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TuanScientist
commited on
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df112e3
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Parent(s):
Duplicate from TuanScientist/BTCforecasting
Browse files- .gitattributes +35 -0
- Bitcoin Historical Data - Investing.com.csv +0 -0
- README.md +14 -0
- app.py +55 -0
- lightning_logs/hello.txt +0 -0
- requirements.txt +7 -0
.gitattributes
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Bitcoin Historical Data - Investing.com.csv
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The diff for this file is too large to render.
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README.md
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---
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title: BTCforecasting
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emoji: 🦀
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colorFrom: red
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colorTo: blue
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sdk: gradio
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sdk_version: 3.35.2
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app_file: app.py
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pinned: false
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license: openrail
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duplicated_from: TuanScientist/BTCforecasting
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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app.py
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import gradio as gr
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import pandas as pd
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from neuralprophet import NeuralProphet, set_log_level
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import warnings
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set_log_level("ERROR")
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warnings.filterwarnings("ignore", category=UserWarning)
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url = "Bitcoin Historical Data - Investing.com.csv"
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df = pd.read_csv(url)
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df = df[["Date", "Price"]]
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df = df.rename(columns={"Date": "ds", "Price": "y"})
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df.fillna(method='ffill', inplace=True)
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df.dropna(inplace=True)
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m = NeuralProphet(n_forecasts=3,
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n_lags=36,
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changepoints_range=1, num_hidden_layers=6, daily_seasonality= False, weekly_seasonality = False, yearly_seasonality = True, ar_reg=True,
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n_changepoints=100, trend_reg_threshold=True, d_hidden=9, global_normalization=True, global_time_normalization=True, seasonality_reg=1, unknown_data_normalization=True,
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seasonality_mode="multiplicative", drop_missing=True,
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learning_rate=0.0314
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)
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m.fit(df, freq='M')
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future = m.make_future_dataframe(df, periods=3, n_historic_predictions=True)
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forecast = m.predict(future)
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def predict_vn_index(option=None):
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fig1 = m.plot(forecast)
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fig1_path = "forecast_plot1.png"
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fig1.savefig(fig1_path)
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# Add code to generate the second image (fig2)
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fig2 = m.plot_latest_forecast(forecast) # Replace this line with code to generate the second image
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fig2_path = "forecast_plot2.png"
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fig2.savefig(fig2_path)
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description = "Dự đoán được thực hiện bởi thuật toán AI học sâu (Deep Learning), và học tăng cường dữ liệu bởi đội ngũ AI Consultant. Dữ liệu được cập nhật mới sau 17h của ngày giao dịch."
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disclaimer = "Quý khách chỉ xem đây là tham khảo, công ty không chịu bất cứ trách nhiệm nào về tình trạng đầu tư của quý khách."
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return fig1_path, fig2_path, description, disclaimer
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if __name__ == "__main__":
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dropdown = gr.inputs.Dropdown(["BTC"], label="Choose an option", default="BTC")
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outputs = [
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gr.outputs.Image(type="filepath", label="Lịch sử BTC và dự đoán"),
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gr.outputs.Image(type="filepath", label="Dự đoán BTC cho 90 ngày tới"),
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gr.outputs.Textbox(label="Mô tả"),
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gr.outputs.Textbox(label="Disclaimer")
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]
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interface = gr.Interface(fn=predict_vn_index, inputs=dropdown, outputs=outputs, title="Dự báo BTC 90 ngày tới")
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interface.launch()
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lightning_logs/hello.txt
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requirements.txt
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gradio==3.32.0
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pandas==1.5.3
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neuralprophet==0.5.1
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matplotlib==3.7.1
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holidays==0.11.3.1
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torch==1.13.1
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pytorch-lightning==1.7.4
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