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added descriptive names
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@ -18,9 +18,9 @@ def get_inputs() -> tuple:
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('1/(1+x**2)', 1.0, -1.0)
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"""
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func = input("Enter function with variable as x: ")
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a = float(input("Enter lower limit: "))
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b = float(input("Enter upper limit: "))
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return func, a, b
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lower_limit = float(input("Enter lower limit: "))
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upper_limit = float(input("Enter upper limit: "))
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return func, lower_limit, upper_limit
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def safe_function_eval(func_str: str) -> float:
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@ -32,7 +32,6 @@ def safe_function_eval(func_str: str) -> float:
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Returns:
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float: The evaluated function result.
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Examples:
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>>> f = safe_function_eval('x**2')
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>>> f(3)
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@ -54,14 +53,14 @@ def safe_function_eval(func_str: str) -> float:
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return lambda_func
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def compute_table(func: str, a: float, b: float, acc: int) -> tuple:
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def compute_table(func: str, lower_limit: float, upper_limit: float, acc: int) -> tuple:
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"""
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Compute the table of function values based on the limits and accuracy.
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Args:
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func (str): The mathematical function with the variable 'x' as a string.
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a (float): The lower limit of the integral.
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b (float): The upper limit of the integral.
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lower_limit (float): The lower limit of the integral.
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upper_limit (float): The upper limit of the integral.
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acc (int): The number of subdivisions for accuracy.
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Returns:
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@ -76,8 +75,8 @@ def compute_table(func: str, a: float, b: float, acc: int) -> tuple:
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"""
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# Weddle's rule requires number of intervals as a multiple of 6 for accuracy
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n_points = acc * 6 + 1
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h = (b - a) / (n_points - 1)
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x_vals = np.linspace(a, b, n_points)
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h = (upper_limit - lower_limit) / (n_points - 1)
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x_vals = np.linspace(lower_limit, upper_limit, n_points)
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# Evaluate function values at all points
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table = func(x_vals)
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@ -111,14 +110,14 @@ def apply_weights(table: list) -> list:
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return add
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def compute_solution(add: list, table: list, h: float) -> float:
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def compute_solution(add: list, table: list, step_size: float) -> float:
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"""
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Compute the final solution using the weighted values and table.
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Args:
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add (list): A list of weighted values from apply_weights.
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table (list): A list of function values.
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h (float): The step size (h) calculated from the limits and accuracy.
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step_size (float): The step size calculated from the limits and accuracy.
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Returns:
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float: The final computed integral solution.
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@ -128,7 +127,7 @@ def compute_solution(add: list, table: list, h: float) -> float:
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... -0.866, -1.0], 0.5235983333333333)
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0.7853975
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"""
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return 0.3 * h * (sum(add) + table[0] + table[-1])
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return 0.3 * step_size * (sum(add) + table[0] + table[-1])
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if __name__ == "__main__":
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