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3x speedup of the distance transform. #28

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18 changes: 16 additions & 2 deletions benches/distance_transform.rs
Original file line number Diff line number Diff line change
Expand Up @@ -9,7 +9,21 @@ mod benches {

#[bench]
fn bench_chebyshev_distance_transform(b: &mut Bencher) {
let terrain = LocalRoomTerrain::new_from_bits(Box::new([0; 2500]));
b.iter(|| black_box(chebyshev_distance_transform_from_terrain(&terrain)));
let mut terrain = LocalRoomTerrain::new_from_bits(Box::new([0; 2500]));
b.iter(|| {
black_box(chebyshev_distance_transform_from_terrain(&*black_box(
&mut terrain,
)))
});
}

#[bench]
fn bench_manhattan_distance_transform(b: &mut Bencher) {
let mut terrain = LocalRoomTerrain::new_from_bits(Box::new([0; 2500]));
b.iter(|| {
black_box(manhattan_distance_transform_from_terrain(&*black_box(
&mut terrain,
)))
});
}
}
352 changes: 295 additions & 57 deletions src/algorithms/distance_transform.rs
Original file line number Diff line number Diff line change
@@ -1,11 +1,12 @@
// Heavily based on https://github.com/Screeps-Tutorials/Screeps-Tutorials/blob/Master/basePlanningAlgorithms/distanceTransform.js

use screeps::{
self,
constants::{extra::ROOM_SIZE, Direction},
local::{LocalCostMatrix, LocalRoomTerrain, RoomXY},
constants::extra::ROOM_SIZE,
local::{LocalCostMatrix, LocalRoomTerrain, RoomCoordinate, RoomXY},
};

use crate::room_coordinate::{range_exclusive, range_inclusive};

/// Provides a Cost Matrix with values equal to the Chebyshev distance from any
/// wall terrain. This does *not* calculate based on constructed walls, only
/// terrain walls.
Expand All @@ -29,67 +30,304 @@ pub fn chebyshev_distance_transform_from_terrain(
/// This allows for calculating the distance transform from an arbitrary set of
/// positions. Other position values in the initial Cost Matrix should be
/// initialized to 255 (u8::MAX) to ensure the calculations work correctly.
pub fn chebyshev_distance_transform_from_cost_matrix(
initial_cm: LocalCostMatrix,
pub fn chebyshev_distance_transform_from_cost_matrix(mut cm: LocalCostMatrix) -> LocalCostMatrix {
let zero = RoomCoordinate::new(0).unwrap();
let one = RoomCoordinate::new(1).unwrap();
let forty_eight = RoomCoordinate::new(ROOM_SIZE - 2).unwrap();
let forty_nine = RoomCoordinate::new(ROOM_SIZE - 1).unwrap();
// Pass 1: Top-to-Bottom, Left-to-Right

// Phase A: first column
range_inclusive(one, forty_nine)
.map(|y| RoomXY { x: zero, y })
.fold(cm.get(RoomXY { x: zero, y: zero }), |top, xy| {
let val = cm.get(xy).min(top.saturating_add(1));
cm.set(xy, val);
val
});

// Phase B: the rest
range_inclusive(one, forty_nine)
.zip(range_inclusive(zero, forty_eight))
.for_each(|(current_x, left_x)| {
let initial_top = cm
.get(RoomXY {
x: current_x,
y: zero,
})
.min(
cm.get(RoomXY { x: left_x, y: zero })
.min(cm.get(RoomXY { x: left_x, y: one }))
.saturating_add(1),
);
cm.set(
RoomXY {
x: current_x,
y: zero,
},
initial_top,
);
let final_top = range_exclusive(zero, forty_nine)
.map(|y| {
(RoomXY { x: current_x, y }, unsafe {
[
RoomCoordinate::unchecked_new(y.u8() - 1),
y,
RoomCoordinate::unchecked_new(y.u8() + 1),
]
})
})
.fold(initial_top, |top, (current_xy, lefts)| {
let val = lefts
.into_iter()
.map(|y| RoomXY { x: left_x, y })
.map(|xy| cm.get(xy))
.min()
.unwrap()
.min(top)
.saturating_add(1)
.min(cm.get(current_xy));
cm.set(current_xy, val);
val
});
cm.set(
RoomXY {
x: current_x,
y: forty_nine,
},
cm.get(RoomXY {
x: current_x,
y: forty_nine,
})
.min(
final_top
.min(cm.get(RoomXY {
x: left_x,
y: forty_eight,
}))
.min(cm.get(RoomXY {
x: left_x,
y: forty_nine,
}))
.saturating_add(1),
),
);
});

// Pass 2: Bottom-to-Top, Right-to-Left

// Phase A: last column
range_inclusive(zero, forty_eight)
.map(|y| RoomXY { x: forty_nine, y })
.rfold(
cm.get(RoomXY {
x: forty_nine,
y: forty_nine,
}),
|bottom, xy| {
let val = cm.get(xy).min(bottom.saturating_add(1));
cm.set(xy, val);
val
},
);

// Phase B: the rest
range_inclusive(zero, forty_eight)
.rev()
.zip(range_inclusive(one, forty_nine).rev())
.for_each(|(current_x, right_x)| {
let initial_bottom = cm
.get(RoomXY {
x: current_x,
y: forty_nine,
})
.min(
cm.get(RoomXY {
x: right_x,
y: forty_nine,
})
.min(cm.get(RoomXY {
x: right_x,
y: forty_eight,
}))
.saturating_add(1),
);
cm.set(
RoomXY {
x: current_x,
y: forty_nine,
},
initial_bottom,
);
let final_bottom = range_exclusive(zero, forty_nine)
.map(|y| {
(RoomXY { x: current_x, y }, unsafe {
[
RoomCoordinate::unchecked_new(y.u8() - 1),
y,
RoomCoordinate::unchecked_new(y.u8() + 1),
]
})
})
.rfold(initial_bottom, |bottom, (current_xy, rights)| {
let val = rights
.into_iter()
.map(|y| RoomXY { x: right_x, y })
.map(|xy| cm.get(xy))
.min()
.unwrap()
.min(bottom)
.saturating_add(1)
.min(cm.get(current_xy));
cm.set(current_xy, val);
val
});
cm.set(
RoomXY {
x: current_x,
y: zero,
},
cm.get(RoomXY {
x: current_x,
y: zero,
})
.min(
final_bottom
.min(cm.get(RoomXY {
x: right_x,
y: zero,
}))
.min(cm.get(RoomXY { x: right_x, y: one }))
.saturating_add(1),
),
);
});

cm
}

/// Provides a Cost Matrix with values equal to the Manhattan distance from any
/// wall terrain. This does *not* calculate based on constructed walls, only
/// terrain walls.
pub fn manhattan_distance_transform_from_terrain(
room_terrain: &LocalRoomTerrain,
) -> LocalCostMatrix {
// Copy the initial cost matrix into the output cost matrix
let mut cm = initial_cm.clone();
Comment on lines -35 to -36
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We actually never needed this clone, since we get the cost-matrix by value; the old owner can't do anything with it.

let mut initial_cm = LocalCostMatrix::new();

for (xy, cm_val) in initial_cm.iter_mut() {
*cm_val = match room_terrain.get_xy(xy) {
screeps::constants::Terrain::Wall => 0,
_ => u8::MAX,
};
}
manhattan_distance_transform_from_cost_matrix(initial_cm)
}

/// Provides a Cost Matrix with values equal to the Manhattan distance from any
/// position in the provided initial Cost Matrix with a value set to 0.
///
/// This allows for calculating the distance transform from an arbitrary set of
/// positions. Other position values in the initial Cost Matrix should be
/// initialized to 255 (u8::MAX) to ensure the calculations work correctly.
pub fn manhattan_distance_transform_from_cost_matrix(mut cm: LocalCostMatrix) -> LocalCostMatrix {
let zero = RoomCoordinate::new(0).unwrap();
let one = RoomCoordinate::new(1).unwrap();
let forty_eight = RoomCoordinate::new(ROOM_SIZE - 2).unwrap();
let forty_nine = RoomCoordinate::new(ROOM_SIZE - 1).unwrap();
// Pass 1: Top-to-Bottom, Left-to-Right

for x in 0..ROOM_SIZE {
for y in 0..ROOM_SIZE {
let current_position = unsafe { RoomXY::unchecked_new(x, y) };

// The distance to the closest wall is the minimum of the current position value
// and all of its neighbors. However, since we're going TTB:LTR, we
// can ignore tiles we know we haven't visited yet: TopRight, Right,
// BottomRight, and Bottom. We could include them and their default
// max values should get ignored, but why waste the processing cycles?
let min_value = [
Direction::Top,
Direction::TopLeft,
Direction::Left,
Direction::BottomLeft,
]
.into_iter()
.filter_map(|dir| current_position.checked_add_direction(dir))
.map(|position| cm.get(position))
.min()
.map(|x| x.saturating_add(1))
.map(|x| x.min(cm.get(current_position)))
.unwrap_or_else(|| cm.get(current_position));

cm.set(current_position, min_value);
}
}
// Phase A: first column
range_inclusive(one, forty_nine)
.map(|y| RoomXY { x: zero, y })
.fold(cm.get(RoomXY { x: zero, y: zero }), |top, xy| {
let val = cm.get(xy).min(top.saturating_add(1));
cm.set(xy, val);
val
});

// Phase B: the rest
range_inclusive(one, forty_nine)
.zip(range_inclusive(zero, forty_eight))
.for_each(|(current_x, left_x)| {
let initial_top = cm
.get(RoomXY {
x: current_x,
y: zero,
})
.min(cm.get(RoomXY { x: left_x, y: zero }).saturating_add(1));
cm.set(
RoomXY {
x: current_x,
y: zero,
},
initial_top,
);
range_inclusive(one, forty_nine)
.map(|y| (RoomXY { x: current_x, y }, RoomXY { x: left_x, y }))
.fold(initial_top, |top, (current_xy, left_xy)| {
let val = cm
.get(left_xy)
.min(top)
.saturating_add(1)
.min(cm.get(current_xy));
cm.set(current_xy, val);
val
});
});

// Pass 2: Bottom-to-Top, Right-to-Left

for x in (0..ROOM_SIZE).rev() {
for y in (0..ROOM_SIZE).rev() {
let current_position = unsafe { RoomXY::unchecked_new(x, y) };

// The same logic as with Pass 1 applies here, we're just going BTT:RTL instead,
// so the neighbors we ignore are: BottomLeft, Left, TopLeft, and
// Top.
let min_value = [
Direction::Bottom,
Direction::Right,
Direction::BottomRight,
Direction::TopRight,
]
.into_iter()
.filter_map(|dir| current_position.checked_add_direction(dir))
.map(|position| cm.get(position))
.min()
.map(|x| x.saturating_add(1))
.map(|x| x.min(cm.get(current_position)))
.unwrap_or_else(|| cm.get(current_position));

cm.set(current_position, min_value);
}
}
// Phase A: last column
range_inclusive(zero, forty_eight)
.map(|y| RoomXY { x: forty_nine, y })
.rfold(
cm.get(RoomXY {
x: forty_nine,
y: forty_nine,
}),
|bottom, xy| {
let val = cm.get(xy).min(bottom.saturating_add(1));
cm.set(xy, val);
val
},
);

// Phase B: the rest
range_inclusive(zero, forty_eight)
.rev()
.zip(range_inclusive(one, forty_nine).rev())
.for_each(|(current_x, right_x)| {
let initial_bottom = cm
.get(RoomXY {
x: current_x,
y: forty_nine,
})
.min(
cm.get(RoomXY {
x: right_x,
y: forty_nine,
})
.saturating_add(1),
);
cm.set(
RoomXY {
x: current_x,
y: forty_nine,
},
initial_bottom,
);
range_inclusive(zero, forty_eight)
.map(|y| (RoomXY { x: current_x, y }, RoomXY { x: right_x, y }))
.rfold(initial_bottom, |bottom, (current_xy, right_xy)| {
let val = cm
.get(right_xy)
.min(bottom)
.saturating_add(1)
.min(cm.get(current_xy));
cm.set(current_xy, val);
val
});
});

cm
}