def __init__(self, fid):
if not Plot._is_flat_iter(fid.data):
raise ValueError('data must be flat iterable.')
if fid.data == [] or fid.data == None:
raise ValueError('data must exist.')
self.fid = fid
self.fig = pylab.figure(figsize=[15, 7.5])
self.phases = numpy.array([0.0, 0.0])
self.y = 0.0
self.ax = self.fig.add_subplot(111)
self.ax.plot(self.fid.data, color='k', linewidth=1.0)
self.ax.hlines(0, 0, len(self.fid.data)-1)
self.ax.set_xlim([0, len(self.fid.data)])
xtcks = numpy.linspace(0,1,10)*len(self.fid.data)
xtcks[-1] = xtcks[-1]-1
self.ax.set_xticks(xtcks)
self.ax.set_xlabel('PPM (%.2f MHz)'%(self.fid._params['reffrq']))
self.ax.set_xticklabels([numpy.round(self.fid._ppm[int(i)], 1) for i in xtcks])
ylims = numpy.array([-6, 6])*numpy.array([max(self.ax.get_ylim())]*2)
self.ax.set_ylim(ylims)
self.ax.grid()
self.visible = True
self.canvas = self.ax.figure.canvas
self.canvas.mpl_connect('motion_notify_event', self.onmove)
self.canvas.mpl_connect('button_press_event', self.press)
self.canvas.mpl_connect('button_release_event', self.release)
self.pressv = None
self.buttonDown = False
self.prev = (0, 0)
self.ax.text(0.05 *self.ax.get_xlim()[1],0.7 *self.ax.get_ylim()[1],'phasing\nleft - zero-order\nright - first order')
cursor = Cursor(self.ax, useblit=True, color='k', linewidth=0.5)
cursor.horizOn = False
pylab.show()
def guided_ringdown_fit(data_x, data_y):
"""
Guided fit of a ringdown. Takes *data_x* and *data_y* as ``pint``
Quantities with dimensions of time and voltage, respectively. Plots the
data and asks user to manually crop to select the region to fit.
It then does a rough linear fit to find initial parameters and performs
a nonlinear fit.
Finally, it plots the data with the curve fit overlayed and returns the
full-width at half-max (FWHM) with units.
"""
# Have user choose crop points
plt.plot(data_x, data_y)
cursor = Cursor(plt.gca(), useblit=True)
cursor.horizOn = False
(x1, y1), (x2, y2) = _ginput(2)
plt.close()
# Crop the data
i1 = searchsorted(data_x.magnitude, x1)
i2 = searchsorted(data_x.magnitude, x2)
data_x = data_x[i1:i2]
data_y = data_y[i1:i2]
# Set t0 = 0 so that the amplitude 'a' doesn't blow up if we
# have a large time offset
t = data_x - data_x[0]
amp = data_y / u.V
def decay(x, a, b, c):
return a * exp(b * x) + c
# Do linear fit to get initial parameter estimate
a0, b0, c0 = _linear_fit_decay(t.magnitude, amp.to('').magnitude)
# Do nonlinear fit
popt, pcov = curve_fit(decay,
t.magnitude,
amp.magnitude,
p0=[a0, b0, c0],
maxfev=2000)
a, b, c = popt
tau = Q_(-1 / b, t.units)
FWHM = (1 / (2 * pi * tau)).to('MHz')
fit = a * exp(-t / tau) + c
t.ito('ns')
plt.plot(t, fit, 'b-', lw=2, zorder=3)
plt.plot(t, amp, 'gx')
plt.title('Ringdown fit')
plt.xlabel('Time (ns)')
plt.ylabel('Transmission (arb. units)')
plt.legend(['Fitted Curve', 'Data Trace'])
plt.show()
return FWHM
def guided_ringdown_fit(data_x, data_y):
"""
Guided fit of a ringdown. Takes *data_x* and *data_y* as ``pint``
Quantities with dimensions of time and voltage, respectively. Plots the
data and asks user to manually crop to select the region to fit.
It then does a rough linear fit to find initial parameters and performs
a nonlinear fit.
Finally, it plots the data with the curve fit overlayed and returns the
full-width at half-max (FWHM) with units.
"""
# Have user choose crop points
plt.plot(data_x, data_y)
cursor = Cursor(plt.gca(), useblit=True)
cursor.horizOn = False
(x1, y1), (x2, y2) = _ginput(2)
plt.close()
# Crop the data
i1 = searchsorted(data_x.magnitude, x1)
i2 = searchsorted(data_x.magnitude, x2)
data_x = data_x[i1:i2]
data_y = data_y[i1:i2]
# Set t0 = 0 so that the amplitude 'a' doesn't blow up if we
# have a large time offset
t = data_x - data_x[0]
amp = data_y / u.V
def decay(x, a, b, c):
return a*exp(b*x) + c
# Do linear fit to get initial parameter estimate
a0, b0, c0 = _linear_fit_decay(t.magnitude, amp.to('').magnitude)
# Do nonlinear fit
popt, pcov = curve_fit(decay, t.magnitude, amp.magnitude, p0=[a0, b0, c0], maxfev=2000)
a, b, c = popt
tau = Q_(-1/b, t.units)
FWHM = (1 / (2*pi*tau)).to('MHz')
fit = a * exp(-t/tau) + c
t.ito('ns')
plt.plot(t, fit, 'b-', lw=2, zorder=3)
plt.plot(t, amp, 'gx')
plt.title('Ringdown fit')
plt.xlabel('Time (ns)')
plt.ylabel('Transmission (arb. units)')
plt.legend(['Fitted Curve', 'Data Trace'])
plt.show()
return FWHM
def choose_windows(spectrum, wstart, wend):
"""
Choose the windows interactively
Parameters
----------
spectrum: array;
Bi-dimensional array containing the spectrum. First column should be
wavelength and the second, flux.
wstart: int, float;
Starting wavelength.
wend: int, float;
Ending wavelength.
"""
#Define function that will obtain the cursor x position
def onselect(vmin, vmax):
""" Function that will obtain the cursor x position"""
windows.append(float(Decimal("%.2f" % vmin)))
windows.append(float(Decimal("%.2f" % vmax)))
plot_windows(windows)
plt.draw()
#Create a plot so the user can choose the windows
windows = [] #Set an empty window
axis = plt.subplot(111)
axis.plot(spectrum[:, 0], spectrum[:, 1], 'k-')
axis.hlines(1, wstart, wend, color = 'b', linestyles = 'dashed')
axis.set_xlim([wstart, wend])
axis.set_ylim([min(subselect_spectra \
(spectrum, wstart, wend)[1]) - 0.2, 1.05])
axis.set_xlabel(r'Wavelength $(\AA)$')
axis.set_ylabel('Normalized Flux')
span = SpanSelector(axis, onselect, 'horizontal', minspan = 0.05)
# Plot a vertical line at cursor position
cursor = Cursor(axis, useblit = True, color = 'red', linewidth = 1 )
cursor.horizOn = False
plt.show()
plt.clf()
return windows
from matplotlib.widgets import Cursor import pylab fig = pylab.figure(figsize=(8, 6)) ax = fig.add_axes([0.075, 0.25, 0.9, 0.725], axisbg='#FFFFCC') x, y = 4 * (pylab.rand(2, 100) - .5) ax.plot(x, y, 'o') ax.set_xlim(-2, 2) ax.set_ylim(-2, 2) # set useblit = True on gtkagg for enhanced performance cursor = Cursor(ax, useblit=True, color='red', linewidth=2) cursor.horizOn = False pylab.show()
s.values.pop(s.gamma)
s.values.pop(s.v)
def my_selector(event):
draw_arrow(event.xdata ,event.ydata)
plt.draw()
def click(label):
global lab_frame_toggle
global force_toggle
if label == "vehicle frame":
lab_frame_toggle = not lab_frame_toggle
else:
force_toggle= not force_toggle
lab_frame_toggle=False
force_toggle=False
rax = plt.axes([0.03, 0.1, 0.2, 0.15])
check = CheckButtons(rax, ('vehicle frame','show force'), (False,False))
check.on_clicked(click)
# set useblit = True on gtkagg for enhanced performance
cursor = Cursor(ax, useblit=True)
cursor.horizOn=False
cursor.vertOn=False
plt.ion()
plt.connect('button_press_event', my_selector)
#plt.connect('motion_notify_event', my_selector)
plt.show()
