def plot_generated():
s = 0
cpm_points, cpm_data = r_cpm(s)
angles_deg_errors = [0 for i in range(4)]
vertical_error = 0
horizontal_error = 0
angles = [0, 38, 67, 180]
signals, profile = generate_profile_signals(
SAMPLES_IN_ROUND,
angles=angles,
cpm_points=cpm_points,
vertical_error=vertical_error,
horizontal_error=horizontal_error,
angles_deg_errors=angles_deg_errors)
signals = np.array(average(signals, SAMPLES_IN_ROUND))
profile = remove_radius(profile)
signals = [s * -1 for s in signals]
angles = [0, 38, 67, 180]
ozono = ozono_f_coeff(signals, angles[0:3])
hybrid = hybrid_f_coeff(signals, angles=angles[0:3])
jansen2 = jansen_roundness_f_coeff(signals, angles)
filtered_ozono = filter_fft(ozono, include_ecc=False)
filtered_hybrid = filter_fft(hybrid, include_ecc=False)
filtered_jansen2 = filter_fft(jansen2, include_ecc=False)
o = get_roundness_profile(filtered_ozono)
h = get_roundness_profile(filtered_hybrid)
ar2 = get_roundness_profile(filtered_jansen2)
offset = 0.40
r_max = 0.3
step = 0.1
f = 1
offset = 0.40
# polar_plot(profile, None, offset * f, True, None, f * r_max, f * 0.1, f, False)
polar_plot(o, "Ozono", offset, False, None, r_max=r_max, step=step)
polar_plot(h,
"4 probe hybrid",
offset,
False,
None,
r_max=r_max,
step=step)
polar_plot(ar2, "4 probe LS", offset, False, None, r_max=r_max, step=step)
plt.legend()
plt.show()
def cpm_generated():
s = 0.1
cpm_points, cpm_data = r_cpm(s)
gen_cpm = [[i[0] for i in cpm_points], [i[1] for i in cpm_points]]
plot_cpms([gen_cpm], ["Center point movement"])
plt.show()
return
# cpm_points = circle_cpm(104.20)
signals, profile = generate_profile_signals(SAMPLES_IN_ROUND,
cpm_points=cpm_points)
signals = np.array(average(signals))
advanced = advanced_roundness_f_coeff(signals, [0, 38, 67])
advanced2 = advanced_roundness_f_coeff(signals, [0, 38, 67, 180])
ozono = ozono_f_coeff(signals, [0, 38, 67])
hybrid = hybrid_f_coeff(signals, angles=[0, 38, 67])
filtered_advanced = filter_fft(advanced)
filtered_advanced2 = filter_fft(advanced2)
filtered_ozono = filter_fft(ozono)
filtered_hybrid = filter_fft(hybrid)
s = [signals[0], signals[2]]
angles = [0, 67]
ozono_cpm = get_cpm(s, angles, filtered_ozono)
hybrid_cpm = get_cpm(s, angles, filtered_hybrid)
ar_cpm = get_cpm(s, angles, filtered_advanced)
ar2_cpm = get_cpm(s, angles, filtered_advanced2)
plot_cpms([gen_cpm, ozono_cpm, hybrid_cpm, ar_cpm, ar2_cpm], [
"Generated", "Ozono", "Jansen (3 probes)", "Jansen (4 probes)",
"Hybrid"
])
plt.show()
def plot_incorrectangles():
s = 0
cpm_points, cpm_data = r_cpm(s)
angles_deg_errors = [0 for i in range(4)]
vertical_error = 0
horizontal_error = 0
signals, profile = generate_profile_signals(
SAMPLES_IN_ROUND,
cpm_points=cpm_points,
vertical_error=vertical_error,
horizontal_error=horizontal_error,
angles_deg_errors=angles_deg_errors)
signals = np.array(average(signals))
profile = remove_radius(profile)
signals = [s * -1 for s in signals]
# advanced = advanced_roundness_f_coeff(signals, [0, 38, 67])
# advanced1 = advanced_roundness_f_coeff(signals, [0, 37.06875, 65.88984375, 179.41640625])
advanced1 = advanced_roundness_f_coeff(
signals, [0, 37.06875, 65.88984375, 179.41640625])
advanced2 = advanced_roundness_f_coeff(signals, [0, 38, 67, 180])
filtered_advanced1 = filter_fft(advanced1, include_ecc=False)
filtered_advanced2 = filter_fft(advanced2, include_ecc=False)
h = get_roundness_profile(filtered_advanced1)
h2 = get_roundness_profile(filtered_advanced2)
offset = 0.45
polar_plot(profile, "Actual profile", offset)
polar_plot(h2, "Angles with errors", offset)
polar_plot(h, "Determined angles", offset)
plt.show()
def montecarlo_single(n=0):
print(n)
if not os.path.exists("res/"):
os.makedirs("res/")
errors = False
if errors:
mu = 10 * 0.1
sigma = 10 * 0.03
s = nr(mu, sigma)
cpm_points, cpm_data = r_cpm(s)
angles_deg_errors = [nr(0, 0.25) for i in range(4)]
vertical_error = nr(0, 0.35)
horizontal_error = nr(0, 0.25)
else:
mu = 0
sigma = 0
cpm_points, cpm_data = r_cpm(0)
angles_deg_errors = [0 for i in range(4)]
vertical_error = 0
horizontal_error = 0
signals, profile = generate_profile_signals(
SAMPLES_IN_ROUND,
cpm_points=cpm_points,
vertical_error=vertical_error,
horizontal_error=horizontal_error,
angles_deg_errors=angles_deg_errors)
# add probe scaling error
signals = np.array(average(signals))
advanced = advanced_roundness_f_coeff(signals, [0, 38, 67])
advanced2 = advanced_roundness_f_coeff(signals, [0, 38, 67, 180])
ozono = ozono_f_coeff(signals, [0, 38, 67])
hybrid = hybrid_f_coeff(signals, angles=[0, 38, 67])
filtered_ozono = filter_fft(ozono, include_ecc=True)
filtered_hybrid = filter_fft(hybrid, include_ecc=True)
filtered_advanced = filter_fft(advanced, include_ecc=True)
filtered_advanced2 = filter_fft(advanced2, include_ecc=True)
errors = {
"SAMPLES_IN_ROUND": SAMPLES_IN_ROUND,
"cpm_data": cpm_data,
"vertical_error": vertical_error,
"horizontal_error": horizontal_error,
"angles_deg_errors": angles_deg_errors
}
res = {
"ozono": list(filtered_ozono[0:FILTERLEVEL]),
"hybrid": list(filtered_hybrid[0:FILTERLEVEL]),
"advanced": list(filtered_advanced[0:FILTERLEVEL]),
"advanced2": list(filtered_advanced2[0:FILTERLEVEL])
}
d = {"res": res, "errors": errors}
if True:
with open(
"res/res-mu{}-sigma{}-{}.pickle".format(
mu, sigma, uuid.uuid4()), "wb") as f:
f.write(pickle.dumps(d))
def plot_generated():
# cpm_points = r_cpm(1.00)
# cpm_points = circle_cpm(1.20)
errors = False
if errors:
s = nr(0.1, 0.03)
cpm_points, cpm_data = r_cpm(s)
angles_deg_errors = [nr(0, 0.5) for i in range(4)]
vertical_error = nr(0, 0.35)
horizontal_error = nr(0, 0.25)
else:
s = 0
cpm_points, cpm_data = r_cpm(s)
angles_deg_errors = [0 for i in range(4)]
vertical_error = 0
horizontal_error = 0
signals, profile = generate_profile_signals(
SAMPLES_IN_ROUND,
cpm_points=cpm_points,
vertical_error=vertical_error,
horizontal_error=horizontal_error,
angles_deg_errors=angles_deg_errors)
# probe scale error
if errors:
signals = [[i + nr(0, 0.003) for i in signal] for signal in signals]
signals = np.array(average(signals))
profile = remove_radius(profile)
signals = [s * -1 for s in signals]
advanced = advanced_roundness_f_coeff(signals, [0, 38, 67])
advanced2 = advanced_roundness_f_coeff(signals, [0, 38, 67, 180])
ozono = ozono_f_coeff(signals, [0, 38, 67])
hybrid = hybrid_f_coeff(signals, angles=[0, 38, 67])
filtered_ozono = filter_fft(ozono, include_ecc=False)
filtered_hybrid = filter_fft(hybrid, include_ecc=False)
filtered_advanced = filter_fft(advanced, include_ecc=False)
filtered_advanced2 = filter_fft(advanced2, include_ecc=False)
# print(ecc)
# print(np.abs(ecc))
# print(np.angle(ecc))
barchart(filtered_ozono)
plt.show()
# barchart(advanced)
# plt.show()
ar = get_roundness_profile(filtered_advanced)
ar2 = get_roundness_profile(filtered_advanced2)
o = get_roundness_profile(filtered_ozono)
h = get_roundness_profile(filtered_hybrid)
offset = 0.30
polar_plot(profile, "Actual profile", offset, True)
# polar_plot(profile, "Actual profile", offset)
polar_plot(o, "Ozono", offset)
polar_plot(h, "Hybrid four point", offset)
polar_plot(ar, "Advanced roundness (3 probes)", offset)
polar_plot(ar2, "Advanced roundness (4 probes)", offset)
plt.show()
def plots_generated():
# signals = np.array(average(SIGNALS))
X = []
e_ar = []
e_ar2 = []
e_ozono = []
e_hybrid = []
diam = 100
l = 0
h = 10
for ecc in np.linspace(l, h, 11):
signals, profile = generate_profile_signals(ecc=(ecc / 100) * diam)
signals = np.array(average(signals))
advanced = advanced_roundness_f_coeff(signals, [0, 38, 67])
advanced2 = advanced_roundness_f_coeff(signals, [0, 38, 67, 180])
ozono = ozono_f_coeff(signals, [0, 38, 67])
hybrid = hybrid_f_coeff(signals, angles=[0, 38, 67])
filtered_ozono = filter_fft(ozono)
filtered_hybrid = filter_fft(hybrid)
ar = get_roundness_profile(advanced)
ar2 = get_roundness_profile(advanced2)
o = get_roundness_profile(filtered_ozono)
h = get_roundness_profile(filtered_hybrid)
X.append(ecc / diam)
# e_ar.append(RRMSE(profile, ar))
# e_ar2.append(RRMSE(profile, ar2))
# e_ozono.append(RRMSE(profile, o))
# e_hybrid.append(RRMSE(profile, h))
e_ar.append(RPPE(profile, ar))
e_ar2.append(RPPE(profile, ar2))
e_ozono.append(RPPE(profile, o))
e_hybrid.append(RPPE(profile, h))
polar_plot(profile,
"Actual profile",
True,
title="Roundness profile e={}% of d".format(ecc))
polar_plot(o,
"Ozono",
False,
title="Roundness profile e={}% of d".format(ecc))
polar_plot(h,
"Hybrid four point",
False,
title="Roundness profile e={}% of d".format(ecc))
polar_plot(ar,
"Advanced roundness (3 probes)",
False,
title="Roundness profile e={}% of d".format(ecc))
polar_plot(ar2,
"Advanced roundness (4 probes)",
False,
title="Roundness profile e={}% of d".format(ecc))
plt.show()
# plt.savefig("profile_{}.png".format(ecc))
# plt.clf()
# plt.plot(X, e_ar, label="ar")
plt.plot(X, e_ar2, label="ar2")
plt.plot(X, e_ozono, label="ozono")
plt.plot(X, e_hybrid, label="hybrid")
plt.legend()
plt.show()