def train(self, data):
self.ind = len(data[0][0])
x_arrays = []
for idx in range(self.ind):
x_arrays.append( scipy.array(misc.get_col(misc.get_col(data, 0), idx)) )
y_array = scipy.array(misc.get_col(data, 1))
v, success = scipy.optimize.leastsq( self.error, self.initial, args=tuple(x_arrays + [y_array]), warning = False, maxfev = 25 )
#print 'success?', success
#print 'v=', v
self.opt = v
def train(self, data):
self.__data__ = copy.deepcopy(data)
self.yhats = misc.get_col(self.__data__, 1)
for i in range(self.iterations):
self.__smooth__()