elephant.current_source_density_src.basis_functions module

This script is used to generate basis sources for the kCSD method Jan et.al (2012) for 1D,2D and 3D cases. Two ‘types’ are described here, gaussian and step source, These can be easily extended. These scripts are based on Grzegorz Parka’s, Google Summer of Code 2014, INFC/pykCSD This was written by : Michal Czerwinski, Chaitanya Chintaluri Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology, Warsaw.

elephant.current_source_density_src.basis_functions.gauss(d, stdev, dim)[source]

Gaussian function Parameters ———- d : floats or np.arrays

Distance array to the point of evaluation
stdev : float
cutoff range
dim : int
dimension of the gaussian function
Z : floats or np.arrays
function evaluated
elephant.current_source_density_src.basis_functions.gauss_1D(d, three_stdev)[source]

Returns normalized gaussian 2D scale function Parameters ———- d : floats or np.arrays

Distance array to the point of evaluation
three_stdev : float
3 * standard deviation of the distribution

Z : (three_std/3)*(1/2*pi)*(exp(-0.5)*stddev**(-2) *(d**2))

elephant.current_source_density_src.basis_functions.gauss_2D(d, three_stdev)[source]

Returns normalized gaussian 2D scale function Parameters ———- d : floats or np.arrays

distance at which we need the function evaluated
three_stdev : float
3 * standard deviation of the distribution
Z : function
Normalized gaussian 2D function
elephant.current_source_density_src.basis_functions.gauss_3D(d, three_stdev)[source]

Returns normalized gaussian 3D scale function Parameters ———- d : floats or np.arrays

distance at which we need the function evaluated
three_stdev : float
3 * standard deviation of the distribution
Z : funtion
Normalized gaussian 3D function
elephant.current_source_density_src.basis_functions.gauss_lim_1D(d, three_stdev)[source]

Returns gausian 2D function cut off after 3 standard deviations. Parameters ———- d : floats or np.arrays

Distance array to the point of evaluation
three_stdev : float
3 * standard deviation of the distribution
Z : (three_std/3)*(1/2*pi)*(exp(-0.5)*stddev**(-2) *((x-mu)**2)),
cut off = three_stdev
elephant.current_source_density_src.basis_functions.gauss_lim_2D(d, three_stdev)[source]

Returns gausian 2D function cut off after 3 standard deviations. Parameters ———- d : floats or np.arrays

distance at which we need the function evaluated
three_stdev : float
3 * standard deviation of the distribution
Z : function
Normalized gaussian 2D function cut off after three_stdev
elephant.current_source_density_src.basis_functions.gauss_lim_3D(d, three_stdev)[source]

Returns normalized gaussian 3D scale function cut off after 3stdev Parameters ———- d : floats or np.arrays

distance at which we need the function evaluated
three_stdev : float
3 * standard deviation of the distribution
Z : funtion
Normalized gaussian 3D function cutoff three_Stdev
elephant.current_source_density_src.basis_functions.step_1D(d, R)[source]

Returns normalized 1D step function. Parameters ———- d : floats or np.arrays

Distance array to the point of evaluation
R : float
cutoff range

s : Value of the function (d <= R) / R

elephant.current_source_density_src.basis_functions.step_2D(d, R)[source]

Returns normalized 2D step function. Parameters ———- d : float or np.arrays

Distance array to the point of evaluation
R : float
cutoff range
Returns:s : step function
elephant.current_source_density_src.basis_functions.step_3D(d, R)[source]

Returns normalized 3D step function. Parameters ———- d : floats or np.arrays

distance at which we need the function evaluated
R : float
cutoff range

s : step function in 3D