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- import matplotlib.pyplot as plt
- import numpy as np
- import os
- LEAD_FILE = 'log'+os.sep+"f_feedback.hist"
- F_FILE = 'log'+os.sep+"f_output.hist"
- LEAD_PROCESSED_IMG = 'img'+os.sep+"feedback_history_processed.png"
- F_PROCESSED_IMG = 'img'+os.sep+"output_history_processed.png"
- SEP = ","
- NODES = 1000 # number of nodes logged
- with open(LEAD_FILE) as f:
- buf = f.read()
- nodes = buf.split(SEP)[:-1]
- node_log = []
- for i in range(0, len(nodes)):
- node_log+=[int(float(nodes[i]))]
- freq_single_lead = sum(np.array(node_log)==1)/float(len(node_log))
- print("single leader frequency: {}".format(freq_single_lead))
- plt.plot(node_log)
- plt.legend(['#leads'])
- plt.savefig(LEAD_PROCESSED_IMG)
- with open(F_FILE) as f:
- buf = f.read()
- nodes = buf.split(SEP)[:-1]
- node_log = []
- for i in range(0, len(nodes)):
- node_log+=[float(nodes[i])]
- plt.plot(node_log)
- plt.legend(['#leads', 'f'])
- plt.savefig(F_PROCESSED_IMG)
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