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//////////////////////////////////////////////////////////////////////
// LibFile: vectors.scad
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// This file provides some mathematical operations that apply to each
// entry in a vector. It provides normalizatoin and angle computation, and
// it provides functions for searching lists of vectors for matches to
// a given vector.
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// Includes:
// include <BOSL2/std.scad>
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// FileGroup: Math
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// FileSummary: Vector arithmetic, angle, and searching.
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// FileFootnotes: STD=Included in std.scad
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//////////////////////////////////////////////////////////////////////
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// Section: Vector Testing
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// Function: is_vector()
// Usage:
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// is_vector(v, [length], ...);
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// Description:
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// Returns true if v is a list of finite numbers.
// Arguments:
// v = The value to test to see if it is a vector.
// length = If given, make sure the vector is `length` items long.
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// zero = If false, require that the length/`norm()` of the vector is not approximately zero. If true, require the length/`norm()` of the vector to be approximately zero-length. Default: `undef` (don't check vector length/`norm()`.)
// all_nonzero = If true, requires all elements of the vector to be more than `eps` different from zero. Default: `false`
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// eps = The minimum vector length that is considered non-zero. Default: `EPSILON` (`1e-9`)
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// Example:
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// is_vector(4); // Returns false
// is_vector([4,true,false]); // Returns false
// is_vector([3,4,INF,5]); // Returns false
// is_vector([3,4,5,6]); // Returns true
// is_vector([3,4,undef,5]); // Returns false
// is_vector([3,4,5],3); // Returns true
// is_vector([3,4,5],4); // Returns true
// is_vector([]); // Returns false
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// is_vector([0,4,0],3,zero=false); // Returns true
// is_vector([0,0,0],zero=false); // Returns false
// is_vector([0,0,1e-12],zero=false); // Returns false
// is_vector([0,1,0],all_nonzero=false); // Returns false
// is_vector([1,1,1],all_nonzero=false); // Returns true
// is_vector([],zero=false); // Returns false
function is_vector ( v , length , zero , all_nonzero = false , eps = EPSILON ) =
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is_list ( v ) && len ( v ) > 0 && [ ] = = [ for ( vi = v ) if ( ! is_num ( vi ) ) 0 ]
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&& ( is_undef ( length ) || len ( v ) = = length )
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&& ( is_undef ( zero ) || ( ( norm ( v ) >= eps ) = = ! zero ) )
&& ( ! all_nonzero || all_nonzero ( v ) ) ;
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// Section: Scalar operations on vectors
// Function: add_scalar()
// Usage:
// v_new = add_scalar(v, s);
// Topics: List Handling
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// Description:
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// Given a vector and a scalar, returns the vector with the scalar added to each item in it.
// Arguments:
// v = The initial array.
// s = A scalar value to add to every item in the array.
// Example:
// a = add_scalar([1,2,3],3); // Returns: [4,5,6]
function add_scalar ( v , s ) =
assert ( is_vector ( v ) , "Input v must be a vector" )
assert ( is_finite ( s ) , "Input s must be a finite scalar" )
[ for ( entry = v ) entry + s ] ;
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// Function: v_mul()
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// Usage:
// v3 = v_mul(v1, v2);
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// Description:
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// Element-wise multiplication. Multiplies each element of `v1` by the corresponding element of `v2`.
// Both `v1` and `v2` must be the same length. Returns a vector of the products.
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// Arguments:
// v1 = The first vector.
// v2 = The second vector.
// Example:
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// v_mul([3,4,5], [8,7,6]); // Returns [24, 28, 30]
function v_mul ( v1 , v2 ) =
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assert ( is_list ( v1 ) && is_list ( v2 ) && len ( v1 ) = = len ( v2 ) , "Incompatible input" )
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[ for ( i = [ 0 : 1 : len ( v1 ) - 1 ] ) v1 [ i ] * v2 [ i ] ] ;
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// Function: v_div()
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// Usage:
// v3 = v_div(v1, v2);
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// Description:
// Element-wise vector division. Divides each element of vector `v1` by
// the corresponding element of vector `v2`. Returns a vector of the quotients.
// Arguments:
// v1 = The first vector.
// v2 = The second vector.
// Example:
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// v_div([24,28,30], [8,7,6]); // Returns [3, 4, 5]
function v_div ( v1 , v2 ) =
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assert ( is_vector ( v1 ) && is_vector ( v2 , len ( v1 ) ) , "Incompatible vectors" )
[ for ( i = [ 0 : 1 : len ( v1 ) - 1 ] ) v1 [ i ] / v2 [ i ] ] ;
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// Function: v_abs()
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// Usage:
// v2 = v_abs(v);
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// Description: Returns a vector of the absolute value of each element of vector `v`.
// Arguments:
// v = The vector to get the absolute values of.
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// Example:
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// v_abs([-1,3,-9]); // Returns: [1,3,9]
function v_abs ( v ) =
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assert ( is_vector ( v ) , "Invalid vector" )
[ for ( x = v ) abs ( x ) ] ;
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// Function: v_floor()
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// Usage:
// v2 = v_floor(v);
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// Description:
// Returns the given vector after performing a `floor()` on all items.
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function v_floor ( v ) =
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assert ( is_vector ( v ) , "Invalid vector" )
[ for ( x = v ) floor ( x ) ] ;
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// Function: v_ceil()
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// Usage:
// v2 = v_ceil(v);
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// Description:
// Returns the given vector after performing a `ceil()` on all items.
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function v_ceil ( v ) =
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assert ( is_vector ( v ) , "Invalid vector" )
[ for ( x = v ) ceil ( x ) ] ;
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// Function: v_lookup()
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// Usage:
// v2 = v_ceil(x, v);
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// Description:
// Works just like the built-in function [`lookup()`](https://en.wikibooks.org/wiki/OpenSCAD_User_Manual/Mathematical_Functions#lookup), except that it can also interpolate between vector result values of the same length.
// Arguments:
// x = The scalar value to look up.
// v = A list of [KEY,VAL] pairs. KEYs are scalars. VALs should either all be scalar, or all be vectors of the same length.
// Example:
// x = v_lookup(4.5, [[4, [3,4,5]], [5, [5,6,7]]]); // Returns: [4,5,6]
function v_lookup ( x , v ) =
is_num ( v [ 0 ] [ 1 ] ) ? lookup ( x , v ) :
let (
i = lookup ( x , [ for ( i = idx ( v ) ) [ v [ i ] . x , i ] ] ) ,
vlo = v [ floor ( i ) ] ,
vhi = v [ ceil ( i ) ] ,
lo = vlo [ 1 ] ,
hi = vhi [ 1 ]
)
assert ( is_vector ( lo ) && is_vector ( hi ) ,
"Result values must all be numbers, or all be vectors." )
assert ( len ( lo ) = = len ( hi ) , "Vector result values must be the same length" )
vlo . x = = vhi . x ? vlo [ 1 ] :
let ( u = ( x - vlo . x ) / ( vhi . x - vlo . x ) )
lerp ( lo , hi , u ) ;
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// Section: Vector Properties
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// Function: unit()
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// Usage:
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// v = unit(v, [error]);
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// Description:
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// Returns the unit length normalized version of vector v. If passed a zero-length vector,
// asserts an error unless `error` is given, in which case the value of `error` is returned.
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// Arguments:
// v = The vector to normalize.
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// error = If given, and input is a zero-length vector, this value is returned. Default: Assert error on zero-length vector.
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// Example:
// v1 = unit([10,0,0]); // Returns: [1,0,0]
// v2 = unit([0,10,0]); // Returns: [0,1,0]
// v3 = unit([0,0,10]); // Returns: [0,0,1]
// v4 = unit([0,-10,0]); // Returns: [0,-1,0]
// v5 = unit([0,0,0],[1,2,3]); // Returns: [1,2,3]
// v6 = unit([0,0,0]); // Asserts an error.
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function unit ( v , error = [ [ [ "ASSERT" ] ] ] ) =
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assert ( is_vector ( v ) , "Invalid vector" )
norm ( v ) < EPSILON ? ( error = = [ [ [ "ASSERT" ] ] ] ? assert ( norm ( v ) >= EPSILON , "Cannot normalize a zero vector" ) : error ) :
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v / norm ( v ) ;
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// Function: v_theta()
// Usage:
// theta = v_theta([X,Y]);
// Description:
// Given a vector, returns the angle in degrees counter-clockwise from X+ on the XY plane.
function v_theta ( v ) =
assert ( is_vector ( v , 2 ) || is_vector ( v , 3 ) , "Invalid vector" )
atan2 ( v . y , v . x ) ;
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// Function: vector_angle()
// Usage:
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// ang = vector_angle(v1,v2);
// ang = vector_angle([v1,v2]);
// ang = vector_angle(PT1,PT2,PT3);
// ang = vector_angle([PT1,PT2,PT3]);
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// Description:
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// If given a single list of two vectors, like `vector_angle([V1,V2])`, returns the angle between the two vectors V1 and V2.
// If given a single list of three points, like `vector_angle([A,B,C])`, returns the angle between the line segments AB and BC.
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// If given two vectors, like `vector_angle(V1,V2)`, returns the angle between the two vectors V1 and V2.
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// If given three points, like `vector_angle(A,B,C)`, returns the angle between the line segments AB and BC.
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// Arguments:
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// v1 = First vector or point.
// v2 = Second vector or point.
// v3 = Third point in three point mode.
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// Example:
// ang1 = vector_angle(UP,LEFT); // Returns: 90
// ang2 = vector_angle(RIGHT,LEFT); // Returns: 180
// ang3 = vector_angle(UP+RIGHT,RIGHT); // Returns: 45
// ang4 = vector_angle([10,10], [0,0], [10,-10]); // Returns: 90
// ang5 = vector_angle([10,0,10], [0,0,0], [-10,10,0]); // Returns: 120
// ang6 = vector_angle([[10,0,10], [0,0,0], [-10,10,0]]); // Returns: 120
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function vector_angle ( v1 , v2 , v3 ) =
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assert ( ( is_undef ( v3 ) && ( is_undef ( v2 ) || same_shape ( v1 , v2 ) ) )
|| is_consistent ( [ v1 , v2 , v3 ] ) ,
"Bad arguments." )
assert ( is_vector ( v1 ) || is_consistent ( v1 ) , "Bad arguments." )
let ( vecs = ! is_undef ( v3 ) ? [ v1 - v2 , v3 - v2 ] :
! is_undef ( v2 ) ? [ v1 , v2 ] :
len ( v1 ) = = 3 ? [ v1 [ 0 ] - v1 [ 1 ] , v1 [ 2 ] - v1 [ 1 ] ]
: v1
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)
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assert ( is_vector ( vecs [ 0 ] , 2 ) || is_vector ( vecs [ 0 ] , 3 ) , "Bad arguments." )
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let (
norm0 = norm ( vecs [ 0 ] ) ,
norm1 = norm ( vecs [ 1 ] )
)
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assert ( norm0 > 0 && norm1 > 0 , "Zero length vector." )
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// NOTE: constrain() corrects crazy FP rounding errors that exceed acos()'s domain.
acos ( constrain ( ( vecs [ 0 ] * vecs [ 1 ] ) / ( norm0 * norm1 ) , - 1 , 1 ) ) ;
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// Function: vector_axis()
// Usage:
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// axis = vector_axis(v1,v2);
// axis = vector_axis([v1,v2]);
// axis = vector_axis(PT1,PT2,PT3);
// axis = vector_axis([PT1,PT2,PT3]);
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// Description:
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// If given a single list of two vectors, like `vector_axis([V1,V2])`, returns the vector perpendicular the two vectors V1 and V2.
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// If given a single list of three points, like `vector_axis([A,B,C])`, returns the vector perpendicular to the plane through a, B and C.
// If given two vectors, like `vector_axis(V1,V2)`, returns the vector perpendicular to the two vectors V1 and V2.
// If given three points, like `vector_axis(A,B,C)`, returns the vector perpendicular to the plane through a, B and C.
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// Arguments:
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// v1 = First vector or point.
// v2 = Second vector or point.
// v3 = Third point in three point mode.
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// Example:
// axis1 = vector_axis(UP,LEFT); // Returns: [0,-1,0] (FWD)
// axis2 = vector_axis(RIGHT,LEFT); // Returns: [0,-1,0] (FWD)
// axis3 = vector_axis(UP+RIGHT,RIGHT); // Returns: [0,1,0] (BACK)
// axis4 = vector_axis([10,10], [0,0], [10,-10]); // Returns: [0,0,-1] (DOWN)
// axis5 = vector_axis([10,0,10], [0,0,0], [-10,10,0]); // Returns: [-0.57735, -0.57735, 0.57735]
// axis6 = vector_axis([[10,0,10], [0,0,0], [-10,10,0]]); // Returns: [-0.57735, -0.57735, 0.57735]
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function vector_axis ( v1 , v2 = undef , v3 = undef ) =
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is_vector ( v3 )
? assert ( is_consistent ( [ v3 , v2 , v1 ] ) , "Bad arguments." )
vector_axis ( v1 - v2 , v3 - v2 )
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: assert ( is_undef ( v3 ) , "Bad arguments." )
is_undef ( v2 )
? assert ( is_list ( v1 ) , "Bad arguments." )
len ( v1 ) = = 2
? vector_axis ( v1 [ 0 ] , v1 [ 1 ] )
: vector_axis ( v1 [ 0 ] , v1 [ 1 ] , v1 [ 2 ] )
: assert ( is_vector ( v1 , zero = false ) && is_vector ( v2 , zero = false ) && is_consistent ( [ v1 , v2 ] )
, "Bad arguments." )
let (
eps = 1e-6 ,
w1 = point3d ( v1 / norm ( v1 ) ) ,
w2 = point3d ( v2 / norm ( v2 ) ) ,
w3 = ( norm ( w1 - w2 ) > eps && norm ( w1 + w2 ) > eps ) ? w2
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: ( norm ( v_abs ( w2 ) - UP ) > eps ) ? UP
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: RIGHT
) unit ( cross ( w1 , w3 ) ) ;
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// Section: Vector Searching
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// Function: pointlist_bounds()
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// Usage:
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// pt_pair = pointlist_bounds(pts);
// Topics: Geometry, Bounding Boxes, Bounds
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// Description:
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// Finds the bounds containing all the points in `pts` which can be a list of points in any dimension.
// Returns a list of two items: a list of the minimums and a list of the maximums. For example, with
// 3d points `[[MINX, MINY, MINZ], [MAXX, MAXY, MAXZ]]`
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// Arguments:
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// pts = List of points.
function pointlist_bounds ( pts ) =
assert ( is_path ( pts , dim = undef , fast = true ) , "Invalid pointlist." )
let (
select = ident ( len ( pts [ 0 ] ) ) ,
spread = [
for ( i = [ 0 : len ( pts [ 0 ] ) - 1 ] )
let ( spreadi = pts * select [ i ] )
[ min ( spreadi ) , max ( spreadi ) ]
]
) transpose ( spread ) ;
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// Function: closest_point()
// Usage:
// index = closest_point(pt, points);
// Topics: Geometry, Points, Distance
// Description:
// Given a list of `points`, finds the index of the closest point to `pt`.
// Arguments:
// pt = The point to find the closest point to.
// points = The list of points to search.
function closest_point ( pt , points ) =
assert ( is_vector ( pt ) , "Invalid point." )
assert ( is_path ( points , dim = len ( pt ) ) , "Invalid pointlist or incompatible dimensions." )
min_index ( [ for ( p = points ) norm ( p - pt ) ] ) ;
// Function: furthest_point()
// Usage:
// index = furthest_point(pt, points);
// Topics: Geometry, Points, Distance
// Description:
// Given a list of `points`, finds the index of the furthest point from `pt`.
// Arguments:
// pt = The point to find the farthest point from.
// points = The list of points to search.
function furthest_point ( pt , points ) =
assert ( is_vector ( pt ) , "Invalid point." )
assert ( is_path ( points , dim = len ( pt ) ) , "Invalid pointlist or incompatible dimensions." )
max_index ( [ for ( p = points ) norm ( p - pt ) ] ) ;
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// Function: vector_search()
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// Usage:
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// indices = vector_search(query, r, target);
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// See Also: vector_search_tree(), vector_nearest()
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// Topics: Search, Points, Closest
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// Description:
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// Given a list of query points `query` and a `target` to search,
// finds the points in `target` that match each query point. A match holds when the
// distance between a point in `target` and a query point is less than or equal to `r`.
// The returned list will have a list for each query point containing, in arbitrary
// order, the indices of all points that match that query point.
// The `target` may be a simple list of points or a search tree.
// When `target` is a large list of points, a search tree is constructed to
// speed up the search with an order around O(log n) per query point.
// For small point lists, a direct search is done dispensing a tree construction.
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// Alternatively, `target` may be a search tree built with `vector_search_tree()`.
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// In that case, that tree is parsed looking for matches.
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// An empty list of query points will return a empty output list.
// An empty list of target points will return a output list with an empty list for each query point.
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// Arguments:
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// query = list of points to find matches for.
// r = the search radius.
// target = list of the points to search for matches or a search tree.
// Example: A set of four queries to find points within 1 unit of the query. The circles show the search region and all have radius 1.
// $fn=32;
// k = 2000;
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// points = list_to_matrix(rands(0,10,k*2,seed=13333),2);
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// queries = [for(i=[3,7],j=[3,7]) [i,j]];
// search_ind = vector_search(queries, points, 1);
// move_copies(points) circle(r=.08);
// for(i=idx(queries)){
// color("blue")stroke(move(queries[i],circle(r=1)), closed=true, width=.08);
// color("red") move_copies(select(points, search_ind[i])) circle(r=.08);
// }
// Example: when a series of search with different radius are needed, its is faster to pre-compute the tree
// $fn=32;
// k = 2000;
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// points = list_to_matrix(rands(0,10,k*2),2,seed=13333);
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// queries1 = [for(i=[3,7]) [i,i]];
// queries2 = [for(i=[3,7]) [10-i,i]];
// r1 = 1;
// r2 = .7;
// search_tree = vector_search_tree(points);
// search_1 = vector_search(queries1, r1, search_tree);
// search_2 = vector_search(queries2, r2, search_tree);
// move_copies(points) circle(r=.08);
// for(i=idx(queries1)){
// color("blue")stroke(move(queries1[i],circle(r=r1)), closed=true, width=.08);
// color("red") move_copies(select(points, search_1[i])) circle(r=.08);
// }
// for(i=idx(queries2)){
// color("green")stroke(move(queries2[i],circle(r=r2)), closed=true, width=.08);
// color("red") move_copies(select(points, search_2[i])) circle(r=.08);
// }
function vector_search ( query , r , target ) =
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query = = [ ] ? [ ] :
is_list ( query ) && target = = [ ] ? is_vector ( query ) ? [ ] : [ for ( q = query ) [ ] ] :
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assert ( is_finite ( r ) && r >= 0 ,
"The query radius should be a positive number." )
let (
tgpts = is_matrix ( target ) , // target is a point list
tgtree = is_list ( target ) // target is a tree
&& ( len ( target ) = = 2 )
&& is_matrix ( target [ 0 ] )
&& is_list ( target [ 1 ] )
&& ( len ( target [ 1 ] ) = = 4 || ( len ( target [ 1 ] ) = = 1 && is_list ( target [ 1 ] [ 0 ] ) ) )
)
assert ( tgpts || tgtree ,
"The target should be a list of points or a search tree compatible with the query." )
let (
dim = tgpts ? len ( target [ 0 ] ) : len ( target [ 0 ] [ 0 ] ) ,
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simple = is_vector ( query , dim )
)
assert ( simple || is_matrix ( query , undef , dim ) ,
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"The query points should be a list of points compatible with the target point list." )
tgpts
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? len ( target ) < = 400
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? simple ? [ for ( i = idx ( target ) ) if ( norm ( target [ i ] - query ) < r ) i ] :
[ for ( q = query ) [ for ( i = idx ( target ) ) if ( norm ( target [ i ] - q ) < r ) i ] ]
: let ( tree = _bt_tree ( target , count ( len ( target ) ) , leafsize = 25 ) )
simple ? _bt_search ( query , r , target , tree ) :
[ for ( q = query ) _bt_search ( q , r , target , tree ) ]
: simple ? _bt_search ( query , r , target [ 0 ] , target [ 1 ] ) :
[ for ( q = query ) _bt_search ( q , r , target [ 0 ] , target [ 1 ] ) ] ;
//Ball tree search
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function _bt_search ( query , r , points , tree ) =
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assert ( is_list ( tree )
&& ( ( len ( tree ) = = 1 && is_list ( tree [ 0 ] ) )
|| ( len ( tree ) = = 4 && is_num ( tree [ 0 ] ) && is_num ( tree [ 1 ] ) ) ) ,
"The tree is invalid." )
len ( tree ) = = 1
? assert ( tree [ 0 ] = = [ ] || is_vector ( tree [ 0 ] ) , "The tree is invalid." )
[ for ( i = tree [ 0 ] ) if ( norm ( points [ i ] - query ) < = r ) i ]
: norm ( query - points [ tree [ 0 ] ] ) > r + tree [ 1 ] ? [ ] :
concat (
[ if ( norm ( query - points [ tree [ 0 ] ] ) < = r ) tree [ 0 ] ] ,
_bt_search ( query , r , points , tree [ 2 ] ) ,
_bt_search ( query , r , points , tree [ 3 ] ) ) ;
// Function: vector_search_tree()
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// Usage:
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// tree = vector_search_tree(points,leafsize);
// See Also: vector_nearest(), vector_search()
// Topics: Search, Points, Closest
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// Description:
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// Construct a search tree for the given list of points to be used as input
// to the function `vector_search()`. The use of a tree speeds up the
// search process. The tree construction stops branching when
// a tree node represents a number of points less or equal to `leafsize`.
// Search trees are ball trees. Constructing the
// tree should be O(n log n) and searches should be O(log n), though real life
// performance depends on how the data is distributed, and it will deteriorate
// for high data dimensions. This data structure is useful when you will be
// performing many searches of the same data, so that the cost of constructing
// the tree is justified. (See https://en.wikipedia.org/wiki/Ball_tree)
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// For a small lists of points, the search with a tree may be more expensive
// than direct comparisons. The argument `treemin` sets the minimum length of
// point set for which a tree search will be done by `vector_search`.
// For an empty list of points it returns an empty list.
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// Arguments:
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// points = list of points to store in the search tree.
// leafsize = the size of the tree leaves. Default: 25
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// treemin = the minimum size of the point list for which a tree search is done. Default: 400
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// Example: A set of four queries to find points within 1 unit of the query. The circles show the search region and all have radius 1.
// $fn=32;
// k = 2000;
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// points = random_points(k, scale=10, dim=2,seed=13333);
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// queries = [for(i=[3,7],j=[3,7]) [i,j]];
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// search_tree = vector_search_tree(points);
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// search_ind = vector_search(queries,1,search_tree);
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// move_copies(points) circle(r=.08);
// for(i=idx(queries)){
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// color("blue") stroke(move(queries[i],circle(r=1)), closed=true, width=.08);
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// color("red") move_copies(select(points, search_ind[i])) circle(r=.08);
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// }
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function vector_search_tree ( points , leafsize = 25 , treemin = 400 ) =
points = = [ ] ? [ ] :
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assert ( is_matrix ( points ) , "The input list entries should be points." )
assert ( is_int ( leafsize ) && leafsize >= 1 ,
"The tree leaf size should be an integer greater than zero." )
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len ( points ) < treemin ? points :
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[ points , _bt_tree ( points , count ( len ( points ) ) , leafsize ) ] ;
//Ball tree construction
function _bt_tree ( points , ind , leafsize = 25 ) =
len ( ind ) < = leafsize ? [ ind ] :
let (
bounds = pointlist_bounds ( select ( points , ind ) ) ,
coord = max_index ( bounds [ 1 ] - bounds [ 0 ] ) ,
projc = [ for ( i = ind ) points [ i ] [ coord ] ] ,
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meanpr = mean ( projc ) ,
pivot = min_index ( [ for ( p = projc ) abs ( p - meanpr ) ] ) ,
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radius = max ( [ for ( i = ind ) norm ( points [ ind [ pivot ] ] - points [ i ] ) ] ) ,
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Lind = [ for ( i = idx ( ind ) ) if ( projc [ i ] < = meanpr && i ! = pivot ) ind [ i ] ] ,
Rind = [ for ( i = idx ( ind ) ) if ( projc [ i ] > meanpr && i ! = pivot ) ind [ i ] ]
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)
[ ind [ pivot ] , radius , _bt_tree ( points , Lind , leafsize ) , _bt_tree ( points , Rind , leafsize ) ] ;
// Function: vector_nearest()
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// Usage:
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// indices = vector_nearest(query, k, target);
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// See Also: vector_search(), vector_search_tree()
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// Description:
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// Search `target` for the `k` points closest to point `query`.
// The input `target` is either a list of points to search or a search tree
// pre-computed by `vector_search_tree(). A list is returned containing the indices
// of the points found in sorted order, closest point first.
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// Arguments:
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// query = point to search for
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// k = number of neighbors to return
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// target = a list of points or a search tree to search in
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// Example: Four queries to find the 15 nearest points. The circles show the radius defined by the most distant query result. Note they are different for each query.
// $fn=32;
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// k = 1000;
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// points = list_to_matrix(rands(0,10,k*2,seed=13333),2);
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// tree = vector_search_tree(points);
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// queries = [for(i=[3,7],j=[3,7]) [i,j]];
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// search_ind = [for(q=queries) vector_nearest(q, 15, tree)];
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// move_copies(points) circle(r=.08);
// for(i=idx(queries)){
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// circle = circle(r=norm(points[last(search_ind[i])]-queries[i]));
// color("red") move_copies(select(points, search_ind[i])) circle(r=.08);
// color("blue") stroke(move(queries[i], circle), closed=true, width=.08);
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// }
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function vector_nearest ( query , k , target ) =
assert ( is_int ( k ) && k > 0 )
assert ( is_vector ( query ) , "Query must be a vector." )
let (
tgpts = is_matrix ( target , undef , len ( query ) ) , // target is a point list
tgtree = is_list ( target ) // target is a tree
&& ( len ( target ) = = 2 )
&& is_matrix ( target [ 0 ] , undef , len ( query ) )
&& ( len ( target [ 1 ] ) = = 4 || ( len ( target [ 1 ] ) = = 1 && is_list ( target [ 1 ] [ 0 ] ) ) )
)
assert ( tgpts || tgtree ,
"The target should be a list of points or a search tree compatible with the query." )
assert ( ( tgpts && ( k < = len ( target ) ) ) || ( tgtree && ( k < = len ( target [ 0 ] ) ) ) ,
"More results are requested than the number of points." )
tgpts
? let ( tree = _bt_tree ( target , count ( len ( target ) ) ) )
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column ( _bt_nearest ( query , k , target , tree ) , 0 )
: column ( _bt_nearest ( query , k , target [ 0 ] , target [ 1 ] ) , 0 ) ;
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//Ball tree nearest
function _bt_nearest ( p , k , points , tree , answers = [ ] ) =
assert ( is_list ( tree )
&& ( ( len ( tree ) = = 1 && is_list ( tree [ 0 ] ) )
|| ( len ( tree ) = = 4 && is_num ( tree [ 0 ] ) && is_num ( tree [ 1 ] ) ) ) ,
"The tree is invalid." )
len ( tree ) = = 1
? _insert_many ( answers , k , [ for ( entry = tree [ 0 ] ) [ entry , norm ( points [ entry ] - p ) ] ] )
: let ( d = norm ( p - points [ tree [ 0 ] ] ) )
len ( answers ) = = k && ( d > last ( answers ) [ 1 ] + tree [ 1 ] ) ? answers :
let (
answers1 = _insert_sorted ( answers , k , [ tree [ 0 ] , d ] ) ,
answers2 = _bt_nearest ( p , k , points , tree [ 2 ] , answers1 ) ,
answers3 = _bt_nearest ( p , k , points , tree [ 3 ] , answers2 )
)
answers3 ;
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function _insert_sorted ( list , k , new ) =
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( len ( list ) = = k && new [ 1 ] >= last ( list ) [ 1 ] ) ? list
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: [
for ( entry = list ) if ( entry [ 1 ] < = new [ 1 ] ) entry ,
new ,
for ( i = [ 0 : 1 : min ( k - 1 , len ( list ) ) - 1 ] ) if ( list [ i ] [ 1 ] > new [ 1 ] ) list [ i ]
] ;
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function _insert_many ( list , k , newlist , i = 0 ) =
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i = = len ( newlist )
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? list
: assert ( is_vector ( newlist [ i ] , 2 ) , "The tree is invalid." )
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_insert_many ( _insert_sorted ( list , k , newlist [ i ] ) , k , newlist , i + 1 ) ;
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// vim: expandtab tabstop=4 shiftwidth=4 softtabstop=4 nowrap