Inversion and fraction fields for power series rings

[Simon King]

This ticket is about at least three bugs related with inversion of elements of power series rings.

Here is the first:

sage: R.<x> = ZZ[[]]
sage: (1/x).parent()
Laurent Series Ring in x over Integer Ring
sage: (x/x).parent()
Power Series Ring in x over Integer Ring

Both parents are wrong. Usually, the parent of a/b is the fraction field of the parent of a,b, even if a==b. And neither above parent is a field.

Next bug:

sage: (1/(2*x)).parent()
ERROR: An unexpected error occurred while tokenizing input
The following traceback may be corrupted or invalid
The error message is: ('EOF in multi-line statement', (919, 0))

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
... very long traceback
TypeError: no conversion of this rational to integer

And the third:

sage: F = FractionField(R)
sage: 1/x in F
False

With the proposed patch, we solve all bugs except

sage: (x/x).parent()
Power Series Ring in x over Integer Ring

---

Apply (old):

• trac-8972_fraction_of_power_series_combined.patch​

[Simon King]

OK, here is a patch.

Idea:

• Introduce a fraction_field method to power series rings that returns the Laurent series ring over the fraction field of the base ring. I hope that the base_extend method for Laurent polynomials works stably enough, otherwise it should be rewritten.
• In the division method of power serise, construct the fraction field of the parent, move numerator and denominator into the fraction field, and divide there. The original form of the method is preserved as a fail safe.

With the patch, I get:

sage: P.<t> = ZZ[]
sage: R.<x> = P[[]]
sage: FractionField(R)
Laurent Series Ring in x over Fraction Field of Univariate Polynomial Ring in t over Integer Ring

O dear. I just realise that there will be more work. There is a segmentation fault, as follows:

sage: R1.<x> = ZZ[[]]
sage: F = FractionField(R1)
sage: F
Laurent Series Ring in x over Rational Field
sage: F(x)
x
sage: ~F(x)
/home/king/SAGE/sage-4.3.1/local/bin/sage-sage: line 206:  4437 Segmentation fault      sage-ipython "$@" -i

So, the division of elements of a Laurent series ring fails with a segmentation fault. By consequence, division of power series segfaults as well, with the patch. "Needs work", I presume.

[Simon King]

Strangely, without the patch, the construction works:

sage: R.<x> = ZZ[[]]
sage: F = LaurentSeriesRing(FractionField(R.base()),R.variable_names())
sage: 1/F(x)
x^-1

The patch does this construction as well -- but segfaults. There seems to be a nasty side effect.

[Simon King]

The segfault problem seems to come from the fact that the div method for Laurent series relies on the div method for power series -- and with my patch, the div method for power series uses the div method for Laurent series. Not good. But that seems solvable.

[Simon King]

Bugfixes for fraction field and inverses of power series over non-fields

[Simon King]

OK, I replaced the old patch, and now it seems to work!

For example:

sage: P.<t> = ZZ[]
sage: R.<x> = P[[]]
sage: 1/(t*x)
1/t*x^-1
sage: (1/x).parent() is FractionField(R)
True
sage: Frac(R)
Laurent Series Ring in x over Fraction Field of Univariate Polynomial Ring in t over Integer Ring

The doc tests for the two modified files pass. So, ready for review!

[Simon King]

PS: Even the following works:

sage: 1/(t+x)
1/t - 1/t^2*x + (-1/-t^3)*x^2 + (1/-t^4)*x^3 + 1/t^5*x^4 - 1/t^6*x^5 + 1/t^7*x^6 - 1/t^8*x^7 + 1/t^9*x^8 + (1/-t^10)*x^9 + 1/t^11*x^10 + (1/-t^12)*x^11 + 1/t^13*x^12 + (1/-t^14)*x^13 + (-1/-t^15)*x^14 + (1/-t^16)*x^15 + (-1/-t^17)*x^16 + (1/-t^18)*x^17 + 1/t^19*x^18 - 1/t^20*x^19 + O(x^20)

[Robert Bradshaw]

I'm wary of such a big change until we have some timing tests in place. In particular, I'm worried about potential slowdowns in the Monsky-Washnitzer code.

[Simon King]

Replying to robertwb:

I'm wary of such a big change until we have some timing tests in place. In particular, I'm worried about potential slowdowns in the Monsky-Washnitzer code.

You are right, timing should be taken into account, and this is something my patch doesn't provide. Without the patch:

sage: R.<x> = ZZ[[]]
sage: timeit('a=1/(1+x)')
625 loops, best of 3: 1.08 ms per loop

With the patch

sage: R.<x> = ZZ[[]]
sage: timeit('a=1/(1+x)')
125 loops, best of 3: 6 ms per loop

So, it is slower by more than a factor five.

[Simon King]

Concerning timings, I see a couple of things that might help improve the div method:

1. My patch calls the fraction_field method; in addition the original code calls the laurent_series_ring method. But the purpose of both is the same. So, only one should be done.
2. The fraction_field method should better be cached; this would save a lot of time, since the fradtion field construction involves the construction of a Laurent series ring and the construction of the fraction field of the base ring.
3. Currently the div methods of power series and of Laurent series call each other; I don't know if this is done efficiently (e.g., avoiding Python calls). I could imagine that this can be stratified.

So, something to do for tomorrow. And I guess the ticket is again "needs work".

[Simon King]

Replying to SimonKing:

Concerning timings, I see a couple of things that might help improve the div method:

One more thing: The old code is quick if the result actually belongs to the power series ring, which is quite often the case; if this is not the case then often an error results. And I guess the parent should always be the fraction field, eventually.

What I just tested (but I really should get some sleep now...) is to cache the fraction_field method, and to try to use the old code if the valuation of the denominator is not bigger than the valuation of the numerator; if this fails, then put numerator and denominator into the fraction field, and try again.

Doing so brings the above timing to about 2ms, which is still a loss of factor two, but two is less than 5 or 6. I'll submit another patch after trying to lift the dependency of the two div methods on each other.

[Simon King]

Improving the timings, to be applied after the bug fix patch

[Simon King]

The second patch does several things:

1. It turned out that in several places it is assumed that the quotient of two power series is a power series, not a Laurent series. I tried to take care of this.

2. I improved the timings, so that (according to the timings below) the performance is competitive (sometimes clearly better, sometimes very little worse) then the original performance.

The reason why the old timings were good was some kind of lazyness: The result of a division was not in the fraction field (as it should be!), but in a simpler ring, so that subsequent computations became easier. On the other hand, transformation into a Laurent polynomial was quite expensive, since there always was a transformation into the Laurent Series Ring's underlying Power Series Ring -- even if the given data already belong to it.

Solution (as usual): Add an optional argument "check" to the init method of Laurent Series.

And then I tried to benefit from keeping the results as simple as possible (like the old code did), but in a more proper way. Let f be a Laurent series in a Laurent series ring L. In the old code, one always had L.power_series_ring() is f.valuation_zero_part().parent(). I suggest to relax this condition: It is sufficient to have a coercion:

sage: R.<x> = ZZ[[]]
sage: f = 1/(1+2*x)
sage: f.parent()
Laurent Series Ring in x over Rational Field
sage: f.parent().power_series_ring()
Power Series Ring in x over Rational Field
sage: f.power_series().parent()
Power Series Ring in x over Integer Ring

Timings

Without the two patches:

sage: R.<x> = ZZ[[]]
sage: timeit('a=1/x')
625 loops, best of 3: 291 µs per loop
sage: timeit('a=(1+x)/x')
625 loops, best of 3: 295 µs per loop
sage: timeit('a=1/(1+x)')
625 loops, best of 3: 1.07 ms per loop
sage: timeit('a=(1+x)/(1-x)')
625 loops, best of 3: 1.07 ms per loop
sage: y = (3*x+2)/(1+x)
sage: y=y/x
sage: z = (x+x^2+1)/(1+x^4+2*x^3+4*x)
sage: z=y/x
sage: timeit('y+z')
625 loops, best of 3: 213 µs per loop
sage: timeit('y*z')
625 loops, best of 3: 118 µs per loop
sage: timeit('y-z')
625 loops, best of 3: 212 µs per loop
sage: timeit('y/z')
ERROR: An unexpected error occurred while tokenizing input
The following traceback may be corrupted or invalid
The error message is: ('EOF in multi-line statement', (27, 0))

---------------------------------------------------------------------------
ArithmeticError                           Traceback (most recent call last)
...
ArithmeticError: division not defined

With the two patches:

sage: R.<x> = ZZ[[]]
sage: timeit('a=1/x')
625 loops, best of 3: 220 µs per loop
sage: timeit('a=(1+x)/x')
625 loops, best of 3: 228 µs per loop
sage: timeit('a=1/(1+x)')
625 loops, best of 3: 1.25 ms per loop
sage: timeit('a=(1+x)/(1-x)')
625 loops, best of 3: 1.26 ms per loop
sage: y = (3*x+2)/(1+x)
sage: y=y/x
sage: z = (x+x^2+1)/(1+x^4+2*x^3+4*x)
sage: z=y/x
sage: timeit('y+z')
625 loops, best of 3: 191 µs per loop
sage: timeit('y*z')
625 loops, best of 3: 92.6 µs per loop
sage: timeit('y-z')
625 loops, best of 3: 191 µs per loop
sage: timeit('y/z')
25 loops, best of 3: 9.35 ms per loop

So, my patches not only fix some bugs, but they also slightly improve the performance.

I tested all files that I have changed, but I can not exclude errors in other files.

I forgot to insert my name as an author, but presumably there will be a revision needed anyway, after comments of referees...

[Simon King]

I forgot one remark:

I don't know how this happens, but the truncate method of Laurent series behaves different than before, although the truncate method of power series did not change:

sage: A.<t> = QQ[[]]
sage: f = (1+t)^100
sage: f.truncate(5)
3921225*t^4 + 161700*t^3 + 4950*t^2 + 100*t + 1
sage: f.truncate(5).parent()
Univariate Polynomial Ring in t over Rational Field
sage: g = 1/f
sage: g.truncate(5)
1 - 100*t + 5050*t^2 - 171700*t^3 + 4421275*t^4 + O(t^5)
sage: g.truncate(5).parent()
Laurent Series Ring in t over Rational Field

In other words, g.truncate(5) is now returning a Laurent series, but without the patch it used to return return a univariate polynomial, similar to f.truncate(5).

I don't know if this is acceptable, and also I don't understand how that happened. Shall I change it?

[Simon King]

Replying to SimonKing:

I forgot one remark:

I don't know how this happens, but the truncate method of Laurent series behaves different than before, although the truncate method of power series did not change:

Outch, now I see my mistake.

• The documentation of LaurentSeries?.truncate states that indeed it returns a Laurent series. It does not have a doc test, so, I will add one.

• The old doc test of PowerSeries?.truncate fails with my patch. The reason is that the power series constructed in this doc test is now in fact a Laurent series; this is what made me believe that the behaviour of the method has changed. So, I only have to change the doc test.

But before submitting a patch to add/correct these doc tests, I'll wait for input of a referee.

[Robert Bradshaw]

Do you have any timings for power series sqrt()?

[Simon King]

Replying to robertwb:

Do you have any timings for power series sqrt()?

Tentatively.

Without the patch:

sage: P.<t> = QQ[[]]
sage: p = 9 - 33*t - 13*t^2 - 155*t^3 - 429*t^4 - 137*t^5 + 170*t^6 + 81*t^7 - 132*t^8 + 179*t^9 + O(t^10)
sage: p.sqrt()
3 - 11/2*t - 173/24*t^2 - 5623/144*t^3 - 174815/1152*t^4 - 8187925/20736*t^5 - 12112939/9216*t^6 - 7942852751/1492992*t^7 - 1570233970141/71663616*t^8 - 12900142229635/143327232*t^9 + O(t^10)
sage: timeit('q = p.sqrt()')
25 loops, best of 3: 13.3 ms per loop
sage: timeit('q = (p^2).sqrt()')
25 loops, best of 3: 13.6 ms per loop
sage: timeit('q = (p^4).sqrt()')
25 loops, best of 3: 14.5 ms per loop
sage: PZ = ZZ[['t']]
sage: timeit('q = (PZ(p)^2).sqrt()')
ERROR: An unexpected error occurred while tokenizing input
The following traceback may be corrupted or invalid
The error message is: ('EOF in multi-line statement', (27, 0))
...
TypeError: no conversion of this rational to integer
sage: p = 9 - 33*t - 13*t^2 - 155*t^3 - 429*t^4 - 137*t^5 + 170*t^6 + 81*t^7 - 132*t^8 + 179*t^9
sage: timeit('q = p.sqrt()')
25 loops, best of 3: 20.7 ms per loop
sage: timeit('q = (p^2).sqrt()')
25 loops, best of 3: 21.9 ms per loop

With the patch:

sage: P.<t> = QQ[[]]
sage: p = 9 - 33*t - 13*t^2 - 155*t^3 - 429*t^4 - 137*t^5 + 170*t^6 + 81*t^7 - 132*t^8 + 179*t^9 + O(t^10)
sage: p.sqrt()
3 - 11/2*t - 173/24*t^2 - 5623/144*t^3 - 174815/1152*t^4 - 8187925/20736*t^5 - 12112939/9216*t^6 - 7942852751/1492992*t^7 - 1570233970141/71663616*t^8 - 12900142229635/143327232*t^9 + O(t^10)
sage: timeit('q = p.sqrt()')
25 loops, best of 3: 15.5 ms per loop
sage: timeit('q = (p^2).sqrt()')
25 loops, best of 3: 15.7 ms per loop
sage: timeit('q = (p^4).sqrt()')
25 loops, best of 3: 16.6 ms per loop
sage: PZ = ZZ[['t']]
sage: timeit('q = (PZ(p)^2).sqrt()')
25 loops, best of 3: 19.2 ms per loop
sage: p = 9 - 33*t - 13*t^2 - 155*t^3 - 429*t^4 - 137*t^5 + 170*t^6 + 81*t^7 - 132*t^8 + 179*t^9
sage: timeit('q = p.sqrt()')
25 loops, best of 3: 23.8 ms per loop
sage: timeit('q = (p^2).sqrt()')
25 loops, best of 3: 24.5 ms per loop

So, over QQ, there is a slight regression (both with exact and inexact input). Over ZZ, it only works with my patch, even for a polynomial that is quadratic by definition.

I will have a closer look at sqrt - perhaps I'll find something.

[Simon King]

Replying to SimonKing:

I will have a closer look at sqrt - perhaps I'll find something.

It seems so.

First, the reason why the old version failed for a power series over ZZ is the fact that the invert method raises an error if the result has coefficients in QQ rather than ZZ. I guess this must change.

Second, there is a division inside the sqrt method. By my patch, this division returns a Laurent series, which slows things slightly down. If I do a*s.invert() instead of a/s then the timings are as good as with the old code.

So, there will soon be a third patch...

[Simon King]

Improving timings for sqrt, further bug fixes, more doc tests. To be applied after the two other patches

[Simon King]

It was worth it!

First, I found one division bug for Laurent series left, which is now fixed (and doc tested):

sage: L.<x> = LaurentSeriesRing(ZZ)
sage: 1/(2+x)
1/2 - 1/4*x + 1/8*x^2 - 1/16*x^3 + 1/32*x^4 - 1/64*x^5 + 1/128*x^6 - 1/256*x^7 + 1/512*x^8 - 1/1024*x^9 + 1/2048*x^10 - 1/4096*x^11 + 1/8192*x^12 - 1/16384*x^13 + 1/32768*x^14 - 1/65536*x^15 + 1/131072*x^16 - 1/262144*x^17 + 1/524288*x^18 - 1/1048576*x^19 + O(x^20)

This used to result in an error.

Second, I added more doc tests (and inserted my name to the author list).

Third, the new timings for sqrt are fully competitive (even very slightly faster than before), and we still have the bug fix:

Loading Sage library. Current Mercurial branch is: powerseries
sage: P.<t> = QQ[[]]
sage: p = 9 - 33*t - 13*t^2 - 155*t^3 - 429*t^4 - 137*t^5 + 170*t^6 + 81*t^7 - 132*t^8 + 179*t^9 + O(t^10)
sage: p.sqrt()
3 - 11/2*t - 173/24*t^2 - 5623/144*t^3 - 174815/1152*t^4 - 8187925/20736*t^5 - 12112939/9216*t^6 - 7942852751/1492992*t^7 - 1570233970141/71663616*t^8 - 12900142229635/143327232*t^9 + O(t^10)
sage: timeit('q = p.sqrt()')
25 loops, best of 3: 13.2 ms per loop
sage: timeit('q = (p^2).sqrt()')
25 loops, best of 3: 13.5 ms per loop
sage: timeit('q = (p^4).sqrt()')
25 loops, best of 3: 14.5 ms per loop
sage: PZ = ZZ[['t']]
sage: timeit('q = (PZ(p)^2).sqrt()')
25 loops, best of 3: 16.4 ms per loop
sage: p = 9 - 33*t - 13*t^2 - 155*t^3 - 429*t^4 - 137*t^5 + 170*t^6 + 81*t^7 - 132*t^8 + 179*t^9
sage: timeit('q = p.sqrt()')
25 loops, best of 3: 20.6 ms per loop
sage: timeit('q = (p^2).sqrt()')
25 loops, best of 3: 21.7 ms per loop

The trick is that I do s*a.invert() instead of s/a, where s and a are power series. This helps, because (after a little change) the invert method returns a power series whenever possible -- and since I know that a.valuation()>=0, I can use fast multiplication of power series rather than slow multiplication of Laurent series.

[Simon King]

O dear, I have to mark it "needs work", because the following fails:

sage: R.<x> = ZZ[[]]
sage: y = (3*x+2)/(1+x)
sage: y=y/x

[Simon King]

Bugfix for LaurentSeries?._div_; to be applied after the other three patches

[Simon King]

Replying to SimonKing:

sage: y=y/x

OK, the last (hopefully the last...) patch fixes this. I was verifying the timings for basic arithmetic (the timings without patches are posted above), and here is the positive result:

sage: R.<x> = ZZ[[]]
sage: timeit('a=1/x')
625 loops, best of 3: 218 µs per loop
sage: timeit('a=(1+x)/x')
625 loops, best of 3: 228 µs per loop
sage: timeit('a=1/(1+x)')
625 loops, best of 3: 1.22 ms per loop
sage: timeit('a=(1+x)/(1-x)')
625 loops, best of 3: 1.24 ms per loop
sage: y = (3*x+2)/(1+x)
sage: y=y/x
sage: z = (x+x^2+1)/(1+x^4+2*x^3+4*x)
sage: z=y/x
sage: timeit('y+z')
625 loops, best of 3: 189 µs per loop
sage: timeit('y*z')
625 loops, best of 3: 92.6 µs per loop
sage: timeit('y-z')
625 loops, best of 3: 189 µs per loop
sage: timeit('y/z')
125 loops, best of 3: 7.1 ms per loop

Now, ready for review, and I'll do something else...

[Robert Bradshaw]

Minor cosmetic changes, apply on top of previous.

[Robert Bradshaw]

Nice work. Apply all 5 patches.

[David Kirkby]

The reviewer field was not filled in. I just added it.

Dave

[David Kirkby]

Sorry about the spelling mistake!

[Mike Hansen]

I had to back these patches out since they caused lots of errors in schemes/elliptic_curves.

[Simon King]

Hi Mike!

That probably means that the elliptic curves code expects the result of a division of two power series to be another power series. But now, the division yields a Laurent series.

I see two possibilities to proceed:

1. Search for all occurences of power series in Sage, see if a division occurs, and change it so that things still work.
2. Change/extend the methods provided by Laurent series so that they match those provided by power series. In that way, the code in schemes/elliptic_curves still has a chance to work.

I'll see what I can do.

Best regards, Simon

[Simon King]

I think the problem boils down to two problems:

1. Laurent series have no attribute exp, unlike power series.

2. In some situations, there still occurs a formal fraction field when it should be a Laurent series ring. The result is an attribute error.

For the first situation, I suggest to implement exp for Laurent series of non-negative valuation (using exp of the underlying power series). For the second situation, I have to analyse what goes wrong.

[Simon King]

The problem is that some code expects the fraction field of a power series ring to be a formal fraction field. So, assume that one changes it, so that the fraction field is in fact a Laurent polynomial ring. When creating elements of the fraction field, the code fails, because it tries to initialise the element by numerator and denominator -- but Laurent series are initialised by a power series and an integer.

A possible solution would be to make the init method of Laurent series accept numerator and denominator. But I think that's a nasty hack, because what happens if the arguments are one power series and one integer? Is the integer supposed to be the valuation of the Laurent series, or the denominator of a formal fraction field element?

[Simon King]

It is really frustrating how many doc tests fail. I solved the problem with exp and one other attribute error. But there remain many problems: ZeroDivisionError, wrong precision of the result (!), and so on.

[Simon King]

In most cases, the problems seem to come from using f/g on power series in situations where g is of valuation zero. This used to return a power series, which I consider the wrong answer (it should be a Laurent series). Now, if one wants f/g as a power series, one should use f * ~g instead.

I am now confident that I'll soon be able to submit another patch that resolves it.

[Simon King]

After fixing what I mentioned above, I get for sage -testall:

The following tests failed:


        sage -t  "devel/sage/sage/crypto/lfsr.py"
        sage -t  "devel/sage/sage/modular/modform/find_generators.py"
        sage -t  "devel/sage/sage/schemes/hyperelliptic_curves/hyperelliptic_padic_field.py"

This seems doable.

Perhaps I was too strict when I implemented _div_: I wanted that the result always lives in the fraction field, and I wanted that an error is raised if no fraction field exists. But I guess it is better to proceed as it is known from other rings that are no integral domains:

sage: K = ZZ.quo(15)
sage: parent(K(3)/K(4))
Ring of integers modulo 15
sage: parent(K(4)/K(3))
---------------------------------------------------------------------------
ZeroDivisionError                         Traceback (most recent call last)
...
ZeroDivisionError: Inverse does not exist.

So, rule:

1. If a fraction field exists then the result of a division must live in it (example: 1/1 is a rational, not an integer).
2. If no fraction field exists, then devision shall yield an element of the original ring, if that's possible, and raise a ZeroDivisionError otherwise.

[Simon King]

Fixing some remaining bugs of Laurent/power series arithmetic; fixing doc tests on elliptic curves.

[Simon King]

I think the problems are now solved. With the last patch, that is to be applied after all others, sage -testall works without errors (at least in version sage-4.4.2).

Changes introduced by the patch

• In some cases, if the code expects a power series, I replaced a/b for power series a,b by a*~b. Namely, the latter returns a power series (not a Laurent series), if possible.

• I added a method exp for Laurent series, that returns the exponential if the Laurent series happens to be a power series.

• With my previous patches, the underlying data of a Laurent series is not necessarily a power series. Therefore add_bigoh (similarly _rmul_ and _lmul_) did in some cases not work. This is now fixed and doctested.

• Some Power Series Rings still returned a formal fraction field. This is now fixed, they return a Laurent series ring.

• If a,b are elements of a power series ring R, the rule is now:

1. If R is an integral domain, then a/b always belongs to Frac(R). This is similar to 1/1 being rational, not integer.

2. If R is no integral domain, then a/b is an element of R or of the Laurent series ring over the base ring of R, if b is invertible. This is similar to division in ZZ.quo(15).

3. If possible, ~b is a power series (possibly over the fraction field of the base of R). So, we always have ~b==1/b, but the parents may be different. I hope this is acceptable.

• A change in the default _div_ method of RingElement: Previously, the default for a._div_(b) was to return a.parent().fraction_field()(a,b). But this may be a problem (e.g., if the fraction field is not a formal fraction field but a Laurent series ring). Therefore, if the old default results in an error, a.parent().fraction_field(a)/a.parent().fraction_field(b) is tried.

Timings

Robert was worried about potential slowdowns in the Monsky-Washnitzer code. It seems to me that my patches actually provide a considerably speedup.

Without my patches:

sage -t  "devel/sage-powerseries/sage/schemes/elliptic_curves/monsky_washnitzer.py"
         [3.9 s]

----------------------------------------------------------------------
All tests passed!
Total time for all tests: 3.9 seconds

With my patches:

sage -t  "devel/sage-powerseries/sage/schemes/elliptic_curves/monsky_washnitzer.py"
         [2.3 s]

----------------------------------------------------------------------
All tests passed!
Total time for all tests: 2.3 seconds

So, the code seems to become faster by more than 33%!

Ready for review again...

[Simon King]

I upgraded to sage-4.4.3.

I verified that all patches still apply.

With the patches, sage -testall passes.

On sage-devel, Robert asked how stable my Monsky-Washnitzer timing is. Here is the answer:

Without the patches, I was running sage -t "devel/sage/sage/schemes/elliptic_curves/monsky_washnitzer.py" 5 times, and got

7.9 s, 2.4 s, 2.4 s, 2.4 s, 2.4 s

With the patches, I obtain

2.4 s, 2.5 s, 2.4 s, 2.4 s, 2.4 s

So, the timing did not improve, except for the first run. But at least there was no slowdown.

[Simon King]

Accidentally, I found that this ticket is rotting.

Recall that it used to be "fixed", but then it was reopened by mhansen, since there was a problem in sage-4.4.alpha0. Subsequently, I fixed these problems, but still the resolution is set to "fixed".

I guess this is why nobody took care of the ticket afterwards.

I don't know if the patch would still apply (probably not), but at least I verified that the original problem did not disappear.

[Gagan Sekhon]

test of sage/modular/modform/find_generators.py failed.

./sage -t sage/modular/modform/find_generators.py
sage -t  "devel/sage-main/sage/modular/modform/find_generators.py"
**********************************************************************
File "/Applications/sage4.6/devel/sage-main/sage/modular/modform/find_generators.py", line 74:
    sage: span_of_series(v)
Exception raised:
    Traceback (most recent call last):
      File "/Applications/sage4.6/local/bin/ncadoctest.py", line 1231, in run_one_test
        self.run_one_example(test, example, filename, compileflags)
      File "/Applications/sage4.6/local/bin/sagedoctest.py", line 38, in run_one_example
        OrigDocTestRunner.run_one_example(self, test, example, filename, compileflags)
      File "/Applications/sage4.6/local/bin/ncadoctest.py", line 1172, in run_one_example
        compileflags, 1) in test.globs
      File "<doctest __main__.example_1[8]>", line 1, in <module>
        span_of_series(v)###line 74:
    sage: span_of_series(v)
      File "/Applications/sage4.6/local/lib/python/site-packages/sage/modular/modform/find_generators.py", line 116, in span_of_series
        B = [V(g.padded_list(n)) for g in v]
      File "element.pyx", line 306, in sage.structure.element.Element.__getattr__ (sage/structure/element.c:2666)
      File "parent.pyx", line 272, in sage.structure.parent.getattr_from_other_class (sage/structure/parent.c:2840)
      File "parent.pyx", line 170, in sage.structure.parent.raise_attribute_error (sage/structure/parent.c:2611)
    AttributeError: 'sage.rings.laurent_series_ring_element.LaurentSeries' object has no attribute 'padded_list'
**********************************************************************
File "/Applications/sage4.6/devel/sage-main/sage/modular/modform/find_generators.py", line 79:
    sage: span_of_series(v,10)
Exception raised:
    Traceback (most recent call last):
      File "/Applications/sage4.6/local/bin/ncadoctest.py", line 1231, in run_one_test
        self.run_one_example(test, example, filename, compileflags)
      File "/Applications/sage4.6/local/bin/sagedoctest.py", line 38, in run_one_example
        OrigDocTestRunner.run_one_example(self, test, example, filename, compileflags)
      File "/Applications/sage4.6/local/bin/ncadoctest.py", line 1172, in run_one_example
        compileflags, 1) in test.globs
      File "<doctest __main__.example_1[9]>", line 1, in <module>
        span_of_series(v,Integer(10))###line 79:
    sage: span_of_series(v,10)
      File "/Applications/sage4.6/local/lib/python/site-packages/sage/modular/modform/find_generators.py", line 116, in span_of_series
        B = [V(g.padded_list(n)) for g in v]
      File "element.pyx", line 306, in sage.structure.element.Element.__getattr__ (sage/structure/element.c:2666)
      File "parent.pyx", line 272, in sage.structure.parent.getattr_from_other_class (sage/structure/parent.c:2840)
      File "parent.pyx", line 170, in sage.structure.parent.raise_attribute_error (sage/structure/parent.c:2611)
    AttributeError: 'sage.rings.laurent_series_ring_element.LaurentSeries' object has no attribute 'padded_list'
**********************************************************************
1 items had failures:
   2 of  14 in __main__.example_1
***Test Failed*** 2 failures.
For whitespace errors, see the file /Users/sekhon/.sage//tmp/.doctest_find_generators.py
	 [4.0 s]
 
----------------------------------------------------------------------
The following tests failed:


	sage -t  "devel/sage-main/sage/modular/modform/find_generators.py"
Total time for all tests: 4.0 seconds

[Simon King]

Apply trac-8972_fraction_of_power_series_combined.patch

(for the patchbot)

[Simon King]

For simplicity, I produced a patch that combines all previous patches and is rebased to sage-4.6.2.alpha4.

I will now try to take care about the failing doc tests.

[Simon King]

I managed to fix the remaining issues, and all tests pass (unless a last minute change that I just did was a bad idea). Hence, this ticket needs review again.

Since the computation time was a point of critique, let me give you some timings:

Without the patch:

# Basic arithmetic
sage: R.<x> = ZZ[[]]
sage: timeit('a=1/(1+x)')
625 loops, best of 3: 803 µs per loop
sage: timeit('a=1/x')
625 loops, best of 3: 279 µs per loop
sage: timeit('a=(1+x)/x')
625 loops, best of 3: 285 µs per loop
sage: timeit('a=1/(1+x)')
625 loops, best of 3: 801 µs per loop
sage: y = (3*x+2)/(1+x)
sage: y=y/x
sage: z = (x+x^2+1)/(1+x^4+2*x^3+4*x)
sage: z=y/x
sage: timeit('y+z')
625 loops, best of 3: 167 µs per loop
sage: timeit('y*z')
625 loops, best of 3: 100 µs per loop
sage: timeit('y-z')
625 loops, best of 3: 166 µs per loop

# square roots
sage: P.<t> = QQ[[]]
sage: p = 9 - 33*t - 13*t^2 - 155*t^3 - 429*t^4 - 137*t^5 + 170*t^6 + 81*t^7 - 132*t^8 + 179*t^9 + O(t^10)
sage: p.sqrt()
3 - 11/2*t - 173/24*t^2 - 5623/144*t^3 - 174815/1152*t^4 - 8187925/20736*t^5 - 12112939/9216*t^6 - 7942852751/1492992*t^7 - 1570233970141/71663616*t^8 - 12900142229635/143327232*t^9 + O(t^10)
sage: timeit('q = p.sqrt()')
625 loops, best of 3: 767 µs per loop
sage: timeit('q = (p^2).sqrt()')
625 loops, best of 3: 791 µs per loop
sage: timeit('q = (p^4).sqrt()')
625 loops, best of 3: 828 µs per loop
sage: PZ = ZZ[['t']]
sage: timeit('q = (PZ(p)^2).sqrt()')
<BOOM>
sage: p = 9 - 33*t - 13*t^2 - 155*t^3 - 429*t^4 - 137*t^5 + 170*t^6 + 81*t^7 - 132*t^8 + 179*t^9
sage: timeit('q = p.sqrt()')
625 loops, best of 3: 1 ms per loop
sage: timeit('q = (p^2).sqrt()')
625 loops, best of 3: 1.04 ms per loop
sage: timeit('q = (p^2).sqrt()')
625 loops, best of 3: 1.04 ms per loop

With the patch:

# Basic arithmetic
sage: R.<x> = ZZ[[]]
sage: timeit('a=1/(1+x)')
625 loops, best of 3: 897 µs per loop
sage: timeit('a=1/x')
625 loops, best of 3: 173 µs per loop
sage: timeit('a=(1+x)/x')
625 loops, best of 3: 179 µs per loop
sage: timeit('a=1/(1+x)')
625 loops, best of 3: 911 µs per loop
sage: timeit('a=(1+x)/(1-x)')
625 loops, best of 3: 900 µs per loop
sage: y = (3*x+2)/(1+x)
sage: y=y/x
sage: z = (x+x^2+1)/(1+x^4+2*x^3+4*x)
sage: z=y/x
sage: timeit('y+z')
625 loops, best of 3: 38.4 µs per loop
sage: timeit('y*z')
625 loops, best of 3: 23.6 µs per loop
sage: timeit('y-z')
625 loops, best of 3: 23.6 µs per loop
sage: timeit('y/z')
625 loops, best of 3: 309 µs per loop

# square roots
sage: P.<t> = QQ[[]]
sage: p = 9 - 33*t - 13*t^2 - 155*t^3 - 429*t^4 - 137*t^5 + 170*t^6 + 81*t^7 - 132*t^8 + 179*t^9 + O(t^10)
sage: p.sqrt()
3 - 11/2*t - 173/24*t^2 - 5623/144*t^3 - 174815/1152*t^4 - 8187925/20736*t^5 - 12112939/9216*t^6 - 7942852751/1492992*t^7 - 1570233970141/71663616*t^8 - 12900142229635/143327232*t^9 + O(t^10)
sage: timeit('q = p.sqrt()')
625 loops, best of 3: 938 µs per loop
sage: timeit('q = (p^2).sqrt()')
625 loops, best of 3: 962 µs per loop
sage: timeit('q = (p^4).sqrt()')
625 loops, best of 3: 1 ms per loop
sage: PZ = ZZ[['t']]
sage: timeit('q = (PZ(p)^2).sqrt()')
125 loops, best of 3: 2.39 ms per loop
sage: p = 9 - 33*t - 13*t^2 - 155*t^3 - 429*t^4 - 137*t^5 + 170*t^6 + 81*t^7 - 132*t^8 + 179*t^9
sage: timeit('q = p.sqrt()')
625 loops, best of 3: 1.22 ms per loop
sage: timeit('q = (p^2).sqrt()')
625 loops, best of 3: 1.26 ms per loop

So, in some cases the patch brings a big speedup (such as 38.4 µs versus 167 µs), in other cases it brings a mild slowdown (such as 962 µs versus 791 µs)

Obvious question to the referee: Should I try to squeeze even more µs out of it, or can it stay as it is (assuming that the long tests pass, as I will try now).

[Simon King]

FWIW: Long tests pass.

[Simon King]

Apply trac-8972_fraction_of_power_series_combined.patch

[Simon King]

Don't be irritated by the patchbot. The patch is for 4.6.2.alpha4, not for 4.6.1

[Kiran Kedlaya]

This fails to apply against 4.7, so more rebasing is needed.

cd "/home/kedlaya/Downloads/sage-4.7/devel/sage" && hg import   "/home/kedlaya/Downloads/trac-8972_fraction_of_power_series_combined.patch"
applying /home/kedlaya/Downloads/trac-8972_fraction_of_power_series_combined.patch
patching file sage/modular/overconvergent/genus0.py
Hunk #1 FAILED at 1653
1 out of 1 hunks FAILED -- saving rejects to file sage/modular/overconvergent/genus0.py.rej
patching file sage/rings/power_series_poly.pyx
Hunk #4 FAILED at 843
Hunk #5 succeeded at 876 with fuzz 2 (offset 11 lines).
1 out of 5 hunks FAILED -- saving rejects to file sage/rings/power_series_poly.pyx.rej
patching file sage/rings/power_series_ring_element.pyx
Hunk #11 FAILED at 1771
Hunk #12 FAILED at 1783
2 out of 12 hunks FAILED -- saving rejects to file sage/rings/power_series_ring_element.pyx.rej
abort: patch failed to apply

[Simon King]

Apparently the trac is locked in "bold face mode". Trying to change it.

[Simon King]

Replaces all previous patches

[Simon King]

I have rebased the patch. The test suite needs to be run, but the patch should now apply to sage-5.0.beta10. Here is some supporting evidence:

First section: The bugs to be fixed

sage-5.0.beta10-gcc without the patch

sage: R.<x> = ZZ[[]]
sage: (1/x).parent()  # bug
Laurent Series Ring in x over Integer Ring
sage: (x/x).parent()  # bug
Power Series Ring in x over Integer Ring
sage: (1/(2*x)).parent()  # bug
Traceback (most recent call last):
...
TypeError: no conversion of this rational to integer
sage: F = FractionField(R)
sage: 1/x in F    # bug
False
sage: F           # I think a Laurent series ring would be better
Fraction Field of Power Series Ring in x over Integer Ring
sage: F(x)
x
sage: ~F(x)   # was a problem with an early form of my patches.
1/x

sage-5.0.beta10-gcc with the patch

age: R.<x> = ZZ[[]]
sage: (1/x).parent()   # bug fixed
Laurent Series Ring in x over Rational Field
sage: (x/x).parent()   # bug fixed
Laurent Series Ring in x over Rational Field
sage: (1/(2*x)).parent() # bug fixed
Laurent Series Ring in x over Rational Field
sage: F = FractionField(R)
sage: 1/x in F         # bug fixed
True
sage: F                # I think that's much better!
Laurent Series Ring in x over Rational Field
sage: F(x)
x
sage: ~F(x)            # new bug avoided
x^-1

Second section: Timings

Here I am collecting the examples that were studied in the comments above.

sage-5.0.beta10-gcc without the patch

sage: R.<x> = ZZ[[]]
sage: timeit('a=1/(1+x)')
625 loops, best of 3: 445 µs per loop
sage: timeit('a=1/x')
625 loops, best of 3: 283 µs per loop
sage: timeit('a=(1+x)/x')
625 loops, best of 3: 290 µs per loop
sage: timeit('a=(1+x)/(1-x)')
625 loops, best of 3: 450 µs per loop
sage: y = (3*x+2)/(1+x)
sage: y=y/x
sage: z = (x+x^2+1)/(1+x^4+2*x^3+4*x)
sage: z=y/x
sage: timeit('y+z')
625 loops, best of 3: 104 µs per loop
sage: timeit('y*z')
625 loops, best of 3: 76.2 µs per loop
sage: timeit('y-z')
625 loops, best of 3: 103 µs per loop
sage: timeit('y/z')    # bug
Traceback (most recent call last):
...
ArithmeticError: division not defined
sage: P.<t> = QQ[[]]
sage: p = 9 - 33*t - 13*t^2 - 155*t^3 - 429*t^4 - 137*t^5 + 170*t^6 + 81*t^7 - 132*t^8 + 179*t^9 + O(t^10)
sage: p.sqrt()
3 - 11/2*t - 173/24*t^2 - 5623/144*t^3 - 174815/1152*t^4 - 8187925/20736*t^5 - 12112939/9216*t^6 - 7942852751/1492992*t^7 - 1570233970141/71663616*t^8 - 12900142229635/143327232*t^9 + O(t^10)
sage: timeit('q = p.sqrt()')
625 loops, best of 3: 810 µs per loop
sage: timeit('q = (p^2).sqrt()')
625 loops, best of 3: 829 µs per loop
sage: timeit('q = (p^4).sqrt()')
625 loops, best of 3: 890 µs per loop
sage: PZ = ZZ[['t']]
sage: timeit('q = (PZ(p)^2).sqrt()')    # bug
ERROR: An unexpected error occurred while tokenizing input
The following traceback may be corrupted or invalid
The error message is: ('EOF in multi-line statement', (2017, 0))
Traceback (most recent call last):
...
TypeError: no conversion of this rational to integer
sage: p = 9 - 33*t - 13*t^2 - 155*t^3 - 429*t^4 - 137*t^5 + 170*t^6 + 81*t^7 - 132*t^8 + 179*t^9
sage: timeit('q = p.sqrt()')
125 loops, best of 3: 1.07 ms per loop
sage: timeit('q = (p^2).sqrt()')
625 loops, best of 3: 1.12 ms per loop
sage: timeit('q = (p^2).sqrt()')
625 loops, best of 3: 1.12 ms per loop

sage-5.0.beta10-gcc with the patch

sage: R.<x> = ZZ[[]]
sage: timeit('a=1/(1+x)')
625 loops, best of 3: 506 µs per loop
sage: timeit('a=1/x')
625 loops, best of 3: 153 µs per loop
sage: timeit('a=(1+x)/x')
625 loops, best of 3: 160 µs per loop
sage: timeit('a=(1+x)/(1-x)')
625 loops, best of 3: 516 µs per loop
sage: y = (3*x+2)/(1+x)
sage: y=y/x
sage: z = (x+x^2+1)/(1+x^4+2*x^3+4*x)
sage: z=y/x
sage: timeit('y+z')
625 loops, best of 3: 37.8 µs per loop
sage: timeit('y*z')
625 loops, best of 3: 26.9 µs per loop
sage: timeit('y-z')
625 loops, best of 3: 20.6 µs per loop
sage: timeit('y/z')      # bug fixed
625 loops, best of 3: 277 µs per loop
sage: P.<t> = QQ[[]]
sage: p = 9 - 33*t - 13*t^2 - 155*t^3 - 429*t^4 - 137*t^5 + 170*t^6 + 81*t^7 - 132*t^8 + 179*t^9 + O(t^10)
sage: p.sqrt()
3 - 11/2*t - 173/24*t^2 - 5623/144*t^3 - 174815/1152*t^4 - 8187925/20736*t^5 - 12112939/9216*t^6 - 7942852751/1492992*t^7 - 1570233970141/71663616*t^8 - 12900142229635/143327232*t^9 + O(t^10)
sage: timeit('q = p.sqrt()')
625 loops, best of 3: 847 µs per loop
sage: timeit('q = (p^2).sqrt()')
625 loops, best of 3: 872 µs per loop
sage: timeit('q = (p^4).sqrt()')
625 loops, best of 3: 932 µs per loop
sage: PZ = ZZ[['t']]
sage: timeit('q = (PZ(p)^2).sqrt()')    # bug fixed
125 loops, best of 3: 1.46 ms per loop
sage: p = 9 - 33*t - 13*t^2 - 155*t^3 - 429*t^4 - 137*t^5 + 170*t^6 + 81*t^7 - 132*t^8 + 179*t^9
sage: timeit('q = p.sqrt()')
625 loops, best of 3: 1.11 ms per loop
sage: timeit('q = (p^2).sqrt()')
625 loops, best of 3: 1.17 ms per loop
sage: timeit('q = (p^2).sqrt()')
625 loops, best of 3: 1.17 ms per loop

I think, given that various bugs are fixed, and I think the timings tend to be better (not in all examples, but it seems to me that the loss is less than the gain), I guess it is "needs review", modulo doc test suite.

Apply trac-8972_fraction_of_power_series_combined.patch

[David Loeffler]

The patchbot reports a doctest failure with 5.0.beta11:

sage -t  -force_lib devel/sage-8972/sage/rings/multi_power_series_ring_element.py
**********************************************************************
File "/storage/masiao/sage-5.0.beta11-patchbot/devel/sage-8972/sage/rings/multi_power_series_ring_element.py", line 139:
    sage: h = 1/f; h
Exception raised:
    Traceback (most recent call last):
      File "/storage/masiao/sage-5.0.beta11-patchbot/local/bin/ncadoctest.py", line 1231, in run_one_test
        self.run_one_example(test, example, filename, compileflags)
      File "/storage/masiao/sage-5.0.beta11-patchbot/local/bin/sagedoctest.py", line 38, in run_one_example
        OrigDocTestRunner.run_one_example(self, test, example, filename, compileflags)
      File "/storage/masiao/sage-5.0.beta11-patchbot/local/bin/ncadoctest.py", line 1172, in run_one_example
        compileflags, 1) in test.globs
      File "<doctest __main__.example_0[46]>", line 1, in <module>
        h = Integer(1)/f; h###line 139:
    sage: h = 1/f; h
      File "element.pyx", line 1799, in sage.structure.element.RingElement.__div__ (sage/structure/element.c:13260)
      File "coerce.pyx", line 738, in sage.structure.coerce.CoercionModel_cache_maps.bin_op (sage/structure/coerce.c:6583)
      File "coerce.pyx", line 1210, in sage.structure.coerce.CoercionModel_cache_maps.get_action (sage/structure/coerce.c:11424)
      File "coerce.pyx", line 1378, in sage.structure.coerce.CoercionModel_cache_maps.discover_action (sage/structure/coerce.c:13135)
      File "ring.pyx", line 1420, in sage.rings.ring.CommutativeRing._pseudo_fraction_field (sage/rings/ring.c:9929)
        return self.fraction_field()
      File "/storage/masiao/sage-5.0.beta11-patchbot/local/lib/python/site-packages/sage/rings/power_series_ring.py", line 672, in fraction_field
        return LaurentSeriesRing(self.base().fraction_field(),self.variable_names())
      File "/storage/masiao/sage-5.0.beta11-patchbot/local/lib/python/site-packages/sage/rings/laurent_series_ring.py", line 91, in LaurentSeriesRing
        R = LaurentSeriesRing_field(base_ring, name, sparse)
      File "/storage/masiao/sage-5.0.beta11-patchbot/local/lib/python/site-packages/sage/rings/laurent_series_ring.py", line 400, in __init__
        LaurentSeriesRing_generic.__init__(self, base_ring, name, sparse)
      File "/storage/masiao/sage-5.0.beta11-patchbot/local/lib/python/site-packages/sage/rings/laurent_series_ring.py", line 121, in __init__
        commutative_ring.CommutativeRing.__init__(self, base_ring, names=name, category=_Fields)
      File "ring.pyx", line 1365, in sage.rings.ring.CommutativeRing.__init__ (sage/rings/ring.c:9627)
        Ring.__init__(self, base_ring, names=names, normalize=normalize,
      File "ring.pyx", line 156, in sage.rings.ring.Ring.__init__ (sage/rings/ring.c:1903)
        Parent.__init__(self, base=base, names=names, normalize=normalize,
      File "parent.pyx", line 532, in sage.structure.parent.Parent.__init__ (sage/structure/parent.c:4484)
      File "parent_gens.pyx", line 331, in sage.structure.parent_gens.ParentWithGens._assign_names (sage/structure/parent_gens.c:3052)
      File "parent_gens.pyx", line 213, in sage.structure.parent_gens.normalize_names (sage/structure/parent_gens.c:2360)
    IndexError: the number of names must equal the number of generators
**********************************************************************

[Simon King]

Arrgh. That's nasty. The reason for the doctest problems is that meanwhile there are multivariate power series rings -- but there are still no multivariate Laurent series rings.

Spontaneously, I suggest a temporary work-around: In the case of multivariate case, the old behaviour (namely: using a formal fraction field) should be used, until multivariate Laurent series are available.

[Simon King]

My spontaneous suggestion does not work easily. Sorry.

[Robert Harron]

I think it would be great for this ticket to come back to life! Is it possible to just take the current power series classes append _old to all the class names and have the multivariable power series inherit from those?

(Since no one has posted a ticket for creating multivariable Laurent series, let me ask here what is wrong with making them a multivariable power series ring with a univariate Laurent series ring in the background?)

[Peter Bruin]

Converted the patch into a Git branch and resolved merge conflicts. Fixed a few relatively straightforward doctest failures in the second commit. Summary of remaining failures:

sage -t --long src/sage/schemes/hyperelliptic_curves/hyperelliptic_padic_field.py  # 4 doctests failed
sage -t --long src/sage/tests/french_book/polynomes.py  # 2 doctests failed
sage -t --long src/sage/rings/multi_power_series_ring_element.py  # 4 doctests failed

[Frédéric Chapoton]

just rebased on 6.3.beta5

---

New commits:

​c29b36d

Merge branch 'u/pbruin/8972-fraction_power_series' of ssh://trac.sagemath.org:22/sage into 8972

[git]

Branch pushed to git repo; I updated commit sha1. New commits:

​ac4f730	Merge branch 'public/ticket/8972' of ssh://trac.sagemath.org:22/sage into 8972
​de0ba0d	trac #8972 using the trac role, plus some python3 formatting

[Frédéric Chapoton]

Failures in src/sage/schemes/hyperelliptic_curves/hyperelliptic_padic_field.py seem to be just about slight changes in precision (either gain or loss by one). Maybe one can just correct the result of the doctests.

Failures in src/sage/rings/multi_power_series_ring_element.py are more serious: they come from trying to build a Laurent series ring in several variables, that we currently do not have !

[Ralf Stephan]

I have a question about the description of this issue. Please forgive that I'm no algebraist.

sage: (1/(2*x)).parent()
...
TypeError: no conversion of this rational to integer

Isn't this correct, with the ring over ZZ? With QQ there is no error.

If so, the description should be corrected.

[git]

Branch pushed to git repo; I updated commit sha1. New commits:

​888cf7a

Merge branch 'public/ticket/8972' into 6.5.rc0

[git]

Branch pushed to git repo; I updated commit sha1. New commits:

​bc2a834

trac #8972 correct trivial doctest failures

[Kiran Kedlaya]

Since the power series issue is somewhat separate, I created #21283 to deal with it on its own.

[git]

Branch pushed to git repo; I updated commit sha1. This was a forced push. New commits:

​2602f8d

Trac #8972: use fraction_field instead of laurent_series

[Michael Jung]

Approach might be too naive, but it seems to solve the first and the last bug without compromising the timing.

[git]

Branch pushed to git repo; I updated commit sha1. New commits:

​f0334c2	Trac #8972: case of non integral domain
​e4b0977	Trac #8972: adapt doctests

[git]

Branch pushed to git repo; I updated commit sha1. This was a forced push. New commits:

​7399856

Trac #8972: use fraction_field instead of laurent_series

[Michael Jung]

This should do.

[Peter Bruin]

Replying to gh-mjungmath:

Approach might be too naive, but it seems to solve the first and the last bug without compromising the timing.

Does this also address the dependency #21283?

[Michael Jung]

Replying to pbruin:

Replying to gh-mjungmath:

Approach might be too naive, but it seems to solve the first and the last bug without compromising the timing.

Does this also address the dependency #21283?

Nope. I just wanted to see what the patchbot has to say before I modify the ticket description. Here we go.

[Michael Jung]

Yay! Patchbot is green! :)

[Michael Jung]

Would be nice to have this ticket reviewed. Thanks. :)

[Michael Jung]

Patchbot seems still be satisfied with beta7. It'd be nice to have this change in version 9.3 though. Otherwise, a rebase might become necessary soon...

[Travis Scrimshaw]

There are a few details that still fixing:

This seems strange:

:doc:`laurent_series_ring_element`.

Wouldn't it be better to be a specific reference to the class? Although I am not sure it is worth the direct reference.

This is wrong:

        If we try a non-zero, non-unit leading coefficient, we end up in the in
        the fraction field, i.e. Laurent series ring::

Even for units, you still end up in the fraction field.

-However, this must fail if the underlying ring is no integral domain::
+However, this must fail if the underlying ring is not an integral domain::

[Michael Jung]

Thank you Travis for taking a look!

Replying to tscrim:

There are a few details that still fixing:

This seems strange:

:doc:`laurent_series_ring_element`.

Wouldn't it be better to be a specific reference to the class? Although I am not sure it is worth the direct reference.

Alright, I'll change it.

This is wrong:

        If we try a non-zero, non-unit leading coefficient, we end up in the in
        the fraction field, i.e. Laurent series ring::

Even for units, you still end up in the fraction field.

Oh right. I think the previous author already meant constant terms instead of leading terms. At least that would make more sense.

-However, this must fail if the underlying ring is no integral domain::
+However, this must fail if the underlying ring is not an integral domain::

Will do.

[git]

Branch pushed to git repo; I updated commit sha1. New commits:

​5aca068

Trac #8972: documentation improved

[Michael Jung]

That should be better.

[Travis Scrimshaw]

Thanks. LGTM.