# Welcome to Crowe Logic Pro IDE
# AI-Powered Development Environment

import numpy as np
import pandas as pd
from sklearn.ensemble import RandomForestClassifier
import matplotlib.pyplot as plt

# Natural Language AI Code Generation Example
# Try typing: "Create a machine learning model to predict mushroom yield"

class MycoMLModel:
    def __init__(self):
        self.model = RandomForestClassifier(n_estimators=100)
        self.features = []
        
    def prepare_data(self, environmental_data):
        """
        Prepare environmental data for ML model training
        """
        # Temperature, humidity, CO2, light features
        features = environmental_data[['temp', 'humidity', 'co2', 'light']]
        return features.fillna(features.mean())
    
    def train_model(self, X, y):
        """
        Train the yield prediction model
        """
        self.model.fit(X, y)
        return self.model.score(X, y)
    
    def predict_yield(self, environmental_conditions):
        """
        Predict mushroom yield based on environmental conditions
        """
        return self.model.predict(environmental_conditions)

# Example usage
model = MycoMLModel()
print("AI-Generated ML Model Ready for Mycology Research!")