def test__subset_and_standardize(self, expression_data_no_na,
standardize, feature_ids,
sample_ids):
from flotilla.data_model.base import BaseData
base_data = BaseData(expression_data_no_na)
base_data.subset, base_data.means = \
base_data._subset_and_standardize(base_data.data,
sample_ids=sample_ids,
feature_ids=feature_ids,
return_means=True,
standardize=standardize)
subset = base_data._subset(base_data.data, sample_ids=sample_ids,
feature_ids=feature_ids)
means = subset.mean().rename_axis(base_data.feature_renamer)
subset = subset.fillna(means).fillna(0)
subset = subset.rename_axis(base_data.feature_renamer, 1)
if standardize:
data = StandardScaler().fit_transform(subset)
else:
data = subset
subset_standardized = pd.DataFrame(data, index=subset.index,
columns=subset.columns)
pdt.assert_frame_equal(subset_standardized, base_data.subset)
pdt.assert_series_equal(means, base_data.means)
def test__subset_and_standardize(self, expression_data_no_na, standardize,
feature_ids, sample_ids):
from flotilla.data_model.base import BaseData
base_data = BaseData(expression_data_no_na)
base_data.subset, base_data.means = \
base_data._subset_and_standardize(base_data.data,
sample_ids=sample_ids,
feature_ids=feature_ids,
return_means=True,
standardize=standardize)
subset = base_data._subset(base_data.data,
sample_ids=sample_ids,
feature_ids=feature_ids)
means = subset.mean().rename_axis(base_data.feature_renamer)
subset = subset.fillna(means).fillna(0)
subset = subset.rename_axis(base_data.feature_renamer, 1)
if standardize:
data = StandardScaler().fit_transform(subset)
else:
data = subset
subset_standardized = pd.DataFrame(data,
index=subset.index,
columns=subset.columns)
pdt.assert_frame_equal(subset_standardized, base_data.subset)
pdt.assert_series_equal(means, base_data.means)
def test_reduce(self, shalek2013_data, featurewise):
# TODO: parameterize and test with featurewise and subsets
from flotilla.compute.decomposition import DataFramePCA
from flotilla.data_model.base import BaseData
expression = BaseData(shalek2013_data.expression)
test_reduced = expression.reduce(featurewise=featurewise)
subset, means = expression._subset_and_standardize(
expression.data, return_means=True, standardize=True)
if featurewise:
subset = subset.T
true_reduced = DataFramePCA(subset)
true_reduced.means = means
pdt.assert_frame_equal(test_reduced.X, subset)
npt.assert_array_equal(test_reduced.reduced_space,
true_reduced.reduced_space)
pdt.assert_series_equal(test_reduced.means,
true_reduced.means)
def test_reduce(self, expression_data_no_na, featurewise):
# TODO: parameterize and test with featurewise and subsets
from flotilla.compute.decomposition import DataFramePCA
from flotilla.data_model.base import BaseData
expression = BaseData(expression_data_no_na)
test_reduced = expression.reduce(featurewise=featurewise)
subset, means = expression._subset_and_standardize(expression.data,
return_means=True,
standardize=True)
if featurewise:
subset = subset.T
true_reduced = DataFramePCA(subset)
true_reduced.means = means
pdt.assert_frame_equal(test_reduced.X, subset)
npt.assert_array_equal(test_reduced.reduced_space,
true_reduced.reduced_space)
pdt.assert_series_equal(test_reduced.means, true_reduced.means)
