
import unittest
import user_code
import ast
import re   
import importlib
import csv
import unittest
import importlib
import math
import numpy as np

class TestTask(unittest.TestCase):
    def test_returns_correct_length(self):
        import user_code
        importlib.reload(user_code)
        result = user_code.approximate_curve_with_polygon(np.sin, (0, np.pi), 5)
        _dynamic_test(
            self,
            isinstance(result, list) and len(result) == 5,
            "Returned list has correct number of vertices (5)",
            f"Expected 5 vertices, got {len(result) if isinstance(result, list) else 'not a list'}",
        )

    def test_returns_tuples_of_xy(self):
        import user_code
        importlib.reload(user_code)
        result = user_code.approximate_curve_with_polygon(np.sin, (0, np.pi), 4)
        all_tuples = all(isinstance(pt, tuple) and len(pt) == 2 for pt in result)
        _dynamic_test(
            self,
            all_tuples,
            "All elements are tuples of length 2 (x, y)",
            f"Not all elements are tuples of length 2: {result}",
        )
        all_nums = all(isinstance(pt[0], (int, float, np.floating)) and isinstance(pt[1], (int, float, np.floating)) for pt in result)
        _dynamic_test(
            self,
            all_nums,
            "All tuple elements are numbers (x, y)",
            f"Not all tuple elements are numbers: {result}",
        )

    def test_x_values_evenly_spaced(self):
        import user_code
        importlib.reload(user_code)
        interval = (0, 10)
        num = 6
        result = user_code.approximate_curve_with_polygon(np.cos, interval, num)
        x_vals = [pt[0] for pt in result]
        expected_x = np.linspace(interval[0], interval[1], num)
        close = np.allclose(x_vals, expected_x)
        _dynamic_test(
            self,
            close,
            "x-values are evenly spaced in the interval",
            f"x-values are not evenly spaced: {x_vals} vs expected {expected_x}",
        )

    def test_y_values_correct(self):
        import user_code
        importlib.reload(user_code)
        interval = (0, np.pi)
        num = 4
        result = user_code.approximate_curve_with_polygon(np.sin, interval, num)
        x_vals = np.linspace(interval[0], interval[1], num)
        y_expected = np.sin(x_vals)
        y_vals = [pt[1] for pt in result]
        close = np.allclose(y_vals, y_expected)
        _dynamic_test(
            self,
            close,
            "y-values are correct for the given curve_func",
            f"y-values do not match function output: {y_vals} vs expected {list(y_expected)}",
        )

def _dynamic_test(test_case, condition, success_message, failure_message):
    if condition:
        test_case._testMethodName = success_message
        test_case.assertTrue(True, success_message)
    else:
        test_case._testMethodName = failure_message
        test_case.fail(failure_message)

def normalize_text(text):
    text = text.lower()
    text = re.sub(r"\\s{2,}", " ", text)
    text = re.sub(r"\\s*([,:?])\\s*", r"\\1 ", text)
    return text.strip()

def change_var(code: str, var_name: str, value: str) -> str:
    tree = ast.parse(code)
    lines = code.splitlines()
    changed = False
    # Collect all assignment nodes to modify
    assign_nodes = [
        (i, node)
        for i, node in enumerate(tree.body)
        if isinstance(node, ast.Assign)
        and any(isinstance(target, ast.Name) and target.id == var_name for target in node.targets)
    ]

    # If nothing to change, return unmodified code
    if not assign_nodes:
        return code

    # Perform replacements for all matching assignments (from last to first to not break line offsets)
    for i, node in reversed(assign_nodes):
        start_line = node.lineno - 1
        line = lines[start_line]
        indent = ' ' * (len(line) - len(line.lstrip()))
        lines[start_line] = f"{indent}{var_name} = {value}"
        next_line = len(lines)
        for next_node in tree.body[i+1:]:
            if hasattr(next_node, 'lineno'):
                next_line = next_node.lineno - 1
                break
        if next_line > start_line + 1:
            lines[start_line+1:next_line] = []
        changed = True

    return '\\n'.join(lines) if changed else code

if __name__ == "__main__":
    unittest.main()


test_main.py

Leer de basisprincipes van geometrisch modelleren met Python. Ontdek hoe je geometrische figuren programmeermatig kunt representeren, manipuleren en benaderen. Deze cursus behandelt basisvormen, transformaties en praktische benaderingstechnieken, waardoor geometrische concepten toegankelijk en interactief worden.

Maak kennis met de kernconcepten van geometrisch modelleren en hoe Python kan worden gebruikt om basisvormen te representeren en te manipuleren.

Verdiep u in geometrische transformaties zoals translatie, rotatie en schaling, en zie hoe deze vormen beïnvloeden in Python.

Leer hoe je krommen en complexe vormen kunt benaderen met behulp van polygonen en andere technieken in Python.

Uitdaging: Krommebenadering

Oplossing