def stability_M(csd_profile, csd_seed, n_src, ele_lims, true_csd_xlims,
total_ele):
"""
Investigates stability of reconstruction for different number of basis
sources
Parameters
----------
csd_profile: function
Function to produce csd profile.
csd_seed: int
Seed for random generator to choose random CSD profile.
n_src: int
Number of basis sources.
ele_lims: list
Boundaries for electrodes placement.
true_csd_xlims: list
Boundaries for ground truth space.
total_ele: int
Number of electrodes.
Returns
-------
obj_all: class object
rms: float
Normalized error of reconstruction.
point_error_all: numpy array
Normalized error of reconstruction calculated separetly at every point
point of estimation space.
eigenvalues: numpy array
Eigenvalues of k_pot matrix.
eigenvectors: numpy array
Eigen vectors of k_pot matrix.
"""
obj_all = []
rms = np.zeros((len(n_src)))
point_error_all = []
eigenvectors = np.zeros((len(n_src), total_ele, total_ele))
eigenvalues = np.zeros((len(n_src), total_ele))
for i, value in enumerate(n_src):
KK = ValidateKCSD1D(csd_seed,
n_src_init=value,
R_init=0.23,
ele_lims=ele_lims,
true_csd_xlims=true_csd_xlims,
sigma=0.3,
h=0.25,
src_type='gauss')
obj, rms[i], point_error = KK.make_reconstruction(csd_profile,
csd_seed,
total_ele=total_ele,
noise=0,
Rs=np.arange(
0.2, 0.5, 0.1))
ss = SpectralStructure(obj)
eigenvectors[i], eigenvalues[i] = ss.evd()
point_error_all.append(point_error)
obj_all.append(obj)
return obj_all, rms, point_error_all, eigenvalues, eigenvectors
def targeted_basis(val, csd_at, true_csd, ele_pos, pots, n_src, R, MU,
true_csd_xlims, ele_lims, title, h=0.25, sigma=0.3,
csd_res=100):
'''
Function investigating kCSD analysis for targeted bases.
Parameters
----------
val: object of the class ValidateKCSD.
csd_at: numpy array
Coordinates of ground truth data.
true_csd: numpy array
Values of ground truth data (true_csd).
ele_pos: numpy array
Locations of electrodes.
pots: numpy array
Potentials measured (calculated) on electrodes.
n_src: int
Number of basis sources.
R: float
Thickness of the groundtruth source.
MU: float
x coordinate of maximum ampliude of groundtruth source.
true_csd_xlims: list
Boundaries for ground truth space.
ele_lims: list
Boundaries for electrodes placement.
h: float
Thickness of analyzed cylindrical slice.
Default: 0.25.
sigma: float
Space conductance of the medium.
Default: 0.3.
csd_res: int
Resolution of ground truth.
Default: 100.
Returns
-------
obj: object of the class KCSD1D
k: object of the class ValidateKCSD1D
'''
k = ValidateKCSD1D(1, n_src_init=n_src, R_init=0.23,
ele_lims=ele_lims,
true_csd_xlims=true_csd_xlims, sigma=sigma, h=h,
src_type='gauss')
obj, est_csd = k.recon(pots, ele_pos, method='cross-validation',
Rs=np.arange(0.2, 0.5, 0.1))
test_csd = csd_profile(obj.estm_x, [R, MU])
rms = val.calculate_rms(test_csd, est_csd)
titl = "Lambda: %0.2E; R: %0.2f; RMS_Error: %0.2E;" % (obj.lambd, obj.R,
rms)
fig = k.make_plot(csd_at, true_csd, obj, est_csd, ele_pos, pots, titl)
save_as = (SAVE_PATH)
fig.savefig(os.path.join(SAVE_PATH, save_as + '/' + title + '.png'))
plt.close()
return obj, k
def default_setting(self, dim, csd_instance):
if dim == 1:
utils = ValidateKCSD1D(csd_seed=42)
elif dim == 2:
utils = ValidateKCSD2D(csd_seed=43)
else:
utils = ValidateKCSD3D(csd_seed=44)
ele_pos = utils.generate_electrodes(total_ele=3)
csd_at, csd = utils.generate_csd(csd_instance, csd_seed=2)
lfp = utils.calculate_potential(csd, csd_at, ele_pos, h=1, sigma=0.3)
return ele_pos, lfp
def setUp(self):
dim = 1
utils = ValidateKCSD1D(csd_seed=42)
self.ele_pos = utils.generate_electrodes(total_ele=10,
ele_lims=[0.1, 0.9])
self.csd_profile = CSD.gauss_1d_mono
self.csd_at, self.csd = utils.generate_csd(self.csd_profile,
csd_seed=42)
pots = utils.calculate_potential(self.csd,
self.csd_at,
self.ele_pos,
h=1.,
sigma=0.3)
self.pots = np.reshape(pots, (-1, 1))
self.test_method = 'KCSD1D'
self.test_params = {
'h': 1.,
'sigma': 0.3,
'R_init': 0.2,
'n_src_init': 100,
'xmin': 0.,
'xmax': 1.,
}
def stability_M(csd_profile,
csd_seed,
n_src,
ele_lims,
true_csd_xlims,
total_ele,
noise=0,
method='cross-validation',
Rs=None,
lambdas=None):
"""
Investigates stability of reconstruction for different number of basis
sources
Parameters
----------
csd_profile: function
Function to produce csd profile.
csd_seed: int
Seed for random generator to choose random CSD profile.
n_src: int
Number of basis sources.
ele_lims: list
Boundaries for electrodes placement.
true_csd_xlims: list
Boundaries for ground truth space.
total_ele: int
Number of electrodes.
noise: float
Determines the level of noise in the data.
Default: 0.
method: string
Determines the method of regularization.
Default: cross-validation.
Rs: numpy 1D array
Basis source parameter for crossvalidation.
Default: None.
lambdas: numpy 1D array
Regularization parameter for crossvalidation.
Default: None.
Returns
-------
obj_all: class object
rms: float
Normalized error of reconstruction.
point_error_all: numpy array
Normalized error of reconstruction calculated separetly at every point
point of estimation space.
eigenvalues: numpy array
Eigenvalues of k_pot matrix.
eigenvectors: numpy array
Eigen vectors of k_pot matrix.
"""
obj_all = []
rms = np.zeros((len(n_src)))
point_error_all = []
eigenvectors = np.zeros((len(n_src), total_ele, total_ele))
eigenvalues = np.zeros((len(n_src), total_ele))
for i, value in enumerate(n_src):
KK = ValidateKCSD1D(csd_seed,
n_src_init=value,
R_init=0.23,
ele_lims=ele_lims,
true_csd_xlims=true_csd_xlims,
sigma=0.3,
h=0.25,
src_type='gauss',
est_xres=0.01)
obj, rms[i], point_error = KK.make_reconstruction(csd_profile,
csd_seed,
total_ele=total_ele,
noise=noise,
Rs=Rs,
lambdas=lambdas)
ss = SpectralStructure(obj)
eigenvectors[i], eigenvalues[i] = ss.evd()
point_error_all.append(point_error)
obj_all.append(obj)
return obj_all, rms, point_error_all, eigenvalues, eigenvectors