Comparing efficiencies of thermodynamic cycles is key for engineering decisions. This challenge will help you automate analysis and visualization.


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

class TestTask(unittest.TestCase):
    def setUp(self):
        import user_code
        importlib.reload(user_code)
        self.user_code = user_code

    def test_average_efficiency_calculation(self):
        import user_code
        importlib.reload(user_code)
        # Patch plt.show to prevent GUI
        plt.show = lambda *args, **kwargs: None
        # Run and capture average
        cycle_names = ['Otto', 'Diesel', 'Brayton', 'Rankine']
        efficiencies = [30, 35, 40, 42]
        # Temporarily patch plt to capture axhline
        original_axhline = plt.axhline
        self.avg_value = None
        def fake_axhline(y, *args, **kwargs):
            self.avg_value = y
            return original_axhline(y, *args, **kwargs)
        plt.axhline = fake_axhline
        self.user_code.analyze_and_plot_efficiency(cycle_names, efficiencies)
        plt.axhline = original_axhline
        expected_avg = sum(efficiencies) / len(efficiencies)
        _dynamic_test(
            self,
            self.avg_value is not None and abs(self.avg_value - expected_avg) < 1e-6,
            f"Correct average efficiency calculated ({expected_avg}) and used for axhline",
            f"Average efficiency not correctly used in axhline: expected {expected_avg}, got {self.avg_value}",
        )

    def test_bar_chart_cycle_names_and_efficiencies(self):
        import user_code
        importlib.reload(user_code)
        plt.show = lambda *args, **kwargs: None
        cycle_names = ['Otto', 'Diesel', 'Brayton', 'Rankine']
        efficiencies = [30, 35, 40, 42]
        fig = plt.figure()
        ax = fig.add_subplot(111)
        original_bar = plt.bar
        bars_data = {}
        def fake_bar(x, height, *args, **kwargs):
            bars_data['x'] = x
            bars_data['height'] = height
            return original_bar(x, height, *args, **kwargs)
        plt.bar = fake_bar
        user_code.analyze_and_plot_efficiency(cycle_names, efficiencies)
        plt.bar = original_bar
        _dynamic_test(
            self,
            'x' in bars_data and 'height' in bars_data and list(bars_data['x']) == cycle_names and list(bars_data['height']) == efficiencies,
            "Bar chart displays all cycle names with correct efficiencies",
            f"Bar chart does not display correct cycles or efficiencies: got {bars_data}",
        )

    def test_axis_labels(self):
        import user_code
        importlib.reload(user_code)
        plt.show = lambda *args, **kwargs: None
        cycle_names = ['Otto', 'Diesel', 'Brayton', 'Rankine']
        efficiencies = [30, 35, 40, 42]
        fig = plt.figure()
        ax = fig.add_subplot(111)
        original_xlabel = plt.xlabel
        original_ylabel = plt.ylabel
        xlabel_val = {}
        ylabel_val = {}
        def fake_xlabel(val, *args, **kwargs):
            xlabel_val['value'] = val
            return original_xlabel(val, *args, **kwargs)
        def fake_ylabel(val, *args, **kwargs):
            ylabel_val['value'] = val
            return original_ylabel(val, *args, **kwargs)
        plt.xlabel = fake_xlabel
        plt.ylabel = fake_ylabel
        user_code.analyze_and_plot_efficiency(cycle_names, efficiencies)
        plt.xlabel = original_xlabel
        plt.ylabel = original_ylabel
        _dynamic_test(
            self,
            xlabel_val.get('value','') == 'Thermodynamic Cycle',
            "X-axis label is correct",
            f"X-axis label incorrect: got {xlabel_val.get('value','')}",
        )
        _dynamic_test(
            self,
            ylabel_val.get('value','') == 'Efficiency (%)',
            "Y-axis label is correct",
            f"Y-axis label incorrect: got {ylabel_val.get('value','')}",
        )

    def test_legend_contains_average(self):
        import user_code
        importlib.reload(user_code)
        plt.show = lambda *args, **kwargs: None
        cycle_names = ['Otto', 'Diesel', 'Brayton', 'Rankine']
        efficiencies = [30, 35, 40, 42]
        legend_label = {}
        original_legend = plt.legend
        def fake_legend(*args, **kwargs):
            handles, labels = plt.gca().get_legend_handles_labels()
            legend_label['labels'] = labels
            return original_legend(*args, **kwargs)
        plt.legend = fake_legend
        user_code.analyze_and_plot_efficiency(cycle_names, efficiencies)
        plt.legend = original_legend
        found = False
        if 'labels' in legend_label:
            for label in legend_label['labels']:
                if 'average efficiency' in label.lower():
                    found = True
        _dynamic_test(
            self,
            found,
            "Legend includes the average efficiency value",
            f"Legend does not include an average efficiency label: {legend_label.get('labels', [])}",
        )

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

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Challenge: Analyze and Plot Efficiency Data

Oplossing

Challenge: Analyze and Plot Efficiency Data

Oplossing