Refactor

Author: cfgnunes

differentiation.py

@@ -34,7 +34,7 @@ def dy_difference(h, y0, y1):
             hx = x[i + 1] - x[i]
             dy[i] = dy_difference(hx, y[i], y[i + 1])
 
-    return [dy]
+    return dy
 
 
 def three_point(x, y):
@@ -72,7 +72,7 @@ def dy_end(h, y0, y1, y2):
         else:
             dy[i] = dy_mid(hx, y[i - 1], y[i + 1])
 
-    return [dy]
+    return dy
 
 
 def five_point(x, y):
@@ -111,4 +111,4 @@ def dy_end(h, y0, y1, y2, y3, y4):
         else:
             dy[i] = dy_mid(hx, y[i - 2], y[i - 1], y[i + 1], y[i + 2])
 
-    return [dy]
+    return dy

integration.py

@@ -28,7 +28,7 @@ def simpson(f, a, b, n):
             sum_odd += f(x)
 
     xi = h / 3 * (f(a) + 2 * sum_even + 4 * sum_odd + f(b))
-    return [xi]
+    return xi
 
 
 def trapezoidal(f, a, b, n):
@@ -52,7 +52,7 @@ def trapezoidal(f, a, b, n):
         sum_x += f(x)
 
     xi = h / 2 * (f(a) + 2 * sum_x + f(b))
-    return [xi]
+    return xi
 
 
 def simpson_array(x, y):
@@ -81,7 +81,7 @@ def simpson_array(x, y):
             sum_odd += y[i]
 
     xi = h / 3 * (y[0] + 2 * sum_even + 4 * sum_odd + y[n - 1])
-    return [xi]
+    return xi
 
 
 def trapezoidal_array(x, y):
@@ -106,7 +106,7 @@ def trapezoidal_array(x, y):
         sum_x += y[i]
 
     xi = h / 2 * (y[0] + 2 * sum_x + y[n - 1])
-    return [xi]
+    return xi
 
 
 def romberg(f, a, b, n):
@@ -143,4 +143,4 @@ def romberg(f, a, b, n):
             r[i, k] = r[i, k - 1] + \
                 (r[i, k - 1] - r[i - 1, k - 1]) / ((4**k) - 1)
 
-    return [float(r[n - 1, n - 1])]
+    return float(r[n - 1, n - 1])

interpolation.py

@@ -24,7 +24,7 @@ def lagrange(x, y, x_int):
                 p = p * (x_int - x[j]) / (x[i] - x[j])
         y_int = y_int + p
 
-    return [y_int]
+    return y_int
 
 
 def newton(x, y, x_int):
@@ -51,7 +51,7 @@ def newton(x, y, x_int):
     for i in range(m - 2, -1, -1):
         y_int = y_int * (x_int - x[i]) + del_y[i]
 
-    return [y_int]
+    return y_int
 
 
 def gregory_newton(x, y, x_int):
@@ -79,7 +79,7 @@ def gregory_newton(x, y, x_int):
     for i in range(m - 2, -1, -1):
         y_int = y_int * (u - i) / (i + 1) + del_y[i]
 
-    return [y_int]
+    return y_int
 
 
 def neville(x, y, x_int):
@@ -106,4 +106,4 @@ def neville(x, y, x_int):
                        (x_int - x[i]) * q[i - 1, j - 1]) / (x[i] - x[i - j])
 
     y_int = q[n - 1, n - 1]
-    return [y_int, q]
+    return y_int, q

linear_systems.py

@@ -30,7 +30,7 @@ def backward_substitution(upper, d):
         x[i] = b[i] / upper[i, i]
         b[0:i] = b[0:i] - upper[0:i, i] * x[i]
 
-    return [x]
+    return x
 
 
 def forward_substitution(lower, c):
@@ -58,7 +58,7 @@ def forward_substitution(lower, c):
         x[i] = b[i] / lower[i, i]
         b[i + 1:n] = b[i + 1:n] - lower[i + 1:n, i] * x[i]
 
-    return [x]
+    return x
 
 
 def gauss_elimination_pp(a, b):
@@ -110,4 +110,4 @@ def gauss_elimination_pp(a, b):
     if a[n - 1, n - 1] == 0:
         print("Info: No unique solution.")
 
-    return [a]
+    return a

linear_systems_iterative.py

@@ -30,7 +30,7 @@ def jacobi(a, b, x0, toler, iter_max):
             break
         x0 = x.copy()
 
-    return [x, i]
+    return x, i
 
 
 def gauss_seidel(a, b, x0, toler, iter_max):
@@ -60,4 +60,4 @@ def gauss_seidel(a, b, x0, toler, iter_max):
             break
         x0 = x.copy()
 
-    return [x, i]
+    return x, i