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src/n/i/nipy-0.3.0/examples/labs/group_reproducibility_analysis.py   nipy(Download)
    voxel_reproducibility, cluster_reproducibility, map_reproducibility,
    peak_reproducibility)
from nipy.labs.spatial_models.discrete_domain import (
    grid_domain_from_binary_array)
 
func = np.reshape(betas, (n_subj, n_vox)).T
var = np.ones((n_vox, n_subj))
domain = grid_domain_from_binary_array(np.ones((shape[0], shape[1], 1)))
 
###############################################################################

src/n/i/nipy-0.3.0/nipy/labs/utils/reproducibility_measures.py   nipy(Download)
 
import numpy as np
from nipy.labs.spatial_models.discrete_domain import \
    grid_domain_from_binary_array
 
    affine = load(mask_images[0]).get_affine()
    mask = intersect_masks(mask_images, threshold=0) > 0
    domain = grid_domain_from_binary_array(mask, affine)
 
    # read the data

src/p/y/pypreprocess-HEAD/pypreprocess/external/nipy_labs/utils/reproducibility_measures.py   pypreprocess(Download)
 
import numpy as np
from nipy.labs.spatial_models.discrete_domain import \
    grid_domain_from_binary_array
 
    affine = load(mask_images[0]).get_affine()
    mask = intersect_masks(mask_images, threshold=0) > 0
    domain = grid_domain_from_binary_array(mask, affine)
 
    # read the data

src/p/y/pypreprocess-HEAD/pypreprocess/external/nipy_labs/utils/tests/test_repro.py   pypreprocess(Download)
def apply_repro_analysis(dataset, thresholds=[3.0], method = 'crfx'):
    """
    perform the reproducibility  analysis according to the 
    """
    from nipy.labs.spatial_models.discrete_domain import \
    func = np.reshape(dataset,(n_subj, dimx * dimy)).T
    var = np.ones((dimx * dimy, n_subj))
    domain = grid_domain_from_binary_array(np.ones((dimx, dimy, 1)))
 
    ngroups = 5

src/n/i/nipy-0.3.0/nipy/labs/utils/tests/test_repro.py   nipy(Download)
def apply_repro_analysis(dataset, thresholds=[3.0], method = 'crfx'):
    """
    perform the reproducibility  analysis according to the 
    """
    from nipy.labs.spatial_models.discrete_domain import \
    func = np.reshape(dataset,(n_subj, dimx * dimy)).T
    var = np.ones((dimx * dimy, n_subj))
    domain = grid_domain_from_binary_array(np.ones((dimx, dimy, 1)))
 
    ngroups = 5