1-norm methods API¶
Available functions¶
hager_norm1_condhager_higham_norm1block_higham_tisseur_norm1power_iteration_norm1oettli_prager_norm1monte_carlo_norm1
When to choose each method¶
hager-higham: default high-accuracy production choice.block-higham: block variant for stronger robustness on some matrices.power: fast rough estimate.oettli-prager: adaptive/random/hybrid sampling style strategies.monte-carlo: stochastic baseline.
Example¶
from sparse_kappa import cond_estimate
result = cond_estimate(
A,
norm=1,
method='hager-higham',
solver='lu',
return_dict=True,
)
print(result['condition_number'])