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src/n/i/nipy-0.3.0/nipy/labs/spatial_models/tests/test_bsa.py   nipy(Download)
from nipy.testing import dec
 
from ...utils.simul_multisubject_fmri_dataset import surrogate_2d_dataset
from ..bayesian_structural_analysis import compute_BSA_simple
from ..discrete_domain import domain_from_binary_array
    # make a dataset with a nothing feature
    null_ampli = np.array([0, 0, 0])
    null_betas = surrogate_2d_dataset(n_subj=n_subj,
                                        shape=shape,
                                        pos=pos,
    # make a dataset with a something feature
    pos_ampli = np.array([5, 7, 6])
    pos_betas = surrogate_2d_dataset(n_subj=n_subj,
                                       shape=shape,
                                       pos=pos,

src/n/i/nipy-0.3.0/nipy/labs/spatial_models/tests/test_parcel.py   nipy(Download)
from nipy.algorithms.graph.field import field_from_coo_matrix_and_data
from ..hierarchical_parcellation import hparcel
from ...utils.simul_multisubject_fmri_dataset import surrogate_2d_dataset
from ..parcellation import MultiSubjectParcellation
from ..discrete_domain import grid_domain_from_binary_array
    n_subj = 10
    shape = (30, 30)
    dataset = surrogate_2d_dataset(n_subj=n_subj, shape=shape)
 
    # step 2 : prepare all the information for the parcellation
    n_subj = 10
    shape = (30, 30)
    dataset = surrogate_2d_dataset(n_subj=n_subj, shape=shape)
 
    # step 2 : prepare all the information for the parcellation

src/p/y/pypreprocess-HEAD/pypreprocess/external/nipy_labs/tests/test_statistical_mapping.py   pypreprocess(Download)
 
from nibabel import Nifti1Image
from ..utils.simul_multisubject_fmri_dataset import \
    surrogate_2d_dataset
from ..statistical_mapping import cluster_stats

src/n/i/nipy-0.3.0/nipy/labs/tests/test_statistical_mapping.py   nipy(Download)
 
from nibabel import Nifti1Image
from ..utils.simul_multisubject_fmri_dataset import \
    surrogate_2d_dataset
from ..statistical_mapping import cluster_stats