Feature/issue 970 mix fun

#### Summary:

Addresses issue #970, with the addition of the binary mixture function

#### Intended Effect:

* Adds a function, log_mix, to simplify the binary mixture model syntax
* fvar version
* var version
* exposed log_mix to parser 

#### How to Verify:

* src/test/unit/agrad/fwd/functions/log_mix_test.cpp
* src/test/unit/agrad/rev/functions/log_mix_test.cpp 
* src/test/unit/gm/parser/math_functions_test.cpp 

The last test will have 83 function signature tests compared to the 82 in develop.

Furthermore, the following model will run correctly in this branch:

```
data {
  int<lower = 0> N;
  vector[N] y;
}
parameters {
  real<lower = 0, upper = 1> theta;
  vector<lower = 0>[2] sigmas;
  vector[2] means;
}
model {
  theta ~ beta(6,4);
  
  sigmas ~ normal(1,2);

  means[1] ~ normal(10,1);
  means[2] ~ normal(-1,1);

  
  for(i in 1:N)
    increment_log_prob(log_mix(theta,normal_log(y[i],means[1],sigmas[1]),
                              normal_log(y[i],means[2],sigmas[2])));
}
``` 

Given this data from R:

```
set.seed(12345)

N <- 1000
dist_1 <- rnorm(N,mean = 10,sd = 1)
dist_2 <- rnorm(N,mean = -1,sd = 2)

theta <- 0.6

indicator <- rbinom(N,size = 1,prob = theta)
y <- indicator * dist_1 + (1 - indicator) * dist_2


stan_rdump(c('N','y'),file = 'normal_mixture_data.Rdat')
```

#### Side Effects:

None.

#### Documentation:

To-do: Add documentation for the log_mix function

#### Reviewer Suggestions:

Anyone
same problem with math (sorry if this was me introducing the problem originally)