diff --git a/h2/MBC_carlsen.py b/h2/MBC_carlsen.py
new file mode 100644
index 0000000..402b27e
--- /dev/null
+++ b/h2/MBC_carlsen.py
@@ -0,0 +1,193 @@
+
+import matplotlib.pyplot as plt
+import collections
+from enum import Enum, auto
+from random import randint
+
+Point = collections.namedtuple("Point", "x y")
+
+class Side(Enum):
+    ON = auto()
+    ABOVE = auto()
+    BELOW = auto()
+
+
+def sidedness(slope, intersection, p3, eps=0.0000001):
+    print(slope * p3[0] + intersection )
+    """ finds where a point is in regards to a line """
+    if p3[1] - eps <= slope * p3[0] + intersection <= p3[1] + eps or p3[0] - eps <= (p3[1] - intersection)/slope <= p3[0] + eps:
+        return Side.ON
+    elif p3[1] > slope * p3[0] + intersection:
+        return Side.ABOVE
+    return Side.BELOW
+
+def diplay_prune_points(points, p1, p2):
+    xs = [p[0] for p in points]
+    ys = [p[1] for p in points]
+
+    plt.plot(xs, ys, 'ro')
+    plt.plot([p1[0], p2[0]], [p1[1], p2[1]])
+    plt.show()
+
+
+def solve1D(points, xm, iteration_num):
+    #print("iter:", iteration_num)
+    point = points[iteration_num]
+
+    if iteration_num == 0:
+        return -float('Inf'), -float('Inf')
+
+    # lad point[1] = point[0] * a + b <=> y = x * a + b
+    # isolere b og sæt ind i constraints
+    a = None
+    b = point[1] - point[0] # * a
+
+    # minimere xm*a + b, hvor b har ny værdi
+    # Vi regner kun med koefficienterne
+    # obj_fun = (xm - point[0]) + points[1] = (xm*a - xi*a) + y
+
+    # max eller min
+    #print("XM og point[0]:", xm, point[0])
+    a = xm - point[0]
+    #print("a lige her:", a)
+
+    a_constraint_list = []
+    # looping over the i constraints
+    for p in points[:iteration_num]:
+        # we can't make a straigt vertical line
+        if p[0] == point[0]:
+            if p[1] > point[1]:
+                p[0] = p[0] + 0.0001
+            else:
+                point[0] = point[0] + 0.0001
+
+        print(p, point)
+        # Spring over den i'te constraint
+        if p != point:
+            # y_j - yi
+            c = p[1] - point[1]
+            # x_j * a - xi * a
+            a_diff = p[0] - point[0]
+
+            print(c, a_diff, c/a_diff)
+            # det her er forkert og skal fikses
+            if a >= 0 and a_diff < 0:
+                a_constraint_list.append(-float('Inf'))
+            else:
+                a_constraint_list.append(c/a_diff)
+
+    # hvis a > 0 så min
+    # hvis a < 0 så max.
+    if a >= 0:
+        v1 = max(a_constraint_list)
+        v2 = point[1] - point[0] * v1
+        v = (v1, v2)
+    elif a < 0:
+        v1 = min(a_constraint_list)
+        v2 = point[1] - point[0] * v1
+        v = (v1, v2)
+
+    return v
+
+
+
+def findBridge(points, xm):
+    if xm > 0:
+        v = (-float('Inf'), -float('Inf'))
+    elif xm < 0:
+        4 # noget
+    else:
+        # TODO: xm == 0
+        4
+    # looping over constraints
+    for point in points:
+        # checking for violation
+        if not point[1] <= point[0] * v[0] + v[1]:
+            v = solve1D(points, xm, points.index(point))
+            #print("HER OVER: ", v)
+
+    slope = v[0]
+    intercept = v[1]
+
+    line_points = [p for p in points if sidedness(slope, intercept, p) == Side.ON]
+
+    if len(line_points) > 3:
+        print("Halli HAllo")
+        print(line_points)
+
+    return line_points[0], line_points[1]
+
+
+def find_median(points):
+    if len(points) % 2 == 0:
+        first_med_idx = int(len(points) / 2 - 1)
+        second_med_idx = int(len(points) / 2)
+        return (points[first_med_idx][0] + points[second_med_idx][0]) / 2
+    else:
+        idx = int((len(points)-1) / 2)
+        return points[idx][0]
+
+
+def upperHull(points, all_points):
+    print("Punkter:", points)
+    if len(points) < 2:
+        return []
+    xm = find_median(points)
+
+    # end-points of bridge
+    (xi, yi), (xj, yj) = findBridge(points, xm)
+
+    #print(xm)
+    print((xi, yi), (xj, yj))
+    prune_points = [p for p in points if p[0] < xi or xj < p[0]] + [(xi, yi), (xj, yj)]
+
+    # Neden for er mest for visualisering
+    prune_all_points = [p for p in all_points if p[0] < xi or xj < p[0]] + [(xi, yi), (xj, yj)]
+    diplay_prune_points(prune_all_points, (xi, yi), (xj, yj))
+
+    Pl = [p for p in prune_points if p[0] < xm]
+    Pr = [p for p in prune_points if p[0] >= xm]
+    #print("Pl:", Pl, "Pr", Pr)
+
+    print("\n")
+    # recurse results and return
+    ret = [(xi, yi), (xj, yj)]
+    ret = ret + [p for p in upperHull(Pl, prune_all_points) if p not in ret]
+    ret = ret + [p for p in upperHull(Pr, prune_all_points) if p not in ret]
+    return ret
+
+
+
+p1 = (2, 1)
+p2 = (3, 4)
+p3 = (5, 2)
+p4 = (6, 5)
+
+list_of_points = []
+
+list_of_points.append(p1)
+list_of_points.append(p2)
+list_of_points.append(p3)
+list_of_points.append(p4)
+
+
+
+
+xs = [p[0] for p in list_of_points]
+ys = [p[1] for p in list_of_points]
+
+plt.plot(xs, ys, 'ro')
+plt.show()
+
+result = list(sorted(upperHull(list_of_points, list_of_points)))
+
+result
+res_xs = [p[0] for p in result]
+res_ys = [p[1] for p in result]
+
+
+#print("result", result)
+plt.plot(res_xs, res_ys)
+plt.plot(xs, ys, 'ro')
+plt.show()
+