theano
79 lines
1.8 KiB
Python
Executable File
79 lines
1.8 KiB
Python
Executable File
#!/usr/bin/python
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import glob, os, re, sys
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import numpy as np
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import matplotlib.pyplot as plt
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import scipy as sp
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import scipy.stats as ss
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log_info = []
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table = {}
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enc_table = ["BPSK 1/2", "BPSK 3/4", "QPSK 1/2",
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"QPSK 3/4", "16QAM 1/2", "16QAM 3/4",
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"64QAM 2/3", "64QAM 3/4"]
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path = sys.argv[1]
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ntrials = int(sys.argv[2])
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snr_list = []
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def mean_confidence_interval(data, confidence=0.95):
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a = 1.0 * np.array(data)
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n = len(a)
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m, se = np.mean(a), ss.sem(a)
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h = se * ss.t._ppf((1 + confidence)/2., n-1)
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return m, h
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for filename in glob.glob(os.path.join(path, "*.log")):
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params = filename.split("/")[1].split("_")
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print params
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try:
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trial = int(params[1])
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npkts = int(params[2])
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snr = float(params[3])
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encode = int(params[4])
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except AssertionError:
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print "Log filename parse failed; exiting!"
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sys.exit()
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pdrate = sum(1 for line in open(filename))/float(npkts)
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if snr not in snr_list:
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snr_list.append(snr)
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if encode not in table:
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table[encode] = {}
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if snr not in table[encode]:
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table[encode][snr] = []
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table[encode][snr].append(pdrate)
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snr_list.sort()
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for enc in sorted(table.keys()): # sort so legend labels are in order
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# Check first that we got all datapoints for each trial
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for snr in table[enc].keys():
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try:
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assert len(table[enc][snr]) == ntrials
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except AssertionError:
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print "You don't have enough datapoints; exiting!"
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sys.exit()
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y = [mean_confidence_interval(table[enc][snr]) for snr in snr_list]
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# print enc_table[enc], snr_list, y
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plt.errorbar(snr_list, [m for m,h in y],
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yerr=[h for m,h in y],
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marker='o',
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label="%s" % enc_table[enc])
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plt.ylabel("PDR")
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plt.xlabel("SNR")
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plt.title("Delivery rate vs. SNR for different encoding schemes")
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plt.legend(loc="upper left")
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plt.savefig(os.path.join(path,"plot.png"))
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plt.show()
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