Ajuste do grafico
Browse files- __pycache__/stocks.cpython-311.pyc +0 -0
- app.py +24 -7
__pycache__/stocks.cpython-311.pyc
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Binary files a/__pycache__/stocks.cpython-311.pyc and b/__pycache__/stocks.cpython-311.pyc differ
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app.py
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@@ -217,17 +217,34 @@ class GradioInterface:
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def generate_simple_plot(self, bt_integration):
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# Implemente aqui a geração do gráfico usando matplotlib
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import matplotlib.pyplot as plt
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plt.
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plt.legend()
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return plt.gcf()
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# Configuração da interface completa
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pipeline = st.AnalysisPipeline()
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def generate_simple_plot(self, bt_integration):
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import matplotlib.pyplot as plt
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import matplotlib.dates as mdates
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plt.figure(figsize=(12, 6))
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# Get data feed from Backtrader
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datafeed = bt_integration.cerebro.datas[0]
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# Extract dates and closing prices
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dates = [datetime.fromordinal(int(date)) for date in datafeed.datetime.array]
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closes = datafeed.close.array
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# Plot
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plt.plot(dates, closes, label='Preço de Fechamento', linewidth=1.5)
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# Format dates
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plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m'))
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plt.gca().xaxis.set_major_locator(mdates.MonthLocator(interval=3))
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plt.gcf().autofmt_xdate() # Rotate dates
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# Add labels and grid
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plt.title("Desempenho Histórico - Evolução do Preço")
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plt.xlabel("Data")
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plt.ylabel("Preço (USD)")
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plt.legend()
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plt.grid(True, alpha=0.3)
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return plt.gcf()
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# Configuração da interface completa
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pipeline = st.AnalysisPipeline()
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