[matplotlib-devel] append a NaN (missing value) to ndarray

2011-09-29 Thread Chao YUE
Dear all, I have a variable d which has several years plus 11 month data
(len(d)%12=11). so I want to append a NaN to the data so that it constitutes
complete
several years of data.

but I cannot use "d=np.concatenate(d,np.array(np.nan))" to finish this job.

another question, is there a simple function like is.Nan(ndarray) in numpy
to check the missing value? and how can I get the index of the missing
value?

Thanks a lot,

Chao

In [246]: d
Out[246]:
array([-24. , -12.9, -14. ,   4.2,   7.3,  12.9,  18.5,  16.9,  10.7,
 7.6,  -1.9,  -9.8, -12. , -16.6, -13.3,   5. ,  12.2,  14. ,
16.5,  15.6,  11.8,   6.4,  -6.6, -14.8, -17.6, -15.4,  -3.7,
-2.1,   6.9,  12.8,  17. ,  16.7,   9. ,   4.5, -11.9, -18.1,
   -18.4, -19.5,  -3.4,   6.4,   8.5,  13.5,  18.3,  16.5,  10.4,
 1.7,  -9.6, -19.5, -17.8, -20.9, -10.9,   0.8,   7.7,  14.7,
20.4,  16.2,   9.1,   6.9,  -8.6, -17.1, -16.6, -20.8, -14.1,
-4.7,  10.7,  15.8,  18.5,  17.1,  12.9,   5.2,  -6. , -18.4,
   -20.5, -22.6,  -8.3,   7. ,  10.9,  14. ,  17.1,  18.6,  10.1,
 2.1,  -1.1, -20.8, -32.9, -17.7, -12.2,  -0.4,   9.5,  14.6,
17.3,  15.1,  11.1,   2.6,  -9.9, -16.9, -22.9, -18.1, -15.4,
 0.5,  11. ,  12.4,  16.9,  14.7,   9.7,  -0.3, -10.7, -20.7,
   -23.1, -13.5, -10.7,   7.6,  11. ,  14.4,  16.8,  15.6,  11.2,
 4.2,  -3.5, -12.2, -19.9, -13.2, -10.1,  -0.1,   8.5,  13.6,
17.2,  17.6,  10.1,   6.3,  -2.3, -12.4, -27.2,  -9.1, -13. ,
-6.2,   7.4,  12.9,  17.3,  14.8,   9.5,   4.3,  -1.1,  -8.6,
   -17.5, -18.5, -15.9,   3.5,   9.6,  15.7,  18.4,  17.1,   9.4,
 4.5, -15.1, -21.9, -21.2, -18.5, -12.2,  -2.1,  10.4,  16.7,
17. ,  16.1,   8.6,   3.9,  -4.8, -16. , -20.9, -16.8,  -9.3,
 0.9,  10.3,  13.8,  19. ,  15.3,  11.1,   3.1,  -5.5, -14.9,
   -12.8, -17.5,  -6.9,   3.7,  11.1,  12.5,  16.5,  16.5,  10.2,
 4.2,  -8.8, -16.3, -24.4, -17.2,  -4.7,   3.5,   8. ,  14. ,
18.3,  14.6,   8.9,  -0.4,  -9.1,  -8.4, -20.8, -15.5, -12. ,
 2.3,   9.8,  13.6,  18.4,  16.8,  11.9,   3.9,  -8. , -13.6,
   -17.4, -13.1,  -6.9,   0.2,  10.6,  17.6,  17.2,  18.8,   6.3,
 3.4,  -7.6, -22.7, -19.5, -20.9, -11.7,   1.7,   9.8,  16.6,
16.4,  16.2,  10.6,   6.1,  -3.6, -14.4, -22.2, -17.8,  -7.5,
 3.2,   8.9,  14.8,  18.6,  17.7,  12.9,   8.4,  -6.9, -16.8,
   -16.4, -10.1, -15.6,   3.5,  11.2,  14.7,  19.5,  14.6,   8.3,
 4.4,  -8.2, -22.3, -23. , -21.8, -14.1,   2.5,   9.1,  15. ,
17.9,  16.4,   5.3,   5.2, -11.6, -14.1, -29. , -20.5,  -8.1,
-0.7,  10.1,  13.9,  17.3,  15.5,  12.4,   3.4, -13.3, -15.1,
   -21. , -19.5, -12.5,  -2.4,   8.9,  13.5,  17.6,  17.3,  14.4,
 2.7,  -5.1, -15.5, -20.7, -14.5,  -3.2,   2.7,   9.6,  14.3,
16. ,  13.7,  10.9,   3.2,  -4.1, -18.6, -29.2, -16.7, -11. ,
 5.1,   9.2,  12.5,  16.2,  17.5,  10.2,  -0.8,  -5.3, -11.4,
   -20.9, -15. , -12.8,   2.1,   8.8,  16.9,  18.2,  16.1,   9.9,
 3.4,  -9. , -23.5, -25.2, -15.4, -10.3,   2.5,  11.7,  14.5,
15.4,  17.8,   9.9,   3.5,  -7.4, -20.7, -25.1, -22.6,  -9.7,
 1.2,  11.6,  16.3,  14.8,  17.4,   5.9,   0.9,  -6.8, -21.4,
   -16.6, -15.8,  -4.1,   1.7,  10.9,  14.5,  16.8,  16.8,   9.8,
 4.2, -12.8, -18.5, -25.2, -16.8, -14.6,   2.4,   6.2,  14.9,
17.9,  13.6,   7.6,   5.3,  -4.2,  -8.5, -17.5, -17.7, -13.4,
 0.1,   8.8,  14.3,  19.3,  14. ,  10. ,   3.5,  -6.1, -16.8,
   -16.5, -12.5, -10. ,   5.8,  11.6,  14.4,  17.7,  16.7,  11.6,
 1.4,  -7.3, -16. , -22.2,  -7.8,  -5.1,   6. ,  13.6,  15.5,
16.3,  12.3,   9.8,   5.2,  -7.9, -21.1, -24.2, -17.4,  -7.6,
 2.5,  11.7,  15.4,  16.7,  14.4,  10.6,   5.9, -10.4, -18. ,
   -21.5, -25.6, -10.2,  -2.9,   7.8,  15. ,  19.2,  15.3,  11.3,
 4.4,  -6. , -14.4, -21. , -15.4, -11.5,   7.4,  13.3,  15.2,
17.6,  15.1,   9.3,   5. ,  -4.4, -19.4, -12.6, -11.4,  -2.6,
 3.2,  10.9,  14.4,  17.9,  19.1,  11.8,   1.9,  -0.9, -14.2,
   -29.7, -17.6,  -9.6,   0.5,   9.2,  14.3,  17.7,  14.6,  10.1,
 4.2, -10.7, -14.4, -14.5, -13.1,  -8.5,   0.5,   8. ,  15.1,
18.8,  19.4,   9.3,   4.4,  -3.2, -23.6, -14.2,  -6.7,  -8. ,
 6.8,   9. ,  15.8,  18.6,  18.8,   7.6,   2.2, -11.3, -21.2,
   -17.2, -19.5,  -4.9,   4.3,  11.8,  12.3,  17.1,  14.3,   7.7,
 3. , -16.7, -14.2, -11.7, -16.4,  -3.8,   2.1,  12.1,  15.3,
16.9,  16.2,   8.5,   4.7, -10.7, -10.7, -11.6, -10.2,  -6.2,
 6.4,  12.7,  17.9,  17.3,  13.7,  12.6,   3.6,  -2.7, -10.8,
   -20.3, -15.3,  -6.8,   4. ,  13.9,  19.3,  18.5,  15.8,  10.9,
 3. ,  -5.3, -12.3, -15.7, -16.7, -12.3,   3.5,  10.7,  16. ,
19.8,  17.1,  10.8,   4.1,  -9.1, -18.6, -15.9, -17.7,  -4.2,
 2.6,  10.3,  16.4,  17.3,  16.9,  12.2,   1.7,  -9.7, -21.7,
   -19.3, -10.7,  -9.5,   4.7,  11.3,  16.5,  18.5,  19.8,

Re: [matplotlib-devel] append a NaN (missing value) to ndarray

2011-09-29 Thread Benjamin Root
On Thu, Sep 29, 2011 at 9:33 AM, Chao YUE  wrote:

> Dear all, I have a variable d which has several years plus 11 month data
> (len(d)%12=11). so I want to append a NaN to the data so that it constitutes
> complete
> several years of data.
>
> but I cannot use "d=np.concatenate(d,np.array(np.nan))" to finish this job.
>
>
> another question, is there a simple function like is.Nan(ndarray) in numpy
> to check the missing value? and how can I get the index of the missing
> value?
>
> Thanks a lot,
>
> Chao
>
> In [246]: d
> Out[246]:
> array([-24. , -12.9, -14. ,   4.2,   7.3,  12.9,  18.5,  16.9,  10.7,
>  7.6,  -1.9,  -9.8, -12. , -16.6, -13.3,   5. ,  12.2,  14. ,
> 16.5,  15.6,  11.8,   6.4,  -6.6, -14.8, -17.6, -15.4,  -3.7,
> -2.1,   6.9,  12.8,  17. ,  16.7,   9. ,   4.5, -11.9, -18.1,
>-18.4, -19.5,  -3.4,   6.4,   8.5,  13.5,  18.3,  16.5,  10.4,
>  1.7,  -9.6, -19.5, -17.8, -20.9, -10.9,   0.8,   7.7,  14.7,
> 20.4,  16.2,   9.1,   6.9,  -8.6, -17.1, -16.6, -20.8, -14.1,
> -4.7,  10.7,  15.8,  18.5,  17.1,  12.9,   5.2,  -6. , -18.4,
>-20.5, -22.6,  -8.3,   7. ,  10.9,  14. ,  17.1,  18.6,  10.1,
>  2.1,  -1.1, -20.8, -32.9, -17.7, -12.2,  -0.4,   9.5,  14.6,
> 17.3,  15.1,  11.1,   2.6,  -9.9, -16.9, -22.9, -18.1, -15.4,
>  0.5,  11. ,  12.4,  16.9,  14.7,   9.7,  -0.3, -10.7, -20.7,
>-23.1, -13.5, -10.7,   7.6,  11. ,  14.4,  16.8,  15.6,  11.2,
>  4.2,  -3.5, -12.2, -19.9, -13.2, -10.1,  -0.1,   8.5,  13.6,
> 17.2,  17.6,  10.1,   6.3,  -2.3, -12.4, -27.2,  -9.1, -13. ,
> -6.2,   7.4,  12.9,  17.3,  14.8,   9.5,   4.3,  -1.1,  -8.6,
>-17.5, -18.5, -15.9,   3.5,   9.6,  15.7,  18.4,  17.1,   9.4,
>  4.5, -15.1, -21.9, -21.2, -18.5, -12.2,  -2.1,  10.4,  16.7,
> 17. ,  16.1,   8.6,   3.9,  -4.8, -16. , -20.9, -16.8,  -9.3,
>  0.9,  10.3,  13.8,  19. ,  15.3,  11.1,   3.1,  -5.5, -14.9,
>-12.8, -17.5,  -6.9,   3.7,  11.1,  12.5,  16.5,  16.5,  10.2,
>  4.2,  -8.8, -16.3, -24.4, -17.2,  -4.7,   3.5,   8. ,  14. ,
> 18.3,  14.6,   8.9,  -0.4,  -9.1,  -8.4, -20.8, -15.5, -12. ,
>  2.3,   9.8,  13.6,  18.4,  16.8,  11.9,   3.9,  -8. , -13.6,
>-17.4, -13.1,  -6.9,   0.2,  10.6,  17.6,  17.2,  18.8,   6.3,
>  3.4,  -7.6, -22.7, -19.5, -20.9, -11.7,   1.7,   9.8,  16.6,
> 16.4,  16.2,  10.6,   6.1,  -3.6, -14.4, -22.2, -17.8,  -7.5,
>  3.2,   8.9,  14.8,  18.6,  17.7,  12.9,   8.4,  -6.9, -16.8,
>-16.4, -10.1, -15.6,   3.5,  11.2,  14.7,  19.5,  14.6,   8.3,
>  4.4,  -8.2, -22.3, -23. , -21.8, -14.1,   2.5,   9.1,  15. ,
> 17.9,  16.4,   5.3,   5.2, -11.6, -14.1, -29. , -20.5,  -8.1,
> -0.7,  10.1,  13.9,  17.3,  15.5,  12.4,   3.4, -13.3, -15.1,
>-21. , -19.5, -12.5,  -2.4,   8.9,  13.5,  17.6,  17.3,  14.4,
>  2.7,  -5.1, -15.5, -20.7, -14.5,  -3.2,   2.7,   9.6,  14.3,
> 16. ,  13.7,  10.9,   3.2,  -4.1, -18.6, -29.2, -16.7, -11. ,
>  5.1,   9.2,  12.5,  16.2,  17.5,  10.2,  -0.8,  -5.3, -11.4,
>-20.9, -15. , -12.8,   2.1,   8.8,  16.9,  18.2,  16.1,   9.9,
>  3.4,  -9. , -23.5, -25.2, -15.4, -10.3,   2.5,  11.7,  14.5,
> 15.4,  17.8,   9.9,   3.5,  -7.4, -20.7, -25.1, -22.6,  -9.7,
>  1.2,  11.6,  16.3,  14.8,  17.4,   5.9,   0.9,  -6.8, -21.4,
>-16.6, -15.8,  -4.1,   1.7,  10.9,  14.5,  16.8,  16.8,   9.8,
>  4.2, -12.8, -18.5, -25.2, -16.8, -14.6,   2.4,   6.2,  14.9,
> 17.9,  13.6,   7.6,   5.3,  -4.2,  -8.5, -17.5, -17.7, -13.4,
>  0.1,   8.8,  14.3,  19.3,  14. ,  10. ,   3.5,  -6.1, -16.8,
>-16.5, -12.5, -10. ,   5.8,  11.6,  14.4,  17.7,  16.7,  11.6,
>  1.4,  -7.3, -16. , -22.2,  -7.8,  -5.1,   6. ,  13.6,  15.5,
> 16.3,  12.3,   9.8,   5.2,  -7.9, -21.1, -24.2, -17.4,  -7.6,
>  2.5,  11.7,  15.4,  16.7,  14.4,  10.6,   5.9, -10.4, -18. ,
>-21.5, -25.6, -10.2,  -2.9,   7.8,  15. ,  19.2,  15.3,  11.3,
>  4.4,  -6. , -14.4, -21. , -15.4, -11.5,   7.4,  13.3,  15.2,
> 17.6,  15.1,   9.3,   5. ,  -4.4, -19.4, -12.6, -11.4,  -2.6,
>  3.2,  10.9,  14.4,  17.9,  19.1,  11.8,   1.9,  -0.9, -14.2,
>-29.7, -17.6,  -9.6,   0.5,   9.2,  14.3,  17.7,  14.6,  10.1,
>  4.2, -10.7, -14.4, -14.5, -13.1,  -8.5,   0.5,   8. ,  15.1,
> 18.8,  19.4,   9.3,   4.4,  -3.2, -23.6, -14.2,  -6.7,  -8. ,
>  6.8,   9. ,  15.8,  18.6,  18.8,   7.6,   2.2, -11.3, -21.2,
>-17.2, -19.5,  -4.9,   4.3,  11.8,  12.3,  17.1,  14.3,   7.7,
>  3. , -16.7, -14.2, -11.7, -16.4,  -3.8,   2.1,  12.1,  15.3,
> 16.9,  16.2,   8.5,   4.7, -10.7, -10.7, -11.6, -10.2,  -6.2,
>  6.4,  12.7,  17.9,  17.3,  13.7,  12.6,   3.6,  -2.7, -10.8,
>-20.3, -15.3,  -6.8,   4. ,  13.9,  19.3,  18.5,  15.8,  10.9,
>  3. ,  -5.3, -12.3, -15.7, -16.7, -12.3,   3.5,  10.7,  16

Re: [matplotlib-devel] append a NaN (missing value) to ndarray

2011-09-29 Thread Pauli Virtanen
29.09.2011 17:38, Benjamin Root kirjoitti:
[clip]
> but I cannot use "d=np.concatenate(d,np.array(np.nan))" to finish this job.
[clip]

Do

d = np.concatenate([d, np.array([np.nan])])

or

d = np.hstack([d, np.nan])

or

d = np.r_[d, np.nan]


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Re: [matplotlib-devel] append a NaN (missing value) to ndarray

2011-09-29 Thread Chao YUE
Thanks Ben! it works fine! help me a lot.

Chao

2011/9/29 Pauli Virtanen 

> 29.09.2011 17:38, Benjamin Root kirjoitti:
> [clip]
> > but I cannot use "d=np.concatenate(d,np.array(np.nan))" to finish this
> job.
> [clip]
>
> Do
>
>d = np.concatenate([d, np.array([np.nan])])
>
> or
>
>d = np.hstack([d, np.nan])
>
> or
>
>d = np.r_[d, np.nan]
>
>
>
> --
> All the data continuously generated in your IT infrastructure contains a
> definitive record of customers, application performance, security
> threats, fraudulent activity and more. Splunk takes this data and makes
> sense of it. Business sense. IT sense. Common sense.
> http://p.sf.net/sfu/splunk-d2dcopy1
> ___
> Matplotlib-devel mailing list
> [email protected]
> https://lists.sourceforge.net/lists/listinfo/matplotlib-devel
>



-- 
***
Chao YUE
Laboratoire des Sciences du Climat et de l'Environnement (LSCE-IPSL)
UMR 1572 CEA-CNRS-UVSQ
Batiment 712 - Pe 119
91191 GIF Sur YVETTE Cedex
Tel: (33) 01 69 08 29 02; Fax:01.69.08.77.16

--
All the data continuously generated in your IT infrastructure contains a
definitive record of customers, application performance, security
threats, fraudulent activity and more. Splunk takes this data and makes
sense of it. Business sense. IT sense. Common sense.
http://p.sf.net/sfu/splunk-d2dcopy1___
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Re: [matplotlib-devel] append a NaN (missing value) to ndarray

2011-09-29 Thread Chao YUE
Thanks a lot Pauli!

Best,

Chao

2011/9/29 Pauli Virtanen 

> 29.09.2011 17:38, Benjamin Root kirjoitti:
> [clip]
> > but I cannot use "d=np.concatenate(d,np.array(np.nan))" to finish this
> job.
> [clip]
>
> Do
>
>d = np.concatenate([d, np.array([np.nan])])
>
> or
>
>d = np.hstack([d, np.nan])
>
> or
>
>d = np.r_[d, np.nan]
>
>
>
> --
> All the data continuously generated in your IT infrastructure contains a
> definitive record of customers, application performance, security
> threats, fraudulent activity and more. Splunk takes this data and makes
> sense of it. Business sense. IT sense. Common sense.
> http://p.sf.net/sfu/splunk-d2dcopy1
> ___
> Matplotlib-devel mailing list
> [email protected]
> https://lists.sourceforge.net/lists/listinfo/matplotlib-devel
>



-- 
***
Chao YUE
Laboratoire des Sciences du Climat et de l'Environnement (LSCE-IPSL)
UMR 1572 CEA-CNRS-UVSQ
Batiment 712 - Pe 119
91191 GIF Sur YVETTE Cedex
Tel: (33) 01 69 08 29 02; Fax:01.69.08.77.16

--
All the data continuously generated in your IT infrastructure contains a
definitive record of customers, application performance, security
threats, fraudulent activity and more. Splunk takes this data and makes
sense of it. Business sense. IT sense. Common sense.
http://p.sf.net/sfu/splunk-d2dcopy1___
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[matplotlib-devel] Typo in backend_qt4.py (matplotlib-1.1.0-rc1-py2.7-python.org-macosx10.3.dmg)?

2011-09-29 Thread Marko Luther
Hi,

just received 

Traceback (most recent call last):
  File 
"/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/matplotlib/backends/backend_qt4.py",
 line 449, in edit_parameters
fmt = "%(axes_repr)s (%(ylabel)s)" % ylabel
TypeError: format requires a mapping

should this postfix "% label" in line 449 be removed?

Cheers and thanks for the great work,
M.

PS: Why is there no subplots.svg (only icon in NavigationToolbar with only a 
.png version)

PPS: Another one caused by clicking the green flag icon ("Edit curves and ..") 
in NavigationToolbar

NotImplementedError: TransformNode instances can not be copied. Consider using 
frozen() instead.
Traceback (most recent call last):
  File 
"/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/matplotlib/backends/backend_qt4.py",
 line 463, in edit_parameters
figureoptions.figure_edit(axes, self)
  File 
"/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/matplotlib/backends/qt4_editor/figureoptions.py",
 line 132, in figure_edit
icon=get_icon('qt4_editor_options.svg'), apply=apply_callback)
  File 
"/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/matplotlib/backends/qt4_editor/formlayout.py",
 line 511, in fedit
dialog = FormDialog(data, title, comment, icon, parent, apply)
  File 
"/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/matplotlib/backends/qt4_editor/formlayout.py",
 line 416, in __init__
parent=self)
  File 
"/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/matplotlib/backends/qt4_editor/formlayout.py",
 line 390, in __init__
widget = FormComboWidget(data, comment=comment, parent=self)
  File 
"/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/matplotlib/backends/qt4_editor/formlayout.py",
 line 368, in __init__
widget = FormWidget(data, comment=comment, parent=self)
  File 
"/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/matplotlib/backends/qt4_editor/formlayout.py",
 line 233, in __init__
self.data = deepcopy(data)
  File 
"/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/copy.py", line 
163, in deepcopy
y = copier(x, memo)
  File 
"/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/copy.py", line 
230, in _deepcopy_list
y.append(deepcopy(a, memo))
  File 
"/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/copy.py", line 
163, in deepcopy
y = copier(x, memo)
  File 
"/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/copy.py", line 
237, in _deepcopy_tuple
y.append(deepcopy(a, memo))
  File 
"/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/copy.py", line 
163, in deepcopy
y = copier(x, memo)
  File 
"/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/copy.py", line 
230, in _deepcopy_list
y.append(deepcopy(a, memo))
  File 
"/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/copy.py", line 
163, in deepcopy
y = copier(x, memo)
  File 
"/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/copy.py", line 
298, in _deepcopy_inst
state = deepcopy(state, memo)
  File 
"/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/copy.py", line 
163, in deepcopy
y = copier(x, memo)
  File 
"/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/copy.py", line 
257, in _deepcopy_dict
y[deepcopy(key, memo)] = deepcopy(value, memo)
  File 
"/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/copy.py", line 
174, in deepcopy
y = copier(memo)
  File 
"/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/matplotlib/transforms.py",
 line 96, in __copy__
"Consider using frozen() instead.")
NotImplementedError: TransformNode instances can not be copied. Consider using 
frozen() instead.
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