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elynx-tree-0.2.2: src/ELynx/Simulate/PointProcess.hs

{-# LANGUAGE BangPatterns #-}

{- |
   Module      :  ELynx.Simulate.PointProcess
   Description :  Point process and functions
   Copyright   :  (c) Dominik Schrempf 2018
   License     :  GPL-3.0-or-later

   Maintainer  :  dominik.schrempf@gmail.com
   Stability   :  unstable
   Portability :  portable

Creation date: Tue Feb 13 13:16:18 2018.

See Gernhard, T. (2008). The conditioned reconstructed process. Journal of
Theoretical Biology, 253(4), 769–778. http://doi.org/10.1016/j.jtbi.2008.04.005.

The point process can be used to simulate reconstructed trees under the birth
and death process.

-}

module ELynx.Simulate.PointProcess
  ( PointProcess(..)
  , TimeSpec
  , simulate
  , toReconstructedTree
  , simulateReconstructedTree
  , simulateNReconstructedTrees
  )
where

import           Control.Monad
import           Control.Monad.Primitive
import           Data.List                      ( mapAccumL )
import           Data.Tree
import qualified Statistics.Distribution       as D
                                                ( genContVar )
import           System.Random.MWC

import           ELynx.Data.Tree
import           ELynx.Distribution.BirthDeath
import           ELynx.Distribution.BirthDeathCritical
import           ELynx.Distribution.BirthDeathCriticalNoTime
import           ELynx.Distribution.BirthDeathNearlyCritical
import           ELynx.Distribution.TimeOfOrigin
import           ELynx.Distribution.TimeOfOriginNearCritical
import           ELynx.Distribution.Types
import           ELynx.Tools

epsNearCriticalPointProcess :: Double
epsNearCriticalPointProcess = 1e-5

epsNearCriticalTimeOfOrigin :: Double
epsNearCriticalTimeOfOrigin = 1e-8

-- | A __point process__ for \(n\) points and of age \(t_{or}\) is defined as
-- follows. Draw $n$ points on the horizontal axis at \(1,2,\ldots,n\). Pick
-- \(n-1\) points at locations \((i+1/2, s_i)\), \(i=1,2,\ldots,n-1\);
-- \(0 < s_i < t_{or}\). There is a bijection between (ranked) oriented trees
-- and the point process. Usually, a will be 'String' (or 'Int') and b will be
-- 'Double'.
data PointProcess a b = PointProcess
  { points :: ![a]
  , values :: ![b]
  , origin :: !b } deriving (Read, Show, Eq)

-- | If nothing, sample time of origin from respective distribution. If time is
-- given, we need to know if we condition on the time of origin, or the time of
-- the most recent common ancestor (MRCA).
type TimeSpec = Maybe (Time, Bool)

-- | Sample a point process using the 'BirthDeathDistribution'. The names of the
-- points will be integers.
simulate
  :: (PrimMonad m)
  => Int        -- ^ Number of points (samples)
  -> TimeSpec   -- ^ Time of origin or MRCA
  -> Rate       -- ^ Birth rate
  -> Rate       -- ^ Death rate
  -> Gen (PrimState m)   -- ^ Generator (see 'System.Random.MWC')
  -> m (PointProcess Int Double)
-- No time of origin given. We also don't need to take care of the conditioning
-- (origin or MRCA).
simulate n Nothing l m g
  |
  -- XXX. There is no formula for the over-critical process.
    m > l
  = error
    "Time of origin distribution formula not available when mu > lambda. Please specify height for the moment."
  |
  -- For the critical process, we have no idea about the time of origin, but can
  -- use a specially derived distribution.
    m =~= l
  = do
    !vs <- replicateM (n - 1) (D.genContVar (BDCNTD l) g)
    -- XXX: The length of the root branch will be 0.
    let t = maximum vs
    return $ PointProcess [0 .. (n - 1)] vs t
  |
  -- For the near critical process, we use a special distribution.
    abs (m - l) <= epsNearCriticalTimeOfOrigin
  = do
    t <- D.genContVar (TONCD n l m) g
    simulate n (Just (t, False)) l m g
  |
  -- For a sub-critical branching process, we can use the formula from Tanja Stadler.
    otherwise
  = do
    t <- D.genContVar (TOD n l m) g
    simulate n (Just (t, False)) l m g
-- Time of origin is given.
simulate n (Just (t, c)) l m g
  | n < 1 = error "Number of samples needs to be one or larger."
  | t < 0.0 = error "Time of origin needs to be positive."
  | l < 0.0 = error "Birth rate needs to be positive."
  |
  -- See Stadler, T., & Steel, M. (2019). Swapping birth and death: symmetries
  -- and transformations in phylodynamic models. , (), .
  -- http://dx.doi.org/10.1101/494583. Should be possible now.
  -- -- | m < 0.0   = error "Death rate needs to be positive."
  -- Now, we have three different cases.
  -- 1. The critical branching process.
  -- 2. The near critical branching process.
  -- 3. Normal values :).
    (m =~= l) && not c = do
    !vs <- replicateM (n - 1) (D.genContVar (BDCD t l) g)
    return $ PointProcess [0 .. (n - 1)] vs t
  | (abs (m - l) <= epsNearCriticalPointProcess) && not c = do
    !vs <- replicateM (n - 1) (D.genContVar (BDNCD t l m) g)
    return $ PointProcess [0 .. (n - 1)] vs t
  | not c = do
    !vs <- replicateM (n - 1) (D.genContVar (BDD t l m) g)
    return $ PointProcess [0 .. (n - 1)] vs t
  | (m =~= l) && c = do
    !vs <- replicateM (n - 2) (D.genContVar (BDCD t l) g)
    vs' <- randomInsertList t vs g
    return $ PointProcess [0 .. (n - 1)] vs' t
  | (abs (m - l) <= epsNearCriticalPointProcess) && c = do
    !vs <- replicateM (n - 2) (D.genContVar (BDNCD t l m) g)
    vs' <- randomInsertList t vs g
    return $ PointProcess [0 .. (n - 1)] vs' t
  | c = do
    !vs <- replicateM (n - 2) (D.genContVar (BDD t l m) g)
    vs' <- randomInsertList t vs g
    return $ PointProcess [0 .. (n - 1)] vs' t
  | otherwise = error "simulate: Fell through guard, this should never happen."

-- | Sort the values of a point process and their indices to be (the indices
-- that they will have while creating the tree).
sort :: (Ord b) => PointProcess a b -> ([b], [Int])
sort (PointProcess _ vs _) = (vsSorted, isSorted)
 where
  vsIsSorted = sortListWithIndices vs
  vsSorted   = map fst vsIsSorted
  isSorted   = flattenIndices $ map snd vsIsSorted

-- Decrement indices that are above the one that is merged.
flattenIndices :: [Int] -> [Int]
flattenIndices is = snd $ mapAccumL fAcc [] is

-- The accumulating function. Count the number of indices which are before the
-- current index and lower than the current index.
fAcc :: [Int] -> Int -> ([Int], Int)
fAcc is i = (i : is, i') where i' = i - length (filter (< i) is)

-- | See 'simulateReconstructedTree', but n times.
simulateNReconstructedTrees
  :: (PrimMonad m)
  => Int        -- ^ Number of trees
  -> Int        -- ^ Number of points (samples)
  -> TimeSpec   -- ^ Time of origin or MRCA
  -> Rate       -- ^ Birth rate
  -> Rate       -- ^ Death rate
  -> Gen (PrimState m)   -- ^ Generator (see 'System.Random.MWC')
  -> m [Tree (PhyloLabel Int)]
simulateNReconstructedTrees nT nP t l m g
  | nT <= 0   = return []
  | otherwise = replicateM nT $ simulateReconstructedTree nP t l m g

-- | Use the point process to simulate a reconstructed tree (see
-- 'toReconstructedTree') possibly with specific height and a fixed number of
-- leaves according to the birth and death process.
simulateReconstructedTree
  :: (PrimMonad m)
  => Int        -- ^ Number of points (samples)
  -> TimeSpec   -- ^ Time of origin or MRCA
  -> Rate       -- ^ Birth rate
  -> Rate       -- ^ Death rate
  -> Gen (PrimState m)   -- ^ Generator (see 'System.Random.MWC')
  -> m (Tree (PhyloLabel Int))
simulateReconstructedTree n t l m g =
  toReconstructedTree 0 <$> simulate n t l m g

-- | Convert a point process to a reconstructed tree. See Lemma 2.2.

-- Of course, I decided to only use one tree structure with extinct and extant
-- leaves (actually a complete tree). So a tree created here just does not
-- contain extinct leaves. A function 'isReconstructed' is provided to test if a
-- tree is reconstructed (and not complete) in this sense. However, a complete
-- tree might show up as "reconstructed", just because, by chance, it does not
-- contain extinct leaves. I wanted to use a Monoid constraint to get the unit
-- element, but this fails for classical 'Int's. So, I rather have another
-- (useless) argument.
toReconstructedTree
  :: a                      -- Default node label.
  -> PointProcess a Double
  -> Tree (PhyloLabel a)
toReconstructedTree l pp@(PointProcess ps vs o)
  | length ps /= length vs + 1 = error "Too few or too many points."
  | length vs <= 1             = error "Too few values."
  |
  -- -- XXX: Test is deactivated.
  -- -- | otherwise = if isReconstructed treeOrigin then treeOrigin else error "Error in algorithm."
    otherwise                  = treeOrigin
 where
  (vsSorted, isSorted) = sort pp
  !lvs                 = [ singleton (PhyloLabel p Nothing Nothing) | p <- ps ]
  !heights             = replicate (length ps) 0
  !treeRoot            = toReconstructedTree' isSorted vsSorted l lvs heights
  !h                   = last vsSorted
  !treeOrigin          = lengthenStem (o - h) treeRoot

-- Move up the tree, connect nodes when they join according to the point process.
toReconstructedTree'
  :: [Int]                 -- Sorted indices, see 'sort'.
  -> [Double]              -- Sorted merge values.
  -> a                     -- Default node label.
  -> [Tree (PhyloLabel a)] -- Leaves with accumulated root branch lengths.
  -> [Double]              -- Accumulated heights of the leaves.
  -> Tree (PhyloLabel a)
toReconstructedTree' [] [] _ trs _  = head trs
toReconstructedTree' is vs l trs hs = toReconstructedTree' is' vs' l trs'' hs'
  -- For the algorithm, see 'ELynx.Coalescent.simulate', but index starts
  -- at zero.
 where
  !i     = head is
  !is'   = tail is
  !v     = head vs
  !vs'   = tail vs
  -- Left: l, right: r.
  !hl    = hs !! i
  !hr    = hs !! (i + 1)
  !dvl   = v - hl
  !dvr   = v - hr
  !tl    = lengthenStem dvl $ trs !! i
  !tr    = lengthenStem dvr $ trs !! (i + 1)
  !h'    = hl + dvl       -- Should be the same as 'hr + dvr'.
  !tm    = Node (PhyloLabel l Nothing Nothing) [tl, tr]
  !trs'' = take i trs ++ [tm] ++ drop (i + 2) trs
  !hs'   = take i hs ++ [h'] ++ drop (i + 2) hs