*YIKES..DOUBLE ARRAY


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Ok, after I posted my last result, it came to my attention that I did the wrong assignment. Now I am really in need of help. THis is also a double arry assignment and I need help from anyone asap..please..The instructions are as follow:

I am to make modifications to the code below. The instruction further states that when the user clicks the Get Temperatures button, the button's Click event procedure should prompt the user to enter the highest and lowest temperatures for seven days. Store the temperatures in a seven-row, two-column Integer array. The first column should contain the highest temp, and the second column should contain the lowest temp. When the user clicks the Display


Related to : *YIKES..DOUBLE ARRAY
Invalid types 'double*[double]' for array subscript
VB & VBnet
Hi people I have the error I named the question in the function: (With "here" I comment where the compiler send me the error):
Code:

void ftshifting(matriz filter,int rows,int cols){
 
 double r2,c2,tmp1_3,tmp2_4;
 r2 = (rows+1)/2;  c2 = (cols+1)/2;
 for (int i = 0; i<rows/2; i++){
  for (int k = 0; k<cols/2; k++){
      tmp1_3 = filter[i][k];
      filter[i][k] = filter[i+r2][k+c2];  //error
      filter[i+r2][k+c2] = tmp1
*YIKES..DOUBLE ARRAY
VB & VBnet

Ok, after I posted my last result, it came to my attention that I did the wrong assignment. Now I am really in need of help. THis is also a double arry assignment and I need help from anyone asap..please..The instructions are as follow:

I am to make modifications to the code below. The instruction further states that when the user clicks the Get Temperatures button, the button's Click event procedure should prompt the user to enter the highest and lowest temperatures for seven days. Store the temperatures in a seven-row, two-column Integer array. The first column should contain the highest temp, and the second column should contain the lowest temp. When the user clicks the Display

How to transform Array[(Double, Double)] into Array[Double] in Scala?
VB & VBnet

I'm using MLlib of Spark (v1.1.0) and Scala to do k-means clustering applied to a file with points (longitude and latitude). My file contains 4 fields separated by comma (the last two are the longitude and latitude).

Here, it's an example of k-means clustering using Spark: https://spark.apache.org/docs/1.1.0/mllib-clustering.html

What I want to do is to read the last two fields of my files that are in a specific directory in HDFS, transform them into an RDD<Vector> o use this method in KMeans class: train(RDD<Vector> data, int k, int maxIterations)

This is my code:

val data = sc.textFile("/user/test/location/*") val parsedData = data.map(s => Vectors.dense(s.split(',').map(fields => (fields(2).toDouble,fields(3).toDouble))))

But when I run it in spark-shell I get the following error:

error: overloaded method value dense with alternatives: (values: Array[Double])org.apache.spark.mllib.linalg.Vector (firstValue: Double,otherValues: Double*)org.apache.spark.mllib.linalg.Vector cannot be applied to (Array[(Double, Double)])

So, I don't know how to transform my Array[(Double, Double)] into Array[Double]. Maybe there is another way to read the two fields and convert them into RDD<Vector>, any suggestion?


Call of overloaded [function](double&, double&, double&, double&, const double&, double&) is ambiguous
VB & VBnet

i'm getting an error message from

void solveforVelocity(double& Vi, double H, double A,
double Xf, double G, double& T)
{    
    T = sqrt(H-(Xf/cos(A)*sin(A))/(0.5*G));    
    Vi = Xf/(T*cos(A));
}

double Vi = -1, H = -1, A = -361, A1, A2, Xf = 0, T = 0;
solveforVelocity(Vi, H, A, Xf, G, T);

with the notes indicating that candidates consist of void solveforVelocity(double&, double, double, double, double, double&) or void solveforVelocity(double, double, double, double, double, double&) .

I'm using DevC++, and it turns out both notes stem from the line containing the first bracket ("{").

The top function is outside of my main, and the reference to the function's purpose is to find T and Vi. I'm not sure if my problem stems from a pointer error or what. What have I done wrong? Thanks for your time.


How to read only the part of data(double) required from a text file in java and put it to double array[]
VB & VBnet

I want to read only the first part of the number mentioned under distribution points. That is "-5.344029659372277" and then store all these points into an array in java.

Using fixed random seed for repeat ability.
............................................
Constructing inference engine of class blog.engine.SamplingEngine
Constructing sampler of class blog.sample.LWSampler
Evidence: []
Query: [x, y, z]
Running for 20 samples...
Query Reporting interval is 10000
========  LW Trial Stats =========
Log of average likelihood weight (this trial): -4.440892098500626E-16
Average likelihood weight (this trial): 0.9999999999999996
Fraction of consistent worlds (this trial): 1.0
Fraction of consistent worlds (running avg, all trials): 1.0
======== Query Results =========
Number of samples: 20
Distribution of values for x
-5.344029659372277  0.05000000000000003
-3.6282706290477384 0.05000000000000003
-3.497553178865327  0.05000000000000003
-0.8324886197923229 0.05000000000000003
Distribution of values for y
-3.8401834274154405 0.05000000000000003
-2.8617608524112454 0.05000000000000003
-2.8211880095793065 0.05000000000000003
-2.1727081725855695 0.05000000000000003
Distribution of values for z
-3.6803989664398955 0.05000000000000003
-2.3049623281250717 0.05000000000000003
-2.300277789550218  0.05000000000000003
-2.110311642917156  0.05000000000000003 
======== Done ========

This is how it looks in the output.txt from the BLOG program.


How to convert org.apache.spark.rdd.RDD[Array[Double]] to Array[Double] which is required by Spark MLlib
VB & VBnet

I am trying to implement KMeans using Apache Spark.

val data = sc.textFile(irisDatasetString)
val parsedData = data.map(_.split(',').map(_.toDouble)).cache()

val clusters = KMeans.train(parsedData,3,numIterations = 20)

on which I get the following error:

error: overloaded method value train with alternatives:
  (data:
org.apache.spark.rdd.RDD[org.apache.spark.mllib.linalg.Vector],k:
Int,maxIterations: Int,runs:
Int)org.apache.spark.mllib.clustering.KMeansModel <and>
  (data:
org.apache.spark.rdd.RDD[org.apache.spark.mllib.linalg.Vector],k:
Int,maxIterations: Int)org.apache.spark.mllib.clustering.KMeansModel
<and>
  (data:
org.apache.spark.rdd.RDD[org.apache.spark.mllib.linalg.Vector],k:
Int,maxIterations: Int,runs: Int,initializationMode:
String)org.apache.spark.mllib.clustering.KMeansModel
 cannot be applied to (org.apache.spark.rdd.RDD[Array[Double]], Int,
numIterations: Int)
       val clusters = KMeans.train(parsedData,3,numIterations = 20)

so I tried converting Array[Double] to Vector as shown here

scala> val vectorData: Vector =
Vectors.dense(parsedData)

on which I got the following error:

error: type Vector takes type parameters
   val vectorData: Vector = Vectors.dense(parsedData)
                   ^
error: overloaded method value dense with alternatives:
  (values: Array[Double])org.apache.spark.mllib.linalg.Vector
<and>
  (firstValue: Double,otherValues:
Double*)org.apache.spark.mllib.linalg.Vector
 cannot be applied to (org.apache.spark.rdd.RDD[Array[Double]])
       val vectorData: Vector = Vectors.dense(parsedData)

So I am inferring that org.apache.spark.rdd.RDD[Array[Double]] is not the same as Array[Double]

How can I proceed with my data as org.apache.spark.rdd.RDD[Array[Double]] ? or how can I convert org.apache.spark.rdd.RDD[Array[Double]] to Array[Double] ?



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