Merge pull request #34 from Katterrina/issue29

[FIX] issue #29

enigmatoolbox/datasets/base.py

@@ -38,8 +38,8 @@ def load_mask(name='midline', surface_name="fsa5", join=False):
  name = ''
  else:
  name = '_' + name
- mask_lh = np.loadtxt(ipth.format('lh', name), dtype=np.bool)
- mask_rh = np.loadtxt(ipth.format('rh', name), dtype=np.bool)
+ mask_lh = np.loadtxt(ipth.format('lh', name), dtype=bool)
+ mask_rh = np.loadtxt(ipth.format('rh', name), dtype=bool)
  if join:
  return np.concatenate([mask_lh, mask_rh])
 
@@ -49,8 +49,8 @@ def load_mask(name='midline', surface_name="fsa5", join=False):
  name = ''
  else:
  print('sorry there\'s no other option for now')
- mask_lh = np.loadtxt(ipth.format('lh', name), dtype=np.bool)
- mask_rh = np.loadtxt(ipth.format('rh', name), dtype=np.bool)
+ mask_lh = np.loadtxt(ipth.format('lh', name), dtype=bool)
+ mask_rh = np.loadtxt(ipth.format('rh', name), dtype=bool)
  if join:
  return np.concatenate([mask_lh, mask_rh])
 
@@ -262,10 +262,10 @@ def load_sc(parcellation='aparc'):
  sctxL = 'strucLabels_sctx_' + parcellation + '.csv'
  sctxL_ipth = os.path.join(root_pth, 'matrices', 'hcp_connectivity', sctxL)
 
- return np.loadtxt(ctx_ipth, dtype=np.float, delimiter=','), \
- np.loadtxt(ctxL_ipth, dtype='str', delimiter=','), \
- np.loadtxt(sctx_ipth, dtype=np.float, delimiter=','), \
- np.loadtxt(sctxL_ipth, dtype='str', delimiter=',')
+ return np.loadtxt(ctx_ipth, dtype=float, delimiter=','), \
+ np.loadtxt(ctxL_ipth, dtype=str, delimiter=','), \
+ np.loadtxt(sctx_ipth, dtype=float, delimiter=','), \
+ np.loadtxt(sctxL_ipth, dtype=str, delimiter=',')
 
 
 def load_fc(parcellation='aparc'):
@@ -316,10 +316,10 @@ def load_fc(parcellation='aparc'):
  sctxL = 'funcLabels_sctx_' + parcellation + '.csv'
  sctxL_ipth = os.path.join(root_pth, 'matrices', 'hcp_connectivity', sctxL)
 
- return np.loadtxt(ctx_ipth, dtype=np.float, delimiter=','), \
- np.loadtxt(ctxL_ipth, dtype='str', delimiter=','), \
- np.loadtxt(sctx_ipth, dtype=np.float, delimiter=','), \
- np.loadtxt(sctxL_ipth, dtype='str', delimiter=',')
+ return np.loadtxt(ctx_ipth, dtype=float, delimiter=','), \
+ np.loadtxt(ctxL_ipth, dtype=str, delimiter=','), \
+ np.loadtxt(sctx_ipth, dtype=float, delimiter=','), \
+ np.loadtxt(sctxL_ipth, dtype=str, delimiter=',')
 
 
 def load_sc_as_one(parcellation='aparc'):
@@ -353,8 +353,8 @@ def load_sc_as_one(parcellation='aparc'):
  ctxL = 'strucLabels_with_sctx_' + parcellation + '.csv'
  ctxL_ipth = os.path.join(root_pth, 'matrices', 'hcp_connectivity', ctxL)
 
- return np.loadtxt(ctx_ipth, dtype=np.float, delimiter=','), \
- np.loadtxt(ctxL_ipth, dtype='str', delimiter=','), \
+ return np.loadtxt(ctx_ipth, dtype=float, delimiter=','), \
+ np.loadtxt(ctxL_ipth, dtype=str, delimiter=','), \
 
 
 def load_fc_as_one(parcellation='aparc'):
@@ -389,8 +389,8 @@ def load_fc_as_one(parcellation='aparc'):
  ctxL = 'funcLabels_with_sctx_' + parcellation + '.csv'
  ctxL_ipth = os.path.join(root_pth, 'matrices', 'hcp_connectivity', ctxL)
 
- return np.loadtxt(ctx_ipth, dtype=np.float, delimiter=','), \
- np.loadtxt(ctxL_ipth, dtype='str', delimiter=','), \
+ return np.loadtxt(ctx_ipth, dtype=float, delimiter=','), \
+ np.loadtxt(ctxL_ipth, dtype=str, delimiter=','), \
 
 
 def structural_covariance(zdata):

enigmatoolbox/histology/base.py

@@ -48,10 +48,10 @@ def economo_koskinas_spider(parcel_data=None, parcellation='aparc_fsa5', fill=0,
  # Average within ve classes
  if 'fsa5' in parcellation:
  parc_pth = os.path.dirname(os.path.dirname(__file__)) + '/datasets/parcellations/economo_koskinas_fsa5.csv'
- ve = np.loadtxt(parc_pth, dtype=np.int)
+ ve = np.loadtxt(parc_pth, dtype=int)
  elif 'conte69' in parcellation:
  parc_pth = os.path.dirname(os.path.dirname(__file__)) + '/datasets/parcellations/economo_koskinas_conte69.csv'
- ve = np.loadtxt(parc_pth, dtype=np.int)
+ ve = np.loadtxt(parc_pth, dtype=int)
 
  ve_class = np.zeros((5, 1))
  for ii in range(5):

enigmatoolbox/mesh/array_operations.py

@@ -430,7 +430,7 @@ def compute_point_area(surf, cell_area=None, area_as='one_third'):
 #
 # adj = me.get_ring_adjacency(surf, n_ring=radius, include_self=False)
 # mask = labeling == dilate_label
-# am = adj[mask].max(axis=0).A[0].astype(np.bool)
+# am = adj[mask].max(axis=0).A[0].astype(bool)
 # am &= labeling == background
 # labeling[am] = dilate_label
 #
@@ -610,9 +610,9 @@ def propagate_labeling(surf, labeling, no_label=np.nan, mask=None, alpha=0.99,
  # Graph matrix
  if mode == 'connectivity':
  adj = me.get_ring_adjacency(surf, n_ring=n_ring, include_self=False,
- dtype=np.float)
+ dtype=np.float64)
  else:
- adj = me.get_ring_distance(surf, n_ring=n_ring, dtype=np.float)
+ adj = me.get_ring_distance(surf, n_ring=n_ring)
  adj.data[:] = np.exp(-adj.data/n_ring**2)
 
  if mask is not None:
@@ -729,7 +729,7 @@ def smooth_array(surf, point_data, n_iter=5, mask=None, kernel='gaussian',
 
  if kernel == 'uniform':
  w = me.get_immediate_adjacency(surf, include_self=False, mask=mask,
- dtype=np.float)
+ dtype=np.float64)
  elif kernel == 'gaussian':
  w = me.get_immediate_distance(surf, metric='sqeuclidean', mask=mask)
  if sigma is None:
@@ -754,7 +754,7 @@ def smooth_array(surf, point_data, n_iter=5, mask=None, kernel='gaussian',
  if np.issubdtype(pd.dtype, np.floating):
  spd = pd.copy()
  else:
- spd = pd.astype(np.float)
+ spd = pd.astype(np.float64)
 
  for _ in range(n_iter):
  wp = w.dot(spd)

enigmatoolbox/mesh/mesh_correspondence.py

@@ -25,7 +25,7 @@ def _find_correspondence(surf, ref_surf, eps=0, n_jobs=1, use_cell=False):
  tree = cKDTree(ref_points, leafsize=20, compact_nodes=False,
  copy_data=False, balanced_tree=False)
  d, idx = tree.query(points, k=1, eps=0, n_jobs=n_jobs,
- distance_upper_bound=eps+np.finfo(np.float).eps)
+ distance_upper_bound=eps+np.finfo(np.float64).eps)
 
  if np.isinf(d).any():
  raise ValueError('Cannot find correspondences. Try increasing '

enigmatoolbox/mesh/mesh_elements.py

@@ -200,7 +200,7 @@ def get_cell_neighbors(surf, include_self=True, with_edge=True,
  ce.eliminate_zeros()
 
  else:
- ce = get_cell2point_connectivity(surf, dtype=np.bool)
+ ce = get_cell2point_connectivity(surf, dtype=bool)
  ce *= ce.T
  if not include_self:
  ce.setdiag(0)
@@ -242,7 +242,7 @@ def get_immediate_adjacency(surf, include_self=True, mask=None,
  Immediate adjacency: set to one all entries of points that
  share and edge with current point.
  """
- adj = get_point2cell_connectivity(surf, mask=mask, dtype=np.bool)
+ adj = get_point2cell_connectivity(surf, mask=mask, dtype=bool)
  adj *= adj.T
  if not include_self:
  adj.setdiag(0)
@@ -287,7 +287,7 @@ def get_ring_adjacency(surf, n_ring=1, include_self=True, mask=None,
  mask=mask, dtype=dtype)
 
  adj = get_immediate_adjacency(surf, include_self=True, mask=mask,
- dtype=np.bool)
+ dtype=bool)
  adj **= n_ring
  if not include_self:
  adj.setdiag(0)
@@ -320,7 +320,7 @@ def get_edges(surf, mask=None):
 
  """
  adj = get_immediate_adjacency(surf, include_self=False, mask=mask,
- dtype=np.bool)
+ dtype=bool)
  adj.sort_indices()
  adj_ud = ssp.triu(adj, k=1, format='coo')
  edges = np.column_stack([adj_ud.row, adj_ud.col])
@@ -620,7 +620,7 @@ def get_boundary_cells(surf, with_edge=True):
 
 
 def get_immediate_distance(surf, metric='euclidean', mask=None,
- dtype=np.float):
+ dtype=float):
  """Get immediate distance matrix.
 
  Parameters
@@ -668,7 +668,7 @@ def get_immediate_distance(surf, metric='euclidean', mask=None,
 
 
 def get_ring_distance(surf, n_ring=1, metric='geodesic', mask=None,
- dtype=np.float):
+ dtype=float):
  """Get distance matrix in the neighborhood of each point.
 
  Parameters
@@ -683,7 +683,7 @@ def get_ring_distance(surf, n_ring=1, metric='geodesic', mask=None,
  Binary mask. If specified, only use points within the mask.
  Default is None.
  dtype : dtype, optional
- Data type. Default is np.float.
+ Data type. Default is float.
 
  Returns
  -------

enigmatoolbox/mesh/mesh_operations.py

@@ -488,7 +488,7 @@ def downsample_with_parcellation(surf, labeling, name='parcel',
  adj = get_immediate_adjacency(surf)
  adj_neigh = adj.multiply(labeling_con).tocsr()
 
- adj_small = np.zeros((nlabs, nlabs), dtype=np.bool)
+ adj_small = np.zeros((nlabs, nlabs), dtype=bool)
  for i in range(nlabs):
  arow = adj_neigh[labeling_con == i]
  for j in range(i + 1, nlabs):

enigmatoolbox/plotting/base.py

@@ -489,7 +489,7 @@ def AddRenderer(self, row, col, renderer=None, **kwargs):
 
  def AddRenderers(self, **kwargs):
  """Some description here."""
- ren = np.empty((self.nrow, self.ncol), dtype=np.object)
+ ren = np.empty((self.nrow, self.ncol), dtype=object)
  for i in range(self.nrow):
  for j in range(self.ncol):
  ren[i, j] = super().AddRenderer(row=i, col=j, **kwargs)

enigmatoolbox/utils/parcellation.py

@@ -210,7 +210,7 @@ def parcel_to_surface(source_val, target_lab, mask=None, fill=0, source_lab=None
  if isinstance(target_lab, str):
  fname = target_lab + '.csv'
  parc_pth = os.path.dirname(os.path.dirname(__file__)) + '/datasets/parcellations/' + fname
- target_lab = np.loadtxt(parc_pth, dtype=np.int)
+ target_lab = np.loadtxt(parc_pth, dtype=int)
 
  if source_val.size == 68 and np.unique(target_lab).size == 71:
  a_idx = list(range(1, 4)) + list(range(5, 39)) + list(range(40, 71))
@@ -267,7 +267,7 @@ def fred(x, w): return np.min(x, axis=axis)
 
 
 def surface_to_parcel(values, labels, weights=None, target_labels=None,
- red_op='mean', axis=0, dtype=np.float):
+ red_op='mean', axis=0, dtype=float):
  """Summarize data in `values` according to `labels` (author: @OualidBenkarim)
 
  Parameters
@@ -304,7 +304,7 @@ def surface_to_parcel(values, labels, weights=None, target_labels=None,
  if isinstance(labels, str):
  fname = labels + '.csv'
  parc_pth = os.path.dirname(os.path.dirname(__file__)) + '/datasets/parcellations/' + fname
- labels = np.loadtxt(parc_pth, dtype=np.int)
+ labels = np.loadtxt(parc_pth, dtype=int)
 
  if axis == 1 and values.ndim == 1:
  axis = 0

enigmatoolbox/vtk_interface/io_support/freesurfer_support.py

@@ -46,7 +46,7 @@ def _fread3_many(fobj, n):
  out : 1D array
  An array of 3 byte int
  """
- b1, b2, b3 = np.fromfile(fobj, ">u1", 3 * n).reshape(-1, 3).astype(np.int).T
+ b1, b2, b3 = np.fromfile(fobj, ">u1", 3 * n).reshape(-1, 3).astype(int).T
  return (b1 << 16) + (b2 << 8) + b3