import pandas as pd
import streamlit as st
import joblib

from sklearn.preprocessing import StandardScaler, OneHotEncoder
from sklearn.model_selection import train_test_split
from sklearn.compose import ColumnTransformer

# Veriyi yükleme ve sütun isimlerini güncelleme
df = pd.read_csv('MiningProcess_Flotation_Plant_Database.csv')
df.columns = df.columns.str.replace(r'[\s\.]', '_', regex=True)
df.columns = df.columns.str.replace(r'%_Silica_Feed', 'Silica_Feed', regex=True)
df.columns = df.columns.str.replace(r'%_Silica_Concentrate', 'Silica_Concentrate', regex=True)
columns_to_convert = df.columns.difference(['date'])
df[columns_to_convert] = df[columns_to_convert].replace(',', '.', regex=True).astype(float)


# Bağımlı ve bağımsız değişkenlerin seçimi
x = df.drop(['date','%_Iron_Feed','%_Iron_Concentrate', 'Silica_Concentrate'], axis=1)
y = df[['Silica_Concentrate']]

# Eğitim ve test verilerini ayırma
x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=0.20, random_state=42)

# Ön işleme (StandardScaler ve OneHotEncoder)
preprocessor = ColumnTransformer(
    transformers=[
        ('num', StandardScaler(), ['Silica_Feed','Starch_Flow','Amina_Flow','Ore_Pulp_Flow','Ore_Pulp_pH','Ore_Pulp_Density',
                                   'Flotation_Column_01_Air_Flow','Flotation_Column_02_Air_Flow','Flotation_Column_03_Air_Flow',
                                   'Flotation_Column_04_Air_Flow','Flotation_Column_05_Air_Flow','Flotation_Column_06_Air_Flow',
                                   'Flotation_Column_07_Air_Flow','Flotation_Column_01_Level','Flotation_Column_02_Level',
                                   'Flotation_Column_03_Level','Flotation_Column_04_Level','Flotation_Column_05_Level',
                                   'Flotation_Column_06_Level','Flotation_Column_07_Level'])
    ]
)

def silica_pred(Silica_Feed,Starch_Flow,Amina_Flow,Ore_Pulp_Flow,Ore_Pulp_pH,Ore_Pulp_Density,Flotation_Column_01_Air_Flow,
               Flotation_Column_02_Air_Flow,Flotation_Column_03_Air_Flow,Flotation_Column_04_Air_Flow,Flotation_Column_05_Air_Flow,
               Flotation_Column_06_Air_Flow,Flotation_Column_07_Air_Flow,Flotation_Column_01_Level,Flotation_Column_02_Level,
               Flotation_Column_03_Level,Flotation_Column_04_Level,Flotation_Column_05_Level,Flotation_Column_06_Level,	
               Flotation_Column_07_Level):
    input_data = pd.DataFrame({
        'Silica_Feed': [Silica_Feed],
        'Starch_Flow': [Starch_Flow],
        'Amina_Flow': [Amina_Flow],
        'Ore_Pulp_Flow': [Ore_Pulp_Flow],
        'Ore_Pulp_pH': [Ore_Pulp_pH],
        'Ore_Pulp_Density': [Ore_Pulp_Density],
        'Flotation_Column_01_Air_Flow': [Flotation_Column_01_Air_Flow],
        'Flotation_Column_02_Air_Flow': [Flotation_Column_02_Air_Flow],
        'Flotation_Column_03_Air_Flow': [Flotation_Column_03_Air_Flow],
        'Flotation_Column_04_Air_Flow': [Flotation_Column_04_Air_Flow],
        'Flotation_Column_05_Air_Flow': [Flotation_Column_05_Air_Flow],
        'Flotation_Column_06_Air_Flow': [Flotation_Column_06_Air_Flow],
        'Flotation_Column_07_Air_Flow': [Flotation_Column_07_Air_Flow],
        'Flotation_Column_01_Level': [Flotation_Column_01_Level],
        'Flotation_Column_02_Level': [Flotation_Column_02_Level],
        'Flotation_Column_03_Level': [Flotation_Column_03_Level],
        'Flotation_Column_04_Level': [Flotation_Column_04_Level],
        'Flotation_Column_05_Level': [Flotation_Column_05_Level],
        'Flotation_Column_06_Level': [Flotation_Column_06_Level],
        'Flotation_Column_07_Level': [Flotation_Column_07_Level]
    })
    input_data_transformed = preprocessor.fit_transform(input_data)

    model = joblib.load('Silisyum.pkl')

    prediction = model.predict(input_data_transformed)
    return float(prediction[0])

min_Silica_Feed = x['Silica_Feed'].min()
max_Silica_Feed = x['Silica_Feed'].max()
min_Starch_Flow = x['Starch_Flow'].min()
max_Starch_Flow = x['Starch_Flow'].max()
min_Amina_Flow = x['Amina_Flow'].min()
max_Amina_Flow = x['Amina_Flow'].max()
min_Ore_Pulp_Flow = x['Ore_Pulp_Flow'].min()
max_Ore_Pulp_Flow = x['Ore_Pulp_Flow'].max()
min_Ore_Pulp_pH = x['Ore_Pulp_pH'].min()
max_Ore_Pulp_pH = x['Ore_Pulp_pH'].max()
min_Ore_Pulp_Density = x['Ore_Pulp_Density'].min()
max_Ore_Pulp_Density = x['Ore_Pulp_Density'].max()
min_Flotation_Column_01_Air_Flow = x['Flotation_Column_01_Air_Flow'].min()
max_Flotation_Column_01_Air_Flow = x['Flotation_Column_01_Air_Flow'].max()
min_Flotation_Column_02_Air_Flow = x['Flotation_Column_02_Air_Flow'].min()
max_Flotation_Column_02_Air_Flow = x['Flotation_Column_02_Air_Flow'].max()
min_Flotation_Column_03_Air_Flow = x['Flotation_Column_03_Air_Flow'].min()
max_Flotation_Column_03_Air_Flow = x['Flotation_Column_03_Air_Flow'].max()
min_Flotation_Column_04_Air_Flow = x['Flotation_Column_04_Air_Flow'].min()
max_Flotation_Column_04_Air_Flow = x['Flotation_Column_04_Air_Flow'].max()
min_Flotation_Column_05_Air_Flow = x['Flotation_Column_05_Air_Flow'].min()
max_Flotation_Column_05_Air_Flow = x['Flotation_Column_05_Air_Flow'].max()
min_Flotation_Column_06_Air_Flow = x['Flotation_Column_06_Air_Flow'].min()
max_Flotation_Column_06_Air_Flow = x['Flotation_Column_06_Air_Flow'].max()
min_Flotation_Column_07_Air_Flow = x['Flotation_Column_07_Air_Flow'].min()
max_Flotation_Column_07_Air_Flow = x['Flotation_Column_07_Air_Flow'].max()
min_Flotation_Column_01_Level = x['Flotation_Column_01_Level'].min()
max_Flotation_Column_01_Level = x['Flotation_Column_01_Level'].max()
min_Flotation_Column_02_Level = x['Flotation_Column_02_Level'].min()
max_Flotation_Column_02_Level = x['Flotation_Column_02_Level'].max()
min_Flotation_Column_03_Level = x['Flotation_Column_03_Level'].min()
max_Flotation_Column_03_Level = x['Flotation_Column_03_Level'].max()
min_Flotation_Column_04_Level = x['Flotation_Column_04_Level'].min()
max_Flotation_Column_04_Level = x['Flotation_Column_04_Level'].max()
min_Flotation_Column_05_Level = x['Flotation_Column_05_Level'].min()
max_Flotation_Column_05_Level = x['Flotation_Column_05_Level'].max()
min_Flotation_Column_06_Level = x['Flotation_Column_06_Level'].min()
max_Flotation_Column_06_Level = x['Flotation_Column_06_Level'].max()
min_Flotation_Column_07_Level = x['Flotation_Column_07_Level'].min()
max_Flotation_Column_07_Level = x['Flotation_Column_07_Level'].max()

st.title("Maden Veri seti ile Silica saflık Regresyon Modeli")
st.write("Veri Gir")
    
Silica_Feed = st.slider('Silica_Feed', float(min_Silica_Feed), float(max_Silica_Feed))
Starch_Flow = st.slider('Starch_Flow', float(min_Starch_Flow), float(max_Starch_Flow))
Amina_Flow = st.slider('Amina_Flow', float(min_Amina_Flow), float(max_Amina_Flow))
Ore_Pulp_Flow = st.slider('Ore_Pulp_Flow', float(min_Ore_Pulp_Flow), float(max_Ore_Pulp_Flow))
Ore_Pulp_pH = st.slider('Ore_Pulp_pH', float(min_Ore_Pulp_pH), float(max_Ore_Pulp_pH))
Ore_Pulp_Density = st.slider('Ore_Pulp_Density', float(min_Ore_Pulp_Density), float(max_Ore_Pulp_Density))
Flotation_Column_01_Air_Flow = st.slider('Flotation_Column_01_Air_Flow', float(min_Flotation_Column_01_Air_Flow), float(max_Flotation_Column_01_Air_Flow))
Flotation_Column_02_Air_Flow = st.slider('Flotation_Column_02_Air_Flow', float(min_Flotation_Column_02_Air_Flow), float(max_Flotation_Column_02_Air_Flow))
Flotation_Column_03_Air_Flow = st.slider('Flotation_Column_03_Air_Flow', float(min_Flotation_Column_03_Air_Flow), float(max_Flotation_Column_03_Air_Flow))
Flotation_Column_04_Air_Flow = st.slider('Flotation_Column_04_Air_Flow', float(min_Flotation_Column_04_Air_Flow), float(max_Flotation_Column_04_Air_Flow))
Flotation_Column_05_Air_Flow = st.slider('Flotation_Column_05_Air_Flow', float(min_Flotation_Column_05_Air_Flow), float(max_Flotation_Column_05_Air_Flow))
Flotation_Column_06_Air_Flow = st.slider('Flotation_Column_06_Air_Flow', float(min_Flotation_Column_06_Air_Flow), float(max_Flotation_Column_06_Air_Flow))
Flotation_Column_07_Air_Flow = st.slider('Flotation_Column_07_Air_Flow', float(min_Flotation_Column_07_Air_Flow), float(max_Flotation_Column_07_Air_Flow))
Flotation_Column_01_Level = st.slider('Flotation_Column_01_Level', float(min_Flotation_Column_01_Level), float(max_Flotation_Column_01_Level))
Flotation_Column_02_Level = st.slider('Flotation_Column_02_Level', float(min_Flotation_Column_02_Level), float(max_Flotation_Column_02_Level))
Flotation_Column_03_Level = st.slider('Flotation_Column_03_Level', float(min_Flotation_Column_03_Level), float(max_Flotation_Column_03_Level))
Flotation_Column_04_Level = st.slider('Flotation_Column_04_Level', float(min_Flotation_Column_04_Level), float(max_Flotation_Column_04_Level))
Flotation_Column_05_Level = st.slider('Flotation_Column_05_Level', float(min_Flotation_Column_05_Level), float(max_Flotation_Column_05_Level))
Flotation_Column_06_Level = st.slider('Flotation_Column_06_Level', float(min_Flotation_Column_06_Level), float(max_Flotation_Column_06_Level))
Flotation_Column_07_Level = st.slider('Flotation_Column_07_Level', float(min_Flotation_Column_07_Level), float(max_Flotation_Column_07_Level))


# Predict button
if st.button('Silica Saflığını Tahmin Et'):
    prediction = silica_pred(Silica_Feed, Starch_Flow, Amina_Flow, Ore_Pulp_Flow, Ore_Pulp_pH, Ore_Pulp_Density, 
                                Flotation_Column_01_Air_Flow, Flotation_Column_02_Air_Flow, Flotation_Column_03_Air_Flow, 
                                Flotation_Column_04_Air_Flow, Flotation_Column_05_Air_Flow, Flotation_Column_06_Air_Flow, 
                                Flotation_Column_07_Air_Flow, Flotation_Column_01_Level, Flotation_Column_02_Level, 
                                Flotation_Column_03_Level, Flotation_Column_04_Level, Flotation_Column_05_Level, 
                                Flotation_Column_06_Level, Flotation_Column_07_Level)
        
    st.write(f'Tahmin edilen Silica Saflığı: {prediction:.2f}')