adding kwargs to find_time_regions for large timeseries which break t…

…he classic plotting

MonoTools/fit.py

@@ -2516,7 +2516,7 @@ def Table(self):
                                        savefileloc=None, tracemask=tracemask)
         '''
 
-    def init_gp_to_plot(self, n_samp=7, max_gp_len=12000, interp=True, newgp=False, overwrite=False):
+    def init_gp_to_plot(self, n_samp=7, max_gp_len=12000, interp=True, newgp=False, overwrite=False,**kwargs):
         """Initialise the GP model for plotting.
 
             As it is memory-intensive to store predicted GP samples for each datapoint in the light curve during sampling, 
@@ -2542,7 +2542,7 @@ def init_gp_to_plot(self, n_samp=7, max_gp_len=12000, interp=True, newgp=False,
         elif interp:
             from scipy import interpolate
         if not hasattr(self,'lc_regions'):
-            self.init_plot(plot_type='lc')
+            self.init_plot(plot_type='lc',**kwargs)
         gp_pred=[]
         gp_sd=[]
         self.gp_to_plot={'n_samp':n_samp}
@@ -2678,7 +2678,7 @@ def init_gp_to_plot(self, n_samp=7, max_gp_len=12000, interp=True, newgp=False,
                 self.gp_to_plot['gp_pred']=np.hstack(gp_pred)
                 self.gp_to_plot['gp_sd']=np.hstack(gp_sd)
 
-    def init_trans_to_plot(self,n_samp=None):
+    def init_trans_to_plot(self,n_samp=None,**kwargs):
         """Initialising the transit models to plot
            
         The result is the `trans_to_plot` array, which is a dictionary of predicted transit flux model percentiles computed for each point in the time series.
@@ -2689,7 +2689,7 @@ def init_trans_to_plot(self,n_samp=None):
         n_samp=len(self.trace['phot_mean']) if n_samp is None else n_samp
         print("Initalising Transit models for plotting with n_samp=",n_samp)
         if not hasattr(self,'lc_regions'):
-            self.init_plot(plot_type='lc')
+            self.init_plot(plot_type='lc',**kwargs)
         self.trans_to_plot={'model':{'allpl':{}},
                             'all':{'allpl':{}},
                             'n_samp':n_samp}
@@ -2921,7 +2921,7 @@ def init_rvs_to_plot(self, n_samp=300, plot_alias='all'):
             self.rvs_to_plot['x']["trend+offset"] = {'med':self.init_soln["rv_trend"]}
             self.rvs_to_plot['x']["offsets"] = {'med':self.init_soln["rv_offsets"]}
 
-    def init_plot(self, interactive=False, gap_thresh=10, plottype='lc',pointcol='k',palette=None, ncols=None, plot_flat=False):
+    def init_plot(self, interactive=False, gap_thresh=10, plottype='lc',pointcol='k',palette=None, ncols=None, plot_flat=False,**kwargs):
         """Initialising plotting
 
         Args:
@@ -2959,7 +2959,7 @@ def init_plot(self, interactive=False, gap_thresh=10, plottype='lc',pointcol='k'
             else:
                 fx_lab='flux'
                 fx_bin_lab='bin_flux'
-            time_regions=tools.find_time_regions(self.lc.time[self.lc.mask])
+            time_regions=tools.find_time_regions(self.lc.time[self.lc.mask],**kwargs)
             self.lc_regions={}
             for nj in range(len(time_regions)):
                 self.lc_regions[nj]={'start':time_regions[nj][0],'end':time_regions[nj][1]}
@@ -3005,7 +3005,7 @@ def init_plot(self, interactive=False, gap_thresh=10, plottype='lc',pointcol='k'
 
 
     def PlotRVs(self, interactive=False, plot_alias='best', nbest=4, n_samp=300, overwrite=False, return_fig=False, plot_resids=False,
-                plot_loc=None, palette=None, pointcol='k', plottype='png',raster=False, nmargtoplot=0, save=True):
+                plot_loc=None, palette=None, pointcol='k', plottype='png',raster=False, nmargtoplot=0, save=True,**kwargs):
         """Varied plotting function for RVs of MonoTransit model
 
         Args:
@@ -3035,7 +3035,7 @@ def PlotRVs(self, interactive=False, plot_alias='best', nbest=4, n_samp=300, ove
 
         # plot_alias - can be 'all' or 'best'. All will plot all aliases. Best will assume the highest logprob.
         ncol=3+2*np.max(list(self.n_margs.values())) if plot_alias=='all' else 3+2*nbest
-        self.init_plot(plottype='rv', pointcol=pointcol, ncols=ncol)
+        self.init_plot(plottype='rv', pointcol=pointcol, ncols=ncol,**kwargs)
 
         if not hasattr(self,'rvs_to_plot') or n_samp!=self.rvs_to_plot['n_samp'] or overwrite:
             self.init_rvs_to_plot(n_samp, plot_alias)