some output formating

mOTUlizer/bin/anvi-script-compute-bayesian-pan-core

@@ -136,6 +136,10 @@ def main(args):
 
     if args.num_bootstraps :
         motu.roc_values(boots=args.num_bootstraps)
+        rocs = motu.roc_values(0)
+        run.warning("You ran the bootstrap option for the pangenome predition, if you have no output file the results are only shown here :", lc = "gray")
+        for k,v in rocs.items() :
+            run.info(k,"{:.2f}".format(v) if k != 'nb_bootstraps' else v, lc = "gray")
 
     if args.store_in_db:
         data2add = {g: {'Gene_cluster_type' : 'CORE' if g in motu.core else 'ACCESSORY', 'Gene_cluster_type_LLR' : motu.likelies[g]} for g in pan.gene_cluster_names}
@@ -147,8 +151,6 @@ def main(args):
             print(motu.pretty_pan_table(), file = handle)
         run.info("Output file", args.output_file, mc="green", nl_before=1)
 
-    if args.num_bootstraps > 0:
-        print(motu.roc_values(0))
 
 
 if __name__ == '__main__':

mOTUlizer/classes/MockData.py

@@ -8,7 +8,7 @@
 
 class MockmOTU(mOTU):
     def __repr__(self) :
-        return "< MockmOTU with {n} genomes, of average {c}% completness, with core/genome_len of {r} >".format(c = 100*self.mean_completeness, n = len(self), r = self.ratio)
+        return "< MockmOTU with {n} genomes, of average {c}% completness>".format(c = 100*self.mean_completeness, n = len(self))
 
     def __init__(self, name, core_len, nb_genomes, completeness, max_it = 20, accessory = None, method = None):
 

mOTUlizer/classes/mOTU.py

@@ -242,8 +242,13 @@ def __core_likelyhood(self, max_it = 20, likeli_cutof = 0 ):
                 core_len = new_core_len
 
         if not self.quiet:
-            json.dump({ self.name : {"nb_mags" : len(self), "core_len" : core_len, "mean_starting_completeness" :  mean([b.checkm_complet for b in self]), "mean_new_completness" : mean([b.new_completness for b in self]), "LHR"  :  sum([l if l > 0 else -l for l in likelies.values()]), "mean_est_binsize" : mean([100*len(b.gene_clusterss)/b.new_completness for b in self])}}, sys.stderr )
-            print(file = sys.stderr)
+            pp =  "\nYour {name}-run for {nb_mags} genomes (with mean initial completeness {mean_start:.2f}) resulted\n"
+            pp += "in a core of {core_len} traits with a total sum of loglikelihood-ratios {llhr:.2f} and a corrected \n"
+            pp += "mean completness of {mean_new:.2f}, resulting to a estimated mean traits per genome count of {trait_count:.2f}\n"
+            pp = pp.format(name = self.name, nb_mags = len(self), core_len = core_len, mean_start = mean([b.checkm_complet for b in self]),
+                        mean_new =  mean([b.new_completness for b in self]), llhr =  sum([l if l > 0 else -l for l in likelies.values()]),
+                        trait_count = mean([100*len(b.gene_clusterss)/b.new_completness for b in self]))
+            print(pp, file = sys.stderr)
         self.iterations = i -1
         return likelies