Exemple #1
0
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
Exemple #2
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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())
Exemple #3
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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
Exemple #4
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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
Exemple #5
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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
Exemple #6
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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
Exemple #7
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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)
Exemple #8
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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)