import numpy as np
from matplotlib import pyplot
import smooth1d
import smooth1d_plot as myplot
#(0) Load datasets:
np.random.seed(0)
dataset_classes = smooth1d.datasets.dataset_classes[1:]
pyplot.close('all')
fontname = u'Times New Roman'
fig = myplot.MyFigure(figsize=(9, 6),
axx=np.linspace(0.06, 0.71, 3),
axy=[0.60, 0.08],
axw=0.28,
axh=0.36,
fontname=fontname,
set_font=True,
set_visible=False)
AX = fig.AX
np.random.seed(0)
for i, (ax, dataset_class) in enumerate(zip(AX.flatten(), dataset_classes)):
dataset = dataset_class()
t, y = dataset.get_data()
### add noise:
J, Q = 5, y.size
sd0 = smooth1d.util.noise_for_target_rmse(y, 0.01)
sd = smooth1d.util.noise_for_target_rmse(y, 0.2)
yn = y + sd * np.random.randn(J, Q)
uJ = np.unique(J)
uamp = np.unique(amp)
h = np.array([[h0[(J == j) & (amp == a)].mean() for a in uamp]
for j in uJ])
H0.append(100 * h)
HH0.append(H0)
### plot:
pyplot.close('all')
fontname = u'Times New Roman'
colors = ['b', 'g', 'r', 'c', 'k']
colors = ['0.80', '0.50', 'k']
# colors = pyplot.cm.jet(np.linspace(0,1,len(cutoffs)+2))[1:-1]
fig = myplot.MyFigure(figsize=(8, 4),
axx=np.linspace(0.07, 0.7, 3),
axy=[0.56, 0.1],
axw=0.29,
axh=0.43,
fontname=fontname,
set_visible=True)
AX = fig.AX.flatten()
for i, (ax, H0) in enumerate(zip(AX, HH0)):
for c, h0 in zip(colors, H0):
ax.plot(uJ, h0[:, 0], 'o-', color=c, markersize=3)
ax.plot(uJ, h0[:, 1], 'o--', color=c, markersize=3)
ax.set_xticks(np.arange(5, 51, 10))
ax.axhline(5, color='k', ls='--')
### create legends:
labels_window = ['Window = %d' % x for x in windows]
labels_noise = ['Noise = 1%', 'Noise = 20%']
leg0 = myplot.dummy_legend(AX[0],