latqcdtools.physics.referenceScales
=============

`_betaRangeWarn(beta, beta_range)`
 
    Many of these ansätze a(beta) have coefficients that were determined by performing a fit within a certain
    beta range. This warning flashes whenever you are using information outside of that range, where the ansatz
    is less likely be to reliable.

    Args:
        beta (float) or numpy array
        beta_range (array-like): min and max beta of range, in that order 
    
`a_div_r1(beta, year)`
 
    Get a/r_1(beta).

    Args:
        beta (float)
        year (int/str): year that parameterization was determined 

    Returns:
        float: a/r_1
    
`a_times_fk(beta, year)`
 
    Get a*f_k(beta).

    Args:
        beta (float)
        year (int/str): year that parameterization was determined 

    Returns:
        float: a*f_k 
    
`a_times_ms_2014(beta)`


`allton_type_ansatz(beta, c0, c2, d2)`


`fit_2014Eos_eqB2(beta, c0, c2, d2)`


`fit_tayloraLambda(beta, a, b, c)`


`ignoreBetaRange()`
 
    Turn off the beta range warnings. 
    
`r0_div_a(beta, year)`
 
    Get r0/a(beta).

    Args:
        beta (float)
        year (int/str): year that parameterization was determined 

    Returns:
        float: r0/a 
    
`r1_times_ms_2014(beta)`


`sqrtt0_div_a(beta)`
 
    Get sqrt(t0/a)(beta)

    Args:
        beta (float)

    Returns:
        float: sqrt(t0/a) 
    
`wuppertal_type_ansatz(beta, c1, c2, c3, c4)`