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[FIX] Preprocess: enums containing function names changed #2151

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Merged
lanzagar merged 2 commits into from
Mar 31, 2017
Merged

[FIX] Preprocess: enums containing function names changed #2151

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e9b99c9
[FIX] Preprocess: enums containing function names changed
jerneju Mar 29, 2017
4fb1caa
preprocess.py: lint
jerneju Mar 29, 2017
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20 changes: 10 additions & 10 deletions Orange/preprocess/preprocess.py
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Original file line number Diff line number Diff line change
Expand Up @@ -33,12 +33,12 @@ def __call__(self, data):


class Continuize(Preprocess):
(Indicators, FirstAsBase, FrequentAsBase,Remove, RemoveMultinomial,
(Indicators, FirstAsBase, FrequentAsBase, Remove, RemoveMultinomial,
ReportError, AsOrdinal, AsNormalizedOrdinal, Leave) = Enum(
"Continuize",
"Indicators, FirstAsBase, FrequentAsBase,"
"Remove, RemoveMultinomial, ReportError, AsOrdinal,"
"AsNormalizedOrdinal, Leave")
"Continuize",
"Indicators, FirstAsBase, FrequentAsBase,"
"Remove, RemoveMultinomial, ReportError, AsOrdinal,"
"AsNormalizedOrdinal, Leave")

def __init__(self, zero_based=True,
multinomial_treatment=Indicators):
Expand Down Expand Up @@ -288,9 +288,9 @@ def __call__(self, data):
for a in data.domain.attributes if a.is_continuous):
# Skip normalization for data sets where all features are marked as already normalized.
# Required for SVMs (with normalizer as their default preprocessor) on sparse data to
# retain sparse structure. Normalizing sparse data would otherwise result in a dense matrix,
# which requires too much memory. For example, this is used for Bag of Words models where
# normalization is not really needed.
# retain sparse structure. Normalizing sparse data would otherwise result in a dense
# matrix, which requires too much memory. For example, this is used for Bag of Words
# models where normalization is not really needed.
return data
normalizer = normalize.Normalizer(
zero_based=self.zero_based,
Expand Down Expand Up @@ -403,8 +403,8 @@ class _MethodEnum(Enum):
def __call__(self, *args, **kwargs):
return getattr(Scale, '_' + self.name)(*args, **kwargs)

CenteringType = _MethodEnum('Scale', 'NoCentering, Mean, Median', type=int)
ScalingType = _MethodEnum('Scale', 'NoScaling, Std, Span', type=int)
CenteringType = _MethodEnum('Scale', 'NoCentering, Mean, Median')
ScalingType = _MethodEnum('Scale', 'NoScaling, Std, Span')
NoCentering, Mean, Median = CenteringType
NoScaling, Std, Span = ScalingType

Expand Down