Python numpy.core.umath.exp() Examples
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Example #1
Source File: test_umath.py From Computable with MIT License | 6 votes |
def test_power_float(self): x = np.array([1., 2., 3.]) assert_equal(x**0, [1., 1., 1.]) assert_equal(x**1, x) assert_equal(x**2, [1., 4., 9.]) y = x.copy() y **= 2 assert_equal(y, [1., 4., 9.]) assert_almost_equal(x**(-1), [1., 0.5, 1./3]) assert_almost_equal(x**(0.5), [1., ncu.sqrt(2), ncu.sqrt(3)]) for out, inp, msg in _gen_alignment_data(dtype=np.float32, type='unary'): exp = [ncu.sqrt(i) for i in inp] assert_almost_equal(inp**(0.5), exp, err_msg=msg) np.sqrt(inp, out=out) assert_equal(out, exp, err_msg=msg) for out, inp, msg in _gen_alignment_data(dtype=np.float64, type='unary'): exp = [ncu.sqrt(i) for i in inp] assert_almost_equal(inp**(0.5), exp, err_msg=msg) np.sqrt(inp, out=out) assert_equal(out, exp, err_msg=msg)
Example #2
Source File: test_umath.py From coffeegrindsize with MIT License | 5 votes |
def test_power_float(self): x = np.array([1., 2., 3.]) assert_equal(x**0, [1., 1., 1.]) assert_equal(x**1, x) assert_equal(x**2, [1., 4., 9.]) y = x.copy() y **= 2 assert_equal(y, [1., 4., 9.]) assert_almost_equal(x**(-1), [1., 0.5, 1./3]) assert_almost_equal(x**(0.5), [1., ncu.sqrt(2), ncu.sqrt(3)]) for out, inp, msg in _gen_alignment_data(dtype=np.float32, type='unary', max_size=11): exp = [ncu.sqrt(i) for i in inp] assert_almost_equal(inp**(0.5), exp, err_msg=msg) np.sqrt(inp, out=out) assert_equal(out, exp, err_msg=msg) for out, inp, msg in _gen_alignment_data(dtype=np.float64, type='unary', max_size=7): exp = [ncu.sqrt(i) for i in inp] assert_almost_equal(inp**(0.5), exp, err_msg=msg) np.sqrt(inp, out=out) assert_equal(out, exp, err_msg=msg)
Example #3
Source File: test_umath.py From pySINDy with MIT License | 5 votes |
def test_power_float(self): x = np.array([1., 2., 3.]) assert_equal(x**0, [1., 1., 1.]) assert_equal(x**1, x) assert_equal(x**2, [1., 4., 9.]) y = x.copy() y **= 2 assert_equal(y, [1., 4., 9.]) assert_almost_equal(x**(-1), [1., 0.5, 1./3]) assert_almost_equal(x**(0.5), [1., ncu.sqrt(2), ncu.sqrt(3)]) for out, inp, msg in _gen_alignment_data(dtype=np.float32, type='unary', max_size=11): exp = [ncu.sqrt(i) for i in inp] assert_almost_equal(inp**(0.5), exp, err_msg=msg) np.sqrt(inp, out=out) assert_equal(out, exp, err_msg=msg) for out, inp, msg in _gen_alignment_data(dtype=np.float64, type='unary', max_size=7): exp = [ncu.sqrt(i) for i in inp] assert_almost_equal(inp**(0.5), exp, err_msg=msg) np.sqrt(inp, out=out) assert_equal(out, exp, err_msg=msg)
Example #4
Source File: test_umath.py From pySINDy with MIT License | 5 votes |
def test_exp_values(self): x = [1, 2, 4, 8, 16, 32, 64, 128, 256, 512, 1024] y = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10] for dt in ['f', 'd', 'g']: log2_ = 0.69314718055994530943 xf = np.array(x, dtype=dt) yf = np.array(y, dtype=dt)*log2_ assert_almost_equal(np.exp(yf), xf)
Example #5
Source File: test_umath.py From pySINDy with MIT License | 5 votes |
def test_expm1(self): assert_almost_equal(ncu.expm1(0.2), ncu.exp(0.2)-1) assert_almost_equal(ncu.expm1(1e-6), ncu.exp(1e-6)-1)
Example #6
Source File: test_umath.py From mxnet-lambda with Apache License 2.0 | 5 votes |
def test_power_float(self): x = np.array([1., 2., 3.]) assert_equal(x**0, [1., 1., 1.]) assert_equal(x**1, x) assert_equal(x**2, [1., 4., 9.]) y = x.copy() y **= 2 assert_equal(y, [1., 4., 9.]) assert_almost_equal(x**(-1), [1., 0.5, 1./3]) assert_almost_equal(x**(0.5), [1., ncu.sqrt(2), ncu.sqrt(3)]) for out, inp, msg in _gen_alignment_data(dtype=np.float32, type='unary', max_size=11): exp = [ncu.sqrt(i) for i in inp] assert_almost_equal(inp**(0.5), exp, err_msg=msg) np.sqrt(inp, out=out) assert_equal(out, exp, err_msg=msg) for out, inp, msg in _gen_alignment_data(dtype=np.float64, type='unary', max_size=7): exp = [ncu.sqrt(i) for i in inp] assert_almost_equal(inp**(0.5), exp, err_msg=msg) np.sqrt(inp, out=out) assert_equal(out, exp, err_msg=msg)
Example #7
Source File: test_umath.py From mxnet-lambda with Apache License 2.0 | 5 votes |
def test_exp_values(self): x = [1, 2, 4, 8, 16, 32, 64, 128, 256, 512, 1024] y = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10] for dt in ['f', 'd', 'g']: log2_ = 0.69314718055994530943 xf = np.array(x, dtype=dt) yf = np.array(y, dtype=dt)*log2_ assert_almost_equal(np.exp(yf), xf)
Example #8
Source File: test_umath.py From mxnet-lambda with Apache License 2.0 | 5 votes |
def test_expm1(self): assert_almost_equal(ncu.expm1(0.2), ncu.exp(0.2)-1) assert_almost_equal(ncu.expm1(1e-6), ncu.exp(1e-6)-1)
Example #9
Source File: test_umath.py From ImageFusion with MIT License | 5 votes |
def test_power_float(self): x = np.array([1., 2., 3.]) assert_equal(x**0, [1., 1., 1.]) assert_equal(x**1, x) assert_equal(x**2, [1., 4., 9.]) y = x.copy() y **= 2 assert_equal(y, [1., 4., 9.]) assert_almost_equal(x**(-1), [1., 0.5, 1./3]) assert_almost_equal(x**(0.5), [1., ncu.sqrt(2), ncu.sqrt(3)]) for out, inp, msg in _gen_alignment_data(dtype=np.float32, type='unary', max_size=11): exp = [ncu.sqrt(i) for i in inp] assert_almost_equal(inp**(0.5), exp, err_msg=msg) np.sqrt(inp, out=out) assert_equal(out, exp, err_msg=msg) for out, inp, msg in _gen_alignment_data(dtype=np.float64, type='unary', max_size=7): exp = [ncu.sqrt(i) for i in inp] assert_almost_equal(inp**(0.5), exp, err_msg=msg) np.sqrt(inp, out=out) assert_equal(out, exp, err_msg=msg)
Example #10
Source File: test_umath.py From ImageFusion with MIT License | 5 votes |
def test_exp_values(self) : x = [1, 2, 4, 8, 16, 32, 64, 128, 256, 512, 1024] y = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10] for dt in ['f', 'd', 'g'] : log2_ = 0.69314718055994530943 xf = np.array(x, dtype=dt) yf = np.array(y, dtype=dt)*log2_ assert_almost_equal(np.exp(yf), xf)
Example #11
Source File: test_umath.py From ImageFusion with MIT License | 5 votes |
def test_expm1(self): assert_almost_equal(ncu.expm1(0.2), ncu.exp(0.2)-1) assert_almost_equal(ncu.expm1(1e-6), ncu.exp(1e-6)-1)
Example #12
Source File: test_umath.py From ImageFusion with MIT License | 5 votes |
def test_priority(self): class A(object): def __array__(self): return np.zeros(1) def __array_wrap__(self, arr, context): r = type(self)() r.arr = arr r.context = context return r class B(A): __array_priority__ = 20. class C(A): __array_priority__ = 40. x = np.zeros(1) a = A() b = B() c = C() f = ncu.minimum self.assertTrue(type(f(x, x)) is np.ndarray) self.assertTrue(type(f(x, a)) is A) self.assertTrue(type(f(x, b)) is B) self.assertTrue(type(f(x, c)) is C) self.assertTrue(type(f(a, x)) is A) self.assertTrue(type(f(b, x)) is B) self.assertTrue(type(f(c, x)) is C) self.assertTrue(type(f(a, a)) is A) self.assertTrue(type(f(a, b)) is B) self.assertTrue(type(f(b, a)) is B) self.assertTrue(type(f(b, b)) is B) self.assertTrue(type(f(b, c)) is C) self.assertTrue(type(f(c, b)) is C) self.assertTrue(type(f(c, c)) is C) self.assertTrue(type(ncu.exp(a) is A)) self.assertTrue(type(ncu.exp(b) is B)) self.assertTrue(type(ncu.exp(c) is C))
Example #13
Source File: test_umath.py From elasticintel with GNU General Public License v3.0 | 5 votes |
def test_power_float(self): x = np.array([1., 2., 3.]) assert_equal(x**0, [1., 1., 1.]) assert_equal(x**1, x) assert_equal(x**2, [1., 4., 9.]) y = x.copy() y **= 2 assert_equal(y, [1., 4., 9.]) assert_almost_equal(x**(-1), [1., 0.5, 1./3]) assert_almost_equal(x**(0.5), [1., ncu.sqrt(2), ncu.sqrt(3)]) for out, inp, msg in _gen_alignment_data(dtype=np.float32, type='unary', max_size=11): exp = [ncu.sqrt(i) for i in inp] assert_almost_equal(inp**(0.5), exp, err_msg=msg) np.sqrt(inp, out=out) assert_equal(out, exp, err_msg=msg) for out, inp, msg in _gen_alignment_data(dtype=np.float64, type='unary', max_size=7): exp = [ncu.sqrt(i) for i in inp] assert_almost_equal(inp**(0.5), exp, err_msg=msg) np.sqrt(inp, out=out) assert_equal(out, exp, err_msg=msg)
Example #14
Source File: test_umath.py From elasticintel with GNU General Public License v3.0 | 5 votes |
def test_exp_values(self): x = [1, 2, 4, 8, 16, 32, 64, 128, 256, 512, 1024] y = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10] for dt in ['f', 'd', 'g']: log2_ = 0.69314718055994530943 xf = np.array(x, dtype=dt) yf = np.array(y, dtype=dt)*log2_ assert_almost_equal(np.exp(yf), xf)
Example #15
Source File: test_umath.py From elasticintel with GNU General Public License v3.0 | 5 votes |
def test_expm1(self): assert_almost_equal(ncu.expm1(0.2), ncu.exp(0.2)-1) assert_almost_equal(ncu.expm1(1e-6), ncu.exp(1e-6)-1)
Example #16
Source File: test_umath.py From recruit with Apache License 2.0 | 5 votes |
def test_exp_values(self): x = [1, 2, 4, 8, 16, 32, 64, 128, 256, 512, 1024] y = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10] for dt in ['f', 'd', 'g']: log2_ = 0.69314718055994530943 xf = np.array(x, dtype=dt) yf = np.array(y, dtype=dt)*log2_ assert_almost_equal(np.exp(yf), xf)
Example #17
Source File: test_umath.py From coffeegrindsize with MIT License | 5 votes |
def test_exp_values(self): x = [1, 2, 4, 8, 16, 32, 64, 128, 256, 512, 1024] y = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10] for dt in ['f', 'd', 'g']: log2_ = 0.69314718055994530943 xf = np.array(x, dtype=dt) yf = np.array(y, dtype=dt)*log2_ assert_almost_equal(np.exp(yf), xf)
Example #18
Source File: test_umath.py From coffeegrindsize with MIT License | 5 votes |
def test_expm1(self): assert_almost_equal(ncu.expm1(0.2), ncu.exp(0.2)-1) assert_almost_equal(ncu.expm1(1e-6), ncu.exp(1e-6)-1)
Example #19
Source File: test_umath.py From Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda with MIT License | 5 votes |
def test_power_float(self): x = np.array([1., 2., 3.]) assert_equal(x**0, [1., 1., 1.]) assert_equal(x**1, x) assert_equal(x**2, [1., 4., 9.]) y = x.copy() y **= 2 assert_equal(y, [1., 4., 9.]) assert_almost_equal(x**(-1), [1., 0.5, 1./3]) assert_almost_equal(x**(0.5), [1., ncu.sqrt(2), ncu.sqrt(3)]) for out, inp, msg in _gen_alignment_data(dtype=np.float32, type='unary', max_size=11): exp = [ncu.sqrt(i) for i in inp] assert_almost_equal(inp**(0.5), exp, err_msg=msg) np.sqrt(inp, out=out) assert_equal(out, exp, err_msg=msg) for out, inp, msg in _gen_alignment_data(dtype=np.float64, type='unary', max_size=7): exp = [ncu.sqrt(i) for i in inp] assert_almost_equal(inp**(0.5), exp, err_msg=msg) np.sqrt(inp, out=out) assert_equal(out, exp, err_msg=msg)
Example #20
Source File: test_umath.py From Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda with MIT License | 5 votes |
def test_exp_values(self): x = [1, 2, 4, 8, 16, 32, 64, 128, 256, 512, 1024] y = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10] for dt in ['f', 'd', 'g']: log2_ = 0.69314718055994530943 xf = np.array(x, dtype=dt) yf = np.array(y, dtype=dt)*log2_ assert_almost_equal(np.exp(yf), xf)
Example #21
Source File: test_umath.py From Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda with MIT License | 5 votes |
def test_expm1(self): assert_almost_equal(ncu.expm1(0.2), ncu.exp(0.2)-1) assert_almost_equal(ncu.expm1(1e-6), ncu.exp(1e-6)-1)
Example #22
Source File: test_umath.py From twitter-stock-recommendation with MIT License | 5 votes |
def test_power_float(self): x = np.array([1., 2., 3.]) assert_equal(x**0, [1., 1., 1.]) assert_equal(x**1, x) assert_equal(x**2, [1., 4., 9.]) y = x.copy() y **= 2 assert_equal(y, [1., 4., 9.]) assert_almost_equal(x**(-1), [1., 0.5, 1./3]) assert_almost_equal(x**(0.5), [1., ncu.sqrt(2), ncu.sqrt(3)]) for out, inp, msg in _gen_alignment_data(dtype=np.float32, type='unary', max_size=11): exp = [ncu.sqrt(i) for i in inp] assert_almost_equal(inp**(0.5), exp, err_msg=msg) np.sqrt(inp, out=out) assert_equal(out, exp, err_msg=msg) for out, inp, msg in _gen_alignment_data(dtype=np.float64, type='unary', max_size=7): exp = [ncu.sqrt(i) for i in inp] assert_almost_equal(inp**(0.5), exp, err_msg=msg) np.sqrt(inp, out=out) assert_equal(out, exp, err_msg=msg)
Example #23
Source File: test_umath.py From twitter-stock-recommendation with MIT License | 5 votes |
def test_exp_values(self): x = [1, 2, 4, 8, 16, 32, 64, 128, 256, 512, 1024] y = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10] for dt in ['f', 'd', 'g']: log2_ = 0.69314718055994530943 xf = np.array(x, dtype=dt) yf = np.array(y, dtype=dt)*log2_ assert_almost_equal(np.exp(yf), xf)
Example #24
Source File: test_umath.py From twitter-stock-recommendation with MIT License | 5 votes |
def test_expm1(self): assert_almost_equal(ncu.expm1(0.2), ncu.exp(0.2)-1) assert_almost_equal(ncu.expm1(1e-6), ncu.exp(1e-6)-1)
Example #25
Source File: test_umath.py From keras-lambda with MIT License | 5 votes |
def test_power_float(self): x = np.array([1., 2., 3.]) assert_equal(x**0, [1., 1., 1.]) assert_equal(x**1, x) assert_equal(x**2, [1., 4., 9.]) y = x.copy() y **= 2 assert_equal(y, [1., 4., 9.]) assert_almost_equal(x**(-1), [1., 0.5, 1./3]) assert_almost_equal(x**(0.5), [1., ncu.sqrt(2), ncu.sqrt(3)]) for out, inp, msg in _gen_alignment_data(dtype=np.float32, type='unary', max_size=11): exp = [ncu.sqrt(i) for i in inp] assert_almost_equal(inp**(0.5), exp, err_msg=msg) np.sqrt(inp, out=out) assert_equal(out, exp, err_msg=msg) for out, inp, msg in _gen_alignment_data(dtype=np.float64, type='unary', max_size=7): exp = [ncu.sqrt(i) for i in inp] assert_almost_equal(inp**(0.5), exp, err_msg=msg) np.sqrt(inp, out=out) assert_equal(out, exp, err_msg=msg)
Example #26
Source File: test_umath.py From keras-lambda with MIT License | 5 votes |
def test_exp_values(self): x = [1, 2, 4, 8, 16, 32, 64, 128, 256, 512, 1024] y = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10] for dt in ['f', 'd', 'g']: log2_ = 0.69314718055994530943 xf = np.array(x, dtype=dt) yf = np.array(y, dtype=dt)*log2_ assert_almost_equal(np.exp(yf), xf)
Example #27
Source File: test_umath.py From keras-lambda with MIT License | 5 votes |
def test_expm1(self): assert_almost_equal(ncu.expm1(0.2), ncu.exp(0.2)-1) assert_almost_equal(ncu.expm1(1e-6), ncu.exp(1e-6)-1)
Example #28
Source File: test_umath.py From Mastering-Elasticsearch-7.0 with MIT License | 5 votes |
def test_exp_values(self): x = [1, 2, 4, 8, 16, 32, 64, 128, 256, 512, 1024] y = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10] for dt in ['f', 'd', 'g']: log2_ = 0.69314718055994530943 xf = np.array(x, dtype=dt) yf = np.array(y, dtype=dt)*log2_ assert_almost_equal(np.exp(yf), xf)
Example #29
Source File: test_umath.py From auto-alt-text-lambda-api with MIT License | 5 votes |
def test_expm1(self): assert_almost_equal(ncu.expm1(0.2), ncu.exp(0.2)-1) assert_almost_equal(ncu.expm1(1e-6), ncu.exp(1e-6)-1)
Example #30
Source File: test_umath.py From vnpy_crypto with MIT License | 5 votes |
def test_power_float(self): x = np.array([1., 2., 3.]) assert_equal(x**0, [1., 1., 1.]) assert_equal(x**1, x) assert_equal(x**2, [1., 4., 9.]) y = x.copy() y **= 2 assert_equal(y, [1., 4., 9.]) assert_almost_equal(x**(-1), [1., 0.5, 1./3]) assert_almost_equal(x**(0.5), [1., ncu.sqrt(2), ncu.sqrt(3)]) for out, inp, msg in _gen_alignment_data(dtype=np.float32, type='unary', max_size=11): exp = [ncu.sqrt(i) for i in inp] assert_almost_equal(inp**(0.5), exp, err_msg=msg) np.sqrt(inp, out=out) assert_equal(out, exp, err_msg=msg) for out, inp, msg in _gen_alignment_data(dtype=np.float64, type='unary', max_size=7): exp = [ncu.sqrt(i) for i in inp] assert_almost_equal(inp**(0.5), exp, err_msg=msg) np.sqrt(inp, out=out) assert_equal(out, exp, err_msg=msg)