Emil_Shanaty/Internal_Point
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This commit is contained in:
Ilya Grigorev
2024-11-02 20:47:34 +05:00
parent 1b783e663a
commit 84eb70638e
1 changed files with 10 additions and 9 deletions
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main.py
+10 -9
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@@ -152,12 +152,13 @@ def print_result(result: Result):
def interior_point( def interior_point(
C: np.array, # Vector of objective function coefficients C: np.array, # Vector of objective function coefficients
A: np.array, # Matrix of constraint coefficients A: np.array, # Matrix of constraint coefficients
x_0: np.array, # Initial point (vector)
b: np.array, # Vector of right-hand side values of constraints b: np.array, # Vector of right-hand side values of constraints
x_0: np.array, # Initial point (vector)
eps: np.float64 = 0.01, # Solution accuracy eps: np.float64 = 0.01, # Solution accuracy
alpha: np.float64 = 0.5, # Step coefficient alpha: np.float64 = 0.5, # Step coefficient
maximizing: bool = True) -> Result: # Flag for maximization or minimization maximizing: bool = True) -> Result: # Flag for maximization or minimization
# Check if the method is applicable: the initial point must satisfy the constraints # Check if the method is applicable: the initial point must satisfy the constraints
print(A)
if (not np.all(np.dot(A, x_0) <= b) or np.any(x_0 == 0)): if (not np.all(np.dot(A, x_0) <= b) or np.any(x_0 == 0)):
print(np.dot(A, x_0), b) print(np.dot(A, x_0), b)
return Result(State.INAPPLICABLE, maximize=maximizing) return Result(State.INAPPLICABLE, maximize=maximizing)
@@ -251,14 +252,14 @@ def TEST_MINIMIZE_CASE():
print("----------------------------RUNNING_TEST_MINIMIZE_CASE----------------------------") print("----------------------------RUNNING_TEST_MINIMIZE_CASE----------------------------")
C = np.array([-2, 2, -6]) C = np.array([-2, 2, -6])
A = np.array([ A = np.array([
[2, 1, -2] [2, 1, -2],
[1, 2, 4] [1, 2, 4],
[1, -1, 2]]) [1, -1, 2]])
b = np.array([24, 23, 10]) b = np.array([24, 23, 10])
x_0 = np.array([1, 1]) x_0 = np.array([1, 1, 1])
eps = 0.01 eps = 0.01
alpha = 0.5 alpha = 0.5
maximize = True maximize = False
print_initial_inputs(C, A, b, x_0, eps, alpha, maximize) print_initial_inputs(C, A, b, x_0, eps, alpha, maximize)
result = interior_point(C, A, b, x_0, eps, alpha, maximize) result = interior_point(C, A, b, x_0, eps, alpha, maximize)
@@ -288,7 +289,7 @@ def TEST_WITH_SLACK_CASE():
[-2, -1, 0, -2], [-2, -1, 0, -2],
[3, 2, 0, 1]]) [3, 2, 0, 1]])
b = np.array([10, 18, 36]) b = np.array([10, 18, 36])
x_0 = np.array([1, 1]) x_0 = np.array([1, 1, 1, 1])
eps = 0.01 eps = 0.01
alpha = 0.5 alpha = 0.5
maximize = True maximize = True
@@ -353,7 +354,7 @@ def TEST_UNSOLVABLE_CASE():
[-1, 0, 0, 10, 0], [-1, 0, 0, 10, 0],
[0, 1, 1, -5, 1]]) [0, 1, 1, -5, 1]])
b = np.array([-24, 6, 1, 2]) b = np.array([-24, 6, 1, 2])
x_0 = np.array([1, 1]) x_0 = np.array([-2, -3, -1, -1, 1])
eps = 0.01 eps = 0.01
alpha = 0.5 alpha = 0.5
maximize = True maximize = True
@@ -391,5 +392,5 @@ for test in tests:
print("----------------------------RESULTS----------------------------") print("----------------------------RESULTS----------------------------")
print("Total number of tests: " << tests.size()) print("Total number of tests: ", tests.size())
print("Total number of passed tests: " << tests_passed) print("Total number of passed tests: ", tests_passed)