remove very old deprecation warning from ticket 4492

src/sage/matrix/special.py

@@ -818,14 +818,14 @@ def diagonal_matrix(arg0=None, arg1=None, arg2=None, sparse=True):
     except TypeError:
         raise TypeError('unable to determine number of entries for diagonal matrix construction')
     # sometimes catches a negative size
-    if not nrows is None and nentries > nrows:
+    if nrows is not None and nentries > nrows:
         raise ValueError('number of diagonal matrix entries (%s) exceeds the requested matrix size (%s)' % (nentries, nrows))
     if nrows is None:
         nrows = nentries
 
     # provide a default ring for an empty list
-    if not len(entries) and ring is None:
-       ring = ZZ
+    if not entries and ring is None:
+        ring = ZZ
 
     # Convert entries to a list v over a common ring
     from sage.modules.free_module_element import prepare
@@ -880,6 +880,7 @@ def identity_matrix(ring, n=0, sparse=False):
         ring = ZZ
     return matrix_space.MatrixSpace(ring, n, n, sparse)(1)
 
+
 @matrix_method
 def lehmer(ring, n=0):
     r"""
@@ -906,6 +907,7 @@ def lehmer(ring, n=0):
         ring = QQ
     return matrix_space.MatrixSpace(ring, n, n).matrix([[min(i, j)/max(i, j) for i in IntegerRange(1, n+1)] for j in IntegerRange(1, n+1)])
 
+
 @matrix_method
 def zero_matrix(ring, nrows=None, ncols=None, sparse=False):
     r"""
@@ -949,6 +951,7 @@ def zero_matrix(ring, nrows=None, ncols=None, sparse=False):
         ring = ZZ
     return matrix_space.MatrixSpace(ring, nrows, ncols, sparse)(0)
 
+
 @matrix_method
 def ones_matrix(ring, nrows=None, ncols=None, sparse=False):
     r"""
@@ -1351,7 +1354,7 @@ def elementary_matrix(arg0, arg1=None, **kwds):
     """
     import sage.structure.element
     # determine ring and matrix size
-    if not arg1 is None and not is_Ring(arg0):
+    if arg1 is not None and not is_Ring(arg0):
         raise TypeError('optional first parameter must be a ring, not {0}'.format(arg0))
     scale = kwds.pop('scale', None)
     if is_Ring(arg0):
@@ -1377,9 +1380,9 @@ def elementary_matrix(arg0, arg1=None, **kwds):
     col1 = kwds.pop('col1', None)
     if row1 is None and col1 is None:
         raise ValueError('row1 or col1 must be specified')
-    if not row1 is None and not col1 is None:
+    if row1 is not None and col1 is not None:
         raise ValueError('cannot specify both row1 and col1')
-    rowop = not row1 is None
+    rowop = row1 is not None
     if rowop:
         opstring = "row"
         row2 = kwds.pop('row2', None)
@@ -1397,16 +1400,16 @@ def elementary_matrix(arg0, arg1=None, **kwds):
         row1 = Integer(row1)
     except TypeError:
         raise TypeError('{0} of elementary matrix must be an integer, not {1}'.format(opstring, row1))
-    if row1 < 0 or row1 >= n :
+    if row1 < 0 or row1 >= n:
         raise ValueError('{0} of elementary matrix must be positive and smaller than {1}, not {2}'.format(opstring, n, row1))
-    if not row2 is None:
+    if row2 is not None:
         try:
             row2 = Integer(row2)
         except TypeError:
             raise TypeError('{0} of elementary matrix must be an integer, not {1}'.format(opstring, row2))
-        if row2 < 0 or row2 >= n :
+        if row2 < 0 or row2 >= n:
             raise ValueError('{0} of elementary matrix must be positive and smaller than {1}, not {2}'.format(opstring, n, row2))
-    if not scale is None:
+    if scale is not None:
         try:
             scale = R(scale)
         except Exception:
@@ -1417,16 +1420,16 @@ def elementary_matrix(arg0, arg1=None, **kwds):
     elem = identity_matrix(R, n, sparse=sparse)
     if row2 is None and scale is None:
         raise ValueError('insufficient parameters provided to construct elementary matrix')
-    elif not row2 is None and not scale is None:
+    elif row2 is not None and scale is not None:
         if row1 == row2:
             raise ValueError('cannot add a multiple of a {0} to itself'.format(opstring))
         elem[row1, row2] = scale
-    elif not row2 is None and scale is None:
+    elif row2 is not None and scale is None:
         elem[row1, row1] = 0
         elem[row2, row2] = 0
         elem[row1, row2] = 1
         elem[row2, row1] = 1
-    elif row2 is None and not scale is None:
+    elif row2 is None and scale is not None:
         if scale == 0:
             raise ValueError('scale parameter of {0} of elementary matrix must be non-zero'.format(opstring))
         elem[row1, row1] = scale
@@ -1435,6 +1438,7 @@ def elementary_matrix(arg0, arg1=None, **kwds):
     else:
         return elem.transpose()
 
+
 @matrix_method
 def circulant(v, sparse=None):
     r"""
@@ -1563,6 +1567,7 @@ def _determine_block_matrix_grid(sub_matrices):
 
     return (row_heights, col_widths)
 
+
 def _determine_block_matrix_rows(sub_matrices):
     """
     For internal use. This tests if the matrices in sub_matrices
@@ -1578,7 +1583,7 @@ def _determine_block_matrix_rows(sub_matrices):
     Non-zero scalars are considered to be square matrices of any size,
     and zeroes are considered to be zero matrices of any size.
 
-    A ValueError is raised if there is insufficient or
+    A ``ValueError`` is raised if there is insufficient or
     conflicting information.
 
     TESTS::
@@ -1593,9 +1598,8 @@ def _determine_block_matrix_rows(sub_matrices):
         ([2, 2], [0, 0], 4)
     """
     total_width = None
-
-    row_heights = [ None ] * len(sub_matrices)
-    zero_widths = [ 0 ] * len(sub_matrices)
+    row_heights = [None] * len(sub_matrices)
+    zero_widths = [0] * len(sub_matrices)
 
     # We first do a pass to see if we can determine the width
     unknowns = False
@@ -1667,7 +1671,7 @@ def _determine_block_matrix_rows(sub_matrices):
                     elif zero_state == 2:
                         zero_state = 3
                 else:
-                     scalars += 1
+                    scalars += 1
 
             remaining_width = total_width - width
             # This remaining width has to be split over the
@@ -1844,32 +1848,14 @@ def block_matrix(*args, **kwds):
         ...
         ValueError: insufficient information to determine submatrix widths
 
-    Historically, giving only a flat list of submatrices, whose number
-    was a perfect square, would create a new matrix by laying out the submatrices
-    in a square grid.  This behavior is now deprecated.  ::
+    Giving only a flat list of submatrices does not work::
 
         sage: A = matrix(2, 3, range(6))
         sage: B = matrix(3, 3, range(9))
         sage: block_matrix([A, A, B, B])
-        doctest:...: DeprecationWarning: invocation of block_matrix with just a list whose length is a perfect square is deprecated. See the documentation for details.
-        [0 1 2|0 1 2]
-        [3 4 5|3 4 5]
-        [-----+-----]
-        [0 1 2|0 1 2]
-        [3 4 5|3 4 5]
-        [6 7 8|6 7 8]
-
-    Historically, a flat list of matrices whose number is not a perfect square,
-    with no specification of the number of rows or columns, would raise an error.
-    This behavior continues, but could be removed when the deprecation above is
-    completed.  ::
-
-        sage: A = matrix(2, 3, range(6))
-        sage: B = matrix(3, 3, range(9))
-        sage: block_matrix([A, A, A, B, B, B])
         Traceback (most recent call last):
         ...
-        ValueError: must specify nrows or ncols for non-square block matrix.
+        ValueError: must specify either nrows or ncols
 
     TESTS::
 
@@ -1971,24 +1957,19 @@ def block_matrix(*args, **kwds):
     else:
         # A flat list
         # determine the block dimensions
-        n = ZZ(len(sub_matrices))
+        n = len(sub_matrices)
         if nrows is None:
             if ncols is None:
-                if n.is_square():
-                    import warnings
-                    warnings.warn("invocation of block_matrix with just a list whose length is a perfect square is deprecated. See the documentation for details.", DeprecationWarning, stacklevel=2)
-                    nrows = ncols = n.sqrt()
-                else:
-                    # this form (ie just a flat list) could be allowed once deprecated invocation (above) goes away
-                    raise ValueError("must specify nrows or ncols for non-square block matrix.")
+                raise ValueError("must specify either nrows or ncols")
             else:
-                nrows = int(n/ncols)
+                nrows = n // ncols
         elif ncols is None:
-            ncols = int(n/nrows)
+            ncols = n // nrows
         if nrows * ncols != n:
             raise ValueError("given number of rows (%s), columns (%s) incompatible with number of submatrices (%s)" % (nrows, ncols, n))
         # Now create a list of lists from this
-        sub_matrices = [ sub_matrices[i*ncols : (i+1)*ncols] for i in range(nrows) ]
+        sub_matrices = [sub_matrices[i * ncols: (i + 1) * ncols]
+                        for i in range(nrows)]
 
     # At this point sub_matrices is a list of lists
 
@@ -2021,7 +2002,6 @@ def block_matrix(*args, **kwds):
             if subdivide:
                 raise ValueError(e)
 
-
     if col_widths is None:
         # Try placing the matrices in rows instead
         # (Only if subdivide is False)
@@ -2696,21 +2676,20 @@ def random_echelonizable_matrix(parent, rank, upper_bound=None, max_tries=100):
                 matrix.add_multiple_of_row(0, randint(1,rows-1), randint(-3,3))
         else:
             if rank == 1:  # would be better just to have a special generator...
-               tries = 0
-               while max(map(abs,matrix.list())) >= upper_bound:
-                  matrix = random_rref_matrix(parent, rank)
-                  tries += 1
-                  if tries > max_tries: # to prevent endless attempts
-                     raise ValueError("tried "+str(max_tries)+" times to get a rank 1 random matrix. Try bigger upper_bound?")
-               matrix_copy = matrix
-
-            rrr = range(len(matrix.pivots())-1,-1,-1)
-            for pivots in rrr:
+                tries = 0
+                while max(abs(c) for c in matrix.list()) >= upper_bound:
+                    matrix = random_rref_matrix(parent, rank)
+                    tries += 1
+                    if tries > max_tries: # to prevent endless attempts
+                        raise ValueError("tried "+str(max_tries)+" times to get a rank 1 random matrix. Try bigger upper_bound?")
+                matrix_copy = matrix
+
+            for pivots in range(len(matrix.pivots()) - 1, -1, -1):
             # keep track of the pivot column positions from the pivot column with the largest index to
             # the one with the smallest.
-                row_index=0
+                row_index = 0
                 tries = 0
-                while row_index<rows:
+                while row_index < rows:
                     # To each row in a pivot column add a scalar multiple of the pivot row.
                     # for full rank, square matrices, using only this row operation preserves the determinant of 1.
                     if pivots!=row_index:
@@ -2750,6 +2729,7 @@ def random_echelonizable_matrix(parent, rank, upper_bound=None, max_tries=100):
             matrix.add_multiple_of_row(0,randint(1,rows-1),ring.random_element())
     return matrix
 
+
 @matrix_method
 def random_subspaces_matrix(parent, rank=None):
     r"""
@@ -2937,7 +2917,8 @@ def random_subspaces_matrix(parent, rank=None):
     # By multiplying the B matrix by J.inverse() we hide the B matrix of the
     # solution using row operations required to change the solution K matrix to
     # the identity matrix.
-    return J.inverse()*B
+    return J.inverse() * B
+
 
 @matrix_method
 def random_unimodular_matrix(parent, upper_bound=None, max_tries=100):
@@ -3664,6 +3645,7 @@ def hankel(c, r=None, ring=None):
     m = len(c)
     r = [0] * (m - 1) if r is None else list(r)
     n = len(r)
+
     def entries(i):
         return c[i] if i < m else r[i - m]
     return matrix(lambda i, j: entries(i + j), nrows=m, ncols=n + 1, ring=ring)