created weight matrices

model.py

@@ -2,27 +2,60 @@
 import sys
 import os
 import csv
+from random import random
+from pprint import pprint as pp
 
-params = {"layers":[57, 57*2, 1], "test":"TestX.csv", "train":"Train.csv"}
+params = {"layers":[57, int(57/2), 1], "test":"TestX.csv", "train":"Train.csv"}
 
-def getData(srcF, isTrain=True):
+def getData(srcF, isTrain=True, addBias=True):
     X,y=[],[]
     with open(srcF) as src:
         reader = csv.reader(src, delimiter=',')
         for i,row in enumerate(reader):
+            temp = []
+            if addBias:
+                temp.append(1)
             end = -1 if isTrain else len(row)
-            X.append(row[:end])
+            temp.extend(row[:end])
             
             #correct data type
-            X[i] = [x for x in map(float, X[i][:-2])]
-            X[i].extend([int(X[i][-2]),int(X[i][-1])])
+            X.append([x for x in map(float, temp)])
 
             if isTrain:
                 y.append(int(row[-1]))
 
     return (X,y)
 
+def getMatrix(r, c, vec):
+    mat = []
+    for i in range(r):
+        temp = []
+        for j in range(c):
+            idx = i*(c)+j
+            temp.append(vec[j])
+        mat.append(temp)
+
+    return mat
+
+
+
+def cost(li, lh, lo, weights, X, y):
+    w1t = weights[:(li+1)*lh]    #28x58
+    w2t = weights[(li+1)*lh:]    #1x29
+
+    w1,w2 = getMatrix(lh, li+1, w1t), getMatrix(lo, lh+1, w2t)   
+
+    
+
+
+
+
+
 if __name__ == "__main__":
     X,y = getData(params["train"])
-    tX,ty = getData(params["test"], isTrain=False)
-
+    # tX,ty = getData(params["test"], isTrain=False)
+    print(len(X), len(X[0]), len(y), X[0])
+    li,lh,lo = tuple(params["layers"])
+    weights = [random() for _ in range(lh*(li+1)+lo*(lh+1))]
+    w1,w2 = cost(li, lh, lo, weights, X, y)
+    #print(len(w1), len(w1[0]), len(w2), len(w2[0]))
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