diff --git a/bilby/core/sampler/ptemcee.py b/bilby/core/sampler/ptemcee.py
index 5aa4ca2c012fa51ff234ca6c570a7e130d17b46e..67c91f5beb14508fc5e1e45fcfcc23b42e91b78a 100644
--- a/bilby/core/sampler/ptemcee.py
+++ b/bilby/core/sampler/ptemcee.py
@@ -45,11 +45,12 @@ class Ptemcee(MCMCSampler):
         swap_ratios=False)
 
     def __init__(self, likelihood, priors, outdir='outdir', label='label',
-                 use_ratio=False, plot=False, skip_import_verification=False,
+                 use_ratio=False, check_point_plot=True, skip_import_verification=False,
                  resume=True, nsamples=5000, burn_in_nact=50, thin_by_nact=1,
                  autocorr_c=5, safety=1, frac_threshold=0.01,
                  autocorr_tol=50, min_tau=1, check_point_deltaT=600, 
-                 threads=1, exit_code=77, store_walkers=False, **kwargs):
+                 threads=1, exit_code=77, plot=False, store_walkers=False,
+                 **kwargs):
         super(Ptemcee, self).__init__(
             likelihood=likelihood, priors=priors, outdir=outdir,
             label=label, use_ratio=use_ratio, plot=plot,
@@ -73,6 +74,7 @@ class Ptemcee(MCMCSampler):
         self.threads = threads
         self.store_walkers = store_walkers
 
+        self.check_point_plot = check_point_plot
         self.resume_file = "{}/{}_checkpoint_resume.pickle".format(self.outdir, self.label)
         self.exit_code = exit_code
 
@@ -243,7 +245,7 @@ class Ptemcee(MCMCSampler):
                 last_checkpoint_s = np.sum(self.time_per_check)
 
             if last_checkpoint_s > self.check_point_deltaT:
-                self.write_current_state(plot=self.plot)
+                self.write_current_state(plot=self.check_point_plot)
 
         # Check if we reached the end without converging
         if sampler.time == self.sampler_function_kwargs["iterations"]:
@@ -254,7 +256,7 @@ class Ptemcee(MCMCSampler):
             )
 
         # Run a final checkpoint to update the plots and samples
-        self.write_current_state(plot=self.plot)
+        self.write_current_state(plot=self.check_point_plot)
 
         # Get 0-likelihood samples and store in the result
         samples = sampler.chain[0, :, :, :]  # nwalkers, nsteps, ndim