def _normalised_numpy(self):
        """Normalised data points using numpy."""
        dx = (self.screen.width / float(len(self.points)))
        oy = (self.screen.height)
        points = np.array(self.points) - self.minimum
        points = points * 4.0 / self.extents * self.size.y
        for x, y in enumerate(points):
            yield Point((
                dx * x,
                min(oy, oy - y),
            ))
def _normalised_numpy(self):
        """Normalised data points using numpy."""
        dx = (self.screen.width / float(len(self.points)))
        oy = (self.screen.height)
        points = np.array(self.points) - self.minimum
        points = points * 4.0 / self.extents * self.size.y
        for x, y in enumerate(points):
            yield Point((
                dx * x,
                min(oy, oy - y),
            ))
def _normalised_numpy ( self ) : dx = ( self . screen . width / float ( len ( self . points ) ) ) oy = ( self . screen . height ) points = np . array ( self . points ) - self . minimum points = points * 4.0 / self . extents * self . size . y for x , y in enumerate ( points ) : yield Point ( ( dx * x , min ( oy , oy - y ) , ) )
Normalised data points using numpy.
Normalised data points using numpy .