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from pypy.interpreter.error import oefmt
from rpython.rlib.listsort import make_timsort_class
from rpython.rlib.objectmodel import specialize
from rpython.rlib.rarithmetic import widen
from rpython.rlib.rawstorage import raw_storage_getitem, raw_storage_setitem, \
free_raw_storage, alloc_raw_storage
from rpython.rlib.unroll import unrolling_iterable
from rpython.rtyper.lltypesystem import rffi, lltype
from pypy.module.micronumpy import descriptor, types, constants as NPY
from pypy.module.micronumpy.base import W_NDimArray
from pypy.module.micronumpy.iterators import AllButAxisIter
INT_SIZE = rffi.sizeof(lltype.Signed)
all_types = (types.all_float_types + types.all_complex_types +
types.all_int_types)
all_types = [i for i in all_types if not issubclass(i[0], types.Float16)]
all_types = unrolling_iterable(all_types)
def make_argsort_function(space, itemtype, comp_type, count=1):
TP = itemtype.T
step = rffi.sizeof(TP)
class Repr(object):
def __init__(self, index_stride_size, stride_size, size, values,
indexes, index_start, start):
self.index_stride_size = index_stride_size
self.stride_size = stride_size
self.index_start = index_start
self.start = start
self.size = size
self.values = values
self.indexes = indexes
def getitem(self, idx):
if count < 2:
v = raw_storage_getitem(TP, self.values, idx * self.stride_size
+ self.start)
else:
v = []
for i in range(count):
_v = raw_storage_getitem(TP, self.values, idx * self.stride_size
+ self.start + step * i)
v.append(_v)
if comp_type == 'int':
v = widen(v)
elif comp_type == 'float':
v = float(v)
elif comp_type == 'complex':
v = [float(v[0]),float(v[1])]
else:
raise NotImplementedError('cannot reach')
return (v, raw_storage_getitem(lltype.Signed, self.indexes,
idx * self.index_stride_size +
self.index_start))
def setitem(self, idx, item):
if count < 2:
raw_storage_setitem(self.values, idx * self.stride_size +
self.start, rffi.cast(TP, item[0]))
else:
i = 0
for val in item[0]:
raw_storage_setitem(self.values, idx * self.stride_size +
self.start + i*step, rffi.cast(TP, val))
i += 1
raw_storage_setitem(self.indexes, idx * self.index_stride_size +
self.index_start, item[1])
class ArgArrayRepWithStorage(Repr):
def __init__(self, index_stride_size, stride_size, size):
start = 0
dtype = descriptor.get_dtype_cache(space).w_longdtype
indexes = dtype.itemtype.malloc(size * dtype.elsize)
values = alloc_raw_storage(size * stride_size,
track_allocation=False)
Repr.__init__(self, dtype.elsize, stride_size,
size, values, indexes, start, start)
def __del__(self):
free_raw_storage(self.indexes, track_allocation=False)
free_raw_storage(self.values, track_allocation=False)
def arg_getitem(lst, item):
return lst.getitem(item)
def arg_setitem(lst, item, value):
lst.setitem(item, value)
def arg_length(lst):
return lst.size
def arg_getitem_slice(lst, start, stop):
retval = ArgArrayRepWithStorage(lst.index_stride_size, lst.stride_size,
stop-start)
for i in range(stop-start):
retval.setitem(i, lst.getitem(i+start))
return retval
if count < 2:
def arg_lt(a, b):
# Does numpy do <= ?
return a[0] < b[0] or b[0] != b[0] and a[0] == a[0]
else:
def arg_lt(a, b):
for i in range(count):
if b[0][i] != b[0][i] and a[0][i] == a[0][i]:
return True
elif b[0][i] == b[0][i] and a[0][i] != a[0][i]:
return False
for i in range(count):
if a[0][i] < b[0][i]:
return True
elif a[0][i] > b[0][i]:
return False
# Does numpy do True?
return False
ArgSort = make_timsort_class(arg_getitem, arg_setitem, arg_length,
arg_getitem_slice, arg_lt)
def argsort(arr, space, w_axis):
if w_axis is space.w_None:
# note that it's fine ot pass None here as we're not going
# to pass the result around (None is the link to base in slices)
if arr.get_size() > 0:
arr = arr.reshape(None, [arr.get_size()])
axis = 0
elif w_axis is None:
axis = -1
else:
axis = space.int_w(w_axis)
# create array of indexes
dtype = descriptor.get_dtype_cache(space).w_longdtype
index_arr = W_NDimArray.from_shape(space, arr.get_shape(), dtype)
with index_arr.implementation as storage, arr as arr_storage:
if len(arr.get_shape()) == 1:
for i in range(arr.get_size()):
raw_storage_setitem(storage, i * INT_SIZE, i)
r = Repr(INT_SIZE, arr.strides[0], arr.get_size(), arr_storage,
storage, 0, arr.start)
ArgSort(r).sort()
else:
shape = arr.get_shape()
if axis < 0:
axis = len(shape) + axis
if axis < 0 or axis >= len(shape):
raise oefmt(space.w_IndexError, "Wrong axis %d", axis)
arr_iter = AllButAxisIter(arr, axis)
arr_state = arr_iter.reset()
index_impl = index_arr.implementation
index_iter = AllButAxisIter(index_impl, axis)
index_state = index_iter.reset()
stride_size = arr.strides[axis]
index_stride_size = index_impl.strides[axis]
axis_size = arr.shape[axis]
while not arr_iter.done(arr_state):
for i in range(axis_size):
raw_storage_setitem(storage, i * index_stride_size +
index_state.offset, i)
r = Repr(index_stride_size, stride_size, axis_size,
arr_storage, storage, index_state.offset, arr_state.offset)
ArgSort(r).sort()
arr_state = arr_iter.next(arr_state)
index_state = index_iter.next(index_state)
return index_arr
return argsort
def argsort_array(arr, space, w_axis):
cache = space.fromcache(ArgSortCache) # that populates ArgSortClasses
itemtype = arr.dtype.itemtype
for tp in all_types:
if isinstance(itemtype, tp[0]):
return cache._lookup(tp)(arr, space, w_axis)
# XXX this should probably be changed
raise oefmt(space.w_NotImplementedError,
"sorting of non-numeric types '%s' is not implemented",
arr.dtype.get_name())
def make_sort_function(space, itemtype, comp_type, count=1):
TP = itemtype.T
step = rffi.sizeof(TP)
class Repr(object):
def __init__(self, stride_size, size, values, start):
self.stride_size = stride_size
self.start = start
self.size = size
self.values = values
def getitem(self, item):
if count < 2:
v = raw_storage_getitem(TP, self.values, item * self.stride_size
+ self.start)
else:
v = []
for i in range(count):
_v = raw_storage_getitem(TP, self.values, item * self.stride_size
+ self.start + step * i)
v.append(_v)
if comp_type == 'int':
v = widen(v)
elif comp_type == 'float':
v = float(v)
elif comp_type == 'complex':
v = [float(v[0]),float(v[1])]
else:
raise NotImplementedError('cannot reach')
return (v)
def setitem(self, idx, item):
if count < 2:
raw_storage_setitem(self.values, idx * self.stride_size +
self.start, rffi.cast(TP, item))
else:
i = 0
for val in item:
raw_storage_setitem(self.values, idx * self.stride_size +
self.start + i*step, rffi.cast(TP, val))
i += 1
class ArgArrayRepWithStorage(Repr):
def __init__(self, stride_size, size):
start = 0
values = alloc_raw_storage(size * stride_size,
track_allocation=False)
Repr.__init__(self, stride_size,
size, values, start)
def __del__(self):
free_raw_storage(self.values, track_allocation=False)
def arg_getitem(lst, item):
return lst.getitem(item)
def arg_setitem(lst, item, value):
lst.setitem(item, value)
def arg_length(lst):
return lst.size
def arg_getitem_slice(lst, start, stop):
retval = ArgArrayRepWithStorage(lst.stride_size, stop-start)
for i in range(stop-start):
retval.setitem(i, lst.getitem(i+start))
return retval
if count < 2:
def arg_lt(a, b):
# handles NAN and INF
return a < b or b != b and a == a
else:
def arg_lt(a, b):
for i in range(count):
if b[i] != b[i] and a[i] == a[i]:
return True
elif b[i] == b[i] and a[i] != a[i]:
return False
for i in range(count):
if a[i] < b[i]:
return True
elif a[i] > b[i]:
return False
# Does numpy do True?
return False
ArgSort = make_timsort_class(arg_getitem, arg_setitem, arg_length,
arg_getitem_slice, arg_lt)
def sort(arr, space, w_axis):
if w_axis is space.w_None:
# note that it's fine to pass None here as we're not going
# to pass the result around (None is the link to base in slices)
arr = arr.reshape(None, [arr.get_size()])
axis = 0
elif w_axis is None:
axis = -1
else:
axis = space.int_w(w_axis)
with arr as storage:
if len(arr.get_shape()) == 1:
r = Repr(arr.strides[0], arr.get_size(), storage,
arr.start)
ArgSort(r).sort()
else:
shape = arr.get_shape()
if axis < 0:
axis = len(shape) + axis
if axis < 0 or axis >= len(shape):
raise oefmt(space.w_IndexError, "Wrong axis %d", axis)
arr_iter = AllButAxisIter(arr, axis)
arr_state = arr_iter.reset()
stride_size = arr.strides[axis]
axis_size = arr.shape[axis]
while not arr_iter.done(arr_state):
r = Repr(stride_size, axis_size, storage, arr_state.offset)
ArgSort(r).sort()
arr_state = arr_iter.next(arr_state)
return sort
def sort_array(arr, space, w_axis, w_order):
cache = space.fromcache(SortCache) # that populates SortClasses
itemtype = arr.dtype.itemtype
if arr.dtype.byteorder == NPY.OPPBYTE:
raise oefmt(space.w_NotImplementedError,
"sorting of non-native byteorder not supported yet")
for tp in all_types:
if isinstance(itemtype, tp[0]):
return cache._lookup(tp)(arr, space, w_axis)
# XXX this should probably be changed
raise oefmt(space.w_NotImplementedError,
"sorting of non-numeric types '%s' is not implemented",
arr.dtype.get_name())
class ArgSortCache(object):
built = False
def __init__(self, space):
if self.built:
return
self.built = True
cache = {}
for cls, it in all_types._items:
if it == 'complex':
cache[cls] = make_argsort_function(space, cls, it, 2)
else:
cache[cls] = make_argsort_function(space, cls, it)
self.cache = cache
self._lookup = specialize.memo()(lambda tp: cache[tp[0]])
class SortCache(object):
built = False
def __init__(self, space):
if self.built:
return
self.built = True
cache = {}
for cls, it in all_types._items:
if it == 'complex':
cache[cls] = make_sort_function(space, cls, it, 2)
else:
cache[cls] = make_sort_function(space, cls, it)
self.cache = cache
self._lookup = specialize.memo()(lambda tp: cache[tp[0]])
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