本文整理汇总了Python中plot.Plot.plot2Subplots方法的典型用法代码示例。如果您正苦于以下问题：Python Plot.plot2Subplots方法的具体用法？Python Plot.plot2Subplots怎么用？Python Plot.plot2Subplots使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类plot.Plot的用法示例。
在下文中一共展示了Plot.plot2Subplots方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: plotIterations
# 需要导入模块: from plot import Plot [as 别名]
# 或者: from plot.Plot import plot2Subplots [as 别名]
def plotIterations(player_number1, tx_node_id1, rx_node_id1, player_number2, tx_node_id2, rx_node_id2, c1=0, c2=0, TruncatedValues=True, saveImage = True):
#This method will read the files which contains information about an experiment identified from c1 and c2, and then plot the results using Plot class
path1 ="./iterations/c1_%d-c2_%d/player_%d_with_tx_%d_and_rx_%d.dat" %(c1, c2, player_number1, tx_node_id1, rx_node_id1)
path2 ="./iterations/c1_%d-c2_%d/player_%d_with_tx_%d_and_rx_%d.dat" %(c1, c2,player_number2, tx_node_id2, rx_node_id2)
if (not os.path.exists(path1) or not os.path.isfile(path1)):
print "No data available for plotting iterations"
return
if (not os.path.exists(path2) or not os.path.isfile(path2)):
print "No data available for plotting iterations"
return
f1 = open(path1, "r")
f2 = open(path2, "r")
#read first file
iterations_list1 =[]
labels1 = []
#read first line, it's a header
f1.readline()
while True:
line = f1.readline()
if not line:
break
#detect line which represent the starting of a new experiment
if line[0:10] == "Experiment":
iterations_list1.append([])
line_list = line.split()
if line_list[9]=="adaptive":
labels1.append("cost=%s gain=%s dB" %(line_list[9], line_list[22] ) )
else:
labels1.append("cost=%s gain=%s dB" %(line_list[8], line_list[22] ) )
continue
line_list = line.split()
try:
if TruncatedValues:
iterations_list1[-1].append(float(line_list[3]))
else:
iterations_list1[-1].append(float(line_list[5]))
except:
continue
f1.close()
#read second file
iterations_list2 =[]
labels2 = []
#read first line, it's a header
f2.readline()
while True:
line = f2.readline()
if not line:
break
if line[0:10] == "Experiment":
iterations_list2.append([])
line_list = line.split()
if line_list[9] == "adaptive":
labels2.append("cost=%s gain=%s dB" %( line_list[9], line_list[22]) )
else:
labels2.append("cost=%s gain=%s dB" %( line_list[8], line_list[22]) )
continue
line_list = line.split()
try:
if TruncatedValues:
iterations_list2[-1].append(float(line_list[3]))
else:
iterations_list2[-1].append(float(line_list[5]))
except:
continue
f2.close()
if TruncatedValues:
Plot.plot2Subplots(iterations_list1, iterations_list2, labels1, labels2, "Iterations", "Power [dBm]", "Best response evolution for player %d. Truncated values" %player_number1, "Best response evolution for player %d. Truncated values" %player_number2,c1, c2,ion=False,Truncated=TruncatedValues,SaveImg = saveImage )
else:
Plot.plot2Subplots(iterations_list1, iterations_list2, labels1, labels2, "Iterations", "Power [dBm]", "Best response evolution for player %d. Real values" %player_number1, "Best response evolution for player %d. Real values" %player_number2,c1, c2,ion=False,Truncated=TruncatedValues,SaveImg = saveImage )