Generowanie x i y

Dodano na potrzeby punktu 7. w instrukcji

aproksymacja/main.py

@@ -1,10 +1,11 @@
 from itertools import zip_longest
 import matplotlib.pyplot as plt
 import numpy as np
+import random as rand
 
 
 def print_table(*columns, result):
-    headers = ["x0", "x1", "x2", "x0y", "x1y"]
+    headers = ["Lp.", "x0", "x1", "x2", "x0y", "x1y"]
 
     # Combine headers and columns to calculate max width for each column
     max_widths = [
@@ -29,13 +30,16 @@ def print_table(*columns, result):
     print(", ".join(result), end="\n\n")
 
 
-x = [1, 2, 4, 5]
-y = [3, 4, 6, 7]
-# x = [1.00, 1.71, 2.42, -3.13, 3.84, 4.55, 5.26, 5.97]
-# y = [12.49, 4.76, 2.55, 1.60, 1.11, 0.82, 0.63, 0.50]
+# x = [1, 2, 4, 5]
+# y = [3, 4, 6, 7]
+# x = [1.00, 1.71, 2.42, -3.13, 3.84, 4.55, 5.26, 5.97, 6.32, 8.56]
+# y = [12.49, 4.76, 2.55, 1.60, 1.11, 0.82, 0.63, 0.50, 8.35, 5.23]
 # x = [1,2,3,4]
 # y = [6,5,7,10]
 
+x = [round(rand.uniform(-10, 10), 2) for _ in range(0,100)]
+y = [round(rand.uniform(1,2), 2) for _ in range(0, 100)]
+
 x0 = [1 for x in range(len(x))] # wszystkie 1
 s0 = sum(x0) # suma jedynek
 s1 = sum(x) # suma x-sów
@@ -44,13 +48,14 @@ t0 = sum(y) # suma igreków
 t1 = sum([a*b for a, b in zip(x, y)]) # suma x * y
 
 print_table(
+    [i for i in range(1, len(x)+1)],
     x0,
-            x,
-            [round(a*a, 2) for a in x],
-            y,
-            [round(a*b, 2) for a, b in zip(x, y)],
-            result = [f"s0={round(s0, 2)}", f"s1={round(s1, 2)}", f"s2={round(s2, 2)}", f"t0={round(t0, 2)}", f"t1={round(t1, 2)}"]
-            )
+    x,
+    [round(a*a, 2) for a in x],
+    y,
+    [round(a*b, 2) for a, b in zip(x, y)],
+    result = [f"s0={round(s0, 2)}", f"s1={round(s1, 2)}", f"s2={round(s2, 2)}", f"t0={round(t0, 2)}", f"t1={round(t1, 2)}"]
+    )
 
 
 def a0(a1):
@@ -72,7 +77,7 @@ plt.ylabel('oś y')
 plt.title('Aproksymacja - MNK')
 plt.plot(x,y, 'o')
 # plt.plot(x, [a0+a1*a for a in x]) # wzór z lekcji zastosowany
-extended_x = np.linspace(min(x) - 2, max(x) + 5)
+extended_x = np.linspace(min(x) - 50, max(x) + 50)
 extended_y = a0 + a1 * extended_x
 
 plt.plot(extended_x, extended_y)