re #24: Switched the save location selector to a button to work better

re #27: reformatted file names, created version 2 of the SOP
re #28: The script now works with the current model output

BroadbandSpecModule/BroadbandSpecModule.py

@@ -43,8 +43,8 @@ class BroadbandSpecModule(ScriptedLoadableModule):
 
   def __init__(self, parent):
     ScriptedLoadableModule.__init__(self, parent)
-    self.parent.title = "BroadbandSpecModule"  # TODO: make this more human readable by adding spaces
-    self.parent.categories = ["Broadband"]
+    self.parent.title = "Broadband Spectroscopy"  # TODO: make this more human readable by adding spaces
+    self.parent.categories = ["Spectroscopy"]
     self.parent.dependencies = []
     parent.contributors = ["David Morton (Queen's University, PERK Lab)"] 
     self.parent.helpText = """
@@ -94,6 +94,10 @@ def setup(self):
     # Create logic class. Logic implements all computations that should be possible to run
     # in batch mode, without a graphical user interface.
     self.logic = BroadbandSpecModuleLogic()
+    # Make sure parameter node is initialized (needed for module reload)
+    self.initializeParameterNode()
+    self.initializeScene()
+    self.logic.setupLists()
 
     # Connections
 
@@ -119,18 +123,22 @@ def setup(self):
     self.ui.clearLastPointButton.connect('clicked(bool)', self.onClearLastPointButtonClicked)
     # Data Collection
     self.ui.dataClassSelector.connect('currentIndexChanged(int)', self.onDataClassSelectorChanged)
-    self.ui.saveLocationSelector.connect('currentPathChanged(QString)', self.onSaveLocationSelectorChanged)
     # add the options cancer and normal to the data class selector
     self.ui.dataClassSelector.addItem("Cancer")
     self.ui.dataClassSelector.addItem("Normal")
+    self.ui.patientNumberSelector.connect('currentIndexChanged(int)', self.onPatientNumberSelectorChanged)
+    # add the options Patient1 the patient number selector
+    self.ui.patientNumberSelector.addItem("Patient1")
+    # self.ui.saveLocationSelector.connect('currentPathChanged(QString)', self.onSaveLocationSelectorChanged)
+    self.ui.saveDirectoryButton.connect('directorySelected(QString)', self.onSaveDirectoryButtonClicked)
+    # update the saveDirectory using parameter node to the self.logic.SAVE_LOCATION
+    self.ui.saveDirectoryButton.directory = self._parameterNode.GetParameter(self.logic.SAVE_LOCATION)
+
     self.ui.samplingDurationSlider.connect('valueChanged(double)', self.onSamplingDurationChanged)
     self.ui.samplingRateSlider.connect('valueChanged(double)', self.onSamplingRateChanged)
     self.ui.collectSampleButton.connect('clicked(bool)', self.onCollectSampleButtonClicked)
     self.ui.continuousCollectionButton.connect('clicked(bool)', self.onContinuousCollectionButtonClicked)
-    # Make sure parameter node is initialized (needed for module reload)
-    self.initializeParameterNode()
-    self.initializeScene()
-    self.logic.setupLists()
+
 
   def initializeScene(self):
         # NeedleModel
@@ -145,11 +153,6 @@ def initializeScene(self):
             # Add it to parameter node
             self._parameterNode.SetNodeReferenceID(self.logic.NEEDLE_MODEL, needleModel.GetID())
 
-        # # If not already transformed, add it to the NeedleToRas transform
-        # needleModelTransform = needleModel.GetParentTransformNode()
-        # if needleModelTransform is None:
-        #     needleModel.SetAndObserveTransformNodeID(needleToRasTransform.GetID())
-
         # NeedleTip pointlist
 
         # If pointList_NeedleTip is not in the scene, create and add it
@@ -165,10 +168,6 @@ def initializeScene(self):
         if pointList_EMT.GetNumberOfControlPoints() == 0:
             pointList_EMT.AddControlPoint(np.array([0, 0, 0]))
             pointList_EMT.SetNthControlPointLabel(0, "origin_Tip")
-        # # If not already transformed, add it to the NeedleToRas transform
-        # pointList_NeedleTipTransform = pointList_NeedleTip.GetParentTransformNode()
-        # if pointList_NeedleTipTransform is None:
-        #     pointList_NeedleTip.SetAndObserveTransformNodeID(needleToRasTransform.GetID())
         pass
 
   # My functions
@@ -188,6 +187,12 @@ def onDataClassSelectorChanged(self):
     dataClass = self.ui.dataClassSelector.currentText
     parameterNode.SetParameter(self.logic.DATA_CLASS, dataClass)
 
+  def onPatientNumberSelectorChanged(self):
+    self.updateParameterNodeFromGUI()
+    parameterNode = self.logic.getParameterNode()
+    patientNumber = self.ui.patientNumberSelector.currentText
+    parameterNode.SetParameter(self.logic.PATIENT_NUM, patientNumber)
+
   def onSamplingDurationChanged(self):
     self.updateParameterNodeFromGUI()
     parameterNode = self.logic.getParameterNode()
@@ -251,14 +256,17 @@ def onConnectButtonClicked(self):
         pointList_NeedleTip = parameterNode.GetNodeReference(self.logic.POINTLIST_EMT)
         pointList_NeedleTip.SetAndObserveTransformNodeID(transformNode.GetID())
 
-  def onSaveLocationSelectorChanged(self):
-      self.updateParameterNodeFromGUI()
-      # get path from the selector
-      path = self.ui.saveLocationSelector.currentPath
-      # get parameter node
-      parameterNode = self.logic.getParameterNode()
-      # set the path in the parameter node
-      parameterNode.SetParameter(self.logic.SAVE_LOCATION, path)
+
+  def onSaveDirectoryButtonClicked(self):
+    self.updateParameterNodeFromGUI()
+    # get the path from the button
+    path = self.ui.saveDirectoryButton.directory
+    # Print the save directory 
+    print('Save directory: ' + path)
+    # Save that path to the parameter node
+    parameterNode = self.logic.getParameterNode()
+    parameterNode.SetParameter(self.logic.SAVE_LOCATION, path)
+    # pass
 
   def onSpectrumImageChanged(self):
     self.updateParameterNodeFromGUI()
@@ -305,7 +313,6 @@ def setEnableClassification(self, enable):
   def onClearLastPointButtonClicked(self):
     self.updateParameterNodeFromGUI()
     # Check to see if the lists exist, and if not create them
-    # self.logic.setupLists()
     print("This button is not currently implemented")
     pass
 
@@ -316,7 +323,6 @@ def onClearControlPointsButtonClicked(self):
   def onAddControlPointButtonClicked(self):
     self.updateParameterNodeFromGUI()
     # Check to see if the lists exist, and if not create them
-    # self.logic.setupLists()
     self.logic.addControlPointToToolTip()
 
   def onScanButtonClicked(self, checked):
@@ -359,7 +365,6 @@ def initializeParameterNode(self):
     self.setParameterNode(self.logic.getParameterNode())
 
     # Ensure the required lists are created and reference in the parameter node
-    # self.logic.setupLists()
 
     # Select default input nodes if nothing is selected yet to save a few clicks for the user
     if not self._parameterNode.GetNodeReference(self.logic.INPUT_VOLUME):
@@ -416,11 +421,6 @@ def updateGUIFromParameterNode(self, caller=None, event=None):
       # set the current path to whatever is stored in the parameter node
       self.ui.modelFileSelector.currentPath = self._parameterNode.GetParameter(self.logic.MODEL_PATH)
 
-    # Update the save location to be the last selection
-    if self.ui.saveLocationSelector.currentPath == '':
-      # set the current path to whatever is stored in the parameter node
-      self.ui.saveLocationSelector.currentPath = self._parameterNode.GetParameter(self.logic.SAVE_LOCATION)
-
     # All the GUI updates are done
     self._updatingGUIFromParameterNode = False
 
@@ -441,7 +441,6 @@ def updateParameterNodeFromGUI(self, caller=None, event=None):
     parameterNode.SetParameter(self.logic.SCANNING_STATE, str(self.ui.scanButton.isChecked()))
     # update parameter node with the state of enable plotting button
     parameterNode.SetParameter(self.logic.PLOTTING_STATE, str(self.ui.enablePlottingButton.isChecked()))
-    # print("Plotting state: " + str(self.ui.enablePlottingButton.isChecked()))
     # update parameter node with the state of enable classification button
     parameterNode.SetParameter(self.logic.CLASSIFYING_STATE, str(self.ui.enableClassificationButton.isChecked()))
     # update parameter node with the current path of the file selector
@@ -510,6 +509,7 @@ class BroadbandSpecModuleLogic(ScriptedLoadableModuleLogic,VTKObservationMixin):
   SAMPLING_DURATION = "Sample Duration"           # Parameter stores the duration of the sampling
   SAMPLING_RATE = "Sample Rate"                   # Parameter stores the rate of the sampling
   DATA_CLASS = "Data Class"                       # Parameter stores the data class we are recording
+  PATIENT_NUM = "Patient Number"               # Parameter stores the patient number
   SAVE_LOCATION = 'Save Location'                 # Parameter stores the location where the data is saved
 
   # ROLES 
@@ -530,8 +530,9 @@ class BroadbandSpecModuleLogic(ScriptedLoadableModuleLogic,VTKObservationMixin):
   CLASS_LABEL_1 = "ClassLabel1"                   # The label of the second class
   CLASS_LABEL_NONE = "WeakSignal"                 # The label of the class when the signal is too weak
   DISTANCE_THRESHOLD = 1 # in mm
-  DEFAULT_SAVE_LOCATION = os.path.join('C:\Spectroscopy_TrackedTissueSensing\data', 'Nov2022_skinTestData')
+  # DEFAULT_SAVE_LOCATION = os.path.join('C:\Spectroscopy_TrackedTissueSensing\data', 'Nov2022_skinTestData')
   DEFAULT_MODEL_PATH = os.path.join('C:\Spectroscopy_TrackedTissueSensing\TrainedModels', 'KNN_WhiteVsBlue2.joblib')
+  DEFAULT_SAVE_LOCATION = os.path.join('C:\Spectroscopy_TrackedTissueSensing\data', 'SkinDataCollection')
 
   def __init__(self):
     """
@@ -560,9 +561,8 @@ def setDefaultParameters(self, parameterNode):
       parameterNode.SetParameter(self.CLASSIFICATION, '')
     # if the self.model path is not set, grab it from the ctkPathLineEdit widget
     if parameterNode.GetParameter(self.MODEL_PATH) == '':
-      parameterNode.SetParameter(self.MODEL_PATH, 'C:/Spectroscopy_TrackedTissueSensing/TrainedModels/KNN_PorkVsBeefTest.joblib') # Hardcoded path
+      parameterNode.SetParameter(self.MODEL_PATH, self.DEFAULT_MODEL_PATH)
     if self.model == None:
-      # parameterNode = self.getParameterNode()
       modelPath = parameterNode.GetParameter(self.MODEL_PATH)
       self.model = load(modelPath)
 
@@ -602,7 +602,7 @@ def addObservers(self):
     parameterNode = self.getParameterNode()
     spectrumImageNode = parameterNode.GetNodeReference(self.INPUT_VOLUME)
     if spectrumImageNode:
-      print("Add observer to {0}".format(spectrumImageNode.GetName()))
+      # print("Add observer to {0}".format(spectrumImageNode.GetName()))
       self.observerTags.append([spectrumImageNode, spectrumImageNode.AddObserver(vtk.vtkCommand.ModifiedEvent, self.onSpectrumImageNodeModified)])
 
   def removeObservers(self):
@@ -810,8 +810,6 @@ def saveSample(self):
     sampleDuration = parameterNode.GetParameter(self.SAMPLING_DURATION)
     # Stop the timer
     browserNode = parameterNode.GetNodeReference(self.SAMPLE_SEQ_BROWSER)
-    # browserNode.SetRecordingActive(False)
-    # print("Recording stopped")
     # Get the sequence node
     sequenceNode = parameterNode.GetNodeReference(self.SAMPLE_SEQUENCE)
     # Save the sequence to a csv
@@ -824,45 +822,46 @@ def saveSample(self):
     # Check to see if any data has been recorded
     if sequenceLength == 0:
       print("No data to save")
-      # Get the number of files in the folder
-      # numFiles = len([name for name in os.listdir(savePath) if os.path.isfile(os.path.join(savePath, name))])
-      # print("Number of files in folder: " + str(numFiles))
-      # Get the path to the current folder
-      currentPath = os.getcwd()
-      print(currentPath)
-      # add the data folder 
-      dataPath = os.path.join(currentPath, "Data")
-      currentPath = os.join
       return
 
     # print("Sequence length: " + str(sequenceLength))
     # Format the empty array
     spectrumArray = slicer.util.arrayFromVolume(sequenceNode.GetNthDataNode(0)) # Get the length of a spectrum
     SpectrumLength = spectrumArray.shape[2]
-    spectrumArray2D = np.zeros((sequenceLength + 1, SpectrumLength + 1)) # Create the 2D array
-    timeVector = np.linspace(0, float(sampleDuration), sequenceLength) # create a time vector using the sampleDuration
-    spectrumArray2D[1:,0] = timeVector # concatenate the time vector to the spectrum array
-    # print shape of the array
-    # print(spectrumArray2D.shape)
+    spectrumArray2D = np.zeros((sequenceLength + 1, SpectrumLength + 1))        # Create the 2D array, add 1 for wavelength and time
+    timeVector = np.linspace(0, float(sampleDuration), sequenceLength)          # create a time vector using the sampleDuration
+    spectrumArray2D[1:,0] = timeVector                                          # concatenate the time vector to the spectrum array
+    waveLengthVector = spectrumArray[0,0,:]
+    # print(waveLengthVector.shape)
+    spectrumArray2D[0,1:] = waveLengthVector
+    # print(spectrumArray2D)
+
     for i in range(sequenceLength):
       # Get a spectrum as an array
       spectrumArray = np.squeeze(slicer.util.arrayFromVolume(sequenceNode.GetNthDataNode(i)))
       spectrumArray2D[i+1,1:] = spectrumArray[1,:]
     # Save the array to a csv
-    # np.savetxt(savePath + '.csv', spectrumArray2D[1:,:], delimiter=",")
-    numFiles = len([name for name in os.listdir(savePath) if os.path.isfile(os.path.join(savePath, name))]).zfill(3)
-    '''File naming convention: DataLabel_#ofFiles_TimeStamp.csv with TimeStamp in the format of YYYY-MM-DD_HH-MM-SS'''
-    # timeStamp = time.strftime("%Y-%m-%d_%H-%M-%S")
-    # fileName = dataLabel + '_' + str(numFiles) + '_' + timeStamp + '.csv'
-    fileName = dataLabel + '_' + str(numFiles) + '.csv'
-    np.savetxt(os.path.join(savePath, fileName), spectrumArray2D[1:,:], delimiter=",")
+    # If the save path does not exist, create it
+    if not os.path.exists(savePath):
+      os.makedirs(savePath)
+
+    '''File naming convention: TimeStamp_Patient#_#ofFiles_DataLabel.csv with TimeStamp in the format of MMMDD'''
+    # timestamp
+    timeStamp = time.strftime("%b%d")
+    FileNum = len([name for name in os.listdir(savePath) if os.path.isfile(os.path.join(savePath, name))]) + 1 # Get the file number
+    patientNum = parameterNode.GetParameter(self.PATIENT_NUM) 
+    fileName = timeStamp + "_" + patientNum + "_" + str(FileNum).zfill(3) + "_" + dataLabel + ".csv"
+
+    # fileName = dataLabel + '_' + str(numFiles).zfill(3) + '.csv'
+    np.savetxt(os.path.join(savePath, fileName), spectrumArray2D[:,:], delimiter=",")
     # print sample saved as well as name
     print("Sample saved as: " + fileName)
 
 #
 # Processing functions
 #
 
+
   def onSpectrumImageNodeModified(self, observer, eventid):
     parameterNode = self.getParameterNode()
     spectrumImageNode = parameterNode.GetNodeReference(self.INPUT_VOLUME)