You can subscribe to this list here.
| 2003 |
Jan
|
Feb
|
Mar
|
Apr
|
May
|
Jun
|
Jul
|
Aug
|
Sep
|
Oct
(1) |
Nov
(33) |
Dec
(20) |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2004 |
Jan
(7) |
Feb
(44) |
Mar
(51) |
Apr
(43) |
May
(43) |
Jun
(36) |
Jul
(61) |
Aug
(44) |
Sep
(25) |
Oct
(82) |
Nov
(97) |
Dec
(47) |
| 2005 |
Jan
(77) |
Feb
(143) |
Mar
(42) |
Apr
(31) |
May
(93) |
Jun
(93) |
Jul
(35) |
Aug
(78) |
Sep
(56) |
Oct
(44) |
Nov
(72) |
Dec
(75) |
| 2006 |
Jan
(116) |
Feb
(99) |
Mar
(181) |
Apr
(171) |
May
(112) |
Jun
(86) |
Jul
(91) |
Aug
(111) |
Sep
(77) |
Oct
(72) |
Nov
(57) |
Dec
(51) |
| 2007 |
Jan
(64) |
Feb
(116) |
Mar
(70) |
Apr
(74) |
May
(53) |
Jun
(40) |
Jul
(519) |
Aug
(151) |
Sep
(132) |
Oct
(74) |
Nov
(282) |
Dec
(190) |
| 2008 |
Jan
(141) |
Feb
(67) |
Mar
(69) |
Apr
(96) |
May
(227) |
Jun
(404) |
Jul
(399) |
Aug
(96) |
Sep
(120) |
Oct
(205) |
Nov
(126) |
Dec
(261) |
| 2009 |
Jan
(136) |
Feb
(136) |
Mar
(119) |
Apr
(124) |
May
(155) |
Jun
(98) |
Jul
(136) |
Aug
(292) |
Sep
(174) |
Oct
(126) |
Nov
(126) |
Dec
(79) |
| 2010 |
Jan
(109) |
Feb
(83) |
Mar
(139) |
Apr
(91) |
May
(79) |
Jun
(164) |
Jul
(184) |
Aug
(146) |
Sep
(163) |
Oct
(128) |
Nov
(70) |
Dec
(73) |
| 2011 |
Jan
(235) |
Feb
(165) |
Mar
(147) |
Apr
(86) |
May
(74) |
Jun
(118) |
Jul
(65) |
Aug
(75) |
Sep
(162) |
Oct
(94) |
Nov
(48) |
Dec
(44) |
| 2012 |
Jan
(49) |
Feb
(40) |
Mar
(88) |
Apr
(35) |
May
(52) |
Jun
(69) |
Jul
(90) |
Aug
(123) |
Sep
(112) |
Oct
(120) |
Nov
(105) |
Dec
(116) |
| 2013 |
Jan
(76) |
Feb
(26) |
Mar
(78) |
Apr
(43) |
May
(61) |
Jun
(53) |
Jul
(147) |
Aug
(85) |
Sep
(83) |
Oct
(122) |
Nov
(18) |
Dec
(27) |
| 2014 |
Jan
(58) |
Feb
(25) |
Mar
(49) |
Apr
(17) |
May
(29) |
Jun
(39) |
Jul
(53) |
Aug
(52) |
Sep
(35) |
Oct
(47) |
Nov
(110) |
Dec
(27) |
| 2015 |
Jan
(50) |
Feb
(93) |
Mar
(96) |
Apr
(30) |
May
(55) |
Jun
(83) |
Jul
(44) |
Aug
(8) |
Sep
(5) |
Oct
|
Nov
(1) |
Dec
(1) |
| 2016 |
Jan
|
Feb
|
Mar
(1) |
Apr
|
May
|
Jun
(2) |
Jul
|
Aug
(3) |
Sep
(1) |
Oct
(3) |
Nov
|
Dec
|
| 2017 |
Jan
|
Feb
(5) |
Mar
|
Apr
|
May
|
Jun
|
Jul
(3) |
Aug
|
Sep
(7) |
Oct
|
Nov
|
Dec
|
| 2018 |
Jan
|
Feb
|
Mar
|
Apr
|
May
|
Jun
|
Jul
(2) |
Aug
|
Sep
|
Oct
|
Nov
|
Dec
|
| S | M | T | W | T | F | S |
|---|---|---|---|---|---|---|
|
|
|
|
1
(2) |
2
(5) |
3
(2) |
4
(3) |
|
5
|
6
(3) |
7
(1) |
8
|
9
|
10
|
11
|
|
12
(1) |
13
(2) |
14
(4) |
15
(1) |
16
|
17
|
18
|
|
19
|
20
|
21
(1) |
22
(4) |
23
(1) |
24
(5) |
25
(1) |
|
26
(1) |
27
|
28
|
29
(1) |
30
|
31
(6) |
|
Yes, that seems reasonable. @elmar you seem to have a pretty good grasp of the code and the use case, would you mind taking a crack at adding those special cases? Tom On Sat, Jul 4, 2015 at 8:58 AM elmar werling <el...@ne...> wrote: > having a look at seaborns ViolinPlotter class > (https://github.com/mwaskom/seaborn/blob/master/seaborn/categorical.py), > they explicit handle the special case of "no data" and "single unique > datapoint" at line 580 ff. > > Could something similar be added to matplotlibs violinplot? > > On 04.07.2015 12:28, elmar werling wrote: > > from an end user point of view, matplotlibs violinplot should just do > > the same as seaborns violinplot. > > > > > > ##################################################################### > > import numpy as np > > import matplotlib.pyplot as plt > > import seaborn as sns > > > > N = 100 > > y1 = np.random.randn(N) + 3.0 > > y2 = np.random.randn(N) * 5.0 + 50 > > y3 = np.ones(N) * 100 # causing plt.violinplot problem > > y4 = np.arange(0) # causing plt.violinplot problem > > > > #plt.violinplot([y1, y2, y3, y4]) > > > > sns.violinplot(data=[y1, y2, y3, y4]) > > > > > > On 03.07.2015 17:52, Thomas Caswell wrote: > >> The KDE computation code is a copy of the KDE code from scipy > >> (https://github.com/scipy/scipy/blob/master/scipy/stats/kde.py), I > >> suggest raising this issue on their mailing list/github. > >> > >> I strongly suspect that violin plot should be doing data sanitation on > >> the way in or catching exceptions like this, but I am not familiar > >> enough with the math to be sure what it should do instead. > >> > >> Tom > >> > >> On Fri, Jul 3, 2015 at 11:41 AM elmar werling > >> <el...@ne... > >> <mailto:el...@ne...>> wrote: > >> > >> > >> Hi all, > >> > >> violinplot is crashing with singular matrix data. See example. > >> > >> Is this behaviour for a singular matrix intended or just a bug? > >> > >> Cheers > >> Elmar > >> > >> > >> > >> ##################################################### > >> import numpy as np > >> import matplotlib.pyplot as plt > >> > >> # data mimicing the > >> # original cumsum data (may sum up to 100) > >> N = 100 > >> y1 = np.random.randn(N) + 3.0 > >> y2 = np.random.randn(N) * 5.0 + 50 > >> y3 = np.ones(N) * 100 # data set causing violinplot problem > >> > >> plt.violinplot([y1, y2, y3]) > >> > >> plt.boxplot([y1, y2, y3]) # ok > >> plt.ylim(0,110) > >> > >> ##################################################### > >> > >> OS: Debian > >> Anaconda 2.3.0 (64-bit) > >> Python 2.7.10 > >> numpy 2.3.0 > >> matplotlib 1.4.3 > >> > >> > >> > ------------------------------------------------------------------------------ > >> Don't Limit Your Business. Reach for the Cloud. > >> GigeNET's Cloud Solutions provide you with the tools and support > that > >> you need to offload your IT needs and focus on growing your > business. > >> Configured For All Businesses. Start Your Cloud Today. > >> https://www.gigenetcloud.com/ > >> _______________________________________________ > >> Matplotlib-devel mailing list > >> Mat...@li... > >> <mailto:Mat...@li...> > >> https://lists.sourceforge.net/lists/listinfo/matplotlib-devel > >> > >> > >> > >> > ------------------------------------------------------------------------------ > >> Don't Limit Your Business. Reach for the Cloud. > >> GigeNET's Cloud Solutions provide you with the tools and support that > >> you need to offload your IT needs and focus on growing your business. > >> Configured For All Businesses. Start Your Cloud Today. > >> https://www.gigenetcloud.com/ > >> > >> > >> > >> _______________________________________________ > >> Matplotlib-devel mailing list > >> Mat...@li... > >> https://lists.sourceforge.net/lists/listinfo/matplotlib-devel > >> > > > > > > > ------------------------------------------------------------------------------ > > Don't Limit Your Business. Reach for the Cloud. > > GigeNET's Cloud Solutions provide you with the tools and support that > > you need to offload your IT needs and focus on growing your business. > > Configured For All Businesses. Start Your Cloud Today. > > https://www.gigenetcloud.com/ > > > > > > ------------------------------------------------------------------------------ > Don't Limit Your Business. Reach for the Cloud. > GigeNET's Cloud Solutions provide you with the tools and support that > you need to offload your IT needs and focus on growing your business. > Configured For All Businesses. Start Your Cloud Today. > https://www.gigenetcloud.com/ > _______________________________________________ > Matplotlib-devel mailing list > Mat...@li... > https://lists.sourceforge.net/lists/listinfo/matplotlib-devel >
having a look at seaborns ViolinPlotter class (https://github.com/mwaskom/seaborn/blob/master/seaborn/categorical.py), they explicit handle the special case of "no data" and "single unique datapoint" at line 580 ff. Could something similar be added to matplotlibs violinplot? On 04.07.2015 12:28, elmar werling wrote: > from an end user point of view, matplotlibs violinplot should just do > the same as seaborns violinplot. > > > ##################################################################### > import numpy as np > import matplotlib.pyplot as plt > import seaborn as sns > > N = 100 > y1 = np.random.randn(N) + 3.0 > y2 = np.random.randn(N) * 5.0 + 50 > y3 = np.ones(N) * 100 # causing plt.violinplot problem > y4 = np.arange(0) # causing plt.violinplot problem > > #plt.violinplot([y1, y2, y3, y4]) > > sns.violinplot(data=[y1, y2, y3, y4]) > > > On 03.07.2015 17:52, Thomas Caswell wrote: >> The KDE computation code is a copy of the KDE code from scipy >> (https://github.com/scipy/scipy/blob/master/scipy/stats/kde.py), I >> suggest raising this issue on their mailing list/github. >> >> I strongly suspect that violin plot should be doing data sanitation on >> the way in or catching exceptions like this, but I am not familiar >> enough with the math to be sure what it should do instead. >> >> Tom >> >> On Fri, Jul 3, 2015 at 11:41 AM elmar werling >> <el...@ne... >> <mailto:el...@ne...>> wrote: >> >> >> Hi all, >> >> violinplot is crashing with singular matrix data. See example. >> >> Is this behaviour for a singular matrix intended or just a bug? >> >> Cheers >> Elmar >> >> >> >> ##################################################### >> import numpy as np >> import matplotlib.pyplot as plt >> >> # data mimicing the >> # original cumsum data (may sum up to 100) >> N = 100 >> y1 = np.random.randn(N) + 3.0 >> y2 = np.random.randn(N) * 5.0 + 50 >> y3 = np.ones(N) * 100 # data set causing violinplot problem >> >> plt.violinplot([y1, y2, y3]) >> >> plt.boxplot([y1, y2, y3]) # ok >> plt.ylim(0,110) >> >> ##################################################### >> >> OS: Debian >> Anaconda 2.3.0 (64-bit) >> Python 2.7.10 >> numpy 2.3.0 >> matplotlib 1.4.3 >> >> >> ------------------------------------------------------------------------------ >> Don't Limit Your Business. Reach for the Cloud. >> GigeNET's Cloud Solutions provide you with the tools and support that >> you need to offload your IT needs and focus on growing your business. >> Configured For All Businesses. Start Your Cloud Today. >> https://www.gigenetcloud.com/ >> _______________________________________________ >> Matplotlib-devel mailing list >> Mat...@li... >> <mailto:Mat...@li...> >> https://lists.sourceforge.net/lists/listinfo/matplotlib-devel >> >> >> >> ------------------------------------------------------------------------------ >> Don't Limit Your Business. Reach for the Cloud. >> GigeNET's Cloud Solutions provide you with the tools and support that >> you need to offload your IT needs and focus on growing your business. >> Configured For All Businesses. Start Your Cloud Today. >> https://www.gigenetcloud.com/ >> >> >> >> _______________________________________________ >> Matplotlib-devel mailing list >> Mat...@li... >> https://lists.sourceforge.net/lists/listinfo/matplotlib-devel >> > > > ------------------------------------------------------------------------------ > Don't Limit Your Business. Reach for the Cloud. > GigeNET's Cloud Solutions provide you with the tools and support that > you need to offload your IT needs and focus on growing your business. > Configured For All Businesses. Start Your Cloud Today. > https://www.gigenetcloud.com/ >
from an end user point of view, matplotlibs violinplot should just do the same as seaborns violinplot. ##################################################################### import numpy as np import matplotlib.pyplot as plt import seaborn as sns N = 100 y1 = np.random.randn(N) + 3.0 y2 = np.random.randn(N) * 5.0 + 50 y3 = np.ones(N) * 100 # causing plt.violinplot problem y4 = np.arange(0) # causing plt.violinplot problem #plt.violinplot([y1, y2, y3, y4]) sns.violinplot(data=[y1, y2, y3, y4]) On 03.07.2015 17:52, Thomas Caswell wrote: > The KDE computation code is a copy of the KDE code from scipy > (https://github.com/scipy/scipy/blob/master/scipy/stats/kde.py), I > suggest raising this issue on their mailing list/github. > > I strongly suspect that violin plot should be doing data sanitation on > the way in or catching exceptions like this, but I am not familiar > enough with the math to be sure what it should do instead. > > Tom > > On Fri, Jul 3, 2015 at 11:41 AM elmar werling > <el...@ne... > <mailto:el...@ne...>> wrote: > > > Hi all, > > violinplot is crashing with singular matrix data. See example. > > Is this behaviour for a singular matrix intended or just a bug? > > Cheers > Elmar > > > > ##################################################### > import numpy as np > import matplotlib.pyplot as plt > > # data mimicing the > # original cumsum data (may sum up to 100) > N = 100 > y1 = np.random.randn(N) + 3.0 > y2 = np.random.randn(N) * 5.0 + 50 > y3 = np.ones(N) * 100 # data set causing violinplot problem > > plt.violinplot([y1, y2, y3]) > > plt.boxplot([y1, y2, y3]) # ok > plt.ylim(0,110) > > ##################################################### > > OS: Debian > Anaconda 2.3.0 (64-bit) > Python 2.7.10 > numpy 2.3.0 > matplotlib 1.4.3 > > > ------------------------------------------------------------------------------ > Don't Limit Your Business. Reach for the Cloud. > GigeNET's Cloud Solutions provide you with the tools and support that > you need to offload your IT needs and focus on growing your business. > Configured For All Businesses. Start Your Cloud Today. > https://www.gigenetcloud.com/ > _______________________________________________ > Matplotlib-devel mailing list > Mat...@li... > <mailto:Mat...@li...> > https://lists.sourceforge.net/lists/listinfo/matplotlib-devel > > > > ------------------------------------------------------------------------------ > Don't Limit Your Business. Reach for the Cloud. > GigeNET's Cloud Solutions provide you with the tools and support that > you need to offload your IT needs and focus on growing your business. > Configured For All Businesses. Start Your Cloud Today. > https://www.gigenetcloud.com/ > > > > _______________________________________________ > Matplotlib-devel mailing list > Mat...@li... > https://lists.sourceforge.net/lists/listinfo/matplotlib-devel >