# Modified Stylesheet for notebook.
from IPython.core.display import HTML
def css_styling():
    styles = open("custom.css", "r").read()
    return HTML(styles)

css_styling()

import matplotlib.pyplot as plt
import numpy as np

from collections import defaultdict
np.random.seed(seed=111111)
np.set_printoptions(precision=2, suppress=True)

import sys; sys.path.append('../src/')
from change_detector import ChangeDetector

# Initialize change detector

detector = ChangeDetector()

print detector
print "Signal size:", detector.signal_size

# Add one point to the change_detector
next(detector.step(10))

# (The step() function is written as a python generator)

print detector
print "Signal size:", detector.signal_size

from change_detector import OnlineSimulator

signal = np.random.randint(10, size=20)
print "Signal: {}".format(signal)

# reset
sim = OnlineSimulator(detector, signal)

# pass the signal the online_simulator
sim.run(plot=True)
(Note that the stopping rule will not be triggered, because we haven't created any stopping rules yet.)
print detector
Fine, okay, that works, but it doesn't do much. 

We'll now write a new Class that extends ChangeDetector. We'll add a residual. 

class MeanDetector(ChangeDetector):
    """
    This is a simple detector that extends the base 
    ChangeDetector. 
    
    This serves as a useful "skeleton" on how to override 
    the methods of ChangeDetector.
    
    We're adding a "residual" -- we'll keep track of the 
    mean of the signal. 
    """
    def __init__(self):
        super(MeanDetector, self).__init__()

        self.total_val = 0
        # Mean is a pretty simple and useful residual
        self.mean_ = np.nan
        
    def update_residuals(self, new_signal_value):
        self._update_base_residuals(new_signal_value)
        
        self.total_val += new_signal_value
        self.mean_ = float(self.total_val) / self.signal_size
    
    def check_stopping_rules(self, new_signal_value):
        # Implement Stopping rules here
        if np.abs(new_signal_value - self.mean_) > 100: 
            self.rules_triggered = True



detector = MeanDetector()

OnlineSimulator(detector, signal).run()

signal[17] = 200

plt.plot(signal)

# Let's run our detector on this signal

OnlineSimulator(detector, signal).run()