text: # Loading dependencies
  from .BasePredictiveModel import BasePredictiveModel
  import numpy as np
  
  class Power(BasePredictiveModel):
  
  	def __init__(self, **params):
  		super().__init__(**params)
  		'''Power growth model for predicting future trends
  
  		::params::
  		growth_rate
  		'''
  		self.growth_rate = params.pop('growth_rate')
  		self.x = self.predict_series(random = True)
  
  	def predict(self, T = None):
  		return self.X0 * (1+self.growth_rate) ** t
  
  	def predict_series(self, random = True):
  
  		if random:
  			T = np.linspace(0, self.settings.horizon, self.settings.n_steps)
  			x = self.X0 * (1+self.growth_rate) ** T
  			return x
  		else:
  			return self.x