coniii.enumerate module

coniii.enumerate.fast_logsumexp(X, coeffs=None)

Simplified version of logsumexp to do correlation calculation in Ising equation files. Scipy’s logsumexp can be around 10x slower in comparison.

X : ndarray

Terms inside logs.

coeffs : ndarray

Factors in front of exponentials.

float

Value of magnitude of quantity inside log (the sum of exponentials).

float

Sign.

coniii.enumerate.get_3idx(n)

Get binary 3D matrix with truth values where index values correspond to the index of all possible ijk parameters. We can do this by recognizing that the pattern along each plane in the third dimension is like the upper triangle pattern that just moves up and over by one block each cut lower into the box.

coniii.enumerate.get_nidx(k, n)

Get the kth order indices corresponding to all the states in which k elements are firing up out of n spins. The ordering correspond to that returned by bin_states().

print where(exact.get_3idx(4)) print where(exact.get_nidx(3,4)) <<<<<

coniii.enumerate.get_terms(subix, prefix, binstate, br, ix0)

Spins are put in explicitly

coniii.enumerate.get_terms01(subix, prefix, binstate, br, ix0)

Specific to {0,1}.

coniii.enumerate.get_terms11(subix, prefix, binstate, br, ix0)

Specific to {-1,1}.

coniii.enumerate.mp_fast_logsumexp(X, coeffs=None)

fast_logsumexp for high precision numbers using mpmath.

X : ndarray

Terms inside logs.

coeffs : ndarray

Factors in front of exponentials.

float

Value of magnitude of quantity inside log (the sum of exponentials).

float

Sign.

coniii.enumerate.pairwise(n, sym=0, **kwargs)

Wrapper for writing pairwise maxent model (Ising) files.

n : int

System size.

sym : int, 0

Can be 0 or 1.

**kwargs

None

coniii.enumerate.triplet(n, sym=0, **kwargs)

Wrapper for writing triplet-order maxent model.

n : int

System size.

sym : int, 0

Can be 0 or 1.

**kwargs

None

coniii.enumerate.write_eqns(n, sym, corrTermsIx, suffix='', high_prec=False)

Create strings for writing out the equations and then write them to file.

TODO: This code needs some cleanup.

n : int

number of spins

sym : int

value of 1 will use {-1,1} formulation, 0 means {0,1}

corrTermsIx : list of ndarrays

Allows specification of arbitrary correlations to constrain using an index based structure. These should be index arrays as would be returned by np.where that specify which correlations to write down. Each consecutive array should specify a matrix of sequentially increasing dimension. [Nx1, NxN, NxNxN, …]

suffix : str, ‘’ high_prec : bool, False

coniii.enumerate.write_py(n, sym, contraintTermsIx, signs, expterms, Z, extra='', suffix='', high_prec=False)

Write out Ising equations for Python.

n : int

System size.

contraintTermsIx : list of str signs : list of ndarray

Sign for each term in the numerator when computing correlations.

expterms : list of str

Every single energy term.

Z : str

Energies for all states that will be put into partition function.

extra : str, ‘’

any extra lines to add at the end

suffix : str, ‘’ high_prec : bool, False

If True, write version that uses mpmath for high precision calculations.