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Fix some warnings from LGTM (#2420)
* fix assignment of a variable to itself * Fix unnecessary 'else' clause in loop * formatting and redundant reasignment fix * mark unreachable code with a TODO comment * fix variable defined multiple times * fix static method without static decorator * revert unintended autoformatting Co-authored-by: Christian Clauss <cclauss@me.com> * revert autoformatting issue * applied black autoformatting Co-authored-by: Christian Clauss <cclauss@me.com>
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@ -218,7 +218,6 @@ def enigma(
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rotorpos1 -= 1
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rotorpos2 -= 1
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rotorpos3 -= 1
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plugboard = plugboard
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result = []
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@ -226,6 +226,7 @@ class DirectedGraph:
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break
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else:
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return True
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# TODO:The following code is unreachable.
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anticipating_nodes.add(stack[len_stack_minus_one])
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len_stack_minus_one -= 1
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if visited.count(node[1]) < 1:
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@ -453,6 +454,8 @@ class Graph:
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break
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else:
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return True
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# TODO: the following code is unreachable
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# is this meant to be called in the else ?
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anticipating_nodes.add(stack[len_stack_minus_one])
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len_stack_minus_one -= 1
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if visited.count(node[1]) < 1:
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@ -146,6 +146,7 @@ class Graph:
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self.parent[root2] = root1
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return root1
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@staticmethod
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def boruvka_mst(graph):
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"""
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Implementation of Boruvka's algorithm
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@ -44,7 +44,6 @@ def pi(precision: int) -> str:
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getcontext().prec = precision
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num_iterations = ceil(precision / 14)
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constant_term = 426880 * Decimal(10005).sqrt()
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multinomial_term = 1
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exponential_term = 1
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linear_term = 13591409
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partial_sum = Decimal(linear_term)
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@ -61,7 +61,6 @@ def triplet_sum2(arr: List[int], target: int) -> Tuple[int, int, int]:
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left += 1
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elif arr[i] + arr[left] + arr[right] > target:
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right -= 1
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else:
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return (0, 0, 0)
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@ -11,7 +11,6 @@ import pandas as pd
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def calculate_waitingtime(
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arrival_time: List[int], burst_time: List[int], no_of_processes: int
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) -> List[int]:
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"""
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Calculate the waiting time of each processes
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Return: list of waiting times.
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@ -126,13 +125,16 @@ if __name__ == "__main__":
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for i in range(no_of_processes):
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print("Enter the arrival time and brust time for process:--" + str(i + 1))
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arrival_time[i], burst_time[i] = map(int, input().split())
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waiting_time = calculate_waitingtime(arrival_time, burst_time, no_of_processes)
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bt = burst_time
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n = no_of_processes
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wt = waiting_time
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turn_around_time = calculate_turnaroundtime(bt, n, wt)
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calculate_average_times(waiting_time, turn_around_time, no_of_processes)
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processes = list(range(1, no_of_processes + 1))
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fcfs = pd.DataFrame(
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list(zip(processes, burst_time, arrival_time, waiting_time, turn_around_time)),
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columns=[
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