On Wed, Apr 22, 2020 at 11:00 AM John H Palmieri <jhpalmier...@gmail.com> wrote:
>
>
>
> On Tuesday, April 21, 2020 at 7:59:18 PM UTC-7, John H Palmieri wrote:
>>
>>
>>
>> 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> 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.
>
>
> By "those failures", I mean the obvious failures are caught. The problematic
> line here still seems to work.
this feels like an uncaught exception in randstate, or something like this.
>
>>
>>
>> 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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