def Plot_transfer(F, RR, Sd, fn, R, channel_id, starttime, endtime, location,
_format):
lw = 1.5
if location == '10':
var = 'aceleracion'
units = 'cuentas/(m/s^2)'
else:
var = 'velocidad'
units = 'cuentas/(m/s)'
xmin = min(F)
xmax = max(F)
ymin = min(abs(RR))
ymax = max(abs(RR)) + 1e1
xmin, xmax = xmin - (xmax - xmin) / 20., xmax + (xmax - xmin) / 20.
ymin, ymax = ymin - (ymax - ymin) / 20., ymax + (ymax - ymin) / 20.
fig = plt.figure()
ax1 = fig.add_subplot(211)
ax1.loglog(F, abs(RR), lw=lw)
ax1.scatter(fn,
ymax,
linewidth=2,
s=30,
marker='o',
color='b',
label='fn = %s Hz' % fn)
ax1.axvline(x=fn, ymax=max(abs(RR)), linewidth=2, linestyle='--')
ax1.grid(True)
ax1.set_xlim([xmin, xmax])
ax1.set_ylim([ymin, ymax])
plt.xlabel('')
plt.ylabel('Sensibilidad %s' % units)
ax1.xaxis.set_major_formatter(mtick.NullFormatter())
ax1.yaxis.set_major_locator(
mtick.LogLocator(base=10, subs=[1, 2, 3, 4, 5, 6, 7, 8, 9]))
ax1.text(xmax - .05 * (xmax - xmin),
ymin + .05 * (ymax - ymin),
'Sensibilidad: %13.3e %s' % (Sd, units),
size=15,
horizontalalignment='right')
plt.title('Respuesta en %s: %s %s - %s' %
(var, channel_id, starttime, endtime))
# Phase
ax2 = fig.add_subplot(212)
ax2.semilogx(F, np.angle(RR), lw=lw)
ax2.scatter(fn,
0,
linewidth=2,
s=30,
marker='o',
color='b',
label='fn = %s Hz' % fn)
plt.legend(loc=1, scatterpoints=1, markerscale=1)
ax2.grid(True)
ax2.set_xlim([xmin, xmax])
plt.xlabel('frecuencia [Hz]')
plt.ylabel('Fase [Radianes]')
minmax2 = ax2.yaxis.get_data_interval()
yticks2 = np.arange(minmax2[0] - minmax2[0] % (np.pi / 2),
minmax2[1] - minmax2[1] % (np.pi / 2) + np.pi,
np.pi / 2)
ax2.set_yticks(yticks2)
ax2.set_yticklabels([_pitick2latex(x) for x in yticks2])
name_fig = '%s_%s.%s' % (channel_id, starttime, _format)
plt.savefig(name_fig, dpi=fig.dpi)
print "%s saved" % name_fig
plt.show()
def test_pitick2latex(self):
self.assertEqual(_pitick2latex(3 * pi / 2), r'$\frac{3\pi}{2}$')
self.assertEqual(_pitick2latex(2 * pi / 2), r'$\pi$')
self.assertEqual(_pitick2latex(1 * pi / 2), r'$\frac{\pi}{2}$')
self.assertEqual(_pitick2latex(0 * pi / 2), r'$0$')
self.assertEqual(_pitick2latex(-1 * pi / 2), r'$-\frac{\pi}{2}$')
self.assertEqual(_pitick2latex(-2 * pi / 2), r'$-\pi$')
self.assertEqual(_pitick2latex(0.5), r'0.500')
self.assertEqual(_pitick2latex(3 * pi + 0.01), r'9.43')
self.assertEqual(_pitick2latex(30 * pi + 0.01), r'94.3')
self.assertEqual(_pitick2latex(300 * pi + 0.01), r'942.')
self.assertEqual(_pitick2latex(3000 * pi + 0.01), r'9.42e+03')
def pi_ticks(ax2):
minmax2 = ax2.yaxis.get_data_interval()
yticks2 = np.arange(minmax2[0] - minmax2[0] % (np.pi / 2), minmax2[1] - minmax2[1] % (np.pi / 2) + np.pi, np.pi / 2)
ax2.set_yticks(yticks2)
ax2.set_yticklabels([_pitick2latex(x) for x in yticks2])
def test_pitick2latex(self):
self.assertEqual(_pitick2latex(3 * pi / 2), r'$\frac{3\pi}{2}$')
self.assertEqual(_pitick2latex(2 * pi / 2), r'$\pi$')
self.assertEqual(_pitick2latex(1 * pi / 2), r'$\frac{\pi}{2}$')
self.assertEqual(_pitick2latex(0 * pi / 2), r'$0$')
self.assertEqual(_pitick2latex(-1 * pi / 2), r'$-\frac{\pi}{2}$')
self.assertEqual(_pitick2latex(-2 * pi / 2), r'$-\pi$')
self.assertEqual(_pitick2latex(0.5), r'0.500')
self.assertEqual(_pitick2latex(3 * pi + 0.01), r'9.43')
self.assertEqual(_pitick2latex(30 * pi + 0.01), r'94.3')
self.assertEqual(_pitick2latex(300 * pi + 0.01), r'942.')
self.assertEqual(_pitick2latex(3000 * pi + 0.01), r'9.42e+03')
def test_pitick2latex(self):
assert _pitick2latex(3 * pi / 2) == r'$\frac{3\pi}{2}$'
assert _pitick2latex(2 * pi / 2) == r'$\pi$'
assert _pitick2latex(1 * pi / 2) == r'$\frac{\pi}{2}$'
assert _pitick2latex(0 * pi / 2) == r'$0$'
assert _pitick2latex(-1 * pi / 2) == r'$-\frac{\pi}{2}$'
assert _pitick2latex(-2 * pi / 2) == r'$-\pi$'
assert _pitick2latex(0.5) == r'0.500'
assert _pitick2latex(3 * pi + 0.01) == r'9.43'
assert _pitick2latex(30 * pi + 0.01) == r'94.3'
assert _pitick2latex(300 * pi + 0.01) == r'942.'
assert _pitick2latex(3000 * pi + 0.01) == r'9.42e+03'
def plot_response(info):
import matplotlib as mpl
import matplotlib.pyplot as plt
mpl.use('Agg')
from matplotlib.ticker import FuncFormatter
# set up figure
fig = plt.figure(figsize=(7, 10), dpi=200)
gs = fig.add_gridspec(3, 1)
gs.update(wspace=0.05, hspace=0.10)
color = {"color": "0.7"}
# stuff to plot
amplitude = np.abs(info['resp']) / info['value']
freqs = info['freqs']
xmin = freqs[0]
xmax = freqs[-1]
# plot Response
ax1 = fig.add_subplot(gs[0, 0])
ax1.loglog(freqs, amplitude, linewidth=2, color='black')
minmax = ax1.get_ylim()
ax1.set_xlim(xmin, xmax)
ax1.set_ylim(amplitude[0] * .1, minmax[1])
# find low freq corner
lowc, highc = find_flatband2(info['resp'], info['value'])
if not lowc and not highc:
lowc, highc = find_flatband(info['resp'], info['value'])
try:
lowcf = info['freqs'][lowc]
highcf = info['freqs'][highc]
except Exception as e:
print(f'problem with flatband\n\t{e}')
lowcf = 0
highcf = 0
pass
# add lines to plot
ax1.axvline(x=lowcf, ymin=0, ymax=1)
ax1.axvline(x=highcf, ymin=0, ymax=1)
# add text
txt = f"{lowcf:0.3f} Hz"
ax1.text(x=lowcf,
y=amplitude[0],
s=txt,
fontsize=8,
ha='center',
va='top',
bbox=dict(facecolor='white', edgecolor='black'))
txt = f"{highcf:0.3f} Hz"
ax1.text(x=highcf,
y=amplitude[0],
s=txt,
fontsize=8,
ha='center',
va='top',
bbox=dict(facecolor='white', edgecolor='black'))
# make things look good
formatter = FuncFormatter(lambda y, _: '{:.16g}'.format(y))
ax1.xaxis.set_major_formatter(formatter)
ax1.xaxis.grid(b=True, which="major", **color)
ax1.yaxis.grid(b=True, which="major", **color)
ax1.set_ylabel('Amplitude')
ax1.set_title(info['SEEDid'], fontsize=12)
# Plot phase
ax2 = fig.add_subplot(gs[1, 0], sharex=ax1)
ax2.semilogx()
ax2.plot(info['freqs'],
np.angle(info['resp'], deg=False),
linewidth=2,
color='black')
# make pretty labels
minmax2 = ax2.yaxis.get_data_interval()
yticks2 = np.arange(minmax2[0] - minmax2[0] % (np.pi / 2),
minmax2[1] - minmax2[1] % (np.pi / 2) + np.pi,
np.pi / 2)
ax2.set_yticks(yticks2)
ax2.set_yticklabels([_pitick2latex(x) for x in yticks2])
ax2.xaxis.set_major_formatter(formatter)
ax2.xaxis.grid(b=True, which="major", **color)
ax2.yaxis.grid(b=True, which="major", **color)
ax2.set_xlabel('Frequency (Hz)')
ax2.set_ylabel('Phase [rad]')
# legend
pos1 = ax2.get_position()
newax = [pos1.x0, pos1.y0, pos1.width * .58, pos1.height * .35]
fig = ax2.get_figure()
ax4 = fig.add_axes(newax)
ax4.patch.set_facecolor('lightgray')
ax4.patch.set_alpha(0.8)
ax4.xaxis.set_visible(False)
ax4.yaxis.set_visible(False)
ax4.set_xlim(0, 10)
ax4.set_ylim(0, 10)
in_units, value = convert_units(info['in_units'], info['value'])
txt = f"ncalib: {value:16.9g} x counts = {in_units}"
ax4.text(x=0.4, y=8, s=txt, ha="left", fontsize=10)
txt = f"ncalib evaluated at {info['freq']} Hz"
ax4.text(x=0.4, y=6, s=txt, ha="left", fontsize=10)
txt = f'Flatband $(\pm 1\sigma)$: {lowcf:0.3f} - {highcf:0.3f} Hz'
# txt+=r"$ (\pm 5 \%)$"
ax4.text(x=.4, y=4, s=txt, ha="left", fontsize=10)
txt = f"Nyquist: {info['sps']/2:0.2f} Hz"
ax4.text(x=.4, y=2, s=txt, ha="left", fontsize=10)
info['value'] = value
info['in_units'] = in_units
plt.savefig(info['outpng'], bbox_inches='tight')
return info