def SimulacionEMA():
symbols = input("Input a symbol or many separated by comma (Input ALL to Simulate for all symbols): ")
if symbols.upper() == "ALL":
symbols = DatabaseActions.getAll()
else:
symbols = symbols.split(",")
for symbol in symbols:
historico = DatabaseActions.getHistoric(symbol)
SimulationEMA.simular(symbol,historico)
def GraphicsTechnicalAnalysis():
symbols = input("Input a symbol or many separated by comma(Input ALL to Calculate for all symbols): ")
if symbols.upper() == "ALL":
symbols = DatabaseActions.getAll()
else:
symbols = symbols.split(",")
for symbol in symbols:
historic = DatabaseActions.getHistoric(symbol)
TechnicalAnalysis.GraphicsStoch(historic, symbol, parameters)
def historico():
symbol = input("Input a symbol: ")
historico = DatabaseActions.getHistoric(symbol)
historicDF = {}
for key in historico:
historicDF[datetime.datetime.fromisoformat(key)] = historico[key]
df = pd.DataFrame.from_dict(historicDF,
orient='index').tail(50).rename(columns={
'o': 'Open',
'h': 'High',
'l': 'Low',
'c': 'Close'
})
op = input("¿Agregar RSI? S/N: ")
if op.lower() == 's':
titulo = 'RSI'
periodo = int(input("Ingrese el periodo: "))
RSI = RelativeStrengthIndex.RSI(historico, periodo)
df[titulo] = df.index.to_series().map(RSI)
op = input("¿Agregar EMA? S/N: ")
while op.lower() == 's':
titulo = input("Ingrese un titulo para la EMA: ")
periodo = int(input("Ingrese el periodo: "))
EMAS = ExponentialMovingAverage.EMA(historico, periodo)
df[titulo] = df.index.to_series().map(EMAS)
op = input("¿Agregar otra EMA? S/N: ")
print(df)
data = df.tail(30)
columns = list(data.columns)[4:]
fig = plt.figure()
fig.set_size_inches((20, 16))
ax_candle = fig.add_axes((0, 0.05, 1, 0.9))
ax_candle.xaxis_date()
if 'RSI' in columns:
ax_candle = fig.add_axes((0, 0.30, 1, 0.7))
ax_rsi = fig.add_axes((0, 0.05, 1, 0.2), sharex=ax_candle)
ax_rsi.set_ylabel("(%)")
ax_rsi.plot(data.index, [70] * len(data.index), label="overbought")
ax_rsi.plot(data.index, [30] * len(data.index), label="oversold")
ax_rsi.plot(data.index, data["RSI"], label="RSI")
ax_rsi.legend(loc="center left")
ohlc = []
for date, row in data.iterrows():
Open, High, Low, Close = row[:4]
ohlc.append([date2num(date), Open, High, Low, Close])
for column in columns:
if column != 'RSI':
ax_candle.plot(data.index, data[column], label=column)
candlestick_ohlc(ax_candle, ohlc, colorup="g", colordown="r")
ax_candle.legend()
plt.show()