Loading scripts/mem_analysis.py +7 −11 Original line number Diff line number Diff line Loading @@ -7,15 +7,11 @@ import sys import struct import numpy as np import pandas as pd import matplotlib import tkinter matplotlib.use('TkAgg') # Qt4Agg TkAgg Gtk3Agg import matplotlib.pyplot as plt # set matplotlib in interactive mode (plots figure and return control) plt.ion() plt.close('all') # plt.ion() # plt.close('all') parser = argparse.ArgumentParser(description='Analyze memory output file') parser.add_argument('input',type=str,help='Memory analysis file (e.g. mem_analysis.csv)') Loading @@ -30,8 +26,6 @@ Nframes = max(df['frame']) df = df.groupby(df.columns.tolist(),as_index=False).size() df = df.rename(columns={'size': 'count'}) # df.loc[df['action_type'] == 'D', 'frame'] += 0.9 # remove column 'action_type' df.drop(columns = ['action_type']) Loading Loading @@ -102,13 +96,15 @@ ax.set_position([box.x0, box.y0 + box.height * 0.2, box.width, box.height * 0.8] # insert the legend below the graph ax.legend(loc="upper left", bbox_to_anchor=(0, -0.1), ncol=2, borderaxespad=0, fontsize='small') # magnify to "almost" fullscreen size # magnify to "almost" fullscreen size (select the alternative for your backend) fig = plt.gcf() fig.set_size_inches(15, 9) # we need to set the size manually, otherwise savefig will save the figure in the default size mng = plt.get_current_fig_manager() mng.full_screen_toggle() # mng.frame.Maximize(True) # mng.window.showMaximized() # mng.window.state('zoomed') # show and save the figure # show and save the figure (use block=True to wait until Figure is closed manually) plt.savefig(os.path.splitext(args.input)[0] + '.png', dpi=100, bbox_inches='tight') plt.show(block=True) # plt.savefig(os.path.splitext(args.input)[0] + '.png', dpi=600) Loading
scripts/mem_analysis.py +7 −11 Original line number Diff line number Diff line Loading @@ -7,15 +7,11 @@ import sys import struct import numpy as np import pandas as pd import matplotlib import tkinter matplotlib.use('TkAgg') # Qt4Agg TkAgg Gtk3Agg import matplotlib.pyplot as plt # set matplotlib in interactive mode (plots figure and return control) plt.ion() plt.close('all') # plt.ion() # plt.close('all') parser = argparse.ArgumentParser(description='Analyze memory output file') parser.add_argument('input',type=str,help='Memory analysis file (e.g. mem_analysis.csv)') Loading @@ -30,8 +26,6 @@ Nframes = max(df['frame']) df = df.groupby(df.columns.tolist(),as_index=False).size() df = df.rename(columns={'size': 'count'}) # df.loc[df['action_type'] == 'D', 'frame'] += 0.9 # remove column 'action_type' df.drop(columns = ['action_type']) Loading Loading @@ -102,13 +96,15 @@ ax.set_position([box.x0, box.y0 + box.height * 0.2, box.width, box.height * 0.8] # insert the legend below the graph ax.legend(loc="upper left", bbox_to_anchor=(0, -0.1), ncol=2, borderaxespad=0, fontsize='small') # magnify to "almost" fullscreen size # magnify to "almost" fullscreen size (select the alternative for your backend) fig = plt.gcf() fig.set_size_inches(15, 9) # we need to set the size manually, otherwise savefig will save the figure in the default size mng = plt.get_current_fig_manager() mng.full_screen_toggle() # mng.frame.Maximize(True) # mng.window.showMaximized() # mng.window.state('zoomed') # show and save the figure # show and save the figure (use block=True to wait until Figure is closed manually) plt.savefig(os.path.splitext(args.input)[0] + '.png', dpi=100, bbox_inches='tight') plt.show(block=True) # plt.savefig(os.path.splitext(args.input)[0] + '.png', dpi=600)