本文整理汇总了Python中scipy.linalg.solveh_banded函数的典型用法代码示例。如果您正苦于以下问题：Python solveh_banded函数的具体用法？Python solveh_banded怎么用？Python solveh_banded使用的例子？那么恭喜您, 这里精选的函数代码示例或许可以为您提供帮助。
在下文中一共展示了solveh_banded函数的20个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于我们的系统推荐出更棒的Python代码示例。
示例1: minimize_Z_EL_cython
def minimize_Z_EL_cython(A, l1, l2, rho):
""""""
# build banded matrix:
n = len(A)
Bmat = numpy.zeros((2,n))
Bmat[0,:] = -2*l2/rho
Bmat[1,1:n-1] = 1 +4*l2/rho
Bmat[1,0] = Bmat[1,n-1] = 1 + 2*l2/rho
# convert A into an array:
A_ = numpy.zeros((len(A), A[0].shape[0], A[0].shape[0]))
for i in range(len(A)):
A_[i,:,:] = A[i]
sudoZ = A_[:]
for i in range(A[0].shape[0]):
for j in range(i, A[0].shape[0]):
resp = A_[:,i,j]
# get LS solution:
beta_hat = solveh_banded(Bmat, resp, overwrite_ab=True, overwrite_b=True)
# shooting algorithm:
beta_hat = Z_shooting.Z_shooting(B=beta_hat, y=resp, l1=l1, l2=l2, tol=0.1, max_iter=100)
sudoZ[:,i,j] = beta_hat
sudoZ[:,j,i] = beta_hat
# return to a list (terribly inefficient! I have to change this!)
Z_ = [None] * len(A)
for i in range(len(A)):
Z_[i] = sudoZ[i,:,:]
return Z_
开发者ID:gmontana，项目名称:pySINGLE，代码行数:34，代码来源:fitSINGLE.py
示例2: fit
def fit(self, y, x=None, weights=None, pen=0.):
banded = True
if x is None:
x = self.tau[(self.M-1):-(self.M-1)] # internal knots
if pen == 0.: # can't use cholesky for singular matrices
banded = False
if x.shape != y.shape:
raise ValueError, 'x and y shape do not agree, by default x are the Bspline\'s internal knots'
bt = self.basis(x)
if pen >= self.penmax:
pen = self.penmax
if weights is None:
weights = N.array(1.)
wmean = weights.mean()
_w = N.sqrt(weights / wmean)
bt *= _w
# throw out rows with zeros (this happens at boundary points!)
mask = N.flatnonzero(1 - N.alltrue(N.equal(bt, 0), axis=0))
bt = bt[:, mask]
y = y[mask]
self.df_total = y.shape[0]
if bt.shape[1] != y.shape[0]:
raise ValueError, "some x values are outside range of B-spline knots"
bty = N.dot(bt, _w * y)
self.N = y.shape[0]
if not banded:
self.btb = N.dot(bt, bt.T)
_g = _band2array(self.g, lower=1, symmetric=True)
self.coef, _, self.rank = L.lstsq(self.btb + pen*_g, bty)[0:3]
self.rank = min(self.rank, self.btb.shape[0])
else:
self.btb = N.zeros(self.g.shape, N.float64)
nband, nbasis = self.g.shape
for i in range(nbasis):
for k in range(min(nband, nbasis-i)):
self.btb[k, i] = (bt[i] * bt[i+k]).sum()
bty.shape = (1, bty.shape[0])
self.chol, self.coef = solveh_banded(self.btb +
pen*self.g,
bty, lower=1)
self.coef = N.squeeze(self.coef)
self.resid = N.sqrt(wmean) * (y * _w - N.dot(self.coef, bt))
self.pen = pen
开发者ID:mbentz80，项目名称:jzigbeercp，代码行数:56，代码来源:smoothers.py
示例3: test_01_float32
def test_01_float32(self):
# Solve
# [ 4 1 0] [1]
# [ 1 4 1] X = [4]
# [ 0 1 4] [1]
#
ab = array([[-99, 1.0, 1.0], [4.0, 4.0, 4.0]], dtype=float32)
b = array([1.0, 4.0, 1.0], dtype=float32)
x = solveh_banded(ab, b)
assert_array_almost_equal(x, [0.0, 1.0, 0.0])
开发者ID:258073127，项目名称:MissionPlanner，代码行数:10，代码来源:test_basic.py
示例4: test_check_finite
def test_check_finite(self):
# Solve
# [ 4 1 0] [1]
# [ 1 4 1] X = [4]
# [ 0 1 4] [1]
# with the RHS as a 1D array.
ab = array([[-99, 1.0, 1.0], [4.0, 4.0, 4.0]])
b = array([1.0, 4.0, 1.0])
x = solveh_banded(ab, b, check_finite=False)
assert_array_almost_equal(x, [0.0, 1.0, 0.0])
开发者ID:7924102，项目名称:scipy，代码行数:10，代码来源:test_basic.py
示例5: test_01_complex
def test_01_complex(self):
# Solve
# [ 4 -j 0] [ -j]
# [ j 4 -j] X = [4-j]
# [ 0 j 4] [4+j]
#
ab = array([[-99, -1.0j, -1.0j], [4.0, 4.0, 4.0]])
b = array([-1.0j, 4.0-1j, 4+1j])
x = solveh_banded(ab, b)
assert_array_almost_equal(x, [0.0, 1.0, 1.0])
开发者ID:258073127，项目名称:MissionPlanner，代码行数:10，代码来源:test_basic.py
示例6: test_01_upper
def test_01_upper(self):
# Solve
# [ 4 1 0] [1]
# [ 1 4 1] X = [4]
# [ 0 1 4] [1]
# with the RHS as a 1D array.
ab = array([[-99, 1.0, 1.0], [4.0, 4.0, 4.0]])
b = array([1.0, 4.0, 1.0])
x = solveh_banded(ab, b)
assert_array_almost_equal(x, [0.0, 1.0, 0.0])
开发者ID:258073127，项目名称:MissionPlanner，代码行数:10，代码来源:test_basic.py
示例7: test_tridiag_01_lower
def test_tridiag_01_lower(self):
# Solve
# [ 4 1 0] [1]
# [ 1 4 1] X = [4]
# [ 0 1 4] [1]
#
ab = array([[4.0, 4.0, 4.0], [1.0, 1.0, -99]])
b = array([1.0, 4.0, 1.0])
x = solveh_banded(ab, b, lower=True)
assert_array_almost_equal(x, [0.0, 1.0, 0.0])
开发者ID:metamorph-inc，项目名称:meta-core，代码行数:10，代码来源:test_basic.py
示例8: test_03_upper
def test_03_upper(self):
# Solve
# [ 4 1 0] [1]
# [ 1 4 1] X = [4]
# [ 0 1 4] [1]
# with the RHS as a 2D array with shape (3,1).
ab = array([[-99, 1.0, 1.0], [4.0, 4.0, 4.0]])
b = array([1.0, 4.0, 1.0]).reshape(-1,1)
x = solveh_banded(ab, b)
assert_array_almost_equal(x, array([0.0, 1.0, 0.0]).reshape(-1,1))
开发者ID:258073127，项目名称:MissionPlanner，代码行数:10，代码来源:test_basic.py
示例9: timestep
def timestep(self, input_signal, output_condition=0,
curr_noise=0, sub_noise=0, cond_noise=0):
"""
Compute the time evolution for one timestep using increments of
the driving noise (current, subunit or conductance or a mixture)
and the corresponding input signal at the soma. The output as an
outflux current can also be specified.
Note that the noise has to be initialized outside the class in
order to be able to compare models for given trajectories of the
noise. Shape of the noise has to be
curr_noise.shape = (N_axon+1, M)
sub_noise.shape = (3, N_axon+1, M)
cond_noise.shape = (11, N_axon+1, M)
"""
[v, m, h, n] = self.state.copy()
# Explicit Euler(-Maruyama) step for gating variables
self.state[1] += self.dt * self.t_m(v) * (self.m_inf(v)-m)
self.state[2] += self.dt * self.t_h(v) * (self.h_inf(v)-h)
self.state[3] += self.dt * self.t_n(v) * (self.n_inf(v)-n)
# If subunit noise is switched on
if np.max(self.sigma_sub):
N = self.N_axon + 1
self.state[1][:N, :] += (np.sqrt(self.alpha_m(v[:N, :]) *
(1-m[:N, :]) + self.beta_m(v[:N, :]) * m[:N, :]) *
self.sigma_sub[0] * sub_noise[0])
self.state[2][:N, :] += (np.sqrt(self.alpha_h(v[:N, :]) *
(1-h[:N, :]) + self.beta_h(v[:N, :]) * h[:N, :]) *
self.sigma_sub[1] * sub_noise[1])
self.state[3][:N, :] += (np.sqrt(self.alpha_n(v[:N, :]) *
(1-n[:N, :]) + self.beta_n(v[:N, :]) * n[:N, :]) *
self.sigma_sub[2] * sub_noise[2])
# Respect boundaries!
for i in xrange(3):
self.state[i][self.state[i]>1] = 1
self.state[i][self.state[i]<0] = 0
# Semi-implicit Euler step for voltage variable
rhs = v - self.dt*self.fv(v, m, h, n)
rhs[:self.N_axon+1, :] += self.sigma_curr*curr_noise
# If conductance noise is switched on
if self.sigma_cond:
rhs[:self.N_axon+1,:] -= self.compute_cond_noise(cond_noise)
# Input signal as Neumann boundary condition for left axon endpoint
rhs[0] += self.boundary * input_signal
# Output condition as Neumann boundary condition for right axon endpoint
rhs[-1] += self.boundary * output_condition
# Modification of RHS to make discrete Neumann Laplacian symmetric
rhs[0] *= 0.5
rhs[-1] *= 0.5
# Solve the linear problem
self.state[0] = lng.solveh_banded(self.bandedmatrix, rhs,
check_finite=False)
# Update state
#self.state = [v_neu, m_neu, h_neu, n_neu]
self.time_elapsed += self.dt
开发者ID:deristnochda，项目名称:Hodgkin-Huxley-SPDE，代码行数:55，代码来源:spatialextneuron.py
示例10: test_01_complex
def test_01_complex(self):
# Solve
# [ 4 -j 2 0] [2-j]
# [ j 4 -j 2] X = [4-j]
# [ 2 j 4 -j] [4+j]
# [ 0 2 j 4] [2+j]
#
ab = array([[0.0, 0.0, 2.0, 2.0], [-99, -1.0j, -1.0j, -1.0j], [4.0, 4.0, 4.0, 4.0]])
b = array([2 - 1.0j, 4.0 - 1j, 4 + 1j, 2 + 1j])
x = solveh_banded(ab, b)
assert_array_almost_equal(x, [0.0, 1.0, 1.0, 0.0])
开发者ID:metamorph-inc，项目名称:meta-core，代码行数:11，代码来源:test_basic.py
示例11: test_tridiag_02_lower
def test_tridiag_02_lower(self):
# Solve
# [ 4 1 0] [1 4]
# [ 1 4 1] X = [4 2]
# [ 0 1 4] [1 4]
#
ab = array([[4.0, 4.0, 4.0], [1.0, 1.0, -99]])
b = array([[1.0, 4.0], [4.0, 2.0], [1.0, 4.0]])
x = solveh_banded(ab, b, lower=True)
expected = array([[0.0, 1.0], [1.0, 0.0], [0.0, 1.0]])
assert_array_almost_equal(x, expected)
开发者ID:metamorph-inc，项目名称:meta-core，代码行数:11，代码来源:test_basic.py
示例12: test_01_lower
def test_01_lower(self):
# Solve
# [ 4 1 2 0] [1]
# [ 1 4 1 2] X = [4]
# [ 2 1 4 1] [1]
# [ 0 2 1 4] [2]
#
ab = array([[4.0, 4.0, 4.0, 4.0], [1.0, 1.0, 1.0, -99], [2.0, 2.0, 0.0, 0.0]])
b = array([1.0, 4.0, 1.0, 2.0])
x = solveh_banded(ab, b, lower=True)
assert_array_almost_equal(x, [0.0, 1.0, 0.0, 0.0])
开发者ID:metamorph-inc，项目名称:meta-core，代码行数:11，代码来源:test_basic.py
示例13: test_01_float32
def test_01_float32(self):
warnings.simplefilter("ignore", category=DeprecationWarning)
# Solve
# [ 4 1 0] [1]
# [ 1 4 1] X = [4]
# [ 0 1 4] [1]
#
ab = array([[-99, 1.0, 1.0], [4.0, 4.0, 4.0]], dtype=float32)
b = array([1.0, 4.0, 1.0], dtype=float32)
c, x = solveh_banded(ab, b)
assert_array_almost_equal(x, [0.0, 1.0, 0.0])
开发者ID:dagss，项目名称:private-scipy-refactor，代码行数:11，代码来源:test_basic.py
示例14: test_01_complex
def test_01_complex(self):
warnings.simplefilter("ignore", category=DeprecationWarning)
# Solve
# [ 4 -j 0] [ -j]
# [ j 4 -j] X = [4-j]
# [ 0 j 4] [4+j]
#
ab = array([[-99, -1.0j, -1.0j], [4.0, 4.0, 4.0]])
b = array([-1.0j, 4.0 - 1j, 4 + 1j])
c, x = solveh_banded(ab, b)
assert_array_almost_equal(x, [0.0, 1.0, 1.0])
开发者ID:dagss，项目名称:private-scipy-refactor，代码行数:11，代码来源:test_basic.py
示例15: test_03_upper
def test_03_upper(self):
warnings.simplefilter("ignore", category=DeprecationWarning)
# Solve
# [ 4 1 0] [1]
# [ 1 4 1] X = [4]
# [ 0 1 4] [1]
# with the RHS as a 2D array with shape (3,1).
ab = array([[-99, 1.0, 1.0], [4.0, 4.0, 4.0]])
b = array([1.0, 4.0, 1.0]).reshape(-1, 1)
c, x = solveh_banded(ab, b)
assert_array_almost_equal(x, array([0.0, 1.0, 0.0]).reshape(-1, 1))
开发者ID:dagss，项目名称:private-scipy-refactor，代码行数:11，代码来源:test_basic.py
示例16: test_01_lower
def test_01_lower(self):
warnings.simplefilter("ignore", category=DeprecationWarning)
# Solve
# [ 4 1 0] [1]
# [ 1 4 1] X = [4]
# [ 0 1 4] [1]
#
ab = array([[4.0, 4.0, 4.0], [1.0, 1.0, -99]])
b = array([1.0, 4.0, 1.0])
c, x = solveh_banded(ab, b, lower=True)
assert_array_almost_equal(x, [0.0, 1.0, 0.0])
开发者ID:dagss，项目名称:private-scipy-refactor，代码行数:11，代码来源:test_basic.py
示例17: test_tridiag_02_complex
def test_tridiag_02_complex(self):
# Solve
# [ 4 -j 0] [ -j 4j]
# [ j 4 -j] X = [4-j -1-j]
# [ 0 j 4] [4+j 4 ]
#
ab = array([[-99, -1.0j, -1.0j], [4.0, 4.0, 4.0]])
b = array([[-1j, 4.0j], [4.0 - 1j, -1.0 - 1j], [4.0 + 1j, 4.0]])
x = solveh_banded(ab, b)
expected = array([[0.0, 1.0j], [1.0, 0.0], [1.0, 1.0]])
assert_array_almost_equal(x, expected)
开发者ID:metamorph-inc，项目名称:meta-core，代码行数:11，代码来源:test_basic.py
示例18: test_tridiag_02_float32
def test_tridiag_02_float32(self):
# Solve
# [ 4 1 0] [1 4]
# [ 1 4 1] X = [4 2]
# [ 0 1 4] [1 4]
#
ab = array([[-99, 1.0, 1.0], [4.0, 4.0, 4.0]], dtype=float32)
b = array([[1.0, 4.0], [4.0, 2.0], [1.0, 4.0]], dtype=float32)
x = solveh_banded(ab, b)
expected = array([[0.0, 1.0], [1.0, 0.0], [0.0, 1.0]])
assert_array_almost_equal(x, expected)
开发者ID:metamorph-inc，项目名称:meta-core，代码行数:11，代码来源:test_basic.py
示例19: test_02_upper
def test_02_upper(self):
warnings.simplefilter("ignore", category=DeprecationWarning)
# Solve
# [ 4 1 0] [1 4]
# [ 1 4 1] X = [4 2]
# [ 0 1 4] [1 4]
#
ab = array([[-99, 1.0, 1.0], [4.0, 4.0, 4.0]])
b = array([[1.0, 4.0], [4.0, 2.0], [1.0, 4.0]])
c, x = solveh_banded(ab, b)
expected = array([[0.0, 1.0], [1.0, 0.0], [0.0, 1.0]])
assert_array_almost_equal(x, expected)
开发者ID:dagss，项目名称:private-scipy-refactor，代码行数:12，代码来源:test_basic.py
示例20: test_02_float32
def test_02_float32(self):
# Solve
# [ 4 1 2 0] [1 6]
# [ 1 4 1 2] X = [4 2]
# [ 2 1 4 1] [1 6]
# [ 0 2 1 4] [2 1]
#
ab = array([[0.0, 0.0, 2.0, 2.0], [-99, 1.0, 1.0, 1.0], [4.0, 4.0, 4.0, 4.0]], dtype=float32)
b = array([[1.0, 6.0], [4.0, 2.0], [1.0, 6.0], [2.0, 1.0]], dtype=float32)
x = solveh_banded(ab, b)
expected = array([[0.0, 1.0], [1.0, 0.0], [0.0, 1.0], [0.0, 0.0]])
assert_array_almost_equal(x, expected)
开发者ID:metamorph-inc，项目名称:meta-core，代码行数:12，代码来源:test_basic.py
注：本文中的scipy.linalg.solveh_banded函数示例由纯净天空整理自Github/MSDocs等源码及文档管理平台，相关代码片段筛选自各路编程大神贡献的开源项目，源码版权归原作者所有，传播和使用请参考对应项目的License；未经允许，请勿转载。 |
客服电话
APP下载
官方微信
请发表评论