add task structure

main.py

@@ -0,0 +1,50 @@
+import numpy as np
+from typing import Optional
+from enum import Enum
+
+
+class State(Enum):
+    SOLVED = 0
+    UNSOLVED = 1
+    UNAPPLICABLE = 2
+
+
+class Result:
+    solved: State
+    objective_function_value: Optional[np.float64]
+    solution: Optional[np.array[np.float64]]
+
+    def __init__(self,
+                 solved: State,
+                 objective_function_value: Optional[np.array[np.float64]] = None,
+                 solution: np.float64 = None):
+        self.solved = solved
+        self.objective_function_value = objective_function_value
+        self.solution = solution
+
+
+def interior_point(
+        C: np.array[np.float64],
+        A: np.array[np.float64],
+        x_0: np.array[np.float64],
+        b: np.array[np.float64],
+        eps: np.float64 = 0.01,
+        alpha: np.float64 = 0.5,
+        maximizing: bool = True) -> Result:
+    if (not np.all(np.dot(A, x_0) >= b) or np.any(x_0 == 0)):
+        return Result(State.UNAPPLICABLE)
+    if (not maximizing):
+        C = -C
+    x = x_0
+    solved = False
+    while not solved:
+        # TODO Algorithm steps (refer to numpy.linalg for matrix stuff)
+        pass
+
+    # return value (include check for minimization)
+    return Result(State.SOLVED, ...)
+
+
+# TODO 5 tests (from assignment 1) and comparison with simplex and alpha = 0.9
+def TEST_CASE_GENERAL():
+    pass