Skip to content
GitLab
Explore
Sign in
Primary navigation
Search or go to…
Project
A
Advent of Coding
Manage
Activity
Members
Labels
Plan
Issues
Issue boards
Milestones
Wiki
Code
Merge requests
Repository
Branches
Commits
Tags
Repository graph
Compare revisions
Snippets
Build
Pipelines
Jobs
Pipeline schedules
Artifacts
Deploy
Releases
Package registry
Container registry
Model registry
Operate
Environments
Terraform modules
Monitor
Incidents
Service Desk
Analyze
Value stream analytics
Contributor analytics
CI/CD analytics
Repository analytics
Model experiments
Help
Help
Support
GitLab documentation
Compare GitLab plans
GitLab community forum
Contribute to GitLab
Provide feedback
Keyboard shortcuts
?
Snippets
Groups
Projects
Show more breadcrumbs
Christopher Bohn
Advent of Coding
Commits
7047dcba
Commit
7047dcba
authored
3 years ago
by
Christopher Bohn
Browse files
Options
Downloads
Patches
Plain Diff
Day 14 in-progress.
parent
6841af35
No related branches found
No related tags found
No related merge requests found
Changes
2
Show whitespace changes
Inline
Side-by-side
Showing
2 changed files
2021/README.md
+29
-1
29 additions, 1 deletion
2021/README.md
2021/src/main/java/edu/unl/cse/bohn/year2021/Day14.java
+122
-0
122 additions, 0 deletions
2021/src/main/java/edu/unl/cse/bohn/year2021/Day14.java
with
151 additions
and
1 deletion
2021/README.md
+
29
−
1
View file @
7047dcba
...
...
@@ -159,9 +159,37 @@ Hmm... part 1 took longer than I think it should have. The big-O complexity is
manageable, but I guess the constant factors are problematic.
For part 2, I'm not even going to try to algorithmically determine which letters
are created (and not just because I'd have to return so
e
mthing other than a
are created (and not just because I'd have to return som
e
thing other than a
long integer).
Hmm... part 2 really didn't take much longer than part 1 did, which suggests
the computational pain point is in parsing the data and creating the "paper"
and not in the folding.
# Day 14
Again, no fancy data structures. Just need a way to store the rules, such as a Map,
and iterate over a string.
The only interesting piece of Part 2 is trying to trip you up over integer
overflow. Since I already converted my abstract base class to long integers back
on Day 6, no big deal. That, and waiting a bit longer for the answer. Quite a bit
longer, it seems. Is there any place I can optimize? I sure hope so, since I
just hit an OutOfMemoryError on the
*sample data*
!
I don't see how I can avoid modeling the full string.
Maybe I can have the StringBuilder work on smaller chunks, thereby allowing for
more frequent garbage collection? That probably will work. I'm pretty sure that
StringBuilder has to have an underlying linked list.
That doesn't seem to be speeding things up, but hopefully it'll help with the
memory problem. (Two hours later...) memory didn't blow up, but the sample data
isn't finished processing yet. It occurs to me that I don't need to use a
StringBuilder. I can create two arrays of characters and merge them. Let's see
how that goes.
Oh, yes. This is
*much*
faster. Still taking a while to get through part 2, but
in a few seconds we got past the point that the StringBuilder approach took a
couple of hours while I was in a meeting. But we still ran out of memory when
growing the new polymer on iteration 28 of the sample data.
This diff is collapsed.
Click to expand it.
2021/src/main/java/edu/unl/cse/bohn/year2021/Day14.java
0 → 100644
+
122
−
0
View file @
7047dcba
package
edu.unl.cse.bohn.year2021
;
import
edu.unl.cse.bohn.Puzzle
;
import
java.util.Arrays
;
import
java.util.HashMap
;
import
java.util.List
;
import
java.util.Map
;
@SuppressWarnings
(
"unused"
)
public
class
Day14
extends
Puzzle
{
private
Map
<
String
,
Character
>
rules
;
public
Day14
(
boolean
isProductionReady
)
{
super
(
isProductionReady
);
sampleData
=
"""
NNCB
CH -> B
HH -> N
CB -> H
NH -> C
HB -> C
HC -> B
HN -> C
NN -> C
BH -> H
NC -> B
NB -> B
BN -> B
BB -> N
BC -> B
CC -> N
CN -> C"""
;
}
private
String
parseData
(
List
<
String
>
data
)
{
String
initialMolecule
=
data
.
get
(
0
);
rules
=
new
HashMap
<>();
for
(
String
rule
:
data
)
{
if
(
rule
.
contains
(
" -> "
))
{
String
[]
halves
=
rule
.
split
(
" -> "
);
rules
.
put
(
halves
[
0
],
halves
[
1
].
charAt
(
0
));
}
}
return
initialMolecule
;
}
@SuppressWarnings
(
"CommentedOutCode"
)
private
String
growMolecule
(
String
molecule
)
{
// StringBuilder growingMolecule = new StringBuilder();
// String pattern = "";
// for (int i = 0; i < molecule.length() - 1; i++) {
// pattern = molecule.substring(i, i + 2);
// growingMolecule.append(pattern.charAt(0)).append(rules.get(pattern));
// }
// growingMolecule.append(pattern.charAt(1));
// return growingMolecule.toString();
char
[]
oldElements
=
molecule
.
toCharArray
();
char
[]
newElements
=
new
char
[
2
*
molecule
.
length
()
-
1
];
for
(
int
i
=
0
;
i
<
oldElements
.
length
-
1
;
i
++)
{
newElements
[
2
*
i
]
=
oldElements
[
i
];
newElements
[
2
*
i
+
1
]
=
rules
.
get
(
molecule
.
substring
(
i
,
i
+
2
));
}
newElements
[
newElements
.
length
-
1
]
=
oldElements
[
oldElements
.
length
-
1
];
return
new
String
(
newElements
);
}
private
Map
<
Character
,
Long
>
countElements
(
String
molecule
)
{
Map
<
Character
,
Long
>
counts
=
new
HashMap
<>();
for
(
char
element
:
molecule
.
toCharArray
())
{
if
(!
counts
.
containsKey
(
element
))
{
counts
.
put
(
element
,
0L
);
}
counts
.
put
(
element
,
counts
.
get
(
element
)
+
1
);
}
return
counts
;
}
private
long
producePolymer
(
List
<
String
>
data
,
int
numberOfSteps
)
{
String
molecule
=
parseData
(
data
);
for
(
int
i
=
0
;
i
<
numberOfSteps
;
i
++)
{
System
.
out
.
print
(
"Molecular growth ("
+
i
+
")--\toriginal size: "
+
molecule
.
length
());
molecule
=
growMolecule
(
molecule
);
System
.
out
.
println
(
"\tnew size: "
+
molecule
.
length
());
// if (molecule.length() < 60) {
// String expectedString = switch (i) {
// case 0 -> "NCNBCHB";
// case 1 -> "NBCCNBBBCBHCB";
// case 2 -> "NBBBCNCCNBBNBNBBCHBHHBCHB";
// case 3 -> "NBBNBNBBCCNBCNCCNBBNBBNBBBNBBNBBCBHCBHHNHCBBCBHCB";
// default -> "??";
// };
// System.out.println("\texpected: " + expectedString);
// System.out.println("\t actual: " + molecule);
// assert (molecule.equals(expectedString));
// }
}
Map
<
Character
,
Long
>
elementCounts
=
countElements
(
molecule
);
char
leastFrequentElement
=
molecule
.
charAt
(
0
);
char
mostFrequentElement
=
molecule
.
charAt
(
0
);
for
(
char
element
:
elementCounts
.
keySet
())
{
if
(
elementCounts
.
get
(
element
)
<
elementCounts
.
get
(
leastFrequentElement
))
{
leastFrequentElement
=
element
;
}
if
(
elementCounts
.
get
(
element
)
>
elementCounts
.
get
(
mostFrequentElement
))
{
mostFrequentElement
=
element
;
}
}
return
elementCounts
.
get
(
mostFrequentElement
)
-
elementCounts
.
get
(
leastFrequentElement
);
}
@Override
public
long
computePart1
(
List
<
String
>
data
)
{
return
producePolymer
(
data
,
10
);
}
@Override
public
long
computePart2
(
List
<
String
>
data
)
{
return
producePolymer
(
data
,
40
);
}
}
This diff is collapsed.
Click to expand it.
Preview
0%
Loading
Try again
or
attach a new file
.
Cancel
You are about to add
0
people
to the discussion. Proceed with caution.
Finish editing this message first!
Save comment
Cancel
Please
register
or
sign in
to comment