       
   processLightcurve: (removeOutliers=false) ->
 
+    console.log 'sliderValue: ', @sliderValue
+    classifier.el.find("#ui-slider").val(0) # reset slider value
+    @zoomOut()
+
+    # restore original values
+    @data.x = @data_raw.x
+    @data.y = @data_raw.y
+
     # this step is necessary or (top) x-axis breaks
     @smallestX = Math.min @data_raw.x...
     @originalMin = @smallestX
-    for xValue, idx in [@data_raw.x...]
-      @data.x[idx] = xValue - @smallestX
+    for x, i in [@data.x...]
+      @data.x[i] = x - @smallestX
 
     if removeOutliers
       @data = @removeOutliers(@data_raw, nsigma=3) # NOTE: nsigma < 8 removes tutorial subject transits
-    else
-      @data.y = @data_raw.y # restore to original values
-
+    
     @data.y = @normalize(@data.y)
 
     # update min/max values

    @sliderValue = +classifier.el.find("#ui-slider").val()
    xClick = e.pageX - e.target.getBoundingClientRect().left - window.scrollX
    yClick = e.pageY - e.target.getBoundingClientRect().top - window.scrollY
    
    @plotPoints(@sliderValue, @sliderValue+@zoomRanges[@zoomLevel])

    if xClick < @leftPadding

    return y_new

  removeOutliers: (data, nsigma) -> 
    data_new = {}
    data_new.x = []
    data_new.y = []
