NeuronDeconstructionRotors.scala:113 executed in 0.00 seconds (0.000 gc):
allData.filter(_._1 == layer).filter(_._2 == band).map(t => t._3.toInt -> t._4).toMap
Returns
{
"1800" : 4.233657195565574,
"756" : 9.550170673019423,
"317" : 4.52350696373959,
"256" : 3.6961381453640607,
"609" : 9.278873007955735,
"394" : 8.072655945408101,
"490" : 8.128745838594275,
"1166" : 6.41219517866365,
"939" : 8.402159586427164,
"1449" : 5.085277161753734
}
NeuronDeconstructionRotors.scala:113 executed in 0.00 seconds (0.000 gc):
allData.filter(_._1 == layer).filter(_._2 == band).map(t => t._3.toInt -> t._4).toMap
Returns
{
"1800" : 4.921530377376821,
"756" : 9.406073299014853,
"317" : 0.7498997137406651,
"256" : 0.10113800332254293,
"609" : 8.018048591658372,
"394" : 3.4548075423024747,
"490" : 5.051636814412211,
"1166" : 6.126794423461974,
"939" : 8.269645305783772,
"1449" : 6.202689469298683
}
NeuronDeconstructionRotors.scala:113 executed in 0.00 seconds (0.000 gc):
allData.filter(_._1 == layer).filter(_._2 == band).map(t => t._3.toInt -> t._4).toMap
Returns
{
"1800" : 2.5946682967754833,
"756" : 3.3542378328259095,
"317" : 6.058476230243639,
"256" : 5.166747157518961,
"609" : 4.598726316948596,
"394" : 8.71892775762446,
"490" : 6.550808625815272,
"1166" : 2.6989320093981264,
"939" : 2.7984523898104623,
"1449" : 2.8103735543338564
}
NeuronDeconstructionRotors.scala:113 executed in 0.00 seconds (0.000 gc):
allData.filter(_._1 == layer).filter(_._2 == band).map(t => t._3.toInt -> t._4).toMap
Returns
{
"1800" : 8.511021460774245,
"756" : 6.3807418140120244,
"317" : 2.434186933714212,
"256" : 2.5611960147412454,
"609" : 4.616027982005862,
"394" : 3.4383376979326106,
"490" : 3.798857074180225,
"1166" : 7.634564202329536,
"939" : 7.289212984956649,
"1449" : 8.708457069332097
}
NeuronDeconstructionRotors.scala:113 executed in 0.00 seconds (0.000 gc):
allData.filter(_._1 == layer).filter(_._2 == band).map(t => t._3.toInt -> t._4).toMap
Returns
{
"1800" : 5.484169245303247,
"756" : 8.42287331516696,
"317" : 3.786986388760258,
"256" : 2.879870193041101,
"609" : 7.653849662786303,
"394" : 6.524308927205144,
"490" : 7.734823986241708,
"1166" : 6.233423739109112,
"939" : 7.246955730093225,
"1449" : 6.1313008550225065
}
NeuronDeconstructionRotors.scala:113 executed in 0.00 seconds (0.000 gc):
allData.filter(_._1 == layer).filter(_._2 == band).map(t => t._3.toInt -> t._4).toMap
Returns
{
"1800" : 8.13402546998952,
"756" : 6.096967114490413,
"317" : 1.2438346943152803,
"256" : 1.7316847002627898,
"609" : 4.464172313948607,
"394" : 1.5376103634813003,
"490" : 3.0059120119074167,
"1166" : 7.440984636884766,
"939" : 6.492288761137395,
"1449" : 8.405206236934001
}
NeuronDeconstructionRotors.scala:113 executed in 0.00 seconds (0.000 gc):
allData.filter(_._1 == layer).filter(_._2 == band).map(t => t._3.toInt -> t._4).toMap
Returns
{
"1800" : 5.343313980662962,
"756" : 8.345073333897052,
"317" : 2.179377428312995,
"256" : 1.6945729879472329,
"609" : 7.271646436633302,
"394" : 4.390811429834184,
"490" : 5.905758356941598,
"1166" : 5.795454183709966,
"939" : 6.856552417937438,
"1449" : 5.9247577758062455
}
NeuronDeconstructionRotors.scala:113 executed in 0.00 seconds (0.000 gc):
allData.filter(_._1 == layer).filter(_._2 == band).map(t => t._3.toInt -> t._4).toMap
Returns
{
"1800" : 4.648635876105852,
"756" : 6.695929731768207,
"317" : 4.493251402881377,
"256" : 2.8875247383756295,
"609" : 7.094252724023092,
"394" : 8.330348545495344,
"490" : 7.495945023968309,
"1166" : 4.890385571028403,
"939" : 5.580394156771351,
"1449" : 4.702218397237194
}
NeuronDeconstructionRotors.scala:113 executed in 0.00 seconds (0.000 gc):
allData.filter(_._1 == layer).filter(_._2 == band).map(t => t._3.toInt -> t._4).toMap
Returns
{
"1800" : 4.501824618295767,
"756" : 8.25720999559679,
"317" : 5.627487950711226,
"256" : 7.488158533767778,
"609" : 8.070153565177707,
"394" : 6.8463111318343755,
"490" : 7.664112480674066,
"1166" : 5.870964810181231,
"939" : 6.852761111492101,
"1449" : 5.393928922061149
}
NeuronDeconstructionRotors.scala:113 executed in 0.00 seconds (0.000 gc):
allData.filter(_._1 == layer).filter(_._2 == band).map(t => t._3.toInt -> t._4).toMap
Returns
{
"1800" : 4.6053953484632375,
"756" : 7.9902441911399364,
"317" : 3.714709799660712,
"256" : 3.9241673134419384,
"609" : 7.60351471062285,
"394" : 6.464983297017764,
"490" : 7.11625378827254,
"1166" : 5.569081654070186,
"939" : 6.7127324823214085,
"1449" : 5.182693356030826
}
