def mpPlot():
listFiles = ut_service.getListLC_test()
if request.method == 'POST':
fileName = str(request.form.get('selectFile'))
inputDuration = int(request.form.get('inputDuration'))
inputHeight = int(request.form.get('inputHeight'))
subsequence_length = int(request.form.get('input_subsequence_length'))
rawInstances, transList = ut_service.getDataLC_test(
fileName, L=int(inputHeight), I=int(inputDuration))
x_axis = list(range(len(rawInstances)))
mp_list = ut_gen.genMartixProfile(
instances=rawInstances,
timestamp=x_axis,
subsequence_length=subsequence_length)
xmin = min(mp_list)
xmax = max(mp_list)
for i, x in enumerate(mp_list):
mp_list[i] = (x - xmin) / (xmax - xmin)
data = {"instances": rawInstances, "timestamp": x_axis}
js, div = ut_exBok.export_JsDiv_RawMP(data=data,
mp_list=mp_list,
isUTC=False)
return render_template("html/mp/mp_test_plot.html",
js=js,
div=div,
file_name=fileName)
def rrcfPlot():
listFiles = ut_service.getListLC_test()
if request.method == 'POST':
fileName = str(request.form.get('selectFile'))
inputDuration = int(request.form.get('inputDuration'))
inputHeight = int(request.form.get('inputHeight'))
rawInstances, transList = ut_service.getDataLC_test(
fileName, L=int(inputHeight), I=int(inputDuration))
x_axis = list(range(len(rawInstances)))
rrcf_resultList = ut_gen.getRRCFresult(fileName=fileName,
duration=inputDuration,
height=inputHeight)
rrcf = {
"instances": rrcf_resultList,
"timestamp": x_axis[0:len(rrcf_resultList)]
}
data = {"instances": rawInstances, "timestamp": x_axis}
js, div = ut_exBok.export_JsDiv_Single(data=data,
legend="RAW",
color='black',
isCircle=True)
jsRRCF, divRRCF = ut_exBok.export_JsDiv_Single(data=rrcf,
legend="RRCF",
color='red',
isCircle=True)
return render_template("html/rrcf/rrcf_test_plot.html",
js=js,
div=div,
jsRRCF=jsRRCF,
divRRCF=divRRCF,
file_name=fileName)
def xmeanPlot():
listFiles = ut_service.getListLC_test()
if request.method == 'POST':
fileName = str(request.form.get('selectFile'))
amount_initial_centers = int(
request.form.get('amount_initial_centers'))
kmax = int(request.form.get('kmax'))
FdataMDF, FtimestampMDF = ut_service.getMDFData(fileName)
resultDic = ut_cluster.cluster_xMean(
listInput=FdataMDF,
amount_initial_centers=amount_initial_centers,
kmax=kmax)
TOOLTIPS = [
("index", "$index"),
("(x,y)", "@x{0,0.000000}, $y"),
]
js, div = ut_bokeh.JSandDivXMeanPlot(x_axis=FtimestampMDF,
y_axisRaw=FdataMDF,
resultDic=resultDic,
title=fileName,
TOOLTIPS=TOOLTIPS)
# js, div = ut_bokeh.JSandDivDoublePlot(x_axis=FtimestampMDF, y_axisRaw=FdataMDF, y_axisBin=sketchInstances,
# title=fileName, transList=transList,alarmList=alarmList)
#
# rows = corePlot.getDataTableMeanVarianceBin()
return render_template("html/LC_test/lc_test_plot.html",
jsResult=js,
divResult=div,
listFiles=listFiles)
def lcFixPlot():
listFiles = ut_service.getListLC_test()
if request.method == 'POST':
fileName = str(request.form.get('selectFile'))
inputDuration = int(request.form.get('inputDuration'))
inputHeight = int(request.form.get('inputHeight'))
windowSize = int(request.form.get('inputWindowSize'))
rawInstances, transList = ut_service.getDataLC_test(
fileName, L=int(inputHeight), I=int(inputDuration))
x_axis = list(range(len(rawInstances)))
data = {
"instances": rawInstances,
"timestamp": x_axis,
"fileName": fileName,
"windowSize": windowSize
}
sketchInstances = ut_gen.genFixBin(binSize=windowSize,
instances=rawInstances)
add_on = []
for tran in transList:
add_on.append({
'type': 'anwser',
'start': int(tran[0]),
'end': int(tran[1])
})
# js, div = ut_exBok.export_JsDiv_saxcompare(data=data, add_on=add_on)
#
js, div = ut_bokeh.JSandDivDoublePlotStandard(
x_axis=x_axis,
y_axisRaw=rawInstances,
y_axisBin=sketchInstances,
title=fileName,
add_on=add_on,
legend_label='Fixed')
rows = []
return render_template("html/LC_test/lc_test_plot.html",
jsResult=js,
divResult=div,
listFiles=listFiles,
rows=rows)
def lcPlot():
listFiles = ut_service.getListLC_test()
if request.method == 'POST':
fileName = str(request.form.get('selectFile'))
inputDuration = int(request.form.get('inputDuration'))
inputHeight = int(request.form.get('inputHeight'))
windowSize = int(request.form.get('inputWindowSize'))
initialBin = int(request.form.get('inputInitialBin'))
rawInstances, transList = ut_service.getDataLC_test(
fileName, L=int(inputHeight), I=int(inputDuration))
x_axis = list(range(len(rawInstances)))
corePlot = sketchDyBinService(windowSize=windowSize,
initialBin=initialBin,
isOnline=False)
sketchInstances = corePlot.sketchMode(instances=rawInstances)
dictResult = corePlot.getListResultTest()
threshold_tTest = float(request.form.get('threshold_tTest'))
if threshold_tTest == 0:
alarmList = []
else:
alarmList = ut_service.genTranFromTtest(
dictResult=dictResult, threshold_tTest=threshold_tTest)
js, div = ut_bokeh.JSandDivDoublePlotWithToggle(
x_axis=x_axis,
y_axisRaw=rawInstances,
y_axisBin=sketchInstances,
title=fileName,
transList=transList,
alarmList=alarmList)
rows = corePlot.getDataTableMeanVarianceBin()
return render_template("html/LC_test/lc_test_plot.html",
jsResult=js,
divResult=div,
listFiles=listFiles,
rows=rows)
def rrcfMain():
listFiles = ut_service.getListLC_test()
return render_template("html/rrcf/lc_rrcf_main.html", listFiles=listFiles)
def mpMain():
listFiles = ut_service.getListLC_test()
return render_template("html/mp/lc_mp_main.html", listFiles=listFiles)
def lcMain():
listFiles = ut_service.getListLC_test()
return render_template("html/LC_test/lc_test_main.html",
listFiles=listFiles)
lc_path_answer = "sq_L{}_I{}\\answer\\".format(L, I)
path_to_lc_data_file = "{}{}".format(dataset_path, lc_path_test)
path_to_lc_ans_file = "{}{}".format(dataset_path, lc_path_answer)
html_path = "sq_L{}_I{}\\html\\".format(L, I)
png_path = "sq_L{}_I{}\\bokeh_pic\\".format(L, I)
driver = webdriver.Chrome(executable_path="C:\\chromedriver\\chromedriver.exe")
pathHtmlOutput = "{}{}".format(dataset_path, html_path)
pathPngOutput = "{}{}".format(dataset_path, png_path)
data = {'inputWindowSize': 100, 'inputInitialBin': 3}
listFile = ut_web.getListLC_test(L=L,I=I)
for indexFile, fileName in enumerate(listFile):
print(fileName)
isFoundHtml = ut.isFileNameInFolder(path=pathHtmlOutput, fileName="{}.html".format(fileName))
isFoundPng = ut.isFileNameInFolder(path=pathPngOutput, fileName="{}.png".format(fileName))
if not (isFoundHtml & isFoundPng):
rawInstances, transList = ut_service.getDataLC_test(fileName,L=L,I=I)
x_axis = list(range(len(rawInstances)))
plotRaw = ut_bokeh.exportPlot(x_axis=x_axis,
y_axis=rawInstances,
fileName=fileName,
transList=transList)