BOSL2/tests/test_arrays.scad

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include <../std.scad>
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// Section: List Query Operations
Sort debugging and optimizing There were bugs in the previous sorting functions. They didn't check the homogeneity of the input list before calling _sort_scalars and _sort_vectors. The bug might result in wrong order and missing list elements in the output. Besides correcting the bug a recode of all sorting functions result in better performance and a enlargement of their scope. With the new functions, list of vectors of any dimension may be sorted, even with idx given, with the native comparison operators. The scope of indexed sorting is also extended. The file test_arrays has been extended to check the new funcionality. New functions: is_homogeneous - checks if a list has elements of the same type (although not distinguing booleans from numbers) up to a given depth _sort_vectors - internal function to sort homgeneous lists of vectors using native comparison operators; extends the scope of the previous _sort_vectors# functions with better performance _lexical_sort - internal function to sort non-homogeneous lists; uses compare_vals _indexed_sort - internal function to perform indexed sorting of non-homogeneous lists; uses compar_vals Changed/reviewed functions: _valid_idx - doesn't requires the input of imin and imax args sort - explores the internal functions to get better performance and an enlarged scope sortidx - explores the internal functions to get better performance and an enlarged scope _sort_general - just for sortings of non-homogeneous lists using compare_vals _array_dim_recurse - changed for bit better performance Functions eliminated: _sort_vectors1 _sort_vectors2 _sort_vectors3 _sort_vectors4
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module test_is_homogeneous(){
assert(is_homogeneous([[1,["a"]], [2,["b"]]])==true);
assert(is_homogeneous([[1,["a"]], [2,[true]]])==false);
assert(is_homogeneous([[1,["a"]], [2,[true]]],1)==true);
assert(is_homogeneous([[1,["a"]], [2,[true]]],2)==false);
assert(is_homogeneous([[1,["a"]], [true,["b"]]])==false);
Sort debugging and optimizing There were bugs in the previous sorting functions. They didn't check the homogeneity of the input list before calling _sort_scalars and _sort_vectors. The bug might result in wrong order and missing list elements in the output. Besides correcting the bug a recode of all sorting functions result in better performance and a enlargement of their scope. With the new functions, list of vectors of any dimension may be sorted, even with idx given, with the native comparison operators. The scope of indexed sorting is also extended. The file test_arrays has been extended to check the new funcionality. New functions: is_homogeneous - checks if a list has elements of the same type (although not distinguing booleans from numbers) up to a given depth _sort_vectors - internal function to sort homgeneous lists of vectors using native comparison operators; extends the scope of the previous _sort_vectors# functions with better performance _lexical_sort - internal function to sort non-homogeneous lists; uses compare_vals _indexed_sort - internal function to perform indexed sorting of non-homogeneous lists; uses compar_vals Changed/reviewed functions: _valid_idx - doesn't requires the input of imin and imax args sort - explores the internal functions to get better performance and an enlarged scope sortidx - explores the internal functions to get better performance and an enlarged scope _sort_general - just for sortings of non-homogeneous lists using compare_vals _array_dim_recurse - changed for bit better performance Functions eliminated: _sort_vectors1 _sort_vectors2 _sort_vectors3 _sort_vectors4
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}
test_is_homogeneous();
module test_select() {
l = [3,4,5,6,7,8,9];
assert(select(l, 5, 6) == [8,9]);
assert(select(l, 5, 8) == [8,9,3,4]);
assert(select(l, 5, 2) == [8,9,3,4,5]);
assert(select(l, -3, -1) == [7,8,9]);
assert(select(l, 3, 3) == [6]);
assert(select(l, 4) == 7);
assert(select(l, -2) == 8);
assert(select(l, [1:3]) == [4,5,6]);
assert(select(l, [1,3]) == [4,6]);
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}
test_select();
module test_slice() {
assert(slice([3,4,5,6,7,8,9], 3, 5) == [6,7]);
assert(slice([3,4,5,6,7,8,9], 2, -1) == [5,6,7,8,9]);
assert(slice([3,4,5,6,7,8,9], 1, 1) == []);
assert(slice([3,4,5,6,7,8,9], 6, -1) == [9]);
assert(slice([3,4,5,6,7,8,9], 2, -2) == [5,6,7,8]);
assert(slice([], 2, -2) == []);
}
test_slice();
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module test_in_list() {
assert(in_list("bar", ["foo", "bar", "baz"]));
assert(!in_list("bee", ["foo", "bar", "baz"]));
assert(in_list("bar", [[2,"foo"], [4,"bar"], [3,"baz"]], idx=1));
assert(!in_list("bee", ["foo", "bar", ["bee"]]));
assert(in_list(NAN, [NAN])==false);
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assert(!in_list(undef, [3,4,5]));
assert(in_list(undef,[3,4,undef,5]));
assert(!in_list(3,[]));
assert(!in_list(3,[4,5,[3]]));
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}
test_in_list();
module test_min_index() {
assert(min_index([5,3,9,6,2,7,8,2,1])==8);
assert(min_index([5,3,9,6,2,7,8,2,7],all=true)==[4,7]);
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}
test_min_index();
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module test_max_index() {
assert(max_index([5,3,9,6,2,7,8,9,1])==2);
assert(max_index([5,3,9,6,2,7,8,9,7],all=true)==[2,7]);
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}
test_max_index();
module test_list_increasing() {
assert(list_increasing([1,2,3,4]) == true);
assert(list_increasing([1,3,2,4]) == false);
assert(list_increasing([4,3,2,1]) == false);
}
test_list_increasing();
module test_list_decreasing() {
assert(list_decreasing([1,2,3,4]) == false);
assert(list_decreasing([4,2,3,1]) == false);
assert(list_decreasing([4,3,2,1]) == true);
}
test_list_decreasing();
Sort debugging and optimizing There were bugs in the previous sorting functions. They didn't check the homogeneity of the input list before calling _sort_scalars and _sort_vectors. The bug might result in wrong order and missing list elements in the output. Besides correcting the bug a recode of all sorting functions result in better performance and a enlargement of their scope. With the new functions, list of vectors of any dimension may be sorted, even with idx given, with the native comparison operators. The scope of indexed sorting is also extended. The file test_arrays has been extended to check the new funcionality. New functions: is_homogeneous - checks if a list has elements of the same type (although not distinguing booleans from numbers) up to a given depth _sort_vectors - internal function to sort homgeneous lists of vectors using native comparison operators; extends the scope of the previous _sort_vectors# functions with better performance _lexical_sort - internal function to sort non-homogeneous lists; uses compare_vals _indexed_sort - internal function to perform indexed sorting of non-homogeneous lists; uses compar_vals Changed/reviewed functions: _valid_idx - doesn't requires the input of imin and imax args sort - explores the internal functions to get better performance and an enlarged scope sortidx - explores the internal functions to get better performance and an enlarged scope _sort_general - just for sortings of non-homogeneous lists using compare_vals _array_dim_recurse - changed for bit better performance Functions eliminated: _sort_vectors1 _sort_vectors2 _sort_vectors3 _sort_vectors4
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// Section: Basic List Generation
module test_repeat() {
assert(repeat(1, 4) == [1,1,1,1]);
assert(repeat(8, [2,3]) == [[8,8,8], [8,8,8]]);
assert(repeat(0, [2,2,3]) == [[[0,0,0],[0,0,0]], [[0,0,0],[0,0,0]]]);
assert(repeat([1,2,3],3) == [[1,2,3], [1,2,3], [1,2,3]]);
assert(repeat(4, [2,-1]) == [[], []]);
}
test_repeat();
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module test_list_range() {
assert(list_range(4) == [0,1,2,3]);
assert(list_range(n=4, step=2) == [0,2,4,6]);
assert(list_range(n=4, s=3, step=3) == [3,6,9,12]);
assert(list_range(e=3) == [0,1,2,3]);
assert(list_range(e=6, step=2) == [0,2,4,6]);
assert(list_range(s=3, e=5) == [3,4,5]);
assert(list_range(s=3, e=8, step=2) == [3,5,7]);
assert(list_range(s=4, e=8, step=2) == [4,6,8]);
assert(list_range(e=4, n=3) == [0,2,4]);
assert(list_range(n=4, s=[3,4], step=[2,3]) == [[3,4], [5,7], [7,10], [9,13]]);
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}
test_list_range();
module test_reverse() {
assert(reverse([3,4,5,6]) == [6,5,4,3]);
assert(reverse("abcd") == "dcba");
assert(reverse([]) == []);
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}
test_reverse();
module test_list_rotate() {
assert(list_rotate([1,2,3,4,5],-2) == [4,5,1,2,3]);
assert(list_rotate([1,2,3,4,5],-1) == [5,1,2,3,4]);
assert(list_rotate([1,2,3,4,5],0) == [1,2,3,4,5]);
assert(list_rotate([1,2,3,4,5],1) == [2,3,4,5,1]);
assert(list_rotate([1,2,3,4,5],2) == [3,4,5,1,2]);
assert(list_rotate([1,2,3,4,5],3) == [4,5,1,2,3]);
assert(list_rotate([1,2,3,4,5],4) == [5,1,2,3,4]);
assert(list_rotate([1,2,3,4,5],5) == [1,2,3,4,5]);
assert(list_rotate([1,2,3,4,5],6) == [2,3,4,5,1]);
assert(list_rotate([],3) == []);
}
test_list_rotate();
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module test_deduplicate() {
assert_equal(deduplicate([8,3,4,4,4,8,2,3,3,8,8]), [8,3,4,8,2,3,8]);
assert_equal(deduplicate(closed=true, [8,3,4,4,4,8,2,3,3,8,8]), [8,3,4,8,2,3]);
assert_equal(deduplicate("Hello"), "Helo");
assert_equal(deduplicate([[3,4],[7,1.99],[7,2],[1,4]],eps=0.1), [[3,4],[7,2],[1,4]]);
assert_equal(deduplicate([], closed=true), []);
assert_equal(deduplicate([[1,[1,[undef]]],[1,[1,[undef]]],[1,[2]],[1,[2,[0]]]]), [[1, [1,[undef]]],[1,[2]],[1,[2,[0]]]]);
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}
test_deduplicate();
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module test_deduplicate_indexed() {
assert(deduplicate_indexed([8,6,4,6,3], [1,4,3,1,2,2,0,1]) == [1,4,1,2,0,1]);
assert(deduplicate_indexed([8,6,4,6,3], [1,4,3,1,2,2,0,1], closed=true) == [1,4,1,2,0]);
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}
test_deduplicate_indexed();
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module test_list_set() {
assert(list_set([2,3,4,5], 2, 21) == [2,3,21,5]);
assert(list_set([2,3,4,5], [1,3], [81,47]) == [2,81,4,47]);
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}
test_list_set();
module test_list_remove() {
assert(list_remove([3,6,9,12],1) == [3,9,12]);
assert(list_remove([3,6,9,12],[1,3]) == [3,9]);
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}
test_list_remove();
module test_list_remove_values() {
animals = ["bat", "cat", "rat", "dog", "bat", "rat"];
assert(list_remove_values(animals, "rat") == ["bat","cat","dog","bat","rat"]);
assert(list_remove_values(animals, "bat", all=true) == ["cat","rat","dog","rat"]);
assert(list_remove_values(animals, ["bat","rat"]) == ["cat","dog","bat","rat"]);
assert(list_remove_values(animals, ["bat","rat"], all=true) == ["cat","dog"]);
assert(list_remove_values(animals, ["tucan","rat"], all=true) == ["bat","cat","dog","bat"]);
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}
test_list_remove_values();
module test_list_insert() {
assert(list_insert([3,6,9,12],1,5) == [3,5,6,9,12]);
assert(list_insert([3,6,9,12],[1,3],[5,11]) == [3,5,6,9,11,12]);
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}
test_list_insert();
module test_bselect() {
assert(bselect([3,4,5,6,7], [false,false,false,false,false]) == []);
assert(bselect([3,4,5,6,7], [false,true,true,false,true]) == [4,5,7]);
assert(bselect([3,4,5,6,7], [true,true,true,true,true]) == [3,4,5,6,7]);
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}
test_bselect();
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module test_list_bset() {
assert(list_bset([false,true,false,true,false], [3,4]) == [0,3,0,4,0]);
assert(list_bset([false,true,false,true,false], [3,4], dflt=1) == [1,3,1,4,1]);
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}
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test_list_bset();
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module test_list_shortest() {
assert(list_shortest(["foobar", "bazquxx", "abcd"]) == 4);
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}
test_list_shortest();
module test_list_longest() {
assert(list_longest(["foobar", "bazquxx", "abcd"]) == 7);
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}
test_list_longest();
module test_list_pad() {
assert(list_pad([4,5,6], 5, 8) == [4,5,6,8,8]);
assert(list_pad([4,5,6,7,8], 5, 8) == [4,5,6,7,8]);
assert(list_pad([4,5,6,7,8,9], 5, 8) == [4,5,6,7,8,9]);
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}
test_list_pad();
module test_list_trim() {
assert(list_trim([4,5,6], 5) == [4,5,6]);
assert(list_trim([4,5,6,7,8], 5) == [4,5,6,7,8]);
assert(list_trim([3,4,5,6,7,8,9], 5) == [3,4,5,6,7]);
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}
test_list_trim();
module test_list_fit() {
assert(list_fit([4,5,6], 5, 8) == [4,5,6,8,8]);
assert(list_fit([4,5,6,7,8], 5, 8) == [4,5,6,7,8]);
assert(list_fit([3,4,5,6,7,8,9], 5, 8) == [3,4,5,6,7]);
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}
test_list_fit();
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module test_idx() {
colors = ["red", "green", "blue", "cyan"];
assert([for (i=idx(colors)) i] == [0,1,2,3]);
assert([for (i=idx(colors,end=-2)) i] == [0,1,2]);
assert([for (i=idx(colors,start=1)) i] == [1,2,3]);
assert([for (i=idx(colors,start=1,end=-2)) i] == [1,2]);
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}
test_idx();
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module test_enumerate() {
assert(enumerate(["a","b","c"]) == [[0,"a"], [1,"b"], [2,"c"]]);
assert(enumerate([[88,"a"],[76,"b"],[21,"c"]], idx=1) == [[0,"a"], [1,"b"], [2,"c"]]);
assert(enumerate([["cat","a",12],["dog","b",10],["log","c",14]], idx=[1:2]) == [[0,"a",12], [1,"b",10], [2,"c",14]]);
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}
test_enumerate();
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module test_shuffle() {
nums1 = [for (i=list_range(100)) i];
nums2 = shuffle(nums1);
nums3 = shuffle(nums2);
assert(len(nums2)==len(nums1));
assert(len(nums3)==len(nums2));
assert(nums1!=nums2);
assert(nums2!=nums3);
assert(nums1!=nums3);
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}
test_shuffle();
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module test_sort() {
assert(sort([7,3,9,4,3,1,8]) == [1,3,3,4,7,8,9]);
Sort debugging and optimizing There were bugs in the previous sorting functions. They didn't check the homogeneity of the input list before calling _sort_scalars and _sort_vectors. The bug might result in wrong order and missing list elements in the output. Besides correcting the bug a recode of all sorting functions result in better performance and a enlargement of their scope. With the new functions, list of vectors of any dimension may be sorted, even with idx given, with the native comparison operators. The scope of indexed sorting is also extended. The file test_arrays has been extended to check the new funcionality. New functions: is_homogeneous - checks if a list has elements of the same type (although not distinguing booleans from numbers) up to a given depth _sort_vectors - internal function to sort homgeneous lists of vectors using native comparison operators; extends the scope of the previous _sort_vectors# functions with better performance _lexical_sort - internal function to sort non-homogeneous lists; uses compare_vals _indexed_sort - internal function to perform indexed sorting of non-homogeneous lists; uses compar_vals Changed/reviewed functions: _valid_idx - doesn't requires the input of imin and imax args sort - explores the internal functions to get better performance and an enlarged scope sortidx - explores the internal functions to get better performance and an enlarged scope _sort_general - just for sortings of non-homogeneous lists using compare_vals _array_dim_recurse - changed for bit better performance Functions eliminated: _sort_vectors1 _sort_vectors2 _sort_vectors3 _sort_vectors4
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assert(sort([[4,0],[7],[3,9],20,[4],[3,1],[8]]) == [20,[3,1],[3,9],[4],[4,0],[7],[8]]);
assert(sort([[4,0],[7],[3,9],20,[4],[3,1],[8]],idx=1) == [[7],20,[4],[8],[4,0],[3,1],[3,9]]);
assert(sort([[8,6],[3,1],[9,2],[4,3],[3,4],[1,5],[8,0]]) == [[1,5],[3,1],[3,4],[4,3],[8,0],[8,6],[9,2]]);
assert(sort([[8,0],[3,1],[9,2],[4,3],[3,4],[1,5],[8,6]],idx=1) == [[8,0],[3,1],[9,2],[4,3],[3,4],[1,5],[8,6]]);
assert(sort(["cat", "oat", "sat", "bat", "vat", "rat", "pat", "mat", "fat", "hat", "eat"])
== ["bat", "cat", "eat", "fat", "hat", "mat", "oat", "pat", "rat", "sat", "vat"]);
assert(sort(enumerate([[2,3,4],[1,2,3],[2,4,3]]),idx=1)==[[1,[1,2,3]], [0,[2,3,4]], [2,[2,4,3]]]);
Sort debugging and optimizing There were bugs in the previous sorting functions. They didn't check the homogeneity of the input list before calling _sort_scalars and _sort_vectors. The bug might result in wrong order and missing list elements in the output. Besides correcting the bug a recode of all sorting functions result in better performance and a enlargement of their scope. With the new functions, list of vectors of any dimension may be sorted, even with idx given, with the native comparison operators. The scope of indexed sorting is also extended. The file test_arrays has been extended to check the new funcionality. New functions: is_homogeneous - checks if a list has elements of the same type (although not distinguing booleans from numbers) up to a given depth _sort_vectors - internal function to sort homgeneous lists of vectors using native comparison operators; extends the scope of the previous _sort_vectors# functions with better performance _lexical_sort - internal function to sort non-homogeneous lists; uses compare_vals _indexed_sort - internal function to perform indexed sorting of non-homogeneous lists; uses compar_vals Changed/reviewed functions: _valid_idx - doesn't requires the input of imin and imax args sort - explores the internal functions to get better performance and an enlarged scope sortidx - explores the internal functions to get better performance and an enlarged scope _sort_general - just for sortings of non-homogeneous lists using compare_vals _array_dim_recurse - changed for bit better performance Functions eliminated: _sort_vectors1 _sort_vectors2 _sort_vectors3 _sort_vectors4
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assert(sort([0,"1",[1,0],2,"a",[1]])== [0,2,"1","a",[1],[1,0]]);
assert(sort([["oat",0], ["cat",1], ["bat",3], ["bat",2], ["fat",3]])== [["bat",2],["bat",3],["cat",1],["fat",3],["oat",0]]);
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}
test_sort();
module test_sortidx() {
Sort debugging and optimizing There were bugs in the previous sorting functions. They didn't check the homogeneity of the input list before calling _sort_scalars and _sort_vectors. The bug might result in wrong order and missing list elements in the output. Besides correcting the bug a recode of all sorting functions result in better performance and a enlargement of their scope. With the new functions, list of vectors of any dimension may be sorted, even with idx given, with the native comparison operators. The scope of indexed sorting is also extended. The file test_arrays has been extended to check the new funcionality. New functions: is_homogeneous - checks if a list has elements of the same type (although not distinguing booleans from numbers) up to a given depth _sort_vectors - internal function to sort homgeneous lists of vectors using native comparison operators; extends the scope of the previous _sort_vectors# functions with better performance _lexical_sort - internal function to sort non-homogeneous lists; uses compare_vals _indexed_sort - internal function to perform indexed sorting of non-homogeneous lists; uses compar_vals Changed/reviewed functions: _valid_idx - doesn't requires the input of imin and imax args sort - explores the internal functions to get better performance and an enlarged scope sortidx - explores the internal functions to get better performance and an enlarged scope _sort_general - just for sortings of non-homogeneous lists using compare_vals _array_dim_recurse - changed for bit better performance Functions eliminated: _sort_vectors1 _sort_vectors2 _sort_vectors3 _sort_vectors4
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lst1 = ["da","bax","eaw","cav"];
assert(sortidx(lst1) == [1,3,0,2]);
Sort debugging and optimizing There were bugs in the previous sorting functions. They didn't check the homogeneity of the input list before calling _sort_scalars and _sort_vectors. The bug might result in wrong order and missing list elements in the output. Besides correcting the bug a recode of all sorting functions result in better performance and a enlargement of their scope. With the new functions, list of vectors of any dimension may be sorted, even with idx given, with the native comparison operators. The scope of indexed sorting is also extended. The file test_arrays has been extended to check the new funcionality. New functions: is_homogeneous - checks if a list has elements of the same type (although not distinguing booleans from numbers) up to a given depth _sort_vectors - internal function to sort homgeneous lists of vectors using native comparison operators; extends the scope of the previous _sort_vectors# functions with better performance _lexical_sort - internal function to sort non-homogeneous lists; uses compare_vals _indexed_sort - internal function to perform indexed sorting of non-homogeneous lists; uses compar_vals Changed/reviewed functions: _valid_idx - doesn't requires the input of imin and imax args sort - explores the internal functions to get better performance and an enlarged scope sortidx - explores the internal functions to get better performance and an enlarged scope _sort_general - just for sortings of non-homogeneous lists using compare_vals _array_dim_recurse - changed for bit better performance Functions eliminated: _sort_vectors1 _sort_vectors2 _sort_vectors3 _sort_vectors4
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lst5 = [3,5,1,7];
assert(sortidx(lst5) == [2,0,1,3]);
lst2 = [
["foo", 88, [0,0,1], false],
["bar", 90, [0,1,0], true],
["baz", 89, [1,0,0], false],
["qux", 23, [1,1,1], true]
];
assert(sortidx(lst2, idx=1) == [3,0,2,1]);
assert(sortidx(lst2, idx=0) == [1,2,0,3]);
assert(sortidx(lst2, idx=[1,3]) == [3,0,2,1]);
Sort debugging and optimizing There were bugs in the previous sorting functions. They didn't check the homogeneity of the input list before calling _sort_scalars and _sort_vectors. The bug might result in wrong order and missing list elements in the output. Besides correcting the bug a recode of all sorting functions result in better performance and a enlargement of their scope. With the new functions, list of vectors of any dimension may be sorted, even with idx given, with the native comparison operators. The scope of indexed sorting is also extended. The file test_arrays has been extended to check the new funcionality. New functions: is_homogeneous - checks if a list has elements of the same type (although not distinguing booleans from numbers) up to a given depth _sort_vectors - internal function to sort homgeneous lists of vectors using native comparison operators; extends the scope of the previous _sort_vectors# functions with better performance _lexical_sort - internal function to sort non-homogeneous lists; uses compare_vals _indexed_sort - internal function to perform indexed sorting of non-homogeneous lists; uses compar_vals Changed/reviewed functions: _valid_idx - doesn't requires the input of imin and imax args sort - explores the internal functions to get better performance and an enlarged scope sortidx - explores the internal functions to get better performance and an enlarged scope _sort_general - just for sortings of non-homogeneous lists using compare_vals _array_dim_recurse - changed for bit better performance Functions eliminated: _sort_vectors1 _sort_vectors2 _sort_vectors3 _sort_vectors4
2020-08-30 11:12:36 +00:00
lst3 = [[-4,0,0],[0,0,-4],[0,-4,0],[-4,0,0],[0,-4,0],[0,0,4],
[0,0,-4],[0,4,0],[4,0,0],[0,0,4],[0,4,0],[4,0,0]];
assert(sortidx(lst3)==[0,3,2,4,1,6,5,9,7,10,8,11]);
Sort debugging and optimizing There were bugs in the previous sorting functions. They didn't check the homogeneity of the input list before calling _sort_scalars and _sort_vectors. The bug might result in wrong order and missing list elements in the output. Besides correcting the bug a recode of all sorting functions result in better performance and a enlargement of their scope. With the new functions, list of vectors of any dimension may be sorted, even with idx given, with the native comparison operators. The scope of indexed sorting is also extended. The file test_arrays has been extended to check the new funcionality. New functions: is_homogeneous - checks if a list has elements of the same type (although not distinguing booleans from numbers) up to a given depth _sort_vectors - internal function to sort homgeneous lists of vectors using native comparison operators; extends the scope of the previous _sort_vectors# functions with better performance _lexical_sort - internal function to sort non-homogeneous lists; uses compare_vals _indexed_sort - internal function to perform indexed sorting of non-homogeneous lists; uses compar_vals Changed/reviewed functions: _valid_idx - doesn't requires the input of imin and imax args sort - explores the internal functions to get better performance and an enlarged scope sortidx - explores the internal functions to get better performance and an enlarged scope _sort_general - just for sortings of non-homogeneous lists using compare_vals _array_dim_recurse - changed for bit better performance Functions eliminated: _sort_vectors1 _sort_vectors2 _sort_vectors3 _sort_vectors4
2020-08-30 11:12:36 +00:00
assert(sortidx([[4,0],[7],[3,9],20,[4],[3,1],[8]]) == [3,5,2,4,0,1,6]);
assert(sortidx([[4,0],[7],[3,9],20,[4],[3,1],[8]],idx=1) == [1,3,4,6,0,5,2]);
lst4=[0,"1",[1,0],2,"a",[1]];
assert(sortidx(lst4)== [0,3,1,4,5,2]);
assert(sortidx(["cat","oat","sat","bat","vat","rat","pat","mat","fat","hat","eat"])
== [3,0,10,8,9,7,1,6,5,2,4]);
assert(sortidx([["oat",0], ["cat",1], ["bat",3], ["bat",2], ["fat",3]])== [3,2,1,4,0]);
assert(sortidx(["Belfry", "OpenScad", "Library", "Documentation"])==[0,3,2,1]);
assert(sortidx(["x",1,[],0,"abc",true])==[5,3,1,4,0,2]);
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}
test_sortidx();
Sort debugging and optimizing There were bugs in the previous sorting functions. They didn't check the homogeneity of the input list before calling _sort_scalars and _sort_vectors. The bug might result in wrong order and missing list elements in the output. Besides correcting the bug a recode of all sorting functions result in better performance and a enlargement of their scope. With the new functions, list of vectors of any dimension may be sorted, even with idx given, with the native comparison operators. The scope of indexed sorting is also extended. The file test_arrays has been extended to check the new funcionality. New functions: is_homogeneous - checks if a list has elements of the same type (although not distinguing booleans from numbers) up to a given depth _sort_vectors - internal function to sort homgeneous lists of vectors using native comparison operators; extends the scope of the previous _sort_vectors# functions with better performance _lexical_sort - internal function to sort non-homogeneous lists; uses compare_vals _indexed_sort - internal function to perform indexed sorting of non-homogeneous lists; uses compar_vals Changed/reviewed functions: _valid_idx - doesn't requires the input of imin and imax args sort - explores the internal functions to get better performance and an enlarged scope sortidx - explores the internal functions to get better performance and an enlarged scope _sort_general - just for sortings of non-homogeneous lists using compare_vals _array_dim_recurse - changed for bit better performance Functions eliminated: _sort_vectors1 _sort_vectors2 _sort_vectors3 _sort_vectors4
2020-08-30 11:12:36 +00:00
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module test_unique() {
assert(unique([]) == []);
assert(unique([8]) == [8]);
assert(unique([7,3,9,4,3,1,8]) == [1,3,4,7,8,9]);
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}
test_unique();
module test_unique_count() {
assert_equal(
unique_count([3,1,4,1,5,9,2,6,5,3,5,8,9,7,9,3,2,3,6]),
[[1,2,3,4,5,6,7,8,9],[2,2,4,1,3,2,1,1,3]]
);
assert_equal(
unique_count(["A","B","R","A","C","A","D","A","B","R","A"]),
[["A","B","C","D","R"],[5,2,1,1,2]]
);
}
test_unique_count();
// Sets
module test_set_union() {
assert_equal(
set_union([2,3,5,7,11], [1,2,3,5,8]),
[2,3,5,7,11,1,8]
);
assert_equal(
set_union([2,3,5,7,11], [1,2,3,5,8], get_indices=true),
[[5,0,1,2,6],[2,3,5,7,11,1,8]]
);
}
test_set_union();
module test_set_difference() {
assert_equal(
set_difference([2,3,5,7,11], [1,2,3,5,8]),
[7,11]
);
}
test_set_difference();
module test_set_intersection() {
assert_equal(
set_intersection([2,3,5,7,11], [1,2,3,5,8]),
[2,3,5]
);
}
test_set_intersection();
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// Arrays
module test_add_scalar() {
assert(add_scalar([1,2,3],3) == [4,5,6]);
assert(add_scalar([[1,2,3],[3,4,5]],3) == [[4,5,6],[6,7,8]]);
}
test_add_scalar();
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module test_subindex() {
v = [[1,2,3,4],[5,6,7,8],[9,10,11,12],[13,14,15,16]];
assert(subindex(v,2) == [3, 7, 11, 15]);
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assert(subindex(v,[2]) == [[3], [7], [11], [15]]);
assert(subindex(v,[2,1]) == [[3, 2], [7, 6], [11, 10], [15, 14]]);
assert(subindex(v,[1:3]) == [[2, 3, 4], [6, 7, 8], [10, 11, 12], [14, 15, 16]]);
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}
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test_subindex();
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// Need decision about behavior for out of bounds ranges, empty ranges
module test_submatrix(){
M = [[1,2,3,4,5],
[6,7,8,9,10],
[11,12,13,14,15],
[16,17,18,19,20],
[21,22,23,24,25]];
assert_equal(submatrix(M,[1:2], [3:4]), [[9,10],[14,15]]);
assert_equal(submatrix(M,[1], [3,4]), [[9,10]]);
assert_equal(submatrix(M,1, [3,4]), [[9,10]]);
assert_equal(submatrix(M, [3,4],1), [[17],[22]]);
assert_equal(submatrix(M, [1,3],[2,4]), [[8,10],[18,20]]);
assert_equal(submatrix(M, 1,3), [[9]]);
A = [[true, 17, "test"],
[[4,2], 91, false],
[6, [3,4], undef]];
assert_equal(submatrix(A,[0,2],[1,2]),[[17, "test"], [[3, 4], undef]]);
}
test_submatrix();
module test_force_list() {
assert_equal(force_list([3,4,5]), [3,4,5]);
assert_equal(force_list(5), [5]);
assert_equal(force_list(7, n=3), [7,7,7]);
assert_equal(force_list(4, n=3, fill=1), [4,1,1]);
}
test_force_list();
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module test_pair() {
assert(pair([3,4,5,6]) == [[3,4], [4,5], [5,6]]);
assert(pair("ABCD") == [["A","B"], ["B","C"], ["C","D"]]);
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}
test_pair();
module test_pair_wrap() {
assert(pair_wrap([3,4,5,6]) == [[3,4], [4,5], [5,6], [6,3]]);
assert(pair_wrap("ABCD") == [["A","B"], ["B","C"], ["C","D"], ["D","A"]]);
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}
test_pair_wrap();
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module test_triplet() {
assert(triplet([3,4,5,6,7]) == [[3,4,5], [4,5,6], [5,6,7]]);
assert(triplet("ABCDE") == [["A","B","C"], ["B","C","D"], ["C","D","E"]]);
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}
test_triplet();
module test_triplet_wrap() {
assert(triplet_wrap([3,4,5,6]) == [[3,4,5], [4,5,6], [5,6,3], [6,3,4]]);
assert(triplet_wrap("ABCD") == [["A","B","C"], ["B","C","D"], ["C","D","A"], ["D","A","B"]]);
2019-10-23 00:10:04 +00:00
}
test_triplet_wrap();
module test_permute() {
assert(permute([3,4,5,6]) == [[3,4],[3,5],[3,6],[4,5],[4,6],[5,6]]);
assert(permute([3,4,5,6],n=3) == [[3,4,5],[3,4,6],[3,5,6],[4,5,6]]);
}
test_permute();
module test_repeat_entries() {
list = [0,1,2,3];
assert(repeat_entries(list, 6) == [0,0,1,2,2,3]);
assert(repeat_entries(list, 6, exact=false) == [0,0,1,1,2,2,3,3]);
assert(repeat_entries(list, [1,1,2,1], exact=false) == [0,1,2,2,3]);
}
test_repeat_entries();
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module test_zip() {
v1 = [1,2,3,4];
v2 = [5,6,7];
v3 = [8,9,10,11];
assert(zip(v1,v3) == [[1,8],[2,9],[3,10],[4,11]]);
assert(zip([v1,v3]) == [[1,8],[2,9],[3,10],[4,11]]);
assert(zip([v1,v2],fit="short") == [[1,5],[2,6],[3,7]]);
assert(zip([v1,v2],fit="long") == [[1,5],[2,6],[3,7],[4,undef]]);
assert(zip([v1,v2],fit="long", fill=0) == [[1,5],[2,6],[3,7],[4,0]]);
assert(zip([v1,v2,v3],fit="long") == [[1,5,8],[2,6,9],[3,7,10],[4,undef,11]]);
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}
test_zip();
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module test_block_matrix() {
A = [[1,2],[3,4]];
B = ident(2);
assert_equal(block_matrix([[A,B],[B,A],[A,B]]), [[1,2,1,0],[3,4,0,1],[1,0,1,2],[0,1,3,4],[1,2,1,0],[3,4,0,1]]);
assert_equal(block_matrix([[A,B],ident(4)]), [[1,2,1,0],[3,4,0,1],[1,0,0,0],[0,1,0,0],[0,0,1,0],[0,0,0,1]]);
text = [["a","b"],["c","d"]];
assert_equal(block_matrix([[text,B]]), [["a","b",1,0],["c","d",0,1]]);
}
test_block_matrix();
2020-09-01 22:38:31 +00:00
module test_diagonal_matrix() {
assert_equal(diagonal_matrix([1,2,3]), [[1,0,0],[0,2,0],[0,0,3]]);
assert_equal(diagonal_matrix([1,"c",2]), [[1,0,0],[0,"c",0],[0,0,2]]);
assert_equal(diagonal_matrix([1,"c",2],"X"), [[1,"X","X"],["X","c","X"],["X","X",2]]);
assert_equal(diagonal_matrix([[1,1],[2,2],[3,3]], [0,0]), [[ [1,1],[0,0],[0,0]], [[0,0],[2,2],[0,0]], [[0,0],[0,0],[3,3]]]);
}
test_diagonal_matrix();
module test_submatrix_set() {
test = [[1,2,3,4,5],[6,7,8,9,10],[11,12,13,14,15], [16,17,18,19,20]];
ragged = [[1,2,3,4,5],[6,7,8,9,10],[11,12], [16,17]];
assert_equal(submatrix_set(test,[[9,8],[7,6]]), [[9,8,3,4,5],[7,6,8,9,10],[11,12,13,14,15], [16,17,18,19,20]]);
assert_equal(submatrix_set(test,[[9,7],[8,6]],1),[[1,2,3,4,5],[9,7,8,9,10],[8,6,13,14,15], [16,17,18,19,20]]);
assert_equal(submatrix_set(test,[[9,8],[7,6]],n=1), [[1,9,8,4,5],[6,7,6,9,10],[11,12,13,14,15], [16,17,18,19,20]]);
assert_equal(submatrix_set(test,[[9,8],[7,6]],1,2), [[1,2,3,4,5],[6,7,9,8,10],[11,12,7,6,15], [16,17,18,19,20]]);
assert_equal(submatrix_set(test,[[9,8],[7,6]],-1,-1), [[6,2,3,4,5],[6,7,8,9,10],[11,12,13,14,15], [16,17,18,19,20]]);
assert_equal(submatrix_set(test,[[9,8],[7,6]],n=4), [[1,2,3,4,9],[6,7,8,9,7],[11,12,13,14,15], [16,17,18,19,20]]);
assert_equal(submatrix_set(test,[[9,8],[7,6]],7,7), [[1,2,3,4,5],[6,7,8,9,10],[11,12,13,14,15], [16,17,18,19,20]]);
assert_equal(submatrix_set(ragged, [["a","b"],["c","d"]], 1, 1), [[1,2,3,4,5],[6,"a","b",9,10],[11,"c"], [16,17]]);
assert_equal(submatrix_set(test, [[]]), test);
}
test_submatrix_set();
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module test_array_group() {
v = [1,2,3,4,5,6];
assert(array_group(v,2) == [[1,2], [3,4], [5,6]]);
assert(array_group(v,3) == [[1,2,3], [4,5,6]]);
assert(array_group(v,4,0) == [[1,2,3,4], [5,6,0,0]]);
2019-05-01 06:45:05 +00:00
}
test_array_group();
module test_flatten() {
assert(flatten([[1,2,3], [4,5,[6,7,8]]]) == [1,2,3,4,5,[6,7,8]]);
2020-07-28 18:02:35 +00:00
assert(flatten([]) == []);
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}
test_flatten();
2020-07-28 18:02:35 +00:00
module test_full_flatten() {
assert(full_flatten([[1,2,3], [4,5,[6,[7],8]]]) == [1,2,3,4,5,6,7,8]);
assert(full_flatten([]) == []);
}
test_full_flatten();
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module test_array_dim() {
assert(array_dim([[[1,2,3],[4,5,6]],[[7,8,9],[10,11,12]]]) == [2,2,3]);
assert(array_dim([[[1,2,3],[4,5,6]],[[7,8,9],[10,11,12]]], 0) == 2);
assert(array_dim([[[1,2,3],[4,5,6]],[[7,8,9],[10,11,12]]], 2) == 3);
assert(array_dim([[[1,2,3],[4,5,6]],[[7,8,9]]]) == [2,undef,3]);
Sort debugging and optimizing There were bugs in the previous sorting functions. They didn't check the homogeneity of the input list before calling _sort_scalars and _sort_vectors. The bug might result in wrong order and missing list elements in the output. Besides correcting the bug a recode of all sorting functions result in better performance and a enlargement of their scope. With the new functions, list of vectors of any dimension may be sorted, even with idx given, with the native comparison operators. The scope of indexed sorting is also extended. The file test_arrays has been extended to check the new funcionality. New functions: is_homogeneous - checks if a list has elements of the same type (although not distinguing booleans from numbers) up to a given depth _sort_vectors - internal function to sort homgeneous lists of vectors using native comparison operators; extends the scope of the previous _sort_vectors# functions with better performance _lexical_sort - internal function to sort non-homogeneous lists; uses compare_vals _indexed_sort - internal function to perform indexed sorting of non-homogeneous lists; uses compar_vals Changed/reviewed functions: _valid_idx - doesn't requires the input of imin and imax args sort - explores the internal functions to get better performance and an enlarged scope sortidx - explores the internal functions to get better performance and an enlarged scope _sort_general - just for sortings of non-homogeneous lists using compare_vals _array_dim_recurse - changed for bit better performance Functions eliminated: _sort_vectors1 _sort_vectors2 _sort_vectors3 _sort_vectors4
2020-08-30 11:12:36 +00:00
assert(array_dim([1,2,3,4,5,6,7,8,9]) == [9]);
assert(array_dim([[1],[2],[3],[4],[5],[6],[7],[8],[9]]) == [9,1]);
assert(array_dim([]) == [0]);
assert(array_dim([[]]) == [1,0]);
assert(array_dim([[],[]]) == [2,0]);
assert(array_dim([[],[1]]) == [2,undef]);
2019-05-01 06:45:05 +00:00
}
test_array_dim();
module test_transpose() {
assert(transpose([[1,2,3],[4,5,6],[7,8,9]]) == [[1,4,7],[2,5,8],[3,6,9]]);
assert(transpose([[1,2,3],[4,5,6]]) == [[1,4],[2,5],[3,6]]);
assert(transpose([[1,2,3],[4,5,6]],reverse=true) == [[6,3], [5,2], [4,1]]);
assert(transpose([3,4,5]) == [3,4,5]);
}
test_transpose();
// vim: expandtab tabstop=4 shiftwidth=4 softtabstop=4 nowrap