Testing bimodality of data I am trying to see if my data is multimodal (in fact, I am more interested in bimodality of the data). I performed dip test and it does evidence against unmodal data. However, I want to see, in particular, if it is bimodal. I believe silver man's test can be used. However, I couldn't find the implementation of it in either r or in python. (The one in R is old and not working with the current version of R). 
Also, assuming that I have a bimodal data and that I am able to get the two components (using mixtools in R), how do I figure out how to find the point of intersection of the two components. For example, here is the histogram (overlaid with its density estimation) of the entire data. 

Here are the two components: 

I want to get the the x value where the curves intersected. I could have uploaded the data, but the length of the vector is rather long. Any general thought and idea is welcome including the R and/or Python packages are welcome.

Thanks
There has been an answer on this question, please check it : 

Test for bimodal distribution