def add_selection_button():
is_unique = True
elements = listbox.get(0, listbox.size())
for i in elements:
if i == variable.get():
is_unique = False
if is_unique:
listbox.insert(END, names1.get(names1.curselection()))
instrumentID = backend.getInstrumentId(
names1.get(names1.curselection()))
instrument = backend.getInstrumentById(instrumentID)
symbol = instrument["symbol"]
global time_frame
time_frame = s.get()
instrument_data = backend.getMarketData(instrumentID, time_frame)
global plot_graph
plot_graph.append(
a.plot(
list(
range((instrument_data["currentEpoch"]) + 1 -
len(instrument_data["price"]),
instrument_data["currentEpoch"] + 1)),
instrument_data["price"]))
title.append(names1.get(names1.curselection()) + '[' + symbol + ']')
a.set_title(', '.join(title))
dataPlot.draw()
color = plot_graph[listbox.size() - 1][0].get_color()
listbox.itemconfig(listbox.size() - 1, {'bg': color})
change_time_frame()
def change_time_frame():
global time_frame
global plot_graph
elements = listbox.get(0, listbox.size())
count = 0
for i in elements:
plot_graph[count][0].remove()
instrumentID = backend.getInstrumentId(i)
time_frame = s.get()
instrument_data = backend.getMarketData(instrumentID, time_frame)
color = plot_graph[count][0].get_color()
plot_graph[count] = (a.plot(list(
range((instrument_data["currentEpoch"]) + 1 -
len(instrument_data["price"]),
instrument_data["currentEpoch"] + 1)),
instrument_data["price"],
color=color))
count += 1
a.set_xlim(instrument_data['currentEpoch'] - time_frame,
instrument_data['currentEpoch'])
maxvalue = 0
minvalue = 10000
for i in plot_graph:
if max(i[0].get_ydata()) > maxvalue:
maxvalue = max(i[0].get_ydata())
if min(i[0].get_ydata()) < minvalue:
minvalue = min(i[0].get_ydata())
if len(plot_graph) > 1:
a.set_ylim(minvalue - (minvalue * 0.05),
maxvalue + (maxvalue * 0.05))
else:
a.set_ylim(minvalue, maxvalue)
dataPlot.draw()
def expo_moving_avg_button():
if 'selected' in b212.state():
index = backend.getInstrumentId(names1.get(names1.curselection()))
market_data = backend.getMarketData(index, time_frame)
expo_moving_avg = backend.expMovingAverage(market_data, 1)
plot_graph.append(
a.plot(
list(
range((market_data["currentEpoch"]) + 1 -
len(expo_moving_avg),
market_data["currentEpoch"] + 1)), expo_moving_avg))
else:
plot_graph[2].pop(0).remove()
dataPlot.draw()
def expo_correlation_pair_button():
if 'selected' in b242.state():
index = backend.getInstrumentId(names1.get(names1.curselection()))
market_data = backend.getMarketData(index, time_frame)
expo_moving_avg = backend.expRollingCorrelation(
["Blank River", "Dew Iceberg"], time_frame)
plot_graph.append(
a.plot(
list(
range((market_data["currentEpoch"]) + 1 -
len(expo_moving_avg),
market_data["currentEpoch"] + 1)), expo_moving_avg))
else:
plot_graph[8].pop(0).remove()
dataPlot.draw()
def expo_standard_deviation_button():
if 'selected' in b222.state():
index = backend.getInstrumentId(names1.get(names1.curselection()))
market_data = backend.getMarketData(index, time_frame)
expo_moving_avg = backend.expMovingStdDev(market_data, 1)
plot_graph.append(
a.plot(
list(
range((market_data["currentEpoch"]) + 1 -
len(expo_moving_avg),
market_data["currentEpoch"] + 1)), expo_moving_avg))
a.set_ylim(0, 10)
else:
plot_graph[4].pop(0).remove()
dataPlot.draw()
def autocorrelation_button():
if 'selected' in b231.state():
index = backend.getInstrumentId(names1.get(names1.curselection()))
market_data = backend.getMarketData(index, time_frame)
expo_moving_avg = backend.rangeAutocorrelation(market_data, 10)
print(expo_moving_avg)
a.set_ylim(-1, 1)
a.set_xlim(4321, 4334)
plot_graph.append(
a.plot(
list(
range((market_data["currentEpoch"]) + 1 -
len(expo_moving_avg),
market_data["currentEpoch"] + 1)), expo_moving_avg))
else:
plot_graph[5].pop(0).remove()
dataPlot.draw()