '2'],
           ['a third string', '3']], dtype=object)
    

    More generally, given bucket ``(i, j, ...)`` and lists ``y1, y2, ...``
    the returned data instances from ``x`` will correspond to the rows where
    y1 had label i, y2 had label j, and so on. Note that ``x`` and ``y``

Files		•	•	•	Coverage
snorkel	2,151	2,091	29	31	97.21%
Project Totals (68 files)	2,151	2,091	29	31	97.21%

TRAVIS_PYTHON_VERSION=3.7
TRAVIS_OS_NAME=linux
TOXENV=coverage,doctest,type,check

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coverage:
  status:
    project:
      default:
        target: 95%
    patch:
      default:
        threshold: 2%

comment:
  layout: "header, diff, flags, files"

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61	61		def get_label_instances(
62	62		bucket: Tuple[int, ...], x: np.ndarray, *y: np.ndarray
63	63		) -> np.ndarray:
64		-	"""Return instances in x with the specified combination of labels
	64	+	"""Return instances in x with the specified combination of labels.
65	65
66	66		Parameters
67	67		----------

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89	89		>>> Y_gold = np.array([1, 1, 1])
90	90		>>> Y_pred = np.array([1, 0, 0])
91	91		>>> bucket = (1, 0)
92		-
93		-	The returned NumPy array of data instances from ``x`` will correspond to
94		-	the rows where the first list had a 1 and the second list had a 0.
	92	+
	93	+	The returned NumPy array of data instances from ``x`` will correspond to
	94	+	the rows where the first list had a 1 and the second list had a 0.
95	95		>>> get_label_instances(bucket, x.to_numpy(), Y_gold, Y_pred)
96	96		array([['a second string', '2'],
97	97		['a third string', '3']], dtype=object)
98		-
	98	+
99	99		More generally, given bucket ``(i, j, ...)`` and lists ``y1, y2, ...``
100	100		the returned data instances from ``x`` will correspond to the rows where
101	101		y1 had label i, y2 had label j, and so on. Note that ``x`` and ``y``

1	coverage:
2	status:
3	project:
4	default:
5	target: 95%
6	patch:
7	default:
8	threshold: 2%
9
10	comment:
11	layout: "header, diff, flags, files"