def sum(A, *dimtype):
restype = 'double'
dim = 1
if len(dimtype) == 2:
dim = dimtype[0]
dimtype = dimtype[1]
elif len(dimtype) == 1:
dimtype = dimtype[0]
if isinstance(dimtype, str):
if dimtype == 'native':
restype = A.dtype
else:
restype = dimtype
else:
dim = dimtype
# finally, our internal arrays are 0-based
dim -= 1
n = A.msize[dim]
stride = 1
for x in A.msize[:dim]:
stride *= x
nshp = list(A.msize)
nshp[dim] = 1
# the result is nshp-aped array, lin. index xrange(_prod(nshp))
res = []
all = [slice(0, n) for n in A.msize]
all[dim] = 0
if dim > 1 and dim == len(nshp) - 1: nshp.pop()
for res_i, el0 in _izip(xrange(_prod(nshp)), _ndilin(A.msize, *all)):
res.append(_sum(A._a[i]
for i in xrange(el0, el0 + n * stride, stride)))
return _marray(A.dtype, nshp, res)
def sum(A, *dimtype):
restype = 'double'
dim = 1
if len(dimtype) == 2:
dim = dimtype[0]
dimtype = dimtype[1]
elif len(dimtype) == 1:
dimtype = dimtype[0]
if isinstance(dimtype, str):
if dimtype == 'native':
restype = A.dtype
else:
restype = dimtype
else:
dim = dimtype
# finally, our internal arrays are 0-based
dim -= 1
n = A.msize[dim]
stride = 1
for x in A.msize[:dim]: stride *= x
nshp = list(A.msize)
nshp[dim] = 1
# the result is nshp-aped array, lin. index xrange(_prod(nshp))
res = []
all = [ slice(0,n) for n in A.msize ]
all[dim] = 0
if dim > 1 and dim == len(nshp)-1: nshp.pop()
for res_i, el0 in _izip(xrange(_prod(nshp)), _ndilin(A.msize, *all)):
res.append( _sum(A._a[i] for i in xrange(el0,el0+n*stride,stride)) )
return _marray(A.dtype, nshp, res)
def _ndilin1(shp, *i):
"""Generator of linear indices into an array of shape `shp`. Indices are
specified by slices of indices in `i`.
The input index is base 1 the linear indices returned are base 0.
This function produces indices, threfore the output type is 'int'."""
cp = [1]
for x in shp[:-1]:
cp += [cp[-1] * x]
i = list(i)
for j, x in enumerate(i):
if isinstance(x, _mslice) and x.hasnoend():
i[j] = x.evaluate_end(shp[j])
for x in _ndi1(*i):
yield int(_sum(x * (y - 1) for x, y in _izip(cp, x)))
def _ndilin1(shp, *i):
"""Generator of linear indices into an array of shape `shp`. Indices are
specified by slices of indices in `i`.
The input index is base 1 the linear indices returned are base 0.
This function produces indices, threfore the output type is 'int'."""
cp = [1]
for x in shp[:-1]:
cp += [cp[-1]*x]
i = list(i)
for j, x in enumerate(i):
if isinstance(x, _mslice) and x.hasnoend():
i[j] = x.evaluate_end(shp[j])
for x in _ndi1(*i):
yield int(_sum( x*(y-1) for x, y in _izip(cp, x) ))
def sum(A, *dimtype):
restype = 'double'
dim = 1
if len(dimtype) == 2:
dim = dimtype[0]
dimtype = dimtype[1]
elif len(dimtype) == 1:
dimtype = dimtype[0]
if isinstance(dimtype, str):
if dimtype == 'native':
restype = A.dtype
else:
restype = dimtype
else:
dim = dimtype
msize = A.msize
dim -= 1
if A.msize[dim] == 1:
return A.__copy__()
for_end = 1
for s in msize[:dim]:
for_end *= s
stride_big = 5
for s in msize[1:dim + 1]:
stride_big *= s
cp = 0
if dim > 0: cp = stride_big - stride_big / msize[dim]
else: cp = stride_big - 1
prod_msize = _prod(msize)
nshp = list(msize)
nshp[dim] = 1
o = zeros(nshp)
oi = 0
i = 0
while oi < _prod(nshp):
for k in xrange(for_end):
s = _sum(A._a[i:i + msize[dim] * for_end:for_end])
o._a[oi] = s
oi += 1
i += 1
i += cp
if len(nshp) > 2 and nshp[-1] == 1:
o.msize = o.msize[:-1]
# FIXME, conversion to 'native' or other type
return o
def sum(A, *dimtype):
restype = 'double'
dim = 1
if len(dimtype) == 2:
dim = dimtype[0]
dimtype = dimtype[1]
elif len(dimtype) == 1:
dimtype = dimtype[0]
if isinstance(dimtype, str):
if dimtype == 'native':
restype = A.dtype
else:
restype = dimtype
else:
dim = dimtype
msize = A.msize
dim -= 1
if A.msize[dim] == 1:
return A.__copy__()
for_end = 1
for s in msize[:dim]: for_end *= s
stride_big = 5
for s in msize[1:dim+1]: stride_big *= s
cp = 0
if dim > 0: cp = stride_big - stride_big/msize[dim]
else: cp = stride_big - 1
prod_msize = _prod(msize)
nshp = list(msize)
nshp[dim] = 1
o = zeros(nshp)
oi = 0
i = 0
while oi < _prod(nshp):
for k in xrange(for_end):
s = _sum(A._a[i:i+msize[dim]*for_end:for_end])
o._a[oi] = s
oi += 1
i += 1
i += cp
if len(nshp) > 2 and nshp[-1] == 1:
o.msize = o.msize[:-1]
# FIXME, conversion to 'native' or other type
return o
def _ndilin(shp, *i):
"""Generator of linear indices into an array of shape `shp`. Indices are
specified by slices of indices in `i`."""
cp = [1]
for x in shp[:-1]:
cp += [cp[-1] * x]
i = list(i)
for j, x in enumerate(i):
if isinstance(x, slice):
start, stop, step = x.start, x.stop, x.step
if x.start is None: start = 0
if x.stop == sys.maxint or x.stop is None: stop = shp[j]
if x.step is None: step = 1
i[j] = slice(start, stop, step)
res = []
for x in _ndi(*i):
res.append(int(_sum(x * y for x, y in _izip(cp, x))))
#yield int(_sum( x*y for x, y in _izip(cp, x) ))
return res
def _ndilin(shp, *i):
"""Generator of linear indices into an array of shape `shp`. Indices are
specified by slices of indices in `i`."""
cp = [1]
for x in shp[:-1]:
cp += [cp[-1]*x]
i = list(i)
for j, x in enumerate(i):
if isinstance(x, slice):
start, stop, step = x.start, x.stop, x.step
if x.start is None: start = 0
if x.stop == sys.maxint or x.stop is None: stop = shp[j]
if x.step is None: step = 1
i[j] = slice(start, stop, step)
res = []
for x in _ndi(*i):
res.append(int(_sum( x*y for x, y in _izip(cp, x) )))
#yield int(_sum( x*y for x, y in _izip(cp, x) ))
return res
def hasPathSum(self, root, sum):
"""
:type root: TreeNode
:type sum: int
:rtype: bool
"""
from __builtin__ import sum as _sum
if root is None:
return False
stack = [root]
path_stack = [(root.val, )]
while len(stack):
node = stack.pop()
path_sum = _sum(path_stack.pop())
if node.left is None and node.right is None and path_sum == sum:
return True
if node.left is not None:
stack.append(node.left)
path_stack.append((path_sum, node.left.val))
if node.right is not None:
stack.append(node.right)
path_stack.append((path_sum, node.right.val))
return False
