use uniform colormap in the plots and use separate output folder for the plots

benchmarks/benchmark-plotters/plot-cost-mtsubmit.py

@@ -81,11 +81,12 @@ def process_file_to_dataset(file_path, engine_label, thread_count):
 # process_file_to_dataset for them in order to build a dataframe
 # which is then displayed and saved
 def main():
-    folder_path = "benchmark-results/"
+    result_path = "benchmark-results/"
+    output_path = "benchmark-plots/"
 
     for engine_label in engine_counts:
         for thread_count in thread_counts:
-            file = os.path.join(folder_path, f"mtsubmit-{thread_count}-{engine_label}.json")
+            file = os.path.join(result_path, f"mtsubmit-{thread_count}-{engine_label}.json")
             process_file_to_dataset(file, engine_label, thread_count)
 
     df = pd.DataFrame(data)
@@ -94,7 +95,7 @@ def main():
     sns.barplot(x=x_label, y=y_label, hue=var_label, data=df, palette="rocket", errorbar="sd")
 
     plt.title(title)
-    plt.savefig(os.path.join(folder_path, "plot-perf-mtsubmit.png"), bbox_inches='tight')
+    plt.savefig(os.path.join(output_path, "plot-perf-mtsubmit.png"), bbox_inches='tight')
     plt.show()
 
 

benchmarks/benchmark-plotters/plot-perf-enginelocation.py

@@ -90,11 +90,12 @@ def create_copy_dataset(file_path, method_label, type_label):
 # process_file_to_dataset for them in order to build a dataframe
 # which is then displayed and saved
 def main():
-    folder_path = "benchmark-results/"
+    result_path = "benchmark-results/"
+    output_path = "benchmark-plots/"
 
     for method_label in copy_methods:
         for type_label in types:
-            file = os.path.join(folder_path, f"{method_label}-{type_label}-1e.json")
+            file = os.path.join(result_path, f"{method_label}-{type_label}-1e.json")
             create_copy_dataset(file, method_label, type_label)
 
     df = pd.DataFrame(data)
@@ -104,7 +105,7 @@ def main():
     sns.barplot(x=x_label, y=y_label, hue=var_label, data=df, palette="rocket", errorbar="sd")
 
     plt.title(title)
-    plt.savefig(os.path.join(folder_path, "plot-perf-enginelocation.png"), bbox_inches='tight')
+    plt.savefig(os.path.join(output_path, "plot-perf-enginelocation.png"), bbox_inches='tight')
     plt.show()
 
 if __name__ == "__main__":

benchmarks/benchmark-plotters/plot-perf-peakthroughput.py

@@ -7,7 +7,8 @@ import matplotlib.pyplot as plt
 
 from common import calc_throughput
 
-folder_path = "benchmark-results/"
+result_path = "benchmark-results/"
+output_path = "benchmark-plots/"
 
 runid = "Run ID"
 x_label = "Destination Node"
@@ -75,10 +76,10 @@ def process_file_to_dataset(file_path, src_node, dst_node):
 def plot_heatmap(table,title,node_config):
     plt.figure(figsize=(8, 6))
 
-    sns.heatmap(table, annot=True, cmap="YlGn", fmt=".0f")
+    sns.heatmap(table, annot=True, cmap="rocket_r", fmt=".0f")
 
     plt.title(title)
-    plt.savefig(os.path.join(folder_path, f"plot-perf-{node_config}-throughput.png"), bbox_inches='tight')
+    plt.savefig(os.path.join(output_path, f"plot-perf-{node_config}-throughput.png"), bbox_inches='tight')
     plt.show()
 
 
@@ -89,7 +90,7 @@ def main(node_config,title):
     for src_node in range(16):
         for dst_node in range(16):
             size = "512mib" if node_config == "allnodes" and src_node == dst_node and src_node >= 8 else "1gib" 
-            file = os.path.join(folder_path, f"copy-n{src_node}ton{dst_node}-{size}-{node_config}-1e.json")
+            file = os.path.join(result_path, f"copy-n{src_node}ton{dst_node}-{size}-{node_config}-1e.json")
             process_file_to_dataset(file, src_node, dst_node)
 
     df = pd.DataFrame(data)

benchmarks/benchmark-plotters/plot-perf-submitmethod.py

@@ -87,11 +87,12 @@ def process_file_to_dataset(file_path, type_label,size_label):
 # process_file_to_dataset for them in order to build a dataframe
 # which is then displayed and saved
 def main():
-    folder_path = "benchmark-results/"
+    result_path = "benchmark-results/"
+    output_path = "benchmark-plots/"
 
     for type_label in types:
         for size in sizes:
-            file = os.path.join(folder_path, f"submit-{type_label}-{size}-1e.json")
+            file = os.path.join(result_path, f"submit-{type_label}-{size}-1e.json")
             process_file_to_dataset(file, type_label, size)
 
     df = pd.DataFrame(data)
@@ -101,7 +102,7 @@ def main():
     sns.barplot(x=x_label, y=y_label, hue=var_label, data=df, palette="rocket", errorbar="sd")
     
     plt.title(title)
-    plt.savefig(os.path.join(folder_path, "plot-opt-submitmethod.png"), bbox_inches='tight')
+    plt.savefig(os.path.join(output_path, "plot-opt-submitmethod.png"), bbox_inches='tight')
     plt.show()
 
 if __name__ == "__main__":