Page Menu
Home
c4science
Search
Configure Global Search
Log In
Files
F101798774
deterministicGrouping.js
No One
Temporary
Actions
Download File
Edit File
Delete File
View Transforms
Subscribe
Mute Notifications
Award Token
Subscribers
None
File Metadata
Details
File Info
Storage
Attached
Created
Thu, Feb 13, 19:54
Size
11 KB
Mime Type
text/x-c++
Expires
Sat, Feb 15, 19:54 (2 d)
Engine
blob
Format
Raw Data
Handle
24232673
Attached To
rOACCT Open Access Compliance Check Tool (OACCT)
deterministicGrouping.js
View Options
/*
MIT License http://www.opensource.org/licenses/mit-license.php
Author Tobias Koppers @sokra
*/
"use strict"
;
// Simulations show these probabilities for a single change
// 93.1% that one group is invalidated
// 4.8% that two groups are invalidated
// 1.1% that 3 groups are invalidated
// 0.1% that 4 or more groups are invalidated
//
// And these for removing/adding 10 lexically adjacent files
// 64.5% that one group is invalidated
// 24.8% that two groups are invalidated
// 7.8% that 3 groups are invalidated
// 2.7% that 4 or more groups are invalidated
//
// And these for removing/adding 3 random files
// 0% that one group is invalidated
// 3.7% that two groups are invalidated
// 80.8% that 3 groups are invalidated
// 12.3% that 4 groups are invalidated
// 3.2% that 5 or more groups are invalidated
/**
*
* @param {string} a key
* @param {string} b key
* @returns {number} the similarity as number
*/
const
similarity
=
(
a
,
b
)
=>
{
const
l
=
Math
.
min
(
a
.
length
,
b
.
length
);
let
dist
=
0
;
for
(
let
i
=
0
;
i
<
l
;
i
++
)
{
const
ca
=
a
.
charCodeAt
(
i
);
const
cb
=
b
.
charCodeAt
(
i
);
dist
+=
Math
.
max
(
0
,
10
-
Math
.
abs
(
ca
-
cb
));
}
return
dist
;
};
/**
* @param {string} a key
* @param {string} b key
* @param {Set<string>} usedNames set of already used names
* @returns {string} the common part and a single char for the difference
*/
const
getName
=
(
a
,
b
,
usedNames
)
=>
{
const
l
=
Math
.
min
(
a
.
length
,
b
.
length
);
let
i
=
0
;
while
(
i
<
l
)
{
if
(
a
.
charCodeAt
(
i
)
!==
b
.
charCodeAt
(
i
))
{
i
++
;
break
;
}
i
++
;
}
while
(
i
<
l
)
{
const
name
=
a
.
slice
(
0
,
i
);
const
lowerName
=
name
.
toLowerCase
();
if
(
!
usedNames
.
has
(
lowerName
))
{
usedNames
.
add
(
lowerName
);
return
name
;
}
i
++
;
}
// names always contain a hash, so this is always unique
// we don't need to check usedNames nor add it
return
a
;
};
/**
* @param {Record<string, number>} total total size
* @param {Record<string, number>} size single size
* @returns {void}
*/
const
addSizeTo
=
(
total
,
size
)
=>
{
for
(
const
key
of
Object
.
keys
(
size
))
{
total
[
key
]
=
(
total
[
key
]
||
0
)
+
size
[
key
];
}
};
/**
* @param {Iterable<Node>} nodes some nodes
* @returns {Record<string, number>} total size
*/
const
sumSize
=
nodes
=>
{
const
sum
=
Object
.
create
(
null
);
for
(
const
node
of
nodes
)
{
addSizeTo
(
sum
,
node
.
size
);
}
return
sum
;
};
const
isTooBig
=
(
size
,
maxSize
)
=>
{
for
(
const
key
of
Object
.
keys
(
size
))
{
const
maxSizeValue
=
maxSize
[
key
];
if
(
typeof
maxSizeValue
===
"number"
)
{
if
(
size
[
key
]
>
maxSizeValue
)
return
true
;
}
}
return
false
;
};
const
isTooSmall
=
(
size
,
minSize
)
=>
{
for
(
const
key
of
Object
.
keys
(
size
))
{
const
minSizeValue
=
minSize
[
key
];
if
(
typeof
minSizeValue
===
"number"
)
{
if
(
size
[
key
]
<
minSizeValue
)
return
true
;
}
}
return
false
;
};
const
getToSmallTypes
=
(
size
,
minSize
)
=>
{
const
types
=
new
Set
();
for
(
const
key
of
Object
.
keys
(
size
))
{
const
minSizeValue
=
minSize
[
key
];
if
(
typeof
minSizeValue
===
"number"
)
{
if
(
size
[
key
]
<
minSizeValue
)
types
.
add
(
key
);
}
}
return
types
;
};
const
getNumberOfMatchingSizeTypes
=
(
size
,
types
)
=>
{
let
i
=
0
;
for
(
const
key
of
Object
.
keys
(
size
))
{
if
(
types
.
has
(
key
))
i
++
;
}
return
i
;
};
const
selectiveSizeSum
=
(
size
,
types
)
=>
{
let
sum
=
0
;
for
(
const
key
of
Object
.
keys
(
size
))
{
if
(
types
.
has
(
key
))
sum
+=
size
[
key
];
}
return
sum
;
};
/**
* @template T
*/
class
Node
{
/**
* @param {T} item item
* @param {string} key key
* @param {Record<string, number>} size size
*/
constructor
(
item
,
key
,
size
)
{
this
.
item
=
item
;
this
.
key
=
key
;
this
.
size
=
size
;
}
}
/**
* @template T
*/
class
Group
{
/**
* @param {Node<T>[]} nodes nodes
* @param {number[]} similarities similarities between the nodes (length = nodes.length - 1)
* @param {Record<string, number>=} size size of the group
*/
constructor
(
nodes
,
similarities
,
size
)
{
this
.
nodes
=
nodes
;
this
.
similarities
=
similarities
;
this
.
size
=
size
||
sumSize
(
nodes
);
/** @type {string} */
this
.
key
=
undefined
;
}
/**
* @param {function(Node): boolean} filter filter function
* @returns {Node[]} removed nodes
*/
popNodes
(
filter
)
{
const
newNodes
=
[];
const
newSimilarities
=
[];
const
resultNodes
=
[];
let
lastNode
;
for
(
let
i
=
0
;
i
<
this
.
nodes
.
length
;
i
++
)
{
const
node
=
this
.
nodes
[
i
];
if
(
filter
(
node
))
{
resultNodes
.
push
(
node
);
}
else
{
if
(
newNodes
.
length
>
0
)
{
newSimilarities
.
push
(
lastNode
===
this
.
nodes
[
i
-
1
]
?
this
.
similarities
[
i
-
1
]
:
similarity
(
lastNode
.
key
,
node
.
key
)
);
}
newNodes
.
push
(
node
);
lastNode
=
node
;
}
}
this
.
nodes
=
newNodes
;
this
.
similarities
=
newSimilarities
;
this
.
size
=
sumSize
(
newNodes
);
return
resultNodes
;
}
}
/**
* @param {Iterable<Node>} nodes nodes
* @returns {number[]} similarities
*/
const
getSimilarities
=
nodes
=>
{
// calculate similarities between lexically adjacent nodes
/** @type {number[]} */
const
similarities
=
[];
let
last
=
undefined
;
for
(
const
node
of
nodes
)
{
if
(
last
!==
undefined
)
{
similarities
.
push
(
similarity
(
last
.
key
,
node
.
key
));
}
last
=
node
;
}
return
similarities
;
};
/**
* @template T
* @typedef {Object} GroupedItems<T>
* @property {string} key
* @property {T[]} items
* @property {Record<string, number>} size
*/
/**
* @template T
* @typedef {Object} Options
* @property {Record<string, number>} maxSize maximum size of a group
* @property {Record<string, number>} minSize minimum size of a group (preferred over maximum size)
* @property {Iterable<T>} items a list of items
* @property {function(T): Record<string, number>} getSize function to get size of an item
* @property {function(T): string} getKey function to get the key of an item
*/
/**
* @template T
* @param {Options<T>} options options object
* @returns {GroupedItems<T>[]} grouped items
*/
module
.
exports
=
({
maxSize
,
minSize
,
items
,
getSize
,
getKey
})
=>
{
/** @type {Group<T>[]} */
const
result
=
[];
const
nodes
=
Array
.
from
(
items
,
item
=>
new
Node
(
item
,
getKey
(
item
),
getSize
(
item
))
);
/** @type {Node<T>[]} */
const
initialNodes
=
[];
// lexically ordering of keys
nodes
.
sort
((
a
,
b
)
=>
{
if
(
a
.
key
<
b
.
key
)
return
-
1
;
if
(
a
.
key
>
b
.
key
)
return
1
;
return
0
;
});
// return nodes bigger than maxSize directly as group
// But make sure that minSize is not violated
for
(
const
node
of
nodes
)
{
if
(
isTooBig
(
node
.
size
,
maxSize
)
&&
!
isTooSmall
(
node
.
size
,
minSize
))
{
result
.
push
(
new
Group
([
node
],
[]));
}
else
{
initialNodes
.
push
(
node
);
}
}
if
(
initialNodes
.
length
>
0
)
{
const
initialGroup
=
new
Group
(
initialNodes
,
getSimilarities
(
initialNodes
));
const
problemTypes
=
getToSmallTypes
(
initialGroup
.
size
,
minSize
);
if
(
problemTypes
.
size
>
0
)
{
// We hit an edge case where the working set is already smaller than minSize
// We merge problematic nodes with the smallest result node to keep minSize intact
const
problemNodes
=
initialGroup
.
popNodes
(
n
=>
getNumberOfMatchingSizeTypes
(
n
.
size
,
problemTypes
)
>
0
);
// Only merge it with result nodes that have the problematic size type
const
possibleResultGroups
=
result
.
filter
(
n
=>
getNumberOfMatchingSizeTypes
(
n
.
size
,
problemTypes
)
>
0
);
if
(
possibleResultGroups
.
length
>
0
)
{
const
bestGroup
=
possibleResultGroups
.
reduce
((
min
,
group
)
=>
{
const
minMatches
=
getNumberOfMatchingSizeTypes
(
min
,
problemTypes
);
const
groupMatches
=
getNumberOfMatchingSizeTypes
(
group
,
problemTypes
);
if
(
minMatches
!==
groupMatches
)
return
minMatches
<
groupMatches
?
group
:
min
;
if
(
selectiveSizeSum
(
min
.
size
,
problemTypes
)
>
selectiveSizeSum
(
group
.
size
,
problemTypes
)
)
return
group
;
return
min
;
});
for
(
const
node
of
problemNodes
)
bestGroup
.
nodes
.
push
(
node
);
bestGroup
.
nodes
.
sort
((
a
,
b
)
=>
{
if
(
a
.
key
<
b
.
key
)
return
-
1
;
if
(
a
.
key
>
b
.
key
)
return
1
;
return
0
;
});
}
else
{
// There are no other nodes with the same size types
// We create a new group and have to accept that it's smaller than minSize
result
.
push
(
new
Group
(
problemNodes
,
null
));
}
}
if
(
initialGroup
.
nodes
.
length
>
0
)
{
const
queue
=
[
initialGroup
];
while
(
queue
.
length
)
{
const
group
=
queue
.
pop
();
// only groups bigger than maxSize need to be splitted
if
(
!
isTooBig
(
group
.
size
,
maxSize
))
{
result
.
push
(
group
);
continue
;
}
// find unsplittable area from left and right
// going minSize from left and right
// at least one node need to be included otherwise we get stuck
let
left
=
1
;
let
leftSize
=
Object
.
create
(
null
);
addSizeTo
(
leftSize
,
group
.
nodes
[
0
].
size
);
while
(
isTooSmall
(
leftSize
,
minSize
))
{
addSizeTo
(
leftSize
,
group
.
nodes
[
left
].
size
);
left
++
;
}
let
right
=
group
.
nodes
.
length
-
2
;
let
rightSize
=
Object
.
create
(
null
);
addSizeTo
(
rightSize
,
group
.
nodes
[
group
.
nodes
.
length
-
1
].
size
);
while
(
isTooSmall
(
rightSize
,
minSize
))
{
addSizeTo
(
rightSize
,
group
.
nodes
[
right
].
size
);
right
--
;
}
if
(
left
-
1
>
right
)
{
// can't split group while holding minSize
// because minSize is preferred of maxSize we return
// the problematic nodes as result here even while it's too big
// To avoid this make sure maxSize > minSize * 3
result
.
push
(
group
);
continue
;
}
if
(
left
<=
right
)
{
// when there is a area between left and right
// we look for best split point
// we split at the minimum similarity
// here key space is separated the most
let
best
=
left
-
1
;
let
bestSimilarity
=
group
.
similarities
[
best
];
for
(
let
i
=
left
;
i
<=
right
;
i
++
)
{
const
similarity
=
group
.
similarities
[
i
];
if
(
similarity
<
bestSimilarity
)
{
best
=
i
;
bestSimilarity
=
similarity
;
}
}
left
=
best
+
1
;
right
=
best
;
}
// create two new groups for left and right area
// and queue them up
const
rightNodes
=
[
group
.
nodes
[
right
+
1
]];
/** @type {number[]} */
const
rightSimilarities
=
[];
for
(
let
i
=
right
+
2
;
i
<
group
.
nodes
.
length
;
i
++
)
{
rightSimilarities
.
push
(
group
.
similarities
[
i
-
1
]);
rightNodes
.
push
(
group
.
nodes
[
i
]);
}
queue
.
push
(
new
Group
(
rightNodes
,
rightSimilarities
));
const
leftNodes
=
[
group
.
nodes
[
0
]];
/** @type {number[]} */
const
leftSimilarities
=
[];
for
(
let
i
=
1
;
i
<
left
;
i
++
)
{
leftSimilarities
.
push
(
group
.
similarities
[
i
-
1
]);
leftNodes
.
push
(
group
.
nodes
[
i
]);
}
queue
.
push
(
new
Group
(
leftNodes
,
leftSimilarities
));
}
}
}
// lexically ordering
result
.
sort
((
a
,
b
)
=>
{
if
(
a
.
nodes
[
0
].
key
<
b
.
nodes
[
0
].
key
)
return
-
1
;
if
(
a
.
nodes
[
0
].
key
>
b
.
nodes
[
0
].
key
)
return
1
;
return
0
;
});
// give every group a name
const
usedNames
=
new
Set
();
for
(
let
i
=
0
;
i
<
result
.
length
;
i
++
)
{
const
group
=
result
[
i
];
if
(
group
.
nodes
.
length
===
1
)
{
group
.
key
=
group
.
nodes
[
0
].
key
;
}
else
{
const
first
=
group
.
nodes
[
0
];
const
last
=
group
.
nodes
[
group
.
nodes
.
length
-
1
];
const
name
=
getName
(
first
.
key
,
last
.
key
,
usedNames
);
group
.
key
=
name
;
}
}
// return the results
return
result
.
map
(
group
=>
{
/** @type {GroupedItems} */
return
{
key
:
group
.
key
,
items
:
group
.
nodes
.
map
(
node
=>
node
.
item
),
size
:
group
.
size
};
});
};
Event Timeline
Log In to Comment