diff --git a/app/build.gradle b/app/build.gradle
index 745bd06136b44c7729689c4f9eb3957e967c3073..ad9df2f06a1dc6a1e10a1a025a226e09b3ba3f32 100644
--- a/app/build.gradle
+++ b/app/build.gradle
@@ -66,9 +66,11 @@ dependencies {
//Neural network
// https://mavenlibs.com/maven/dependency/org.jetbrains.kotlinx/kotlin-deeplearning-api
-// implementation ("org.jetbrains.kotlinx:kotlin-deeplearning-api:0.4.0") {
-// exclude(group = "org.apache.commons", module = "commons-lang3")
-// }
+// implementation ("org.jetbrains.kotlinx:kotlin-deeplearning-api:0.4.0")
+
+ implementation ("org.jetbrains.kotlinx:kotlin-deeplearning-api:0.4.0") {
+ exclude group:"org.apache.commons", module:"commons-lang3"
+ }
// implementation 'org.tensorflow:tensorflow-lite:2.0.0'
diff --git a/app/src/main/java/com/example/mindrover/EegSignalFragment.kt b/app/src/main/java/com/example/mindrover/EegSignalFragment.kt
index 92bfa476d6f61447e0a09e049e12f2e968f0f834..be562e3caff8b03e96fc2d8475fde1a4dfd2498a 100644
--- a/app/src/main/java/com/example/mindrover/EegSignalFragment.kt
+++ b/app/src/main/java/com/example/mindrover/EegSignalFragment.kt
@@ -16,12 +16,12 @@ import com.jjoe64.graphview.series.DataPoint
import com.jjoe64.graphview.series.LineGraphSeries
import kotlinx.coroutines.launch
-
/**
* A simple [Fragment] subclass.
* Use the [EegSignalFragment.newInstance] factory method to
* create an instance of this fragment.
*/
+
class EegSignalFragment : Fragment() {
private val eegListener: EEGDataListener by viewModels()
diff --git a/app/src/main/java/com/example/mindrover/TestFragment.kt b/app/src/main/java/com/example/mindrover/TestFragment.kt
index d52ddfb56193d3d7787314a3832064f91c15e7a9..37c8d6c386669e35a522ba9c6001459454157130 100644
--- a/app/src/main/java/com/example/mindrover/TestFragment.kt
+++ b/app/src/main/java/com/example/mindrover/TestFragment.kt
@@ -60,19 +60,19 @@ class TestFragment : Fragment() {
graphSeries = graphSeries.plus(LineGraphSeries())
}
- lifecycleScope.launch {
-
-
- lifecycle.repeatOnLifecycle(Lifecycle.State.STARTED) {
- eegListener.latestData.collect {
-// if (graphView1 != null)
-// Log.d("Retrevition", "Package size ${it.size}")
- for (i in 0..it.size-1) {
- graphSeries[i].resetData(it[i])
- }
- }
- }
- }
+// lifecycleScope.launch {
+//
+//
+// lifecycle.repeatOnLifecycle(Lifecycle.State.STARTED) {
+// eegListener.latestData.collect {
+//// if (graphView1 != null)
+//// Log.d("Retrevition", "Package size ${it.size}")
+// for (i in 0..it.size-1) {
+// graphSeries[i].resetData(it[i])
+// }
+// }
+// }
+// }
}
override fun onCreateView(
diff --git a/app/src/main/java/com/example/mindrover/TrainFragment.kt b/app/src/main/java/com/example/mindrover/TrainFragment.kt
index 376024c3152a459bbdd1f421e1921901e7639451..ad6fb383996866dedc006017cd090ffea4c956e4 100644
--- a/app/src/main/java/com/example/mindrover/TrainFragment.kt
+++ b/app/src/main/java/com/example/mindrover/TrainFragment.kt
@@ -15,10 +15,11 @@ import com.example.mindrover.model.EEGDataListener
import com.example.mindrover.model.ExperimentCommand
import com.example.mindrover.model.ExperimentNavigator
import com.example.mindrover.model.ExperimentState
+import kotlin.math.exp
class TrainFragment : Fragment() {
-// private val experimentNavigator: ExperimentNavigator by viewModels()
+ private val experimentNavigator: ExperimentNavigator by viewModels()
private val eegDataListener: EEGDataListener by viewModels()
private lateinit var binding: FragmentTrainBinding
@@ -27,8 +28,6 @@ class TrainFragment : Fragment() {
override fun onCreate(savedInstanceState: Bundle?) {
super.onCreate(savedInstanceState)
-
-
}
override fun onCreateView(
@@ -39,6 +38,16 @@ class TrainFragment : Fragment() {
// binding.imageView3.setImageResource(R.drawable.ic_arrow_circle_left)
// binding.startTrainTexview.setText(R.string.left_command)
+
+ return binding.root
+ }
+
+
+ override fun onViewCreated(view: View, savedInstanceState: Bundle?) {
+ super.onViewCreated(view, savedInstanceState)
+
+ experimentRuns = true
+
val commandObserver = Observer<ExperimentCommand> { state ->
binding.imageView3.setImageResource(state.imgId)
if (experimentRuns) {
@@ -46,8 +55,8 @@ class TrainFragment : Fragment() {
binding.startTrainTexview.setText(state.textId)
}
}
- eegDataListener.actualCommand.observe(viewLifecycleOwner, commandObserver)
-
+// eegDataListener.actualCommand.observe(viewLifecycleOwner, commandObserver)
+ experimentNavigator.actualCommand.observe(viewLifecycleOwner, commandObserver)
val runningObserver = Observer<ExperimentState> { state ->
if (state == ExperimentState.FINISHED) {
@@ -55,33 +64,26 @@ class TrainFragment : Fragment() {
}
}
- eegDataListener.doesExperimentRun.observe(viewLifecycleOwner, runningObserver)
+ experimentNavigator.doesExperimentRun.observe(viewLifecycleOwner, runningObserver)
val intObserver = Observer<Int> { state ->
binding.imageView3.setImageResource(state)
}
- eegDataListener.experimentRun.observe(viewLifecycleOwner, intObserver)
-
-
+ experimentNavigator.experimentRun.observe(viewLifecycleOwner, intObserver)
- return binding.root
- }
- override fun onViewCreated(view: View, savedInstanceState: Bundle?) {
- super.onViewCreated(view, savedInstanceState)
-
- experimentRuns = true
-
val impedanceObserver = Observer<Array<Double>> { state ->
Log.d("HEllo", "${state.size}")
if (state.size > 0)
binding.startTrainTexview.setText("${state[0]}")
}
-// eegDataListener.impedances.observe(viewLifecycleOwner, impedanceObserver)
+ eegDataListener.impedances.observe(viewLifecycleOwner, impedanceObserver)
+
+ experimentNavigator.startExperiment(5)
}
diff --git a/app/src/main/java/com/example/mindrover/TrainHomeFragment.kt b/app/src/main/java/com/example/mindrover/TrainHomeFragment.kt
index 47577d50ae3bf36e07e611263071062107b5b638..1be43a25f3afd50a8c12d6fb24a1089fe908bb8b 100644
--- a/app/src/main/java/com/example/mindrover/TrainHomeFragment.kt
+++ b/app/src/main/java/com/example/mindrover/TrainHomeFragment.kt
@@ -16,7 +16,7 @@ import com.example.mindrover.model.ExperimentNavigator
class TrainHomeFragment : Fragment() {
private lateinit var binding: FragmentTrainHomeBinding
-// private val experimentNavigator: ExperimentNavigator by viewModels()
+ private val experimentNavigator: ExperimentNavigator by viewModels()
private val eegDataListener: EEGDataListener by viewModels()
@@ -40,8 +40,8 @@ class TrainHomeFragment : Fragment() {
override fun onViewCreated(view: View, savedInstanceState: Bundle?) {
super.onViewCreated(view, savedInstanceState)
binding.button3.setOnClickListener {
-// experimentNavigator.startExperiment(1)
- eegDataListener.startExperiment(3)
+// experimentNavigator.startExperiment(3)
+// eegDataListener.startExperiment(3)
findNavController().navigate(R.id.action_trainHomeFragment_to_trainFragment)
}
}
diff --git a/app/src/main/java/com/example/mindrover/model/EEGDataListener.kt b/app/src/main/java/com/example/mindrover/model/EEGDataListener.kt
index db914781a60c964c16a8556b7ad249d7d174c7ff..e9720e37c907529e4a3a83dd0d09fd281720534a 100644
--- a/app/src/main/java/com/example/mindrover/model/EEGDataListener.kt
+++ b/app/src/main/java/com/example/mindrover/model/EEGDataListener.kt
@@ -8,6 +8,7 @@ import androidx.lifecycle.viewModelScope
import brainflow.BoardIds
import brainflow.BoardShim
import brainflow.BrainFlowInputParams
+import brainflow.BrainFlowPresets
import com.example.mindrover.R
import com.jjoe64.graphview.series.DataPoint
import kotlinx.coroutines.delay
@@ -27,6 +28,9 @@ class EEGDataListener: ViewModel() {
// private val _dataset = MutableLiveData<Array<DataPoint>>()
// val dataset: LiveData<Array<DataPoint>> = _dataset
+ private val _lastData = MutableLiveData<Array<Array<DataPoint>>>()
+ val lastData: LiveData<Array<Array<DataPoint>>> = _lastData
+
private val _impedances = MutableLiveData<Array<Double>>()
val impedances: LiveData<Array<Double>> = _impedances
@@ -49,108 +53,75 @@ class EEGDataListener: ViewModel() {
val latestData: Flow<Array<Array<DataPoint>>> = flow {
- var currentData = arrayOf<Array<DataPoint>>()
- for (i in 0 until numOfChannels) {
- wholeData = wholeData.plus(arrayOf<DataPoint>())
- currentData = currentData.plus(arrayOf<DataPoint>())
- }
-
- _impedances.value = emptyArray()
- repeat(numOfChannels) {
- _impedances.value = _impedances.value?.plus(Random.nextDouble()*20+2)
- }
+// fun startStreaming() {
+// viewModelScope.launch {
-//------------------------------------------------------------------------------------------------------------
-// val commands= mutableListOf<ExperimentCommand>()
-//
-// val left = ExperimentCommand("left", R.drawable.ic_arrow_circle_left, R.string.left_command)
-// val right = ExperimentCommand("right", R.drawable.ic_arrow_circle_right, R.string.right_command)
-// val action = ExperimentCommand("action", R.drawable.ic_cancel, R.string.no_command)
-//
-// repeat(5) {
-// commands.add(left)
-// commands.add(right)
-// }
-//
-// commands.shuffle()
-//
-// var commandnumtest = 1
-// var testtimer = 1
-//------------------------------------------------------------------------------------------------------------
+ var currentData = arrayOf<Array<DataPoint>>()
+ for (i in 0 until numOfChannels) {
+ wholeData = wholeData.plus(arrayOf<DataPoint>())
+ currentData = currentData.plus(arrayOf<DataPoint>())
+ }
+ _impedances.value = emptyArray()
+ repeat(numOfChannels) {
+ _impedances.value = _impedances.value?.plus(Random.nextDouble()*20+2)
+ }
- while (true) {
-//Get last package of data
- for (i in 0..5) {
- time++
+ while (true) {
- for (ch in 0 until numOfChannels) {
- if ((time.toInt() % 4000) == 20) {
- wholeData[ch] = wholeData[ch].plus(DataPoint(time, 20.0))
- }
- else {
- wholeData[ch] =
- wholeData[ch].plus(DataPoint(time, Random.nextDouble() * 10))
+ //Get last package of data
+ for (i in 0..5) {
+ time++
+
+ for (ch in 0 until numOfChannels) {
+ if ((time.toInt() % 4000) == 20) {
+ wholeData[ch] = wholeData[ch].plus(DataPoint(time, 20.0))
+ }
+ else {
+ wholeData[ch] =
+ wholeData[ch].plus(DataPoint(time, Random.nextDouble() * 10))
+ }
}
}
- }
-
-//Update dataset
- var imps = _impedances.value!!
- for (i in 0 until numOfChannels) {
- imps[i] = imps[i] + (Random.nextDouble() - 0.5)
- }
- _impedances.value = imps
-
- delay(100)
-
-//Update impedances
- val size = minOf(100, wholeData[0].size)
- for (ch in 0 until numOfChannels) {
- val data = wholeData[ch].takeLast(size).toTypedArray()
- for (i in 0 until size) {
- data[i] = DataPoint(i.toDouble(), data[i].y)
+ //Update dataset
+ var imps = _impedances.value!!
+ for (i in 0 until numOfChannels) {
+ imps[i] = imps[i] + (Random.nextDouble() - 0.5)
}
- currentData[ch] = data
- }
+ _impedances.value = imps
+
+ delay(100)
-//Free memory with whole data
+ //Update impedances
+ val size = minOf(100, wholeData[0].size)
- if (wholeData[0].size > MAXSTOREDPOINT*2) {
for (ch in 0 until numOfChannels) {
- wholeData[ch] = wholeData[ch].takeLast(MAXSTOREDPOINT).toTypedArray()
+ val data = wholeData[ch].takeLast(size).toTypedArray()
+ for (i in 0 until size) {
+ data[i] = DataPoint(i.toDouble(), data[i].y)
+ }
+ currentData[ch] = data
}
- }
-
-
-// testtimer+=1
-// if (testtimer%35==0) {
-// if (testtimer%14 == 0) {
-// commandnumtest += 1
-// commandnumtest = commandnumtest % 10
-// _actualCommand.value = commands[commandnumtest % 10]
-// } else {
-// _actualCommand.value = action
-// }
-//
-//// if (commandnumtest % 2 == 1)
-//// _actualCommand.value = right
-//// else
-//// _actualCommand.value = left
-// Log.d("Feri", "${_actualCommand.value}")
-// }
+ //Free memory with whole data
+ if (wholeData[0].size > MAXSTOREDPOINT*2) {
+ for (ch in 0 until numOfChannels) {
+ wholeData[ch] = wholeData[ch].takeLast(MAXSTOREDPOINT).toTypedArray()
+ }
+ }
- emit(currentData)
+ _lastData.value = currentData
+ emit(currentData)
- }
+ }
+// }
}
@@ -159,7 +130,7 @@ class EEGDataListener: ViewModel() {
// }
init {
- testCoroutine()
+// testCoroutine()
_connection.value = ConnectionState.NO_CONNECTION
// establishConnection()
}
@@ -170,11 +141,30 @@ class EEGDataListener: ViewModel() {
try {
val par = BrainFlowInputParams()
+ par.set_ip_protocol(22)
par.ip_address
+ val shim = BoardShim(38, par)
+// val shim = BoardShim(BoardIds.PIEEG_BOARD, BrainFlowInputParams())
- BoardShim.enable_board_logger()
- BoardShim.get_eeg_channels(4)
- Log.d("Connection", "Ip address: ${par.ip_protocol}")
+// try {
+// BoardShim.enable_board_logger()
+
+// } catch (e: Exception) {
+// Log.d("EEGException","Connection enabled fail")
+// }
+// BoardShim.get_eeg_channels(10)
+// BoardShim.enable_board_logger()
+
+ Log.d("HEllo", "BoardId:${BoardIds.PIEEG_BOARD}")
+// try {
+// val shim = BoardShim(BoardIds.PIEEG_BOARD, BrainFlowInputParams())
+// println(shim.get_board_data().size)
+// } catch (e: Exception) {
+//
+// }
+
+
+ Log.d("EEGConnection", "Ip address: ${par.ip_protocol}")
// Log.d("Connection", "Create dsocket")
// val port = 4210
@@ -183,12 +173,16 @@ class EEGDataListener: ViewModel() {
// Log.d("Connection", "------------------Created dsocket--------------------")
// var serverAddress = InetAddress.getByName("192.168.4.1")
+
+
+
_connection.value = ConnectionState.PENDING
delay(2000)
test_connection_num++
- if (test_connection_num%2 == 0) {
+ if (test_connection_num%2 == 1) {
_connection.value = ConnectionState.CONNECTION
+// startStreaming()
} else {
_connection.value = ConnectionState.NO_CONNECTION
}
@@ -198,114 +192,6 @@ class EEGDataListener: ViewModel() {
}
}
}
-
-
- fun testCoroutine() {
-
- viewModelScope.launch {
- while (true) {
- delay(90)
-
- latestData.collect() {
-// Log.d("Jeromos", "collected ${it.size}")
- }
-
-// Log.d("Signal", "Signal: $signal1")
- }
- }
- }
-
-
-
-// suspend fun streamSimulation() {
-// for (i in 1..10) {
-// delay(20)
-// addRandomData()
-// }
-//
-// while(true) {
-// for (i in 1..10) {
-// delay(20)
-// addRandomData()
-// }
-// updateDataset(20)
-// }
-// }
-
-// fun addRandomData() {
-// time++
-// wholeData.plus(DataPoint(time, Random.nextDouble()*10))
-// }
-//
-// fun updateDataset(num: Int) {
-// _dataset.value = wholeData.takeLast(num).toTypedArray()
-// }
-
-
-
- //-------------------------------------------------------------------------------------------------------------------------
-
- private val _actualCommand = MutableLiveData<ExperimentCommand>()
- val actualCommand: LiveData<ExperimentCommand> = _actualCommand
-
- private val _doesExperimentRun = MutableLiveData<ExperimentState>()
- val doesExperimentRun: LiveData<ExperimentState> = _doesExperimentRun
-
- private val _experimentRun = MutableLiveData<Int>()
- val experimentRun: LiveData<Int> = _experimentRun
-
-
-
-
- init {
- _doesExperimentRun.value = ExperimentState.PENDING
- _experimentRun.value = R.drawable.ic_arrow_circle_right
- }
-
- fun startExperiment(num: Int) {
-
- viewModelScope.launch {
-
-
- val left = ExperimentCommand("left", R.drawable.ic_arrow_circle_left, R.string.left_command)
- val right = ExperimentCommand("right", R.drawable.ic_arrow_circle_right, R.string.right_command)
- val action = ExperimentCommand("action", R.drawable.ic_cancel, R.string.no_command)
-
- val commands= mutableListOf<ExperimentCommand>()
-
- repeat(num) {
- commands.add(left)
- commands.add(right)
- }
-
- commands.shuffle()
-
- _doesExperimentRun.value = ExperimentState.STARTED
- for (comm in commands) {
- Log.d("Experiment", comm.id)
- _actualCommand.value = comm
- _experimentRun.value = comm.imgId
- Log.d("Experiment__", "${_experimentRun.value}")
- Log.d("Experiment__", "${experimentRun.value}")
-
- delay(1000)
-// actualCommand.value?.let { Log.d("Experiment", it.id) }
- _actualCommand.value = action
- _experimentRun.value = R.drawable.ic_cancel
- delay(1000)
- //TODO: Save data
- }
- _doesExperimentRun.value = ExperimentState.FINISHED
-
- Log.d("Jeromos", "${_doesExperimentRun.value}")
- }
- }
-}
-
-data class ExperimentCommand(val id: String, val imgId:Int, val textId:Int)
-
-enum class ExperimentState {
- PENDING, STARTED, FINISHED
}
diff --git a/app/src/main/java/com/example/mindrover/model/ExperimentNavigator.kt b/app/src/main/java/com/example/mindrover/model/ExperimentNavigator.kt
index 81c3ca8d2f4a1c64bd4846dc9b9dde248b4759c1..67f761c41696fa1e891ad70ed35322d74ffcd807 100644
--- a/app/src/main/java/com/example/mindrover/model/ExperimentNavigator.kt
+++ b/app/src/main/java/com/example/mindrover/model/ExperimentNavigator.kt
@@ -10,11 +10,11 @@ import kotlinx.coroutines.delay
import kotlinx.coroutines.launch
-//data class ExperimentCommand(val id: String, val imgId:Int, val textId:Int)
-//
-//enum class ExperimentState {
-// PENDING, STARTED, FINISHED
-//}
+data class ExperimentCommand(val id: String, val imgId:Int, val textId:Int)
+
+enum class ExperimentState {
+ PENDING, STARTED, FINISHED
+}
@@ -39,8 +39,8 @@ class ExperimentNavigator: ViewModel() {
val left = ExperimentCommand("left", R.drawable.ic_arrow_circle_left, R.string.left_command)
- val right = ExperimentCommand("right", R.drawable.ic_arrow_circle_left, R.string.right_command)
- val action = ExperimentCommand("action", R.drawable.ic_arrow_circle_left, R.string.no_command)
+ val right = ExperimentCommand("right", R.drawable.ic_arrow_circle_right, R.string.right_command)
+ val action = ExperimentCommand("action", R.drawable.ic_cancel, R.string.no_command)
val commands= mutableListOf<ExperimentCommand>()
@@ -58,10 +58,10 @@ class ExperimentNavigator: ViewModel() {
_actualCommand.value = comm
_experimentRun.value = comm.imgId
Log.d("Experiment__", "${_experimentRun.value}")
- delay(1000)
+ delay(2000)
// actualCommand.value?.let { Log.d("Experiment", it.id) }
_actualCommand.value = action
- delay(1000)
+ delay(2000)
//TODO: Save data
}
_doesExperimentRun.value = ExperimentState.FINISHED
diff --git a/app/src/main/java/com/example/mindrover/model/NeuralNetwork.kt b/app/src/main/java/com/example/mindrover/model/NeuralNetwork.kt
new file mode 100644
index 0000000000000000000000000000000000000000..2a5aadf0d3c3a95862326c141b8886d4bd499125
--- /dev/null
+++ b/app/src/main/java/com/example/mindrover/model/NeuralNetwork.kt
@@ -0,0 +1,116 @@
+package com.example.mindrover.model
+
+import org.jetbrains.kotlinx.dl.api.core.Sequential
+import org.jetbrains.kotlinx.dl.api.core.activation.Activations
+import org.jetbrains.kotlinx.dl.api.core.initializer.Constant
+import org.jetbrains.kotlinx.dl.api.core.initializer.GlorotNormal
+import org.jetbrains.kotlinx.dl.api.core.initializer.Zeros
+import org.jetbrains.kotlinx.dl.api.core.layer.convolutional.Conv2D
+import org.jetbrains.kotlinx.dl.api.core.layer.convolutional.ConvPadding
+import org.jetbrains.kotlinx.dl.api.core.layer.core.Dense
+import org.jetbrains.kotlinx.dl.api.core.layer.core.Input
+import org.jetbrains.kotlinx.dl.api.core.layer.pooling.AvgPool2D
+import org.jetbrains.kotlinx.dl.api.core.layer.reshaping.Flatten
+import org.jetbrains.kotlinx.dl.dataset.OnHeapDataset
+import org.jetbrains.kotlinx.dl.dataset.handler.NUMBER_OF_CLASSES
+import org.jetbrains.kotlinx.dl.dataset.mnist
+
+
+private const val EPOCHS = 3
+private const val TRAINING_BATCH_SIZE = 1000
+private const val NUM_CHANNELS = 1L
+private const val IMAGE_SIZE = 28L
+private const val SEED = 12L
+private const val TEST_BATCH_SIZE = 1000
+
+
+class NeuralNetwork {
+
+
+ private lateinit var model: Sequential
+
+ val network = Sequential.of(
+ Input(
+ 6L,
+ 200L,
+ 100
+ )
+ )
+
+ init {
+
+ val (train, test) = mnist()
+
+ val heapdata: OnHeapDataset
+
+ model = Sequential.of(
+
+ Input(
+ IMAGE_SIZE,
+ IMAGE_SIZE,
+ NUM_CHANNELS
+ ),
+ Conv2D(
+ filters = 6,
+ kernelSize = intArrayOf(5, 5),
+ strides = intArrayOf(1, 1, 1, 1),
+ activation = Activations.Tanh,
+ kernelInitializer = GlorotNormal(SEED),
+ biasInitializer = Zeros(),
+ padding = ConvPadding.SAME
+ ),
+ AvgPool2D(
+ poolSize = intArrayOf(1, 2, 2, 1),
+ strides = intArrayOf(1, 2, 2, 1),
+ padding = ConvPadding.VALID
+ ),
+ Conv2D(
+ filters = 16,
+ kernelSize = intArrayOf(5, 5),
+ strides = intArrayOf(1, 1, 1, 1),
+ activation = Activations.Tanh,
+ kernelInitializer = GlorotNormal(SEED),
+ biasInitializer = Zeros(),
+ padding = ConvPadding.SAME
+ ),
+ AvgPool2D(
+ poolSize = intArrayOf(1, 2, 2, 1),
+ strides = intArrayOf(1, 2, 2, 1),
+ padding = ConvPadding.VALID
+ ),
+ Flatten(), // 3136
+ Dense(
+ outputSize = 120,
+ activation = Activations.Tanh,
+ kernelInitializer = GlorotNormal(SEED),
+ biasInitializer = Constant(0.1f)
+ ),
+ Dense(
+ outputSize = 84,
+ activation = Activations.Tanh,
+ kernelInitializer = GlorotNormal(SEED),
+ biasInitializer = Constant(0.1f)
+ ),
+ Dense(
+ outputSize = NUMBER_OF_CLASSES,
+ activation = Activations.Linear,
+ kernelInitializer = GlorotNormal(SEED),
+ biasInitializer = Constant(0.1f)
+ )
+
+ )
+
+ }
+
+ fun saveNeuralNetwork(name: String) {
+// model.save('keras-cifar-10/weights', savingFormat='h5')
+//
+//
+// model_json = model.to_json()
+// with open("keras-cifar-10/model.json", "w") as json_file:
+// json_file.write(model_json)
+
+ }
+
+
+}
\ No newline at end of file
diff --git a/app/src/main/res/layout/fragment_game.xml b/app/src/main/res/layout/fragment_game.xml
index adb8e3949adc5a18d0257281685bcfb6ff44ec78..f1ce432c571363b1e3b5bb8cf76c997a76b17cc8 100644
--- a/app/src/main/res/layout/fragment_game.xml
+++ b/app/src/main/res/layout/fragment_game.xml
@@ -5,10 +5,68 @@
android:layout_height="match_parent"
tools:context=".GameFragment">
- <!-- TODO: Update blank fragment layout -->
- <TextView
+ <LinearLayout
android:layout_width="match_parent"
android:layout_height="match_parent"
- android:text="@string/hello_blank_fragment" />
+ android:orientation="vertical">
+
+ <Space
+ android:layout_width="match_parent"
+ android:layout_height="100px" />
+
+ <TextView
+ android:id="@+id/textView2"
+ android:layout_width="match_parent"
+ android:layout_height="wrap_content"
+ android:text="TextView" />
+
+ <Space
+ android:layout_width="match_parent"
+ android:layout_height="100px" />
+
+ <RadioGroup
+ android:layout_width="match_parent"
+ android:layout_height="278dp">
+
+ <RadioButton
+ android:id="@+id/radioButton3"
+ android:layout_width="match_parent"
+ android:layout_height="wrap_content"
+ android:text="RadioButton" />
+
+ <RadioButton
+ android:id="@+id/radioButton4"
+ android:layout_width="match_parent"
+ android:layout_height="wrap_content"
+ android:text="RadioButton" />
+
+ <RadioButton
+ android:id="@+id/radioButton5"
+ android:layout_width="match_parent"
+ android:layout_height="wrap_content"
+ android:text="RadioButton" />
+
+ <RadioButton
+ android:id="@+id/radioButton6"
+ android:layout_width="match_parent"
+ android:layout_height="wrap_content"
+ android:text="RadioButton" />
+
+ </RadioGroup>
+
+ <Space
+ android:layout_width="match_parent"
+ android:layout_height="wrap_content" />
+
+ <Button
+ android:id="@+id/button6"
+ android:layout_width="match_parent"
+ android:layout_height="wrap_content"
+ android:text="Button" />
+
+ <Space
+ android:layout_width="match_parent"
+ android:layout_height="wrap_content" />
+ </LinearLayout>
</FrameLayout>
\ No newline at end of file
diff --git a/app/src/main/res/layout/impedance_item.xml b/app/src/main/res/layout/impedance_item.xml
index b5b6eae303ddcf09129a7f1f5bcdcdb032da900e..5f206694efab9673b879923cf678c0b36c556b27 100644
--- a/app/src/main/res/layout/impedance_item.xml
+++ b/app/src/main/res/layout/impedance_item.xml
@@ -1,18 +1,19 @@
<?xml version="1.0" encoding="utf-8"?>
-<LinearLayout
-xmlns:android="http://schemas.android.com/apk/res/android"
-xmlns:app="http://schemas.android.com/apk/res-auto"
+<LinearLayout xmlns:android="http://schemas.android.com/apk/res/android"
+ xmlns:app="http://schemas.android.com/apk/res-auto"
xmlns:tools="http://schemas.android.com/tools"
android:layout_width="match_parent"
-android:layout_height="wrap_content"
-android:orientation="horizontal">
+ android:layout_height="wrap_content"
+ android:gravity="center"
+ android:orientation="horizontal">
<TextView
android:id="@+id/impedanceChannelTextview"
- android:layout_width="wrap_content"
+ android:layout_width="70dp"
android:layout_height="wrap_content"
android:layout_weight="1"
android:textSize="24sp"
+ android:layout_margin="20dp"
tools:text="Channel" />
<TextView