<!DOCTYPE html> <html> <head> <meta name="databricks-html-version" content="1"> <title>052_ChangeDetectionInRandomGraphSeries - Databricks</title> <meta charset="utf-8"> <meta name="google" content="notranslate"> <meta http-equiv="Content-Language" content="en"> <meta http-equiv="Content-Type" content="text/html; charset=UTF8"> <link rel="stylesheet" href="https://fonts.googleapis.com/css?family=Source+Code+Pro:400,700"> <link rel="stylesheet" type="text/css" href="https://databricks-prod-cloudfront.cloud.databricks.com/static/201602081754420800-0c2673ac858e227cad536fdb45d140aeded238db/lib/css/bootstrap.min.css"> <link rel="stylesheet" type="text/css" href="https://databricks-prod-cloudfront.cloud.databricks.com/static/201602081754420800-0c2673ac858e227cad536fdb45d140aeded238db/lib/jquery-ui-bundle/jquery-ui.min.css"> <link rel="stylesheet" type="text/css" href="https://databricks-prod-cloudfront.cloud.databricks.com/static/201602081754420800-0c2673ac858e227cad536fdb45d140aeded238db/css/main.css"> <link rel="stylesheet" href="https://databricks-prod-cloudfront.cloud.databricks.com/static/201602081754420800-0c2673ac858e227cad536fdb45d140aeded238db/css/print.css" media="print"> <link rel="icon" type="image/png" href="https://databricks-prod-cloudfront.cloud.databricks.com/static/201602081754420800-0c2673ac858e227cad536fdb45d140aeded238db/img/favicon.ico"/> <script>window.settings = {"sparkDocsSearchGoogleCx":"004588677886978090460:_rj0wilqwdm","dbcForumURL":"http://forums.databricks.com/","dbfsS3Host":"https://databricks-prod-storage-sydney.s3.amazonaws.com","enableThirdPartyApplicationsUI":false,"enableClusterAcls":false,"notebookRevisionVisibilityHorizon":0,"enableTableHandler":true,"isAdmin":true,"enableLargeResultDownload":false,"nameAndEmail":"Raazesh Sainudiin (r.sainudiin@math.canterbury.ac.nz)","enablePresentationTimerConfig":true,"enableFullTextSearch":true,"enableElasticSparkUI":true,"clusters":true,"hideOffHeapCache":false,"applications":false,"useStaticGuide":false,"fileStoreBase":"FileStore","configurableSparkOptionsSpec":[{"keyPattern":"spark\\.kryo(\\.[^\\.]+)+","valuePattern":".*","keyPatternDisplay":"spark.kryo.*","valuePatternDisplay":"*","description":"Configuration options for Kryo serialization"},{"keyPattern":"spark\\.io\\.compression\\.codec","valuePattern":"(lzf|snappy|org\\.apache\\.spark\\.io\\.LZFCompressionCodec|org\\.apache\\.spark\\.io\\.SnappyCompressionCodec)","keyPatternDisplay":"spark.io.compression.codec","valuePatternDisplay":"snappy|lzf","description":"The codec used to compress internal data such as RDD partitions, broadcast variables and shuffle outputs."},{"keyPattern":"spark\\.serializer","valuePattern":"(org\\.apache\\.spark\\.serializer\\.JavaSerializer|org\\.apache\\.spark\\.serializer\\.KryoSerializer)","keyPatternDisplay":"spark.serializer","valuePatternDisplay":"org.apache.spark.serializer.JavaSerializer|org.apache.spark.serializer.KryoSerializer","description":"Class to use for serializing objects that will be sent over the network or need to be cached in serialized form."},{"keyPattern":"spark\\.rdd\\.compress","valuePattern":"(true|false)","keyPatternDisplay":"spark.rdd.compress","valuePatternDisplay":"true|false","description":"Whether to compress serialized RDD partitions (e.g. for StorageLevel.MEMORY_ONLY_SER). 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Corrected Stochastic BlockModel Graphs\n### Scalable data science project by Shakira Suwan\n\n*supported by* [](https://databricks.com/)\nand \n[](https://www.awseducate.com/microsite/CommunitiesEngageHome)","commandVersion":0,"state":"finished","results":null,"errorSummary":null,"error":null,"startTime":0.0,"submitTime":0.0,"finishTime":0.0,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"610c1608-b502-4445-bfb9-425286fbc20b"},{"version":"CommandV1","origId":140759,"guid":"d6ab393f-93d0-437d-8650-62ffb4d834e6","subtype":"command","commandType":"auto","position":2.5,"command":"%md\nThe [html source url](https://raw.githubusercontent.com/raazesh-sainudiin/scalable-data-science/master/db/studentProjects/06_ShakiraSuwan/052_ChangeDetectionInRandomGraphSeries.html) of this databricks notebook and its recorded Uji :\n\n[](https://www.youtube.com/v/rnpa6YsDXWY?rel=0&autoplay=1&modestbranding=1&start=0&end=926)\n","commandVersion":0,"state":"error","results":null,"errorSummary":null,"error":null,"startTime":0.0,"submitTime":0.0,"finishTime":0.0,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"b055d94e-801b-4043-80f9-b9d1fc2db560"},{"version":"CommandV1","origId":121832,"guid":"52a9cc64-f474-4f88-ba54-8e1146b7ce25","subtype":"command","commandType":"auto","position":3.0,"command":"%md \n## Network Analysis\n\n<img src =\"https://raw.githubusercontent.com/raazesh-sainudiin/scalable-data-science/master/db/studentProjects/06_ShakiraSuwan/images/a700c516-2394-11e6-9880-0d0b94669f88.png\" width =\"600\">\n<img src =\"https://raw.githubusercontent.com/raazesh-sainudiin/scalable-data-science/master/db/studentProjects/06_ShakiraSuwan/images/e05fd6ac-2395-11e6-971e-a54d295ab04a.png\" width 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src=\"https://raw.githubusercontent.com/raazesh-sainudiin/scalable-data-science/master/db/studentProjects/06_ShakiraSuwan/images/28704784-27eb-11e6-81cf-09e71af68bb3.png\" width=\"700\">\n\n","commandVersion":0,"state":"finished","results":null,"errorSummary":null,"error":null,"startTime":0.0,"submitTime":1.464839748665E12,"finishTime":0.0,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"shakira.suwan@pg.canterbury.ac.nz","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"8467d13b-c2e5-425b-85ca-872172151110"},{"version":"CommandV1","origId":121834,"guid":"a96fd57e-968a-4163-9b7f-fb2b80c86ed6","subtype":"command","commandType":"auto","position":4.125,"command":"%md \n## Stochastic Blockmodel\n\n<img src=\"https://raw.githubusercontent.com/raazesh-sainudiin/scalable-data-science/master/db/studentProjects/06_ShakiraSuwan/images/4e2b79ae-251f-11e6-90ec-7a2e8e0a6920.png\" width=\"900\">\n\n ####Limitations: \n* SBM treats all nodes within a community as stochastically equivalent.\n* Thus does not allow for the existence of ?hubs,? high-degree nodes at the center of many communities observed in real data. \n* To address this issue, Karrer and Newman [20] proposed the degree-corrected stochastic block model, which can accommodate hubs.\n\n\n\n\n\n\n\n\n","commandVersion":0,"state":"finished","results":null,"errorSummary":null,"error":null,"startTime":0.0,"submitTime":1.464839748727E12,"finishTime":0.0,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"shakira.suwan@pg.canterbury.ac.nz","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"e7c49633-6767-47db-aa70-19cd26f55c44"},{"version":"CommandV1","origId":121835,"guid":"c19dd3f1-d805-4bf7-973a-d75f09faf7f4","subtype":"command","commandType":"auto","position":4.1875,"command":"%md \n## Degree Corrected Stochastic Blockmodel\n\n<img src=\"https://raw.githubusercontent.com/raazesh-sainudiin/scalable-data-science/master/db/studentProjects/06_ShakiraSuwan/images/5abba378-2525-11e6-871a-b96828a50dea.png\" width=\"900\">\n","commandVersion":0,"state":"finished","results":null,"errorSummary":null,"error":null,"startTime":0.0,"submitTime":1.464839748765E12,"finishTime":0.0,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"shakira.suwan@pg.canterbury.ac.nz","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"862bb96f-992b-4346-87dc-4628484b0953"},{"version":"CommandV1","origId":121836,"guid":"193c0628-85a8-47dd-a80b-dba72674498e","subtype":"command","commandType":"auto","position":4.25,"command":"%md\n\n<img src =\"https://raw.githubusercontent.com/raazesh-sainudiin/scalable-data-science/master/db/studentProjects/06_ShakiraSuwan/images/a489c5e8-251b-11e6-95a9-8839b41ec6a4.png\" width=\"800\" >\n\n####Change Detection\nIde and Kashima (2004) compare the current activity vector with the past average vector (profile vector) by computing the change score \\\\(s_t\\\\) for time instant, \\\\(t\\\\) as\n\n$$s_{t} = 1 - \\tilde{\\mathbf{u}}(t-1) \\cdot \\mathbf{u}(t) $$\n\nThe change scores of the nodes, \\\\(s^i_t\\\\) at time \\\\(t\\\\) is\n\n\n$$s^i_{t} = \\left | \\tilde{\\mathbf{u}}(t-1) - \\mathbf{u}(t) \\right | $$\n","commandVersion":0,"state":"finished","results":null,"errorSummary":null,"error":null,"startTime":0.0,"submitTime":1.464839748813E12,"finishTime":0.0,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"shakira.suwan@pg.canterbury.ac.nz","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"8e261fb6-5509-424f-8b33-c8b0ff667693"},{"version":"CommandV1","origId":121837,"guid":"412977b9-4eda-4779-927a-6c186aa5d12c","subtype":"command","commandType":"auto","position":4.5,"command":"%md \n\n<img src 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width=\"1000\">\n\n\n","commandVersion":0,"state":"finished","results":null,"errorSummary":null,"error":null,"startTime":0.0,"submitTime":1.464839748858E12,"finishTime":0.0,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"shakira.suwan@pg.canterbury.ac.nz","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"74f229b1-78be-4e19-8391-348196222647"},{"version":"CommandV1","origId":121838,"guid":"36359b84-db8f-4885-9007-a0f0332f11e7","subtype":"command","commandType":"auto","position":5.0,"command":"%md \n\n## Simulation Studies\n\n####Parameter Setting:\n<img src =\"https://raw.githubusercontent.com/raazesh-sainudiin/scalable-data-science/master/db/studentProjects/06_ShakiraSuwan/images/b50edfd8-2517-11e6-94f3-06b4aae2860f.png\" width=\"300\">\n* K =3, \n* n= 900 \n* \\\\( B_{i,i} = 0.05\\\\), for \\\\( i= 1,...,K\\\\)\n* \\\\(B_{i,j} = 0.008 \\\\), for \\\\( i\\neq j\\\\)\n* 30 graph realizations \n* G =21 is generated from one of the following change scenarios\n\n\n\n####Change scenarios:\n* ####Split\n\n<img src =\"https://raw.githubusercontent.com/raazesh-sainudiin/scalable-data-science/master/db/studentProjects/06_ShakiraSuwan/images/ab8f3dfe-2517-11e6-9a20-13bcf50b1617.png\" width=\"300\">\n\n* ####Form\n\n<img src =\"https://raw.githubusercontent.com/raazesh-sainudiin/scalable-data-science/master/db/studentProjects/06_ShakiraSuwan/images/a388654a-2517-11e6-8121-52e74e8b9875.png\" width=\"300\">\n\n* ####Shift\n\n<img src 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width=\"300\">\n","commandVersion":0,"state":"finished","results":null,"errorSummary":null,"error":null,"startTime":0.0,"submitTime":1.46483974892E12,"finishTime":0.0,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"shakira.suwan@pg.canterbury.ac.nz","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"db36b2fc-aa38-48a6-9bca-9aa6d8a796b1"},{"version":"CommandV1","origId":121839,"guid":"b40431b7-5306-401f-bba4-963f0a918898","subtype":"command","commandType":"auto","position":8.0,"command":"%md \n## Source Code","commandVersion":0,"state":"finished","results":null,"errorSummary":null,"error":null,"startTime":0.0,"submitTime":1.464839748973E12,"finishTime":0.0,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"shakira.suwan@pg.canterbury.ac.nz","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"bbf9675c-f6bf-4789-a7c9-70893340f5dc"},{"version":"CommandV1","origId":121840,"guid":"da36de32-3788-454c-ac68-87d4ca6050ba","subtype":"command","commandType":"auto","position":9.5,"command":"%md\nFirst let's import various libraries.","commandVersion":0,"state":"finished","results":null,"errorSummary":null,"error":null,"startTime":0.0,"submitTime":0.0,"finishTime":0.0,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"05755d5c-7240-45c4-940d-4f429ab3e23a"},{"version":"CommandV1","origId":121841,"guid":"d564733f-0b7f-49c5-8a00-5e10ecd1a573","subtype":"command","commandType":"auto","position":11.0,"command":"import breeze.linalg._\nimport breeze.numerics._\nimport breeze.stats.distributions._","commandVersion":0,"state":"finished","results":{"type":"html","data":"<div class=\"ansiout\">import breeze.linalg._\nimport breeze.numerics._\nimport breeze.stats.distributions._\n</div>","arguments":{},"addedWidgets":{},"removedWidgets":[]},"errorSummary":"The spark context has been stopped or the cluster has been terminated. Please restart the cluster or attach this notebook to a different cluster.","error":null,"startTime":1.464839963241E12,"submitTime":1.464839749065E12,"finishTime":1.464839964873E12,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"shakira.suwan@pg.canterbury.ac.nz","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"2bdb9f6e-d33f-442d-a47e-58bcb89e2b8b"},{"version":"CommandV1","origId":123471,"guid":"50739cd2-8f38-4de6-b4e5-7f5e4f838094","subtype":"command","commandType":"auto","position":11.5625,"command":"%md\n####Powerlaw Distribution \n\n* This function returns \\\\(n\\\\) random numbers generated from a powerlaw distribution.","commandVersion":0,"state":"finished","results":null,"errorSummary":null,"error":null,"startTime":0.0,"submitTime":1.464839749085E12,"finishTime":0.0,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"shakira.suwan@pg.canterbury.ac.nz","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"5dba2304-7175-46a7-b57e-eeccf199e2d0"},{"version":"CommandV1","origId":121842,"guid":"ea486f5b-74eb-4e88-8875-c5dcc122b4dd","subtype":"command","commandType":"auto","position":12.125,"command":"def powerlawRnd(n:Int,xmin:Double, alpha:Double ):DenseVector[Double]={\n \n val u=Range(0,n).map(v=>{\n var r= new scala.util.Random\n r.nextDouble()\n }).toArray\n \n val plx=u.map(a=>xmin*pow((1-a),(-1/alpha-1)))\n new DenseVector(plx)\n}\n","commandVersion":0,"state":"finished","results":{"type":"html","data":"<div class=\"ansiout\">powerlawRnd: (n: Int, xmin: Double, alpha: Double)breeze.linalg.DenseVector[Double]\n</div>","arguments":{},"addedWidgets":{},"removedWidgets":[]},"errorSummary":"The spark context has been stopped or the cluster has been terminated. Please restart the cluster or attach this notebook to a different cluster.","error":null,"startTime":1.464839964878E12,"submitTime":1.464839749161E12,"finishTime":1.46483996702E12,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"shakira.suwan@pg.canterbury.ac.nz","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"d135b4ca-8eba-48fe-ab16-d767d9985f55"},{"version":"CommandV1","origId":123472,"guid":"3bc19fd4-840a-4fe7-9b48-80fc61cc405a","subtype":"command","commandType":"auto","position":12.3125,"command":"%md\n#### DCSBM Graphs\n* This function returns an \\\\(n_1 \\times n_2\\\\) degree corrected stochastic blockmodel graph","commandVersion":0,"state":"finished","results":null,"errorSummary":null,"error":null,"startTime":0.0,"submitTime":1.464839749179E12,"finishTime":0.0,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"shakira.suwan@pg.canterbury.ac.nz","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"7b40e67c-58d6-45b9-8df7-583116af0cf0"},{"version":"CommandV1","origId":121843,"guid":"98e15189-9a16-4f0d-9567-6d6a3a15b92b","subtype":"command","commandType":"auto","position":12.5,"command":"def constructGraph(K:Int,p:DenseVector[Double], r:Double, theta1:DenseVector[Double],theta2:DenseVector[Double],lambda:Double,rho:DenseVector[Double],N1:Int,N2:Int):DenseMatrix[Double]={ \n\nvar n1_block:DenseVector[Double]= rho :* N1.toDouble\nn1_block = floor(n1_block)\nvar n1_ind = DenseMatrix.zeros[Double](K,2)\nval tmp = accumulate(n1_block)\nn1_ind(::,1) := tmp -1.toDouble\nn1_ind(0,0) = 0;\nn1_ind(1 to -1,0) := tmp(0 to -1-1) \n\n\nvar n2_block:DenseVector[Double]= rho :* N2.toDouble\nn2_block = floor(n2_block)\nvar n2_ind = DenseMatrix.zeros[Double](K,2)\nval tmp2 = accumulate(n2_block)\nn2_ind(::,1) := tmp2 - 1.toDouble\nn2_ind(0,0) = 0;\nn2_ind(1 to -1,0) := tmp2(0 to -1-1) \n \nvar temp1 = DenseMatrix.fill(K,K){n1_block(1)}\nvar temp2 = DenseMatrix.fill(K,K){n2_block(1)}\nvar expectedNum = temp1 :* temp2\n \n\nvar p2:DenseVector[Double]=null\nif(p.length==1){ \n var p1=p(0)\n p2= DenseVector.fill(K){p1}\n}else{\n p2 = p\n}\n \nvar p1 = DenseVector.rangeD(1,K+1,1):* p2//clear structure (p1>p2) \nvar B = (lambda*DenseMatrix.eye[Double](K):* diag(p1)) :* expectedNum :+ ((1-lambda) * DenseMatrix.fill(K,K)(r) :*expectedNum) \n \n // generate node probabilities\n \nvar Z1 = DenseMatrix.zeros[Double](N1,K)\nvar Z2 = DenseMatrix.zeros[Double](N2,K)\nvar blockDeg1 = DenseVector.zeros[Double](K)\nvar blockDeg2 = DenseVector.zeros[Double](K)\nvar rowDeg = DenseVector.zeros[Double](N1)\nvar colDeg = DenseVector.zeros[Double](N2)\n \nval n1Ind = n1_ind.mapValues(_.toInt)\nval n2Ind = n2_ind.mapValues(_.toInt)\nfor(k <- 0 to K-1){\n blockDeg1(k) = sum(theta1.slice(n1Ind(k,0),n1Ind(k,1)))\n blockDeg2(k) = sum(theta2.slice(n2Ind(k,0),n2Ind(k,1)))\n \n rowDeg.slice(n1Ind(k,0),n1Ind(k,1)) := theta1.slice(n1Ind(k,0),n1Ind(k,1)) :/ blockDeg1(k)\n colDeg.slice(n2Ind(k,0),n1Ind(k,1)) := theta2.slice(n2Ind(k,0),n2Ind(k,1)) :/ blockDeg2(k)\n Z1(n1Ind(k,0) to n1Ind(k,1), k) := 1.0;\n Z2(n2Ind(k,0) to n2Ind(k,1), k) := 1.0;\n}\n \nvar nodeProb = diag(rowDeg) * Z1 * B * Z2.t * diag(colDeg)\n \n // create graph realizations\nvar W = DenseMatrix.zeros[Double](N1,N2)\nfor(i<-0 to N1-1){\n for(j<- i+1 to N2-1){\n var poi= Poisson(nodeProb(i,j))\n W(i ,j) = poi.draw\n }\n}\nvar A = W\nfor(i<-0 to N1-1){\n for(j<- i+1 to N2-1){\n if(W(i,j)!=0.0)\n A(i ,j) = 1.0\n }\n}\n var A1 = upperTriangular(A) + upperTriangular(A).t\n A1\n \n}","commandVersion":0,"state":"finished","results":{"type":"html","data":"<div class=\"ansiout\">constructGraph: (K: Int, p: breeze.linalg.DenseVector[Double], r: Double, theta1: breeze.linalg.DenseVector[Double], theta2: breeze.linalg.DenseVector[Double], lambda: Double, rho: breeze.linalg.DenseVector[Double], N1: Int, N2: Int)breeze.linalg.DenseMatrix[Double]\n</div>","arguments":{},"addedWidgets":{},"removedWidgets":[]},"errorSummary":"The spark context has been stopped or the cluster has been terminated. Please restart the cluster or attach this notebook to a different cluster.","error":null,"startTime":1.464839967023E12,"submitTime":1.464839749215E12,"finishTime":1.46483997041E12,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"shakira.suwan@pg.canterbury.ac.nz","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"32465c3f-8a3b-4d12-b01b-c59254ab41c1"},{"version":"CommandV1","origId":123473,"guid":"46c519e1-bf9b-4605-a38d-1648a68d0b06","subtype":"command","commandType":"auto","position":12.75,"command":"%md \n#### Change Scenarios \n* This function returns an \\\\(n_1 \\times n_2\\\\) changed dcsbm graph.","commandVersion":0,"state":"finished","results":null,"errorSummary":null,"error":null,"startTime":0.0,"submitTime":1.464839749244E12,"finishTime":0.0,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"shakira.suwan@pg.canterbury.ac.nz","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"e9fadef1-e131-421c-a0dc-c1221f3229b6"},{"version":"CommandV1","origId":121844,"guid":"b4e663fd-2a1e-4f85-9709-0e064c60f765","subtype":"command","commandType":"auto","position":13.0,"command":"// create an anomaly graph, form, split, shift\ncase class graphAnomalyClass(W:DenseMatrix[Double],A1:DenseVector[Double], A2:DenseVector[Double])\ndef createA_anomaly(K:Int,p:Double, r:Double, theta1:DenseVector[Double],theta2:DenseVector[Double],lambda:Double,rho:DenseVector[Double],changeType:String, graphType:String):graphAnomalyClass={ \n \n var N1:Int = theta1.length\n var N2:Int = theta2.length\n val s1 = rho(0)*N1.toDouble\n val s2 = rho(1)*N2.toDouble\n var s1_temp = DenseVector.fill(K){s1}\n var s2_temp = DenseVector.fill(K){s2}\n val s1_cumsum = accumulate(s1_temp)\n var s2_cumsum = accumulate(s2_temp)\n val constD = DenseVector{0.0}\n val constI = DenseVector{0}\n var W_poi:DenseMatrix[Double]=null\n var anomalies1:DenseVector[Double]=null\n var anomalies2:DenseVector[Double]=null\n changeType match{\n case \"form\" => \n var pnew = DenseVector.fill(K)(p)\n pnew(0) = pnew(0)*3.0 \n W_poi = constructGraph(K,pnew,r,theta1,theta2,lambda,rho,N1,N2)\n anomalies1 = DenseVector.rangeD(1, s1_cumsum(0)+1,1)\n anomalies2 = DenseVector.rangeD(1, s2_cumsum(0)+1,1) \n \n case \"split\" =>\n var stmp1 = DenseVector.vertcat(constD,s1_temp)\n var stmp2 = DenseVector.vertcat(constD,s2_temp)\n val k2 = K+1\n val temp1 = stmp1(1)*0.5\n val temp2 = stmp2(1)*0.5\n stmp1(0)= temp1\n stmp1(1)= stmp1(1) - temp1\n stmp2(0)= temp2\n stmp2(1)= stmp2(1) - temp2\n val rho_tmp = stmp1 :/ N1.toDouble \n anomalies1 = DenseVector.rangeD(1,s1_temp(0)+1.0,1)\n anomalies2 = DenseVector.rangeD(1,s2_temp(0)+1.0,1)\n var pnew = DenseVector.fill(k2){p} \n \n for(i <- 1 to pnew.length-1){\n pnew(i) = pnew(i)*(1.0/(i+1.0))\n }\n var rowV = DenseVector.range(1,k2,1) \n rowV = DenseVector.vertcat(constI+1,rowV) \n var pnew1 = pnew:*rowV.mapValues(_.toDouble) \n W_poi = constructGraph(k2,pnew1,r,theta1,theta2,lambda,rho_tmp,N1,N2)\n \n case \"shift\" =>\n var stmp1 = s1_temp\n val temp1 = stmp1(0)*0.5\n stmp1(0) = stmp1(0) - temp1\n stmp1(1) = stmp1(1) + temp1\n var stmp2 = s2_temp\n val temp2 = stmp2(0)*0.5\n stmp2(0) =stmp2(0) - temp2\n stmp2(1) =stmp2(1) + temp2\n var rho_tmp = stmp1:/N1.toDouble\n var pnew = DenseVector.fill(K){p} \n anomalies1 = DenseVector.rangeD(stmp1(0),(stmp1(0)+temp1)+1.0)\n anomalies2 = DenseVector.rangeD(stmp2(0),(stmp2(0)+temp2)+1.0) \n W_poi = constructGraph(K,pnew,r,theta1,theta2,lambda,rho_tmp,N1,N2)\n }\n val result=graphAnomalyClass(W_poi,anomalies1,anomalies2)\n result\n}","commandVersion":0,"state":"finished","results":{"type":"html","data":"<div class=\"ansiout\">defined class graphAnomalyClass\ncreateA_anomaly: (K: Int, p: Double, r: Double, theta1: breeze.linalg.DenseVector[Double], theta2: breeze.linalg.DenseVector[Double], lambda: Double, rho: breeze.linalg.DenseVector[Double], changeType: String, graphType: String)graphAnomalyClass\n</div>","arguments":{},"addedWidgets":{},"removedWidgets":[]},"errorSummary":"The spark context has been stopped or the cluster has been terminated. Please restart the cluster or attach this notebook to a different cluster.","error":null,"startTime":1.464839970413E12,"submitTime":1.464839749288E12,"finishTime":1.464839971679E12,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"shakira.suwan@pg.canterbury.ac.nz","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"dec97499-8615-4a21-bfc5-ba8c741a6eaf"},{"version":"CommandV1","origId":121846,"guid":"67be5774-8390-4abb-9b2c-98f46283e99f","subtype":"command","commandType":"auto","position":14.0,"command":"def preprocessGraph(adj:DenseMatrix[Double],N1:Int,N2:Int):DenseMatrix[Double]={ \n val totalUniqueNode=N1.toDouble+N2.toDouble\n val totalConnection = sum(adj)\n val avgCon=(2.0*totalConnection.toDouble)/totalUniqueNode\n \n val perturbationP = totalConnection / pow(totalUniqueNode,2)\n var W = adj + perturbationP // perturbation\n\n var degree = sum(W(*, ::))\n var invDeg = pow(degree,-0.5)\n var invD = diag(invDeg)\n var normW = invD*W*invD\n normW\n \n}","commandVersion":0,"state":"finished","results":{"type":"html","data":"<div class=\"ansiout\">preprocessGraph: (adj: breeze.linalg.DenseMatrix[Double], N1: Int, N2: Int)breeze.linalg.DenseMatrix[Double]\n</div>","arguments":{},"addedWidgets":{},"removedWidgets":[]},"errorSummary":"The spark context has been stopped or the cluster has been terminated. Please restart the cluster or attach this notebook to a different cluster.","error":null,"startTime":1.464839971686E12,"submitTime":1.464839749319E12,"finishTime":1.464839972544E12,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"shakira.suwan@pg.canterbury.ac.nz","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"93c67a05-586c-43d9-8343-4a9496f6df72"},{"version":"CommandV1","origId":123474,"guid":"08bf5554-9d01-48a2-9f09-0fdce67ab589","subtype":"command","commandType":"auto","position":14.5,"command":"%md\n####Activity Vector\n* compute the singular value decomposition (SVD) and extract the principle singular vector (left singular vector corresponding to the largest singular value)","commandVersion":0,"state":"finished","results":null,"errorSummary":null,"error":null,"startTime":0.0,"submitTime":1.46483974935E12,"finishTime":0.0,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"shakira.suwan@pg.canterbury.ac.nz","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"6f47c40d-316d-4dea-a1d3-ae5eb9d915ac"},{"version":"CommandV1","origId":121845,"guid":"002b6154-72b1-4935-af4a-685122e37191","subtype":"command","commandType":"auto","position":15.0,"command":"def getActivity(edge:DenseMatrix[Double]):DenseVector[Double]={\n val leftSingular= svd(edge) \n var U =leftSingular.U\n var Ac1 = abs(U(::,0)) \n Ac1 \n}","commandVersion":0,"state":"finished","results":{"type":"html","data":"<div class=\"ansiout\">getActivity: (edge: breeze.linalg.DenseMatrix[Double])breeze.linalg.DenseVector[Double]\n</div>","arguments":{},"addedWidgets":{},"removedWidgets":[]},"errorSummary":"The spark context has been stopped or the cluster has been terminated. Please restart the cluster or attach this notebook to a different cluster.","error":null,"startTime":1.464839972546E12,"submitTime":1.464839749397E12,"finishTime":1.464839972787E12,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"shakira.suwan@pg.canterbury.ac.nz","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"ad04beee-6499-489d-b8b1-f57c93262d36"},{"version":"CommandV1","origId":123619,"guid":"e1b6fed3-4870-4903-8e56-b873e703d2a7","subtype":"command","commandType":"auto","position":15.1875,"command":"%md\n#### Activity Vectors in the first window","commandVersion":0,"state":"finished","results":null,"errorSummary":null,"error":null,"startTime":0.0,"submitTime":1.464839749419E12,"finishTime":0.0,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"shakira.suwan@pg.canterbury.ac.nz","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"f47c2d7c-903c-498a-9a8a-3abd9c06227c"},{"version":"CommandV1","origId":121847,"guid":"9030e442-e6df-4594-ae5f-1220ebe9ede9","subtype":"command","commandType":"auto","position":15.375,"command":"// perform SVD and get activity vectors for the first 5 graphs\ndef getFirstActivityVectors(N1:Int,N2:Int,edgeArray:Array[DenseMatrix[Double]],tw:Int):DenseMatrix[Double]={\n var winActivity1= DenseMatrix.zeros[Double](N1,tw) \n for(i<- 0 to (tw-1)){ \n var edge_i=edgeArray(i)\n var W = preprocessGraph(edge_i,N1,N2)\n winActivity1(::,i) := getActivity(W) \n}\n winActivity1\n}","commandVersion":0,"state":"finished","results":{"type":"html","data":"<div class=\"ansiout\">getFirstActivityVectors: (N1: Int, N2: Int, edgeArray: Array[breeze.linalg.DenseMatrix[Double]], tw: Int)breeze.linalg.DenseMatrix[Double]\n</div>","arguments":{},"addedWidgets":{},"removedWidgets":[]},"errorSummary":"The spark context has been stopped or the cluster has been terminated. Please restart the cluster or attach this notebook to a different cluster.","error":null,"startTime":1.464839972789E12,"submitTime":1.464839749466E12,"finishTime":1.46483997306E12,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"shakira.suwan@pg.canterbury.ac.nz","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"c9453829-e71e-4b57-8427-ccca832acae8"},{"version":"CommandV1","origId":123620,"guid":"7c25eecb-230c-4e5f-9d23-788b13224c6b","subtype":"command","commandType":"auto","position":15.4375,"command":"%md \nLet's use MLlib svd rountine next.","commandVersion":0,"state":"finished","results":null,"errorSummary":null,"error":null,"startTime":0.0,"submitTime":1.464839749494E12,"finishTime":0.0,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"shakira.suwan@pg.canterbury.ac.nz","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"ffafc691-173c-4c1c-9291-ba78df309895"},{"version":"CommandV1","origId":121848,"guid":"3e6b32b9-3377-4dde-8cd3-2e8669929933","subtype":"command","commandType":"auto","position":15.5,"command":"// MLlib svd\nimport org.apache.spark.mllib.linalg.Matrix\nimport org.apache.spark.mllib.linalg.distributed.RowMatrix\nimport org.apache.spark.mllib.linalg.SingularValueDecomposition\nimport org.apache.spark.mllib.linalg.distributed.{IndexedRow, IndexedRowMatrix}\n\ndef getSvdSpark(winActivity:DenseMatrix[Double]):DenseVector[Double] = {\nval tWinAc1_0 = winActivity.t\nval arr = new Array[(Int, Array[Double])](tWinAc1_0.cols)\n for(i <- 0 until tWinAc1_0.cols) {\n arr(i) = (i, tWinAc1_0(::,i).toArray)\n }\nval rdd = sc.parallelize(arr)\n\nrdd.cache()\n val svd = new IndexedRowMatrix(rdd.map{case(row: Int, colVector: Array[Double]) => {\n new IndexedRow(row, new org.apache.spark.mllib.linalg.DenseVector(colVector))\n }}).computeSVD(5, true, 1e-9)\n rdd.unpersist()\nval uMatrix = svd.U.rows\nval firstCol = DenseVector.zeros[Double](uMatrix.count.toInt)\nuMatrix.collect.foreach{row => {\n firstCol(row.index.toInt) = row.vector(0)\n}}\n abs(firstCol)\n}\n ","commandVersion":0,"state":"finished","results":{"type":"html","data":"<div class=\"ansiout\">import org.apache.spark.mllib.linalg.Matrix\nimport org.apache.spark.mllib.linalg.distributed.RowMatrix\nimport org.apache.spark.mllib.linalg.SingularValueDecomposition\nimport org.apache.spark.mllib.linalg.distributed.{IndexedRow, IndexedRowMatrix}\ngetSvdSpark: (winActivity: breeze.linalg.DenseMatrix[Double])breeze.linalg.DenseVector[Double]\n</div>","arguments":{},"addedWidgets":{},"removedWidgets":[]},"errorSummary":"The spark context has been stopped or the cluster has been terminated. Please restart the cluster or attach this notebook to a different cluster.","error":null,"startTime":1.464839973064E12,"submitTime":1.464839749532E12,"finishTime":1.464839973521E12,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"shakira.suwan@pg.canterbury.ac.nz","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"1702e7fb-682a-401e-8f83-1747031c9753"},{"version":"CommandV1","origId":121849,"guid":"04729901-6cfc-41cc-ba98-7b2b78053726","subtype":"command","commandType":"auto","position":15.5625,"command":"%md\n##Generate DCSBM Graphs","commandVersion":0,"state":"finished","results":null,"errorSummary":null,"error":null,"startTime":0.0,"submitTime":1.464839749575E12,"finishTime":0.0,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"shakira.suwan@pg.canterbury.ac.nz","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"4c546f2f-9329-4edb-b4f6-c932877a3299"},{"version":"CommandV1","origId":121850,"guid":"00e05775-1522-4228-ae9f-a3448e94a64d","subtype":"command","commandType":"auto","position":15.625,"command":"// Parameter settings\nvar graphType:String = \"unipartite\"\nvar N1:Int = 900\nvar N2:Int = N1\nvar K1:Int = 3\nvar K2:Int = 3\nvar s1:Double = N1/K1\nvar s2:Double = N2/K2\nvar rho1 = DenseVector.fill(K1){s1/N1}\nvar rho2 = DenseVector.fill(K2){s2/N2}\nvar p =DenseVector[Double]{0.05} // within block probability\nvar r:Double = 0.008 // between block probabilty\nvar lambda:Double = 0.8 //signal in the graph\nval nd: Int = 29 // graph realization sets\nvar beforeChange:String = \"simple\"\nvar changeType:String = \"shift\" // form, split, shift\nval tw =5\n// parameter for the powerLaw degree distribution\nval beta:Double = 2.5\nval xmin:Double = 1\nvar theta1 = DenseVector.zeros[Double](N1)\nvar theta2 = DenseVector.zeros[Double](N2)\nif(graphType == \"unipartite\"){\n N2 = N1\n K2 = K1\n theta1 = powerlawRnd(N1,xmin,beta) // generate powerlaw random variable \n theta2 = theta1\n}else{ \n theta1 = powerlawRnd(N1,xmin,beta) // type 1 node \n theta2 = powerlawRnd(N2,xmin,beta) // type 2 node\n}\n","commandVersion":0,"state":"finished","results":{"type":"html","data":"<div class=\"ansiout\">graphType: String = unipartite\nN1: Int = 900\nN2: Int = 900\nK1: Int = 3\nK2: Int = 3\ns1: Double = 300.0\ns2: Double = 300.0\nrho1: breeze.linalg.DenseVector[Double] = DenseVector(0.3333333333333333, 0.3333333333333333, 0.3333333333333333)\nrho2: breeze.linalg.DenseVector[Double] = DenseVector(0.3333333333333333, 0.3333333333333333, 0.3333333333333333)\np: breeze.linalg.DenseVector[Double] = DenseVector(0.05)\nr: Double = 0.008\nlambda: Double = 0.8\nnd: Int = 29\nbeforeChange: String = simple\nchangeType: String = shift\ntw: Int = 5\nbeta: Double = 2.5\nxmin: Double = 1.0\ntheta1: breeze.linalg.DenseVector[Double] = DenseVector(321.52979319034984, 29.90430071357021, 3.8131325057399845, 2.110870346481692, 3.5903974838038706, 1.7820198019307625, 1.8958116967986849, 2.340958732456228, 2.438216369024197, 6.0161685498780715, 6.141661314497876, 1.5010864231679477, 2.574276600148193, 11.51242875492055, 30.663819477830625, 1.2642255433118352, 13.419530135215028, 2.161665194607944, 1.666117045016207, 62.2880631314573, 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1.4172137301893377, 1.1531701723045942, 1.462487434275048, 5.5987935896847345, 1.28831728351524, 3.611143215912892, 2.224316896401353, 9.03953620616361, 81.51325648173835, 30.085124363089722, 1.9312471292142717, 1.3092495914632019, 25.37371117840254, 8.405464955219129, 1.0261320295856313, 1.2322437896387128, 1.24875992298269, 1.935761163906034, 4.196755833335895, 3.5539849036023727, 1.1798201783139193, 1.7983979775849734, 1.2792809073699596, 5.591870011948141, 26.07558852861867, 6.453951928856153, 49.046783116458506, 10.003988038102136, 4.25469569123575, 8.614003246553612, 1.1653582852358415, 7.180330542721905, 191.90121200587245, 13.38427898163767, 79.80726761289242, 1.3789183658710498, 2.9160989926152934, 1.4567610244202418, 4.164078742859197, 63.623198929510885, 1.1369714513408626, 5.495235364219996, 2.927526877725072, 1.093880013321569, 32.18081414713918, 3.716081025300188, 1.4448242443528152, 6.835496412821226, 4.028163999575485, 1.2415176636583114, 1.3592591532391347, 1.0776291174246635, 1.8589388572941115, 5.079190291643576, 2.082269956480783, 1.322113122832993, 1.613261143422763, 42.77728804243997, 1.3887523464757807, 1.532122971267311, 5.180743037005496, 7.408235969428793, 1.4564318180535616, 5.4472720195061815, 1.0746294586790315, 2.1062403255942765, 16.363387543624608, 1.454738491753614, 41.65422574598576, 1.9432360003152245, 18.063823492428906, 1.4848380248913726, 286.9348064330177, 5.278108966768818, 13.412154292189859, 2.0854128160894643, 52.64448202641718, 3.213097697748853, 23.23047089586063, 1.168173879601893, 9.533604541704872, 7.049814100288208, 3.4815063139739775, 1.6188555596924394, 1.2466356757690795, 1.2167592037581587, 68.29211004476483, 1.119093145757415, 4.417577812399449, 8.04363987770888, 1.3026518950919728, 2.4309584773274784, 10.387646252355669, 2.002681404307972, 1.4081041686510714, 1.5035849337797127, 1.2362990223916046, 2.5121932465497405, 9.47895285290117, 2.157506649781247, 1.6467237484635306, 2.676783993021413, 2.0520761804651704, 5.3244114226763, 1.129628367236582, 1.4801996504862527, 16.86205790337014, 23.597361156987706, 2.0231135680331627, 1.6651852550363597, 151.49502485853623, 16.239610238420344, 4.1146780907495515, 1.6908442348676593, 9.693924515853112, 4.350725481173378, 1388.3231240229215, 2.0336374073191332, 1.8185696369938236, 1.1798278247535758, 1.729350952986593, 5.687874183550335, 2.620969383989831, 1.2760747002751898, 1.4562745330264366, 3.5896712281731875, 1.030599290518794, 1.1069831933283565, 3.035088725150175, 2.581639186224783, 6.427979955718173, 9.529065900963943, 1.4179555660102414, 83.62566710395319, 3.576017401492991, 2.434702097363553, 2.04479500037912, 2.1669866198766954, 2.91007653497154, 4.881613945649881, 1.457059223010274, 1.2784570100833577, 1.1736876878352072, 1.9133569491359632, 43.08616533788833, 1.0032813405277778, 14.42666183765739, 3.0045481167730075, 6.2485343042688966, 2.9213815987960614, 6.159558009482315, 67.66896538337211, 1.9462132814785986, 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3.5928790618604185)\n</div>","arguments":{},"addedWidgets":{},"removedWidgets":[]},"errorSummary":"The spark context has been stopped or the cluster has been terminated. Please restart the cluster or attach this notebook to a different cluster.","error":null,"startTime":1.464839973524E12,"submitTime":1.464839749621E12,"finishTime":1.464839974649E12,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"shakira.suwan@pg.canterbury.ac.nz","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"0b967abd-c245-4989-be23-a83c9da3509d"},{"version":"CommandV1","origId":121851,"guid":"cce77d29-0f82-41bf-99c1-7d3dd56bce1e","subtype":"command","commandType":"auto","position":15.75,"command":"// generate a dynamic network\n\nval tChange = 20 // at day 21 is the change\nvar sparseA: Array[DenseMatrix[Double]]=new Array[DenseMatrix[Double]](nd+1)\nvar anomaly1:DenseVector[Double]=null\nvar anomaly2:DenseVector[Double]=null\nfor (m <- 0 to nd){ \n if(m<tChange && m >tChange){\n sparseA(m) = constructGraph(K1,p,r, theta1,theta2,lambda,rho1,N1,N2) \n }else{ \n val G = createA_anomaly(K2, p(0), r, theta1,theta2,lambda,rho2,changeType,graphType)\n sparseA(m) = G.W\n anomaly1 =G.A1\n anomaly2 =G.A2\n \n }\n // create graph 1:20 from Dist A\n // create graph 21 from Dist B\n // create graph 22:30 graph Dist A\n \n}\n","commandVersion":0,"state":"finished","results":{"type":"html","data":"<div class=\"ansiout\">tChange: Int = 20\nsparseA: Array[breeze.linalg.DenseMatrix[Double]] = \nArray(0.0 1.0 1.0 0.0 1.0 0.0 0.0 0.0 0.0 1.0 1.0 0.0 ... 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(900 total)\n1.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 ...\n0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 1.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 1.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 1.0 0.0 0.0 0.0 1.0 0.0 1.0 1.0 1.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0 1.0 1.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n... (900 total), 0.0 1.0 0.0 0.0 1.0 0.0 1.0 0.0 0.0 1.0 1.0 1.0 ... (900 total)\n1.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 1.0 0.0 1.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 ...\n1.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 1.0 0.0 1.0 0.0 0.0 1.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 1.0 1.0 1.0 0.0 0.0 0.0 1.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n... (900 total), 0.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 ... (900 total)\n1.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 1.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 1.0 0.0 0.0 1.0 0.0 0.0 0.0 1.0 1.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 1.0 1.0 1.0 0.0 0.0 0.0 1.0 0.0 1.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 1.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 ...\n0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n... (900 total), 0.0 1.0 1.0 1.0 1.0 0.0 1.0 1.0 0.0 1.0 0.0 0.0 ... (900 total)\n1.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 1.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 1.0 1.0 1.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 1.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n... (900 total), 0.0 1.0 1.0 1.0 0.0 0.0 0.0 1.0 0.0 1.0 1.0 0.0 ... (900 total)\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 1.0 1.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 1.0 0.0 1.0 1.0 0.0 1.0 1.0 0.0 1.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 1.0 1.0 0.0 0.0 0.0 ...\n0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n... (900 total), 0.0 1.0 1.0 0.0 0.0 1.0 0.0 1.0 0.0 1.0 0.0 0.0 ... (900 total)\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 1.0 0.0 0.0 0.0 1.0 0.0 0.0 1.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 1.0 0.0 0.0 1.0 0.0 0.0 1.0 1.0 0.0 1.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 1.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 ...\n1.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 1.0 0.0 ...\n0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n... (900 total), 0.0 1.0 1.0 0.0 1.0 0.0 0.0 1.0 1.0 1.0 0.0 1.0 ... (900 total)\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 1.0 0.0 0.0 0.0 1.0 0.0 1.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 1.0 0.0 1.0 0.0 0.0 1.0 0.0 0.0 1.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n... (900 total), 0.0 1.0 1.0 0.0 1.0 0.0 0.0 0.0 1.0 1.0 1.0 1.0 ... (900 total)\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 1.0 0.0 0.0 1.0 0.0 1.0 0.0 0.0 ...\n0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 1.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 1.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n1.0 0.0 1.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n... (900 total), 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 1.0 0.0 ... 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Please restart the cluster or attach this notebook to a different cluster.","error":null,"startTime":1.464839974652E12,"submitTime":1.464839749659E12,"finishTime":1.464839981645E12,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"shakira.suwan@pg.canterbury.ac.nz","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"ec03bdc8-eba9-44ed-8391-6406d15ae594"},{"version":"CommandV1","origId":121852,"guid":"4846e388-b456-4334-a911-f998e783d1aa","subtype":"command","commandType":"auto","position":16.0,"command":"%md ","commandVersion":0,"state":"finished","results":null,"errorSummary":null,"error":null,"startTime":0.0,"submitTime":1.464839749685E12,"finishTime":0.0,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"shakira.suwan@pg.canterbury.ac.nz","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"9fb0fc0c-0287-4e9b-849f-da8eadb383ff"},{"version":"CommandV1","origId":121853,"guid":"848f4914-33ea-4847-9d3a-6d63f98c2b9c","subtype":"command","commandType":"auto","position":16.5,"command":"%md\n##Computing node and time scores ","commandVersion":0,"state":"finished","results":null,"errorSummary":null,"error":null,"startTime":0.0,"submitTime":1.46483974973E12,"finishTime":0.0,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"shakira.suwan@pg.canterbury.ac.nz","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"46ef9239-c418-4031-8da6-5e1a54cf37a3"},{"version":"CommandV1","origId":121854,"guid":"9d694f17-85ac-4455-a237-1ad8b9509c7b","subtype":"command","commandType":"auto","position":17.0,"command":"// computing node scores and time scores from day 6 onwards\nvar winAc1_0 = getFirstActivityVectors(N1,N2,sparseA,tw)\nvar nt = sparseA.length-tw \nvar timeScore = DenseVector.zeros[Double](nt)\nvar nodeScore = DenseMatrix.zeros[Double](N1,nt) \n \n for(i <- 0 to nt-1){\n var edge_i= sparseA(i+tw)\n var W_i = preprocessGraph(edge_i,N1,N2)\n var winAc1 = winAc1_0 \n var refAc1 = getSvdSpark(winAc1) // get reference embedding\n var Ac1 = getActivity(W_i) // get current embedding\n \n timeScore(i) = 1 - norm(refAc1.t * Ac1) \n var tmp =(Ac1.t * refAc1)* refAc1.t\n for(j <- 0 to N1-1){\n nodeScore(j,i) = abs((Ac1(j) - tmp.toDenseVector(j)))\n }\n var winAc_tmp = winAc1_0(::,1 to 4)\n winAc1_0 = DenseMatrix.horzcat(winAc_tmp,Ac1.toDenseMatrix.t)\n \n }","commandVersion":0,"state":"finished","results":{"type":"html","data":"<div class=\"ansiout\">winAc1_0: breeze.linalg.DenseMatrix[Double] = \n0.07564693848006343 0.07681150881094234 0.07765151395427256 ... (5 total)\n0.04227227033856251 0.0444170327895681 0.03896304082737878 ...\n0.025474786637534275 0.02352501617282582 0.02035207270650652 ...\n0.021431318360516753 0.02028501280112764 0.017838568968293785 ...\n0.023540031445366802 0.022496922131744816 0.022587589160095175 ...\n0.020294964148287836 0.020285012801127832 0.01913663249225828 ...\n0.019091090406018727 0.020285012801127798 0.020352072706506484 ...\n0.019091090406018592 0.016417585168109854 0.01913663249225808 ...\n0.02029496414828795 0.022496922131744812 0.022587589160095647 ...\n0.030552573959734392 0.021419538390727386 0.02908904099855263 ...\n0.02727263148298942 0.030527781284776533 0.022587589160095383 ...\n0.02354003144536694 0.021419538390727615 0.016438320550755822 ...\n0.021431318360516576 0.020285012801127714 0.023626158053573435 ...\n0.03206698378931308 0.03684805768206093 0.03507337435538447 ...\n0.0393683331515167 0.042232845981650606 0.03771108895141631 ...\n0.0178060073009434 0.023525016172825895 0.017838568968293587 ...\n0.03131893376943966 0.03129313520088851 0.027389413750592267 ...\n0.0190910904060188 0.020285012801127794 0.020352072706506574 ...\n0.02251038079552057 0.019083156547384506 0.01783856896829369 ...\n0.05184443789335012 0.05269939061164104 0.05025970470433096 ...\n0.020294964148287915 0.02249692213174454 0.020352072706506387 ...\n0.01642065952121696 0.014907119849998408 0.016438320550755663 ...\n0.023540031445366864 0.019083156547384454 0.019136632492258242 ...\n0.0281284956031507 0.02249692213174476 0.029089040998552657 ...\n0.05045392184765106 0.05446545045217203 0.046282487341424684 ...\n0.046031029727817356 0.03872627010867779 0.040768946901256604 ...\n0.020294964148288023 0.01908315654738461 0.02035207270650646 ...\n0.022510380795520334 0.017800336605863925 0.02035207270650624 ...\n0.021431318360516396 0.021419538390727307 0.020352072706506644 ...\n0.036232395320779036 0.035540815886535924 0.03295683704106671 ...\n0.03814490767258131 0.031293135200888215 0.03641612155745413 ...\n0.019091090406018696 0.020285012801127815 0.01913663249225791 ...\n0.02251038079552061 0.020285012801127787 0.021498907501500863 ...\n0.020294964148288026 0.020285012801127666 0.020352072706506484 ...\n0.019091090406018477 0.02352501617282608 0.019136632492258058 ...\n0.022510380795520278 0.024510023795615888 0.022587589160095387 ...\n0.04445906192369122 0.04750539006269844 0.05304728908068331 ...\n0.01909109040601863 0.026369888652049735 0.027389413750592017 ...\n0.0697780354939515 0.06693699627198468 0.06880306164043018 ...\n0.022510380795520344 0.017800336605863998 0.01913663249225786 ...\n0.03131893376943964 0.034868821507913254 0.02649875139122498 ...\n0.01909109040601855 0.01780033660586411 0.022587589160095446 ...\n0.03876144757667444 0.04223284598165078 0.036416121557454474 ...\n0.019091090406018744 0.017800336605864057 0.01913663249225805 ...\n0.01490711984999847 0.020285012801127832 0.01783856896829375 ...\n0.021431318360516583 0.02249692213174487 0.016438320550755663 ...\n0.02251038079552034 0.02141953839072755 0.02149890750150056 ...\n0.02251038079552045 0.019083156547384468 0.01913663249225837 ...\n0.02547478663753448 0.022496922131744545 0.02149890750150085 ...\n0.020294964148288075 0.02141953839072742 0.020352072706506644 ...\n0.0327979768618979 0.03811048564372217 0.035751052417797295 ...\n0.034213140165916395 0.030527781284776425 0.03222044300508959 ...\n0.02143131836051678 0.01908315654738455 0.01913663249225824 ...\n0.06374092100270674 0.06586817766058116 0.06595371110589164 ...\n0.017806007300943585 0.014907119849998408 0.017838568968293535 ...\n0.016420659521217 0.017800336605864123 0.020352072706506488 ...\n0.023540031445367076 0.021419538390727688 0.01783856896829376 ...\n0.01909109040601853 0.02352501617282601 0.024620956615850398 ...\n0.03351302915469017 0.03052778128477629 0.03771108895141653 ...\n0.03206698378931338 0.03204021209716 0.029089040998552817 ...\n0.020294964148287846 0.025456946929896824 0.02557709258275421 ...\n0.034899209115711406 0.03620033804276647 0.037711088951416324 ...\n0.024526494191758834 0.022496922131744736 0.027389413750592218 ...\n0.050453921847651115 0.047505390062698355 0.0483120406910927 ...\n0.017806007300943616 0.02028501280112768 0.019136632492258245 ...\n0.022510380795520295 0.020285012801127683 0.02035207270650643 ...\n0.03131893376943958 0.027252264273843845 0.02908904099855324 ...\n0.01909109040601846 0.01641758516810983 0.02035207270650657 ...\n0.017806007300943588 0.023525016172826062 0.022587589160095452 ...\n0.019091090406018616 0.019083156547384548 0.02258758916009539 ...\n0.02354003144536685 0.023525016172825857 0.02649875139122506 ...\n0.02143131836051653 0.020285012801127655 0.02035207270650629 ...\n0.017806007300943585 0.017800336605863942 0.019136632492258242 ...\n0.053198620763568884 0.04800080171766995 0.05213465793687767 ...\n0.019091090406018366 0.022496922131744423 0.016438320550755874 ...\n0.01642065952121695 0.01908315654738459 0.016438320550755663 ...\n0.02354003144536672 0.025456946929896748 0.02362615805357296 ...\n0.02547478663753465 0.02810695267333977 0.028252011360402427 ...\n0.01909109040601869 0.019083156547384596 0.017838568968294007 ...\n... (900 total)\nnt: Int = 25\ntimeScore: breeze.linalg.DenseVector[Double] = DenseVector(0.0028465502840171464, 0.002722192901465803, 0.0029186973513897208, 0.003163395276381209, 0.0027109041163621006, 0.002830666345289279, 0.0027114775321523954, 0.0027410185005207754, 0.002864021394196281, 0.0029724351629102364, 0.002728765537939326, 0.00297020436719464, 0.0028471004199570604, 0.003046959526131987, 0.0030594818010618585, 0.002889148765703231, 0.002808150313361235, 0.003052190467420779, 0.002728624440274885, 0.002963887768901108, 0.0030525907062062263, 0.002812022009928028, 0.00315490348788372, 0.002977000199138713, 0.002963287498641831)\nnodeScore: breeze.linalg.DenseMatrix[Double] = \n0.0014142714995389327 0.0011109648728329924 ... (25 total)\n0.004550044244761742 0.0013940358585073503 ...\n9.989600920690643E-4 0.0031564518234939096 ...\n3.028724223677129E-4 9.029142779024037E-4 ...\n0.0017387060608158138 0.001656834199016171 ...\n0.0019155937927404776 0.002970806962811545 ...\n0.0019305371501236006 0.0014878972555986344 ...\n3.1043355758568134E-4 7.056532677250024E-4 ...\n5.714375577331732E-4 6.86397550476437E-4 ...\n0.0020117921785141844 0.001490667368145935 ...\n0.003704223435175305 0.0035419667622176264 ...\n0.0033615081111660026 2.06264918103799E-4 ...\n5.159769436317088E-4 4.1760149359248294E-4 ...\n5.788540308279411E-4 0.006478480909857781 ...\n7.259181763597938E-4 1.7310913553962581E-4 ...\n3.131815707309374E-4 4.8401991687782933E-4 ...\n0.0019985456494306456 2.3096182898144774E-4 ...\n3.485412661441978E-4 0.0025627058835662464 ...\n0.002087345909488437 0.0020805156286904138 ...\n0.00242791860727809 6.687502100171591E-4 ...\n8.000340763305303E-4 2.567199352952569E-4 ...\n8.538307679360965E-4 8.673982808902955E-4 ...\n6.56840326298265E-4 0.0018427598056139638 ...\n1.904876846407083E-4 5.367913047191544E-5 ...\n0.0010329339764022644 0.0015628639107123712 ...\n0.0074618054464083775 0.0014754222757620214 ...\n0.0029672186559664485 0.0012004792474718216 ...\n0.0021398246952716235 3.336097257389571E-4 ...\n4.208013632445544E-4 1.7911215854128984E-4 ...\n0.0015551620755180767 0.004935225182297651 ...\n7.995049584018851E-4 3.978150662245772E-4 ...\n3.1052163978532304E-4 0.0035236590515106657 ...\n0.0020272253622151334 2.3609878330697887E-4 ...\n0.003362220406474506 0.0031102255529273475 ...\n8.847823027376134E-5 0.0025159123340200325 ...\n0.0026199794666912773 0.0016130837096775125 ...\n0.002235235579407767 0.001613018853332003 ...\n0.0037212848100389474 0.001992718302981377 ...\n5.925708521059975E-4 9.214728762115404E-4 ...\n5.236603181662559E-4 4.115365642030598E-4 ...\n0.00236026545066937 0.0030353537189464486 ...\n0.0014869285905952205 2.1513645526647848E-4 ...\n0.0029063000829789784 0.0010248245409780893 ...\n1.3750169926745812E-4 0.001455743508738793 ...\n0.0025623631939250685 0.0017146006560995151 ...\n5.29975089874693E-4 0.00265169866110615 ...\n0.002347799119170872 1.5389839543568026E-4 ...\n1.236043456309746E-4 0.0017227078575056884 ...\n0.0012679542381221522 3.195580377710408E-4 ...\n0.0026896431703014867 6.344822996993266E-4 ...\n0.0018864244967274034 2.051088292572209E-4 ...\n8.608980281688619E-4 3.4012790714117724E-4 ...\n0.0010258507578634161 4.680324090814321E-4 ...\n0.0017007269388690655 0.0018976318582129698 ...\n9.151613897637675E-4 2.5724761948540953E-4 ...\n8.189129830768124E-4 0.0019267344383576135 ...\n9.797351968384924E-5 9.494751185528706E-4 ...\n0.0023943759429739947 0.0010260092500832402 ...\n7.105034516773322E-4 0.0015870581647909818 ...\n0.00428512349119016 4.7839604503679967E-4 ...\n0.004876249042850306 0.005857544614946971 ...\n0.003146411540741058 0.005221216201552539 ...\n0.003000314212850578 0.001483052181621286 ...\n6.821809114975555E-4 0.0023564755581926486 ...\n3.358553230286311E-4 0.0021494659534952443 ...\n0.005599027530205046 0.003845423161712075 ...\n3.706860237419618E-4 2.2264962412445535E-4 ...\n0.002232036575989152 0.0041162640226677025 ...\n0.00167293569121095 2.735620528510306E-4 ...\n0.00367395766091581 0.0022713661269749934 ...\n6.764935360296549E-4 4.4495388630535343E-4 ...\n7.176350045684891E-4 0.0015659391385583442 ...\n0.0024222844171363014 7.212229851940137E-4 ...\n0.0011702416834849447 5.909400815124893E-4 ...\n1.3304616635300553E-4 0.0011492297938385972 ...\n0.0011172614391392992 0.0010504589275555053 ...\n0.0034346898400479248 6.195527957960321E-4 ...\n2.640760026070485E-4 0.005771070476548599 ...\n0.0015621785501864043 5.101871593625219E-4 ...\n... (900 total)\n</div>","arguments":{},"addedWidgets":{},"removedWidgets":[]},"errorSummary":"The spark context has been stopped or the cluster has been terminated. Please restart the cluster or attach this notebook to a different cluster.","error":null,"startTime":1.464839981649E12,"submitTime":1.464839749768E12,"finishTime":1.464840014506E12,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"shakira.suwan@pg.canterbury.ac.nz","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"9e39003e-0f76-4b57-a097-8c1d3cfec650"},{"version":"CommandV1","origId":121855,"guid":"026599ff-0c34-47a2-9972-c9149a0e5ea3","subtype":"command","commandType":"auto","position":18.5,"command":"%md\n##Results","commandVersion":0,"state":"finished","results":null,"errorSummary":null,"error":null,"startTime":0.0,"submitTime":1.464839749791E12,"finishTime":0.0,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"shakira.suwan@pg.canterbury.ac.nz","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"9843b3ea-b5ed-4d42-b88c-c863ff202cc9"},{"version":"CommandV1","origId":121856,"guid":"2a89676e-81ae-44e1-a86f-cd028e5f111d","subtype":"command","commandType":"auto","position":18.78125,"command":"// \nimport org.apache.spark.sql.types._\nimport org.apache.spark.sql.DataFrame\n\ndef convertScore(matrix:DenseMatrix[Double]):DataFrame={\n//val matrix = timeScore.toDenseMatrix\nval n = matrix.rows\nval m = matrix.cols\nval tSb = sc.broadcast(matrix)\n\n// creating schema for DataFrame matrix\nval columns = for (i <- 0 until m) yield StructField(s\"$i\", DoubleType, false)\nval indexColumn = Seq(StructField(\"index\", IntegerType, false))\nval schema = StructType(indexColumn ++ columns)\n\nval df = sqlContext.createDataFrame(sc.parallelize(0 until n).map { v => \n val values = v +: tSb.value(v,::).t.toArray\n Row(values: _*)\n}, schema)\n df\n \n}","commandVersion":0,"state":"finished","results":{"type":"html","data":"<div class=\"ansiout\">import org.apache.spark.sql.types._\nimport org.apache.spark.sql.DataFrame\nconvertScore: (matrix: breeze.linalg.DenseMatrix[Double])org.apache.spark.sql.DataFrame\n</div>","arguments":{},"addedWidgets":{},"removedWidgets":[]},"errorSummary":"The spark context has been stopped or the cluster has been terminated. Please restart the cluster or attach this notebook to a different cluster.","error":null,"startTime":1.464840014511E12,"submitTime":1.464839749837E12,"finishTime":1.464840014967E12,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"shakira.suwan@pg.canterbury.ac.nz","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"35ce0ed5-039a-485c-a7ba-ec5c0eec698a"},{"version":"CommandV1","origId":121857,"guid":"98224e28-bfe0-4d21-b217-cddb4317a64f","subtype":"command","commandType":"auto","position":18.796875,"command":"val tScoreDF = convertScore(timeScore.toDenseMatrix)\nval nodeScoreDF = convertScore(nodeScore.toDenseMatrix)\n\ntScoreDF.registerTempTable(\"timeScore_table\")\nnodeScoreDF.registerTempTable(\"nodeScore_table\")","commandVersion":0,"state":"finished","results":{"type":"html","data":"<div class=\"ansiout\">tScoreDF: org.apache.spark.sql.DataFrame = [index: int, 0: double, 1: double, 2: double, 3: double, 4: double, 5: double, 6: double, 7: double, 8: double, 9: double, 10: double, 11: double, 12: double, 13: double, 14: double, 15: double, 16: double, 17: double, 18: double, 19: double, 20: double, 21: double, 22: double, 23: double, 24: double]\nnodeScoreDF: org.apache.spark.sql.DataFrame = [index: int, 0: double, 1: double, 2: double, 3: double, 4: double, 5: double, 6: double, 7: double, 8: double, 9: double, 10: double, 11: double, 12: double, 13: double, 14: double, 15: double, 16: double, 17: double, 18: double, 19: double, 20: double, 21: double, 22: double, 23: double, 24: double]\n</div>","arguments":{},"addedWidgets":{},"removedWidgets":[]},"errorSummary":"The spark context has been stopped or the cluster has been terminated. Please restart the cluster or attach this notebook to a different cluster.","error":null,"startTime":1.464840014969E12,"submitTime":1.464839749865E12,"finishTime":1.464840015228E12,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"shakira.suwan@pg.canterbury.ac.nz","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"1d21dd9a-8ea4-494a-bc1b-fe8ff9c7ccf6"},{"version":"CommandV1","origId":121858,"guid":"7a22f9fc-ca86-4f8b-a2df-c0625f8a071f","subtype":"command","commandType":"auto","position":18.8125,"command":"%r\ntimedf <- sql(sqlContext, \"FROM timeScore_table SELECT *\")\ntimeScore <- collect(timedf)\nnodedf <- sql(sqlContext, \"FROM nodeScore_table SELECT *\")\nnodeScore <- collect(nodedf)\n\n\n\n","commandVersion":0,"state":"finished","results":{"type":"html","data":"<pre style=\"font-size:10p\"></pre><pre style = 'font-size:10pt'></pre>","arguments":{},"addedWidgets":{},"removedWidgets":[]},"errorSummary":"The spark context has been stopped or the cluster has been terminated. Please restart the cluster or attach this notebook to a different cluster.","error":null,"startTime":1.46484001523E12,"submitTime":1.464839749894E12,"finishTime":1.464840019302E12,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"shakira.suwan@pg.canterbury.ac.nz","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"79ce3033-0947-4d58-b02e-f954c5842e6a"},{"version":"CommandV1","origId":121859,"guid":"d4bf9846-bbf7-4ad6-9011-9eb66ebc560e","subtype":"command","commandType":"auto","position":18.875,"command":"%r\ndisplay(timeScore)\ndisplay(nodeScore)\n","commandVersion":0,"state":"finished","results":{"type":"table","data":[[0.0,0.0014142714995389327,0.0011109648728329924,0.004260704049500852,0.002180973759360272,0.002501709157137877,9.20346934636232E-4,0.0035641468193753495,0.0010242622629044323,0.003047050874356763,0.0011996400315565092,1.7818916956670316E-4,0.0031882734340981517,0.003653823045235108,0.0010549644283597004,1.6487045464849692E-4,0.0015719165310672245,0.0010961630005562745,7.065557358229141E-4,0.0030480210493186027,0.002346435376071848,0.002026048837352648,7.780758410246558E-4,6.66962599547849E-5,0.0016428673885182238,0.0051119356568758295],[9.0,0.0020117921785141844,0.001490667368145935,0.0038993920133119225,8.317025442396118E-4,0.0030058903558950745,0.002246139699928304,0.0010135751038465209,0.0014515544043772442,0.0021753190309055127,0.004325417838886278,1.4081560796917053E-4,9.581292937206262E-5,0.0030682881895536494,6.238490806574556E-4,0.0022823140436844247,0.0016094626026370296,4.988546579312476E-4,0.006532846495977535,0.0027783899887954266,0.006280720378235384,0.005881872774379775,0.0035637633389268737,0.005478320158595416,7.143754447497611E-4,0.0038930895608973067],[99.0,0.0015955776486096356,0.0017107080041613362,0.0013856229887739754,2.1749781791538525E-4,0.001840779863797444,0.002219062627398235,0.001063678130610736,0.0013904040954183447,0.0030734517978950535,0.0032884855397030052,0.003028502753291567,0.0025985415644950716,0.0010686936298908573,0.0013192876386781509,6.046584618838967E-4,8.713082660798364E-4,1.0615278615801887E-4,7.357588445354724E-4,0.0016334656708530647,0.0019872211562607274,0.004994088573544213,7.999137195524066E-4,0.001761751029409779,0.002484862559823057,7.321032358698354E-4],[100.0,0.0028384822239035483,0.0021572746126124857,0.002052541197605423,8.378095793975214E-4,0.002180646961130777,0.0024280900792301337,9.424209312952313E-4,6.342274318787561E-4,0.002909797447941953,0.0015805298317753125,4.412505192567112E-6,3.64131918343287E-5,2.0110106483869558E-4,3.73020371434947E-4,0.0020623973081682866,0.0024701235611207586,3.205729847979358E-4,0.0031169716376977102,0.0035672012278766922,0.005646300069462838,3.0469832856923687E-4,0.001509994597544296,3.8207277203243517E-4,0.003540729175662772,0.001520704663365742],[101.0,7.449671314660594E-4,0.0029679807297431013,0.001974327180662306,0.0016369435899168568,5.924922774348529E-4,3.286152775646839E-4,0.0034072840766300252,5.432892557863736E-5,0.002282661010248665,0.0015343227513792378,0.004387157221735237,0.0022886994363682314,1.384821217689583E-4,1.098138934185304E-4,0.0028939255088366485,3.8351443131560276E-4,0.0011110231645356343,0.0017028519260044207,0.004491097699148072,0.0023892497172387506,6.015002736724437E-4,8.687536903440977E-4,7.976161040241826E-4,0.001655158828774709,1.632412373909209E-4],[102.0,0.0040069961871096425,0.0014770983876395798,6.810848053293017E-4,0.0012455361782057056,0.0017219101289353417,0.0025423606816450013,7.676603810787344E-4,0.002587655012250903,0.003544169019913942,0.0032645713635812076,0.0012417113070804092,0.001747845241520645,8.508534380484781E-4,0.003505421388662878,0.0055519528619624205,6.154076285134688E-5,0.0016458945467591399,3.761806115688583E-4,8.000359444629429E-4,0.0017130115113110252,6.695507021057465E-4,0.0016537481861889844,1.2422993004478425E-4,0.0010959401893524852,6.572394028073539E-5],[103.0,7.787537546421509E-4,7.064895151889863E-4,0.0036511836312860466,0.0015206551797637378,0.0016551754368469042,0.0014027952449275384,0.002396061423981785,1.6634355803107556E-4,0.0015765206093287486,0.0012925013811833815,0.004963465561477927,0.0039792839708628035,0.0043304876240155,4.990615900891948E-4,0.003174797888280831,0.0020077209933522036,0.002473901884729811,0.0022685458593877383,9.860028087342182E-4,0.001576290332751775,0.002171600983466134,0.0014392958912596496,6.11618178811002E-4,0.0024371181925436046,0.001264917645599245],[104.0,2.713658135775239E-4,8.476316145873998E-4,9.332344978221808E-4,0.0035402632465941046,0.001263816157133231,0.001225589539644592,0.006696254717885354,0.0020234460920907707,2.1559832604809218E-4,5.832395235104391E-4,0.003903082637181206,0.005773558678934615,0.0016898907543063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ACM, 2004. ](http://dl.acm.org/citation.cfm?id=1014102)\n\n* [Brian Karrer and M. E. J. Newman, Stochastic blockmodels and community structure in networks, Phys. Rev. E 83, 016107 ? Published 21 January 2011](http://journals.aps.org/pre/abstract/10.1103/PhysRevE.83.016107).\n","commandVersion":0,"state":"finished","results":null,"errorSummary":null,"error":null,"startTime":0.0,"submitTime":1.464839750364E12,"finishTime":0.0,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"shakira.suwan@pg.canterbury.ac.nz","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"b9d12418-2491-428f-8665-8bb02322409c"}],"dashboards":[],"guid":"a9c52190-94ce-4aca-b71e-74a42adc00d1","globalVars":{},"iPythonMetadata":null,"inputWidgets":{}};</script> <script src="https://databricks-prod-cloudfront.cloud.databricks.com/static/201602081754420800-0c2673ac858e227cad536fdb45d140aeded238db/js/notebook-main.js" onerror="window.mainJsLoadError = true;"></script> </head> <body> <script> if (window.mainJsLoadError) { var u = 'https://databricks-prod-cloudfront.cloud.databricks.com/static/201602081754420800-0c2673ac858e227cad536fdb45d140aeded238db/js/notebook-main.js'; var b = document.getElementsByTagName('body')[0]; var c = document.createElement('div'); c.innerHTML = ('<h1>Network Error</h1>' + '<p><b>Please check your network connection and try again.</b></p>' + '<p>Could not load a required resource: ' + u + '</p>'); c.style.margin = '30px'; c.style.padding = '20px 50px'; c.style.backgroundColor = '#f5f5f5'; c.style.borderRadius = '5px'; b.appendChild(c); } </script> </body> </html>