I want to try the ReedSolomonDecoder from the ZXing library on the example given on page 10 of this paper
Basically, it encodes the message
1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11
using the generator polynomial
x^4 + 15x^3 + 3x^2 + x + 12
which results in
1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 3, 3, 12, 12
I want to decode this in the following manner:
int[] data = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 3, 3, 12, 12};
GenericGF field = new GenericGF(?, 16, 1); // what integer should I use for primitive here?
ReedSolomonDecoder decoder = new ReedSolomonDecoder(field);
decoder.decode(data, 4);
I don't know how to create a GenericGF object from the given generator polynomial. I know that it expects a binary integer representation of the polynomial, but to do that, I would need the polynomial to be in an irreducible form, i.e. all the coefficients to be either 0 or 1. How can I achieve that from this given generator polynomial?
I'm pretty new to this as well but I think you would want to use
public static GenericGF AZTEC_PARAM = new GenericGF(0x13, 16, 1);
Related
I have a single trained classifier tested on 2 related multiclass classification tasks. As each trial of the classification tasks are related, the 2 sets of predictions constitute paired data. I would like to run a paired permutation test to find out if the difference in classification accuracy between the 2 prediction sets is significant.
So my data consists of 2 lists of predicted classes, where each prediction is related to the prediction in the other test set at the same index.
Example:
actual_classes = [1, 3, 6, 1, 22, 1, 11, 12, 9, 2]
predictions1 = [1, 3, 6, 1, 22, 1, 11, 12, 9 10] # 90% acc.
predictions2 = [1, 3, 7, 10, 22, 1, 7, 12, 2, 10] # 50% acc.
H0: There is no significant difference in classification accuracy.
How do I go about running a paired permutation test to test significance of the difference in classification accuracy?
I have been thinking about this and I'm going to post a proposed solution and see if someone approves or explains why I'm wrong.
actual_classes = [1, 3, 6, 1, 22, 1, 11, 12, 9, 2]
predictions1 = [1, 3, 6, 1, 22, 1, 11, 12, 9 10] # 90% acc.
predictions2 = [1, 3, 7, 10, 22, 1, 7, 12, 2, 10] # 50% acc.
paired_predictions = [[1,1], [3,3], [6,7], [1,10], [22,22], [1,1], [11,7], [12,12], [9,2], [10,10]]
actual_test_statistic = predictions1 - predictions2 # 90%-50%=40 # 0.9-0.5=0.4
all_simulations = [] # empty list
for number_of_iterations:
shuffle(paired_predictions) # only shuffle between pairs, not within
simulated_predictions1 = paired_predictions[first prediction of each pair]
simulated_predictions2 = paired_predictions[second prediction of each pair]
simulated_accuracy1 = proportion of times simulated_predictions1 equals actual_classes
simulated_accuracy2 = proportion of times simulated_predictions2 equals actual_classes
all_simulations.append(simulated_accuracy1 - simulated_accuracy2) # Put the simulated difference in the list
p = count(absolute(all_simulations) > absolute(actual_test_statistic ))/number_of_iterations
If you have any thoughts, let me know in the comments. Or better still, provide your own corrected version in your own answer. Thank you!
I have a dasaset of length 200 and length of each row of data is also 200. This dataset is space separated. Here is sample dataset (first row).
-0.1100208269729097 0.1248460463105589 -0.01559138588255286 -0.01625839428292603 -0.05323888667281371 0.06722185430549973 -0.0490877148079949 -0.05039368886946847 0.0897270838973875 0.00754589058726465 -0.06693447805463611 -0.1193740974362337 -0.02214573804045866 0.02930806967704801 -0.009567144727872222 -0.02288991169653539 0.04256313697292451 -0.08190168271952417 0.008274133732539695 -0.02299227162395361 0.0111923018567119 -0.009872522389769637 0.06866110814693088 0.04622954799009332 0.05498202029091768 -0.06672541846259043 -0.05130079655965012 0.1107659505844031 0.07912810279475517 0.02246390669165305 -0.06997067603392053 -0.02069109953229961 -0.05191987832821615 -0.01971016519416264 -0.008691704006401698 -0.02963829527404451 0.02332929010677706 -0.1035585589634834 0.03801924036385142 -0.07035181096148016 -0.02460761051792025 0.05545479574143786 0.06632500394350074 -0.01693623441811409 -0.0202000922412099 0.0387732166529701 -0.06835009268170482 -0.06684471565316714 0.09737868086728406 -0.03776102176325794 -0.03087980353481784 -0.04630278791951752 -0.1129739647985331 0.09622849675187727 0.05975310144103099 -0.08083650075114446 0.05258346559791484 0.05583993856089118 -0.03916345795047688 -0.2981097687887527 0.04087798461219992 0.07153463501552468 0.07113045074135986 0.01717619972420815 -0.01893649865573213 -0.007503347735166889 0.06551854299072507 -0.005153581328393866 -0.08659840104899437 0.04864888731854276 0.08965801176651583 -0.004562179660153576 -0.1252787635844004 0.06896990208188783 -0.003925090827015415 -0.05755687748680104 -0.02544736897698906 0.02530385776038159 -0.125784848738536 0.07433650535349738 0.02153916317259382 0.04738213124034089 -0.03299623626264642 0.02073383160046674 -0.008966711746564809 0.04983292315200202 0.01974696673478601 -0.04419678420395467 -0.02442715323795661 -0.0694663145847256 0.1101497271416977 0.04200639135007367 -0.06082113335723243 -0.01473508072467703 0.01142600017146485 -0.03532257289246362 -0.02260329422449697 0.05396810070565884 0.1581078158241939 -0.05426153505070038 -0.01534772560258162 -0.04461245038675606 -0.05082561044342486 0.003953621713155758 -0.09395992245069541 0.02029879424655968 0.09397373054431565 -0.01540603811173099 -0.00188325436669238 0.07341578917873427 -0.07930228379622654 -0.01519407550785842 0.01388266474816023 0.09152064522133056 0.0106446218365201 -0.2157572256227169 0.04804075039482639 0.01970079327929429 -0.04738197196862703 0.06770927522186629 0.1006260778362594 -0.06299061441376895 0.02961951153113571 0.01572783315493193 0.1349089347411493 -0.0242042239418958 -0.07337276266118564 -0.09620055007994345 0.04754719051788902 -0.04777964847293222 0.01477148963357754 0.06678924792453055 0.05579081171364433 -0.03405429131223387 0.03615588517175376 -0.1554971840439641 -0.04581567263300179 -0.07873107398807083 0.05966093431149457 -0.128446162280915 -0.05912532817875745 0.1194692701951161 0.1103496401807509 0.0153127716173752 0.01607453121383664 -0.07114032721360454 0.03276185612322021 0.1169776569257143 0.07706242373764424 0.04889932405415184 0.0008715101384050066 0.006894007893755344 0.04519320187367908 -0.001306669064508431 0.0291067296150834 -0.02697983215093226 -0.07374490898814057 -0.04408652590757124 0.118965444980577 0.08668199929217432 0.02704832616237655 0.01473294258443707 0.02049896556673346 -0.0569226246137925 -0.0120183686689177 -0.1007080842912528 0.03517628230997978 -0.2003177929062758 0.01491215547976228 0.04590546935765301 0.1670139443078561 -0.05992676476987346 0.07038240324837636 -0.003567431692839979 0.08197255057946093 -0.01384071718153512 0.01443837418022523 -0.0393556604031245 0.003264844777785919 -0.190455395258628 -0.09122702488367737 -0.007113243408323287 0.1221344569965773 -0.06583221256210335 0.002275841418885295 -0.02418590378253777 -0.02462843336523757 -0.1054326841702153 -0.009075125286585313 0.05233463322601897 -0.09944517224527978 0.08201627957443283 0.1144830692826725 -0.1488155291532296 0.001711351371442085 0.06463339531524601 0.02089587578959802 -0.05699940762150812 0.01798950350182588 -0.01642350646709232
I tried in following way to convert it into comma seperated data. Here is my code
val bufferedSource1 = Source.fromFile(Path1 + name)
val lines1 : Iterator[String] = bufferedSource1.getLines()
val lines2 = lines1.toArray
println( lines2(0).toList )
Result of last line of code is
List(-, 0, ., 1, 1, 0, 0, 2, 0, 8, 2, 6, 9, 7, 2, 9, 0, 9, 7, , 0, ., 1, 2, 4, 8, 4, 6, 0, 4, 6, 3, 1, 0, 5, 5, 8, 9, , -, 0, ., 0, 1, 5, 5, 9, 1, 3, 8, 5, 8, 8, 2, 5, 5, 2, 8, 6, , -, 0, ., 0, 1, 6, 2, 5, 8, 3, 9, 4, 2, 8, 2, 9, 2, 6, 0, 3, , -, 0, ., 0, 5, 3, 2,.........
This is returning me single character but I want complete row that will be space separated. How can I fix This issue?
here is remaining code for conversion
val data1 : Array[Array[Double]] = lines2.flatMap{xz : String =>
Seq (xz.replaceAll(" ", ",").split(",").map(_.toDouble) )
}.toArray
import spark.implicits._
val ds = List("-0.1100208269729097 0.1248460463105589 -0.01559138588255286 -0.01625839428292603 -0.05323888667281371 0.06722185430549973 -0.0490877148079949 -0.05039368886946847 0.0897270838973875 0.00754589058726465 -0.06693447805463611 -0.1193740974362337 -0.02214573804045866 0.02930806967704801 -0.009567144727872222 -0.02288991169653539 0.04256313697292451 -0.08190168271952417 0.008274133732539695 -0.02299227162395361 0.0111923018567119 -0.009872522389769637 0.06866110814693088 0.04622954799009332 0.05498202029091768 -0.06672541846259043 -0.05130079655965012 0.1107659505844031 0.07912810279475517 0.02246390669165305 -0.06997067603392053 -0.02069109953229961 -0.05191987832821615 -0.01971016519416264 ","-0.1100208269729097 0.1248460463105589 -0.01559138588255286 -0.01625839428292603 -0.05323888667281371 0.06722185430549973 -0.0490877148079949 -0.05039368886946847 0.0897270838973875 0.00754589058726465 -0.06693447805463611 -0.1193740974362337 -0.02214573804045866 0.02930806967704801 -0.009567144727872222 -0.02288991169653539 0.04256313697292451 -0.08190168271952417 0.008274133732539695 -0.02299227162395361 0.0111923018567119 -0.009872522389769637 0.06866110814693088 0.04622954799009332 0.05498202029091768 -0.06672541846259043 -0.05130079655965012 0.1107659505844031 0.07912810279475517 0.02246390669165305 -0.06997067603392053 -0.02069109953229961 -0.05191987832821615 -0.01971016519416264 ").toDS()
ds.map(i=> i.split(" ").mkString(",")).show(false)
-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
|-0.1100208269729097,0.1248460463105589,-0.01559138588255286,-0.01625839428292603,-0.05323888667281371,0.06722185430549973,-0.0490877148079949,-0.05039368886946847,0.0897270838973875,0.00754589058726465,-0.06693447805463611,-0.1193740974362337,-0.02214573804045866,0.02930806967704801,-0.009567144727872222,-0.02288991169653539,0.04256313697292451,-0.08190168271952417,0.008274133732539695,-0.02299227162395361,0.0111923018567119,-0.009872522389769637,0.06866110814693088,0.04622954799009332,0.05498202029091768,-0.06672541846259043,-0.05130079655965012,0.1107659505844031,0.07912810279475517,0.02246390669165305,-0.06997067603392053,-0.02069109953229961,-0.05191987832821615,-0.01971016519416264|
|-0.1100208269729097,0.1248460463105589,-0.01559138588255286,-0.01625839428292603,-0.05323888667281371,0.06722185430549973,-0.0490877148079949,-0.05039368886946847,0.0897270838973875,0.00754589058726465,-0.06693447805463611,-0.1193740974362337,-0.02214573804045866,0.02930806967704801,-0.009567144727872222,-0.02288991169653539,0.04256313697292451,-0.08190168271952417,0.008274133732539695,-0.02299227162395361,0.0111923018567119,-0.009872522389769637,0.06866110814693088,0.04622954799009332,0.05498202029091768,-0.06672541846259043,-0.05130079655965012,0.1107659505844031,0.07912810279475517,0.02246390669165305,-0.06997067603392053,-0.02069109953229961,-0.05191987832821615,-0.01971016519416264|
+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
I have a string that consists of few numbers. First number is the number of the row, remaining are numbers in this row.(Array but string, kind of). The problem is that remaining numbers are unsorted, and I want to find the clearest way of sorting them without creating new List and sorting everything there.
String unsorted = '9, 12, 14, 11, 2, 10';
print(unsorted.sort()); // '9, 2, 10, 11, 12, 14'
You cant really avoid converting to a list of numbers if you want to sort it.
void main() {
print(sortNumString('9, 12, 14, 11, 2, 10')); // 2, 9, 10, 11, 12, 14
}
String sortNumString(String numString, [String separator = ', ']) =>
(numString.split(separator).map(int.parse).toList()..sort())
.join(separator);
The .. means to return the previous thing, the list, since sort returns void.
I'm not exactly experienced when it comes to dart programming language but this is what i came up with.
void main() {
var unsorted = "9, 12, 14, 11, 2, 10";
var nums_int = unsorted.split(", ").map(int.parse).toList();
nums_int.sort();
for (var n in nums_int) {
stdout.write(n.toString() + ", ");
}
}
That should give the expected output: "2, 9, 10, 11, 12, 14"
Hope this helps.
I gave all values for stochastic nodes, but WinBUGS still gives me the message that a chain contains uninitialized variables. When I try to generate it, BUGS gives me an error undefined real result. What node I am missing here?
model {
# Population Model start on the 1 of October 2014
# Look up initial numbers in each age class
F1.2014 <- 4 # no. first-year females October 2014
F2.2014 <- 2 # no. older females October 2014
F.2014 <- F1.2014+F2.2014 # total no. of females in October 2014
F.trans <- 15 # no. of trans. juv females in March 2015
F2[1] ~ dbin(phi.af.annual, F.2014) # sample number older females alive October 2015 (12 mo)
mutot.2014 <- mu.1*F1.2014+mu.2*F2.2014 # expected number of fledglings 2014/15
J.2014 ~ dpois(mutot.2014) # sample actual number of fledglings
JF.2014 ~ dbin(0.5,J.2014) # sample no. juv females in January 2015
phi.trans<-pow((phi.jf.mo),6) # probability trans juvs survive from March to October
F1.trans ~ dbin(phi.trans, F.trans) # sample no. translocated female juven in October 2015
F1.juvs ~ dbin(phi.jf,JF.2014) # sample no. female juven in October 2015
F1[1]<-F1.juvs+F1.trans # total number of first year birds in October 2015
F[1] <- F1[1]+F2[1]
PE[1] <- step(-F[1]) # prob extinction by October 2015
# run simulations for 20 years
for (i in 1:20) {
mutot[i] <- mu.1*F1[i]*mu.2*F2[i] # expected number of total fledglings by females
J[i] ~ dpois(mutot[i]) # sample total fledglings
JF[i] ~ dbin(0.5,J[i]) # sample number female fledglings
F1[i+1] ~ dbin(phi.jf,JF[i]) # sample number female recruits next year
F2[i+1] ~ dbin(phi.af.annual,F[i]) # sample number adult females that survive to next year
F[i+1] <- F1[i+1]+F2[i+1] # total number of females next year
PE[i+1] <- step(-F[i+1]) # prob that population extinct next year
}
}
# Data
list(phi.af.annual=0.6, mu.1=2.5, mu.2=3.1, phi.jf.mo=0.8, phi.jf=0.87)
# Inits
list(F1=c(NA, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5),
F2=c(NA, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3),
F1.trans=10, F1.juvs=6, J.2014=20, JF.2014=10,
J=c(10, 10, 10, 10, 10, 10, 10, 10, 10, 10,
10, 10, 10, 10, 10, 10, 10, 10, 10, 10),
JF=c(5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5)
)
I have two arrays
var availableIndex: Int[] = [0, 1, 2, 3, 4, 5, 7, 8, 9, 10, 11, 12, 13, 14]
var answerIndex: Int[] = [1, 3, 10, 8]
I want to remove 1, 3, 10, 8 from availableIndex array. I've seen the documentation how to achieve that using removeObjectsInArray
availableIndex.removeObjectsInArray(answerIndex)
but I can't use that method, it gave me an error. I have no idea where's my fault. Sorry if my bad English
edit:
here is the error 'Int[]' does not have a member named 'removeObjectsInArray'
The proper Swifty way to do this is
availableIndex = availableIndex.filter { value in
!answerIndex.contains(value)
}
(will create a new filtered array only with values not contained in answerIndex)
Of course, a better solution would be to convert answerIndex into a Set.
removeObjectsInArray is defined only on Obj-C mutable arrays (NSMutableArray).
An Obj-C workaround is to define the array directly as NSMutableArray
var availableIndex: NSMutableArray = [0, 1, 2, 3, 4, 5, 7, 8, 9, 10, 11, 12, 13, 14]
var answerIndex: Int[] = [1, 3, 10, 8]
availableIndex.removeObjectsInArray(answerIndex)
It's also possible to do it like that:
availableIndex.removeAll(where: { answerIndex.contains($0) })