def make_figure():
fig = plt.figure(figsize=(12, 4))
gs1 = matplotlib.gridspec.GridSpec(ncols=3, nrows=1, figure=fig)
gs2 = matplotlib.gridspec.GridSpec(ncols=3, nrows=1, figure=fig)
gs1.update(left=0.06,
right=0.995,
bottom=0.6,
top=0.9,
hspace=0.45,
wspace=0.1)
gs2.update(left=0.06,
right=0.995,
bottom=0.1,
top=0.55,
hspace=0.45,
wspace=0.1)
ax11 = fig.add_subplot(gs1[0])
ax12 = fig.add_subplot(gs1[1])
ax13 = fig.add_subplot(gs1[2])
ax21 = fig.add_subplot(gs2[0])
ax22 = fig.add_subplot(gs2[1])
ax23 = fig.add_subplot(gs2[2])
axes = [ax11, ax12, ax13, ax21, ax22, ax23]
return fig, axes
def make_angle_single_figure_grid():
fig = plt.figure(figsize=(8, 3.25))
gs1 = matplotlib.gridspec.GridSpec(ncols=1, nrows=1, figure=fig)
gs2 = matplotlib.gridspec.GridSpec(ncols=1, nrows=1, figure=fig)
gs1.update(left=0.15, right=0.9, bottom=0.475, top=0.88, hspace=0.15, wspace=0.15)
gs2.update(left=0.15, right=0.9, bottom=0.18, top=0.425, hspace=0.15, wspace=0.15)
return fig, fig.add_subplot(gs1[0]), fig.add_subplot(gs2[0])
def make_starting_point_plot(dname, problemFunc, optimizers, results):
fig = plt.figure(figsize=(6, 2.5))
gs = matplotlib.gridspec.GridSpec(ncols=1, nrows=1, figure=fig)
gs.update(left=0.1, right=0.95, bottom=0.15, top=0.85, hspace=0.2, wspace=0.1)
def plot_1d(ax):
LR = 0.5
N_ITERS = 10
thetas = [0.5, 1.0, 2.0, 4.0]
ds = eftk.datasets.load("1D-Quadratic")
problem = eftk.problem_defs.LinearRegression(*ds.get_train(), prior_var=np.inf)
for opt_name, opt in optimizers.items():
if opt_name is "GD":
continue
for i, theta0 in enumerate(thetas):
res = list(opt(problem, lr=LR, theta=np.array([theta0]), damping=10**-6).run(n_iter=N_ITERS))
if i == 0:
ax.plot(res, color=efplt.colors[opt_name], linewidth=LINEWIDTH, label=r"\bf{" + opt_name + "}", linestyle=efplt.linestyles[opt_name])
else:
ax.plot(res, color=efplt.colors[opt_name], linewidth=LINEWIDTH, linestyle=efplt.linestyles[opt_name])
ax.set_title(r"\LARGE $\mathbf{(x-0.5)^2 + (x+0.5)^2}$")
ax.set_ylabel(r"\bf{Loss}")
ax.set_xlabel("Iteration", labelpad=-15)
ax.set_yscale("log")
ax.set_xticks([0, 10])
efplt.hide_frame([ax])
def plot_boston(ax):
factors = 1.0 - np.array([0.125, 0.25, 0.5, 1])
hyperparameters = find_best_hyperparameters(results)
different_startingpoints = run_different_startingpoints(dname, problemFunc, optimizers, hyperparameters, factors)
for i, startingPoint in enumerate(different_startingpoints):
ax.plot(startingPoint["NGD"], color=efplt.colors["NGD"], linewidth=LINEWIDTH, linestyle=efplt.linestyles["NGD"], label=r"\bf{NGD}" if i == 0 else None)
for i, startingPoint in enumerate(different_startingpoints):
ax.plot(startingPoint["EFGD"], color=efplt.colors["EFGD"], linewidth=LINEWIDTH, linestyle=efplt.linestyles["EFGD"], label=r"\bf{EFGD}" if i == 0 else None)
ax.set_title(r"\bf{" + dname + "}")
ax.set_yscale("log")
ax.set_xlabel("Iteration", labelpad=-15)
efplt.hide_frame([ax])
ax.set_xticks([0, 20])
plot_boston(fig.add_subplot(gs[0]))
fig.legend(loc='right', bbox_to_anchor=(0.998, 0.85), ncol=1, borderpad=.25, handletextpad=0.4, borderaxespad=0)
return fig
def make_angle_figure_grid():
fig = plt.figure(figsize=(12, 3))
gs1 = matplotlib.gridspec.GridSpec(ncols=3, nrows=1, figure=fig)
gs2 = matplotlib.gridspec.GridSpec(ncols=3, nrows=1, figure=fig)
gs1.update(left=0.08, right=0.98, bottom=0.475, top=0.88, hspace=0.15, wspace=0.15)
gs2.update(left=0.08, right=0.98, bottom=0.18, top=0.425, hspace=0.15, wspace=0.15)
axes1 = [fig.add_subplot(gs1[0]), fig.add_subplot(gs1[1]), fig.add_subplot(gs1[2])]
axes2 = [fig.add_subplot(gs2[0]), fig.add_subplot(gs2[1]), fig.add_subplot(gs2[2])]
return fig, axes1, axes2
def fig_and_axes():
fig = plt.figure(figsize=(12, 3.2))
gs = matplotlib.gridspec.GridSpec(1, 4)
gs.update(left=0.01,
right=0.99,
wspace=0.1,
hspace=0.2,
bottom=0.05,
top=0.90)
axes = [fig.add_subplot(gs[i, j]) for i in range(1) for j in range(4)]
return fig, axes