final presentation, restructure of the repository, updated code to have weighted probabilities and more

code/Dockerfile

@@ -2,10 +2,10 @@ FROM python:3.14-slim
 
 WORKDIR /app
 
-COPY ./main.py /app
+COPY requirements.txt /app/
-COPY ./simulator.py /app
-COPY ./requirements.txt /app
 
-RUN pip install -r requirements.txt
+RUN pip install --no-cache-dir -r requirements.txt
+
+COPY main.py simulator.py /app/
 
 CMD ["python", "main.py"]

code/main.py

@@ -30,18 +30,6 @@ def Continue(title="") -> None:
     print()
 
 
-# def MainMenu() -> None:
-#     global currentFunction
-#     options = ["Simulator", "Calculator", "Quit"]
-#     actions: list[Callable[[], None]] = [SimulatorMenu, StopApplication]
-
-#     selectedIndex = ShowMenu(
-#         options, title="Boolean Network Simulator\nby Tom Zuidberg"
-#     )
-
-#     currentFunction = actions[selectedIndex]
-
-
 def StopApplication() -> None:
     quit()
 
@@ -151,11 +139,14 @@ def BooleanNetworkMenu(
     functionStrings: list = [None for _ in range(3)]
     functionsDirtyFlag = False
     current_highlight = 0
+    functions_highlight = 0
+    probFunctionStrings: list[list[str]] = [[] for _ in range(3)]
 
     if bn is not None and funcStrings is not None and funcs is not None:
         boolNetwork = bn
         functions = funcs
         functionStrings = funcStrings
+        probFunctionStrings = [[] for _ in range(boolNetwork.size)]
 
     def Menu() -> None:
         nonlocal current_highlight
@@ -164,10 +155,7 @@ def BooleanNetworkMenu(
             f"Set size (current: {boolNetwork.size})  WARNING: this will reset all other options!",
             f"Set state (current: {str(boolNetwork)[-boolNetwork.size :]})",
             f"Set update scheme (current: {boolNetwork.updateScheme})",
-            *[
+            "Edit update functions",
-                f"Set update function of node x{i} (current: {functionStrings[i - 1]})"
-                for i in range(1, boolNetwork.size + 1)
-            ],
             None,
             "Update once (hold ENTER for continuous updates)",
             "Update multiple times",
@@ -182,7 +170,7 @@ def BooleanNetworkMenu(
             SetSizeHelper,
             SetStateHelper,
             SetUpdateSchemeHelper,
-            *[partial(SetFunctionHelper, i) for i in range(boolNetwork.size)],
+            FunctionsMenu,
             None,
             UpdateHelper,
             MultiUpdateHelper,
@@ -204,7 +192,7 @@ def BooleanNetworkMenu(
         actions[selectedIndex]()
 
     def SetSizeHelper() -> None:
-        nonlocal boolNetwork, functions, functionStrings
+        nonlocal boolNetwork, functions, functionStrings, probFunctionStrings
         while True:
             size = input("Set new size (Leave empty to cancel):\n").strip()
             if size == "":
@@ -219,6 +207,7 @@ def BooleanNetworkMenu(
             boolNetwork = BooleanNetwork(size)
             functions = [None for _ in range(size)]
             functionStrings = [None for _ in range(size)]
+            probFunctionStrings = [[] for _ in range(size)]
             return
 
     def SetStateHelper() -> None:
@@ -237,9 +226,32 @@ def BooleanNetworkMenu(
                 print("Invalid input:", e)
 
     def SetUpdateSchemeHelper() -> None:
-        nonlocal boolNetwork
+        nonlocal boolNetwork, functions, functionStrings, functionsDirtyFlag
+
+        def AdoptFromProbabilistic() -> None:
+            nonlocal functionsDirtyFlag
+
+            for i in range(boolNetwork.size):
+                if probFunctionStrings[i]:
+                    funcString = probFunctionStrings[i][0]
+                    func = eval(
+                        "lambda "
+                        + ",".join(f"x{j}" for j in range(1, boolNetwork.size + 1))
+                        + ":"
+                        + funcString
+                    )
+                    functions[i] = func
+                    functionStrings[i] = funcString
+            functionsDirtyFlag = True
+
+        def SwitchToSynchronous() -> None:
+            wasProbabilistic = boolNetwork.updateScheme == "probabilistic"
+            boolNetwork.UseSynchronousScheme()
+            if wasProbabilistic:
+                AdoptFromProbabilistic()
 
         def SetSequentialHelper() -> None:
+            wasProbabilistic = boolNetwork.updateScheme == "probabilistic"
             while True:
                 seq = input(
                     "Set sequence. (Leave empty to cancel)\nFormat example: '1,4,3,2'\n"
@@ -252,26 +264,24 @@ def BooleanNetworkMenu(
                 try:
                     seq = [int(i) for i in seq]
                     boolNetwork.UseSequentialScheme(seq)
+                    if wasProbabilistic:
+                        AdoptFromProbabilistic()
                     return
                 except Exception as e:
                     print("Invalid input:", e)
 
-        def SetProbabilisticHelper() -> None:
+        def SwitchToAsyncRandom() -> None:
-            while True:
+            wasProbabilistic = boolNetwork.updateScheme == "probabilistic"
-                chance = input(
+            boolNetwork.UseAsynchronousRandomScheme()
-                    "Set flip chance as float between 0.0 and 1.0. (Leave empty to cancel)\n"
+            if wasProbabilistic:
-                ).strip()
+                AdoptFromProbabilistic()
-                if chance == "":
-                    print("Cancelled")
-                    return
 
-                try:
+        def SwitchToProbabilistic() -> None:
-                    chance = float(chance)
+            for i in range(boolNetwork.size):
-                    boolNetwork.UseProbabilisticScheme(chance)
+                if not probFunctionStrings[i] and functions[i] is not None:
-                    return
+                    boolNetwork.AddProbabilisticFunction(i, functions[i], 1.0)
-
+                    probFunctionStrings[i].append(functionStrings[i])
-                except Exception as e:
+            boolNetwork.UseProbabilisticScheme()
-                    print("Invalid input:", e)
 
         title = "Select update scheme:"
         options = [
@@ -282,15 +292,120 @@ def BooleanNetworkMenu(
             "Cancel",
         ]
         actions = [
-            lambda: boolNetwork.UseSynchronousScheme(),
+            SwitchToSynchronous,
             SetSequentialHelper,
-            SetProbabilisticHelper,
+            SwitchToProbabilistic,
-            lambda: boolNetwork.UseAsynchronousRandomScheme(),
+            SwitchToAsyncRandom,
             lambda: None,
         ]
 
         actions[ShowMenu(options=options, title=title)]()
 
+    def FunctionsMenu() -> None:
+        nonlocal functions_highlight
+        done: bool = False
+
+        def Menu() -> None:
+            nonlocal functions_highlight
+            title = "Edit update functions:"
+            deleteTargets: list = []
+
+            if boolNetwork.updateScheme in ("synchronous", "sequential", None):
+                options = [
+                    *[
+                        f"Set update function of node x{i} (current: {functionStrings[i - 1]})"
+                        for i in range(1, boolNetwork.size + 1)
+                    ],
+                    None,
+                    "Return",
+                ]
+                actions = [
+                    *[partial(SetFunctionHelper, i) for i in range(boolNetwork.size)],
+                    None,
+                    ReturnHelper,
+                ]
+            elif boolNetwork.updateScheme == "asynchronous_random":
+                options = [
+                    *[
+                        f"Set update function of node x{i} (current: {functionStrings[i - 1]})"
+                        for i in range(1, boolNetwork.size + 1)
+                    ],
+                    None,
+                    *[
+                        f"Set selection weight of node x{i} (current: {boolNetwork.node_selection_weights[i - 1]})"
+                        for i in range(1, boolNetwork.size + 1)
+                    ],
+                    None,
+                    "Return",
+                ]
+                actions = [
+                    *[partial(SetFunctionHelper, i) for i in range(boolNetwork.size)],
+                    None,
+                    *[partial(SetNodeWeightHelper, i) for i in range(boolNetwork.size)],
+                    None,
+                    ReturnHelper,
+                ]
+            else:  # probabilistic
+                title = "Edit update functions:\n(highlight a function entry and press 'd' to delete it)"
+                options = []
+                actions = []
+                for i in range(boolNetwork.size):
+                    for j in range(len(probFunctionStrings[i])):
+                        options.append(
+                            f"Set update function #{j + 1} of node x{i + 1} (current: {probFunctionStrings[i][j]})"
+                        )
+                        actions.append(partial(EditProbFunctionHelper, i, j))
+                        deleteTargets.append((i, j))
+                        options.append(
+                            f"Set weight of function #{j + 1} of node x{i + 1} (current: {boolNetwork.probabilistic_weights[i][j]})"
+                        )
+                        actions.append(partial(EditProbWeightHelper, i, j))
+                        deleteTargets.append(None)
+                    options.append(f"Add new function for node x{i + 1}")
+                    actions.append(partial(AddProbFunctionHelper, i))
+                    deleteTargets.append(None)
+                    options.append(None)
+                    actions.append(None)
+                    deleteTargets.append(None)
+                options.append("Return")
+                actions.append(ReturnHelper)
+                deleteTargets.append(None)
+
+            if boolNetwork.updateScheme == "probabilistic":
+                menu = TerminalMenu(
+                    menu_entries=options,
+                    title=title,
+                    multi_select=False,
+                    cursor_index=functions_highlight,
+                    accept_keys=("enter", "d"),
+                )
+                selectedIndex = menu.show()
+                if selectedIndex is None:
+                    selectedIndex = len(options) - 1
+                    acceptKey = "enter"
+                else:
+                    acceptKey = menu.chosen_accept_key
+                functions_highlight = selectedIndex
+
+                if acceptKey == "d" and deleteTargets[selectedIndex] is not None:
+                    DeleteProbFunctionHelper(*deleteTargets[selectedIndex])
+                else:
+                    actions[selectedIndex]()
+                return
+
+            selectedIndex = ShowMenu(
+                options=options, title=title, highlight_entry=functions_highlight
+            )
+            functions_highlight = selectedIndex
+            actions[selectedIndex]()
+
+        def ReturnHelper() -> None:
+            nonlocal done
+            done = True
+
+        while not done:
+            Menu()
+
     def UpdateHelper() -> None:
         nonlocal functions, boolNetwork, functionsDirtyFlag
         if functionsDirtyFlag:
@@ -377,6 +492,115 @@ def BooleanNetworkMenu(
             except Exception as e:
                 print("Error while parsing function:", e)
 
+    def SetNodeWeightHelper(index: int) -> None:
+        nonlocal boolNetwork
+        while True:
+            weight = input(
+                f"Set new selection weight for node x{index + 1}. Must be a positive number. (Leave empty to cancel)\n"
+            ).strip()
+            if weight == "":
+                print("Cancelled")
+                return
+            try:
+                weight = float(weight)
+                boolNetwork.SetNodeSelectionWeight(index, weight)
+                return
+            except Exception as e:
+                print("Invalid input:", e)
+
+    def AddProbFunctionHelper(index: int) -> None:
+        nonlocal boolNetwork, probFunctionStrings
+        while True:
+            funcString = input(
+                f"Set new function for node x{index + 1}. The function will receive all nodes in form of x1, x2, ..., x[size]. (Leave empty to cancel)\n"
+            )
+            if funcString == "":
+                print("Cancelled")
+                return
+            try:
+                func = (
+                    "lambda "
+                    + ",".join(f"x{i}" for i in range(1, boolNetwork.size + 1))
+                    + ":"
+                    + funcString
+                )
+                func = eval(func)
+                if not isinstance(func, FunctionType):
+                    print("Please enter a valid function. Got: " + func)
+                    continue
+            except Exception as e:
+                print("Error while parsing function:", e)
+                continue
+
+            weight = 1.0
+            weightInput = input(
+                "Set weight for this function. Must be a positive number. (Leave empty for default 1.0)\n"
+            ).strip()
+            if weightInput != "":
+                try:
+                    weight = float(weightInput)
+                except ValueError:
+                    print("Invalid weight, using default 1.0")
+                    weight = 1.0
+
+            try:
+                boolNetwork.AddProbabilisticFunction(index, func, weight)
+                probFunctionStrings[index].append(funcString)
+                return
+            except Exception as e:
+                print("Error while adding function:", e)
+
+    def EditProbFunctionHelper(index: int, function_index: int) -> None:
+        nonlocal boolNetwork, probFunctionStrings
+        while True:
+            funcString = input(
+                f"Set new function for node x{index + 1}, function #{function_index + 1}. (Leave empty to cancel)\n"
+            )
+            if funcString == "":
+                print("Cancelled")
+                return
+            try:
+                func = (
+                    "lambda "
+                    + ",".join(f"x{i}" for i in range(1, boolNetwork.size + 1))
+                    + ":"
+                    + funcString
+                )
+                func = eval(func)
+                if not isinstance(func, FunctionType):
+                    print("Please enter a valid function. Got: " + func)
+                    continue
+                boolNetwork.SetProbabilisticFunction(index, function_index, func)
+                probFunctionStrings[index][function_index] = funcString
+                return
+            except Exception as e:
+                print("Error while parsing function:", e)
+
+    def EditProbWeightHelper(index: int, function_index: int) -> None:
+        nonlocal boolNetwork
+        while True:
+            weight = input(
+                f"Set new weight for node x{index + 1}, function #{function_index + 1}. Must be a positive number. (Leave empty to cancel)\n"
+            ).strip()
+            if weight == "":
+                print("Cancelled")
+                return
+            try:
+                weight = float(weight)
+                boolNetwork.SetProbabilisticFunctionWeight(index, function_index, weight)
+                return
+            except Exception as e:
+                print("Invalid input:", e)
+
+    def DeleteProbFunctionHelper(index: int, function_index: int) -> None:
+        nonlocal boolNetwork, probFunctionStrings
+        try:
+            boolNetwork.RemoveProbabilisticFunction(index, function_index)
+            del probFunctionStrings[index][function_index]
+        except Exception as e:
+            print("Error while deleting function:", e)
+            Continue()
+
     def ToggleWriteToFileHelper():
         nonlocal writeToFile
         writeToFile = not writeToFile

code/simulator.py

@@ -7,6 +7,19 @@ import numpy as np
 import scipy.linalg
 
 
+def _wrap_bool_function(
+    function: Callable[Concatenate[bool, ...], bool],
+) -> Callable[Concatenate[bool, ...], bool]:
+    def wrap(*args, **kwargs) -> bool:
+        result = function(*args, **kwargs)
+        assert type(result) is bool, (
+            f"Function error: Boolean network functions must always return a bool, however got type {type(result)}, {result=}"
+        )
+        return result
+
+    return wrap
+
+
 class BooleanNetwork:
     def __init__(self, size: int) -> None:
         assert type(size) is int and size > 0, (
@@ -17,8 +30,7 @@ class BooleanNetwork:
         self.__has_update_functions = False
         self.__has_update_scheme = False
         self.__has_sequence = False
-        self.__has_flip_chance = False
+        self.__has_probabilistic_functions = False
-        self.flip_chance: float = 0
         self.sequence: list[int] = list()
         self.seed: int | None = None
         self.time_step = 0
@@ -29,21 +41,23 @@ class BooleanNetwork:
             lambda x: x for _ in range(size)
         ]
 
+        # asynchronous_random: relative likelihood that node i is the one picked
+        # to update on a given time step. Doesn't need to sum to 1 - it is
+        # normalised (weight_i / sum(weights)) whenever it is used.
+        self.node_selection_weights: list[float] = [1.0 for _ in range(size)]
+
+        # probabilistic: each node may have any number of candidate update
+        # functions. On every update, one candidate per node is drawn
+        # according to its weight (again normalised at use-time, not
+        # required to sum to 1) and applied synchronously.
+        self.probabilistic_functions: list[
+            list[Callable[Concatenate[bool, ...], bool]]
+        ] = [list() for _ in range(size)]
+        self.probabilistic_weights: list[list[float]] = [list() for _ in range(size)]
+
     def SetFunctions(
         self, functions: Iterable[Callable[Concatenate[bool, ...], bool]]
     ) -> Self:
-        def wrapper(
-            function: Callable[Concatenate[bool, ...], bool],
-        ) -> Callable[Concatenate[bool, ...], bool]:
-            def wrap(*args, **kwargs) -> bool:
-                result = function(*args, **kwargs)
-                assert type(result) is bool, (
-                    f"Function error: Boolean network functions must always return a bool, however got type {type(result)}, {result=}"
-                )
-                return result
-
-            return wrap
-
         funcs: list[Callable[Concatenate[bool, ...], bool]] = list(functions)
 
         assert len(funcs) == self.size, (
@@ -56,7 +70,7 @@ class BooleanNetwork:
                 f"Function error: Function arg amount mismatch. Given function takes {len(inspect.signature(func).parameters)} arguments, expected {self.size}"
             )
 
-            self.functions[i] = wrapper(func)
+            self.functions[i] = _wrap_bool_function(func)
 
         self.__has_update_functions = True
         return self
@@ -64,22 +78,101 @@ class BooleanNetwork:
     def SetFunction(
         self, index: int, function: Callable[Concatenate[bool, ...], bool]
     ) -> Self:
-        def wrapper(
-            function: Callable[Concatenate[bool, ...], bool],
-        ) -> Callable[Concatenate[bool, ...], bool]:
-            def wrap(*args, **kwargs) -> bool:
-                result = function(*args, **kwargs)
-                assert type(result) is bool, (
-                    f"Function error: Boolean network functions must always return a bool, however got type {type(result)}, {result=}"
-                )
-                return result
-
-            return wrap
-
         assert 0 <= index < self.size, (
             f"Function error: cannot set function at index {index} - out of bound."
         )
-        self.functions[index] = wrapper(function)
+        assert len(inspect.signature(function).parameters) == self.size, (
+            f"Function error: Function arg amount mismatch. Given function takes {len(inspect.signature(function).parameters)} arguments, expected {self.size}"
+        )
+        self.functions[index] = _wrap_bool_function(function)
+        return self
+
+    def SetNodeSelectionWeight(self, index: int, weight: float) -> Self:
+        assert 0 <= index < self.size, (
+            f"Weight error: cannot set selection weight at index {index} - out of bound."
+        )
+        assert type(weight) is float and weight > 0, (
+            f"Weight error: weight must be a positive float. got {weight=}"
+        )
+        self.node_selection_weights[index] = weight
+        return self
+
+    def AddProbabilisticFunction(
+        self,
+        index: int,
+        function: Callable[Concatenate[bool, ...], bool],
+        weight: float = 1.0,
+    ) -> Self:
+        assert 0 <= index < self.size, (
+            f"Function error: cannot add function at index {index} - out of bound."
+        )
+        assert len(inspect.signature(function).parameters) == self.size, (
+            f"Function error: Function arg amount mismatch. Given function takes {len(inspect.signature(function).parameters)} arguments, expected {self.size}"
+        )
+        assert type(weight) is float and weight > 0, (
+            f"Weight error: weight must be a positive float. got {weight=}"
+        )
+
+        self.probabilistic_functions[index].append(_wrap_bool_function(function))
+        self.probabilistic_weights[index].append(weight)
+        self.__has_probabilistic_functions = all(
+            len(functions) > 0 for functions in self.probabilistic_functions
+        )
+        return self
+
+    def SetProbabilisticFunction(
+        self,
+        index: int,
+        function_index: int,
+        function: Callable[Concatenate[bool, ...], bool],
+    ) -> Self:
+        assert 0 <= index < self.size, (
+            f"Function error: cannot set function at index {index} - out of bound."
+        )
+        assert 0 <= function_index < len(self.probabilistic_functions[index]), (
+            f"Function error: node {index} has no function at position {function_index}."
+        )
+        assert len(inspect.signature(function).parameters) == self.size, (
+            f"Function error: Function arg amount mismatch. Given function takes {len(inspect.signature(function).parameters)} arguments, expected {self.size}"
+        )
+
+        self.probabilistic_functions[index][function_index] = _wrap_bool_function(
+            function
+        )
+        return self
+
+    def SetProbabilisticFunctionWeight(
+        self, index: int, function_index: int, weight: float
+    ) -> Self:
+        assert 0 <= index < self.size, (
+            f"Weight error: cannot set weight at index {index} - out of bound."
+        )
+        assert 0 <= function_index < len(self.probabilistic_weights[index]), (
+            f"Weight error: node {index} has no function at position {function_index}."
+        )
+        assert type(weight) is float and weight > 0, (
+            f"Weight error: weight must be a positive float. got {weight=}"
+        )
+
+        self.probabilistic_weights[index][function_index] = weight
+        return self
+
+    def RemoveProbabilisticFunction(self, index: int, function_index: int) -> Self:
+        assert 0 <= index < self.size, (
+            f"Function error: cannot remove function at index {index} - out of bound."
+        )
+        assert 0 <= function_index < len(self.probabilistic_functions[index]), (
+            f"Function error: node {index} has no function at position {function_index}."
+        )
+        assert len(self.probabilistic_functions[index]) > 1, (
+            f"Function error: node {index} must keep at least one probabilistic function."
+        )
+
+        del self.probabilistic_functions[index][function_index]
+        del self.probabilistic_weights[index][function_index]
+        self.__has_probabilistic_functions = all(
+            len(functions) > 0 for functions in self.probabilistic_functions
+        )
         return self
 
     def UseSynchronousScheme(self) -> Self:
@@ -127,16 +220,9 @@ class BooleanNetwork:
         self.__has_update_scheme = True
         return self
 
-    def UseProbabilisticScheme(self, flip_chance: float) -> Self:
+    def UseProbabilisticScheme(self) -> Self:
-        if flip_chance is not None:
-            assert type(flip_chance) is float, (
-                f"Probabilistic error: given flip_chance is not a float: got {flip_chance}"
-            )
-            self.flip_chance = flip_chance
-
         self.updateScheme = "probabilistic"
         self.__has_update_scheme = True
-        self.__has_flip_chance = True
         return self
 
     def __synchronous_update(self) -> None:
@@ -150,15 +236,21 @@ class BooleanNetwork:
             self.nodes[i] = self.functions[i](*self.nodes)
 
     def __asynchronous_random_update(self) -> None:
-        index = random.randrange(0, self.size)
+        index = random.choices(
+            range(self.size), weights=self.node_selection_weights, k=1
+        )[0]
         self.nodes[index] = self.functions[index](*self.nodes)
 
     def __probabilistic_update(self) -> None:
-        self.__synchronous_update()
+        temp = list()
         for i in range(self.size):
-            rng = random.random()
+            chosen = random.choices(
-            if rng <= self.flip_chance:
+                self.probabilistic_functions[i],
-                self.nodes[i] = not self.nodes[i]
+                weights=self.probabilistic_weights[i],
+                k=1,
+            )[0]
+            temp.append(chosen(*self.nodes))
+        self.nodes = temp
 
     def SetState(self, state: str | list[bool] | tuple[bool, ...]) -> Self:
         assert isinstance(state, (str, list, tuple)), (
@@ -192,7 +284,9 @@ class BooleanNetwork:
         assert type(n) is int and n >= 0, (
             f"Update error: amount of updates must be an integer and positive. got {n=}"
         )
-        assert self.__has_update_functions, "Update error: no update functions defined"
+        assert self.updateScheme == "probabilistic" or self.__has_update_functions, (
+            "Update error: no update functions defined"
+        )
         assert self.__has_update_scheme, "Update error: no update scheme defined"
         assert type(verbose) is bool, "Update error: verbose must be a bool"
         assert type(writeToFile) is bool, "Update error: writeToFile must be a bool"
@@ -208,7 +302,9 @@ class BooleanNetwork:
             case "asynchronous_random":
                 selected_update = self.__asynchronous_random_update
             case "probabilistic":
-                assert self.__has_flip_chance, "Update error: no flip_chance defined"
+                assert self.__has_probabilistic_functions, (
+                    "Update error: no probabilistic functions defined for every node"
+                )
                 selected_update = self.__probabilistic_update
             case _:
                 raise Exception("Update error: update scheme selection went wrong")
@@ -261,36 +357,37 @@ class BooleanNetwork:
         matrix: np.ndarray = np.zeros((dimension, dimension))
 
         if self.updateScheme == "probabilistic":
-            flipChance = self.flip_chance
-            self.UseSynchronousScheme()
             for i, state in enumerate(product((False, True), repeat=self.size)):
-                self.SetState(state)
+                choice_ranges = [
-                self.Update()
+                    range(len(self.probabilistic_functions[n]))
-                for flips in product((False, True), repeat=self.size):
+                    for n in range(self.size)
-                    flipped = int(
+                ]
-                        "".join(
+                for combo in product(*choice_ranges):
-                            str(
-                                int(
-                                    self.nodes[j] if not flips[j] else not self.nodes[j]
-                                )
-                            )
-                            for j in range(self.size)
-                        ),
-                        2,
-                    )
                     prob = np.float64(1)
-                    for flip in flips:
+                    result: list[bool] = []
-                        prob *= flipChance if flip else 1 - flipChance
+                    for n in range(self.size):
-                    matrix[i][flipped] = prob
+                        weights = self.probabilistic_weights[n]
-            self.UseProbabilisticScheme(flipChance)
+                        total_weight = sum(weights)
+                        chosen_index = combo[n]
+                        prob *= weights[chosen_index] / total_weight
+                        result.append(
+                            self.probabilistic_functions[n][chosen_index](*state)
+                        )
+                    result_index = int(
+                        "".join(str(int(b)) for b in result), 2
+                    )
+                    matrix[i][result_index] += prob
             return matrix
 
         if self.updateScheme == "asynchronous_random":
+            total_weight = sum(self.node_selection_weights)
             for i, state in enumerate(product((False, True), repeat=self.size)):
                 for j in range(self.size):
                     self.SetState(state)
                     self.nodes[j] = self.functions[j](*self.nodes)
-                    matrix[i][int(self.state, 2)] += np.float64(1) / self.size
+                    matrix[i][int(self.state, 2)] += (
+                        np.float64(self.node_selection_weights[j]) / total_weight
+                    )
             return matrix
 
         for i, state in enumerate(product((False, True), repeat=self.size)):