def ssr_curve(self,
x,
y,
slopes=[
0.1, 0.2, 0.3, 0.4, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0,
4.0, 5.0, 7.5, 10.0
]):
ssrs = []
for slope in slopes:
yint = (np.mean(y) - slope * np.mean(x))
ssrs.append(
self.get_ss_res(zip(x, y), lambda val: slope * val + yint))
image_manager = ImageManager()
plotter = Plotter()
plotter.set_title('Sum of Squared Residuals')
plotter.set_axis_labels('Slope Selected', 'Sum of Squared Residual')
plotter.set_output_filename(g.files['ls-ssr'])
ssr_plot = ScatterSketch()
ssr_plot.add_x(slopes)
ssr_plot.add_y(ssrs)
plotter.load(ssr_plot)
plotter.save()
plotter.close()
g.debug.prn(self, 'Drawn Sum of Squared Residuals Plot')
image_manager.scale(g.files['ls-ssr'], g.files['ls-ssr'], 250)
def gen_plot():
plotter.set_title(g.graph_titles['main'])
g.x = g.randomizer.random_list(25, 0, 100)
g.y = g.randomizer.random_list(25, 0, 100)
# plotter.add_x_val(x) # [-2, -1, 0, 1, 2]
# plotter.add_y_val(y) # [4,1,0,1,4]
scatter = ScatterSketch()
scatter.add_x(g.x)
scatter.add_y(g.y)
plotter.load(scatter)
plotter.save()
plotter.close()
# g.modeller.gen_least_squares(x,y)
# g.analyzer.f_dist(LinearModel, 100)
image_manager.scale(g.files['plot'], g.files['plot'], g.image_height)