init

.gitignore

@@ -0,0 +1,4 @@
+.cache
+.py
+compile_commands.json
+build

CMakeLists.txt

@@ -0,0 +1,13 @@
+cmake_minimum_required(VERSION 3.5)
+project(white-screen-qt)
+
+add_executable(${PROJECT_NAME} main.cpp)
+
+set(CMAKE_EXPORT_COMPILE_COMMANDS ON)
+set(CMAKE_EXPORT_COMPILE_COMMANDS ON CACHE INTERNAL "")
+
+find_package(Qt5 COMPONENTS Widgets Gui REQUIRED)
+
+target_link_libraries(${PROJECT_NAME} PRIVATE Qt5::Widgets Qt5::Gui)
+
+qt5_wrap_cpp(${PROJECT_NAME} main.cpp)

conanfile.txt

@@ -0,0 +1,7 @@
+[requires]
+qt/6.8.3
+[generators]
+CMakeDeps
+CMakeToolchain
+[layout]
+cmake_layout

delays.csv

@@ -0,0 +1,527 @@
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latency.py

@@ -0,0 +1,208 @@
+import pandas as pd
+import matplotlib.pyplot as plt
+import numpy as np
+from scipy import stats
+
+def calculate_confidence_interval(data, confidence=0.95):
+    """
+    Вычисление доверительного интервала для среднего значения
+    
+    Parameters:
+    data: массив данных
+    confidence: уровень доверия (по умолчанию 95%)
+    
+    Returns:
+    tuple: (среднее, нижняя граница, верхняя граница, стандартная ошибка)
+    """
+    n = len(data)
+    mean = np.mean(data)
+    std_error = stats.sem(data)  # Стандартная ошибка среднего
+    
+    # Вычисление доверительного интервала с использованием t-распределения
+    ci = stats.t.interval(confidence, n-1, loc=mean, scale=std_error)
+    
+    return mean, ci[0], ci[1], std_error
+
+def plot_delay_histogram_with_ci(csv_file_path, save_to_file=True, show_plot=False, 
+                               confidence_level=0.99, delimiter=','):
+    """
+    Универсальный скрипт для построения гистограммы с доверительным интервалом
+    """
+    
+    try:
+        # Чтение данных
+        df = pd.read_csv(csv_file_path, delimiter=delimiter, header=None, 
+                        names=['index', 'delay_ms'])
+        delays = df['delay_ms'].values
+        
+        # Вычисление базовой статистики
+        mean_delay = np.mean(delays)
+        median_delay = np.median(delays)
+        std_delay = np.std(delays)
+        min_delay = np.min(delays)
+        max_delay = np.max(delays)
+        
+        # Вычисление доверительного интервала
+        mean_ci, ci_lower, ci_upper, std_error = calculate_confidence_interval(
+            delays, confidence_level)
+        
+        # Вывод статистики
+        print("=" * 60)
+        print("АНАЛИЗ ЗАДЕРЖЕК С ДОВЕРИТЕЛЬНЫМ ИНТЕРВАЛОМ")
+        print("=" * 60)
+        print(f"Количество измерений (n): {len(delays)}")
+        print(f"Уровень доверия: {confidence_level*100}%")
+        print("\n--- ОСНОВНАЯ СТАТИСТИКА ---")
+        print(f"Минимальная задержка: {min_delay:.2f} мс")
+        print(f"Максимальная задержка: {max_delay:.2f} мс")
+        print(f"Средняя задержка: {mean_delay:.2f} мс")
+        print(f"Медианная задержка: {median_delay:.2f} мс")
+        print(f"Стандартное отклонение: {std_delay:.2f} мс")
+        print(f"Стандартная ошибка: {std_error:.4f} мс")
+        
+        print(f"\n--- ДОВЕРИТЕЛЬНЫЙ ИНТЕРВАЛ {confidence_level*100}% ---")
+        print(f"Точечная оценка среднего: {mean_ci:.2f} мс")
+        print(f"Доверительный интервал: [{ci_lower:.2f}, {ci_upper:.2f}] мс")
+        print(f"Ширина интервала: {ci_upper - ci_lower:.2f} мс")
+        print(f"Погрешность: ±{(ci_upper - ci_lower)/2:.2f} мс")
+        
+        # Дополнительные метрики
+        cv = (std_delay / mean_delay) * 100  # Коэффициент вариации
+        print(f"\n--- ДОПОЛНИТЕЛЬНЫЕ МЕТРИКИ ---")
+        print(f"Коэффициент вариации: {cv:.1f}%")
+        print(f"Q1 (25-й перцентиль): {np.percentile(delays, 25):.2f} мс")
+        print(f"Q3 (75-й перцентиль): {np.percentile(delays, 75):.2f} мс")
+        print(f"IQR (межквартильный размах): {np.percentile(delays, 75) - np.percentile(delays, 25):.2f} мс")
+        
+        # Создание гистограммы
+        plt.figure(figsize=(14, 8))
+        n_bins = min(30, len(delays) // 5)
+        
+        # Гистограмма
+        n, bins, patches = plt.hist(delays, bins=n_bins, alpha=0.7, color='steelblue', 
+                                   edgecolor='black', linewidth=0.5, density=False)
+        
+        plt.xlabel('Задержка (мс)', fontsize=12)
+        plt.ylabel('Частота', fontsize=12)
+        plt.title(f'Распределение задержек на обработку нажатия мыши (n={len(delays)}, CI={confidence_level*100}%)', 
+                 fontsize=14, fontweight='bold')
+        plt.grid(True, alpha=0.3)
+        
+        # Добавление статистических линий
+        plt.axvline(mean_delay, color='red', linestyle='-', linewidth=2, 
+                   label=f'Среднее ({mean_delay:.1f} мс)')
+        plt.axvline(median_delay, color='green', linestyle='-', linewidth=2, 
+                   label=f'Медиана ({median_delay:.1f} мс)')
+        
+        # Добавление доверительного интервала
+        plt.axvspan(ci_lower, ci_upper, alpha=0.2, color='yellow', 
+                   label=f'ДИ {confidence_level*100}%: [{ci_lower:.1f}, {ci_upper:.1f}] мс')
+        
+        # Вертикальные линии для границ доверительного интервала
+        plt.axvline(ci_lower, color='orange', linestyle='--', linewidth=1, alpha=0.7)
+        plt.axvline(ci_upper, color='orange', linestyle='--', linewidth=1, alpha=0.7)
+        
+        plt.legend(loc='upper right', fontsize=10)
+        plt.tight_layout()
+        
+        # Сохранение в файл
+        if save_to_file:
+            output_file = f'delay_distribution_ci_{int(confidence_level*100)}.png'
+            plt.savefig(output_file, dpi=300, bbox_inches='tight')
+            print(f"\n✓ Гистограмма сохранена как: {output_file}")
+        
+        # Показ графика
+        if show_plot:
+            plt.show()
+        else:
+            plt.close()
+            
+        print("\n✓ Анализ завершен успешно")
+        
+        return {
+            'data': delays,
+            'mean': mean_delay,
+            'median': median_delay,
+            'std': std_delay,
+            'ci_lower': ci_lower,
+            'ci_upper': ci_upper,
+            'confidence_level': confidence_level
+        }
+        
+    except FileNotFoundError:
+        print(f"✗ Ошибка: Файл '{csv_file_path}' не найден")
+        return None
+    except Exception as e:
+        print(f"✗ Ошибка: {e}")
+        return None
+
+def compare_confidence_intervals(csv_file_path, confidence_levels=[0.90, 0.95, 0.99], delimiter=','):
+    """
+    Сравнение доверительных интервалов для разных уровней доверия
+    """
+    try:
+        df = pd.read_csv(csv_file_path, delimiter=delimiter, header=None, 
+                        names=['index', 'delay_ms'])
+        delays = df['delay_ms'].values
+        
+        print("=" * 70)
+        print("СРАВНЕНИЕ ДОВЕРИТЕЛЬНЫХ ИНТЕРВАЛОВ ДЛЯ РАЗНЫХ УРОВНЕЙ ДОВЕРИЯ")
+        print("=" * 70)
+        print(f"Количество измерений: {len(delays)}")
+        print(f"Среднее значение: {np.mean(delays):.2f} мс")
+        print(f"Стандартная ошибка: {stats.sem(delays):.4f} мс\n")
+        
+        results = []
+        for conf in confidence_levels:
+            mean, ci_lower, ci_upper, std_error = calculate_confidence_interval(delays, conf)
+            width = ci_upper - ci_lower
+            margin = width / 2
+            
+            results.append({
+                'confidence': conf,
+                'mean': mean,
+                'ci_lower': ci_lower,
+                'ci_upper': ci_upper,
+                'width': width,
+                'margin': margin
+            })
+            
+            print(f"Доверительный интервал {conf*100:.0f}%:")
+            print(f"  [{ci_lower:.2f}, {ci_upper:.2f}] мс")
+            print(f"  Ширина: {width:.2f} мс, Погрешность: ±{margin:.2f} мс")
+            print()
+        
+        return results
+        
+    except Exception as e:
+        print(f"Ошибка при сравнении интервалов: {e}")
+        return None
+
+# Пример использования
+if __name__ == "__main__":
+    # Укажите путь к вашему файлу
+    csv_file = "delays.csv"
+    
+    print("АНАЛИЗ ДОВЕРИТЕЛЬНЫХ ИНТЕРВАЛОВ ДЛЯ ЗАДЕРЖЕК")
+    print("=" * 50)
+    
+    # Основной анализ с 95% доверительным интервалом
+    results = plot_delay_histogram_with_ci(
+        csv_file_path=csv_file,
+        save_to_file=True,
+        show_plot=False,
+        confidence_level=0.99
+    )
+    
+    print("\n" + "=" * 50)
+    
+    # Сравнение разных уровней доверия
+    compare_results = compare_confidence_intervals(csv_file, [0.90, 0.95, 0.99])
+    
+    # Интерпретация результатов
+    if results:
+        print("\n--- ИНТЕРПРЕТАЦИЯ РЕЗУЛЬТАТОВ ---")
+        print(f"С вероятностью 95% истинное среднее значение задержки ")
+        print(f"находится в интервале от {results['ci_lower']:.2f} до {results['ci_upper']:.2f} мс.")
+        print(f"Это означает, что если бы мы повторили эксперимент много раз,")
+        print(f"95% вычисленных таким образом интервалов содержали бы истинное среднее значение.")

main.cpp

@@ -0,0 +1,55 @@
+#include <QApplication>
+#include <QWidget>
+#include <QMouseEvent>
+#include <QVBoxLayout>
+#include <QLabel>
+#include <QTimer>
+
+class ClickableWindow : public QWidget
+{
+public:
+    ClickableWindow(QWidget *parent = nullptr) : QWidget(parent)
+    {
+        // Create a label to show instructions
+        QLabel *label = new QLabel("Click anywhere to change background color!");
+        label->setAlignment(Qt::AlignCenter);
+        
+        // Set up layout
+        QVBoxLayout *layout = new QVBoxLayout(this);
+        layout->addWidget(label);
+        
+        // Set initial background color
+        setStyleSheet("background-color: black;");
+        
+        // Set window properties
+        setWindowTitle("Click to Change Background Color");
+        resize(400, 300);
+    }
+
+protected:
+    void mousePressEvent(QMouseEvent *event) override
+    {
+        if (event->button() == Qt::LeftButton) {        
+            setStyleSheet("background-color: white");
+        }
+
+        QTimer::singleShot(200, this, &ClickableWindow::backToBlack);
+        
+        QWidget::mousePressEvent(event);
+    }
+
+    void backToBlack() 
+    {
+        setStyleSheet("background-color: black");
+    }
+};
+
+int main(int argc, char *argv[])
+{
+    QApplication app(argc, argv);
+    
+    ClickableWindow window;
+    window.show();
+    
+    return app.exec();
+}