(214 / 2)) * u.V * np.ones(len(ref)) # [V/rtHz]
_ampnoise = 6e-7 * u.V * np.ones(len(ref)) # [V/rtHz]
_aanoise = 7e-8 * u.V * np.ones(len(ref)) # [V/rtHz]
_adcnoise = FrequencySeries(_adcnoise, frequencies=ref.frequencies)
_adcnoise2 = FrequencySeries(_adcnoise2, frequencies=ref.frequencies)
_ampnoise = FrequencySeries(_ampnoise, frequencies=ref.frequencies)
_aanoise = FrequencySeries(_aanoise, frequencies=ref.frequencies)
amp = 10**(30 / 20.)
tr120q = Trillium('120QA')
tr240 = Trillium('240')
v2vel = tr120q.v2vel
v2vel = tr240.v2vel
adcnoise = v2vel(_adcnoise) / amp
ampnoise = v2vel(_ampnoise) / amp #
aanoise = v2vel(_aanoise) / amp
selfnoise_120q = tr120q.selfnoise()
selfnoise_240 = tr240.selfnoise()
# Plot
if True:
from gwpy.plot import Plot
plot = Plot()
ax = plot.gca(xscale='log',
xlim=(1e-3, 10),
xlabel='Frequency [Hz]',
yscale='log',
ylim=(1e-12, 1e-4),
ylabel=r'Velocity [m/sec/\rtHz]')
#ax.loglog(x1500,label='x1500 (ref. GIF data)')
ax.loglog(selfnoise_120q,
'k--',
if __name__ == '__main__':
unit = 'um'
#
tr120 = Trillium('120QA')
v2vel = tr120.v2vel
#
h50 = percentile('H', pctl=50, unit=unit)
h10 = percentile('H', pctl=10, unit=unit)
h90 = percentile('H', pctl=90, unit=unit)
z50 = percentile('Z', pctl=50, unit=unit)
z10 = percentile('Z', pctl=10, unit=unit)
z90 = percentile('Z', pctl=90, unit=unit)
nlnm, nhnm = peterson_noise_model(unit=unit)
selfnoise = tr120.selfnoise(unit=unit.replace('um', 'm')) * 1e6
#
fig, ax = plt.subplots(1, 1, figsize=(9, 7))
ax.plot_mmm(h50,
h10,
h90,
label='Horizontal (10,50,90 percentile)',
color='blue')
ax.plot_mmm(z50,
z10,
z90,
label='Vertical (10,50,90 percentile)',
color='red')
ax.loglog(selfnoise, 'g--', label='Selfnoise of Seismometer', alpha=1.0)
ax.loglog(nlnm[0], nlnm[1], 'k--')
ax.loglog(nhnm[0],
bw = exv.df.value
# Read Noise
_adcnoise = 2e-6*u.V*np.ones(len(freq)) # [V/rtHz]
_adcnoise2 = np.sqrt((10/2**15)**2/12/(214/2))*u.V*np.ones(len(freq)) # [V/rtHz]
_ampnoise = 6e-7*u.V*np.ones(len(freq)) # [V/rtHz]
_aanoise = 7e-8*u.V*np.ones(len(freq)) # [V/rtHz]
_adcnoise = FrequencySeries(_adcnoise, frequencies=freq)
_adcnoise2 = FrequencySeries(_adcnoise2, frequencies=freq)
_ampnoise = FrequencySeries(_ampnoise, frequencies=freq)
_aanoise = FrequencySeries(_aanoise, frequencies=freq)
adcnoise = v2vel_120(_adcnoise)/amp
ampnoise = v2vel_120(_ampnoise)/amp #
aanoise = v2vel_120(_aanoise)/amp
selfnoise_120q = tr120q.selfnoise(unit=unit)
selfnoise_240 = tr240.selfnoise(unit=unit)
#
# Plot
from gwpy.plot import Plot
plot = Plot()
ax = plot.gca(xscale='log', xlim=(1e-3, 10), xlabel='Frequency [Hz]',
yscale='log', ylim=(1e-12, 1e-4),
ylabel=r'Velocity [{0}/\rtHz]'.format(unit))
#ax.loglog(x1500,label='x1500 (ref. GIF data)')
ax.loglog(selfnoise_120q,'k--',label='Self Noise 120Q',linewidth=1,alpha=0.7)
#ax.loglog(selfnoise_240,'m--',label='Self Noise 240',linewidth=1,alpha=0.7)
#ax.loglog(adcnoise,'r--',label='ADC Noise',linewidth=1,alpha=0.7)
#ax.loglog(ampnoise,'g--',label='Amp Noise',linewidth=1,alpha=0.7)
#ax.loglog(aanoise,'b--',label='AA Noise',linewidth=1,alpha=0.7)
ax.loglog(exv,'k-',label='EXV')
def hoge(fname=None, unit='m', **kwargs):
#
kwargs['unit'] = unit
plot_selfnoise = kwargs.pop('plot_selfnoise', True)
peterson = kwargs.pop('peterson', True)
prefix, suffix = fname.split('_compare_')
path = prefix.split('_')
dof, suffix = suffix[:-4].split('_with_')
dof = dof.split('_vs_')
option = suffix.split('_')
dof = list(set(dof))
#print(path)
if not len(set(dof) & set(['X', 'Y', 'Z', 'H', 'V'])):
path = [path[0] + '_' + _dof for _dof in dof]
dof = list(filter(lambda x: x in ['X', 'Y', 'Z', 'H', 'V'], option))
option = list(set(option) ^ set(dof))
data = []
for _path in path:
for _dof in dof:
if 'V' in _path:
model = '120QA'
else:
model = 'compact'
data += [huge(_dof, _dir=_path, model=model, **kwargs)]
# Plot
fig, ax = plt.subplots(1, 1, figsize=(8, 7))
colors = ['blue', 'red', 'green', 'magenta']
label = ['{0}_{1}'.format(_path, _dof) for _dof in dof for _path in path]
if len(data) != len(label):
raise ValueError('plot error.')
for _data, _color, _label in zip(data, colors, label):
asd01, asd10, asd50, asd90, asd99, asdmean = _data
ax.loglog(asdmean.frequencies.value, asdmean.value, color='k')
if '_V' in _label:
_color = 'red'
if '90' in option:
ax.plot_mmm(asd50,
asd10,
asd90,
color=_color,
alpha=0.3,
label=_label)
if '99' in option:
ax.plot_mmm(asd50, asd01, asd99, color=_color, zorder=0, alpha=0.1)
if plot_selfnoise:
if 'V' in path[0]:
model = '120QA'
else:
model = 'compact'
seis = Trillium(model)
if 'um' in unit:
selfnoise = seis.selfnoise(unit=unit.replace('um', 'm')) * 1e6
else:
selfnoise = seis.selfnoise(unit=unit)
ax.loglog(selfnoise,
'g--',
label='Selfnoise of Trillium 120Q seismometer',
alpha=1.0)
if peterson:
nlnm, nhnm = peterson_noise_model(unit=unit)
ax.loglog(nlnm[0], nlnm[1], '--', color='black')
ax.loglog(nhnm[0],
nhnm[1],
'--',
label='Peterson Low and High Noise Models',
color='black')
ax.set_xscale('log')
ax.set_yscale('log')
ax.set_xlabel('Frequency [Hz]', fontsize=20)
ax.set_xlim(1e-3, 100)
if unit == 'um/sec/sec':
ax.set_ylim(1e-4, 1e3)
ax.set_ylabel('Acceleration [um/sec/sec/rtHz]', fontsize=20)
elif unit == 'm/sec/sec':
ax.set_ylim(1e-10, 1e-3)
ax.set_ylabel('ASD [$\mathrm{m}/\mathrm{s}^2/ \sqrt{\mathrm{Hz}}$]',
fontsize=20)
if unit == 'um/sec':
ax.set_ylim(1e-5, 10)
ax.set_ylabel('Velocity [um/sec/rtHz]', fontsize=20)
elif unit == 'um':
ax.set_ylim(1e-6, 1e2)
ax.set_yticks(np.logspace(-6, 2, 9))
ax.set_ylabel('Displacement [um/rtHz, or um]', fontsize=20)
elif unit == 'm':
ax.set_ylim(1e-13, 1e-4)
ax.set_yticks(np.logspace(-13, -4, 10))
ax.set_ylabel('Displacement [m/rtHz', fontsize=20)
ax.legend(fontsize=14) #,loc='lower left')
ax.grid(b=True, which='major', axis='both', linestyle='-')
ax.grid(b=True, which='minor', axis='both', linestyle='--')
#plt.suptitle(fname[:-4],fontsize=20)
print('./results/' + fname)
plt.tight_layout()
plt.savefig('./results/' + fname)
plt.close()