def setup_plot(self, plot_title, kbars):
import finplot as fplt
kbars = kbars.reset_index().rename(columns={'ts': 'time'})
# adopt TWSE style
fplt.display_timezone = gettz(self._exchange.brokerage.TIMEZONE)
fplt.candle_bull_color = '#ef5350'
fplt.candle_bull_body_color = fplt.candle_bull_color
fplt.candle_bear_color = '#26a69a'
fplt.volume_bull_color = '#f7a9a7'
fplt.volume_bull_body_color = fplt.volume_bull_color
fplt.volume_bear_color = '#92d2cc'
main_ax, rsi_ax, macd_ax = fplt.create_plot(plot_title, rows=3)
fplt.candlestick_ochl(kbars[['time', 'open', 'close', 'high', 'low']],
ax=main_ax)
fplt.volume_ocv(kbars[['time', 'open', 'close', 'volume']],
ax=main_ax.overlay())
fplt.plot(kbars['time'], kbars['rsi'], ax=rsi_ax, legend='RSI')
fplt.set_y_range(0, 100, ax=rsi_ax)
fplt.add_band(self.MIN_RSI, self.MAX_RSI, ax=rsi_ax)
fplt.volume_ocv(kbars[['time', 'open', 'close', 'macd_hist']],
ax=macd_ax,
colorfunc=fplt.strength_colorfilter)
fplt.plot(kbars['time'], kbars['macd'], ax=macd_ax, legend='MACD')
fplt.plot(kbars['time'],
kbars['macd_signal'],
ax=macd_ax,
legend='Signal')
return fplt
def change_asset(*args, **kwargs):
'''Resets and recalculates everything, and plots for the first time.'''
# save window zoom position before resetting
fplt._savewindata(fplt.windows[0])
symbol = ctrl_panel.symbol.currentText()
interval = ctrl_panel.interval.currentText()
ws.df = None
df = load_price_history(symbol, interval=interval)
ws.reconnect(symbol, interval, df)
# remove any previous plots
ax.reset()
axo.reset()
ax_rsi.reset()
# calculate plot data
indicators = ctrl_panel.indicators.currentText().lower()
data,price_data = calc_plot_data(df, indicators)
# some space for legend
ctrl_panel.move(100 if 'clean' in indicators else 200, 0)
# plot data
global plots
plots = {}
plots['price'] = fplt.candlestick_ochl(data['price'], ax=ax)
plots['volume'] = fplt.volume_ocv(data['volume'], ax=axo)
if data['ma50'] is not None:
plots['ma50'] = fplt.plot(data['ma50'], legend='MA-50', ax=ax)
plots['ma200'] = fplt.plot(data['ma200'], legend='MA-200', ax=ax)
plots['vema24'] = fplt.plot(data['vema24'], color=4, legend='V-EMA-24', ax=axo)
if data['rsi'] is not None:
ax.set_visible(xaxis=False)
ax_rsi.show()
fplt.set_y_range(0, 100, ax=ax_rsi)
fplt.add_band(30, 70, color='#6335', ax=ax_rsi)
plots['sar'] = fplt.plot(data['sar'], color='#55a', style='+', width=0.6, legend='SAR', ax=ax)
plots['rsi'] = fplt.plot(data['rsi'], legend='RSI', ax=ax_rsi)
plots['stoch'] = fplt.plot(data['stoch'], color='#880', legend='Stoch', ax=ax_rsi)
plots['stoch_s'] = fplt.plot(data['stoch_s'], color='#650', ax=ax_rsi)
else:
ax.set_visible(xaxis=True)
ax_rsi.hide()
# price line
ax.price_line = pg.InfiniteLine(angle=0, movable=False, pen=fplt._makepen(fplt.candle_bull_body_color, style='.'))
ax.price_line.setPos(price_data['last_close'])
ax.price_line.pen.setColor(pg.mkColor(price_data['last_col']))
ax.addItem(ax.price_line, ignoreBounds=True)
# restores saved zoom position, if in range
fplt.refresh()
def plotRsi(cls, df, ax, key="Close", period=1):
diff = df[key].diff().values
gains = diff
losses = -diff
with np.errstate(invalid='ignore'):
gains[(gains<0)|np.isnan(gains)] = 0.0
losses[(losses<=0)|np.isnan(losses)] = 1e-10 # we don't want divide by zero/NaN
n = 14
m = (n-1) / n
ni = 1 / n
g = gains[n] = np.nanmean(gains[:n])
l = losses[n] = np.nanmean(losses[:n])
gains[:n] = losses[:n] = np.nan
for i,v in enumerate(gains[n:],n):
g = gains[i] = ni*v + m*g
for i,v in enumerate(losses[n:],n):
l = losses[i] = ni*v + m*l
rs = gains / losses
df['rsi'] = 100 - (100/(1+rs))
df.rsi.plot(ax=ax, legend='RSI')
fplt.set_y_range(0, 100, ax=ax)
fplt.add_band(30, 70, ax=ax)