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Diffstat (limited to 'src/rip_condition.py')
| -rw-r--r-- | src/rip_condition.py | 49 |
1 files changed, 49 insertions, 0 deletions
diff --git a/src/rip_condition.py b/src/rip_condition.py new file mode 100644 index 0000000..fccf9a4 --- /dev/null +++ b/src/rip_condition.py @@ -0,0 +1,49 @@ +import numpy as np +import cascade_creation +import itertools +from scipy import sparse +from scipy.sparse import linalg + +def find_kth_rip_constants(M, k): + """ + Returns max(A_1, A_2) where: + 1 + A_1 = arg max |Mx|_2^2 s.t. |x|_2 = 1 and |x|_0 = k + 1 - A_2 = arg min |Mx|_2^2 s.t. |x|_2 = 1 and |x|_0 = kx + """ + delta = 0 + print M.shape + for col_set in itertools.combinations(xrange(M.shape[1]), k): + M_kcol = M[:,list(col_set)] + delta_upper, delta_lower = upperlower_bound_rip(M_kcol) + delta = max(delta, max(delta_upper, delta_lower)) + return delta + + +def upperlower_bound_rip(M): + """ + returns arg max/min |Mx|_2^2 s.t. |x|_2 = 1 + which is the greatest eigenvalue value of M^T*M + or the square of the greatest singular value of M + """ + M = sparse.csc_matrix(M) + s_upper = linalg.svds(M, 1, tol=.01, which ='LM', maxiter = 2000, + return_singular_vectors=False) + s_lower = linalg.svds(M, 1, tol=.01, which = 'SM', maxiter= 2000, + return_singular_vectors=False) + return s_upper ** 2 - 1, 1 -s_lower ** 2 + + +def test(): + """ + unit test + """ + G = cascade_creation.InfluenceGraph(max_proba=.3) + G.erdos_init(n=10, p =1) + cascades = cascade_creation.generate_cascades(G, p_init=.3, n_cascades=10) + M, __ = cascade_creation.icc_matrixvector_for_node(cascades, None) + M = cascade_creation.normalize_matrix(M) + print find_kth_rip_constants(M, 5) + + +if __name__=="__main__": + test() |
