
import unittest
import user_code
import ast
import re   
import importlib
import csv
import unittest
import importlib
import numpy as np
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import user_code

class TestTask(unittest.TestCase):
    def setUp(self):
        # Save the current figure state
        plt.close('all')

    def test_plot_original_and_transformed(self):
        # Test with a simple quadrilateral and a translation
        quad = [(0,0), (1,0), (1,1), (0,1)]
        T = np.array([
            [1, 0, 2],
            [0, 1, 3],
            [0, 0, 1]
        ])
        fig = plt.figure()
        user_code.apply_transformations_and_plot(quad, [T])
        # There should be two lines (original and transformed)
        ax = plt.gca()
        lines = ax.get_lines()
        _dynamic_test(
            self,
            len(lines) == 2,
            "Both original and transformed quadrilaterals are plotted.",
            f"Expected 2 lines for original and transformed shapes, got {len(lines)}."
        )

    def test_vertices_connected_and_closed(self):
        quad = [(0,0), (3,0), (3,2), (0,2)]
        S = np.array([
            [2,0,0],
            [0,0.5,0],
            [0,0,1]
        ])
        plt.figure()
        user_code.apply_transformations_and_plot(quad, [S])
        ax = plt.gca()
        lines = ax.get_lines()
        # Check that the first and last vertices are the same (closed shape)
        for line in lines:
            xdata = line.get_xdata()
            ydata = line.get_ydata()
            _dynamic_test(
                self,
                np.isclose(xdata[0], xdata[-1]) and np.isclose(ydata[0], ydata[-1]),
                "Quadrilateral is closed (first and last vertex are the same).",
                f"Quadrilateral is not closed: x0={xdata[0]}, xN={xdata[-1]}, y0={ydata[0]}, yN={ydata[-1]}"
            )

    def test_transformation_order(self):
        # Test that transformations are applied in the correct order
        quad = [(0,0), (1,0), (1,1), (0,1)]
        # Scaling by 2, then translation by (1,1)
        S = np.array([
            [2,0,0],
            [0,2,0],
            [0,0,1]
        ])
        T = np.array([
            [1,0,1],
            [0,1,1],
            [0,0,1]
        ])
        # If order is S then T, (0,0) -> (0,0) -> (1,1), (1,0) -> (2,0) -> (3,1)
        plt.figure()
        user_code.apply_transformations_and_plot(quad, [T, S])
        ax = plt.gca()
        lines = ax.get_lines()
        # The second line is the transformed quadrilateral
        xdata = lines[1].get_xdata()
        ydata = lines[1].get_ydata()
        # The transformed first vertex should be (2,2) (scale then translate)
        _dynamic_test(
            self,
            np.isclose(xdata[0], 2) and np.isclose(ydata[0], 2),
            "Transformations are applied in the correct order.",
            f"Expected first transformed vertex at (2,2), got ({xdata[0]},{ydata[0]})"
        )

    def test_any_valid_quadrilateral(self):
        # Try with a non-rectangular quadrilateral and a rotation
        quad = [(1,2), (4,2), (3,5), (0,4)]
        theta = np.pi / 4
        R = np.array([
            [np.cos(theta), -np.sin(theta), 0],
            [np.sin(theta),  np.cos(theta), 0],
            [0, 0, 1]
        ])
        plt.figure()
        try:
            user_code.apply_transformations_and_plot(quad, [R])
            _dynamic_test(
                self,
                True,
                "Function handles any valid quadrilateral and transformation.",
                "Function failed on a valid quadrilateral and transformation."
            )
        except Exception as e:
            _dynamic_test(
                self,
                False,
                "Function handles any valid quadrilateral and transformation.",
                f"Function raised an exception: {e}"
            )

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

Aprende los fundamentos de la modelización geométrica utilizando Python. Explora cómo representar, manipular y aproximar figuras geométricas de forma programática. Este curso abarca formas básicas, transformaciones y técnicas prácticas de aproximación, haciendo que los conceptos geométricos sean accesibles e interactivos.

Comience con los conceptos fundamentales del modelado geométrico y cómo Python puede utilizarse para representar y manipular formas básicas.

Profundiza en las transformaciones geométricas como la traslación, la rotación y la escala, y observa cómo afectan a las figuras en Python.

Aprenda a aproximar curvas y formas complejas utilizando polígonos y otras técnicas en Python.

Desafío: Transformaciones Combinadas

Solución