treez
A collection of useful data structures
current implementations: segment tree, rb tree, autograd, indexed tree
work in progress: sarsa/mcts search
segment tree
implementation: array based
todo: generic type
notes: for static use after initialization
let mut segments = vec![];
for i in 0..10 {
let n = (i*5, 5*i+5, i); segments.push( n );
}
let t : treez::seg::TreeSeg = treez::seg::TreeSeg::init( segments.as_slice() );
let query_segs: HashSet<_> = t.get_segs_from_bound( (15,20) ).iter().cloned().collect();
let check: HashSet<_> = [ 2, 3, 4 ].iter().cloned().collect();
println!( "query segs: {:?}", query_segs );
assert!( check.intersection(&query_segs).count() == check.len() );
red black tree
implementation: array based, threshold compaction, minimal heap allocation
todo: optimize internal representation and operations, generic type
notes: comparable performance to BTreeMap
let mut t = treez::rb::TreeRb::new();
for i in 0..nums.len() {
let r = nums[i];
t.insert( r, i as isize );
}
for i in 0..nums.len() {
let r = nums[i];
let v = t.remove( &r ).expect( "remove unsuccessful" );
}
reverse automatic gradient differentiation
implementation: array based, scalar variable
todo: add more test coverage, tweek to more ergonomic interface, interval optimization
let mut c : autograd::Context = Default::default();
let mut buf = {
let mut x = autograd::init_var( & mut c, &[ 6f64 ] );
let mut y = autograd::init_var( & mut c, &[ 7f64, 3f64 ] );
let mut z = autograd::init_op( & mut c, autograd::OpType::Mul, & mut [ & mut x, & mut y ] );
let mut a = autograd::init_var( & mut c, &[ 3f64, 8f64 ] );
let mut b = autograd::init_op( & mut c, autograd::OpType::Add, & mut [ & mut z, & mut a ] );
vec![ x, y, z, a, b ]
};
let var_ids = autograd::fwd_pass( & mut c, & mut buf ).unwrap();
let mut var_map = HashMap::new();
for i in [ "x", "y", "z", "a", "b" ].iter().zip( var_ids ) {
var_map.insert( i.0, i.1 );
}
{
let mut var_grad = HashMap::new();
let b_id = *var_map.get(&"b").unwrap();
for i in var_map.iter() {
let grad = autograd::compute_grad( & mut c, b_id, *i.1 ).unwrap();
var_grad.insert( *i.0, grad );
}
assert_eq!( c.get_var(*var_map.get(&"x").unwrap()).unwrap()._val.len(), 2usize );
assert_eq!( c.get_var(*var_map.get(&"x").unwrap()).unwrap()._grad.len(), 2usize );
assert_eq!( c.get_var(*var_map.get(&"z").unwrap()).unwrap()._val, &[ 42f64, 18f64 ] );
assert_eq!( c.get_var(*var_map.get(&"x").unwrap()).unwrap()._val, &[ 6f64, 6f64 ] );
assert_eq!( c.get_var(*var_map.get(&"y").unwrap()).unwrap()._val, &[ 7f64, 3f64 ] );
assert_eq!( c.get_var(*var_map.get(&"b").unwrap()).unwrap()._val, &[ 45f64, 26f64 ] );
assert_eq!( c.get_var(*var_map.get(&"a").unwrap()).unwrap()._val, &[ 3f64, 8f64 ] );
assert_eq!( var_grad.get(&"z").unwrap(), &[ 1f64, 1f64 ] );
assert_eq!( var_grad.get(&"x").unwrap(), &[ 7f64, 3f64 ] );
assert_eq!( var_grad.get(&"y").unwrap(), &[ 6f64, 6f64 ] );
assert_eq!( var_grad.get(&"b").unwrap(), &[ 1f64, 1f64 ] );
assert_eq!( var_grad.get(&"a").unwrap(), &[ 1f64, 1f64 ] );
}
{
let z_id = *var_map.get(&"z").unwrap();
let a_id = *var_map.get(&"a").unwrap();
let grad = autograd::compute_grad( & mut c, z_id, a_id ).unwrap();
assert_eq!( &grad[..], &[ 0f64, 0f64 ] );
}
prefix sum tree
implementation: array based
todo: support generic commutative operation
let mut t = treez::prefix::TreePrefix::init(16);
t.set(0, 5);
t.set(1, 7);
t.set(10, 4);
assert_eq!( t.get_interval(0, 16), 16isize );
assert_eq!( t.get_interval(10, 11), 4isize );
assert_eq!( t.get_interval(1, 11), 11isize );
t.set(1, 9);
assert_eq!( t.get_interval(1, 2), 9isize );
assert_eq!( t.get_interval(1, 11), 13isize );
assert_eq!( t.get_interval_start( 2 ), 14isize );
assert_eq!( t.get_interval_start( 11 ), 18isize );
t.add( 0, 1);
assert_eq!( t.get_interval_start( 2 ), 15isize );
assert_eq!( t.get_interval_start( 11 ), 19isize );