151 lines
3.5 KiB
Python
151 lines
3.5 KiB
Python
import ast
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import math
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VERSION = "0.0.0"
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sContinue = True
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state = []
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def show_help():
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print("vector [5,6,7...] - set the current dataset to the given vector")
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print("stdev - get the standard deviation of the current dataset")
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print("pstdev - get the population standard deviation of the current dataset")
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print("variance - get the variance of the current dataset")
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print("pvariance - get the population variance of the current dataset")
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print("mean - get the mean of the current dataset")
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print("median - get the median of the current dataset")
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print("mode - get the mode of the current dataset")
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print("var - get the variance of the current dataset")
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print("print - prints the current dataset")
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print("clear - clears the current dataset")
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print("clr - clears the screen")
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def get_mean():
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"""
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Get the mean value of the state vector.
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:return: The average value of the state vector.
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"""
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global state
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mean = sum(state) / len(state)
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return mean
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def get_median():
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"""
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This function calculates the median of the state vector.
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The implementation uses the algorithm based on sorting.
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:return: The median value of the sorted `state` list.
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"""
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global state
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state.sort()
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n = len(state)
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median = 0
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if n % 2 == 0:
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median = (state[n // 2 - 1] + state[n // 2]) / 2
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else:
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median = state[n // 2]
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return median
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def get_mode():
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"""
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:return: The most frequent element in the global variable 'state'.
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"""
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global state
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from collections import Counter
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mode = Counter(state).most_common(1)[0][0]
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return mode
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def get_variance():
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global state
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n = len(state)
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mean = get_mean()
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variance = sum((x - mean) ** 2 for x in state) / (n - 1)
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return variance
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def get_population_variance():
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global state
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n = len(state)
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mean = get_mean()
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variance = sum((x - mean) ** 2 for x in state) / n
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return variance
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def get_standard_deviation():
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variance = get_variance()
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std_dev = math.sqrt(variance)
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return std_dev
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def get_population_standard_deviation():
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pvariance = get_population_variance()
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std_dev = math.sqrt(pvariance)
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return std_dev
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def start_shell():
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global state
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state = []
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print(f'Welcome to math-shell v{VERSION}')
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handle_input()
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def handle_input():
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global state
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value = []
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print('>>>', end=' ')
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i = input()
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should_split = i.__contains__(' ')
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if should_split:
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command, value = i.split(sep=' ', maxsplit=1)
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value = ast.literal_eval(value)
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else:
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command = i
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match command.lower():
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case 'vector':
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state = value
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print(f"Set state to: {value}")
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case 'mean':
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print(get_mean())
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case 'median':
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print(get_median())
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case 'mode':
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print(get_mode())
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case 'stdev':
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print(get_standard_deviation())
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case 'pstdev':
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print(get_population_standard_deviation())
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case 'variance':
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print(get_variance())
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case 'pvariance':
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print(get_population_variance())
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case 'print':
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if state is not None:
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print(f"{state}")
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else:
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print("No state")
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case 'exit':
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return False
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case other:
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show_help()
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return True
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if __name__ == '__main__':
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start_shell()
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while sContinue:
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sContinue = handle_input()
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