Merge branch 'main' of https://github.com/spyrchat/Hyperdimensional-C…

…omputing-Encoder-Circuit

playground_testing.py

@@ -0,0 +1,47 @@
+import matplotlib.pyplot as plt
+import numpy as np
+
+def lookup_generate(dim, n_keys, mode = 1):
+    table = np.empty((0, dim)) 
+    prob_array = [0] * n_keys
+    if mode == 0:
+        for i in range(n_keys):    
+            row =  np.random.choice([-1, 1], size=(dim), p=[0.5, 0.5])
+            table = np.vstack((table, row))
+    else:
+        for i in range(n_keys):
+            probability = i / (n_keys-1)
+            row =  np.random.choice([-1, 1], size=(dim), p=[1-probability, probability])
+            table = np.vstack((table, row))
+            prob_array[i] = probability
+
+    return table.astype(np.int8),prob_array
+
+
+def test_matrix_probability(LUT,in_p):
+    rows = len(LUT)
+    print(rows)
+    cols = len(LUT[0])
+    cntr_plus1 = [0] * rows
+    cntr_minus1 = [0] * rows
+    p_plus1 = [0] * rows
+    for i in range(rows):
+        for j in range(cols):
+            if LUT[i,j]==1:
+                cntr_plus1[i]+=1
+            elif LUT[i,j]==-1:
+                cntr_minus1[i]+=1
+            else:
+                print("matrix element is not +1 or -1")
+        p_plus1[i] = cntr_plus1[i]/cols
+    plt.plot(in_p, p_plus1)
+    plt.ylabel("output probability")
+    plt.xlabel("input probability")
+    plt.show()
+
+
+LUT,p_in = lookup_generate(1024,256,1)
+test_matrix_probability(LUT,p_in)
+
+
+