def DataGrid(xValues, yValues):
## setup window
dataGrid = Tk()
dataGrid.wm_title("Data")
## setup frame
frame = Frame(dataGrid)
frame.pack()
label = Label(dataGrid, text=("Showing %.0f data points" % len(xValues)), font=("Verdana", 12))
label.pack(pady=5, padx=10)
dataDict = {}
## iterate through time
for i in range(0, len(xValues)):
xVal = "%.2f" % float(xValues[i])
yVal = "%.2f" % float(yValues[i])
dataDict[xVal] = {"Time (s)": xVal, "Height (m)": yVal}
model = TableModel()
model.importDict(dataDict)
model.moveColumn(model.getColumnIndex("Time (s)"), 0)
table = TableCanvas(frame, model=model, editable=False)
table.createTableFrame()
## order by time
table.sortTable(columnName="Time (s)")
dataGrid.mainloop()
class App(Frame):
"""Basic test frame for the table"""
data = {}
table = TableCanvas
def __init__(self, parent=None):
self.table = TableCanvas
self.parent = parent
Frame.__init__(self)
self.main = self.master
self.main.title('Test')
# Initialize frame for the table
#f = Frame(self.main)
# Initialize the grid location of the table
#f.grid(row=0, column=1, sticky="nsew")
# no need to pack since we using grid geometry
# f.pack(fill=tk.Y,expand=-1,side = tk.LEFT)
# Create/Format table
#table = TableCanvas(f, cellwidth=60, data = test, cellbackgr='white', thefont=('Arial',12),rowheight=25, rowheaderwidth=30, rowselectedcolor='yellow', editable=True)
#Import table from csv
#table.importCSV('2017_Traffic_Volume_Flow.csv')
"""if importing table as dictionary, use this: data is of type dictionary
"""
# table = TableCanvas(f, cellwidth=60, data = data, cellbackgr='white',
# thefont=('Arial', 12), rowheight=25, rowheaderwidth=30,
# rowselectedcolor='yellow', editable=True)
#print (table.model.columnNames)
#table.show()
# sort the first column from highest to lowest (the sum of incident column)
# table.sortTable(reverse=1)
return
def importData(self, dataImport):
data = dataImport
model = TableModel()
model.importDict(data)
f = Frame(self.main)
self.table = TableCanvas(f,
model,
cellwidth=60,
cellbackgr='white',
thefont=('Arial', 12),
rowheight=25,
rowheaderwidth=30,
rowselectedcolor='yellow',
editable=True)
self.table.createTableFrame()
self.table.show()
f.grid(row=0, column=1, sticky="nsew")
def sortData(self, l, c):
self.table.sortTable(reverse=l, columnIndex=c)
self.table.redraw()
def DataGrid(xValues, yValues):
## setup window
dataGrid = Tk()
dataGrid.wm_title("Data")
## setup frame
frame = Frame(dataGrid)
frame.pack()
label = Label(dataGrid,
text=("Showing %.0f data points" % len(xValues)),
font=("Verdana", 12))
label.pack(pady=5, padx=10)
dataDict = {}
## iterate through time
for i in range(0, len(xValues)):
xVal = ("%.2f" % float(xValues[i]))
yVal = ("%.2f" % float(yValues[i]))
dataDict[xVal] = {"Time (s)": xVal, "Height (m)": yVal}
model = TableModel()
model.importDict(dataDict)
model.moveColumn(model.getColumnIndex('Time (s)'), 0)
table = TableCanvas(frame, model=model, editable=False)
table.createTableFrame()
## order by time
table.sortTable(columnName='Time (s)')
dataGrid.mainloop()
def classify_handler(self):
# Show Classification waiting window
wdw = Tkinter.Toplevel()
wdw.title('Classification Results ' + self.dropdown_value.get())
Tkinter.Label(wdw, text="Classification in Progress... Please wait", font=("Helvetica", 12), width=50, fg="blue").pack()
wdw.update()
wdw.deiconify()
# Predict and load results
resultModel = TableModel()
resultDict = speakerclassifier.classify_audio(self.currentFile, self.dropdown_value.get())
if len(resultDict) > 0 :
resultModel.importDict(resultDict)
wdw.destroy()
if len(resultDict) > 0 :
# Show Classification results in modal table window
wdw = Tkinter.Toplevel()
wdw.geometry('350x200+200+200')
wdw.title('Classification Results ' + self.dropdown_value.get())
tframe = Tkinter.Frame(wdw)
tframe.pack()
table = TableCanvas(tframe, model=resultModel, editable=False)
table.createTableFrame()
table.sortTable(columnName='Score (%)', reverse=True)
wdw.transient(self.root)
wdw.grab_set()
self.root.wait_window(wdw)
else :
tkMessageBox.showerror('Classification Results', 'There are currently no users in the System')
def classify_handler(self):
# Show Classification waiting window
wdw = Tkinter.Toplevel()
wdw.title('Classification Results ' + self.dropdown_value.get())
Tkinter.Label(wdw,
text="Classification in Progress... Please wait",
font=("Helvetica", 12),
width=50,
fg="blue").pack()
wdw.update()
wdw.deiconify()
# Predict and load results
resultModel = TableModel()
resultDict = speakerclassifier.classify_audio(
self.currentFile, self.dropdown_value.get())
if len(resultDict) > 0:
resultModel.importDict(resultDict)
wdw.destroy()
if len(resultDict) > 0:
# Show Classification results in modal table window
wdw = Tkinter.Toplevel()
wdw.geometry('350x200+200+200')
wdw.title('Classification Results ' + self.dropdown_value.get())
tframe = Tkinter.Frame(wdw)
tframe.pack()
table = TableCanvas(tframe, model=resultModel, editable=False)
table.createTableFrame()
table.sortTable(columnName='Score (%)', reverse=True)
wdw.transient(self.root)
wdw.grab_set()
self.root.wait_window(wdw)
else:
tkMessageBox.showerror(
'Classification Results',
'There are currently no users in the System')
inplace=True)
games_prediction = games_prediction[['Date', 'Visitor', 'Visitor Win%', 'Home', 'Home Win%']]
elos.to_csv('elos.csv', index=True)
games_prediction.to_csv('prediction.csv', index=False)
root = Tk()
root.title('NHL Elo Predictions')
root.geometry('800x600')
one = Label(root, text='NHL Elo Rankings', bg='blue', fg='white')
one.pack()
tframe = Frame(root)
tframe.pack()
table = TableCanvas(tframe, rowheaderwidth=0,
cellwidth=100, editable=False, width=325)
table.importCSV('elos.csv')
table.sortTable(columnName='Elo Rating', reverse=1)
colIndex = 1
table.show()
two = Label(root, text='Games Today', bg='blue', fg='white')
two.pack()
tframe2 = Frame(root)
tframe2.pack()
table2 = TableCanvas(tframe2, rowheaderwidth=0, editable=False, width=725)
table2.importCSV('prediction.csv')
table2.show()
root.mainloop()