本文整理汇总了Python中neurosynth.base.dataset.Dataset.get_feature_data方法的典型用法代码示例。如果您正苦于以下问题：Python Dataset.get_feature_data方法的具体用法？Python Dataset.get_feature_data怎么用？Python Dataset.get_feature_data使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类neurosynth.base.dataset.Dataset的用法示例。
在下文中一共展示了Dataset.get_feature_data方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: Masker
# 需要导入模块: from neurosynth.base.dataset import Dataset [as 别名]
# 或者: from neurosynth.base.dataset.Dataset import get_feature_data [as 别名]
base_path = '/home/pauli/Development/neurobabel/'
test_data_path = base_path + 'ACE/'
masker_filename = base_path + 'atlases/whs_sd/WHS_SD_rat_one_sm_v2.nii.gz'
atlas_filename = base_path + 'atlases/whs_sd/WHS_SD_rat_atlas_brain_sm_v2.nii.gz'
mask = nib.load(masker_filename)
masker = Masker(mask)
r = 1.0
transform = {'BREGMA': transformations.bregma_to_whs()}
target = 'WHS'
# load data set
dataset = Dataset(os.path.join(test_data_path, 'db_bregma_cog_atlas_export.txt'), masker=masker_filename, r=r, transform=transform, target=target)
dataset.feature_table = FeatureTable(dataset)
dataset.add_features(os.path.join(test_data_path, "db_bregma_cog_atlas_features.txt")) # add features
fn = dataset.get_feature_names()
features = dataset.get_feature_data()
n_xyz, n_articles = dataset.image_table.data.shape
# do topic modeling (LSA)
n_components = 20
svd = TruncatedSVD(n_components=n_components)
X = svd.fit_transform(features)
X_orig = X.copy()
X = StandardScaler().fit_transform(X_orig)
# db = DBSCAN(eps=10.0, min_samples=10).fit(X)
# core_samples_mask = np.zeros_like(db.labels_, dtype=bool)
# core_samples_mask[db.core_sample_indices_] = True
# labels = db.labels_