def Diff_FSPM():
'''
Diff-FSPM 算法分为如下3个步骤：
- 原始序列数据集局部转换
- 获取最优序列长度 l_opt ok
- 截断原始序列数据集 ok
- 层次遍历构建绕动闭前缀序列树
- min_sup 约束剪枝
- 闭等价关系 剪枝
- 预测计数值 PK. 噪音计数值
- 描述上是挖掘FSP树, 实际直接输出结果集
@summary: Diff-FSPM algorithm
'''
dplog.info( " === Phase 1: Decomposing input sequence dataset to n-grams (%d<=n<=%d) Begin ===" % (1, conf.l_opt) )
conf.l_opt = GetOptSeqLength(conf.dataset, conf.epsilon, mechanism="Exponential")
ngram_set = NGramSet( int(conf.l_opt), N_max=int(conf.n_max) )
ngram_set.load_dataset( conf.dataset, conf.dataset_ngrams % (conf.l_opt) )
dplog.info( " === Phase 1: Decomposing input sequence dataset to n-grams (%d<=n<=%d) End ===" % (1, conf.l_opt) )
dplog.info( " === Phase 2: Sanitizing n-grams to build noisy frequent sequential patterns Tree Begin ===" )
ngram_set = Sanitizer.ngram( ngram_set, conf.n_max, conf.epsilon, conf.l_opt, conf.min_sup)
ngram_set.dump( conf.dataset_noisy % (conf.l_opt, conf.epsilon))
dplog.info( " === Phase 2: Sanitizing n-grams to build noisy frequent sequential patterns Tree End ===" )
dplog.info( " === Phase 3: Synthetic frequent sequential patterns from santized n-grams Begin ===" )
factory = Reconstruction( ngram_set, conf.min_sup )
factory.extend()
factory.ngramset.dump( conf.dataset_result % (conf.l_opt, conf.epsilon))
dplog.info( " === Phase 3: Synthetic frequent sequential patterns from santized n-grams End ===" )
print "\n=== Phase 2.1: Sanitizing clos_n-grams\n"
ngram_set = Sanitizer.Equivalence(
ngram_set, output_dir + dataset_name + "-" + str(scale) +
"-original-" + str(n_max) + "grams.dat", output_dir + dataset_name +
"-" + str(scale) + "-original-" + str(n_max) + "_clo_grams.dat")
print "\n=== Phase 2.2: Sanitizing n-grams\n"
ngram_set = Sanitizer.ngram(ngram_set,
n_max,
budget=epsilon,
sensitivity=l_max)
ngram_set.dump(output_dir + dataset_name + file_id + ".dat")
print "\n=== Phase 3: Synthetic sequential database generation from sanitized n-grams\n"
factory = Reconstruction(ngram_set, lUp)
# Reconstruct longer grams from shorter ones using the Markov approach
factory.extend()
# Saving the extended ngramset
factory.ngramset.dump(outdataset_name_info %
(scale, n_max, topN, lLeft, lUp, deta, epsilon) +
"-extended.dat")
# Generating dataset
factory.reconstruct(outdataset_name_info %
(scale, n_max, topN, lLeft, lUp, deta, epsilon) +
"-reconstructed.dat")
print "\n=== Phase 4: Get Consolidated Frequency"
def __init__(self):
self.root = Tkinter.Tk()
self.root.wm_title("Test Bench Dashboard")
self.top = None
self.topplot = None
self.topcanvas = None
self.topcbar = None
self.topcbaxes = None
menu = Tkinter.Menu(self.root)
self.root.config(menu=menu)
filemenu = Menu(menu)
menu.add_cascade(label="File", menu=filemenu)
filemenu.add_command(label="Exit", command=self.root.quit)
viewmenu = Menu(menu)
menu.add_cascade(label="View", menu=viewmenu)
viewmenu.add_command(label="Dedicated Reconstruction Window",
command=self.Eitwin)
viewmenu.add_separator()
viewmenu.add_command(label="something else",
command=self.Something_else)
helpmenu = Menu(menu)
menu.add_cascade(label="Help", menu=helpmenu)
helpmenu.add_command(label="About...", command=self.About)
self.root.protocol("WM_DELETE_WINDOW", self.quit)
# make Esc exit the program
self.root.bind('<Escape>', lambda e: self.root.destroy())
# Matplotlibbing.
fig = mpl.figure.Figure(figsize=(5, 4), dpi=100)
# pos = [left, bottom, width, height]
image_position = [0.1, 0.25, 0.7, 0.7]
histogram_position = [0.1, 0.08, 0.8, 0.1]
colorbar_position = [0.85, 0.25, 0.03, 0.7]
self.imageplt = fig.add_axes(image_position)
self.histplt = fig.add_axes(histogram_position)
self.cbaxes = fig.add_axes(colorbar_position)
# 180,225,270,315,0,45,90,135
# 1,2,3,4,5,6,7,8
# Add text for electrode locations.
self.imageplt.annotate('180d(AFE1)',
xy=(0.4, 0.9),
xycoords='axes fraction')
self.imageplt.annotate('225d(AFE2)',
xy=(0.15, 0.75),
xycoords='axes fraction')
self.imageplt.annotate('270d(AFE3)',
xy=(0.0, 0.5),
xycoords='axes fraction')
self.imageplt.annotate('315d(AFE4)',
xy=(0.2, 0.2),
xycoords='axes fraction')
self.imageplt.annotate('0d(AFE5)',
xy=(0.5, 0.1),
xycoords='axes fraction')
self.imageplt.annotate('45d(AFE6)',
xy=(0.75, 0.25),
xycoords='axes fraction')
self.imageplt.annotate('90d(AFE7)',
xy=(0.9, 0.5),
xycoords='axes fraction')
self.imageplt.annotate('135d(AFE8)',
xy=(0.8, 0.8),
xycoords='axes fraction')
ypadding = 10
xpadding = 20
#
#
self.file_marker = 0
self.file_name = ''
self.data_file_array = []
# Will this often need to be changed?
scale_max = 90000
self.sliders = [0, scale_max, 0, scale_max]
min_cbar = 0
max_cbar = scale_max
scale_tick_interval = float(scale_max / 10)
# intialize the reconstruction library.
self.image_reconstruct = eit.Reconstruction()
self.img = self.image_reconstruct.img
self.plot = self.imageplt.imshow(self.img, interpolation='nearest')
# self.imageplt.set_position(image_position) # set a new position
# self.histplt.set_position(histogram_position)
self.cbar = mpl.pyplot.colorbar(self.plot, cax=self.cbaxes)
# self.cbar = mpl.pyplot.colorbar(self.imageplt,cax = self.cbaxes)
self.cbar.set_clim([min_cbar, max_cbar])
#
self.canvas = mpl.backends.backend_tkagg.FigureCanvasTkAgg(
fig, master=self.root)
self.canvas.show()
self.canvas.get_tk_widget().pack(side=Tk.TOP, fill=Tk.BOTH, expand=1)
toolbar = mpl.backends.backend_tkagg.NavigationToolbar2TkAgg(
self.canvas, self.root)
toolbar.update()
self.canvas._tkcanvas.pack(side=Tk.TOP, fill=Tk.BOTH, expand=1)
# canvas.mpl_connect('key_press_event', on_key_event)
self.use_blit = False
# cache the background, in the init.
if self.use_blit: # cache the background.
self.background = self.canvas.copy_from_bbox(self.imageplt.bbox)
self.histbackground = self.canvas.copy_from_bbox(self.histplt.bbox)
self.cbbackground = self.canvas.copy_from_bbox(self.cbaxes.bbox)
self.total_rendering_time = 0.0
self.total_processing_time = 0.0
# ---------------
# defining frames
# ---------------
bottomframe0 = Frame(self.root)
bottomframe1 = Frame(self.root)
bottomframe2 = Frame(self.root)
bottomframe3 = Frame(self.root)
bottomframe0.pack(side=TOP)
bottomframe1.pack(side=TOP)
bottomframe2.pack(side=TOP)
bottomframe3.pack(side=TOP)
# This is the text box...
self.msg = Tkinter.Text(bottomframe0,
height=1.0,
bg="light cyan",
state=Tkinter.NORMAL)
self.msg.grid(row=1, column=0, columnspan=3)
self.msg.pack(fill="x", expand=True)
# sliders.
self.w1 = Tkinter.Scale(bottomframe0,
from_=self.sliders[0],
to=self.sliders[1],
length=600,
tickinterval=scale_tick_interval,
orient=HORIZONTAL,
label='MIN')
self.w1.set(scale_max / 10)
self.w1.pack(fill="x", expand=True)
self.w2 = Tkinter.Scale(bottomframe0,
from_=self.sliders[2],
to=self.sliders[3],
length=600,
tickinterval=scale_tick_interval,
orient=HORIZONTAL,
label='MAX')
self.w2.set(9 * scale_max / 10)
self.w2.pack(fill="x", expand=True)
# Text entry boxes for min and max range of each slider bar.
#
#
cbarbut = Tkinter.Button(bottomframe0,
text='Update HIST',
command=self.update_hist)
cbarbut.pack(side=Tkinter.RIGHT, padx=3, pady=ypadding)
cbarbut = Tkinter.Button(bottomframe0,
text='Update CBAR',
command=self.update_cbar)
cbarbut.pack(side=Tkinter.RIGHT, padx=3, pady=ypadding)
self.hist_update = False
self.min_slider_l = Tkinter.Entry(bottomframe0)
self.min_slider_h = Tkinter.Entry(bottomframe0)
self.max_slider_l = Tkinter.Entry(bottomframe0)
self.max_slider_h = Tkinter.Entry(bottomframe0)
self.max_slider_h.pack(side=Tkinter.RIGHT, padx=3, pady=ypadding)
self.max_slider_h_label = Tkinter.Label(
bottomframe0, text="max_h:").pack(side=Tkinter.RIGHT)
self.max_slider_l.pack(side=Tkinter.RIGHT, padx=3, pady=ypadding)
self.max_slider_l_label = Tkinter.Label(
bottomframe0, text="max_l:").pack(side=Tkinter.RIGHT)
self.min_slider_h.pack(side=Tkinter.RIGHT, padx=3, pady=ypadding)
self.min_slider_h_label = Tkinter.Label(
bottomframe0, text="min_h:").pack(side=Tkinter.RIGHT)
self.min_slider_l.pack(side=Tkinter.RIGHT, padx=3, pady=ypadding)
self.min_slider_l_label = Tkinter.Label(
bottomframe0, text="min_l:").pack(side=Tkinter.RIGHT)
self.min_slider_l.bind("<Return>", self.evaluate)
self.min_slider_h.bind("<Return>", self.evaluate)
self.max_slider_l.bind("<Return>", self.evaluate)
self.max_slider_h.bind("<Return>", self.evaluate)
full_ports = list(serial.tools.list_ports.comports())
portnames = [item[0] for item in full_ports]
if len(portnames) > 0:
self.menuselect = StringVar(self.root)
self.menuselect.set(portnames[0])
# apply has been deprecated.
# listboxdataconnect = apply(OptionMenu, (self.root, self.menuselect) + tuple(portnames ))
listboxdataconnect = OptionMenu(*(self.root, self.menuselect) +
tuple(portnames))
listboxdataconnect.pack(in_=bottomframe1,
side=Tkinter.LEFT,
padx=3,
pady=ypadding)
self.baselinebut = Tkinter.Button(master=bottomframe1,
text="Baseline",
command=self.baseline)
self.baselinebut.pack(side=Tkinter.RIGHT, padx=3, pady=ypadding)
self.recorddata = Tkinter.Button(master=bottomframe1,
text='Record',
command=self.record)
self.recorddata.pack(side=Tkinter.RIGHT, padx=3, pady=ypadding)
self.buttonconnect = Tkinter.Button(master=bottomframe1,
text='Connect',
command=self.connect)
self.buttonconnect.pack(side=Tkinter.RIGHT, padx=3, pady=ypadding)
else:
# no serial port detected.
print('no serial port found, hope that\'s OK')
self.text = "no serial port found, hope that's OK"
if expertMode is False:
tkMessageBox.showwarning(
"No serial port",
"No device detected\nCheck cable and connection")
readfilerunbut = Tkinter.Button(bottomframe2,
text='Run',
command=self.run_file)
readfilerunbut.pack(side=Tkinter.RIGHT, padx=3, pady=ypadding)
readfilestartbut = Tkinter.Button(bottomframe2,
text='Step',
command=self.step_file)
readfilestartbut.pack(side=Tkinter.RIGHT, padx=3, pady=ypadding)
readfilebut = Tkinter.Button(bottomframe2,
text='ReadFromFile',
command=self.load_file)
readfilebut.pack(side=Tkinter.RIGHT, padx=3, pady=ypadding)
# start Serial handler off in a separate process.
self.s = Serialhandler.Serialhandler()
self.s.start()
self.s.join()
self.text = 'hi'
self.root.after(200, self.process_data)
self.root.mainloop()
