Uniformly random selection of unlabelled rooted trees.
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#include <rand_ulab_rooted_trees.hpp>
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std::pair< uint64_t, uint64_t > | ranrut (const uint64_t n, const uint64_t lr, uint64_t nt) noexcept |
| Generates uniformly at random a rooted unlabelled tree of n nodes.
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void | init_rn () noexcept |
| Initialiases m_rn with values from the OEIS (see [45]).
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const numeric::integer & | get_rn (const uint64_t n) noexcept |
| Computes all the values \(t_i\) for \(i \in [1,n]\).
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bool | has_rn (const uint64_t n) const noexcept |
| Returns whether or not the value \(r_n\) (m_rn) has been computed.
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std::pair< uint64_t, uint64_t > | choose_jd_from_T (const uint64_t n) noexcept |
| Chooses uniformly at random a pair \((j,d)\), according to some probability.
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uint64_t | m_n |
| Number of nodes of the tree.
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std::mt19937 | m_gen |
| Random number generator.
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std::uniform_real_distribution< double > | m_unif |
| Distribution of the numbers.
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std::vector< numeric::integer > | m_rn |
| The number of unlabelled rooted trees.
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std::vector< numeric::integer > | m_rn_times_n |
| The number of unlabelled rooted trees times number of vertices.
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std::vector< numeric::integer > | m_rn_times_n_minus_1 |
| The number of unlabelled rooted trees times number of vertices minus 1.
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head_vector | m_head_vector |
| The head vector of the tree under construction.
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Uniformly random selection of unlabelled rooted trees.
Users should refrain from using this class. The generation of random labelled trees should be done using the wrapper class rand_ulab_rooted_trees. This class, however, contains the actual code to generate labelled rooted trees uniformly at random.
Every call to get_tree generates rooted unlabelled trees uniformly at random using the ranrut procedure (see [38], chapter 29).
◆ _rand_ulab_rooted_trees() [1/3]
lal::generate::_rand_ulab_rooted_trees::_rand_ulab_rooted_trees |
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const uint64_t | n, |
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const uint64_t | seed = 0 ) |
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inlinenoexcept |
Constructor with size of tree and seed for the random number generator.
In case the seed given is '0', a random seed will be generated.
- Parameters
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n | Number of nodes. |
seed | The seed used for the random number generator. If the seed is 0 then a random seed is generated and used. |
◆ _rand_ulab_rooted_trees() [2/3]
Copy constructor.
- Parameters
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Gen | Random unlabelled rooted tree generator. |
◆ _rand_ulab_rooted_trees() [3/3]
Move constructor.
- Parameters
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Gen | Random unlabelled rooted tree generator. |
◆ choose_jd_from_T()
std::pair< uint64_t, uint64_t > lal::generate::_rand_ulab_rooted_trees::choose_jd_from_T |
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const uint64_t | n | ) |
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nodiscardprotectednoexcept |
Chooses uniformly at random a pair \((j,d)\), according to some probability.
Probability of choosing \((j,d)\) is: \(\frac{d \cdot t_{k - jd} \cdot t_d}{(k - 1)t_k}\).
- Parameters
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- Returns
- A pair of integers \((j,d)\) such that \(j \ge 1\), \(jd \le n\) and \(j \ge 1\), \(jd \le n\).
◆ clear()
void lal::generate::_rand_ulab_rooted_trees::clear |
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inlinenoexcept |
Clears the memory used.
In order to save computation time, this class has been designed to reuse memory when generating trees. For example, since it needs the values of well-known integer sequences (see attribute m_rn) that are costly to compute every time they are needed, they are stored in memory and reused over time.
So, if the user wants to generate trees of 1000 nodes there will be too much memory occupied (and unused) if then this class is used to generate trees of 10 nodes. In cases like this it is recommended to clear the memory occupied.
- Postcondition
- After calling this method, the contents of the attributes m_rn are cleared. Attribute m_rn is then assigned the same values that it is assigned when creating an object of this class.
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Method init must be called after every call to clear.
◆ get_rn()
const numeric::integer & lal::generate::_rand_ulab_rooted_trees::get_rn |
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const uint64_t | n | ) |
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nodiscardprotectednoexcept |
Computes all the values \(t_i\) for \(i \in [1,n]\).
Here \(n\) is m_n. In case these values have already been calculated, this method does nothing.
◆ get_tree()
Generates uniformly at random a free unlabelled tree.
- Returns
- An unlabelled rooted tree. The tree is rooted at vertex 0.
◆ init()
void lal::generate::_rand_ulab_rooted_trees::init |
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const uint64_t | n, |
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const uint64_t | seed = 0 ) |
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inlinenoexcept |
Sets the size of the unlabelled trees to generate.
Adds the remaining necessary values to m_rn..
Initializes the random number generator with seed. When seed is 0, a random seed is used.
- Parameters
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n | Number of vertices. |
seed | Integer value used to seed the random number generator. |
◆ ranrut()
std::pair< uint64_t, uint64_t > lal::generate::_rand_ulab_rooted_trees::ranrut |
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const uint64_t | n, |
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const uint64_t | lr, |
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uint64_t | nt ) |
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nodiscardprotectednoexcept |
Generates uniformly at random a rooted unlabelled tree of n nodes.
The first call to this method should have lr = m_n + 1.
- Parameters
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n | Number of nodes of the rooted tree to generate. |
lr | Pointer to the root of the last tree added. m_head_vector[lr] is the node that the root points to. |
nt | Index to m_head_vector where we have to place the new tree. |
- Returns
- Two indices: the index of the root of the last tree generated and where to store the next tree in m_head_vector.
◆ m_head_vector
head_vector lal::generate::_rand_ulab_rooted_trees::m_head_vector |
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The head vector of the tree under construction.
The first position always contains the root vertex. The parent of vertex u is located at m_head_vector[u], but the value is an index from 0 to \(n - 1\), both included.
◆ m_rn
The number of unlabelled rooted trees.
Contains \(r_n\) for \(n\ge 0\).
◆ m_rn_times_n
std::vector<numeric::integer> lal::generate::_rand_ulab_rooted_trees::m_rn_times_n |
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The number of unlabelled rooted trees times number of vertices.
Contains \(r_n \cdot n\) for \(n\ge 0\).
◆ m_rn_times_n_minus_1
std::vector<numeric::integer> lal::generate::_rand_ulab_rooted_trees::m_rn_times_n_minus_1 |
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The number of unlabelled rooted trees times number of vertices minus 1.
Contains \(r_n \cdot (n - 1)\) for \(n\ge 0\).
The documentation for this class was generated from the following file: