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gh-38354: add uniform generator of random proper interval graphs
This PR implements the random proper interval graph generator proposed
in
- Toshiki Saitoh, Katsuhisa Yamanaka, Masashi Kiyomi, Ryuhei Uehara:
Random Generation and Enumeration of Proper Interval Graphs. IEICE
Trans. Inf. Syst. 93-D(7): 1816-1823 (2010)
The time complexity of the generator is in $O(n^3)$.
To check that the generator is uniform, we can use:
```py
def test(n, steps=1000):
from collections import Counter
C = Counter()
for _ in range(steps):
G = graphs.RandomProperIntervalGraph(n)
C[G.canonical_label().copy(immutable=True)] += 1
L = list(C.values())
import numpy
print(f"different graphs = {len(L)}, avg number = {numpy.mean(L)},
standard deviation = {numpy.std(L)}")
```
and we get
```py
sage: test(10, 100000)
different graphs = 2542, avg number = 39.33910306845004, standard
deviation = 7.640982640860865
sage: test(15, 100000)
different graphs = 96384, avg number = 1.0375166002656042, standard
deviation = 0.19487594733725658
sage: test(100, 100000)
different graphs = 100000, avg number = 1.0, standard deviation = 0.0
```
It seems that the generator is asymptotically uniform.
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- [x] The title is concise and informative.
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- [ ] I have linked a relevant issue or discussion.
- [x] I have created tests covering the changes.
- [x] I have updated the documentation and checked the documentation
preview.
### ⌛ Dependencies
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URL: #38354
Reported by: David Coudert
Reviewer(s): Frédéric Chapoton
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