inst/z1.txt

@@ -1,68 +1,5 @@
-Programming Challenges - Increasing Difficulty
+Napisz program w języku Python, który narysuje wykres funkcji liniowej y=x.
 
-Task 1: Basic Plotting
+Author: AI
-Create a Python script that plots a simple quadratic function y = x^2 for x values from -5 to 5.
-Requirements:
-- Use NumPy to generate the x values (at least 100 points)
-- Calculate corresponding y values
-- Plot the function using Matplotlib
-- Add appropriate labels and title
 
-Task 2: Multiple Functions
-Extend your script to plot two functions on the same graph:
-- y1 = sin(x)
-- y2 = cos(x)
-Requirements:
-- Plot both functions for x values from 0 to 4π
-- Use different colors for each function
-- Add a legend to distinguish the functions
-- Include axis labels and a title
 
-Task 3: Parametric Plotting
-Create a script that plots a parametric curve (e.g., a spiral or Lissajous figure).
-Requirements:
-- Use parametric equations to generate x and y coordinates
-- Plot the curve with appropriate styling
-- Add labels, title, and grid
-- Experiment with different parameter ranges
-
-Task 4: Data Visualization
-Create a script that visualizes a dataset (you can generate synthetic data or use built-in datasets).
-Requirements:
-- Create at least 2 different types of plots (e.g., line plot, scatter plot, bar chart)
-- Include proper labels, titles, and legends
-- Use color effectively to enhance understanding
-- Add annotations or special markers for important data points
-
-Task 5: Interactive Plotting
-Create an interactive plot where users can modify parameters and see the results in real-time.
-Requirements:
-- Use matplotlib widgets or another interactive library
-- Allow users to change at least 2 parameters of a function
-- Update the plot dynamically as parameters change
-- Include clear instructions for the user
-
-Task 6: Advanced Visualization
-Create a comprehensive visualization that combines multiple plot types in subplots.
-Requirements:
-- Create at least 3 subplots with different types of visualizations
-- Share axes where appropriate
-- Use consistent styling across all subplots
-- Include a main title for the entire figure
-- Save the figure to a file with high resolution
-
-Task 7: Object-Oriented Plotting
-Refactor one of your previous scripts to use object-oriented Matplotlib approach.
-Requirements:
-- Use Figure and Axes objects explicitly
-- Create reusable plotting functions or classes
-- Implement proper error handling
-- Document your code with comments or docstrings
-
-Task 8: Custom Visualization
-Create a unique visualization of your choice that demonstrates advanced Matplotlib features.
-Requirements:
-- Use advanced features like custom colormaps, 3D plotting, or animations
-- Include data analysis or transformation
-- Make the visualization informative and visually appealing
-- Provide a clear explanation of what the visualization shows

roz/1.py

@@ -1,37 +0,0 @@
-import matplotlib.pyplot as plt
-import numpy as np
-
-# Zdefiniuj zakres wartości x
-x = np.linspace(-10, 10, 400)  # 400 punktów od -10 do 10
-
-# Oblicz wartości y = x
-y = x
-
-# Narysuj wykres
-plt.plot(x, y, label='y = x')
-
-# Dodaj okrąg
-theta = np.linspace(0, 2*np.pi, 400)
-radius = 5
-x_circle = radius * np.cos(theta)
-y_circle = radius * np.sin(theta)
-plt.plot(x_circle, y_circle, label=f'Okrąg o promieniu {radius}')
-
-# Dodaj siatkę
-plt.grid(True)
-
-# Dodaj etykiety osi
-plt.xlabel('x')
-plt.ylabel('y')
-
-# Dodaj tytuł
-plt.title('Wykres funkcji liniowej y = x z okręgiem')
-
-# Pokaż legendę
-plt.legend()
-
-# Ustaw skalę osi, żeby wyglądało proporcjonalnie
-plt.axis('equal')
-
-# Wyświetl wykres
-plt.show()

rozw

@@ -1,28 +0,0 @@
-import numpy as np
-import matplotlib.pyplot as plt
-
-# Generate x values from 0 to 4π
-x = np.linspace(0, 4*np.pi, 1000)
-
-# Calculate y values for both functions
-y1 = np.sin(x)
-y2 = np.cos(x)
-
-# Create the plot
-plt.figure(figsize=(10, 6))
-plt.plot(x, y1, color='blue', label='sin(x)')
-plt.plot(x, y2, color='red', label='cos(x)')
-
-# Add labels and title
-plt.xlabel('x')
-plt.ylabel('y')
-plt.title('Sine and Cosine Functions')
-
-# Add legend
-plt.legend()
-
-# Add grid for better readability
-plt.grid(True, alpha=0.3)
-
-# Display the plot
-plt.show()