theideasmith

theideasmith

import matplotlib.pyplot as plt
import numpy as np

def gen_vectors(f,x,y):
    assert len(x) == len(y)

    d = len(x), len(y)
    t = len(x)
    res = []
    xs = []

theideasmith

theideasmith

from numpy import *
import matplotlib.pyplot as plt
import numpy as np
class DiscreteRandomVariable:
  def __init__(self,X, P, bins):
    self.X = X
    self.P = P
    self.H = P*X.shape[0]
    self.bins = bins
    

theideasmith

theideasmith

class AbstractRegression:
    def __init__(self, xs, ys, w,alpha, epsilon=0.02):
        self.w = w
        self.xs = xs
        self.ys = ys
        self.yhats = self.f(self.xs,self.w)
        self.loss = 
        self.a = alpha
        self.N = xs.shape[0]
        self.e = epsilon

theideasmith

theideasmith

theideasmith

<ipython-input-20-db8ed034fc79> in <module>()
----> 1 model.fit(X,y)

<home>/.conda/envs/flytrackerML/lib/python2.7/site-packages/keras/models.pyc in fit(self, x, y, batch_size, nb_epoch, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, **kwargs)
    406                               shuffle=shuffle,
    407                               class_weight=class_weight,
--> 408                               sample_weight=sample_weight)
    409 
    410     def evaluate(self, x, y, batch_size=32, verbose=1,

theideasmith

from enum import Enum

nodes = connectome

class NeuronState():
  S = 1
  E = 2
  R = 3

class TopologicalSimulator: