def __init__(self, parent, controller, config, dbvar=None, wd=14, ht=7.5):
self.widget_name = "graphframe"
self.lines_list = []
self.bars_list = []
self.event_polygon_list = []
self.prime_graph_pack = None
self.secondary_graph_pack = None
super().__init__(parent, controller, config, dbvar=None)
self.my_figure = Figure(figsize=(wd, ht), dpi=85)
self.my_legend = self.my_figure.legend()
self.axis_prime = self.my_figure.add_subplot(1, 1, 1)
# self.axis_prime.set_title("No Query Selected")
self.axis_secondary = self.my_figure.add_subplot(
111, sharex=self.axis_prime, frameon=False)
self.axis_secondary.xaxis.set_visible(False)
self.axis_secondary.yaxis.set_label_position("right")
self.axis_secondary.yaxis.tick_right()
self.canvas = FigureCanvas(self.my_figure, self)
self.canvas.draw()
#
# self.canvas.manager.toolbar.add_tool('zoom', 'foo')
# self.toolbar = NavigationToolbar2TkAgg(self.canvas, self)
# self.toolbar.update()
self.canvas._tkcanvas.pack()
def initiate_canvas(self):
# Add the figure to a Canvas
self.Canvas = FigureCanvas(self.figure, self.frame_canvas)
self.Canvas.get_tk_widget().configure(background=self.root.color['bg'])
self.figure.patch.set_facecolor(self.root.color['bg'])
self.Canvas.draw()
self.widget = self.Canvas.get_tk_widget()
if self.direction == "x":
self.widget.grid(row=0, column=0, stick='NSEW')
if self.direction == "y":
self.widget.grid(row=0, column=1, stick='NSEW')
def __init__(
self,
master=None,
title=None,
):
super(NetworkPlotTk,
self).__init__(matplotlib_figure=matplotlib.figure.Figure(), )
if master is None:
master = tk.Tk()
master.withdraw()
self.master = master
#self.master.protocol("WM_DELETE_WINDOW", self.on_closing)
# Create a Toplevel widget, which is a child of GUILoom
# and contains plots,
self.toplevel = tk.Toplevel(master)
self.toplevel.wm_title(title)
self.toplevel.protocol("WM_DELETE_WINDOW", self.on_closing)
self.plot_idx_scale = None
self.plot_idx_entry = None
self.plot_idx_entry_var = tk.StringVar()
self.plot_idx_entry_var.trace('w', self.plot_idx_entry_change)
self.canvas = FigureCanvas(self.figure,
master=self.toplevel,
resize_callback=self.canvas_resize_callback)
self.canvas.show()
self.canvas.get_tk_widget().pack(side=tk.TOP, fill=tk.BOTH, expand=1)
toolbar = NavigationToolbar(self.canvas, self.toplevel)
toolbar.update()
self.canvas.get_tk_widget().pack(side=tk.TOP, fill=tk.BOTH, expand=1)
def addMainFigure(self) :
""" Add main figure area """
self.fig = plt.figure(figsize=(5,4), dpi=100)
self.ax = self.fig.add_subplot(111)
self.ax.set_title('No data')
self.fig.canvas.draw()
self.canvas = FigureCanvas(self.fig, self)
""" Set up callback from canvas draw events, i.e. pan/zoom """
#self.cid1 = self.fig.canvas.mpl_connect('draw_event', self.updateFromCavas)
#self.cid1 = self.fig.canvas.mpl_connect('button_release_event', self.updateFromCavas)
#TODO animation
self.canvas.draw()
self.canvas.get_tk_widget().pack(side=tk.BOTTOM, fill=tk.BOTH, expand=True)
self.canvas._tkcanvas.pack(side=tk.TOP, fill=tk.BOTH, expand=True)
def __init__(self, parent, dim):
Frame.__init__(self, parent)
self.dim = dim
self.figure = pyplot.Figure(figsize=(5.5, 3.2),
facecolor=(240 / 255, 240 / 255,
237 / 255))
self.figure.subplots_adjust(left=0.15, bottom=0.2)
self.canvas = FigureCanvas(self.figure, master=self)
self.canvas.get_tk_widget().pack()
self.canvas.get_tk_widget().configure(highlightthickness=0)
toolbar = CutDownNavigationToolbar(self.canvas, self)
toolbar.pack()
if dim == 2:
self.axes = self.figure.add_subplot(1, 1, 1)
elif dim == 3:
self.axes = Axes3D(self.figure)
else:
raise ValueError("Dimension must be either 2 or 3")
self.currentLines = []
def __init__(self, master=None, packedHighSpeed=True):
self.maxtraces = 5
self.selChan = 0
Tk.Frame.__init__(self,master) # hack to make work in python2
self.pack()
self.figure = Figure(figsize=(15,7), dpi=100, facecolor='white')
self.canvas = FigureCanvas(self.figure, master=self)
self.canvas.show()
self.canvas.get_tk_widget().pack(side=Tk.TOP, fill=Tk.BOTH, expand=1)
self.toolbar = NaviationToolbar(self.canvas,self)
self.toolbar.update()
self.canvas._tkcanvas.pack(side=Tk.TOP, fill=Tk.BOTH, expand=1)
self.pauseButton = Tk.Button(self,text="Pause",command=self.pause)
self.pauseButton.pack(side=Tk.LEFT)
self.playButton = Tk.Button(self,text="Play",command=self.play,state=Tk.DISABLED)
self.playButton.pack(side=Tk.LEFT)
self.prevButton = Tk.Button(self,text="Previous Trace",command=self.prevTrace,state=Tk.DISABLED)
self.prevButton.pack(side=Tk.LEFT)
self.nextButton = Tk.Button(self,text="Next Trace",command=self.nextTrace,state=Tk.DISABLED)
self.nextButton.pack(side=Tk.LEFT)
self.packedHighSpeed = packedHighSpeed
self.femb = None
self.iTrace = -1
self.traces = []
self.timestamps = []
self.reset()
def drawPlot(self, filename=""):
scrolledframe = self.builder.get_object("plot_frame")
figure = Figure(figsize=(8, 8), dpi=80)
axis = figure.add_subplot(111)
x, y = calculateValues(self)
axis.plot(x, y)
if do_zoom:
i = 0
last = y[i]
for i, _ in enumerate(y):
if y[i] > last:
break
last = y[i]
axis.set_ylim(top=y[i:].max() + abs(y[i:].max() * 0.075),
bottom=y[i:].min() - abs(y[i:].min() * 0.075))
else:
axis.set_ylim(top=y.max() + abs(y.max() * 0.075),
bottom=y.min() - abs(y.min() * 0.075))
if do_lambda:
axis.set_xlabel("Wellenlänge in m")
else:
axis.set_xlabel("Glanzinkel in °")
if do_persecond:
axis.set_ylabel("Zählrahte in 1/s")
else:
axis.set_ylabel("Zählrahte in 1/" + str(measure_time) + "s")
axis.set_title("Röntgenspektrum")
canvas = FigureCanvas(figure, master=scrolledframe)
canvas.draw()
canvas.get_tk_widget().grid(row=0, column=0, sticky="nsew")
if filename != "":
figure.savefig(filename)
def __init__(self, root, subplots, title=''):
ttk.Frame.__init__(self, root)
self.signal_mouse_press = Signal()
self.signal_mouse_release = Signal()
self._fig = Figure()
self._subplots = []
self._canvas = FigureCanvas(self._fig, self)
self._canvas.get_tk_widget().pack(expand=tk.YES, fill=tk.BOTH)
self._canvas.mpl_connect('button_press_event', self.signal_mouse_press)
self._canvas.mpl_connect('button_release_event',
self.signal_mouse_release)
toolbar = NavigationToolbar2Tk(self._canvas, self)
toolbar.update()
num_rows = len(subplots)
num_columns = max(len(graphs) for graphs in subplots)
for i in range(num_rows):
for j in range(num_columns):
subplot = subplots[i][j]
if subplot is not None:
index = (i * num_columns) + j + 1
ax = self._fig.add_subplot(num_rows, num_columns, index)
subplot.set_axis(ax)
self._subplots.append(subplot)
self._fig.suptitle(title,
fontweight='bold',
fontsize=self.DEFAULT_TITLE_SIZE)
self._fig.subplots_adjust(hspace=.6, wspace=.3)
def __init__(self, window, tracer):
self.window = window
self.tracer = tracer
# PARAMÈTRES DE LA FENÊTRE :
window.title(self.tracer.window_title)
if self.tracer.x is not None or self.tracer.y is not None:
window.geometry('%+i%+i' % (self.tracer.x, self.tracer.y))
window.geometry('%ix%i' % (self.tracer.w, self.tracer.h))
# DÉFINITION DE L'AGENCEMENT :
self.canvas = FigureCanvas(self.tracer.fig, self.window)
self.toolbar = TracerToolbar(self.canvas, self.window, self.tracer,
self.save_window, self.get_band_n_rate)
self.canvas._tkcanvas.pack(side=tk.TOP, fill=tk.BOTH, expand=1)
# GESTION DES ÉVÉNEMENTS :
self.canvas.mpl_connect('key_press_event', self.on_key)
def destroy(*args):
self.window.quit()
self.canvas._tkcanvas.bind("<Destroy>", destroy)
self.canvas.draw()
def __init__(self,master,size,dpi,task):
Figure.__init__(self,figsize=(size[0]/dpi,size[1]/dpi),dpi=dpi,facecolor='w',edgecolor='b',frameon=True,linewidth=0)
FigureCanvas(self,master=master)
self.master = master
self._errors = collections.OrderedDict()
self._dirty = True
self._task = task
self.add_subplot(111,axisbg='w')
def __init__(self,master,size,dpi,data,fold):
Figure.__init__(self,figsize=(size[0]/dpi,size[1]/dpi),dpi=dpi,facecolor='w',edgecolor='b',frameon=True,linewidth=0)
FigureCanvas(self,master=master)
self.master = master
self._dirty = True
self._fold = fold
self._indices = None
self._targets = None
self._outputs = None
self._outshape = data.Yshape
self._outrange = data.Yrange
self.add_subplot(111,axisbg='w')
def __init__(self,master,size,dpi,get_matrices_fn,percentiles,transposed,ranges=None,title=""):
Figure.__init__(self,figsize=(size[0]/dpi,size[1]/dpi),dpi=dpi,facecolor='w',edgecolor='b',frameon=True,linewidth=0)
FigureCanvas(self,master=master)
self.master = master
self._dirty = True
self._get_matrices_fn = get_matrices_fn
self._P = []
self._t = percentiles
self._ranges = ranges
self._title = title
self._transposed = transposed
self.add_subplot(111,axisbg='w')
def __init__(self, controller):
"""SuperSID Viewer using Tkinter GUI for standalone and client.
Creation of the Frame with menu and graph display using matplotlib
"""
matplotlib.use('TkAgg')
self.version = "1.4 20170920 (tk)"
self.controller = controller # previously referred as 'parent'
self.tk_root = tk.Tk()
self.tk_root.title("supersid @ " + self.controller.config['site_name'])
# All Menus creation
menubar = tk.Menu(self.tk_root)
filemenu = tk.Menu(menubar, tearoff=0)
filemenu.add_command(label="Save Raw buffers", command=lambda: self.save_file('r'),underline=5,accelerator="Ctrl+R")
filemenu.add_command(label="Save Filtered buffers", command=lambda: self.save_file('f'),underline=5,accelerator="Ctrl+F")
filemenu.add_command(label="Save Extended raw buffers", command=lambda: self.save_file('e'),underline=5,accelerator="Ctrl+E")
filemenu.add_command(label="Save filtered as ...", command=lambda: self.save_file('s'),underline=5,accelerator="Ctrl+S")
filemenu.add_separator()
filemenu.add_command(label="Exit", command=lambda : self.close(force_close=False)) # ,underline=1,accelerator="Ctrl+X")
self.tk_root.bind_all("<Control-r>", self.save_file)
self.tk_root.bind_all("<Control-f>", self.save_file)
self.tk_root.bind_all("<Control-e>", self.save_file)
self.tk_root.bind_all("<Control-s>", self.save_file)
self.tk_root.protocol("WM_DELETE_WINDOW", lambda : self.close(False)) # user click on the [X] to close the window
menubar.add_cascade(label="File", menu=filemenu)
helpmenu = tk.Menu(menubar, tearoff=0)
helpmenu.add_command(label="About...", command=self.on_about)
menubar.add_cascade(label="Help", menu=helpmenu)
self.tk_root.config(menu=menubar)
# FigureCanvas
self.psd_figure = Figure(facecolor='beige')
self.canvas = FigureCanvas(self.psd_figure, master=self.tk_root)
self.canvas.show()
self.canvas.get_tk_widget().pack(side=tk.TOP, fill=tk.BOTH, expand=1)
self.toolbar = NavigationToolbar2TkAgg( self.canvas, self.tk_root)
self.toolbar.update()
self.canvas._tkcanvas.pack(side=tk.TOP, fill=tk.BOTH, expand=1)
self.axes = self.psd_figure.add_subplot(111)
self.axes.hold(False)
# StatusBar
self.statusbar_txt = tk.StringVar()
self.label=tk.Label(self.tk_root, bd=1, relief=tk.SUNKEN, anchor=tk.W,
textvariable=self.statusbar_txt,
font=('arial',12,'normal'))
self.statusbar_txt.set('Initialization...')
self.label.pack(fill=tk.X)
def __init__(self,master,size,dpi,model,featshape,direction='input'):
Figure.__init__(self,figsize=(size[0]/dpi,size[1]/dpi),dpi=dpi,facecolor='w',edgecolor='b',frameon=True,linewidth=0)
FigureCanvas(self,master=master)
self.master = master
self._dirty = True
self._model = model
self._feat = None
self._featrange = None
self._featshape = featshape
self._direction = direction
self._sorted = True
self._update_count = 0
self._ordering = None
self.add_subplot(111,axisbg='w')
def __init__(self, master):
self.amp_started = False
ttk.Frame.__init__(self, master)
self.master.title('Mushu')
self.pack()
self.available_amps = libmushu.get_available_amps()
frame = tk.Frame(self)
frame.pack(fill=tk.BOTH, expand=1)
self.label1 = ttk.Label(frame, text='Select Amplifier')
self.label1.grid(column=0, row=0, sticky='we')
self.amp_combobox = ttk.Combobox(
frame, values=[str(i) for i in self.available_amps])
self.amp_combobox.grid(column=0, row=1, sticky='we')
self.amp_combobox.bind("<<ComboboxSelected>>",
self.on_amplifier_selected)
self.label2 = ttk.Label(frame, text='Select Configuration Preset')
self.label2.grid(column=1, row=0, sticky='we')
self.config_combobox = ttk.Combobox(frame)
self.config_combobox.grid(column=1, row=1, sticky='we')
self.config_combobox.bind("<<ComboboxSelected>>",
self.onComboboxSelected)
self.label3 = ttk.Label(frame, text='Start/Stop Amplifier')
self.label3.grid(column=2, row=0, sticky='we')
self.start_stop_button = ttk.Button(
frame, text='Start', command=self.onStartStopButtonClicked)
self.start_stop_button.grid(column=2, row=1, sticky='we')
# set up the figure
fig = Figure()
self.canvas = FigureCanvas(fig, master=self.master)
self.canvas.get_tk_widget().pack(side=tk.TOP, fill=tk.BOTH, expand=1)
self.canvas.show()
self.axis = fig.add_subplot(111)
# self.PAST_POINTS = 256
self.PAST_POINTS = 5000 * 3
self.SCALE = 30000
self.channels = []
self.n_channels = 0
self.init_plot()
self.master.after_idle(self.visualizer)
def __init__(self, parent, width=8, height=8, dpi=100, **kwargs):
super().__init__(parent)
fig = Figure(dpi=dpi, **kwargs)
self.image = FigureCanvas(fig, master=self)
self.image._tkcanvas.pack(expand=1, fill=tkinter.BOTH)
#self.toolbar = NavigationToolbar2TkAgg(self.image, self)
#self.toolbar.update()
#self.toolbar.pack(expand=0)
self.axes = fig.add_subplot(111)
self.fig = fig
# We want the axes cleared every time plot() is called
self.axes.hold(False)
def __init__(self, master=None):
self.frame = tkinter.Frame(master)
self.frame.pack(padx=15, pady=15)
self.fig = matplotlib.figure.Figure(figsize=(6, 4), dpi=100)
self.ax = self.fig.add_subplot(111)
self.ax.plot(np.linspace(0, 4), np.sin(np.linspace(0, 4)))
self.canvas = FigureCanvas(self.fig, master=self.frame)
self.canvas.get_tk_widget().pack(side=tkinter.TOP,
fill=tkinter.BOTH,
expand=1)
self.mpl_toolbar = NavigationToolbar(self.canvas, master)
self.mpl_toolbar.update()
self.canvas._tkcanvas.pack(side=tkinter.TOP,
fill=tkinter.BOTH,
expand=1)
def __init__(self, waveforms, metadata, master=None):
Tk.Frame.__init__(self, master) # hack to make work in python2
self.pack()
self.figure = Figure(figsize=(8, 8), dpi=100)
self.axs = []
for iPlot in range(16):
self.axs.append(self.figure.add_subplot(4, 4, iPlot + 1))
self.canvas = FigureCanvas(self.figure, master=self)
self.canvas.show()
self.canvas.get_tk_widget().pack(side=Tk.TOP, fill=Tk.BOTH, expand=1)
self.toolbar = NaviationToolbar(self.canvas, self)
self.toolbar.update()
self.canvas._tkcanvas.pack(side=Tk.TOP, fill=Tk.BOTH, expand=1)
self.draw_fft(waveforms, metadata)
def __init__(self,master,size,dpi,layer,xaxis=True):
Figure.__init__(self,figsize=(size[0]/dpi,size[1]/dpi),dpi=dpi,facecolor='w',edgecolor='b',frameon=True,linewidth=0)
FigureCanvas(self,master=master)
self.master = master
self.dirty = True
self.layer = layer
self.xaxis = xaxis
self._indices = None
self._fold = 'train'
self._H = None
self._S = None
self._timerange = None
left = 0.08; width = 0.89-left
#left = 0.016; width = 0.89-left
bottom = 0.12; height=0.82-bottom
rect_plot = [left,bottom,width,height]
rect_hist = [left+width+.005,bottom,1-.005-width-left,height]
self.plot = self.add_axes(rect_plot,axisbg='w')
self.hist = self.add_axes(rect_hist,axisbg='w')
def show_clipped_image(self): # Display the clipped image
if self.display.winfo_exists():
self.display.grid_forget()
self.display.destroy()
self.display = ttk.Frame(self)
self.display.grid(row=0,
column=2,
columnspan=4,
rowspan=3,
sticky='nsew')
frame = self.display
fp = self.msfile
self.fig = plt.Figure(figsize=(8, 4), dpi=100)
self.ax = self.fig.add_subplot(111)
self.canvas_preview = FigureCanvas(self.fig, frame)
fp = 'OutputImages/' + self.outname.get() + '.tif'
self.dataset = gdal.Open(fp)
self.band = self.dataset.GetRasterBand(1)
self.geotransform = self.dataset.GetGeoTransform()
self.arr = self.band.ReadAsArray()
self.ax.imshow(self.arr, cmap='terrain')
self.ax.axis('equal')
self.ax.set(title="", xticks=[], yticks=[])
self.ax.spines["top"].set_visible(False)
self.ax.spines["right"].set_visible(False)
self.ax.spines["left"].set_visible(False)
self.ax.spines["bottom"].set_visible(False)
self.canvas_preview.draw()
self.fig.subplots_adjust(left=0.0, bottom=0.0, right=1.0, top=1.0)
#self.canvas_preview.get_tk_widget().pack(side='top', fill='both', expand = 1)
self.toolbar = NavigationToolbar2Tk(self.canvas_preview, frame)
self.toolbar.update()
self.canvas_preview.get_tk_widget().pack(side='top',
fill='both',
expand=1)
def __init__(self, chatbot_name, username, init_emotional_state,
init_emotional_history):
# initialise variables
self.chatbot_name = chatbot_name
self.username = username
self.user_input = None
# initialize all ui elements
self.dgm = DiagramManager(init_emotional_state, init_emotional_history)
self.root = tk.Tk()
self.menubar = tk.Menu()
self.file_menu = tk.Menu(tearoff=0)
self.debug_menu = tk.Menu(tearoff=0)
self.load_menu = tk.Menu(tearoff=0)
self.response_menu = tk.Menu(tearoff=0)
self.chat_out = tk.Text(self.root, width=40, state="disabled")
self.chat_in = tk.Entry(self.root)
self.log = tk.Text(self.root, width=40, state="disabled")
self.info_label = tk.Label(
self.root, text="EIKA v.0.0.1, Marcel Müller, FH Dortmund ")
self.send_button = tk.Button(
self.root,
text="Send",
command=lambda: self.forward_user_intent(
intent="get_response", user_input=self.chat_in.get()))
self.diagram_frame = tk.Frame(self.root)
self.diagram_canvas = FigureCanvas(self.dgm.get_diagrams(),
master=self.diagram_frame)
self.chat_in.bind(
sequence='<Return>',
func=lambda event: self.forward_user_intent(
intent="get_response", user_input=self.chat_in.get()))
# create frame and menu
self.create_frame(self.chatbot_name)
self.pack_widgets()
# set subscriber list (implements observer pattern)
self.controller = None
self.subscribers = set()
def __init__(self,
infilename,
sampleMax=None,
fullADCRange=False,
master=None):
Tk.Frame.__init__(self, master) # hack to make work in python2
self.pack()
self.figure = Figure(figsize=(8, 8), dpi=100)
self.axs = []
for iPlot in range(16):
self.axs.append(self.figure.add_subplot(4, 4, iPlot + 1))
self.canvas = FigureCanvas(self.figure, master=self)
self.canvas.show()
self.canvas.get_tk_widget().pack(side=Tk.TOP, fill=Tk.BOTH, expand=1)
self.toolbar = NaviationToolbar(self.canvas, self)
self.toolbar.update()
self.canvas._tkcanvas.pack(side=Tk.TOP, fill=Tk.BOTH, expand=1)
self.draw_trace(infilename,
sampleMax=sampleMax,
fullADCRange=fullADCRange)
def cb2():
L = 10 # Breite der Skala
def cs1(val):
global ua
ua = cs1.get() # Obergrenze für alpha in der Gamma Verteilung
ct1.delete('1.0', tk.END)
ct1.insert(tk.END, ua)
cb2plot()
def cs2(val):
global ub
ub = cs2.get() #Obergrenze für beta in der Gamma Verteilung
ct2.delete('1.0', tk.END)
ct2.insert(tk.END, ub)
cb2plot()
def cs3(val):
#global Alpha
Alpha = cs3.get()
ct3.delete('1.0', tk.END)
ct3.insert(tk.END, Alpha)
cb2plot()
def cs4(val):
#global Beta
Beta = cs4.get()
ct4.delete('1.0', tk.END)
ct4.insert(tk.END, Beta)
cb2plot()
def cs5(val):
#global Lambda
Lambda = cs4.get()
ct5.delete('1.0', tk.END)
ct5.insert(tk.END, Lambda)
cb2plot()
# Definieren der Wahrscheinlichkeitsfunktionen
def Poisson(k, mu):
P = ss.poisson.pmf(k, mu)
return P
def Gamma(p, al, bet):
G = ss.gamma.pdf(p, al) * np.exp(-(bet - 1) * p) * bet**al
return G
# Bestimmen der Aposteriori-Funktion
def Posteriori(x):
a = np.arange(0, 100000)
Int = integrate.simps(Poisson(a, Lambda) * Gamma(a, Alpha, Beta))
Post = 1 / Int * Poisson(x, Lambda) * Gamma(x, Alpha, Beta)
return Post
def Maxposteriori():
# Bestimmen des Maximums der Aposteriori
global MaxX
global MaxY
global limit
MaxX = 0
MaxY = Posteriori(0)
for i in np.arange(0, L + 1):
TestY = Posteriori(i)
if TestY >= MaxY:
MaxX = i
MaxY = TestY
else:
break
# Definieren des Wertes, ab dem drei Punkte gefittet werden
if MaxX == 0:
StartX = 1
elif MaxX == 1:
StartX = 1
else:
StartX = MaxX - 1
# ein paar Nebensächlichkeiten
i = 0
limit = MaxY / 100 # maximaler zugelassener Abstand zwischen Fit und Aposteriori
List = []
List2 = []
"""
Bestimmen aller Parameter-Kombinationen für Gamma, die auf mindestens zwei von drei ausgewählten
Punkten identisch (+/- Toleranz) mit der Aposteriori ist
Warnung einfügen
Mit eingabe
parameter bestimmung evtl.
"""
while i <= 3:
xValue = StartX + i
Checker = Posteriori(xValue)
if i == 0:
for a in np.arange(0.1, ua,
0.1): # Obergrenze alpha posteriori
for b in np.arange(0.1, ub,
0.1): #Obergrenze beta posteriori
if abs(Gamma(xValue, a, b) - Checker) < limit:
List.append((a, b))
else:
for item in List:
a = item[0]
b = item[1]
if abs(Gamma(xValue, a, b) - Checker) < i * limit:
List2.append(item)
i += 1
"""
Auswählen der Parameter-Kombination, die die meisten Punkte der Aposteriori schneidet
(+/- Toleranz)
"""
Counter = {}
for item in List2:
Counter[item] = Counter.get(item, 0) + 1
return Counter
def sort(x):
Counter = Maxposteriori()
return Counter[x]
def BestL():
Counter = Maxposteriori()
BestList = sorted(Counter, key=sort, reverse=1)
for item in BestList:
ConjMax = 0
for i in np.arange(MaxX - 1, MaxX + 1, 0.1):
TestY = Gamma(i, item[0], item[1])
if TestY >= ConjMax:
ConjMax = TestY
if abs(ConjMax - MaxY) > limit:
BestList.remove(item)
Best = BestList[0]
return Best
def cb2plot():
# Globale Variablen definieren
global Lambda
global Beta
global Alpha
global ua
global ub
Lambda = cs4.get()
Beta = cs4.get()
Alpha = cs3.get()
ua = cs1.get()
ub = cs2.get()
#Aufrufen der Funktionen
Best = BestL()
# Plot in der Canvas des aw
plt.cla(
) # Löscht die aktuellen Plots aus dem Fenster, lässt dieses aber noch offen
ay = fig.add_subplot(111)
I = np.linspace(0, L, 10 * L + 1)
X = Poisson(I, Lambda)
Y = Gamma(I, Best[0], Best[1])
Z = Posteriori(I)
ay.plot(I, X, 'b-', label='priori')
ay.plot(I, Y, 'g-', label=Best)
ay.plot(I, Z, 'r-', label='posteriori')
ay.set_xlabel(
'Erfolgswahrscheinlich p') # Axenbeschriftung in x Richtung
ay.set_ylabel(
'Wahrscheinlichkeitsdichte') # Axenbeschriftung in y Richtung
ay.legend(loc='best')
ccb2.draw()
cb2w = tk.Tk() # Definition eines Auswahlfensters
cb2w.title("Gamma-Poisson Verteilung") # Beschriftung des Fensters
cb2w.geometry("1200x600") # Anpassung der Größe
# Canvas, Felds für den Plot
fig = plt.figure(figsize=(10, 5))
ccb2 = FigureCanvas(fig, master=cb2w)
L1 = tk.Label(cb2w, text="Obere Grenze für Alpha : ")
L2 = tk.Label(cb2w, text="Obere Grenze für Beta: ")
L3 = tk.Label(cb2w, text="Alpha: ")
L4 = tk.Label(cb2w, text="Beta: ")
L5 = tk.Label(cb2w, text="Lambda: ")
# Eingabeslider
cs1 = tk.Scale(master=cb2w, from_=0, to=50, orient=HORIZONTAL,
command=cs1) # Obere Grenze Alpha
cs2 = tk.Scale(master=cb2w, from_=0, to=50, orient=HORIZONTAL,
command=cs2) # Obere Grenze Beta
cs3 = tk.Scale(master=cb2w,
from_=0,
to=5,
resolution=0.01,
orient=HORIZONTAL,
command=cs3) # Alpha
cs4 = tk.Scale(master=cb2w,
from_=0,
to=5,
resolution=0.01,
orient=HORIZONTAL,
command=cs4) # Beta
cs5 = tk.Scale(master=cb2w,
from_=0,
to=5,
resolution=0.01,
orient=HORIZONTAL,
command=cs5) # Lambda command
#--> cs1-5 neu definieren
#Definition von Startwerten
cs1.set(5)
cs2.set(5)
cs3.set(1)
cs4.set(1)
cs5.set(4)
# Textfelder
ct1 = tk.Text(master=cb2w, height=1, width=10)
ct2 = tk.Text(master=cb2w, height=1, width=10)
ct3 = tk.Text(master=cb2w, height=1, width=10)
ct4 = tk.Text(master=cb2w, height=1, width=10)
ct5 = tk.Text(master=cb2w, height=1, width=10)
ccb2._tkcanvas.grid(row=0, column=0, columnspan=4)
# Zuweisung der Labels durch .grid()
L1.grid(row=2, column=0)
L2.grid(row=3, column=0)
L3.grid(row=4, column=0)
L4.grid(row=5, column=0)
L5.grid(row=6, column=0)
#Zuweisung der Scale durch .grid()
cs1.grid(row=2, column=1)
cs2.grid(row=3, column=1)
cs3.grid(row=4, column=1)
cs4.grid(row=5, column=1)
cs5.grid(row=6, column=1)
#Zuweisung der Scale durch .grid()
ct1.grid(row=2, column=2)
ct2.grid(row=3, column=2)
ct3.grid(row=4, column=2)
ct4.grid(row=5, column=2)
ct5.grid(row=6, column=2)
#Anfangsplot
cb2plot()
def cb1():
def binCo(n, k):
r = 1
j = 1
if k > (n / 2):
while j <= n - k:
r = r * (k + j)
j = j + 1 #j+=1
x = r / math.factorial(n - k)
else:
while j <= k:
r = r * ((n - k) + j)
j = j + 1 # j+=1
x = r / math.factorial(k)
return x
def BinDist(p, n, k):
P = binCo(n, k) * p**k * (1 - p)**(n - k)
return P
# Verschiedene apriori Verteilungen
def BetaDist(x, p, q):
Beta = ss.beta.pdf(x, p, q)
return Beta
def NorDist(x, m, s):
v = -0.5 * ((x - m) / s)**2
N = 1 / (s * np.sqrt(2 * np.pi)) * np.exp(v)
return N
def ExpDist(x, L):
v = -L * x
E = L * np.exp(v)
return E
# Definition eines numerische Integrals
def numInt(f, a, b, N):
x = np.linspace(a + (b - a) / (2 * N), b - (b - a) / (2 * N), N)
fx = f(x)
area = np.sum(fx) * (b - a) / N
return area
# Berechnung der apriori Verteilung (fürs plotten)
def konj(alpha1, beta1, HeadCount1, ThrowCount1):
alphapost1 = alpha1 + HeadCount1
betapost1 = beta1 + ThrowCount1 - HeadCount
return (alphapost1, betapost1)
def preDistribution(x, prDist):
u = sp.Symbol('u')
if prDist == 1:
X = BetaDist(x, alpha, beta)
elif prDist == 2:
X = NorDist(x, mu, sigma)
elif prDist == 3:
X = ExpDist(x, Lambda)
return X
# Berechnung der aposteriori Verteilung
def Distribution(x, prDist):
if prDist == 1:
X = BetaDist(x, alphapost, betapost)
return X
def wplot():
# Globale Variablen definieren
global priori
global alphapost
global betapost
z2 = 0.5
#Berechnung der posteriori Größen
alphapost, betapost = konj(alpha, beta, HeadCount, ThrowCount)
# Plot in der Canvas des aw
plt.cla()
ax = fig.add_subplot(111)
x = np.linspace(0, 1, num=200)
y = [preDistribution(i, 1) for i in x]
z = [Distribution(i, 1) for i in x]
ax.plot(x, y, 'b-', label='priori')
ax.plot(x, z, 'r-', label='posteriori')
ax.plot(z2, 0, 'g-', label='Median')
ax.set_xlabel(
'Erfolgswahrscheinlich p') # Axenbeschriftung in x Richtung
ax.set_ylabel(
'Wahrscheinlichkeitsdichte') # Axenbeschriftung in y Richtung
ax.legend(loc='best')
canvas.draw()
def cs1(val):
global ThrowCount
global s1max
s1max = s1.get()
ThrowCount = s1max
t1.delete('1.0', tk.END)
t1.insert(tk.END, ThrowCount)
wplot()
def cs2(val):
global HeadCount
HeadCount = s2.get()
t2.delete('1.0', tk.END)
t2.insert(tk.END, HeadCount)
wplot()
def cs3(val):
global alpha
alpha = s3.get()
t3.delete('1.0', tk.END)
t3.insert(tk.END, alpha)
wplot()
def cs4(val):
global beta
beta = s4.get()
t4.delete('1.0', tk.END)
t4.insert(tk.END, beta)
wplot()
aw = tk.Tk() # Definition eines Auswahlfensters
aw.title("Beta-Verteilung") # Beschriftung des Fensters
aw.geometry("1200x600") # Anpassung der Größe
# Canvas, Felds für den Plot
fig = plt.figure(figsize=(10, 5))
canvas = FigureCanvas(fig, master=aw)
L1 = tk.Label(aw, text="Anzahl : ")
L2 = tk.Label(aw, text="Anzahl eingetretenes Ereignis: ")
L3 = tk.Label(aw, text="Alpha: ")
L4 = tk.Label(aw, text="Beta: ")
# Eingabeslider
s1 = tk.Scale(master=aw, from_=0, to=1000, orient=HORIZONTAL,
command=cs1) # Anzahl an Ereignissen
s2 = tk.Scale(master=aw, from_=0, to=1000, orient=HORIZONTAL,
command=cs2) # Anzahl an eigetretenen Ereignissen
s3 = tk.Scale(master=aw,
from_=0,
to=5,
resolution=0.01,
orient=HORIZONTAL,
command=cs3) # Alpha
s4 = tk.Scale(master=aw,
from_=0,
to=5,
resolution=0.01,
orient=HORIZONTAL,
command=cs4) # Beta
#Definition von Startwerten
s1.set(500)
s2.set(250)
s3.set(0.5)
s4.set(0.5)
# Textfelder
t1 = tk.Text(master=aw, height=1, width=10)
t2 = tk.Text(master=aw, height=1, width=10)
t3 = tk.Text(master=aw, height=1, width=10)
t4 = tk.Text(master=aw, height=1, width=10)
canvas._tkcanvas.grid(row=0, column=0, columnspan=4)
# Zuweisung der Labels durch .grid()
L1.grid(row=2, column=0)
L2.grid(row=3, column=0)
L3.grid(row=4, column=0)
L4.grid(row=5, column=0)
#Zuweisung der Scale durch .grid()
s1.grid(row=2, column=1)
s2.grid(row=3, column=1)
s3.grid(row=4, column=1)
s4.grid(row=5, column=1)
#Zuweisung der Scale durch .grid()
t1.grid(row=2, column=2)
t2.grid(row=3, column=2)
t3.grid(row=4, column=2)
t4.grid(row=5, column=2)
#Anfangsplot
wplot()
def plot_gmpe_group_bias( params ):
from numpy import log, loadtxt, array, where
from matplotlib.figure import Figure
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg as FigureCanvas
freqs = [0.25, 0.5, 1.0, 2.0, 3.0, 5.0]
distances = [10, 15, 20, 25, 30]
try:
# create data structure to hold bias results
bias = {}
for dist in distances:
bias[dist] = []
for freq in freqs:
bias[freq] = []
# loop through all the directories
for d in os.listdir( params['root_dir'] ):
cwd = os.path.join( params['root_dir'], d )
if os.path.isdir( cwd ):
for freq in freqs:
filename = os.path.join(cwd, 'gmrotD50_%05.2fHz_plot.dat' % freq)
data = loadtxt(filename, delimiter=',' )
gmpe_mid = (data[:,2] + data[:,3]) / 2
log_bias = log(data[:,1] / gmpe_mid)
bias[freq].append(log_bias)
for dist in distances:
ind = where(data[:,0] == dist + 0.5)
gmpe_mid = (data[ind,2] + data[ind,3]) / 2
log_bias = log(data[ind,1] / gmpe_mid)
bias[dist].append(log_bias)
# make figure
for key in bias.keys():
if key in freqs:
# print key
fig = Figure()
canvas = FigureCanvas(fig)
ax = fig.add_subplot(111)
ax.set_title( 'log(sim/gmpe) vs. distance @ %s Hz' % key )
ax.set_xlabel('Distance (km)')
ax.set_ylabel('log(sim/gmpe)')
# plot horizontal line at 0
ax.axhline(y=0, color='black')
# plot bias and error bars
b = array(bias[key])
avgb = b.mean(axis=0)
minb = b.min(axis=0)
maxb = b.max(axis=0)
ylower = avgb - minb
yupper = maxb - avgb
ax.errorbar(data[:,0], avgb, yerr=[ylower,yupper], fmt='o', ecolor='g', capthick=2)
fig.savefig( os.path.join(params['root_dir'], 'dist_bias_%shz.pdf' % key ) )
if key in distances:
fig = Figure()
canvas = FigureCanvas(fig)
ax = fig.add_subplot(111)
ax.set_title('log(sim/gmpe) vs. period @ %s km' % key )
ax.set_xlabel('Period (s)')
ax.set_ylabel('log(sim/gmpe)')
# plot horizontal line at 0
ax.axhline(y=0, color='black')
b = array(bias[key])
b = b.reshape([b.size/len(freqs),len(freqs)])
# plot bias and error bars
avgb = b.mean(axis=0)
minb = b.min(axis=0)
maxb = b.max(axis=0)
ylower = avgb - minb
yupper = maxb - avgb
ax.errorbar(1./array(freqs), avgb, yerr=[ylower,yupper], fmt='o', ecolor='g', capthick=2)
fig.savefig(os.path.join(params['root_dir'], 'dist_freq_%skm.pdf' % key) )
except Exception as e:
print 'exception: %s' % str(e)
def __plot_gmpe_individual( name ):
try:
from numpy import loadtxt, exp
from matplotlib.figure import Figure
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg as FigureCanvas
fig = Figure()
canvas = FigureCanvas(fig)
data = loadtxt(name, delimiter=',')
# read data
bin_edges = data[:,0]
med_sim = data[:,1]
min_med_gmpe = data[:,2]
max_med_gmpe = data[:,3]
med_sig_gmpe = data[:,4]
ax = fig.add_subplot(111)
ax.fill_between(bin_edges, min_med_gmpe, max_med_gmpe, color='gray', alpha=0.4)
ax.loglog(bin_edges, med_sim, 'b')
ax.loglog(bin_edges, max_med_gmpe*exp(med_sig_gmpe), '--k')
ax.loglog(bin_edges, min_med_gmpe*exp(-med_sig_gmpe), '--k')
ax.set_xlim([1.0,30.0])
ax.set_xlabel( r'$R_{rup} (km) $' )
ax.set_ylabel( 'SA (g)' )
basename = name[:-4] # strip off file extension
fig.savefig( basename + '.pdf' )
except Exception as e:
print 'Unable to launch job due to error: %s' % e
return False
return True
def __prepare_parameters( self, cwd ):
from numpy import fromfile
par = {}
# read default parameters
try:
with open(os.path.join(self.params['root_dir'], 'params.txt'), 'r') as file:
temp = file.readlines()
for line in temp:
line = line.split()
if line:
key = line[0]
val = line[1]
par[key] = val
except IOError:
print '\tERROR: unable to read params.txt file.'
return False
# try reading the magnitude
try:
mw = self.__read_magnitude( cwd )
par.update(mw)
except IOError:
print '\tERROR: unable to find magnitude file.'
return False
# try getting the extent of the fault
try:
extent = self.__get_fault_extent( cwd, par )
par.update(extent)
except IOError:
print 'unable to determine fault extent. skipping model...'
return False
# copy necessary files
try:
# temporary until i get fortran codes implemented
shutil.copy( os.path.join(self.params['script_dir'], 'gmpe_calc.m'), cwd )
shutil.copy( os.path.join(self.params['script_dir'], 'ASK_2014_nga.m'), cwd )
shutil.copy( os.path.join(self.params['script_dir'], 'BSSA_2014_nga.m'), cwd )
shutil.copy( os.path.join(self.params['script_dir'], 'CB_2014_nga.m'), cwd )
shutil.copy( os.path.join(self.params['script_dir'], 'CY_2014_nga.m'), cwd )
except IOError:
print 'unable to copy necessary files.'
return False
# now write the parameters file
# when i get fortran routines, no reason to write file anymore
try:
with open(os.path.join(cwd, 'params.txt'), 'w') as file:
for k,v in par.iteritems():
file.write(k + ' ' + str(v) + '\n')
except IOError:
print 'unable to write to params.txt file'
return False
# made it through the gauntlet
return True
def __read_magnitude( self, cwd ):
import os
from numpy import fromfile, where
# try finding that file anywhere in the model directory
for root, dirs, files in os.walk( cwd ):
for name in files:
if name == 'mw':
mw = fromfile(os.path.join(root, name),'f')[-1]
return { 'mw' : mw }
raise IOError
def __get_fault_extent( self, cwd, par ):
import os
from numpy import fromfile, where, floor
nx = int(par['fltnx'])
nz = int(par['fltnz'])
psv = fromfile( os.path.join(cwd, 'out/psv'), 'f' ).reshape([nz,nx])
y,x = where( psv > 1.0 ) # returns inds where condition is true
strtx = x.min()
endx = x.max()
nflt = floor( (endx - strtx) / 2 )
if nflt < 0:
print 'negative fault length, something is wrong.'
raise ValueError
return { 'strtx' : strtx, 'nflt' : nflt }
self._emit('select', self.selected)
else:
self.selected = None
self.fig.canvas.draw_idle()
if __name__ == '__main__':
ncf = netcdf_file('KTLX_20100510_22Z.nc')
data = ncf.variables['Reflectivity']
lats = ncf.variables['lat']
lons = ncf.variables['lon']
stormcells = storm_loader('polygons.shp')
win = tk.Tk()
fig = Figure()
canvas = FigureCanvas(fig, master=win)
ax = fig.add_subplot(1, 1, 1)
raddisp = RadarDisplay(ax, lats, lons)
raddisp.update_display(data[0])
fig.colorbar(raddisp.im)
polycolls = Stormcells(ax, stormcells)
linecoll = Tracks(ax)
# Turn on the first frame's polygons
polycolls.toggle_polygons(0, True)
ax.autoscale(True)
ctrl_sys = ControlSys(fig, raddisp, data, polycolls, linecoll, stormcells)
win.wm_title("Embedding with Tk")
canvas.get_tk_widget().pack(side=tk.TOP, fill=tk.BOTH, expand=1)
class PageThree(tk.Frame):
"""Frame showing Data View and chop capabilities
"""
def __init__(self, parent, controller, **kwargs):
tk.Frame.__init__(self, parent) # call class parent
""" Initialize data members """
self.DA = DA
self.isSafeToUpdate = False
self.numViews = 2
self.deactList = list()
self.DVconfig = controller.DVconfig
""" Create label for frame """
#label = tk.Label(self, text="Data View", font=LARGE_FONT)
#label.pack(pady=10,padx=10)
""" Create button to go back to other frame """
#button1 = ttk.Button(self, text="Back to Home",
# command=lambda: controller.show_frame(StartPage))
#button1.pack()
""" Add menu item to load data """
filemenu = controller.filemenu
filemenu.insert_command(index=1,label="Load", command=self.load)
self.addMainFigure() # Add main figure area to frame
self.addDataWindow() # Add widgets for setting data window
self.addDataView() # Add widgets for setting data view
self.addChop() # Add chop button
self.addStat() # Add stat button
def addDeactivateList(self, listLike) :
""" Keep a list of deactivate-able widgets """
if isinstance(listLike, list) or isinstance(listLike, tuple) :
for item in listLike :
self.deactList.append(item)
else :
self.deactList.append(listLike)
def deactivateWidgets(self) :
for widget in self.deactList :
widget.configure(state='disabled')
def activateWidgets(self) :
if not self.DA.isLoaded :
return DataNotLoaded()
for widget in self.deactList :
widget.configure(state='normal')
def addDataView(self) :
""" Add widgets that control the view """
self.viewList = list(('No Data','No Data'))
""" Add View Widget Sub-Frames """
self.dataViewSubFrameList = list() # list of "subframes"
for frameNum in range(0,self.numViews) :
subFrame = viewWidgetGroupFrame(self, label="Data View "+str(frameNum))
subFrame.setEventHandler(self.viewChangeTrace)
subFrame.pack()
self.dataViewSubFrameList.append(subFrame)
""" Data View Index Selection """
self.altIdxSel = tk.StringVar(self)
self.altIdxSel.set("No data") # default value
"""
self.altIdxSelW = tk.OptionMenu(self, self.altIdxSel, "No Data" )
self.altIdxSelW.configure(state="disabled")
self.altIdxSelW.pack()
self.altIdxSel.trace('w', self.viewChangeTrace) # set up event
self.addDeactivateList(self.altIdxSelW)
"""
def addDataWindow(self) :
""" Data Window Size Widget """
self.dataWindowSizeWidgetLabel = tk.Label(self, text='View Size')
self.dataWindowSizeWidgetLabel.pack()
self.dataWindowSizeWidget = tk.Scale(self, from_=1, to=10, resolution=1,
orient="horizontal")
self.dataWindowSizeWidget.bind("<ButtonRelease-1>", self.updateEvent)
self.dataWindowSizeWidget.bind("<Button1-Motion>", self.updateEvent)
self.dataWindowSizeWidget.pack(fill=tk.X,expand=1)
""" Data Window Start Widget """
self.dataWindowStartWidgetLabel = tk.Label(self, text='View Start')
self.dataWindowStartWidgetLabel.pack()
self.dataWindowStartWidget = tk.Scale(self, from_=0, to=10, resolution=1,
orient="horizontal")
self.dataWindowStartWidget.bind("<ButtonRelease-1>", self.updateEvent)
self.dataWindowStartWidget.bind("<Button1-Motion>", self.updateEvent)
self.dataWindowStartWidget.pack(fill=tk.X,expand=1)
def addMainFigure(self) :
""" Add main figure area """
self.fig = plt.figure(figsize=(5,4), dpi=100)
self.ax = self.fig.add_subplot(111)
self.ax.set_title('No data')
self.fig.canvas.draw()
self.canvas = FigureCanvas(self.fig, self)
""" Set up callback from canvas draw events, i.e. pan/zoom """
#self.cid1 = self.fig.canvas.mpl_connect('draw_event', self.updateFromCavas)
#self.cid1 = self.fig.canvas.mpl_connect('button_release_event', self.updateFromCavas)
#TODO animation
self.canvas.draw()
self.canvas.get_tk_widget().pack(side=tk.BOTTOM, fill=tk.BOTH, expand=True)
self.canvas._tkcanvas.pack(side=tk.TOP, fill=tk.BOTH, expand=True)
def addChop(self) :
chopBW = tk.Button(self, text="Chop", command=self.doChop)
chopBW.pack()
self.chopButtonW = chopBW
def addStat(self) :
statBW = tk.Button(self, text="Stats", command=self.doStat)
statBW.pack()
self.statButtonW = statBW
def postLoad(self) :
""" Things to run after loading a new DataAnalyser object. """
debug("postLoad: get current view from DA...")
viewList = self.DA.getView() # retrieve the default view after load
debug("postLoad: get labels from DA...")
self.updateLabels() # get new data types from data loaded
self.setAltIndex('index')
self.setView(viewList) # configure GUI to reflect new data
self.isSafeToUpdate = True
debug("postLoad: isSafeToUpdate:"+str(self.isSafeToUpdate))
""" now, set the window """
#TODO use data values instead of index values
limitDict=self.DA.getIndexLimits()
maxSize, minVal = ( limitDict['max'] , limitDict['min'] )
#print( "DEBUG: postLoad: maxSize: "+str(maxSize) )
#print( "DEBUG: postLoad: minValue: "+str(minVal) )
self.setWindow( minVal=minVal, start=0,
maxSize=maxSize, size=int(maxSize/2)) # reset the GUI window
self.updateEvent(None) # update GUI
def setWindow(self, minVal=0, start=0, maxSize=10, size=10) :
""" set the GUI values that correspond to the window """
debug("DEBUG: setWindow: %s, start: %s, maxSize: %s, size: %s"
,minVal, start, maxSize, size )
self.dataWindowSizeWidget.config(from_=1, to=maxSize-start+1)
self.dataWindowSizeWidget.set(size)
self.dataWindowStartWidget.config(from_=minVal, to=maxSize-size+1)
self.dataWindowStartWidget.set(start)
def load(self, *args, **kwargs) :
""" catch all load method
Currently, the only implemented mode is CSV file data.
"""
self.isSafeToUpdate = False
name = filedialog.askopenfilename()
self.loadFileData(path=name, *args, **kwargs)
def loadFileData(self, path=None, *args, **kwargs) :
""" Show a dialog to select a file and load it. """
if path is None:
raise TypeError("loadFileData: path option is required")
print("Got filename:" +path)
loadData(path, *args, **kwargs)
self.postLoad()
def updateLabels(self) :
""" Update labels from the DataAnalyser object
Call whenever DA is loaded/changed.
"""
#print("DEBUG: updateLabels: isSafeToUpdate:", self.isSafeToUpdate)
if not self.DA.isLoaded :
return DataNotLoaded()
newLabels = DA.getLabels()
#debug("DEBUG: got label list from DA: "+str(newLabels))
for viewSubFrame in self.dataViewSubFrameList:
viewSubFrame.setOptionsList(newLabels)
""" re-enable widgets """
self.activateWidgets()
def updateFromCavas(self, event) :
""" Called when view is changed using figure canvas area. """
""" Get the figure axis limits """
figMinX, figMaxX = self.ax.get_xlim()
debug('Got interval from MPL axis:'+str((figMinX,figMaxX)))
""" Set the current window to match """
#TODO
def viewChangeTrace(self, *args):
"""View is changed, make proper updates downward."""
debug("viewChange: isSafeToUpdate:"+str(self.isSafeToUpdate))
if not self.isSafeToUpdate :
#print("DEBUG: viewChangeTrace: not safe, returning")
return
"""Do other updates"""
self.updateEvent(None)
def setView(self, viewList) :
""" Set the GUI representation of the current data view
Takes a "view" object and sets the GUI so that it matches.
"""
self.isSafeToUpdate = False
self.viewList = viewList
for view,subFrame in zip(viewList,self.dataViewSubFrameList) :
debug("DataViewApp: setView: "+str(view))
subFrame.disable()
subFrame.setView(view)
subFrame.enable()
def setAltIndex(self, newIdx):
""" Set the GUI presentation of alt index """
self.isSafeToUpdate = False
self.altIdxSel.set(newIdx)
def updateEvent(self, event):
""" Change/Update data view when user requests a change.
Call this whenever the user makes a change to view values.
"""
debug("updateEvent: called, event:"+str(event))
if not self.DA.isLoaded :
return DataNotLoaded()
DA = self.DA
""" Set window from interface settings """
newWinSize = self.dataWindowSizeWidget.get()
newWinStart = self.dataWindowStartWidget.get()
limitDict=self.DA.getIndexLimits()
debug("DEBUG: updateEvent: got limits: "+str(limitDict))
maxSize, minVal = ( limitDict['max'] , limitDict['min'] )
self.setWindow( minVal=minVal, start=newWinStart,
maxSize=maxSize, size=newWinSize )
""" Set views from interface settings """
newViewList = list()
for subFrame in self.dataViewSubFrameList :
newView = subFrame.getView()
debug("updateEvent: newView: "+str(newView))
if newView is not None :
"""If view frame returns None, don't add to list."""
newViewList.append(newView)
""" set index """
try :
pass
#DA.setAltIndexColumn(self.altIdxSel.get())
#TODO
except Exception as e:
warn('updateEvent: Failed to set altnernate index, ignoring selection')
print(e)
else :
""" just leave it set to index """
pass
DA.setView( viewList=newViewList, windowStart=newWinStart, windowSize=newWinSize,
windowType='index' )
"""Redraw the plot"""
dfList = self.DA.getViewData()
#print("DEBUG: updateEvent: got updated data:", df.colums.tolist())
ax = self.ax
ax.clear()
xlabelList, ylabelList = list(), list()
for df in dfList :
"""draw all df data as x,y data"""
(xlabel, ylabel) = df.columns.tolist()
ax.plot(df[xlabel].values, df[ylabel].values, 'o-')
"""store labels"""
xlabelList.append(xlabel)
ylabelList.append(ylabel)
"""Set labels"""
newXlabel, newYlabel = str(), str()
xlabelOverride = self.DVconfig.get('xlabel')
ylabelOverride = self.DVconfig.get('ylabel')
"""Remember, configer doesn't hold native objects"""
debug("Plotting: xlabelOverride: %s" % xlabelOverride)
debug("Plotting: xlabelOverride eq None: %s" % (xlabelOverride == None))
if (xlabelOverride == None) or (ylabelOverride == None) :
"""Write the labels for all data"""
debug("Plotting: Label overrides OFF")
sep = "\n"
newXlabel = sep.join( xlabelList )
newYlabel = sep.join( ylabelList )
debug("new xlabel: %s" % newXlabel)
else :
"""the labels"""
debug("Plotting: Label overrides ON")
newXlabel = xlabelOverride
newYlabel = ylabelOverride
ax.set_xlabel(newXlabel)
ax.set_ylabel(newYlabel)
self.fig.canvas.draw()
""" Show Statistics """
#self.showStats()
def showStats(self):
""" Get and report statsistics for the current view """
quantiles = self.DVconfig.get('statQuantiles')
statsList = self.DA.getStats( quantiles )
dirpath = self.DVconfig.get('saveCDFDir')
prefix = self.DVconfig.get('statFilePrefix')
for statDF in statsList :
fmt = self.DVconfig.get('statFileFmt')
cols = ','.join(map(str,statDF.columns))
start,end = self.DA.getStartEnd()
filename = prefix + "_{},{}-{}".format(cols,start,end) + fmt
pathname = os.path.join( dirpath , filename )
statDF.to_csv(pathname)
for stats in statsList:
print("Data View Statistics:")
print(stats)
def doChop(self) :
self.saveViewPlot()
directory=pathlib.PurePath(os.path.curdir)
chopConf = self.DVconfig.get('chopOpts')
debug('chopConf:'+str(chopConf))
debug('dict(chopConf):'+str(dict(chopConf)))
self.DA.chop(dirpath=directory, **dict(chopConf))
def saveViewPlot(self) :
fig = self.fig # Get figure
start,end = self.DA.getStartEnd() # Get view range
dirpath = self.DVconfig.get('savePlotDir')
prefix = self.DVconfig.get('savePlotPrefix')
viewList = self.DA.getView()
viewStr = ','.join(map(lambda x: ','.join(map(str,x)) if isinstance(x,tuple) else str(x), viewList))
filename = prefix + "_{vl},{start}-{end}".format(
start=start,end=end, vl=viewStr
) + ".pdf"
pathname = os.path.join( dirpath , filename )
fig.savefig(pathname) # Save plot
def doStat(self) :
""" Do actions for "stats" button
"""
# First, show stats on STDOUT
self.showStats()
# Then, save the current view plot
self.saveViewPlot()
# Next, make a CDF plot for all the visible data
num_bins = self.DVconfig.get('saveCDFbins')
cdfInfoLst = self.DA.getCDFall(num_bins=num_bins) # get CDF info from DA
prefix = self.DVconfig.get('saveCDFprefix')
dirpath = self.DVconfig.get('saveCDFDir')
for cdfInfoT in cdfInfoLst :
i = cdfInfoLst.index(cdfInfoT)
label, cdf, counts, bin_edges = cdfInfoT
start,end = self.DA.getStartEnd()
filename = prefix +"_{},{}-{},{}.pdf".format(label,start,end,i)
pathname = os.path.join( dirpath , filename )
fig = plt.figure() # mk new fig
plt.plot(bin_edges[1:], cdf/cdf[-1])
plt.xlabel("{} values".format(label))
plt.ylabel("Normalized Cumulative Sum (CDF)".format())
fig.savefig(pathname)
def cb2():
def cs1(val):
global ua
ua = cs1.get() # Obergrenze für alpha in der Gamma Verteilung
ct1.delete('1.0', tk.END)
ct1.insert(tk.END, ua)
cb2plot()
def cs2(val):
global ub
ub = cs2.get() #Obergrenze für beta in der Gamma Verteilung
ct2.delete('1.0', tk.END)
ct2.insert(tk.END, ub)
cb2plot()
def cs3(val):
#global Alpha
Alpha = cs3.get()
ct3.delete('1.0', tk.END)
ct3.insert(tk.END, Alpha)
cb2plot()
def cs4(val):
#global Beta
Beta = cs4.get()
ct4.delete('1.0', tk.END)
ct4.insert(tk.END, Beta)
cb2plot()
def cs5(val):
#global Lambda
Lambda = cs5.get()
ct5.delete('1.0', tk.END)
ct5.insert(tk.END, Lambda)
cb2plot()
# Definieren der Wahrscheinlichkeitsfunktionen
def cb2plot():
# Globale Variablen definieren
global Beta
global Alpha
global ua
global ub
global Sum
global postalpha
global postbeta
Sum = cs5.get()
Beta = cs4.get()
Alpha = cs3.get()
ua = cs1.get()
ub = cs2.get()
postalpha = alpha + Sum
postbeta = beta + n
#Aufrufen der Funktionen
Best = BestL()
# Plot in der Canvas des aw
plt.cla(
) # Löscht die aktuellen Plots aus dem Fenster, lässt dieses aber noch offen
ay = fig.add_subplot(111)
I = np.linspace(0, L, 10 * L + 1)
X = Poisson(I, Lambda)
Y = Gamma(I, Best[0], Best[1])
Z = Posteriori(I)
ay.plot(I, X, 'b-', label='priori')
ay.plot(I, Y, 'g-', label=Best)
ay.plot(I, Z, 'r-', label='posteriori')
if postalpha > 1:
ay.plot((postalpha - 1) / postbeta,
0,
'.',
markersize=10,
label='Modus (Posteriori)')
ay.plot(postalpha / postbeta,
0,
'.',
markersize=10,
label="Erwartungswert (Posteriori)")
ay.set_xlabel(
'Erfolgswahrscheinlich p') # Axenbeschriftung in x Richtung
ay.set_ylabel(
'Wahrscheinlichkeitsdichte') # Axenbeschriftung in y Richtung
ay.legend(loc='best')
ccb2.draw()
cb2w = tk.Tk() # Definition eines Auswahlfensters
cb2w.title("Gamma-Poisson Verteilung") # Beschriftung des Fensters
cb2w.geometry("1200x600") # Anpassung der Größe
# Canvas, Felds für den Plot
fig = plt.figure(figsize=(10, 5))
ccb2 = FigureCanvas(fig, master=cb2w)
L1 = tk.Label(cb2w, text="Obere Grenze für Alpha : ")
L2 = tk.Label(cb2w, text="Obere Grenze für Beta: ")
L3 = tk.Label(cb2w, text="Alpha: ")
L4 = tk.Label(cb2w, text="Beta: ")
L5 = tk.Label(cb2w, text="Lambda: ")
# Eingabeslider
cs1 = tk.Scale(master=cb2w, from_=0, to=50, orient=HORIZONTAL,
command=cs1) # Obere Grenze Alpha
cs2 = tk.Scale(master=cb2w, from_=0, to=50, orient=HORIZONTAL,
command=cs2) # Obere Grenze Beta
cs3 = tk.Scale(master=cb2w,
from_=0,
to=5,
resolution=0.01,
orient=HORIZONTAL,
command=cs3) # Alpha
cs4 = tk.Scale(master=cb2w,
from_=0,
to=5,
resolution=0.01,
orient=HORIZONTAL,
command=cs4) # Beta
cs5 = tk.Scale(master=cb2w,
from_=0,
to=5,
resolution=0.01,
orient=HORIZONTAL,
command=cs5) # Lambda command
#--> cs1-5 neu definieren
#Definition von Startwerten
cs1.set(10)
cs2.set(10)
cs3.set(1)
cs4.set(1)
cs5.set(4)
# Textfelder
ct1 = tk.Text(master=cb2w, height=1, width=10)
ct2 = tk.Text(master=cb2w, height=1, width=10)
ct3 = tk.Text(master=cb2w, height=1, width=10)
ct4 = tk.Text(master=cb2w, height=1, width=10)
ct5 = tk.Text(master=cb2w, height=1, width=10)
ccb2._tkcanvas.grid(row=0, column=0, columnspan=4)
# Zuweisung der Labels durch .grid()
L1.grid(row=2, column=0)
L2.grid(row=3, column=0)
L3.grid(row=4, column=0)
L4.grid(row=5, column=0)
L5.grid(row=6, column=0)
#Zuweisung der Scale durch .grid()
cs1.grid(row=2, column=1)
cs2.grid(row=3, column=1)
cs3.grid(row=4, column=1)
cs4.grid(row=5, column=1)
cs5.grid(row=6, column=1)
#Zuweisung der Scale durch .grid()
ct1.grid(row=2, column=2)
ct2.grid(row=3, column=2)
ct3.grid(row=4, column=2)
ct4.grid(row=5, column=2)
ct5.grid(row=6, column=2)
#Anfangsplot
cb2plot()
def cb1():
def wplot():
# Globale Variablen definieren
global priori
global alphapost
global betapost
#Berechnung der posteriori Größen
alphapost, betapost = konj(alpha, beta, HeadCount, ThrowCount)
# Plot in der Canvas des aw
plt.cla()
ax = fig.add_subplot(111)
x = np.linspace(0, 1, num=200)
y = [preDistribution(i, 1) for i in x]
z = [Distribution(i, 1) for i in x]
ax.plot(x, y, 'b-', label='priori')
ax.plot(x, z, 'r-', label='posteriori')
if alpha > 1:
if beta > 1:
ax.plot((alphapost - 1) / (alphapost + betapost - 2),
0,
'.',
markersize=12,
label='Modus (Posteriori)')
ax.set_xlabel(
'Erfolgswahrscheinlich p') # Axenbeschriftung in x Richtung
ax.set_ylabel(
'Wahrscheinlichkeitsdichte') # Axenbeschriftung in y Richtung
ax.legend(loc='best')
canvas.draw()
def cs1(val):
global ThrowCount
global s1max
s1max = s1.get()
ThrowCount = s1max
t1.delete('1.0', tk.END)
t1.insert(tk.END, ThrowCount)
wplot()
def cs2(val):
global HeadCount
HeadCount = s2.get()
t2.delete('1.0', tk.END)
t2.insert(tk.END, HeadCount)
wplot()
def cs3(val):
global alpha
alpha = s3.get()
t3.delete('1.0', tk.END)
t3.insert(tk.END, alpha)
wplot()
def cs4(val):
global beta
beta = s4.get()
t4.delete('1.0', tk.END)
t4.insert(tk.END, beta)
wplot()
aw = tk.Tk() # Definition eines Auswahlfensters
aw.title("Beta-Verteilung") # Beschriftung des Fensters
aw.geometry("1200x600") # Anpassung der Größe
# Canvas, Felds für den Plot
fig = plt.figure(figsize=(10, 5))
canvas = FigureCanvas(fig, master=aw)
L1 = tk.Label(aw, text="Anzahl : ")
L2 = tk.Label(aw, text="Anzahl eingetretenes Ereignis: ")
L3 = tk.Label(aw, text="Alpha: ")
L4 = tk.Label(aw, text="Beta: ")
# Eingabeslider
s1 = tk.Scale(master=aw, from_=0, to=1000, orient=HORIZONTAL,
command=cs1) # Anzahl an Ereignissen
s2 = tk.Scale(master=aw, from_=0, to=1000, orient=HORIZONTAL,
command=cs2) # Anzahl an eigetretenen Ereignissen
s3 = tk.Scale(master=aw,
from_=0,
to=5,
resolution=0.01,
orient=HORIZONTAL,
command=cs3) # Alpha
s4 = tk.Scale(master=aw,
from_=0,
to=5,
resolution=0.01,
orient=HORIZONTAL,
command=cs4) # Beta
#Definition von Startwerten
s1.set(500)
s2.set(250)
s3.set(0.5)
s4.set(0.5)
# Textfelder
t1 = tk.Text(master=aw, height=1, width=10)
t2 = tk.Text(master=aw, height=1, width=10)
t3 = tk.Text(master=aw, height=1, width=10)
t4 = tk.Text(master=aw, height=1, width=10)
canvas._tkcanvas.grid(row=0, column=0, columnspan=4)
# Zuweisung der Labels durch .grid()
L1.grid(row=2, column=0)
L2.grid(row=3, column=0)
L3.grid(row=4, column=0)
L4.grid(row=5, column=0)
#Zuweisung der Scale durch .grid()
s1.grid(row=2, column=1)
s2.grid(row=3, column=1)
s3.grid(row=4, column=1)
s4.grid(row=5, column=1)
#Zuweisung der Scale durch .grid()
t1.grid(row=2, column=2)
t2.grid(row=3, column=2)
t3.grid(row=4, column=2)
t4.grid(row=5, column=2)
#Anfangsplot
wplot()
for dimension in sorted( dimensionIndex.keys(), key = dimensionIndex.get ): dimensionCheck[ dimension ] = IntVar() Checkbutton( dimensionFrame, variable = dimensionCheck[ dimension ], fg = 'black' ).grid( row = pos, column = 1, padx = 10 ) Label( dimensionFrame, text = dimensionTranslation[ dimension ] + ':' ).grid( row = pos, column = 2, pady = 10, sticky = E ) dimensionEntry[ dimension ] = Label( dimensionFrame, width = 12, fg = 'black', bg = 'white', justify = CENTER, relief = SUNKEN ) dimensionEntry[ dimension ].grid( row = pos, column = 3, padx = 10, sticky = W ) dimensionScale[ dimension ] = Scale( dimensionFrame, label = 'Escala', from_ = 10, to = 1, length = 30, width = 10, sliderlength = 5, troughcolor = 'white' ) dimensionScale[ dimension ].grid( row = pos, column = 4, sticky = W ) pos += 1 # Canvas para exibição do grafico scroll = ttk.Scrollbar( window, orient = HORIZONTAL ) figure = Figure( dpi = 100, figsize = (5, 4) ) figure.subplots_adjust( left = 0.05, right = 0.9, top = 0.97, bottom = 0.05, hspace = 0.1 ) plotWidth = ( 400, 100 ) mplCanvas = FigureCanvas( figure, master = window ) mplCanvas.show() dataCanvas = mplCanvas.get_tk_widget() # Callback para deslocar o canvas da matplotlib com o slider (não ideal, procurando solução melhor) def move( mode, position, c = UNITS ): if float(position) < 0.0: position = 0.0 if float(position) > 1.0: position = 1.0 width = scroll.get()[1] - scroll.get()[0] space = 1.0 - width scroll.set( float(position) * space, float(position) * space + width ) scroll[ 'command' ] = move dataCanvas.grid( row = 5, column = 2, rowspan = 2, sticky = (N, S, E, W) ) scroll.grid( row = 7, column = 2, pady = 5, sticky = (N, E, W) ) # Espaço para configurações personalizadas
