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import pandas as pd
from scipy.signal import savgol_filter
import joblib
import numpy as np
import plotly.express as px
import gradio as gr
#desc='Better use Without Last Node for now (same as SMA Principle). For one-time prediction only. EURUSD TF 1D for now.'
titik1=gr.Number(label='Node 1 (Close)')
titik2=gr.Number(label='Node 2 (Close)')
titik3=gr.Number(label='Node 3 (Close)')
titik4=gr.Number(label='Node 4 (Close)')
titik5=gr.Number(label='Node 5 (Close)')
titik6=gr.Number(label='Node 6 (Close)')
titik7=gr.Number(label='Node 7 (Close)')
titik8=gr.Number(label='Node 8 (Close)')
titik9=gr.Number(label='Node 9 (Close)')
titik10=gr.Number(label='Node 10 (Close)')
titik11=gr.Number(label='Node 11 (Close)')
pair=gr.Dropdown(["With Last Node","Without Last Node"])
net=joblib.load('model_savgolfilt')
def fn(pair,titik1,titik2,titik3,titik4,titik5,titik6,titik7,titik8,titik9,titik10,titik11):
titik=np.array([])
titik=np.append(titik,titik1)
titik=np.append(titik,titik2)
titik=np.append(titik,titik3)
titik=np.append(titik,titik4)
titik=np.append(titik,titik5)
titik=np.append(titik,titik6)
titik=np.append(titik,titik7)
titik=np.append(titik,titik8)
titik=np.append(titik,titik9)
titik=np.append(titik,titik10)
titik=np.append(titik,titik11)
x=savgol_filter(titik,11,3)
if pair=="With Last Node":
hasil=net.predict([[x[len(x)-2],x[len(x)-1]]])
keluar=px.line(y=[x[len(x)-2],x[len(x)-1],hasil[0]])
elif pair=="Without Last Node":
hasil=net.predict([[x[len(x)-3],x[len(x)-2]]])
keluar=px.line(y=[x[len(x)-3],x[len(x)-2],hasil[0]])
return keluar
app=gr.Interface(fn,inputs=[pair,titik1,titik2,titik3,titik4,titik5,titik6,titik7,titik8,titik9,titik10,titik11],outputs=[gr.Plot()],title='Savitsky-Golay Prediction') #description=desc
app.launch() |