Beispiel #1
0
 def zero_eig(result):
   """ Qff and Qaa cannot be singular. """
   from dcprogs.likelihood import svd
   from numpy import all, any, abs
   try: singular = svd(result.aa)[1]
   except: return False
   if any(abs(singular) < 1e-8): return False
   try: singular = svd(result.ff)[1]
   except: return False
   return all(abs(singular) > 1e-8)
Beispiel #2
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 def zero_eig(result):
     """ Qff and Qaa cannot be singular. """
     from dcprogs.likelihood import svd
     from numpy import all, any, abs
     try:
         singular = svd(result.aa)[1]
     except:
         return False
     if any(abs(singular) < 1e-8): return False
     try:
         singular = svd(result.ff)[1]
     except:
         return False
     return all(abs(singular) > 1e-8)
Beispiel #3
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 def zero_eig(result):
     from dcprogs.likelihood import svd
     from numpy import sum, abs
     try:
         U, sing, V = svd(result)
     except:
         return False
     else:
         return sum(abs(sing) < tolerance) == 1
Beispiel #4
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def step(context):
  from dcprogs.likelihood import inv, svd
  from numpy import abs, all, dot, identity
  for matrix, idealg in zip(context.qmatrices, context.idealgs):
    occupancies = idealg.final_occupancies
    kernel = dot( dot(inv(matrix.ff), matrix.fa), dot(inv(matrix.aa), matrix.af) )
    kernel = identity(kernel.shape[0]) - kernel
    U, singvals, V = svd(kernel)

    try:
      assert sum(abs(singvals) < context.tolerance) == 1
      assert all(dot(occupancies, kernel) < context.tolerance)
    except:
      print(matrix)
      print("Equilibrium: {0}".format(occupancies))
      print("Kernel Application: {0}".format(dot(occupancies, kernel)))
      raise
Beispiel #5
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def step(context):
    from dcprogs.likelihood import inv, svd
    from numpy import abs, all, dot, identity
    for matrix, idealg in zip(context.qmatrices, context.idealgs):
        occupancies = idealg.final_occupancies
        kernel = dot(dot(inv(matrix.ff), matrix.fa),
                     dot(inv(matrix.aa), matrix.af))
        kernel = identity(kernel.shape[0]) - kernel
        U, singvals, V = svd(kernel)

        try:
            assert sum(abs(singvals) < context.tolerance) == 1
            assert all(dot(occupancies, kernel) < context.tolerance)
        except:
            print(matrix)
            print("Equilibrium: {0}".format(occupancies))
            print("Kernel Application: {0}".format(dot(occupancies, kernel)))
            raise
Beispiel #6
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def step(context, name):
  from dcprogs.likelihood import svd
  from numpy import dot, identity, abs, all
  for qmatrix, G, occ in zip(context.qmatrices, context.likelihoods, context.occupancies):
    eqmatrix = dot(G.laplace_af(0), G.laplace_fa(0)) if name == "initial"                         \
               else dot(G.laplace_fa(0), G.laplace_af(0))
    eqmatrix -= identity(eqmatrix.shape[0])

    left, sings, right = svd(eqmatrix)
    sings = sorted(sings)

    try:
      assert abs(sings[0]) < context.tolerance
      assert sings[0] < sings[1] + context.tolerance
      assert all(abs(dot(occ,  eqmatrix)) < context.tolerance)
    except: 
      print(G)
      print(" * occupancies: {0}".format(occ))
      print(" * matrix:\n{0}".format(eqmatrix))
      print(" * error: {0}".format(dot(occ, eqmatrix)))
      print(" * singular values: {0}".format(sings))
      raise
Beispiel #7
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def step(context, name):
    from dcprogs.likelihood import svd
    from numpy import dot, identity, abs, all
    for qmatrix, G, occ in zip(context.qmatrices, context.likelihoods,
                               context.occupancies):
        eqmatrix = dot(G.laplace_af(0), G.laplace_fa(0)) if name == "initial"                         \
                   else dot(G.laplace_fa(0), G.laplace_af(0))
        eqmatrix -= identity(eqmatrix.shape[0])

        left, sings, right = svd(eqmatrix)
        sings = sorted(sings)

        try:
            assert abs(sings[0]) < context.tolerance
            assert sings[0] < sings[1] + context.tolerance
            assert all(abs(dot(occ, eqmatrix)) < context.tolerance)
        except:
            print(G)
            print(" * occupancies: {0}".format(occ))
            print(" * matrix:\n{0}".format(eqmatrix))
            print(" * error: {0}".format(dot(occ, eqmatrix)))
            print(" * singular values: {0}".format(sings))
            raise
Beispiel #8
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 def zero_eig(result): 
   from dcprogs.likelihood import svd
   from numpy import sum, abs
   try: U, sing, V = svd(result)
   except: return False
   else: return sum(abs(sing) < tolerance) == 1