Matplotlib\'s line2D
objects, such as those returned by a call to plot
, have a convenient method, set_data
, that let\'s me quickly upd
Thanks to the help from @tacaswell.
Below is the python function that can both update xerr
and yerr
, as well as the x_data
and y_data
for the baseline plotting:
def adjustErrbarxy(self, errobj, x, y, x_error, y_error):
ln, (errx_top, errx_bot, erry_top, erry_bot), (barsx, barsy) = errobj
x_base = x
y_base = y
xerr_top = x_base + x_error
xerr_bot = x_base - x_error
yerr_top = y_base + y_error
yerr_bot = y_base - y_error
errx_top.set_xdata(xerr_top)
errx_bot.set_xdata(xerr_bot)
errx_top.set_ydata(y_base)
errx_bot.set_ydata(y_base)
erry_top.set_xdata(x_base)
erry_bot.set_xdata(x_base)
erry_top.set_ydata(yerr_top)
erry_bot.set_ydata(yerr_bot)
new_segments_x = [np.array([[xt, y], [xb,y]]) for xt, xb, y in zip(xerr_top, xerr_bot, y_base)]
new_segments_y = [np.array([[x, yt], [x,yb]]) for x, yt, yb in zip(x_base, yerr_top, yerr_bot)]
barsx.set_segments(new_segments_x)
barsy.set_segments(new_segments_y)
The first input parameter (self
is for python class) is the already created errorbar
plot handler, that is also the object whose properties need to be updated; x
and y
are the updated numpy
arrays which should be shown the average values along x
and y
axis; the last two parameters x_error
and y_error
are the errorbar
ranges calculated for x
and y
arrays. If only the errorbars are need to be updated, the x_base
and y_base
should be writen as ln.get_xdata()
and ln.get_ydata()
, respectively.
Up to now, the solution for the errorbar
updating in matplotlib
is truly non-trivial, hope it be much easier in the future versions.
I followed the link provided by Tong and learned that there is a problem in his code - input of self variable is not needed. There is also a more generalized solution provided by mitpre - I used it and it works great. Below is the code for quicker reference:
def update_errorbar(errobj, x, y, xerr=None, yerr=None):
ln, caps, bars = errobj
if len(bars) == 2:
assert xerr is not None and yerr is not None, "Your errorbar object has 2 dimension of error bars defined. You must provide xerr and yerr."
barsx, barsy = bars # bars always exist (?)
try: # caps are optional
errx_top, errx_bot, erry_top, erry_bot = caps
except ValueError: # in case there is no caps
pass
elif len(bars) == 1:
assert (xerr is None and yerr is not None) or\
(xerr is not None and yerr is None), \
"Your errorbar object has 1 dimension of error bars defined. You must provide xerr or yerr."
if xerr is not None:
barsx, = bars # bars always exist (?)
try:
errx_top, errx_bot = caps
except ValueError: # in case there is no caps
pass
else:
barsy, = bars # bars always exist (?)
try:
erry_top, erry_bot = caps
except ValueError: # in case there is no caps
pass
ln.set_data(x,y)
try:
errx_top.set_xdata(x + xerr)
errx_bot.set_xdata(x - xerr)
errx_top.set_ydata(y)
errx_bot.set_ydata(y)
except NameError:
pass
try:
barsx.set_segments([np.array([[xt, y], [xb, y]]) for xt, xb, y in zip(x + xerr, x - xerr, y)])
except NameError:
pass
try:
erry_top.set_xdata(x)
erry_bot.set_xdata(x)
erry_top.set_ydata(y + yerr)
erry_bot.set_ydata(y - yerr)
except NameError:
pass
try:
barsy.set_segments([np.array([[x, yt], [x, yb]]) for x, yt, yb in zip(x, y + yerr, y - yerr)])
except NameError:
pass