Hello,
Stealing a solution from ->
http://old.nabble.com/scientific-notation-in-ticklabels-for-linear-plot-td29993489.html
This seems to produce nicer looking y tick-labels. I tend to switch to
log-scale in cases like yours, but this one provides a clean solution as
well.
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.ticker import FuncFormatter
def scinot(x,pos=None):
if x == 0:
s = '0'
else:
xp = int(np.floor(np.log10(np.abs(x))))
mn = x/10.**xp
# Here we truncate to 2 significant digits -- may not be enough
# in all cases
s = '$'+str('%.3f'%mn) +'\\times 10^{'+str(xp)+'}$'
return s
A = np.array([[ 1.00000000e+00, 0.00000000e+00, 1.99236400e-04],
[ 2.00000000e+00, 1.00000000e+00, 2.00043800e-04],
[ 3.00000000e+00, 2.00000000e+00, 2.00046000e-04],
[ 4.00000000e+00, 3.00000000e+00, 2.00043900e-04]])
fig = plt.figure()
ax = fig.add_subplot(111)
ax.plot(A[:,1],A[:,2])
ax.yaxis.set_major_formatter(FuncFormatter(scinot))
y_min,y_max = ax.get_ylim()
print 'y range', y_max-y_min
plt.show()
On Mon, Feb 20, 2012 at 8:32 AM, Nils Wagner
<nwag...@iam.uni-stuttgart.de>wrote:
> Hi all,
>
> How can I improve the presentation of yticks for a small y range, e.g.
>
> y_min,y_max = ax.get_ylim()
>>>
>>>> y_max-y_min
>>>>
>>> 8.9999999999996767e-07
>
> I would like to avoid "+1.992 x 10^{-4}" in the attached figure.
>
> import numpy as np
> import matplotlib.pyplot as plt
> from matplotlib.ticker import ScalarFormatter
> formatter = ScalarFormatter(useMathText=**True)
> formatter.set_scientific(True)
> formatter.set_powerlimits((-**15,15))
> #A = np.loadtxt('trash.dat')
> A = np.array([[ 1.00000000e+00, 0.00000000e+00, 1.99236400e-04],
> [ 2.00000000e+00, 1.00000000e+00, 2.00043800e-04],
> [ 3.00000000e+00, 2.00000000e+00, 2.00046000e-04],
> [ 4.00000000e+00, 3.00000000e+00, 2.00043900e-04]])
>
>
> fig = plt.figure()
> ax = fig.add_subplot(111)
> ax.yaxis.set_major_formatter(**formatter)
> ax.plot(A[:,1],A[:,2])
> y_min,y_max = ax.get_ylim()
> print 'y range', y_max-y_min
> plt.show()
>
>
> Nils
>
>
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