evomap.mapping._sammon#

Nonlinear Sammon Mapping, as proposed in:

Sammon, J. W. (1969). A nonlinear mapping for data structure analysis. IEEE Transactions on computers, 100(5), 401-409.

Module Contents#

Classes#

Sammon

Functions#

_check_prepare_input_sammon(D)

Check and, if necessary, prepare data for Sammon Mapping.

_sammon_stress_function(positions, disparities[, ...])

_sammon_stress_gradient(Y, D_map, D)

class evomap.mapping._sammon.Sammon(n_dims=2, n_iter=2000, n_iter_check=50, init=None, verbose=0, input_type='distance', maxhalves=5, tol=0.001, n_inits=1, step_size=1)[source]#
fit(X)[source]#
fit_transform(X)[source]#
evomap.mapping._sammon._check_prepare_input_sammon(D)[source]#

Check and, if necessary, prepare data for Sammon Mapping.

Parameters

D (ndarray of shape (n_samples, n_samples)) – Input distance matrix.

Returns

Prepared input data

Return type

ndarray of shape (n_samples, n_samples)

evomap.mapping._sammon._sammon_stress_function(positions, disparities, compute_error=True, compute_grad=True)[source]#
evomap.mapping._sammon._sammon_stress_gradient(Y, D_map, D)[source]#