axes.set_title('step approach %s' % timestamp)
axes.plot(pos_array, def_array, '.', label=timestamp)
#_pylab.legend(loc='best')
+ figure.canvas.draw()
figure.show()
+ if not _matplotlib.is_interactive():
+ _matplotlib_pyplot.show()
if return_data:
data = {
(input_data, input_names)]:
for i,name in enumerate(names):
axes.plot(d[:,i], label=name)
+ figure.canvas.draw()
figure.show()
+ if not _matplotlib.is_interactive():
+ _matplotlib_pyplot.show()
return input_data
def named_ramp(self, data, frequency, output_names, input_names=()):
[fit_fn(start_pos, params), fit_fn(params[2], params),
fit_fn(final_pos, params)], '-',label='fit')
#_pylab.legend(loc='best')
+ figure.canvas.draw()
figure.show()
+ if not _matplotlib.is_interactive():
+ _matplotlib_pyplot.show()
# check that the fit is reasonable
# params[1] is slope in non-contact region
timestamp = _time.strftime('%H%M%S')
axes.set_title('wiggle for interference %s' % timestamp)
plot = axes.plot(output, output, 'b.-')
+ figure.canvas.draw()
figure.show()
- _matplotlib_pyplot.draw()
- _matplotlib_pyplot.show()
+ if not _matplotlib.is_interactive():
+ _matplotlib_pyplot.show()
return (figure, axes, plot)
def _update_plot(figure, axes, plot, cycle, data):