plotting figure from saved traces in pymc
mcmc, pickle, plot, pymc, python
Solution
You can't just pass a database backend to the plot function. You can either pass (1) the original node/stochastic (2) a trace object (3) a dictionary of pymc nodes/stochastics or (4) raw output.
Problem
I need to run MCMC different times with different parameters to check the convergence. So I decided to save the traces so that when I need to know (for comaprison purposes) what was the result of `pymc.MCMC (iter = 10000, burn = 1000, thin = 10)` I don't need to rerun it. (It takes a lot of time (I have to do the same for many different values of parameters)). I found out a solution ``` m = MCMC([tau, rv], db='pickle', dbname='10000iter1000burn.pickle') m.sample(iter = 10000, burn = 5000, thin = 10) m.db.close() ``` So the trace is saved now in a database named 10000iter1000burn.pickle Now, to load teh trace, I do the following ``` db = pymc.database.pickle.load('10000iter5000burn.pickle') ``` and when I perform `print db.trace('tau')[:]` I get the same output, but when I want tp plot the figure or get other information, it fails ``` plot(db) #error ``` plot() takes at least 2 arguments (1 given) but when I do plot(m) (initial case when I have run the sampler again), it works fine. Similarly `db.tau.summary()` gives error 'Trace' object has no attribute 'summary' It works fine when I do `m.tau.summary()` Same is true for `db.logp` I am a novice in this field. Kindly correct me if there is any mistake somewhere in the syntax. If there is some other way that I can replot the figure and get log-probability of the model without running mcmc again, I will be happy to know.