def generate_graph(self, csv_file, save_path):
''' Generate a graph
This function generates a graph with data from csv_file.
Each line (PlotData) in the graph have some settings (parameters). For example:
- x values - [List] X values on the graph
- y values - [List] Y values on the graph
- color - [String] What color the line is going to have
- label - [String] Label/name of the line. Used for "plt.legend"
Even the graph (gh) have some settings (parameters). For example:
- gh(line (plot) 1, line (plot) 2, Title on graph, x label, y label, ticks settings (more information
about this further down), save path
plot1 - [PlotData obj] Obj containing line data
plot2 - [PlotData obj] Obj containing line data
title,- [String] Title on the graph
xlabel - [String] X-label
ylabel - [String] Y-label
validation - [Boolean] A flag that determines how the y-values are going to be generated (plt.yticks). So right
now there are two different settings (true or false). (If you need more settings this could be changed to a
string or something.)
save_path - [String] Where the graph is going to be saved.
:args:
:param csv_file: The location of the csv file where the data are collected
:param save_path: The location where the graph is going to be saved at
'''
# Read the csv file
df = pd.read_csv(csv_file)
# Epochs
epochs = []
for x in range(len(df['loss'])):
epochs.append(x)
# Accuracy
plot1 = PlotData(epochs, df['val_accuracy'], "red",
"Validation accuracy")
plot2 = PlotData(epochs, df['accuracy'], "blue", "Training accuracy")
graph = gh(plot1, plot2, "TITLE", "Training Epoch",
"Training Accuracy", False, save_path)
graph.generate_graph()
del plot1, plot2, graph
# Loss
plot1 = PlotData(epochs, df['val_loss'], "red", "Validation loss")
plot2 = PlotData(epochs, df['loss'], "blue", "Training loss")
graph = gh(plot1, plot2, "TITLE", "Training Epoch", "Training Loss",
True, save_path)
graph.generate_graph()
del plot1, plot2, graph
def analyzeCompareResult(q):
wrFile = WRFile()
#fileKind = "F:\\data\\experiment/Delay_SQ_q"
fileKind = "F:\\data\\experiment/Delay_q"
x = wrFile.readDataFromExcel(filePath=fileKind + str(q) + ".xlsx",
min_cols=1,
max_cols=1)
y = wrFile.readDataFromExcel(filePath=fileKind + str(q) + ".xlsx",
min_cols=2,
max_cols=2)
z = wrFile.readDataFromExcel(filePath=fileKind + str(q) + ".xlsx",
min_cols=3,
max_cols=3)
a = wrFile.readDataFromExcel(filePath=fileKind + str(q) + ".xlsx",
min_cols=5,
max_cols=5)
#plot4DSeperate(x,y,z,a,q)
PlotData().plot4D(x, y, z, a, q)
def __init__(self):
"""Create a PlotView instance"""
QFrame.__init__(self)
self.setSizePolicy(QSizePolicy.Expanding, QSizePolicy.Expanding)
# setup some default data values
self.data = PlotData()
self.data.x_data_type = "number"
self.data.setValid(False)
self.plot_figure = PlotFigure()
self.plot_settings = PlotSettings()
self.canvas = FigureCanvas(self.plot_figure.getFigure())
self.canvas.setParent(self)
self.canvas.setSizePolicy(QSizePolicy.Expanding, QSizePolicy.Expanding)
self.mouse_handler = MouseHandler(self)
def start(self):
""" Initialise audio, make DetectorBank, open PlotData window and
start audio
"""
print('Initializing audio...')
deviceIdx = self.deviceBox.currentIndex()
device = self.availableDevices[deviceIdx]
self.initializeAudio(device)
print('Making DetectorBank...')
pitchOffset = self.makeDetectorBank()
print('Making PlotData object...')
self.pd = PlotData(self.db.getChans(), pitchOffset)
# self.pd.show()
print('Starting audio...')
self.startAudio()
def plotDelayDistribution(q):
ATBM_data = []
SQ_data = []
ATBM_file = "F:\data\experiment/Seperate_Delay_ATBM_q" + str(q) + ".xlsx"
SQ_file = "F:\data\experiment/Seperate_Delay_SQ_q" + str(q) + ".xlsx"
#获取各类延迟的数据
for j in range(4, 10):
ATBM_data.append(caculateSumOfSeperateDelay(ATBM_file, j))
SQ_data.append(caculateSumOfSeperateDelay(SQ_file, j))
#数据进行归于话处理
ATBM_data = np.array(ATBM_data)
SQ_data = np.array(SQ_data)
ATBM_data = np.round(ATBM_data / np.sum(ATBM_data), 2)
SQ_data = np.round(SQ_data / np.sum(SQ_data), 2)
data = [ATBM_data, SQ_data]
colors = ("k", "w")
labels = ("ATBM", "SQ")
title = u"队列级数为" + str(q) + u"时ATBM和SQ下不同延迟的分布"
xticks = []
for i in range(5):
xticks.append("d=" + str(i))
xticks.append("d>=" + str(4))
plot = PlotData()
plot.plotBar(data,
colors,
labels,
title,
xlabel=u"请求延迟",
ylabel=u"延迟对应的比例",
ylimit=1,
xticks=xticks)
print("ATBM各级延迟", ATBM_data)
print("SQ各级延迟", SQ_data)
'''
