Hi, While reading the code and the examples of scipy.stats I came across the attribute rv.dist. Specifically, line 227 of the scipy.stats source on the gibhub server mentions:
x = np.linspace(0, np.minimum(rv.dist.b, 3))
The problem is that the meaning of this attribute is nowhere explained. Is this a bug? Nicky
On Sat, Apr 21, 2012 at 3:56 PM, nicky van foreest <vanforeest@gmail.com> wrote:
Hi,
While reading the code and the examples of scipy.stats I came across the attribute rv.dist. Specifically, line 227 of the scipy.stats source on the gibhub server mentions:
x = np.linspace(0, np.minimum(rv.dist.b, 3))
The problem is that the meaning of this attribute is nowhere explained. Is this a bug?
Do you have the github link to the source? It's not clear which module you are talking about. (klick on line number and you get the link to that specific line) It would safe me some time searching for this. Josef
Nicky _______________________________________________ SciPy-Dev mailing list SciPy-Dev@scipy.org http://mail.scipy.org/mailman/listinfo/scipy-dev
Hopefully this is the correct link: https://github.com/scipy/scipy/blob/master/scipy/stats/distributions.py#L227 btw, I am compiling a list of points about the scipy.stats code. Once finished what should I do with it? Would it be best to send it to this list? Should I send the points one by one, or better as one file? I am very enthousiastic about the fact that the code is now easily accessible via the web. On 21 April 2012 22:17, <josef.pktd@gmail.com> wrote:
On Sat, Apr 21, 2012 at 3:56 PM, nicky van foreest <vanforeest@gmail.com> wrote:
Hi,
While reading the code and the examples of scipy.stats I came across the attribute rv.dist. Specifically, line 227 of the scipy.stats source on the gibhub server mentions:
x = np.linspace(0, np.minimum(rv.dist.b, 3))
The problem is that the meaning of this attribute is nowhere explained. Is this a bug?
Do you have the github link to the source? It's not clear which module you are talking about. (klick on line number and you get the link to that specific line) It would safe me some time searching for this.
Josef
Nicky _______________________________________________ SciPy-Dev mailing list SciPy-Dev@scipy.org http://mail.scipy.org/mailman/listinfo/scipy-dev
_______________________________________________ SciPy-Dev mailing list SciPy-Dev@scipy.org http://mail.scipy.org/mailman/listinfo/scipy-dev
On Sat, Apr 21, 2012 at 4:22 PM, nicky van foreest <vanforeest@gmail.com> wrote:
Hopefully this is the correct link:
https://github.com/scipy/scipy/blob/master/scipy/stats/distributions.py#L227
much easier answer a link https://github.com/scipy/scipy/blob/master/scipy/stats/distributions.py#L453 dist is an attribute of the frozen class. the frozen class delegates to the real class and has that attached as `dist` so this is the same as the upper bound .b attribute of the class.
btw, I am compiling a list of points about the scipy.stats code. Once finished what should I do with it? Would it be best to send it to this list? Should I send the points one by one, or better as one file?
I am very enthousiastic about the fact that the code is now easily accessible via the web.
pull request on github? depends on what the "points" are. If you find bugs, individual tickets would be useful. If you find several/many smaller things, then one would make it easier to go over all of them. Josef
On 21 April 2012 22:17, <josef.pktd@gmail.com> wrote:
On Sat, Apr 21, 2012 at 3:56 PM, nicky van foreest <vanforeest@gmail.com> wrote:
Hi,
While reading the code and the examples of scipy.stats I came across the attribute rv.dist. Specifically, line 227 of the scipy.stats source on the gibhub server mentions:
x = np.linspace(0, np.minimum(rv.dist.b, 3))
The problem is that the meaning of this attribute is nowhere explained. Is this a bug?
Do you have the github link to the source? It's not clear which module you are talking about. (klick on line number and you get the link to that specific line) It would safe me some time searching for this.
Josef
Nicky _______________________________________________ SciPy-Dev mailing list SciPy-Dev@scipy.org http://mail.scipy.org/mailman/listinfo/scipy-dev
_______________________________________________ SciPy-Dev mailing list SciPy-Dev@scipy.org http://mail.scipy.org/mailman/listinfo/scipy-dev
SciPy-Dev mailing list SciPy-Dev@scipy.org http://mail.scipy.org/mailman/listinfo/scipy-dev
On 21 April 2012 22:39, <josef.pktd@gmail.com> wrote:
On Sat, Apr 21, 2012 at 4:22 PM, nicky van foreest <vanforeest@gmail.com> wrote:
Hopefully this is the correct link:
https://github.com/scipy/scipy/blob/master/scipy/stats/distributions.py#L227
much easier
answer a link https://github.com/scipy/scipy/blob/master/scipy/stats/distributions.py#L453
dist is an attribute of the frozen class. the frozen class delegates to the real class and has that attached as `dist`
so this is the same as the upper bound .b attribute of the class.
Sure. I have seen this in the code. The point I wanted to make is that for a user who doesn't (want to) read the source the text in the example is somewhat confusing. Shouldn't these doc strings be targeted at plain users (with `plain' I have no derogatory intentions)?
btw, I am compiling a list of points about the scipy.stats code. Once finished what should I do with it? Would it be best to send it to this list? Should I send the points one by one, or better as one file?
I am very enthousiastic about the fact that the code is now easily accessible via the web.
pull request on github?
depends on what the "points" are. If you find bugs, individual tickets would be useful. If you find several/many smaller things, then one would make it easier to go over all of them.
Josef
On 21 April 2012 22:17, <josef.pktd@gmail.com> wrote:
On Sat, Apr 21, 2012 at 3:56 PM, nicky van foreest <vanforeest@gmail.com> wrote:
Hi,
While reading the code and the examples of scipy.stats I came across the attribute rv.dist. Specifically, line 227 of the scipy.stats source on the gibhub server mentions:
> x = np.linspace(0, np.minimum(rv.dist.b, 3))
The problem is that the meaning of this attribute is nowhere explained. Is this a bug?
Do you have the github link to the source? It's not clear which module you are talking about. (klick on line number and you get the link to that specific line) It would safe me some time searching for this.
Josef
Nicky _______________________________________________ SciPy-Dev mailing list SciPy-Dev@scipy.org http://mail.scipy.org/mailman/listinfo/scipy-dev
_______________________________________________ SciPy-Dev mailing list SciPy-Dev@scipy.org http://mail.scipy.org/mailman/listinfo/scipy-dev
SciPy-Dev mailing list SciPy-Dev@scipy.org http://mail.scipy.org/mailman/listinfo/scipy-dev
_______________________________________________ SciPy-Dev mailing list SciPy-Dev@scipy.org http://mail.scipy.org/mailman/listinfo/scipy-dev
On Sat, Apr 21, 2012 at 4:56 PM, nicky van foreest <vanforeest@gmail.com> wrote:
On 21 April 2012 22:39, <josef.pktd@gmail.com> wrote:
On Sat, Apr 21, 2012 at 4:22 PM, nicky van foreest <vanforeest@gmail.com> wrote:
Hopefully this is the correct link:
https://github.com/scipy/scipy/blob/master/scipy/stats/distributions.py#L227
much easier
answer a link https://github.com/scipy/scipy/blob/master/scipy/stats/distributions.py#L453
dist is an attribute of the frozen class. the frozen class delegates to the real class and has that attached as `dist`
so this is the same as the upper bound .b attribute of the class.
Sure. I have seen this in the code. The point I wanted to make is that for a user who doesn't (want to) read the source the text in the example is somewhat confusing. Shouldn't these doc strings be targeted at plain users (with `plain' I have no derogatory intentions)?
As a user I would think it's just an upper bound for the plot. But I'm not a good measure for users new to the distributions. It would be possible to inject a number into the docstring, by changing the template https://github.com/scipy/scipy/blob/master/scipy/stats/distributions.py#L115... Josef
btw, I am compiling a list of points about the scipy.stats code. Once finished what should I do with it? Would it be best to send it to this list? Should I send the points one by one, or better as one file?
I am very enthousiastic about the fact that the code is now easily accessible via the web.
pull request on github?
depends on what the "points" are. If you find bugs, individual tickets would be useful. If you find several/many smaller things, then one would make it easier to go over all of them.
Josef
On 21 April 2012 22:17, <josef.pktd@gmail.com> wrote:
On Sat, Apr 21, 2012 at 3:56 PM, nicky van foreest <vanforeest@gmail.com> wrote:
Hi,
While reading the code and the examples of scipy.stats I came across the attribute rv.dist. Specifically, line 227 of the scipy.stats source on the gibhub server mentions:
>> x = np.linspace(0, np.minimum(rv.dist.b, 3))
The problem is that the meaning of this attribute is nowhere explained. Is this a bug?
Do you have the github link to the source? It's not clear which module you are talking about. (klick on line number and you get the link to that specific line) It would safe me some time searching for this.
Josef
Nicky _______________________________________________ SciPy-Dev mailing list SciPy-Dev@scipy.org http://mail.scipy.org/mailman/listinfo/scipy-dev
_______________________________________________ SciPy-Dev mailing list SciPy-Dev@scipy.org http://mail.scipy.org/mailman/listinfo/scipy-dev
SciPy-Dev mailing list SciPy-Dev@scipy.org http://mail.scipy.org/mailman/listinfo/scipy-dev
_______________________________________________ SciPy-Dev mailing list SciPy-Dev@scipy.org http://mail.scipy.org/mailman/listinfo/scipy-dev
_______________________________________________ SciPy-Dev mailing list SciPy-Dev@scipy.org http://mail.scipy.org/mailman/listinfo/scipy-dev
btw, I am compiling a list of points about the scipy.stats code. Once finished what should I do with it? Would it be best to send it to this list? Should I send the points one by one, or better as one file?
I am very enthousiastic about the fact that the code is now easily accessible via the web.
pull request on github?
I have seen this request coming by some time ago. I am happy to see that it has been implemented.
depends on what the "points" are. If you find bugs, individual tickets would be useful. If you find several/many smaller things, then one would make it easier to go over all of them.
I don't always know whether these points are bugs, or due to my misunderstanding of the code or the example text. Hence, it is not always clear to me whether these points are bugs. Here are two examples that confuse me: In [11]: from scipy.stats import uniform In [12]: U = uniform(loc = 3, scale = 5) In [13]: U.mean() Out[13]: 5.5 In [14]: U.moment(1) Out[14]: 0.5 In [15]: U.moment(8) Out[15]: array(0.11111111111111112) First point: why in line 14 is U.moment(1) not equal to U.mean()? I checked the code on line https://github.com/scipy/scipy/blob/master/scipy/stats/distributions.py#L358 to see why, and this explains the result. However, from the doc-string on line https://github.com/scipy/scipy/blob/master/scipy/stats/distributions.py#L129 I would expect to see that U.moment(1) = U.mean(). Second point: From the code I understand that U.moment(1) returns a float, and that the U.moment(8) returns an array. From a user's perspective I find this inconsistent, however. So, are these points real bugs?
In [11]: from scipy.stats import uniform
In [12]: U = uniform(loc = 3, scale = 5)
In [13]: U.mean() Out[13]: 5.5
In [14]: U.moment(1) Out[14]: 0.5
In [15]: U.moment(8) Out[15]: array(0.11111111111111112)
First point: why in line 14 is U.moment(1) not equal to U.mean()? I checked the code on line https://github.com/scipy/scipy/blob/master/scipy/stats/distributions.py#L358 to see why, and this explains the result. However, from the doc-string on line https://github.com/scipy/scipy/blob/master/scipy/stats/distributions.py#L129 I would expect to see that U.moment(1) = U.mean().
Interestingly, http://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.moment.html says that moment() does compute the central moment. However, I need the real moments, i.e., E (X^n) = \int x^n dF(x) where F is the distribution function of the R.V. X.
On Sat, Apr 21, 2012 at 5:12 PM, nicky van foreest <vanforeest@gmail.com> wrote:
In [11]: from scipy.stats import uniform
In [12]: U = uniform(loc = 3, scale = 5)
In [13]: U.mean() Out[13]: 5.5
In [14]: U.moment(1) Out[14]: 0.5
In [15]: U.moment(8) Out[15]: array(0.11111111111111112)
First point: why in line 14 is U.moment(1) not equal to U.mean()? I checked the code on line https://github.com/scipy/scipy/blob/master/scipy/stats/distributions.py#L358 to see why, and this explains the result. However, from the doc-string on line https://github.com/scipy/scipy/blob/master/scipy/stats/distributions.py#L129 I would expect to see that U.moment(1) = U.mean().
Looks like a bug. And I don't think the test suite checks whether loc and scale is handled correctly in all code paths.
Interestingly, http://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.moment.html
this is empirical moment, a stats function, not for the distribution non-central for data is just (data**k).mean() if we don't care about ddof. Do we need a function?
says that moment() does compute the central moment. However, I need the real moments, i.e., E (X^n) = \int x^n dF(x) where F is the distribution function of the R.V. X.
the distribution method moment is non-centered, raw moment. (It was a bit inconsistent when I went through this, and I think I decided everywhere on raw moments,) Josef
_______________________________________________ SciPy-Dev mailing list SciPy-Dev@scipy.org http://mail.scipy.org/mailman/listinfo/scipy-dev
On Sat, Apr 21, 2012 at 5:31 PM, nicky van foreest <vanforeest@gmail.com> wrote:
In [11]: from scipy.stats import uniform
In [12]: U = uniform(loc = 3, scale = 5)
In [13]: U.mean() Out[13]: 5.5
In [14]: U.moment(1) Out[14]: 0.5
Might this problem be due to the fact that my ubuntu machine does not support the latest version of scipy.stats?
I'm stil on 0.9 and there is no loc, scale option
import scipy scipy.__version__ '0.9.0' stats.uniform.moment(loc = 3, scale = 5) Traceback (most recent call last): File "<stdin>", line 1, in <module> TypeError: moment() got an unexpected keyword argument 'loc' U.moment(1) 0.5 stats.uniform.moment(1) 0.5
Obviously I'm not up to date in this. can you try the distribution directly instead of the frozen distribution? Josef
_______________________________________________ SciPy-Dev mailing list SciPy-Dev@scipy.org http://mail.scipy.org/mailman/listinfo/scipy-dev
On 21 April 2012 23:45, <josef.pktd@gmail.com> wrote:
On Sat, Apr 21, 2012 at 5:31 PM, nicky van foreest <vanforeest@gmail.com> wrote:
In [11]: from scipy.stats import uniform
In [12]: U = uniform(loc = 3, scale = 5)
In [13]: U.mean() Out[13]: 5.5
In [14]: U.moment(1) Out[14]: 0.5
Might this problem be due to the fact that my ubuntu machine does not support the latest version of scipy.stats?
I'm stil on 0.9 and there is no loc, scale option
import scipy scipy.__version__ '0.9.0' stats.uniform.moment(loc = 3, scale = 5) Traceback (most recent call last): File "<stdin>", line 1, in <module> TypeError: moment() got an unexpected keyword argument 'loc' U.moment(1) 0.5 stats.uniform.moment(1) 0.5
Obviously I'm not up to date in this.
can you try the distribution directly instead of the frozen distribution?
I am having the same problems as you, although: In [9]: ? uniform.moment Type: instancemethod Base Class: <type 'instancemethod'> String Form: <bound method uniform_gen.moment of <scipy.stats.distributions.uniform_gen object at 0x2e901d0>> Namespace: Interactive File: /usr/lib/python2.7/dist-packages/scipy/stats/distributions.py Definition: uniform.moment(self, n, *args) Docstring: n'th order non-central moment of distribution Parameters ---------- n: int, n>=1 order of moment arg1, arg2, arg3,... : array-like The shape parameter(s) for the distribution (see docstring of the instance object for more information) BTW: all of these points stem from my intention to add some function to scipy stats to compute/approximate the convolution of two r.v.s. One such method proposes to use moment matching...
On Sat, Apr 21, 2012 at 5:58 PM, nicky van foreest <vanforeest@gmail.com> wrote:
On 21 April 2012 23:45, <josef.pktd@gmail.com> wrote:
On Sat, Apr 21, 2012 at 5:31 PM, nicky van foreest <vanforeest@gmail.com> wrote:
In [11]: from scipy.stats import uniform
In [12]: U = uniform(loc = 3, scale = 5)
In [13]: U.mean() Out[13]: 5.5
In [14]: U.moment(1) Out[14]: 0.5
Might this problem be due to the fact that my ubuntu machine does not support the latest version of scipy.stats?
I'm stil on 0.9 and there is no loc, scale option
import scipy scipy.__version__ '0.9.0' stats.uniform.moment(loc = 3, scale = 5) Traceback (most recent call last): File "<stdin>", line 1, in <module> TypeError: moment() got an unexpected keyword argument 'loc' U.moment(1) 0.5 stats.uniform.moment(1) 0.5
Obviously I'm not up to date in this.
can you try the distribution directly instead of the frozen distribution?
I am having the same problems as you, although:
In [9]: ? uniform.moment Type: instancemethod Base Class: <type 'instancemethod'> String Form: <bound method uniform_gen.moment of <scipy.stats.distributions.uniform_gen object at 0x2e901d0>> Namespace: Interactive File: /usr/lib/python2.7/dist-packages/scipy/stats/distributions.py Definition: uniform.moment(self, n, *args) Docstring: n'th order non-central moment of distribution
Parameters ---------- n: int, n>=1 order of moment
arg1, arg2, arg3,... : array-like The shape parameter(s) for the distribution (see docstring of the instance object for more information)
stats.uniform.moment(1, loc=3, scale=1) 3.5 stats.uniform(loc=3, scale=1).moment(1) 3.5
import scipy scipy.__version__ '0.10.0b2'
version mismatch with new documentation In the older versions of scipy, the frozen distributions didn't always pass on the keywords, loc and scale, so they were just quietly ignored. It looks like now moment handles loc and scale
stats.uniform.mean(1, loc=3, scale=5) 5.5 stats.uniform.moment(1, loc=3, scale=5) 5.5
stats.uniform.ppf([0, 1], loc=3, scale=5) array([ 3., 8.]) stats.uniform.ppf([0, 1], loc=3, scale=5).mean() 5.5
Josef
BTW: all of these points stem from my intention to add some function to scipy stats to compute/approximate the convolution of two r.v.s. One such method proposes to use moment matching... _______________________________________________ SciPy-Dev mailing list SciPy-Dev@scipy.org http://mail.scipy.org/mailman/listinfo/scipy-dev
On 22 April 2012 02:41, <josef.pktd@gmail.com> wrote:
On Sat, Apr 21, 2012 at 5:58 PM, nicky van foreest <vanforeest@gmail.com> wrote:
On 21 April 2012 23:45, <josef.pktd@gmail.com> wrote:
On Sat, Apr 21, 2012 at 5:31 PM, nicky van foreest <vanforeest@gmail.com> wrote:
In [11]: from scipy.stats import uniform
In [12]: U = uniform(loc = 3, scale = 5)
In [13]: U.mean() Out[13]: 5.5
In [14]: U.moment(1) Out[14]: 0.5
Might this problem be due to the fact that my ubuntu machine does not support the latest version of scipy.stats?
I'm stil on 0.9 and there is no loc, scale option
import scipy scipy.__version__ '0.9.0' stats.uniform.moment(loc = 3, scale = 5) Traceback (most recent call last): File "<stdin>", line 1, in <module> TypeError: moment() got an unexpected keyword argument 'loc' U.moment(1) 0.5 stats.uniform.moment(1) 0.5
Obviously I'm not up to date in this.
can you try the distribution directly instead of the frozen distribution?
I am having the same problems as you, although:
In [9]: ? uniform.moment Type: instancemethod Base Class: <type 'instancemethod'> String Form: <bound method uniform_gen.moment of <scipy.stats.distributions.uniform_gen object at 0x2e901d0>> Namespace: Interactive File: /usr/lib/python2.7/dist-packages/scipy/stats/distributions.py Definition: uniform.moment(self, n, *args) Docstring: n'th order non-central moment of distribution
Parameters ---------- n: int, n>=1 order of moment
arg1, arg2, arg3,... : array-like The shape parameter(s) for the distribution (see docstring of the instance object for more information)
stats.uniform.moment(1, loc=3, scale=1) 3.5 stats.uniform(loc=3, scale=1).moment(1) 3.5
import scipy scipy.__version__ '0.10.0b2'
version mismatch with new documentation
In the older versions of scipy, the frozen distributions didn't always pass on the keywords, loc and scale, so they were just quietly ignored.
It looks like now moment handles loc and scale
stats.uniform.mean(1, loc=3, scale=5) 5.5 stats.uniform.moment(1, loc=3, scale=5) 5.5
stats.uniform.ppf([0, 1], loc=3, scale=5) array([ 3., 8.]) stats.uniform.ppf([0, 1], loc=3, scale=5).mean() 5.5
Josef
Ok. So this is clear now. . Let's try to wrap up the above couple of mails. The problem with the moments is solved. The point about rv.dist.b in the examples text is not in my opinion. Is it ok to make a ticket for this? I'll try to figure out how to do this. Hopefully this is covered in the doc of Ralf. BTW. I can also try to repair a few of the tickets. For instance, I came across a similar problem like the one in http://projects.scipy.org/scipy/ticket/1493. I think I have a nice solution for this.
On Sun, Apr 22, 2012 at 1:28 PM, nicky van foreest <vanforeest@gmail.com> wrote:
On 22 April 2012 02:41, <josef.pktd@gmail.com> wrote:
On Sat, Apr 21, 2012 at 5:58 PM, nicky van foreest <vanforeest@gmail.com> wrote:
On 21 April 2012 23:45, <josef.pktd@gmail.com> wrote:
On Sat, Apr 21, 2012 at 5:31 PM, nicky van foreest <vanforeest@gmail.com> wrote:
In [11]: from scipy.stats import uniform
In [12]: U = uniform(loc = 3, scale = 5)
In [13]: U.mean() Out[13]: 5.5
In [14]: U.moment(1) Out[14]: 0.5
Might this problem be due to the fact that my ubuntu machine does not support the latest version of scipy.stats?
I'm stil on 0.9 and there is no loc, scale option
> import scipy > scipy.__version__ '0.9.0' > stats.uniform.moment(loc = 3, scale = 5) Traceback (most recent call last): File "<stdin>", line 1, in <module> TypeError: moment() got an unexpected keyword argument 'loc' > U.moment(1) 0.5 > stats.uniform.moment(1) 0.5
Obviously I'm not up to date in this.
can you try the distribution directly instead of the frozen distribution?
I am having the same problems as you, although:
In [9]: ? uniform.moment Type: instancemethod Base Class: <type 'instancemethod'> String Form: <bound method uniform_gen.moment of <scipy.stats.distributions.uniform_gen object at 0x2e901d0>> Namespace: Interactive File: /usr/lib/python2.7/dist-packages/scipy/stats/distributions.py Definition: uniform.moment(self, n, *args) Docstring: n'th order non-central moment of distribution
Parameters ---------- n: int, n>=1 order of moment
arg1, arg2, arg3,... : array-like The shape parameter(s) for the distribution (see docstring of the instance object for more information)
stats.uniform.moment(1, loc=3, scale=1) 3.5 stats.uniform(loc=3, scale=1).moment(1) 3.5
import scipy scipy.__version__ '0.10.0b2'
version mismatch with new documentation
In the older versions of scipy, the frozen distributions didn't always pass on the keywords, loc and scale, so they were just quietly ignored.
It looks like now moment handles loc and scale
stats.uniform.mean(1, loc=3, scale=5) 5.5 stats.uniform.moment(1, loc=3, scale=5) 5.5
stats.uniform.ppf([0, 1], loc=3, scale=5) array([ 3., 8.]) stats.uniform.ppf([0, 1], loc=3, scale=5).mean() 5.5
Josef
Ok. So this is clear now. . Let's try to wrap up the above couple of mails. The problem with the moments is solved. The point about rv.dist.b in the examples text is not in my opinion. Is it ok to make a ticket for this? I'll try to figure out how to do this. Hopefully this is covered in the doc of Ralf.
Fine, the template would need a new place holder, the value can then be inserted when the doc string is created in the line that I linked to, I think.
BTW. I can also try to repair a few of the tickets. For instance, I came across a similar problem like the one in http://projects.scipy.org/scipy/ticket/1493. I think I have a nice solution for this.
That would be a good ticket to have a solution for. Thanks, Josef
_______________________________________________ SciPy-Dev mailing list SciPy-Dev@scipy.org http://mail.scipy.org/mailman/listinfo/scipy-dev
Ok. So this is clear now. . Let's try to wrap up the above couple of mails. The problem with the moments is solved. The point about rv.dist.b in the examples text is not in my opinion. Is it ok to make a ticket for this? I'll try to figure out how to do this. Hopefully this is covered in the doc of Ralf.
I tried to submit a ticket at http://projects.scipy.org/scipy but I get an error that the database is locked. Should I just wait and see?
BTW. I can also try to repair a few of the tickets. For instance, I came across a similar problem like the one in http://projects.scipy.org/scipy/ticket/1493. I think I have a nice solution for this.
That would be a good ticket to have a solution for.
I give it a try right now.
On Sun, Apr 22, 2012 at 1:41 PM, nicky van foreest <vanforeest@gmail.com> wrote:
Ok. So this is clear now. . Let's try to wrap up the above couple of mails. The problem with the moments is solved. The point about rv.dist.b in the examples text is not in my opinion. Is it ok to make a ticket for this? I'll try to figure out how to do this. Hopefully this is covered in the doc of Ralf.
I tried to submit a ticket at http://projects.scipy.org/scipy but I get an error that the database is locked. Should I just wait and see?
Try again, and again, ... and hope it doesn't take more than a few minutes. Josef
BTW. I can also try to repair a few of the tickets. For instance, I came across a similar problem like the one in http://projects.scipy.org/scipy/ticket/1493. I think I have a nice solution for this.
That would be a good ticket to have a solution for.
I give it a try right now. _______________________________________________ SciPy-Dev mailing list SciPy-Dev@scipy.org http://mail.scipy.org/mailman/listinfo/scipy-dev
participants (2)
-
josef.pktd＠gmail.com -
nicky van foreest