Commit 4916083c authored by Brewer, Wes's avatar Brewer, Wes
Browse files

Update telemetry analysis histogram plot feature (-m raps.telemetry -p)

parent ed131292

raps/telemetry.py

+16 −11
Original line number Diff line number Diff line
@@ -72,6 +72,7 @@ if __name__ == "__main__": 
    dt_list = []

    wt_list = []

    nr_list = []

    submit_times = []

    last = 0

    for job_vector in jobs:

        job = Job(job_vector, 0)
@@ -81,6 +82,7 @@ if __name__ == "__main__": 
            dt = job.submit_time - last

            dt_list.append(dt)

            last = job.submit_time

            submit_times.append(job.submit_time)

        if args.verbose: print(job)



    print(f'Simulation will run for {timesteps} seconds')
@@ -95,6 +97,7 @@ if __name__ == "__main__": 


        import matplotlib.pyplot as plt



        print("plotting nodes required histogram...")

        # Define the number of bins you want

        num_bins = 25

        data = nr_list
@@ -118,19 +121,21 @@ if __name__ == "__main__": 
        # Save the histogram to a file

        plt.savefig('histogram.png', dpi=300, bbox_inches='tight')



        print("plotting submit times...")

        # Plot number of nodes over time

        #plt.clf()

        #plt.figure(figsize=(10, 2))

        ## Create a bar chart

        #plt.bar(submit_times, nr_list, width=10.0, color='blue', edgecolor='black', alpha=0.7)

        plt.clf()

        plt.figure(figsize=(10, 2))

        # Create a bar chart

        plt.bar(submit_times, nr_list, width=10.0, color='blue', edgecolor='black', alpha=0.7)

        # Add labels and title

        #plt.xlabel('Allocation Time (s)')

        #plt.ylabel('Number of Nodes')

        plt.xlabel('Submit Time (s)')

        plt.ylabel('Number of Nodes')

        # Set min-max axix bounds

        #plt.xlim(1, max(submit_times))

        plt.xlim(1, max(submit_times))

        # Set the y-axis to logarithmic scale with base 2

        #plt.yscale('log', base=2)

        #y_ticks = [2**i for i in range(0, 14)]

        #plt.yticks(y_ticks, labels=[str(tick) for tick in y_ticks])

        plt.yscale('log', base=2)

        y_ticks = [2**i for i in range(0, 14)]

        plt.yticks(y_ticks, labels=[str(tick) for tick in y_ticks])

        # Save the plot to a file

        #plt.savefig('nodes_time.png', dpi=300, bbox_inches='tight')
 
        plt.savefig('nodes_time.png', dpi=300, bbox_inches='tight')