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Release v0.1.0
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@stdlib-bot
stdlib-bot committed Oct 14, 2023
1 parent 20049e5 commit 130d9f5
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Showing 5 changed files with 17 additions and 318 deletions.
12 changes: 10 additions & 2 deletions .github/workflows/publish.yml
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Expand Up @@ -182,7 +182,11 @@ jobs:
fi
# Trim leading and trailing whitespace:
dep=$(echo "$dep" | xargs)
version="^$(npm view $dep version)"
version="$(npm view $dep version)"
if [[ -z "$version" ]]; then
continue
fi
version="^$version"
jq -r --arg dep "$dep" --arg version "$version" '.dependencies[$dep] = $version' package.json > package.json.tmp
mv package.json.tmp package.json
done
Expand All @@ -192,7 +196,11 @@ jobs:
fi
# Trim leading and trailing whitespace:
dep=$(echo "$dep" | xargs)
version="^$(npm view $dep version)"
version="$(npm view $dep version)"
if [[ -z "$version" ]]; then
continue
fi
version="^$version"
jq -r --arg dep "$dep" --arg version "$version" '.devDependencies[$dep] = $version' package.json > package.json.tmp
mv package.json.tmp package.json
done
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4 changes: 2 additions & 2 deletions README.md
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Expand Up @@ -204,8 +204,8 @@ Copyright © 2016-2023. The Stdlib [Authors][stdlib-authors].
[npm-image]: http://img.shields.io/npm/v/@stdlib/ndarray-strides.svg
[npm-url]: https://npmjs.org/package/@stdlib/ndarray-strides

[test-image]: https://github.com/stdlib-js/ndarray-strides/actions/workflows/test.yml/badge.svg?branch=main
[test-url]: https://github.com/stdlib-js/ndarray-strides/actions/workflows/test.yml?query=branch:main
[test-image]: https://github.com/stdlib-js/ndarray-strides/actions/workflows/test.yml/badge.svg?branch=v0.1.0
[test-url]: https://github.com/stdlib-js/ndarray-strides/actions/workflows/test.yml?query=branch:v0.1.0

[coverage-image]: https://img.shields.io/codecov/c/github/stdlib-js/ndarray-strides/main.svg
[coverage-url]: https://codecov.io/github/stdlib-js/ndarray-strides?branch=main
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2 changes: 1 addition & 1 deletion dist/index.js
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2 changes: 1 addition & 1 deletion package.json
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@@ -1,6 +1,6 @@
{
"name": "@stdlib/ndarray-strides",
"version": "0.0.0",
"version": "0.1.0",
"description": "Return the strides of a provided ndarray.",
"license": "Apache-2.0",
"author": {
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315 changes: 3 additions & 312 deletions test/dist/test.js
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Expand Up @@ -21,322 +21,13 @@
// MODULES //

var tape = require( 'tape' );
var zeros = require( '@stdlib/ndarray-zeros' );
var strides = require( './../../dist' );
var main = require( './../../dist' );


// TESTS //

tape( 'main export is a function', function test( t ) {
tape( 'main export is defined', function test( t ) {
t.ok( true, __filename );
t.strictEqual( typeof strides, 'function', 'main export is a function' );
t.end();
});

tape( 'the function throws an error if not provided a minimal ndarray-like object', function test( t ) {
var values;
var i;

values = [
'5',
5,
NaN,
true,
false,
null,
void 0,
{},
function noop() {},
{
'strides': 3.14
},
{
'strides': -1
},
{
'strides': null
},
{
'strides': {}
},
{
'strides': [ 3.14 ]
},
{
'strides': [ -1.5 ]
},
{
'shape': null
},
{
'shape': {}
}
];
for ( i = 0; i < values.length; i++ ) {
t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
}
t.end();

function badValue( value ) {
return function badValue() {
strides( value );
};
}
});

tape( 'if provided a zero-dimensional ndarray, the function returns a single-element strides array', function test( t ) {
t.deepEqual( strides( zeros( [] ) ), [ 0 ], 'returns expected value' );
t.end();
});

tape( 'if provided a zero-dimensional minimal ndarray-like object, the function returns a single-element strides array', function test( t ) {
var x = {
'shape': []
};
t.deepEqual( strides( x ), [ 0 ], 'returns expected value' );
t.end();
});

tape( 'the function returns the strides of an ndarray (row-major)', function test( t ) {
var expected;
var values;
var out;
var i;

values = [
zeros( [ 3, 3, 3 ], {
'order': 'row-major'
}),
zeros( [ 1, 1 ], {
'order': 'row-major'
}),
zeros( [ 3, 3, 0, 3 ], {
'order': 'row-major'
}),
zeros( [ 1, 2, 3, 4 ], {
'order': 'row-major'
}),
zeros( [ 5 ], {
'order': 'row-major'
})
];

expected = [
values[ 0 ].strides,
values[ 1 ].strides,
values[ 2 ].strides,
values[ 3 ].strides,
values[ 4 ].strides
];

for ( i = 0; i < values.length; i++ ) {
out = strides( values[ i ] );
t.deepEqual( out, expected[ i ], 'returns expected value for strides '+values[ i ].strides.join( 'x' ) );
}
t.end();
});

tape( 'the function returns the strides of an ndarray (column-major)', function test( t ) {
var expected;
var values;
var out;
var i;

values = [
zeros( [ 3, 3, 3 ], {
'order': 'column-major'
}),
zeros( [ 1, 1 ], {
'order': 'column-major'
}),
zeros( [ 3, 3, 0, 3 ], {
'order': 'column-major'
}),
zeros( [ 1, 2, 3, 4 ], {
'order': 'column-major'
}),
zeros( [ 5 ], {
'order': 'column-major'
})
];

expected = [
values[ 0 ].strides,
values[ 1 ].strides,
values[ 2 ].strides,
values[ 3 ].strides,
values[ 4 ].strides
];

for ( i = 0; i < values.length; i++ ) {
out = strides( values[ i ] );
t.deepEqual( out, expected[ i ], 'returns expected value for strides '+values[ i ].strides.join( 'x' ) );
}
t.end();
});

tape( 'the function accepts minimal ndarray-like objects (strides)', function test( t ) {
var expected;
var values;
var out;
var i;

values = [
{
'strides': [ 9, 3, 1 ]
},
{
'strides': [ 1, 1 ]
},
{
'strides': [ 27, 9, 0, 3 ]
},
{
'strides': [ 48, 24, 12, 4 ]
},
{
'strides': [ 5 ]
}
];

expected = [
values[ 0 ].strides,
values[ 1 ].strides,
values[ 2 ].strides,
values[ 3 ].strides,
values[ 4 ].strides
];

for ( i = 0; i < values.length; i++ ) {
out = strides( values[ i ] );
t.deepEqual( out, expected[ i ], 'returns expected value for strides '+values[ i ].strides.join( 'x' ) );
}
t.end();
});

tape( 'the function accepts minimal ndarray-like objects (shape)', function test( t ) {
var expected;
var values;
var out;
var i;

values = [
{
'shape': [ 3, 3, 3 ]
},
{
'shape': [ 1, 1 ]
},
{
'shape': [ 3, 3, 0, 3 ]
},
{
'shape': [ 1, 2, 3, 4 ]
},
{
'shape': [ 5 ]
}
];

expected = [
[ 9, 3, 1 ],
[ 1, 1 ],
[ 0, 0, 3, 1 ],
[ 24, 12, 4, 1 ],
[ 1 ]
];

for ( i = 0; i < values.length; i++ ) {
out = strides( values[ i ] );
t.deepEqual( out, expected[ i ], 'returns expected value for shape '+values[ i ].shape.join( 'x' ) );
}
t.end();
});

tape( 'the function accepts minimal ndarray-like objects (shape, order=row-major)', function test( t ) {
var expected;
var values;
var out;
var i;

values = [
{
'shape': [ 3, 3, 3 ],
'order': 'row-major'
},
{
'shape': [ 1, 1 ],
'order': 'row-major'
},
{
'shape': [ 3, 3, 0, 3 ],
'order': 'row-major'
},
{
'shape': [ 1, 2, 3, 4 ],
'order': 'row-major'
},
{
'shape': [ 5 ],
'order': 'row-major'
}
];

expected = [
[ 9, 3, 1 ],
[ 1, 1 ],
[ 0, 0, 3, 1 ],
[ 24, 12, 4, 1 ],
[ 1 ]
];

for ( i = 0; i < values.length; i++ ) {
out = strides( values[ i ] );
t.deepEqual( out, expected[ i ], 'returns expected value for shape '+values[ i ].shape.join( 'x' ) );
}
t.end();
});

tape( 'the function accepts minimal ndarray-like objects (shape, order=column-major)', function test( t ) {
var expected;
var values;
var out;
var i;

values = [
{
'shape': [ 3, 3, 3 ],
'order': 'column-major'
},
{
'shape': [ 1, 1 ],
'order': 'column-major'
},
{
'shape': [ 3, 3, 0, 3 ],
'order': 'column-major'
},
{
'shape': [ 1, 2, 3, 4 ],
'order': 'column-major'
},
{
'shape': [ 5 ],
'order': 'column-major'
}
];

expected = [
[ 1, 3, 9 ],
[ 1, 1 ],
[ 1, 3, 9, 0 ],
[ 1, 1, 2, 6 ],
[ 1 ]
];

for ( i = 0; i < values.length; i++ ) {
out = strides( values[ i ] );
t.deepEqual( out, expected[ i ], 'returns expected value for shape '+values[ i ].shape.join( 'x' ) );
}
t.strictEqual( main !== void 0, true, 'main export is defined' );
t.end();
});

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