xerr is +/- relative to the data:
*xerr*/*yerr*: [ scalar | N, Nx1, or 2xN array-like ]
If a scalar number, len(N) array-like object, or an Nx1
array-like object, errorbars are drawn at +/-value relative
to the data.
If a sequence of shape 2xN, errorbars are drawn at -row1
and +row2 relative to the data.
I think you want:
xdat=10**data_x_log
ax.errorbar(10**data_x_log,data_y,xerr=[xdat-error_x_lower,error_x_upper-xdat],ls='',marker='o')
Cheers, Jody
> On 7 Apr 2015, at 13:51 PM, Markus Haider <markus.hai...@uibk.ac.at> wrote:
>
> I have the error from a table which is in log units, and the error is
> given to be symmetric in log space.
>
> Cheers,
> Markus
>
> On 2015-04-07 16:40, Yuxiang Wang wrote:
>> Typo - "standard deviation OR standard error of mean", not "OF".
>>
>> Sorry.
>>
>> Shawn
>>
>>
>> On Tue, Apr 7, 2015 at 10:39 AM, Yuxiang Wang <yw...@virginia.edu> wrote:
>>> If you error bars denote standard deviation of standard error of mean,
>>> shouldn't they be non-symmetric in log scale?
>>>
>>> Shawn
>>>
>>> On Tue, Apr 7, 2015 at 10:11 AM, Markus Haider <markus.hai...@uibk.ac.at>
>>> wrote:
>>>> Hi,
>>>>
>>>> I am trying to make an errorbar plot with a logarithmic x-axis. I have
>>>> symmetric errors in logspace, however if I plot them, the errors are not
>>>> symmetric anymore, as you can see in the enclosed image. Am I
>>>> misunderstanding something or is this a bug?
>>>>
>>>> Thanks for your help,
>>>> Markus
>>>>
>>>> Here the code I used to produce the plot:
>>>>
>>>> import matplotlib.pyplot as plt
>>>>
>>>> import numpy as np
>>>>
>>>> data_x_log = np.array([13.0,15.0])
>>>>
>>>> data_y = np.array([0.5,1])
>>>>
>>>> error_x_log = np.array([0.5,1.])
>>>>
>>>> error_x_lower = 10**(data_x_log-error_x_log)
>>>>
>>>> error_x_upper = 10**(data_x_log+error_x_log)
>>>>
>>>> fig = plt.figure()
>>>>
>>>> ax = fig.add_subplot(111)
>>>>
>>>> ax.errorbar(10**data_x_log,data_y,xerr=[error_x_lower,error_x_upper],ls='',marker='o')
>>>>
>>>> ax.set_xscale('log')
>>>>
>>>> ax.set_xlim([1E11,1E17])
>>>>
>>>> ax.set_ylim([0,2])
>>>>
>>>> plt.savefig('error.png')
>>>>
>>>>
>>>> ------------------------------------------------------------------------------
>>>> BPM Camp - Free Virtual Workshop May 6th at 10am PDT/1PM EDT
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>>>
>>>
>>> --
>>> Yuxiang "Shawn" Wang
>>> Gerling Research Lab
>>> University of Virginia
>>> yw...@virginia.edu
>>> +1 (434) 284-0836
>>> https://sites.google.com/a/virginia.edu/yw5aj/
>>
>>
>
>
> ------------------------------------------------------------------------------
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> Develop your own process in accordance with the BPMN 2 standard
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--
Jody Klymak
http://web.uvic.ca/~jklymak/
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Develop your own process in accordance with the BPMN 2 standard
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