I'm learning how to code and as a first project I thought it would be a good idea to create a little stone paper scissors game against the computer. The problem is, that obviously the computer may not show his choice, so I have to create a function, which makes a random picture x (I'm using Apple's smileys for it) appear on the position x on the screen.
So I have to:
random number between 1 and 3 var rN = GKRandomDistribution(lowestValue: 1, highestValue: 3)
let array = [opStone, opPaper, opScissors] //already declared as files
let choiceOp = array[rN]
choiceOp.position = CGPoint(x. ?, y: ?)
self.addChild(choiceOp)
In theory. The problem is, that Swift does not accept a GKRandom distributed number rN at the third step.
Do you have any ideas how I could do it?
In your step 3, you should call nextInt() on rN. GKRandomDistribution generates a new random number every time you call nextInt() based on the lowest and highest value you have given it at initialization. So your new code would be:
let choiceOp = array[rN.nextInt()]
Related
I am currently writing an (simple) analytisis code to sum time connected powerreadings. With the data being assumingly raw (e.g. disturbances from the measuring device have not been calculated out) I have to account for disturbances by calculation the mean of the first one thousand samples. The calculation of the mean itself is not a problem. I only am unsure of how to generate the appropriate DataSet.
For now it looks about like this:
DataSet<Tupel2<long,double>>Gyrotron_1=ECRH.includeFields('11000000000'); // obviously the line to declare the first gyrotron, continues for the next ten lines, assuming separattion of not occupied space
DataSet<Tupel2<long,double>>Gyrotron_2=ECRH.includeFields('10100000000');
DataSet<Tupel2<long,double>>Gyrotron_3=ECRH.includeFields('10010000000');
DataSet<Tupel2<long,double>>Gyrotron_4=ECRH.includeFields('10001000000');
DataSet<Tupel2<long,double>>Gyrotron_5=ECRH.includeFields('10000100000');
DataSet<Tupel2<long,double>>Gyrotron_6=ECRH.includeFields('10000010000');
DataSet<Tupel2<long,double>>Gyrotron_7=ECRH.includeFields('10000001000');
DataSet<Tupel2<long,double>>Gyrotron_8=ECRH.includeFields('10000000100');
DataSet<Tupel2<long,double>>Gyrotron_9=ECRH.includeFields('10000000010');
DataSet<Tupel2<long,double>>Gyrotron_10=ECRH.includeFields('10000000001');
for (int=1,i<=10;i++) {
DataSet<double> offset=Gyroton_'+i+'.groupBy(1).first(1000).sum()/1000;
}
It's the part in the for-loop I'm unsure of. Does anybody know if it is possible to append values to DataSets and if so how?
In case of doubt, I could always put the values into an array but I do not know if that is the wise thing to do.
This code will not work for many reasons. I'd recommend looking into the fundamentals of Java and the basic data structures and also in Flink.
It's really hard to understand what you actually try to achieve but this is the closest that I came up with
String[] codes = { "11000000000", ..., "10000000001" };
DataSet<Tuple2<Long, Double>> result = env.fromElements();
for (final String code : codes) {
DataSet<Tuple2<Long, Double>> codeResult = ECRH.includeFields(code)
.groupBy(1)
.first(1000)
.sum(0)
.map(sum -> new Tuple2<>(sum.f0, sum.f1 / 1000d));
result = codeResult.union(result);
}
result.print();
But please take the time and understand the basics before delving deeper. I also recommend to use an IDE like IntelliJ that would point to at least 6 issues in your code.
I am creating a very naive AI (it maybe shouldn't even be called an AI, as it just tests out a lot of possibilites and picks the best one for him), for a board game I am making. This is to simplify the amount of manual tests I will need to do to balance the game.
The AI is playing alone, doing the following things: in each turn, the AI, playing with one of the heroes, attacks one of the max 9 monsters on the battlefield. His goal is to finish the battle as fast as possible (in the least amount of turns) and with the fewest amount of monster activations.
To achieve this, I've implemented a think ahead algorithm for the AI, where instead of performing the best possible move at the moment, he selects a move, based on the possible outcome of future moves of other heroes. This is the code snippet where he does this, it is written in PHP:
/** Perform think ahead moves
*
* #params int $thinkAheadLeft (the number of think ahead moves left)
* #params int $innerIterator (the iterator for the move)
* #params array $performedMoves (the moves performed so far)
* #param Battlefield $originalBattlefield (the previous state of the Battlefield)
*/
public function performThinkAheadMoves($thinkAheadLeft, $innerIterator, $performedMoves, $originalBattlefield, $tabs) {
if ($thinkAheadLeft == 0) return $this->quantify($originalBattlefield);
$nextThinkAhead = $thinkAheadLeft-1;
$moves = $this->getPossibleHeroMoves($innerIterator, $performedMoves);
$Hero = $this->getHero($innerIterator);
$innerIterator++;
$nextInnerIterator = $innerIterator;
foreach ($moves as $moveid => $move) {
$performedUpFar = $performedMoves;
$performedUpFar[] = $move;
$attack = $Hero->getAttack($move['attackid']);
$monsters = array();
foreach ($move['targets'] as $monsterid) $monsters[] = $originalBattlefield->getMonster($monsterid)->getName();
if (self::$debug) echo $tabs . "Testing sub move of " . $Hero->Name. ": $moveid of " . count($moves) . " (Think Ahead: $thinkAheadLeft | InnerIterator: $innerIterator)\n";
$moves[$moveid]['battlefield']['after']->performMove($move);
if (!$moves[$moveid]['battlefield']['after']->isBattleFinished()) {
if ($innerIterator == count($this->Heroes)) {
$moves[$moveid]['battlefield']['after']->performCleanup();
$nextInnerIterator = 0;
}
$moves[$moveid]['quantify'] = $moves[$moveid]['battlefield']['after']->performThinkAheadMoves($nextThinkAhead, $nextInnerIterator, $performedUpFar, $originalBattlefield, $tabs."\t", $numberOfCombinations);
} else $moves[$moveid]['quantify'] = $moves[$moveid]['battlefield']['after']->quantify($originalBattlefield);
}
usort($moves, function($a, $b) {
if ($a['quantify'] === $b['quantify']) return 0;
else return ($a['quantify'] > $b['quantify']) ? -1 : 1;
});
return $moves[0]['quantify'];
}
What this does is that it recursively checks future moves, until the $thinkAheadleft value is reached, OR until a solution was found (ie, all monsters were defeated). When it reaches it's exit parameter, it calculates the state of the battlefield, compared to the $originalBattlefield (the battlefield state before the first move). The calculation is made in the following way:
/** Quantify the current state of the battlefield
*
* #param Battlefield $originalBattlefield (the original battlefield)
*
* returns int (returns an integer with the battlefield quantification)
*/
public function quantify(Battlefield $originalBattlefield) {
$points = 0;
foreach ($originalBattlefield->Monsters as $originalMonsterId => $OriginalMonster) {
$CurrentMonster = $this->getMonster($originalMonsterId);
$monsterActivated = $CurrentMonster->getActivations() - $OriginalMonster->getActivations();
$points+=$monsterActivated*($this->quantifications['activations'] + $this->quantifications['activationsPenalty']);
if ($CurrentMonster->isDead()) $points+=$this->quantifications['monsterKilled']*$CurrentMonster->Priority;
else {
$enragePenalty = floor($this->quantifications['activations'] * (($CurrentMonster->Enrage['max'] - $CurrentMonster->Enrage['left'])/$CurrentMonster->Enrage['max']));
$points+=($OriginalMonster->Health['left'] - $CurrentMonster->Health['left']) * $this->quantifications['health'];
$points+=(($CurrentMonster->Enrage['max'] - $CurrentMonster->Enrage['left']))*$enragePenalty;
}
}
return $points;
}
When quantifying some things net positive points, some net negative points to the state. What the AI is doing, is, that instead of using the points calculated after his current move to decide which move to take, he uses the points calculated after the think ahead portion, and selecting a move based on the possible moves of the other heroes.
Basically, what the AI is doing, is saying that it isn't the best option at the moment, to attack Monster 1, but IF the other heroes will do this-and-this actions, in the long run, this will be the best outcome.
After selecting a move, the AI performs a single move with the hero, and then repeats the process for the next hero, calculating with +1 moves.
ISSUE: My issue is, that I was presuming, that an AI, that 'thinks ahead' 3-4 moves, should find a better solution than an AI that only performs the best possible move at the moment. But my test cases show differently, in some cases, an AI, that is not using the think ahead option, ie only plays the best possible move at the moment, beats an AI that is thinking ahead 1 single move. Sometimes, the AI that thinks ahead only 3 moves, beats an AI that thinks ahead 4 or 5 moves. Why is this happening? Is my presumption incorrect? If so, why is that? Am I using wrong numbers for weights? I was investigating this, and run a test, to automatically calculate the weights to use, with testing an interval of possible weights, and trying to use the best outcome (ie, the ones, which yield the least number of turns and/or the least number of activations), yet the problem I've described above, still persists with those weights also.
I am limited to a 5 move think ahead with the current version of my script, as with any larger think ahead number, the script gets REALLY slow (with 5 think ahead, it finds a solution in roughly 4 minutes, but with 6 think ahead, it didn't even find the first possible move in 6 hours)
HOW THE FIGHT WORKS: The fight works in the following way: a number of heroes (2-4) controlled by the AI, each having a number of different attacks (1-x), which can be used once or multiple times in a combat, are attacking a number of monsters (1-9). Based on the values of the attack, the monsters lose health, until they die. After each attack, the attacked monster gets enraged if he didn't die, and after each heroes performed a move, all monsters get enraged. When the monsters reach their enrage limit, they activate.
DISCLAIMER: I know that PHP is not the language to use for this kind of operation, but as this is only an in-house project, I've preferred to sacrifice speed, to be able to code this as fast as possible, in my native programming language.
UPDATE: The quantifications that we currently use look something like this:
$Battlefield->setQuantification(array(
'health' => 16,
'monsterKilled' => 86,
'activations' => -46,
'activationsPenalty' => -10
));
If there is randomness in your game, then anything can happen. Pointing that out since it's just not clear from the materials you have posted here.
If there is no randomness and the actors can see the full state of the game, then a longer look-ahead absolutely should perform better. When it does not, it is a clear indication that your evaluation function is providing incorrect estimates of the value of a state.
In looking at your code, the values of your quantifications are not listed and in your simulation it looks like you just have the same player make moves repeatedly without considering the possible actions of the other actors. You need to run a full simulation, step by step in order to produce accurate future states and you need to look at the value estimates of the varying states to see if you agree with them, and make adjustments to your quantifications accordingly.
An alternative way to frame the problem of estimating value is to explicitly predict your chances of winning the round as a percentage on a scale of 0.0 to 1.0 and then choose the move that gives you the highest chance of winning. Calculating the damage done and number of monsters killed so far doesn't tell you much about how much you have left to do in order to win the game.
So I'm making a little text based game in Python and I decided for a save system I wanted to use the old "insert code" trick. The code needs to keep track of the players inventory (as well as other things, but the inventory is what I'm having trouble with).
So my thought process on this would be to tie each item and event in the game to a code. For example, the sword in your inventory would be stored as "123" or something unique like that.
So, for the code that would generate to save the game, imagine you have a sword and a shield in your inventory, and you were in the armory.
location(armory) = abc
sword = 123
shield = 456
When the player inputs the command to generate the code, I would expect an output something like:
abc.123.456
I think putting periods between items in the code would make it easier to distinguish one item from another when it comes to decoding the code.
Then, when the player starts the game back up and they input their code, I want that abc.123.456 to be translated back into your location being the armory and having a sword and shield in your inventory.
So there are a couple questions here:
How do I associate each inventory item with its respective code?
How do I generate the full code?
How do I decode it when the player loads back in?
I'm pretty damn new to Python and I'm really not sure how to even start going about this... Any help would be greatly appreciated, thanks!
So, if I get you correctly, you want to serialize info into a string which can't be "saved" but could be input in your program;
Using dots is not necessary, you can program your app to read your code without them.. this will save you a few caracters in lenght.
The more information your game needs to "save", the longer your code will be; I would suggest to use as short as possible strings.
Depending on the amount of locations, items, etc. you want to store in your save code: you may prefer longer or shorter options:
digits (0-9): will allow you to keep 10 names stored in 1 character each.
hexadecimal (0-9 + a-f, or 0-9 + a-F): will allow you to keep from 16 to 22 names (22 if you make your code case sensitive)
alphanum (0-9 + a-z, or 0-9 + a-Z): will allow you to keep from 36 to 62 names (62 if case sensitive)
more options are possible if you decide to use punctuation and punctuated characters, this example will not go there, you will need to cover that part yourself if you need.
For this example I'm gonna stick with digits as I'm not listing more than 10 items or locations.
You define each inventory item and each place as dictionaries, in your source code:
You can a use single line like I have done for places
places = {'armory':'0', 'home':'1', 'dungeon':'2'}
# below is the same dictionary but sorted by values for reversing.
rev_places = dict(map(reversed, places.items()))
Or for improved readability; use multiple lines:
items = {
'dagger':'0',
'sword':'1',
'shield':'2',
'helmet':'3',
'magic wand':'4'
}
#Below is the same but sorted by value for reversing.
rev_items = dict(map(reversed, items.items()))
Store numbers as strings, for easier understanding, also if you use hex or alphanum options it will be required.
Then also use dictionaries to manage in game information, below is just a sample of how you should represent your game infos that the code will produce or parse, this portion should not be in your source code, I have intentionally messed items order to test it.;
game_infos = {
'location':'armory',
'items':{
'slot1':'sword',
'slot2':'shield',
'slot3':'dagger',
'slot4':'helmet'
}
}
Then you could generate your save code with following function that reads your inventory and whereabouts like so:
def generate_code(game_infos):
''' This serializes the game information dictionary into a save
code. '''
location = places[game_infos['location']]
inventory = ''
#for every item in the inventory, add a new character to your save code.
for item in game_infos['items']:
inventory += items[game_infos['items'][item]]
return location + inventory # The string!
And the reading function, which uses the reverse dictionaries to decipher your save code.
def read_code(user_input):
''' This takes the user input and transforms it back to game data. '''
result = dict() # Let's start with an empty dictionary
# now let's make the user input more friendly to our eyes:
location = user_input[0]
items = user_input[1:]
result['location'] = rev_places[location] # just reading out from the table created earlier, we assign a new value to the dictionary location key.
result['items'] = dict() # now make another empty dictionary for the inventory.
# for each letter in the string of items, decode and assign to an inventory slot.
for pos in range(len(items)):
slot = 'slot' + str(pos)
item = rev_items[items[pos]]
result['items'][slot] = item
return result # Returns the decoded string as a new game infos file :-)
I recommend you play around with this working sample program, create a game_infos dictionary of your own with more items in inventory, add some places, etc.
You could even add some more lines/loops to your functions to manage hp or other fields your game will require.
Hope this helps and that you had not given up on this project!
I use code like the example below to do basic plotting of a list of values from F# Interactive. When plotting more points, the time taken to display increases dramatically. In the examples below, 10^4 points display in 4 seconds whereas 4.10^4 points take a patience-testing 53 seconds to display. Overall it's roughly as if the time to plot N points is in N^2.
The result is that I'll probably add an interpolation layer in front of this code, but
1) I wonder if someone who knows the workings of FSharpChart and Windows.Forms could explain what is causing this behaviour? (The data is bounded so one thing that seems to rule out is the display needing to adjust scale.)
2)Is there a simple remedy other than interpolating the data myself?
let plotl (f:float list) =
let chart = FSharpChart.Line(f, Name = "")
|> FSharpChart.WithSeries.Style(Color = System.Drawing.Color.Red, BorderWidth = 2)
let form = new Form(Visible = true, TopMost = true, Width = 700, Height = 500)
let ctl = new ChartControl(chart, Dock = DockStyle.Fill)
form.Controls.Add(ctl)
let z1 = [for i in 1 .. 10000 do yield sin(float(i * i))]
let z2 = [for i in 1 .. 20000 do yield sin(float(i * i))]
plotl z1
plotl z2
First of all, FSharpChart is a name used in an older version of the library. The latest version is called F# Charting, comes with a new documentation and uses just Chart.
To answer your question, Chart.Line and Chart.Points are quite slow for large number of points. The library also has Chart.FastLine and Chart.FastPoints (which do not support as many features, but are faster). So, try getting the latest version of F# Charting and using the "Fast" version of the method.
Its quite a big task but ill try to explain.
I have an array with a list of 200 strings and I want to be able to randomly select one and add it to the stage using code. I have movieclips exported for actionscript with the same class name as the strings in the array. Also, if it is possible, would I be able to select the strings with predictability such as the first has a 0.7 chance the second a 0.1 etc. Here is what i have currently
var nameList:Array=["Jimmy","Bob","Fred"]
var instance:DisplayObject = createRandom(nameList);
addChild(instance);
function createRandom(typeArray:Array):*
{
// Select random String from typeArray.
var selection:String = typeArray[ int(Math.random() * typeArray.length) ];
// Create instance of relevant class.
var Type:Class = getDefinitionByName(selection) as Class;
// Return created instance.
return new Type();
}
All this throws me this error
ReferenceError: Error #1065: Variable [class Jimmy] is not defined.
Ive searched for other threads similar but none combine the three specific tasks of randomisation, predictability and addChild().
I think that you've got two problems: a language problem and a logic problem. In the .fla connected to your code above, in the Library find each symbol representing a name and write into the 'AS linkage' column for that symbol the associated name -- e.g., 'Bob,' 'Fred' -- just the name, no punctuation.
Now getDefinitionByName() will find your 'Class'
If you put a different graphic into each MovieClip -- say, a piece of fruit or a picture of Bob,Jim, Fred -- and run your program you'll get a random something on stage each time.
That should solve your language problem. But the logic problem is a little harder, no?
That's why I pointed you to Mr. Kelly's solution (the first one, which for me is easier to grasp).