Merge pull request #598 from pfebrer/sparse_fixes

maint: Adapt to breaking changes in scipy.sparse.isspmatrix

src/sisl/io/tbtrans/tbt.py

@@ -16,7 +16,7 @@
 ndarray = np.ndarray
 
 # The sparse matrix for the orbital/bond currents
-from scipy.sparse import SparseEfficiencyWarning, csr_matrix, isspmatrix_csr
+from scipy.sparse import SparseEfficiencyWarning, csr_matrix, issparse
 
 import sisl._array as _a
 from sisl import Atoms, Geometry, constant
@@ -1158,7 +1158,7 @@ def map_col(c):
             map_col = o2a
 
         # Lets do array notation for speeding up the computations
-        if not isspmatrix_csr(Dij):
+        if not (issparse(Dij) and Dij.format == 'csr'):
             Dij = Dij.tocsr()
 
         # Check for the simple case of 1-orbital systems

src/sisl/physics/electron.py

@@ -65,7 +65,7 @@
     sort,
     zeros,
 )
-from scipy.sparse import csr_matrix, hstack, identity, isspmatrix
+from scipy.sparse import csr_matrix, hstack, identity, issparse
 
 import sisl._array as _a
 from sisl import Geometry, Grid, Lattice, constant, units
@@ -374,7 +374,7 @@ def tosize(diag, idx):
 
         cop = oplist(tosize(d, idx) for d in cop)
 
-    elif isspmatrix(M):
+    elif issparse(M):
 
         # create the new list
         cop0 = M.multiply(0.).real

src/sisl/physics/sparse.py

@@ -10,7 +10,7 @@
 import sisl.linalg as lin
 from sisl._internal import set_module
 from sisl.messages import warn
-from sisl.sparse import isspmatrix
+from sisl.sparse import issparse
 from sisl.sparse_geometry import SparseOrbital
 
 from ._matrix_ddk import matrix_ddk, matrix_ddk_nc, matrix_ddk_nc_diag, matrix_ddk_so
@@ -148,7 +148,7 @@ def fromsp(cls, geometry, P, S=None, **kwargs):
              a new sparse matrix that holds the passed geometry and the elements of `P` and optionally being non-orthogonal if `S` is not none
         """
         # Ensure list of csr format (to get dimensions)
-        if isspmatrix(P):
+        if issparse(P):
             P = [P]
         if isinstance(P, tuple):
             P = list(P)

src/sisl/physics/tests/test_hamiltonian.py

@@ -7,7 +7,7 @@
 import numpy as np
 import pytest
 from scipy.linalg import block_diag
-from scipy.sparse import SparseEfficiencyWarning, isspmatrix
+from scipy.sparse import SparseEfficiencyWarning, issparse
 
 from sisl import (
     Atom,
@@ -1240,7 +1240,7 @@ def test_coop_sp_vs_np(self, setup):
         for k in ([0] *3, [0.2] * 3):
             es = HS.eigenstate(k)
             COOP_sp = es.COOP(E, 'lorentzian')
-            assert isspmatrix(COOP_sp[0])
+            assert issparse(COOP_sp[0])
 
             es = HS.eigenstate(k, format='array')
             COOP_np = es.COOP(E, 'lorentzian')

src/sisl/sparse.py

@@ -45,6 +45,7 @@
     isspmatrix_csc,
     isspmatrix_csr,
     isspmatrix_lil,
+    issparse,
     spmatrix,
 )
 
@@ -139,7 +140,7 @@ def __init__(self, arg1, dim=1, dtype=None, nnzpr=20, nnz=None,
         # for the insert row is increased at least by this number
         self._ns = 10
 
-        if isspmatrix(arg1):
+        if issparse(arg1):
             # This is a sparse matrix
             # The data-type is infered from the
             # input sparse matrix.
@@ -1387,8 +1388,8 @@ def copy(self, dims=None, dtype=None):
         # The default sizes are not passed
         # Hence we *must* copy the arrays
         # directly
-        copyto(new.ptr, self.ptr, casting='no')
-        copyto(new.ncol, self.ncol, casting='no')
+        copyto(new.ptr, self.ptr, casting='same_kind')
+        copyto(new.ncol, self.ncol, casting='same_kind')
         new.col = self.col.copy()
         new._nnz = self.nnz
 
@@ -2050,7 +2051,7 @@ def ispmatrix(matrix, map_row=None, map_col=None):
     #it = np.nditer([geom.o2a(tmp.row), geom.o2a(tmp.col % geom.no), tmp.data],
     #               flags=['buffered'], op_flags=['readonly'])
 
-    if isspmatrix_csr(matrix):
+    if issparse(matrix) and matrix.format == "csr":
         for r in range(matrix.shape[0]):
             rr = map_row(r)
             if rows[rr]: continue
@@ -2062,7 +2063,7 @@ def ispmatrix(matrix, map_row=None, map_col=None):
                 cols[c] = True
                 yield rr, c
 
-    elif isspmatrix_lil(matrix):
+    elif issparse(matrix) and matrix.format == "lil":
         for r in range(matrix.shape[0]):
             rr = map_row(r)
             if rows[rr]: continue
@@ -2075,10 +2076,10 @@ def ispmatrix(matrix, map_row=None, map_col=None):
                 cols[c] = True
                 yield rr, c
 
-    elif isspmatrix_coo(matrix):
+    elif issparse(matrix) and matrix.format == "coo":
         raise ValueError("mapping and unique returns are not implemented for COO matrix")
 
-    elif isspmatrix_csc(matrix):
+    elif issparse(matrix) and matrix.format == "csc":
         raise ValueError("mapping and unique returns are not implemented for CSC matrix")
 
     elif isinstance(matrix, SparseCSR):
@@ -2113,20 +2114,20 @@ def _ispmatrix_all(matrix):
     int, int
        the row, column indices of the non-zero elements
     """
-    if isspmatrix_csr(matrix):
+    if issparse(matrix) and matrix.format == "csr":
         for r in range(matrix.shape[0]):
             for ind in range(matrix.indptr[r], matrix.indptr[r+1]):
                 yield r, matrix.indices[ind]
 
-    elif isspmatrix_lil(matrix):
+    elif issparse(matrix) and matrix.format == "lil":
         for r in range(matrix.shape[0]):
             for c in matrix.rows[r]:
                 yield r, c
 
-    elif isspmatrix_coo(matrix):
+    elif issparse(matrix) and matrix.format == "coo":
         yield from zip(matrix.row, matrix.col)
 
-    elif isspmatrix_csc(matrix):
+    elif issparse(matrix) and matrix.format == "csc":
         for c in range(matrix.shape[1]):
             for ind in range(matrix.indptr[c], matrix.indptr[c+1]):
                 yield matrix.indices[ind], c
@@ -2171,22 +2172,22 @@ def ispmatrixd(matrix, map_row=None, map_col=None):
     #it = np.nditer([geom.o2a(tmp.row), geom.o2a(tmp.col % geom.no), tmp.data],
     #               flags=['buffered'], op_flags=['readonly'])
 
-    if isspmatrix_csr(matrix):
+    if issparse(matrix) and matrix.format == "csr":
         for r in range(matrix.shape[0]):
             rr = map_row(r)
             for ind in range(matrix.indptr[r], matrix.indptr[r+1]):
                 yield rr, map_col(matrix.indices[ind]), matrix.data[ind]
 
-    elif isspmatrix_lil(matrix):
+    elif issparse(matrix) and matrix.format == "lil":
         for r in range(matrix.shape[0]):
             rr = map_row(r)
             for c, m in zip(map_col(matrix.rows[r]), matrix.data[r]):
                 yield rr, c, m
 
-    elif isspmatrix_coo(matrix):
+    elif issparse(matrix) and matrix.format == "coo":
         yield from zip(map_row(matrix.row), map_col(matrix.col), matrix.data)
 
-    elif isspmatrix_csc(matrix):
+    elif issparse(matrix) and matrix.format == "csc":
         for c in range(matrix.shape[1]):
             cc = map_col(c)
             for ind in range(matrix.indptr[c], matrix.indptr[c+1]):

src/sisl/sparse_geometry.py

@@ -39,7 +39,7 @@
 from .geometry import Geometry
 from .messages import SislError, SislWarning, progressbar, warn
 from .orbital import Orbital
-from .sparse import SparseCSR, _ncol_to_indptr, isspmatrix
+from .sparse import SparseCSR, _ncol_to_indptr, issparse
 from .utils.ranges import list2str
 
 __all__ = ['SparseAtom', 'SparseOrbital']
@@ -1078,7 +1078,7 @@ def fromsp(cls, geometry, P, **kwargs):
              a new sparse matrix that holds the passed geometry and the elements of `P`
         """
         # Ensure list of * format (to get dimensions)
-        if isspmatrix(P):
+        if issparse(P):
             P = [P]
         if isinstance(P, tuple):
             P = list(P)

src/sisl/tests/test_sparse.py

@@ -1357,10 +1357,10 @@ def test_sparse_column_out_of_bounds(j):
     with pytest.raises(IndexError):
         S[0, j] = 1
 
-
 def test_fromsp_csr():
     csr1 = sc.sparse.random(10, 100, 0.01, random_state=24812)
     csr2 = sc.sparse.random(10, 100, 0.02, random_state=24813)
+
     csr = SparseCSR.fromsp(csr1, csr2)
     csr_1 = csr.tocsr(0)
     csr_2 = csr.tocsr(1)

src/sisl_toolbox/btd/_btd.py

@@ -918,7 +918,7 @@ def _matrix_to_btd(self, M):
         BI = BM.block_indexer
         c = self.btd_cum0
         nb = len(BI)
-        if ssp.isspmatrix(M):
+        if ssp.issparse(M):
             for jb in range(nb):
                 for ib in range(max(0, jb-1), min(jb+2, nb)):
                     BI[ib, jb] = M[c[ib]:c[ib+1], c[jb]:c[jb+1]].toarray()