Add files via upload

src/main.py

@@ -77,9 +77,9 @@ def add_vals_to_dict(name_tool, max_comp, max_decomp, avg_num_bytes):
 
 		new_val_max_comp = max(infos[0], max_comp)
 		new_val_max_decomp = max(infos[1], max_decomp)
-		new_avg_num_bytes = infos[2] + avg_num_bytes
+		new_num_bytes = infos[2] + avg_num_bytes
 
-		info_tools[name_tool] = [new_val_max_comp, new_val_max_decomp, new_avg_num_bytes]
+		info_tools[name_tool] = [new_val_max_comp, new_val_max_decomp, new_num_bytes]
 
 
 def update_vars(max_comp, max_decomp, num_bytes, time, count, list_vals):
@@ -162,12 +162,12 @@ def import_files_in_dir(path):
 		shutil.move("tables_results_" + file_name + ".tsv", path + "/tables_results_" + file_name + ".tsv")
 
 	file_results = open("plot_data_mem_comp_size.tsv", "w")
-	file_results.write("Name tool\tMax_comp_mem\tMax_decomp_mem\tAverage_bytes\n")
+	file_results.write("Name tool\tMax_comp_mem\tMax_decomp_mem\tSum_of_avg_comp_size\n")
 
 	#Get the max compression and decompression memory and the average compression size for each tool (all datasets)
 	for i in info_tools.keys():
 		infos = info_tools[i]
-		file_results.write(i + "\t" + str(infos[0]) + "\t" + str(infos[1]) + "\t" + str(infos[2]) + "\n")
+		file_results.write(i + "\t" + str(infos[0]) + "\t" + str(infos[1]) + "\t" + str(round(infos[2],3)) + "\n")
 
 	file_results.close()
 
@@ -206,9 +206,6 @@ def check_correlations():
 
 	import_files_in_dir(directory_path) #calculates the basic metrics
 
-	'''for i in range(1,11):
-
-		calc_weissman(directory_path, tool_weissman, i/10)'''
 	calc_weissman(directory_path, tool_weissman, 1)
 
 	if not os.path.exists(directory_path + "/final_tsv"):

src/main_best_weissman.py

@@ -73,30 +73,28 @@ def calc_weissman(standard_tool, alpha):
 		# For all tools, do calculations and write to file
 		for i in file_content:
 
-			if first_line == False:
-				values = i.split("\n")[0].split("\t")
+			values = i.split("\n")[0].split("\t")
+
+			name_tool = values[0]
+			compressed_size_tool = float(values[1])
+			time_tool = float(values[2]) * 60 # Convert to seconds (to avoid log(>1))
 
-				name_tool = values[0]
-				compressed_size_tool = float(values[1])
-				time_tool = float(values[2]) * 60 # Convert to seconds (to avoid log(>1))
+			compression_ratio = uncompressed_size / compressed_size_tool
+			compression_ratio_standard = uncompressed_size / number_bytes_standard
 
-				compression_ratio = uncompressed_size / compressed_size_tool
-				compression_ratio_standard = uncompressed_size / number_bytes_standard
+			weissman_score = alpha * (compression_ratio / compression_ratio_standard) * (math.log10(time_standard) / math.log10(time_tool))
 
-				weissman_score = alpha * (compression_ratio / compression_ratio_standard) * (math.log10(time_standard) / math.log10(time_tool))
+			# "File\tName tool\tWeissman score\tCompression ratio\tCompressed size\tTime\tSize uncompressed file\tTime ratio(time_standard/time_tool)\n"
+			file_res.write(file + "\t" + name_tool + "\t" + str(round(weissman_score, num_cases)) + "\t" + str(
+				round(compression_ratio, num_cases)) + "\t" + str(
+				round(compressed_size_tool, num_cases)) + "\t" + str(round(time_tool, num_cases)) + "\t" + str(
+				round(uncompressed_size, num_cases)) + "\t" + str(
+				round(time_standard / time_tool, num_cases)) + "\n")
 
-				# "File\tName tool\tWeissman score\tCompression ratio\tCompressed size\tTime\tSize uncompressed file\tTime ratio(time_standard/time_tool)\n"
-				file_res.write(file + "\t" + name_tool + "\t" + str(round(weissman_score, num_cases)) + "\t" + str(
-					round(compression_ratio, num_cases)) + "\t" + str(
-					round(compressed_size_tool, num_cases)) + "\t" + str(round(time_tool, num_cases)) + "\t" + str(
-					round(uncompressed_size, num_cases)) + "\t" + str(
-					round(time_standard / time_tool, num_cases)) + "\n")
+			#Get best values
+			update_best_val_dictionary(file, name_tool, weissman_score, compression_ratio)
 
-				#Get best values
-				update_best_val_dictionary(file, name_tool, weissman_score, compression_ratio)
 
-			else:
-				first_line = False
 
 	file_results = open("best_weissman_comp_ratios.tsv", "w")
 	file_results.write("File\tName tool\tBest weissman score\tBest compression ratio\n")