cleaned

.gitignore

@@ -4,4 +4,4 @@ __pyscache__
 .DS_Store
 algorithm/__pyscache__
 components/__pyscache__
-visualization/__pyscache__
+viz/__pyscache__

components/encoders.py

@@ -20,9 +20,9 @@ def current_time(self):
         return 'TODO'
 
 class WordEncoder():
-    def __init__(self):
+    def __init__(self,size):
         self.words = self.word2vec()
-
+        self.size = size
     def word2vec(self):
         #read word2vec file and save it as a dictionary
         with open("assets/words.txt") as f:
@@ -40,7 +40,7 @@ def encode(self,word):
 
     @classmethod
     def transform(word):
-        #takes a word vector and turns into a SDR
+        #takes a word vector and turns into a SDR of (size,size)
         #TODO
         """
         array([ 0.120765,  0.066397,  0.173003, -0.457878,  0.268186, -0.023906,

components/sdr.py

@@ -34,7 +34,7 @@ def viz(sdr):
     """
     Turn SDR into grid-like representation. We accept 2d numpy array
     """
-    colormap = colors.ListedColormap(["white","red"])
+    colormap = colors.ListedColormap(["black","red"])
     pyplot.figure(figsize=(5,5))
     pyplot.imshow(sdr,cmap=colormap)
     pyplot.show()

tester.py

@@ -1,8 +1,10 @@
 """
 Use this document to test and experiment with the diferent components of the spatial pooler.py
 """
+
 from components.sdr import viz,generate_sdr,overlap,overlap_score
 from components.pooler import Connection,Neuron,Column,SpatialPool
+from components.encoders import TimeEncoder, WordEncoder 
 
 potential_connections = .85 # % of potential connections 
 active_columns = 40 # number of 
@@ -14,4 +16,6 @@
 sparsity = .02 
 size = 64
 
-sdr = viz(generate_sdr(size,sparsity))
+sdr = viz(generate_sdr(size,sparsity))
+
+