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

```Python
_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 
'''
```
```Python
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
'''
```
```Python
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 
'''
```
```Python
a_times_ms_2014(beta):
'''
'''
```
```Python
allton_type_ansatz(beta, c0, c2, d2):
'''
'''
```
```Python
fit_2014Eos_eqB2(beta, c0, c2, d2):
'''
'''
```
```Python
fit_tayloraLambda(beta, a, b, c):
'''
'''
```
```Python
ignoreBetaRange():
'''
Turn off the beta range warnings. 
'''
```
```Python
r0_div_a(beta, year):
'''
Get r0/a(beta).

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

Returns:
    float: r0/a 
'''
```
```Python
r1_times_ms_2014(beta):
'''
'''
```
```Python
sqrtt0_div_a(beta):
'''
Get sqrt(t0/a)(beta)

Args:
    beta (float)

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