
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 user_code

class TestTask(unittest.TestCase):
    def setUp(self):
        self.wavenumbers = [4000, 3500, 3000, 2500, 2000, 1500, 1000, 500]
        self.absorbance = [0.05, 0.15, 0.40, 0.25, 0.10, 0.20, 0.18, 0.09]

    def test_line_plot_exists(self):
        plt.close('all')
        importlib.reload(user_code)
        fig = plt.figure()
        user_code.plot_ir_spectrum(self.wavenumbers, self.absorbance)
        ax = plt.gca()
        found = False
        for line in ax.get_lines():
            xdata = list(line.get_xdata())
            ydata = list(line.get_ydata())
            if xdata == self.wavenumbers and ydata == self.absorbance:
                found = True
                break
        _dynamic_test(
            self,
            found,
            "Line plot displays correct data",
            f"Expected line plot with x={self.wavenumbers}, y={self.absorbance}"
        )

    def test_xaxis_label(self):
        plt.close('all')
        importlib.reload(user_code)
        fig = plt.figure()
        user_code.plot_ir_spectrum(self.wavenumbers, self.absorbance)
        ax = plt.gca()
        label = ax.get_xlabel()
        _dynamic_test(
            self,
            label == "Wavenumber (cm$^{-1}$)",
            "X-axis label is correct",
            f"Expected x-axis label 'Wavenumber (cm$^{-1}$)', got '{label}'"
        )

    def test_yaxis_label(self):
        plt.close('all')
        importlib.reload(user_code)
        fig = plt.figure()
        user_code.plot_ir_spectrum(self.wavenumbers, self.absorbance)
        ax = plt.gca()
        label = ax.get_ylabel()
        _dynamic_test(
            self,
            label == "Absorbance",
            "Y-axis label is correct",
            f"Expected y-axis label 'Absorbance', got '{label}'"
        )

    def test_title(self):
        plt.close('all')
        importlib.reload(user_code)
        fig = plt.figure()
        user_code.plot_ir_spectrum(self.wavenumbers, self.absorbance)
        ax = plt.gca()
        title = ax.get_title()
        _dynamic_test(
            self,
            title == "IR Spectrum",
            "Plot title is correct",
            f"Expected plot title 'IR Spectrum', got '{title}'"
        )

    def test_xaxis_inverted(self):
        plt.close('all')
        importlib.reload(user_code)
        fig = plt.figure()
        user_code.plot_ir_spectrum(self.wavenumbers, self.absorbance)
        ax = plt.gca()
        lims = ax.get_xlim()
        _dynamic_test(
            self,
            lims[0] > lims[1],
            "X-axis is inverted (decreasing order)",
            f"Expected x-axis inverted, got limits {lims}"
        )

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

An engaging, hands-on course introducing Python programming through real-world chemistry problems. Learn to clean experimental data, perform molar calculations, visualize spectra, and analyze reaction rates using Python and scientific libraries.

Learn Python basics through chemistry-themed examples, focusing on variables, data types, and simple calculations relevant to laboratory work.

Dive into real-world chemistry data: clean, process, and analyze raw experimental results using Python.

Explore how to visualize and analyze chemical spectra and reaction rates using Python's scientific libraries.

Challenge: Visualize an IR Spectrum

Ratkaisu

Challenge: Visualize an IR Spectrum

Ratkaisu