Added NAB detector layout; baking parameters as option

HotgymExample/hotgym.py

@@ -314,7 +314,7 @@ def main(parameters=default_parameters, argv=None, verbose=True):
     return -accuracy[5]
 
 
-#with this method, the structure for visualisation is defined
+#with this method, the structure for visualization is defined
 def BuildPandaSystem(sp,tm,consumptionBits_size,dateBits_size):
 
     #we have two inputs connected to proximal synapses of Layer1

PandaVis/bakeReader/bakeReader.py

@@ -66,6 +66,8 @@ def BuildStructure(self):
 
         # figure out how many iterations there are
         self.cntIterations = self.LoadMaxIteration("inputs_"+next(iter(self.inputs)))# get first input
+        if self.cntIterations is None:
+            raise RuntimeError("Database contains no data!")
         Log("Database contains data for "+str(self.cntIterations)+" iterations.")
 
     def LoadDataStreams(self):

dashVis/layouts/NAB htmcore detector.txt

@@ -0,0 +1,43 @@
+{"plotsPerRow" : 3,
+"streams": [{"name" : "rawAnomaly",
+			 "type" : "line",
+			 "yaxis": "anomaly"},
+		   {"name" : "value",
+			 "type" : "line",
+			 "yaxis": "kWh"},
+		   {"name" : "numberOfWinnerCells",
+			 "type" : "line",
+			 "yaxis": "cells"},
+
+		   {"name" : "numberOfPredictiveCells",
+			 "type" : "line",
+			 "yaxis": "cells"}, 
+		   {"name" : "valueInput_sparsity",
+			 "type" : "line",
+			 "yaxis": "%"},
+		   {"name" : "dateInput_sparsity",
+			 "type" : "line",
+			 "yaxis": "%"},
+
+		   {"name" : "Layer1_SP_overlap_metric",
+			 "type" : "line",
+			 "yaxis": "avg cells"},
+		   {"name" : "Layer1_TM_overlap_metric",
+			 "type" : "line",
+			 "yaxis": "avg cells"},			 
+		   {"name" : "Layer1_SP_activation_frequency",
+			 "type" : "line",
+			 "yaxis": "Hz"},
+		   {"name" : "Layer1_TM_activation_frequency",
+			 "type" : "line",
+			 "yaxis": "Hz"},
+
+		   {"name" : "Layer1_SP_entropy",
+			 "type" : "line",
+			 "yaxis": "entropy"},
+		   {"name" : "Layer1_TM_entropy",
+			 "type" : "line",
+			 "yaxis": "entropy"}
+		   ]
+}
+

pandaBaker/pandaBaker.py

@@ -14,7 +14,7 @@
 CPU_CORES = 4
 
 class PandaBaker(object):
-    def __init__(self, databaseFilePath):
+    def __init__(self, databaseFilePath, bakeProximalSynapses = True, bakeDistalSynapses = True):
         self.databaseFilePath = databaseFilePath
         self.db = None
 
@@ -23,8 +23,8 @@ def __init__(self, databaseFilePath):
         self.dataStreams = {}  # can contain cDataStream instances
 
         #flags what to bake
-        self.bakeProximalSynapses = True
-        self.bakeDistalSynapses = True
+        self.bakeProximalSynapses = bakeProximalSynapses
+        self.bakeDistalSynapses = bakeDistalSynapses
 
         # for raw anomaly calculation
         self.previousPredictiveCells = {} # dict storing predictive cells for previous timestamp for each layer
@@ -136,6 +136,6 @@ def Log(s):
     print(str(s))
     from datetime import datetime
     dateStr=datetime.now().strftime('%Y-%m-%d %H:%M:%S')
-    with open("logs/pandaBaker.log","a") as file:
+    with open(os.path.join(os.getcwd(), "logs","pandaBaker.log"),"a") as file:
         file.write(dateStr+" >> "+str(s)+"\n")