renaming directory + creating dataset directory

1 files changed, 0 insertions, 49 deletions

diff --git a/jpa_test/rip_condition.py b/jpa_test/rip_condition.py
deleted file mode 100644
index fccf9a4..0000000
--- a/jpa_test/rip_condition.py
+++ /dev/null
@@ -1,49 +0,0 @@
-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()