Figure Save Option

docs/source/how-to-run.rst

@@ -135,6 +135,10 @@ Probability value that is used for z-score calculation. It is a determination pe
 
 Plotting option for debugging. While enabled, DomHMM will print Hidden Markov model iterations result, prediction results, Getis-Ord statistic results and clustering result of three frame.
 
+* ``save_plots``
+
+Option for saving result plots in pdf format.
+
 * ``verbose``
 
 Verbose option for debugging. Although, DomHMM doesn't print middle values, it shows which steps are done and shows middle step plots which may give clues about succession of model.

domhmm/analysis/base.py

@@ -70,6 +70,8 @@ class LeafletAnalysisBase(AnalysisBase):
         Debug option to print step progress, warnings and errors
     result_plots: bool
         Plotting intermediate result option
+    save_plots : bool
+        Option for saving intermediate plots in pdf format
     trained_hmms: dict
         User-specific HMM (e.g., pre-trained on another simulation)
 
@@ -120,6 +122,7 @@ def __init__(
             result_plots: bool = False,
             trained_hmms: Dict[str, Any] = {},
             n_init_hmm: int = 2,
+            save_plots: bool = False,
             **kwargs
     ):
         # the below line must be kept to initialize the AnalysisBase class!
@@ -147,6 +150,7 @@ def __init__(
         self.result_plots = result_plots
         self.tmd_protein = None
         self.n_init_hmm = n_init_hmm
+        self.save_plots = save_plots
 
         assert heads.keys() == tails.keys(), "Heads and tails don't contain same residue names"
 

domhmm/analysis/domhmm.py

@@ -648,8 +648,8 @@ def plot_hmm_result(self):
         plt.text(s="Tolerance 1e-4", x=1, y=1E-4 + 0.00005, color="k", fontsize=15)
         plt.title("a", fontsize=20, fontweight="bold", loc="left")
         plt.tight_layout()
-        # TODO Add plot save option to here
-        # plt.savefig("a.pdf")
+        if self.save_plots:
+            plt.savefig("a.pdf")
         plt.show()
 
     def predict_states(self):
@@ -798,8 +798,8 @@ def predict_plot(self):
         plt.xlim(8, 10)
         plt.title("b", fontsize=20, fontweight="bold", loc="left")
         plt.tight_layout()
-        # TODO Add plot save option to here
-        # plt.savefig("b.pdf")
+        if self.save_plots:
+            plt.savefig("b.pdf")
         plt.show()
 
     # ------------------------------ GETIS-ORD STATISTIC ------------------------------------------------------------- #
@@ -928,8 +928,8 @@ def getis_ord_plot(self):
 
         plt.title("c", fontsize=20, fontweight="bold", loc="left")
         plt.tight_layout()
-        # TODO Add plot save option to here
-        # plt.savefig("c.pdf")
+        if self.save_plots:
+            plt.savefig("c.pdf")
         plt.show()
 
     def permut_getis_ord_stat(self, weight_matrix_all, leaflet):
@@ -1095,8 +1095,8 @@ def clustering_plot(self):
         ax[1].text(s=f"Frame {self.start + frame_list[1]}", x=71.5, y=144, fontsize=18, ha="center", va="center")
         ax[2].text(s=f"Frame {self.start + frame_list[2]}", x=71.5, y=144, fontsize=18, ha="center", va="center")
         plt.tight_layout()
-        # TODO Add plot save option to here
-        # plt.savefig("d.pdf")
+        if self.save_plots:
+            plt.savefig("d.pdf")
         plt.show()
 
     def result_clustering(self):