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Update numpy bool and str type (#22322) 

Signed-off-by: nico <cheng.yuan@zilliz.com>
pull/22326/head
NicoYuan1986 2023-02-21 17:00:27 +08:00 committed by GitHub
parent 8959382ca6
commit c2c8ddd432
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1 changed files with 14 additions and 14 deletions
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28
tests/python_client/common/common_func.py
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@ -289,7 +289,7 @@ def gen_dataframe_all_data_type(nb=ct.default_nb, dim=ct.default_dim, start=0):
int32_values = pd.Series(data=[np.int32(i) for i in range(start, start + nb)], dtype="int32")
int16_values = pd.Series(data=[np.int16(i) for i in range(start, start + nb)], dtype="int16")
int8_values = pd.Series(data=[np.int8(i) for i in range(start, start + nb)], dtype="int8")
bool_values = pd.Series(data=[np.bool(i) for i in range(start, start + nb)], dtype="bool")
bool_values = pd.Series(data=[np.bool_(i) for i in range(start, start + nb)], dtype="bool")
float_values = pd.Series(data=[np.float32(i) for i in range(start, start + nb)], dtype="float32")
double_values = pd.Series(data=[np.double(i) for i in range(start, start + nb)], dtype="double")
string_values = pd.Series(data=[str(i) for i in range(start, start + nb)], dtype="string")
@ -352,7 +352,7 @@ def gen_default_tuple_data(nb=ct.default_nb, dim=ct.default_dim):
def gen_numpy_data(nb=ct.default_nb, dim=ct.default_dim):
int_values = np.arange(nb, dtype='int64')
float_values = np.arange(nb, dtype='float32')
string_values = [np.str(i) for i in range(nb)]
string_values = [np.str_(i) for i in range(nb)]
float_vec_values = gen_vectors(nb, dim)
data = [int_values, float_values, string_values, float_vec_values]
return data
@ -574,20 +574,20 @@ def ip(x, y):
def jaccard(x, y):
x = np.asarray(x, np.bool)
y = np.asarray(y, np.bool)
x = np.asarray(x, np.bool_)
y = np.asarray(y, np.bool_)
return 1 - np.double(np.bitwise_and(x, y).sum()) / np.double(np.bitwise_or(x, y).sum())
def hamming(x, y):
x = np.asarray(x, np.bool)
y = np.asarray(y, np.bool)
x = np.asarray(x, np.bool_)
y = np.asarray(y, np.bool_)
return np.bitwise_xor(x, y).sum()
def tanimoto(x, y):
x = np.asarray(x, np.bool)
y = np.asarray(y, np.bool)
x = np.asarray(x, np.bool_)
y = np.asarray(y, np.bool_)
res = np.double(np.bitwise_and(x, y).sum()) / np.double(np.bitwise_or(x, y).sum())
if res == 0:
value = 0
@ -597,20 +597,20 @@ def tanimoto(x, y):
def tanimoto_calc(x, y):
x = np.asarray(x, np.bool)
y = np.asarray(y, np.bool)
x = np.asarray(x, np.bool_)
y = np.asarray(y, np.bool_)
return np.double((len(x) - np.bitwise_xor(x, y).sum())) / (len(y) + np.bitwise_xor(x, y).sum())
def substructure(x, y):
x = np.asarray(x, np.bool)
y = np.asarray(y, np.bool)
x = np.asarray(x, np.bool_)
y = np.asarray(y, np.bool_)
return 1 - np.double(np.bitwise_and(x, y).sum()) / np.count_nonzero(y)
def superstructure(x, y):
x = np.asarray(x, np.bool)
y = np.asarray(y, np.bool)
x = np.asarray(x, np.bool_)
y = np.asarray(y, np.bool_)
return 1 - np.double(np.bitwise_and(x, y).sum()) / np.count_nonzero(x)