def _sort_internal(a: ndarray,
axis: int = -1,
ascending: bool = True) \
-> af.Array:
if axis is None:
a = a.flatten()
axis = 0
elif axis == -1:
axis = a.ndim - 1
elif axis >= a.ndim:
raise ValueError(f"Parameter axis must be between -1 and {a.ndim - 1}")
return af.sort(a._af_array, dim=axis, is_ascending=ascending)
def sort(self, axis=-1, kind='quicksort', order=None):
if kind != 'quicksort':
print("sort 'kind' argument ignored")
if order is not None:
raise ValueError('order argument is not supported')
if (axis is None):
input = self.flatten()
axis = 0
else:
input = self
if (axis < 0):
axis = self.ndim + axis
s = arrayfire.sort(input.d_array, pu.c2f(input.shape, axis))
self.d_array = s
def sort(self, axis=-1, kind='quicksort', order=None):
if kind != 'quicksort':
print( "sort 'kind' argument ignored" )
if order is not None:
raise ValueError('order argument is not supported')
if(axis is None):
input = self.flatten()
axis = 0
else:
input = self
if(axis < 0):
axis = self.ndim+axis
s = arrayfire.sort(input.d_array, pu.c2f(input.shape, axis))
self.d_array = s
def sort(a, axis=-1, kind='quicksort', order=None):
try:
if kind != 'quicksort':
print( "sort 'kind' argument ignored" )
if order is not None:
raise ValueError('order argument is not supported')
if(axis is None):
input = a.flatten()
axis = 0
else:
input = a
if(axis < 0):
axis = a.ndim+axis
s = arrayfire.sort(input.d_array, pu.c2f(input.shape, axis))
return afnumpy.ndarray(input.shape, dtype=pu.typemap(s.dtype()), af_array=s)
except AttributeError:
return numpy.argsort(a, axis, kind, order)
def unique(ar: ndarray,
return_index: bool = False,
return_inverse: bool = False,
return_counts: bool = False) -> ndarray:
if return_index:
raise ValueError("return_index=True is not supported")
if return_inverse:
raise ValueError("return_inverse=True is not supported")
if return_counts:
raise ValueError("return_counts=True is not supported")
unsorted_unique_set_af_array = af.set_unique(ar._af_array, is_sorted=False)
sorted_unique_set_af_array = af.sort(unsorted_unique_set_af_array,
dim=0,
is_ascending=True)
return ndarray(sorted_unique_set_af_array)
def simple_algorithm(verbose = False):
display_func = _util.display_func(verbose)
print_func = _util.print_func(verbose)
a = af.randu(3, 3)
print_func(af.sum(a), af.product(a), af.min(a), af.max(a),
af.count(a), af.any_true(a), af.all_true(a))
display_func(af.sum(a, 0))
display_func(af.sum(a, 1))
display_func(af.product(a, 0))
display_func(af.product(a, 1))
display_func(af.min(a, 0))
display_func(af.min(a, 1))
display_func(af.max(a, 0))
display_func(af.max(a, 1))
display_func(af.count(a, 0))
display_func(af.count(a, 1))
display_func(af.any_true(a, 0))
display_func(af.any_true(a, 1))
display_func(af.all_true(a, 0))
display_func(af.all_true(a, 1))
display_func(af.accum(a, 0))
display_func(af.accum(a, 1))
display_func(af.sort(a, is_ascending=True))
display_func(af.sort(a, is_ascending=False))
b = (a > 0.1) * a
c = (a > 0.4) * a
d = b / c
print_func(af.sum(d));
print_func(af.sum(d, nan_val=0.0));
display_func(af.sum(d, dim=0, nan_val=0.0));
val,idx = af.sort_index(a, is_ascending=True)
display_func(val)
display_func(idx)
val,idx = af.sort_index(a, is_ascending=False)
display_func(val)
display_func(idx)
b = af.randu(3,3)
keys,vals = af.sort_by_key(a, b, is_ascending=True)
display_func(keys)
display_func(vals)
keys,vals = af.sort_by_key(a, b, is_ascending=False)
display_func(keys)
display_func(vals)
c = af.randu(5,1)
d = af.randu(5,1)
cc = af.set_unique(c, is_sorted=False)
dd = af.set_unique(af.sort(d), is_sorted=True)
display_func(cc)
display_func(dd)
display_func(af.set_union(cc, dd, is_unique=True))
display_func(af.set_union(cc, dd, is_unique=False))
display_func(af.set_intersect(cc, cc, is_unique=True))
display_func(af.set_intersect(cc, cc, is_unique=False))
af.display(af.max(a, 0)) af.display(af.max(a, 1)) af.display(af.count(a, 0)) af.display(af.count(a, 1)) af.display(af.any_true(a, 0)) af.display(af.any_true(a, 1)) af.display(af.all_true(a, 0)) af.display(af.all_true(a, 1)) af.display(af.accum(a, 0)) af.display(af.accum(a, 1)) af.display(af.sort(a, is_ascending=True)) af.display(af.sort(a, is_ascending=False)) val, idx = af.sort_index(a, is_ascending=True) af.display(val) af.display(idx) val, idx = af.sort_index(a, is_ascending=False) af.display(val) af.display(idx) b = af.randu(3, 3) keys, vals = af.sort_by_key(a, b, is_ascending=True) af.display(keys) af.display(vals) keys, vals = af.sort_by_key(a, b, is_ascending=False) af.display(keys)
af.print_array(af.max(a, 0)) af.print_array(af.max(a, 1)) af.print_array(af.count(a, 0)) af.print_array(af.count(a, 1)) af.print_array(af.any_true(a, 0)) af.print_array(af.any_true(a, 1)) af.print_array(af.all_true(a, 0)) af.print_array(af.all_true(a, 1)) af.print_array(af.accum(a, 0)) af.print_array(af.accum(a, 1)) af.print_array(af.sort(a, is_ascending=True)) af.print_array(af.sort(a, is_ascending=False)) val,idx = af.sort_index(a, is_ascending=True) af.print_array(val) af.print_array(idx) val,idx = af.sort_index(a, is_ascending=False) af.print_array(val) af.print_array(idx) b = af.randu(3,3) keys,vals = af.sort_by_key(a, b, is_ascending=True) af.print_array(keys) af.print_array(vals) keys,vals = af.sort_by_key(a, b, is_ascending=False) af.print_array(keys)
af.display(af.max(a, 0)) af.display(af.max(a, 1)) af.display(af.count(a, 0)) af.display(af.count(a, 1)) af.display(af.any_true(a, 0)) af.display(af.any_true(a, 1)) af.display(af.all_true(a, 0)) af.display(af.all_true(a, 1)) af.display(af.accum(a, 0)) af.display(af.accum(a, 1)) af.display(af.sort(a, is_ascending=True)) af.display(af.sort(a, is_ascending=False)) val,idx = af.sort_index(a, is_ascending=True) af.display(val) af.display(idx) val,idx = af.sort_index(a, is_ascending=False) af.display(val) af.display(idx) b = af.randu(3,3) keys,vals = af.sort_by_key(a, b, is_ascending=True) af.display(keys) af.display(vals) keys,vals = af.sort_by_key(a, b, is_ascending=False) af.display(keys)
def simple_algorithm(verbose=False):
display_func = _util.display_func(verbose)
print_func = _util.print_func(verbose)
a = af.randu(3, 3)
k = af.constant(1, 3, 3, dtype=af.Dtype.u32)
af.eval(k)
print_func(af.sum(a), af.product(a), af.min(a), af.max(a), af.count(a),
af.any_true(a), af.all_true(a))
display_func(af.sum(a, 0))
display_func(af.sum(a, 1))
rk = af.constant(1, 3, dtype=af.Dtype.u32)
rk[2] = 0
af.eval(rk)
display_func(af.sumByKey(rk, a, dim=0))
display_func(af.sumByKey(rk, a, dim=1))
display_func(af.productByKey(rk, a, dim=0))
display_func(af.productByKey(rk, a, dim=1))
display_func(af.minByKey(rk, a, dim=0))
display_func(af.minByKey(rk, a, dim=1))
display_func(af.maxByKey(rk, a, dim=0))
display_func(af.maxByKey(rk, a, dim=1))
display_func(af.anyTrueByKey(rk, a, dim=0))
display_func(af.anyTrueByKey(rk, a, dim=1))
display_func(af.allTrueByKey(rk, a, dim=0))
display_func(af.allTrueByKey(rk, a, dim=1))
display_func(af.countByKey(rk, a, dim=0))
display_func(af.countByKey(rk, a, dim=1))
display_func(af.product(a, 0))
display_func(af.product(a, 1))
display_func(af.min(a, 0))
display_func(af.min(a, 1))
display_func(af.max(a, 0))
display_func(af.max(a, 1))
display_func(af.count(a, 0))
display_func(af.count(a, 1))
display_func(af.any_true(a, 0))
display_func(af.any_true(a, 1))
display_func(af.all_true(a, 0))
display_func(af.all_true(a, 1))
display_func(af.accum(a, 0))
display_func(af.accum(a, 1))
display_func(af.scan(a, 0, af.BINARYOP.ADD))
display_func(af.scan(a, 1, af.BINARYOP.MAX))
display_func(af.scan_by_key(k, a, 0, af.BINARYOP.ADD))
display_func(af.scan_by_key(k, a, 1, af.BINARYOP.MAX))
display_func(af.sort(a, is_ascending=True))
display_func(af.sort(a, is_ascending=False))
b = (a > 0.1) * a
c = (a > 0.4) * a
d = b / c
print_func(af.sum(d))
print_func(af.sum(d, nan_val=0.0))
display_func(af.sum(d, dim=0, nan_val=0.0))
val, idx = af.sort_index(a, is_ascending=True)
display_func(val)
display_func(idx)
val, idx = af.sort_index(a, is_ascending=False)
display_func(val)
display_func(idx)
b = af.randu(3, 3)
keys, vals = af.sort_by_key(a, b, is_ascending=True)
display_func(keys)
display_func(vals)
keys, vals = af.sort_by_key(a, b, is_ascending=False)
display_func(keys)
display_func(vals)
c = af.randu(5, 1)
d = af.randu(5, 1)
cc = af.set_unique(c, is_sorted=False)
dd = af.set_unique(af.sort(d), is_sorted=True)
display_func(cc)
display_func(dd)
display_func(af.set_union(cc, dd, is_unique=True))
display_func(af.set_union(cc, dd, is_unique=False))
display_func(af.set_intersect(cc, cc, is_unique=True))
display_func(af.set_intersect(cc, cc, is_unique=False))
