Python numpy.linalg.eigvals() Examples

The following are 30 code examples of numpy.linalg.eigvals(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module numpy.linalg , or try the search function .
Example #1
Source File: test_linalg.py    From Computable with MIT License 6 votes vote down vote up 
def do(self, a, b):
        d = linalg.det(a)
        (s, ld) = linalg.slogdet(a)
        if asarray(a).dtype.type in (single, double):
            ad = asarray(a).astype(double)
        else:
            ad = asarray(a).astype(cdouble)
        ev = linalg.eigvals(ad)
        assert_almost_equal(d, multiply.reduce(ev, axis=-1))
        assert_almost_equal(s * np.exp(ld), multiply.reduce(ev, axis=-1))

        s = np.atleast_1d(s)
        ld = np.atleast_1d(ld)
        m = (s != 0)
        assert_almost_equal(np.abs(s[m]), 1)
        assert_equal(ld[~m], -inf)
Example #2
Source File: test_linalg.py    From auto-alt-text-lambda-api with MIT License 6 votes vote down vote up 
def do(self, a, b):
        d = linalg.det(a)
        (s, ld) = linalg.slogdet(a)
        if asarray(a).dtype.type in (single, double):
            ad = asarray(a).astype(double)
        else:
            ad = asarray(a).astype(cdouble)
        ev = linalg.eigvals(ad)
        assert_almost_equal(d, multiply.reduce(ev, axis=-1))
        assert_almost_equal(s * np.exp(ld), multiply.reduce(ev, axis=-1))

        s = np.atleast_1d(s)
        ld = np.atleast_1d(ld)
        m = (s != 0)
        assert_almost_equal(np.abs(s[m]), 1)
        assert_equal(ld[~m], -inf)
Example #3
Source File: test_linalg.py    From lambda-packs with MIT License 6 votes vote down vote up 
def do(self, a, b):
        d = linalg.det(a)
        (s, ld) = linalg.slogdet(a)
        if asarray(a).dtype.type in (single, double):
            ad = asarray(a).astype(double)
        else:
            ad = asarray(a).astype(cdouble)
        ev = linalg.eigvals(ad)
        assert_almost_equal(d, multiply.reduce(ev, axis=-1))
        assert_almost_equal(s * np.exp(ld), multiply.reduce(ev, axis=-1))

        s = np.atleast_1d(s)
        ld = np.atleast_1d(ld)
        m = (s != 0)
        assert_almost_equal(np.abs(s[m]), 1)
        assert_equal(ld[~m], -inf)
Example #4
Source File: test_linalg.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 6 votes vote down vote up 
def test_0_size(self):
        # Check that all kinds of 0-sized arrays work
        class ArraySubclass(np.ndarray):
            pass
        a = np.zeros((0, 1, 1), dtype=np.int_).view(ArraySubclass)
        res = linalg.eigvals(a)
        assert_(res.dtype.type is np.float64)
        assert_equal((0, 1), res.shape)
        # This is just for documentation, it might make sense to change:
        assert_(isinstance(res, np.ndarray))

        a = np.zeros((0, 0), dtype=np.complex64).view(ArraySubclass)
        res = linalg.eigvals(a)
        assert_(res.dtype.type is np.complex64)
        assert_equal((0,), res.shape)
        # This is just for documentation, it might make sense to change:
        assert_(isinstance(res, np.ndarray))
Example #5
Source File: test_linalg.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 6 votes vote down vote up 
def do(self, a, b, tags):
        d = linalg.det(a)
        (s, ld) = linalg.slogdet(a)
        if asarray(a).dtype.type in (single, double):
            ad = asarray(a).astype(double)
        else:
            ad = asarray(a).astype(cdouble)
        ev = linalg.eigvals(ad)
        assert_almost_equal(d, multiply.reduce(ev, axis=-1))
        assert_almost_equal(s * np.exp(ld), multiply.reduce(ev, axis=-1))

        s = np.atleast_1d(s)
        ld = np.atleast_1d(ld)
        m = (s != 0)
        assert_almost_equal(np.abs(s[m]), 1)
        assert_equal(ld[~m], -inf)
Example #6
Source File: test_linalg.py    From vnpy_crypto with MIT License 6 votes vote down vote up 
def test_0_size(self):
        # Check that all kinds of 0-sized arrays work
        class ArraySubclass(np.ndarray):
            pass
        a = np.zeros((0, 1, 1), dtype=np.int_).view(ArraySubclass)
        res = linalg.eigvals(a)
        assert_(res.dtype.type is np.float64)
        assert_equal((0, 1), res.shape)
        # This is just for documentation, it might make sense to change:
        assert_(isinstance(res, np.ndarray))

        a = np.zeros((0, 0), dtype=np.complex64).view(ArraySubclass)
        res = linalg.eigvals(a)
        assert_(res.dtype.type is np.complex64)
        assert_equal((0,), res.shape)
        # This is just for documentation, it might make sense to change:
        assert_(isinstance(res, np.ndarray))
Example #7
Source File: test_linalg.py    From vnpy_crypto with MIT License 6 votes vote down vote up 
def do(self, a, b, tags):
        d = linalg.det(a)
        (s, ld) = linalg.slogdet(a)
        if asarray(a).dtype.type in (single, double):
            ad = asarray(a).astype(double)
        else:
            ad = asarray(a).astype(cdouble)
        ev = linalg.eigvals(ad)
        assert_almost_equal(d, multiply.reduce(ev, axis=-1))
        assert_almost_equal(s * np.exp(ld), multiply.reduce(ev, axis=-1))

        s = np.atleast_1d(s)
        ld = np.atleast_1d(ld)
        m = (s != 0)
        assert_almost_equal(np.abs(s[m]), 1)
        assert_equal(ld[~m], -inf)
Example #8
Source File: test_linalg.py    From Mastering-Elasticsearch-7.0 with MIT License 6 votes vote down vote up 
def test_0_size(self):
        # Check that all kinds of 0-sized arrays work
        class ArraySubclass(np.ndarray):
            pass
        a = np.zeros((0, 1, 1), dtype=np.int_).view(ArraySubclass)
        res = linalg.eigvals(a)
        assert_(res.dtype.type is np.float64)
        assert_equal((0, 1), res.shape)
        # This is just for documentation, it might make sense to change:
        assert_(isinstance(res, np.ndarray))

        a = np.zeros((0, 0), dtype=np.complex64).view(ArraySubclass)
        res = linalg.eigvals(a)
        assert_(res.dtype.type is np.complex64)
        assert_equal((0,), res.shape)
        # This is just for documentation, it might make sense to change:
        assert_(isinstance(res, np.ndarray))
Example #9
Source File: test_linalg.py    From Mastering-Elasticsearch-7.0 with MIT License 6 votes vote down vote up 
def do(self, a, b, tags):
        d = linalg.det(a)
        (s, ld) = linalg.slogdet(a)
        if asarray(a).dtype.type in (single, double):
            ad = asarray(a).astype(double)
        else:
            ad = asarray(a).astype(cdouble)
        ev = linalg.eigvals(ad)
        assert_almost_equal(d, multiply.reduce(ev, axis=-1))
        assert_almost_equal(s * np.exp(ld), multiply.reduce(ev, axis=-1))

        s = np.atleast_1d(s)
        ld = np.atleast_1d(ld)
        m = (s != 0)
        assert_almost_equal(np.abs(s[m]), 1)
        assert_equal(ld[~m], -inf)
Example #10
Source File: test_linalg.py    From GraphicDesignPatternByPython with MIT License 6 votes vote down vote up 
def do(self, a, b, tags):
        d = linalg.det(a)
        (s, ld) = linalg.slogdet(a)
        if asarray(a).dtype.type in (single, double):
            ad = asarray(a).astype(double)
        else:
            ad = asarray(a).astype(cdouble)
        ev = linalg.eigvals(ad)
        assert_almost_equal(d, multiply.reduce(ev, axis=-1))
        assert_almost_equal(s * np.exp(ld), multiply.reduce(ev, axis=-1))

        s = np.atleast_1d(s)
        ld = np.atleast_1d(ld)
        m = (s != 0)
        assert_almost_equal(np.abs(s[m]), 1)
        assert_equal(ld[~m], -inf)
Example #11
Source File: test_linalg.py    From recruit with Apache License 2.0 6 votes vote down vote up 
def do(self, a, b, tags):
        d = linalg.det(a)
        (s, ld) = linalg.slogdet(a)
        if asarray(a).dtype.type in (single, double):
            ad = asarray(a).astype(double)
        else:
            ad = asarray(a).astype(cdouble)
        ev = linalg.eigvals(ad)
        assert_almost_equal(d, multiply.reduce(ev, axis=-1))
        assert_almost_equal(s * np.exp(ld), multiply.reduce(ev, axis=-1))

        s = np.atleast_1d(s)
        ld = np.atleast_1d(ld)
        m = (s != 0)
        assert_almost_equal(np.abs(s[m]), 1)
        assert_equal(ld[~m], -inf)
Example #12
Source File: test_linalg.py    From GraphicDesignPatternByPython with MIT License 6 votes vote down vote up 
def test_0_size(self):
        # Check that all kinds of 0-sized arrays work
        class ArraySubclass(np.ndarray):
            pass
        a = np.zeros((0, 1, 1), dtype=np.int_).view(ArraySubclass)
        res = linalg.eigvals(a)
        assert_(res.dtype.type is np.float64)
        assert_equal((0, 1), res.shape)
        # This is just for documentation, it might make sense to change:
        assert_(isinstance(res, np.ndarray))

        a = np.zeros((0, 0), dtype=np.complex64).view(ArraySubclass)
        res = linalg.eigvals(a)
        assert_(res.dtype.type is np.complex64)
        assert_equal((0,), res.shape)
        # This is just for documentation, it might make sense to change:
        assert_(isinstance(res, np.ndarray))
Example #13
Source File: test_linalg.py    From Mastering-Elasticsearch-7.0 with MIT License 5 votes vote down vote up 
def test_types(self, dtype):
        x = np.array([[1, 0.5], [0.5, 1]], dtype=dtype)
        assert_equal(linalg.eigvals(x).dtype, dtype)
        x = np.array([[1, 0.5], [-1, 1]], dtype=dtype)
        assert_equal(linalg.eigvals(x).dtype, get_complex_dtype(dtype))
Example #14
Source File: test_linalg.py    From recruit with Apache License 2.0 5 votes vote down vote up 
def do(self, a, b, tags):
        ev = linalg.eigvals(a)
        evalues, evectors = linalg.eig(a)
        assert_almost_equal(ev, evalues)
Example #15
Source File: test_linalg.py    From Mastering-Elasticsearch-7.0 with MIT License 5 votes vote down vote up 
def do(self, a, b, tags):
        ev = linalg.eigvals(a)
        evalues, evectors = linalg.eig(a)
        assert_almost_equal(ev, evalues)
Example #16
Source File: test_linalg.py    From auto-alt-text-lambda-api with MIT License 5 votes vote down vote up 
def test_types(self):
        def check(dtype):
            x = np.array([[1, 0.5], [0.5, 1]], dtype=dtype)
            assert_equal(linalg.eigvals(x).dtype, dtype)
            x = np.array([[1, 0.5], [-1, 1]], dtype=dtype)
            assert_equal(linalg.eigvals(x).dtype, get_complex_dtype(dtype))
        for dtype in [single, double, csingle, cdouble]:
            yield check, dtype
Example #17
Source File: math.py    From Computable with MIT License 5 votes vote down vote up 
def is_psd(m):
    eigvals = linalg.eigvals(m)
    return np.isreal(eigvals).all() and (eigvals >= 0).all()
Example #18
Source File: test_linalg.py    From recruit with Apache License 2.0 5 votes vote down vote up 
def test_0_size(self):
        # Check that all kinds of 0-sized arrays work
        class ArraySubclass(np.ndarray):
            pass
        a = np.zeros((0, 1, 1), dtype=np.int_).view(ArraySubclass)
        res = linalg.eigvals(a)
        assert_(res.dtype.type is np.float64)
        assert_equal((0, 1), res.shape)
        # This is just for documentation, it might make sense to change:
        assert_(isinstance(res, np.ndarray))

        a = np.zeros((0, 0), dtype=np.complex64).view(ArraySubclass)
        res = linalg.eigvals(a)
        assert_(res.dtype.type is np.complex64)
        assert_equal((0,), res.shape)
        # This is just for documentation, it might make sense to change:
        assert_(isinstance(res, np.ndarray))
Example #19
Source File: test_linalg.py    From recruit with Apache License 2.0 5 votes vote down vote up 
def test_types(self, dtype):
        x = np.array([[1, 0.5], [0.5, 1]], dtype=dtype)
        assert_equal(linalg.eigvals(x).dtype, dtype)
        x = np.array([[1, 0.5], [-1, 1]], dtype=dtype)
        assert_equal(linalg.eigvals(x).dtype, get_complex_dtype(dtype))
Example #20
Source File: test_linalg.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 5 votes vote down vote up 
def do(self, a, b, tags):
        ev = linalg.eigvals(a)
        evalues, evectors = linalg.eig(a)
        assert_almost_equal(ev, evalues)
Example #21
Source File: test_linalg.py    From auto-alt-text-lambda-api with MIT License 5 votes vote down vote up 
def do(self, a, b):
        ev = linalg.eigvals(a)
        evalues, evectors = linalg.eig(a)
        assert_almost_equal(ev, evalues)
Example #22
Source File: studykde.py    From bayestsa with Apache License 2.0 5 votes vote down vote up 
def eigenvalueconstraint(params):
    sd1 = params[0]
    sd2 = params[1]
    cor = params[2]
    bandwidth = maths.stats.choleskysqrt2d(sd1, sd2, cor)
    bandwidthsq = bandwidth.dot(bandwidth.T)
    return -np.min(la.eigvals(bandwidthsq))
Example #23
Source File: test_linalg.py    From GraphicDesignPatternByPython with MIT License 5 votes vote down vote up 
def do(self, a, b, tags):
        ev = linalg.eigvals(a)
        evalues, evectors = linalg.eig(a)
        assert_almost_equal(ev, evalues)
Example #24
Source File: statesp.py    From python-control with BSD 3-Clause "New" or "Revised" License 5 votes vote down vote up 
def pole(self):
        """Compute the poles of a state space system."""

        return eigvals(self.A) if self.states else np.array([])
Example #25
Source File: test_linalg.py    From vnpy_crypto with MIT License 5 votes vote down vote up 
def do(self, a, b, tags):
        ev = linalg.eigvals(a)
        evalues, evectors = linalg.eig(a)
        assert_almost_equal(ev, evalues)
Example #26
Source File: test_linalg.py    From vnpy_crypto with MIT License 5 votes vote down vote up 
def test_types(self):
        def check(dtype):
            x = np.array([[1, 0.5], [0.5, 1]], dtype=dtype)
            assert_equal(linalg.eigvals(x).dtype, dtype)
            x = np.array([[1, 0.5], [-1, 1]], dtype=dtype)
            assert_equal(linalg.eigvals(x).dtype, get_complex_dtype(dtype))
        for dtype in [single, double, csingle, cdouble]:
            yield check, dtype
Example #27
Source File: test_linalg.py    From Computable with MIT License 5 votes vote down vote up 
def test_types(self):
        def check(dtype):
            x = np.array([[1, 0.5], [0.5, 1]], dtype=dtype)
            assert_equal(linalg.eigvals(x).dtype, dtype)
            x = np.array([[1, 0.5], [-1, 1]], dtype=dtype)
            assert_equal(linalg.eigvals(x).dtype, get_complex_dtype(dtype))
        for dtype in [single, double, csingle, cdouble]:
            yield check, dtype
Example #28
Source File: test_linalg.py    From GraphicDesignPatternByPython with MIT License 5 votes vote down vote up 
def test_types(self):
        def check(dtype):
            x = np.array([[1, 0.5], [0.5, 1]], dtype=dtype)
            assert_equal(linalg.eigvals(x).dtype, dtype)
            x = np.array([[1, 0.5], [-1, 1]], dtype=dtype)
            assert_equal(linalg.eigvals(x).dtype, get_complex_dtype(dtype))
        for dtype in [single, double, csingle, cdouble]:
            check(dtype)
Example #29
Source File: linear_algebra.py    From Computable with MIT License 5 votes vote down vote up 
def eigenvalues(a):
    return linalg.eigvals(a)
Example #30
Source File: test_linalg.py    From Computable with MIT License 5 votes vote down vote up 
def do(self, a, b):
        ev = linalg.eigvals(a)
        evalues, evectors = linalg.eig(a)
        assert_almost_equal(ev, evalues)