On Tuesday, April 21, 2020 at 5:26:00 PM UTC-7, Dima Pasechnik wrote:
>
> On Wed, Apr 22, 2020 at 2:56 AM k2wagle <archi...@gmail.com <javascript:>>
> wrote:
> >
> > Tried this just now, getting the same error. Open a ticket please.
>
> This error is already in Sage 9.0 - and this is an example from the
> manual!
>
> It's quite alarming that our doctests let it through, as it never
> showed in doctests, and
> indeed if I do
>
> ./sage -tp --verbose src/sage/graphs/hypergraph_generators.py
>
> I see in particular
> -----------------------------------
> Trying (line 218): H = hypergraphs.UniformRandomUniform(52, 3, 17)
> Expecting nothing
> ok [0.01 s]
> Trying (line 219): H
> Expecting:
> Incidence structure with 52 points and 17 blocks
> ok [0.00 s]
> -------------------------------------
>
> as if it works.
>
Maybe it is working: maybe there is something in the doctesting framework
that makes it work somehow. If I put obviously failing doctests in that
file immediately before and after these lines, those failures are caught.
It's very strange.
To fix this particular problem, do something like:
diff --git a/src/sage/graphs/hypergraph_generators.py
b/src/sage/graphs/hypergraph_generators.py
index aa3d5e3988..679ddea5ce 100644
--- a/src/sage/graphs/hypergraph_generators.py
+++ b/src/sage/graphs/hypergraph_generators.py
@@ -262,7 +262,7 @@ class HypergraphGenerators():
raise ValueError("the uniformity should be an integer")
all_edges = Subsets(vertices, uniformity)
try:
- edges = sample(all_edges, m)
+ edges = sample(set(all_edges), m)
except OverflowError:
raise OverflowError("binomial({}, {}) too large to be
treated".format(n, k))
except ValueError:
>
>
>
> >
> > On Tuesday, 21 April 2020 23:56:45 UTC+5:30, Vipul Gupta wrote:
> >>
> >> On running the example given here in the documentation of
> `UniformRandomUniform` method.
> >> It is raising the following error.
> >>
> >> sage: H = hypergraphs.UniformRandomUniform(52, 3, 17)
> >>
> ---------------------------------------------------------------------------
> >> TypeError Traceback (most recent call
> last)
> >> <ipython-input-1-56df6490a66e> in <module>()
> >> ----> 1 H = hypergraphs.UniformRandomUniform(Integer(52), Integer(3),
> Integer(17))
> >>
> >>
> /home/vipul/sage/local/lib/python3.7/site-packages/sage/graphs/hypergraph_generators.py
>
> in UniformRandomUniform(self, n, k, m)
> >> 263 all_edges = Subsets(vertices, uniformity)
> >> 264 try:
> >> --> 265 edges = sample(all_edges, m)
> >> 266 except OverflowError:
> >> 267 raise OverflowError("binomial({}, {}) too large to
> be treated".format(n, k))
> >>
> >> /home/vipul/sage/local/lib/python3.7/site-packages/sage/misc/prandom.py
> in sample(population, k)
> >> 178 [357009070, 558990255, 196187132, 752551188, 85926697,
> 954621491, 624802848]
> >> 179 """
> >> --> 180 return _pyrand().sample(population, k)
> >> 181
> >> 182 def random():
> >>
> >> /home/vipul/sage/local/lib/python3.7/random.py in sample(self,
> population, k)
> >> 315 population = tuple(population)
> >> 316 if not isinstance(population, _Sequence):
> >> --> 317 raise TypeError("Population must be a sequence or
> set. For dicts, use list(d).")
> >> 318 randbelow = self._randbelow
> >> 319 n = len(population)
> >>
> >> TypeError: Population must be a sequence or set. For dicts, use
> list(d).
> >>
> >>
> >>
> >> Can somebody please point out if I am doing something wrong.
> >> Or Should I open a ticket on trac server regarding this, so that this
> defect can be solved.
> >>
> >> Regards
> >> Vipul Gupta
> >>
> >>
> >>
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>
>
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