def ca5(arg):
d = arg[0]
t = arg[1]
a = arg[2]
k = arg[4]
ss = 1
for x in d:
ss *= x
if t == 'int32' or t == 'int64' or t == 'uint32' or t == 'uint64':
seed = [random.randint(1, ss * ss) for i in range(ss)]
elif t == 'float64' or t == 'float32':
seed = [random.random() for i in range(ss)]
else:
pass
na = np.array(seed)
ans = np.median(na, axis=a, keepdims=k)
np.save(fil, ans)
ok = np.load(fil)
dst = ny.median(na, axis=a, keepdims=k)
return ok, dst
def test_me_case_3():
ny_a = ny.array([[10, ny.nan, 4], [3, 2, 1]])
np_a = np.array([[10, np.nan, 4], [3, 2, 1]])
ans_ny = ny.median(ny_a, axis=1)
ans_np = np.median(np_a, axis=1)
print("ans1={} ans2={}".format(ans_ny, ans_np))
assert_array_equal(ans_np, ans_ny.get())
def ca1(arg):
d = arg[0]
na = np.array(d)
src = np.median(na)
np.save(fil, src)
ok = np.load(fil)
dst = ny.median(na)
return dst, ok
def ca2(arg):
d = arg[0]
a = arg[2]
na = np.array(d)
src = np.median(na, axis=a)
np.save(fil, src)
ok = np.load(fil)
dst = ny.median(na, axis=a)
return dst, ok
def ca4(arg):
d = arg[0]
t = arg[1]
a = arg[2]
ss = 1
for x in d:
ss *= x
if t == 'int32' or t == 'int64' or t == 'uint32' or t == 'uint64':
seed = [random.randint(1, ss * ss) for i in range(ss)]
elif t == 'float64' or t == 'float32':
seed = [random.random() for i in range(ss)]
else:
pass
na = ny.array(seed)
ans = ny.median(na, axis=a)
out = ny.zeros_like(ans)
dst = ny.median(na, axis=a, out=out)
return dst, out
def ca3(arg):
d = arg[0]
t = arg[1]
a = arg[2]
ss = 1
for x in d:
ss *= x
if t == 'int32' or t == 'int64' or t == 'uint32' or t == 'uint64':
seed = [random.randint(1, ss * ss) for i in range(ss)]
elif t == 'float64' or t == 'float32':
seed = [random.random() for i in range(ss)]
else:
pass
na = np.array(seed)
src = np.median(na, axis=a)
np.save(fil, src)
ok = np.load(fil)
dst = ny.median(na, axis=a)
return dst, ok
def test_me_case_2():
a = nlcpy.array([[10, 7, 4], [3, 2, 1]])
b = a.copy()
ny.median(b, axis=None, overwrite_input=True)
assert not ny.all(a == b)
def test_me_case_1():
a = ny.array([[10, 7, 4], [3, 2, 1]])
b = a.copy()
ny.median(b, overwrite_input=False)
print("a={} b={}".format(a, b))
assert ny.all(a == b)
