analysis.ipynb

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   "source": [
    "# Анализ статьи [On the convergence of Single-Call Stochastic Extra-Gradient Methods](https://arxiv.org/abs/1908.08465)"
   ]
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    "**Latex preset**\n",
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    "\n",
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   "source": [
    "## Причины статьи\n",
    "\n",
    "Машинное обучение (в частности GANы) нуждается в методах для решения вариациационных неравенств, которые бы требовали как можно меньше вызовов оракула (вычисление градиента, поиск проекции). Базовые методы требуют 2 вызова и градиента, и проекции за 1 итерацию.\n",
    "\n",
    "Очень часто в таких задачах либо нет ограничений на решения, либо они крайне незначительны и их можно простыми способами обойти, поэтому проекция не страшна. Вся борьба ведётся за вычисление градиента."
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    "## Основные определения\n",
    "\n",
    "### Стохастический анализ\n",
    "\n",
    "Пусть $(\\Omega, \\cF, P)$ - вероятностной пространство, $(E, \\cE)$ - измеримое пространство. Тогда множество случайных величин $\\{X_t\\}_{t = 1}^\\infty$, $X_t \\colon \\Omega \\to E$ называется *стохастическим (случайным) процессом*.\n",
    "\n",
    "В силу исторических причин, $t$ соотносится обычно со временем.\n",
    "\n",
    "**Определение:** пусть $T \\colon \\cX \\to \\cX$ - отображение, сохраняющее вероятностную меру, $f \\in L_1(P)$ (то есть $f$ интегрируема по Лебегу по мере $P$), $x \\in \\cX$ Тогда *эргодическим средним* или же *средним по времени* называется следующая точка, если она существует:\n",
    "$$\n",
    "    \\hat{f}(x) = \\lim_{n \\to \\infty} \\frac{1}{n} \\sum_{k = 0}^{n - 1} f(T^k(x))\n",
    "$$\n",
    "где $T^k$ соответствует композиции $k$ раз.\n",
    "\n",
    "**В контексте алгоритмов:** $x = x_0$ - стартовая точка метода оптимизации. За $T$ можно считать 1 итерацию алгоритма, а $f$ нас обычно интересует лишь вида $f = id$.\n",
    "\n",
    "**Замечание:** мы также будем называть эргодическим средним выражение, стоящее под знаком предела.\n",
    "\n",
    "### Оптимизация\n",
    "\n",
    "Далее везде мы живём в пространстве $\\R^d$, если не сказано явно иного. Также мы закрепляем следующие обозначения:\n",
    "\n",
    "- $\\cX \\subseteq \\R^d$ за непустым замкнутым выпуклым подмножеством точек\n",
    "- $V \\colon \\R^d \\to \\R^d$ - некоторый оператор на нашем пространстве, чьи свойства мы будем уточнять по мере необходимости.\n",
    "\n",
    "**Определение:** *седловой точкой* дифференцируемой функции $f \\colon \\R^d \\to \\R^n$ называется критическая точка $f$, которая не является ни локальным минимумом, ни локальным максимумом $f$.\n",
    "\n",
    "**Определение:** Пусть $\\cX = \\Theta \\times \\Phi$, где $\\Theta \\subseteq \\R^{d_1}$ и $\\Phi \\subseteq \\R^{d_2}$. $\\cL(\\theta, \\phi)$ - дифференцируемая функция двух переменных с липшицевым градиентом. Тогда *min-max задачей* называется следующая задача оптимизации:\n",
    "$$\n",
    "    \\min_{\\theta \\in \\R^{d_1}} \\max_{\\phi \\in \\R^{d_2}} \\cL(\\theta, \\phi), \\text{ s.t. } \\theta \\in \\Theta \\wedge \\phi \\in \\Phi\n",
    "$$\n",
    "\n",
    "**Определение:** в min-max задаче, где $\\cL$ является выпукло-вогнутой функцией, имеет место *функция ошибки Никаидо-Исоды*:\n",
    "$$\n",
    "    NI(\\wdh{x}) := \\sup_{\\phi \\in \\Phi} \\cL(\\wdh{\\theta}, \\phi) - \\inf_{\\theta \\in \\Theta} \\cL(\\theta, \\wdh{\\phi})\n",
    "$$\n",
    "И также есть ограниченный вариант:\n",
    "$$\n",
    "    NI_R(\\wdh{x}) := \\max_{\\phi \\in \\Phi_R} \\cL(\\wdh{\\theta}, \\phi) - \\min_{\\theta \\in \\Theta_R} \\cL(\\theta, \\wdh{\\phi})\n",
    "$$\n",
    "где $\\Phi_R = \\{\\phi \\in \\Phi \\colon \\|\\phi\\| \\le R\\}$, $\\Theta_R = \\{\\theta \\in \\Theta \\colon \\|\\theta\\| \\le R\\}$\n",
    "\n",
    "**Определение:** оператор $V$ называется *монотонным*, если выполнено следующее условие:\n",
    "$$\n",
    "    \\forall x, x' \\in \\R^d\\ \\ \\tbr{V(x') - V(x), x' - x} \\ge 0\n",
    "$$\n",
    "\n",
    "**Интуиция:** вектор изменения значений $V$ сонаправлен с осью, задаваемой вектором $x' - x$. Для случая $V = \\nabla f$, где $f$ некоторая *достаточно гладкая* функция, выполнение условия эквивалентно тому, что $f$ выпукла\n",
    "\n",
    "**Определение:** оператор $V$ называется *$\\alpha$-строго монотонным*, если выполнено следующее условие:\n",
    "$$\n",
    "    \\exists \\alpha > 0 \\such \\forall x, x' \\in \\R^d\\ \\ \\tbr{V(x') - V(x), x' - x} \\ge \\alpha\\|x' - x\\|^2\n",
    "$$"
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   "source": [
    "## Основные цели\n",
    "- Обобщить уже имеющиеся результаты про 1-EG методы\n",
    "- Показать, что детерминированные 1-EG методы сохраняют оптимальный порядок сходимости $O(1 / t)$ в случае монотонного вариационного неравенства с липшицевостью.\n",
    "- Показать, что стохастические 1-EG методы сохраняют оптимальный порядок $O(1 / t)$ локальной сходимости (для последней итерации) в случае немонотонного вариационного неравенства\n",
    "\n",
    "<img src=\"assets/ArticleResults.png\" width=\"600\" height=\"600\">\n",
    "\n",
    "Обведённые результаты - то, что было получено в статье.\n",
    "\n",
    "**Замечание:** зачем изучать и эргодическую точку, и точку последней итерации алгоритма? Потому что первое хорошо работает в монотонном случае, а второе, соответственно, в немонотонном случае (когда, например, неприменимо неравенство Йенсена)"
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    "## Постановка задачи\n",
    "\n",
    "**Определение:** *вариационным неравенством (variational inequality, или просто VI)* называется задача поиска такого $x^* \\in \\cX$, что выполнено неравенство:\n",
    "$$\n",
    "    \\exists x^* \\in \\cX \\such \\forall x \\in \\cX\\ \\ \\tbr{V(x^*), x - x^*} \\ge 0\n",
    "$$\n",
    "\n",
    "**Интуиция к определению:** мы уже сталкивались с похожим неравенством, когда говорили о задаче минимизации выпуклой дифференцируемой функции $f$ на некотором выпуклом множестве $\\cX$. Тогда получалось, что $x^*$ - искомый минимум тогда и только тогда, когда выполнено неравенство:\n",
    "$$\n",
    "    \\forall x \\in \\cX \\tbr{\\nabla f(x^*), x - x^*} \\ge 0\n",
    "$$\n",
    "По сути это означает, что множество $\\cX$ лежит по одну сторону от гиперплоскости, которая задаётся своей точкой $x^*$ и нормалью $\\nabla f(x^*)$\n",
    "\n",
    "<img src=\"assets/FullConvexTheorem.png\" width=\"400\" height=\"400\">\n",
    "\n",
    "**Примеры:**\n",
    "\n",
    "1. Задача минимизации. Если $f$ - гладкая функция потерь на $\\cX = \\R^d$, то при $V = \\nabla f$ точка $x^*$ является решением вариационного неравенства тогда и только тогда, когда $\\nabla f(x^*) = 0$.\n",
    "\n",
    "2. Min-max оптимизация. Пусть $\\cX = \\Theta \\times \\Phi$, $\\Theta = \\R^{d_1}$ и $\\Phi = \\R^{d_2}$ и задана гладкая функция $L(\\theta, \\phi)$. Тогда задачу min-max оптимизации можно переписать в виде вариационного неравенства, используя $V(x) = (\\nabla_\\theta \\cL(x), -\\nabla_\\phi \\cL(x))$\n",
    "\n",
    "**Определение:** *функцией ошибки* для потенциального решения $\\wdh{x} \\in \\cX$ вариационного неравенства мы назовём следующую функцию:\n",
    "$$\n",
    "    \\Err(\\wdh{x}) = \\sup_{x \\in \\cX} \\tbr{V(x), \\wdh{x} - x}\n",
    "$$\n",
    "и её *ограниченный* вариант:\n",
    "$$\n",
    "    \\Err_R(\\wdh{x}) = \\max_{x \\in \\cX_R} \\tbr{V(x), \\wdh{x} - x}\n",
    "$$\n",
    "где $\\cX_R = \\cX \\cap \\ole{B}_R(0) = \\{x \\in \\cX \\colon \\|x\\| \\le R\\}$\n",
    "\n",
    "**Интуиция:** самая простая функция ошибки. Ровно говорит нам о том, насколько мы близко/далеко с желаемым неравенством с нулём.\n",
    "\n",
    "**Определение:** будем говорить, что решение вариационного неравенства $x^* \\in \\cX$ является *регулярным*, если выполнены условия:\n",
    "1. Оператор $V$ является $C^1$-гладким в окрестности $x^*$\n",
    "2. Якобиан $J_V(x^*)$ является положительно определённым относительно всех касательных направлений к $\\cX$ в точке $x^*$ (множество таких направлений обозначил за $Z_{\\cX, x^*}$):\n",
    "$$\n",
    "    \\forall z \\in Z_{\\cX, x^*} \\bs \\{0\\}\\ \\ z^TJ_V(x^*)z = \\sum_{i = 1}^d \\sum_{j = 1}^d z_i \\pd{V_i}{x_j}(x^*)z_j > 0\n",
    "$$\n",
    "\n",
    "**Интуиция:** эти условия соотносятся с требованиями на гессиан, если мы рассматриваем задачу $V = \\nabla f$"
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   "source": [
    "**Лемма (Нестеров, 2007):** пусть $V$ монотонна. Тогда $x^* \\in \\cX$ является решением вариационного неравенства тогда и только тогда, когда $\\Err(x^*) = 0$.\n",
    "\n",
    "Более того, так как $\\Err(x^*) = 0$ влечёт за собой $\\Err_R(x^*) = 0$ для достаточно большого $R > 0$, то наличие условия $\\Err_R(x^*) = 0$ также является достаточным для того, чтобы $x^* \\in \\cX_R$ было решением."
   ]
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   "source": [
    "## Теоретическая часть"
   ]
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   "source": [
    "**Допущение:** Далее мы столкнёмся с изучением *стохастических (случайных) алгоритмов*. Все они будут генерировать последовательности точек $X_t$ из пространства $\\cX$ (говоря явно, $X_t \\colon \\Omega \\to \\cX$, где $\\Omega$ относится к множеству исходов вероятностного пространства). Случайность возникает из-за использования *стохастического оракула*, чьё поведение мы моделируем так:\n",
    "$$\n",
    "    V_t = V(X_t) + Z_t\n",
    "$$\n",
    "где $Z_t \\in \\R^d$ - случайный шум. Если $\\cF_t$ - это натуральная фильтрация $X_t$, то мы допускаем следующие условия:\n",
    "1. $\\forall t\\ \\ \\E(Z_t | \\cF_t) = 0$\n",
    "\n",
    "2. $\\forall t\\ \\ \\E(\\|Z_t\\|^2| \\cF_t) \\le \\sigma^2$\n",
    "\n",
    "Понятно, что если $\\sigma^2 = 0$, то случайный процесс вырождается в детерминированный, всегда верно равенство $V_t = V(X_t)$. Далее мы будем использовать переменные случайных точек, но алгоритмы, описанные таким образом, естественно можно рассматривать как детерминированные."
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   "source": [
    "### Алгоритмы"
   ]
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    "**Экстра-градиентный спуск (Extra-Gradient algorithm):** (t + 1)-итерация для EG-алгоритма записывается следующим образом:\n",
    "$$\n",
    "    \\begin{aligned}\n",
    "        &{X_{t + 1 / 2} = \\Pi_\\cX(X_t - \\gamma_tV_t)}\n",
    "        \\\\\n",
    "        &{X_{t + 1} = \\Pi_\\cX(X_t - \\gamma_tV_{t + 1 / 2})}\n",
    "    \\end{aligned}\n",
    "$$\n",
    "где\n",
    "- $\\Pi_\\cX$ - обыкновенная евклидова проекция на $\\cX$: $\\Pi_\\cX(y) := \\arg \\min_{x \\in \\cX} \\|y - x\\|$\n",
    "- $\\gamma_t > 0$ - произвольно выбранный шаг итерации\n",
    "\n",
    "**Замечание:** отличие от обычного градиентного спуска состоит в том, что здесь мы находим *промежуточную точку (её ещё называют ведущей)* $X_{t + 1 / 2}$, а затем по информации в ней строим следующую *базовую точку* $X_t$, используя при этом один и тот же шаг $\\gamma_t$. В своей идее экстраградиентный метод крайне напоминает метод Нестерова.\n",
    "\n",
    "**Экстра-градиентный спуск с одним вызовом (оракула):** существуют разные способы убрать градиент из итерации. Так, в статье рассмотрены следующие 3 (они используют либо предыдущий, уже посчитанный градиент, либо аппроксимируют его через разность уже имеющихся $X_t$):\n",
    "1. Экстра-градиентный спуск по прошлому оракулу (Past Extra-Gradient, PEG):\n",
    "    $$\n",
    "        \\begin{aligned}\n",
    "            &{X_{t + 1 / 2} = \\Pi_\\cX(X_t - \\gamma_tV_{t - 1 / 2})}\n",
    "            \\\\\n",
    "            &{X_{t + 1} = \\Pi_\\cX(X_t - \\gamma_tV_{t + 1 / 2})}\n",
    "        \\end{aligned}\n",
    "    $$\n",
    "    \n",
    "    **Идея:** используем $V_{t - 1 / 2}$ вместо того, чтобы считать $V_t$ при вычислении $X_{t + 1 / 2}$\n",
    "\n",
    "2. Отражённый градиентный спуск (Reflected Gradient, RG):\n",
    "    $$\n",
    "        \\begin{aligned}\n",
    "            &{X_{t + 1 / 2} = X_t - (X_{t - 1} - X_t)}\n",
    "            \\\\\n",
    "            &{X_{t + 1} = \\Pi_\\cX(X_t - \\gamma_tV_{t + 1 / 2})}\n",
    "        \\end{aligned}\n",
    "    $$\n",
    "    \n",
    "    **Идея:** используем $\\frac{X_{t - 1} - X_t}{\\gamma_t}$ вместо $V_t$ и отказываемся от проекции при вычислении $X_{t + 1 / 2}$\n",
    "\n",
    "3. Оптимистичный градиентный спуск (Optimistic Gradient, OG):\n",
    "    $$\n",
    "        \\begin{aligned}\n",
    "            &{X_{t + 1 / 2} = \\Pi_\\cX(X_t - \\gamma_tV_{t - 1 / 2})}\n",
    "            \\\\\n",
    "            &{X_{t + 1} = X_{t + 1 / 2} + \\gamma_tV_{t - 1 / 2} - \\gamma_tV_{t + 1 / 2}}\n",
    "        \\end{aligned}\n",
    "    $$\n",
    "    \n",
    "    **Идея:** используем $V_{t - 1 / 2}$ вместо $V_t$ при вычислении $X_{t + 1 / 2}$. Используем $X_{t + 1 / 2} + \\gamma_tV_{t - 1 / 2}$ вместо $X_t$ и отказываемся от проекции при вычислении $X_{t + 1}$\n",
    "    \n",
    "Далее, чтобы говорить об этих методах сразу, мы будем называть их *1-EG методами* или *1-EG алгоритмами*"
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   },
   "source": [
    "**Утверждение:** если все 1-EG детерминированные методы имеют одинаковые стартовые значения $X_0 = X_1 \\in \\cX$, $V_{1 / 2} = 0$ и запускаются с постоянным шагом $\\gamma_t = \\gamma$, то в случае $\\cX = \\R^d$ точки $X_t$ на каждой итерации у всех 1-EG совпадают."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6a95c6ad",
   "metadata": {
    "id": "6a95c6ad"
   },
   "source": [
    "**Доказательство:** индукция по $t$. Отметим, что коль скоро $\\cX = \\R^d$, то оператор проекции является просто тождественным, его можно не писать:\n",
    "- База индукции $t \\le 2$:\n",
    "    - PEG:\n",
    "    $$\n",
    "        \\begin{aligned}\n",
    "            &{X_{3 / 2} = X_1 - \\gamma V_{1 / 2} = X_0}\n",
    "            \\\\\n",
    "            &{X_2 = X_1 - \\gamma V_{3 / 2}}\n",
    "        \\end{aligned}\n",
    "    $$\n",
    "    - RG:\n",
    "    $$\n",
    "        \\begin{aligned}\n",
    "            &{X_{3 / 2} = X_1 - (X_0 - X_1) = X_1 = X_0}\n",
    "            \\\\\n",
    "            &{X_2 = X_1 - \\gamma V_{3 / 2}}\n",
    "        \\end{aligned}\n",
    "    $$\n",
    "    - OG:\n",
    "    $$\n",
    "        \\begin{aligned}\n",
    "            &{X_{3 / 2} = X_1 - \\gamma V_{1 / 2} = X_0}\n",
    "            \\\\\n",
    "            &{X_2 = X_{3 / 2} + \\gamma V_{1 / 2} - \\gamma V_{3 / 2} = X_1 - \\gamma V_{3 / 2}}\n",
    "        \\end{aligned}\n",
    "    $$\n",
    "- Переход $t > 2$: покажем, что правила приводятся к одинаковому виду, тем самым точки получатся одинаковые.\n",
    "    - PEG:\n",
    "      $$\n",
    "          \\begin{aligned}\n",
    "              &{X_{t + 1 / 2} = X_t - \\gamma V_{t - 1 / 2}}\n",
    "              \\\\\n",
    "              &{X_{t + 1} = X_t - \\gamma V_{t + 1 / 2}}\n",
    "          \\end{aligned}\n",
    "      $$\n",
    "    - RG:\n",
    "      $$\n",
    "          \\begin{aligned}\n",
    "              &{X_{t + 1 / 2} = X_t - (X_{t - 1} - X_t)}\n",
    "              \\\\\n",
    "              &{X_{t + 1} = X_t - \\gamma V_{t + 1 / 2}}\n",
    "          \\end{aligned}\n",
    "      $$\n",
    "      Преобразуем первое правило. Для этого распишем $X_t$ через второе правило:\n",
    "      $$\n",
    "          X_t = X_{t - 1} - \\gamma V_{t - 1 + 1 / 2} = X_{t - 1} - \\gamma V_{t - 1 / 2} \\Lora X_{t - 1} - X_t = \\gamma V_{t - 1 / 2}\n",
    "      $$\n",
    "      Подстановка тривиально делает первое правило RG таким же, как и у PEG'а\n",
    "    - OG:\n",
    "      $$\n",
    "          \\begin{aligned}\n",
    "              &{X_{t + 1 / 2} = X_t - \\gamma V_{t - 1 / 2} \\Lora X_{t + 1 / 2} + \\gamma V_{t - 1 / 2} = X_t}\n",
    "              \\\\\n",
    "              &{X_{t + 1} = X_{t + 1 / 2} + \\gamma V_{t - 1 / 2} - \\gamma V_{t + 1 / 2} \\Lora X_{t + 1} = X_t - \\gamma V_{t + 1 / 2}}\n",
    "          \\end{aligned}\n",
    "      $$"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a8b13fd8",
   "metadata": {
    "id": "a8b13fd8"
   },
   "source": [
    "### Технические леммы"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d6829346",
   "metadata": {
    "id": "d6829346"
   },
   "source": [
    "**Замечание:** дальше будет довольно удобно использовать нотацию для подстановки переменных. Так, выражение $(x_1, \\ldots, x_n) \\la (y_1, \\ldots, y_n)$ означает подстановку вместо переменных $x_1, \\ldots, x_n$ переменные $y_1, \\ldots, y_n$."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bf4fa311",
   "metadata": {
    "id": "bf4fa311"
   },
   "source": [
    "**Техлемма 0:** имеет место так называемое *неравенство Юнга*:\n",
    "$$\n",
    "    \\forall x, y \\in \\R^d\\ \\ 2\\tbr{x, y} \\le \\|x\\|^2 + \\|y\\|^2\n",
    "$$"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e1d6a992",
   "metadata": {
    "id": "e1d6a992"
   },
   "source": [
    "**Доказательство:** заметим, что если перенести всё направо, то получим $\\|x - y\\|^2 \\ge 0$"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8926e960",
   "metadata": {
    "id": "8926e960"
   },
   "source": [
    "**Следствие:** верно неравенство $\\forall x, y \\in \\R^d\\ \\ \\|x + y\\|^2 \\le 2\\|x\\|^2 + 2\\|y\\|^2$"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "35ecb89b",
   "metadata": {
    "id": "35ecb89b"
   },
   "source": [
    "**Техлемма 1:** пусть $x, y \\in \\R^d$ и $\\cC \\subseteq \\R^d$ - замкнутое выпуклое множество. Определим $x^+ := \\Pi_\\cC(x - y)$. Тогда верно следующее неравенство:\n",
    "$$\n",
    "    \\forall p \\in \\cC\\ \\ \\|x^+ - p\\|^2 \\le \\|x - p\\|^2 - 2\\tbr{y, x^+ - p} - \\|x^+ - x\\|^2\n",
    "$$"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "78b0ec3b",
   "metadata": {
    "id": "78b0ec3b"
   },
   "source": [
    "**Доказательство:** распишем величину слева в неравенстве:\n",
    "$$\n",
    "    \\begin{aligned}\n",
    "        &\\|x^+ - p\\|^2 = \\|x^+ - x + x - p\\|^2 =\n",
    "        \\\\\n",
    "        &\\|x - p\\|^2 + 2\\tbr{x^+ - x, x - p} + \\|x^+ - x\\|^2 =\n",
    "        \\\\\n",
    "        &\\|x - p\\|^2 + 2\\tbr{x^+ - x, x^+ - p} + \\|x^+ - x\\|^2\n",
    "    \\end{aligned}\n",
    "$$\n",
    "Проекция, как известно, обладает хорошим свойством на скалярное произведение: $\\tbr{x^+ - (x - y), x^+ - p} \\le 0$. Из этого неравенства выражаем то скалярное произведение, что наисано выше и тривиально получаем требуемое."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f5744074",
   "metadata": {
    "id": "f5744074"
   },
   "source": [
    "**Техлемма 2:** пусть $x, y_1, y_2 \\in \\R^d$ и $\\cC_1, \\cC_2 \\subseteq \\R^d$ - замкнутые выпуклые множества. Определим $x_i^+ := \\Pi_{\\cC_i}(x - y_i)$. Имеет место два факта:\n",
    "\n",
    "1. Если $\\cC_2 = \\R^d$, то\n",
    "   $$\n",
    "       \\forall p \\in \\R^d\\ \\ \\|x_2^+ - p\\|^2 = \\|x - p\\|^2 - 2\\tbr{y_2, x_1^+ - p} + \\|x_2^+ - x_1^+\\|^2 - \\|x_1^+ - x\\|^2\n",
    "   $$\n",
    "   \n",
    "2. Если $\\cC_2 \\subseteq \\cC_1$, то\n",
    "   $$\n",
    "       \\begin{aligned}\n",
    "           \\forall p \\in \\cC_2\\ \\ \\|x_2^+ - p\\|^2 &\\le \\|x - p\\|^2 - 2\\tbr{y_2, x_1^+ - p} + 2\\tbr{y_2 - y_1, x_1^+ - x_2^+} - \\|x_2^+ - x_1^+\\|^2 - \\|x_1^+ - x\\|^2\n",
    "           \\\\\n",
    "           &\\le \\|x - p\\|^2 - 2\\tbr{y_2, x_1^+ - p} + \\|y_2 - y_1\\|^2 - \\|x_1^+ - x\\|^2\n",
    "       \\end{aligned}\n",
    "   $$"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "56cc1417",
   "metadata": {
    "id": "56cc1417"
   },
   "source": [
    "**Доказательство:**\n",
    "\n",
    "1. Воспользуемся той же схемой доказательства, что и в Техлемме 1: просто распишем левую часть:\n",
    "\n",
    "   $$\n",
    "       \\begin{aligned}\n",
    "           \\|x_2^+ - p\\|^2 &= \\|x_2^+ - x_1^+ + x_1^+ - x + x - p\\|^2\n",
    "           \\\\\n",
    "           &[\\text{через скал. произв.}]= \\|x_2^+ - x_1^+\\|^2 + \\|x_1^+ - x\\|^2 + \\|x - p\\|^2 + 2\\tbr{x_2^+ - x_1^+, x_1^+ - p} + 2\\tbr{x^+ - x, x - p}\n",
    "           \\\\\n",
    "           &[\\text{переход к проекции в конце}]= \\|x_2^+ - x_1^+\\|^2 - \\|x_1^+ - x\\|^2 + \\|x - p\\|^2 + 2\\tbr{x_2^+ - x_1^+, x_1^+ - p} + 2\\tbr{x_1^+ - x, x_1^+ - p}\n",
    "           \\\\\n",
    "           &= \\|x - p\\|^2 - 2\\tbr{y_2, x_1^+ - p} + \\|x_2^+ - x_1^+\\|^2 - \\|x_1^+ - x\\|^2\n",
    "       \\end{aligned}\n",
    "   $$\n",
    "   \n",
    "   Равенство в 4й строке достигнуто за счёт того, что мы воспользовались преобразованием:\n",
    "   \n",
    "   $$\n",
    "       \\tbr{x^+ - x, x - p} = \\tbr{x^+ - x, x - x^+ + x^+ - p} = \\tbr{x^+ - x, x^+ - p} - \\|x^+ - x\\|^2\n",
    "   $$\n",
    "   \n",
    "   А последнее равенство достигнуто при помощи $x_2^+ - x = -y_2$, коль скоро $\\cC_2 = \\R^d$\n",
    "   \n",
    "2. За счёт вложенности множеств, имеем $x_2^+ \\in \\cC_2 \\subseteq \\cC_1$. Значит, мы можем воспользоваться результатом Техлеммы 1 с подстановкой $(x, y, x^+, p, \\cC) \\la (x, y_1, x_1^+, x_2^+ \\cC_1)$. Вместе с другой подстановкой $(x, y, x^+, p, \\cC) \\la (x, y_2, x_2^+, p, \\cC_2)$ вначале это даёт 2 неравенства:\n",
    "\n",
    "   $$\n",
    "       \\begin{aligned}\n",
    "           \\|x_1^+ - x_2^+\\|^2 &\\le \\|x - x_2^+\\|^2 - 2\\tbr{y_1, x_1^+ - x_2^+} - \\|x_1^+ - x\\|^2\n",
    "           \\\\\n",
    "           \\|x_2^+ - p\\|^2 &\\le \\|x - p\\|^2 - 2\\tbr{y_2, x_2^+ - p} - \\|x_2^+ - x\\|^2\n",
    "       \\end{aligned}\n",
    "   $$\n",
    "   \n",
    "   Если их сложить и перенести $\\|x_1^+ - x_2^+\\|^2$ в правую часть, то мы получаем в первое из неравенств пункта (по модулю того, что скалярные произведения нужно перегруппировать). Чтобы из него получить второе, нужно воспользоваться простеньким неравенством из неотрицательности нормы $\\|y_2 - y_1 + x_1^+ - x_2^+\\|^2 \\ge 0$:\n",
    "   \n",
    "   $$\n",
    "       2\\tbr{y_2 - y_1, x_1^+ - x_2^+} \\le \\|y_2 - y_1\\|^2 + \\|x_1^+ - x_2^+\\|^2\n",
    "   $$"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7c4846c6",
   "metadata": {
    "id": "7c4846c6"
   },
   "source": [
    "**Техлемма 3:** пусть $\\{a_t\\}_{t = 1}^\\infty \\subset \\R$ и $b, t_0 \\in \\N$ таковы, что выполнено рекурсивное неравенство:\n",
    "$$\n",
    "    \\exists q > 1, q' > 0 \\such \\forall t \\ge t_0\\; a_{t + 1} \\le \\ps{1 - \\frac{q}{t + b}}a_t + \\frac{q'}{(t + b)^2}\n",
    "$$\n",
    "Тогда рекурсивное неравенство можно развернуть в следующее:\n",
    "$$\n",
    "    a_t \\le \\frac{q'}{q - 1} \\cdot \\frac{1}{t} + o\\ps{\\frac{1}{t}}\n",
    "$$"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "269e9e58",
   "metadata": {
    "id": "269e9e58"
   },
   "source": [
    "**Доказательство:** для начала покажем, что мы можем к изучению такой $a'_t \\le a_t$, что выполнено то же неравенство из условия, но без крайнего слагаемого:\n",
    "$$\n",
    "    \\forall t \\ge t_0\\; a'_{t + 1} \\le \\ps{1 - \\frac{q}{t + b}}a'_t\n",
    "$$\n",
    "**Далее идёт слишком синтетическое утверждение, посему доказательство прерывается**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "32bc5dc9",
   "metadata": {
    "id": "32bc5dc9"
   },
   "source": [
    "**Техлемма 4:** пусть $x^*$ - регулярное решение вариационного неравенства. Тогда, существуют константы $r, \\alpha, \\beta > 0$ такие, что выполнены свойства:\n",
    "- $V$ является $\\beta$-липшицевым на $K = \\ole{B}_r(x^*)$\n",
    "- $\\forall x \\in U := \\cX \\cap K\\ \\ \\tbr{V(x), x - x^*} \\ge \\alpha\\|x - x^*\\|^2$ ($V$ является $\\alpha$-строго монотонным в $U$)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e9ce63b4",
   "metadata": {
    "id": "e9ce63b4"
   },
   "source": [
    "**Доказательство:** существование окрестности, где $V$ является $\\beta$-липшицевым тривиально в силу того, что $V$ является $C^1$-гладкой функцией (а значит на компакте мы нужную константу найдём). Остаётся лишь найти $\\alpha$. Пусть $TC_\\cX(x^*)$ обозначает конус касательных направлений к $\\cX$ в точке $x^*$. Рассмотрим следующую функцию $\\phi \\colon \\R^{d \\times d} \\to \\R$:\n",
    "\n",
    "$$\n",
    "    \\phi(G) = \\min_{z \\in TC_\\cX(x^*) \\wedge \\|z\\| = 1} z^TGz\n",
    "$$\n",
    "\n",
    "Эта функция является выпуклой вверх, коль скоро представляет собой минимум от множества функций, линейных по тому же аргументу:\n",
    "\n",
    "$$\n",
    "    \\phi(\\theta G_1 + (1 - \\theta) G_2) = \\min_{z \\in TC_\\cX(x^*) \\wedge \\|z\\| = 1} \\underbrace{z^T(\\theta G_1 + (1 - \\theta) G_2)z}_{\\theta z^TG_1z + (1 - \\theta) z^TG_2z} \\ge \\theta \\phi(G_1) + (1 - \\theta) \\phi(G_2)\n",
    "$$\n",
    "\n",
    "В свою очередь, из-за этого факта $\\phi$ является непрерывной на внутренности своей эффективной области определения. В силу регулярности решения, $\\phi(J_V(x^*)) > 0$, а композиция $\\phi \\circ J_V$ непрерывна. Стало быть, можно найти $r, \\alpha > 0$ через поиск оценки $\\phi(J_V(x)) \\ge \\alpha$ для всех $x \\in U$. Итак, распишем разность значений $V$ через интеграл по якобиану (интеграл матрицы нужно понимать поэлементно):\n",
    "\n",
    "$$\n",
    "    V(x) - V(x^*) = \\ps{\\int_0^1 J_V\\big(x^* + \\lambda(x - x^*)\\big)d\\lambda}(x - x^*)\n",
    "$$\n",
    "\n",
    "Для упрощения вводим обозначения $z = x - x^* \\in TC_\\cX(x^*)$, $x_\\lambda = x^* + \\lambda(x - x^*) \\in K$. Тогда, взяв скалярное произведение с $z$ с обеих сторон, имеем:\n",
    "\n",
    "$$\n",
    "    \\begin{aligned}\n",
    "        \\tbr{V(x) - V(x^*), z} &= \\tbr{V(x) - V(x^*), x - x^*} = z^T\\ps{\\int_0^1 J_V(x_\\lambda)d\\lambda}z\n",
    "        \\\\\n",
    "        &\\ge \\ps{\\int_0^1 \\phi(J_V(x_\\lambda))d\\lambda}\\|z\\|^2 \\ge \\alpha\\|z\\|^2 = \\alpha\\|x - x^*\\|^2\n",
    "    \\end{aligned}\n",
    "$$\n",
    "\n",
    "Наконец, пользуемся тем, что $x^*$ является решением, а значит $\\tbr{V(x^*), x - x^*} \\ge 0$ и верна цепочка неравенств:\n",
    "\n",
    "$$\n",
    "    \\tbr{V(x), x - x^*} \\ge \\tbr{V(x) - V(x^*), x - x^*} \\ge \\alpha\\|x - x^*\\|^2\n",
    "$$"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "442bd5f4",
   "metadata": {
    "id": "442bd5f4"
   },
   "source": [
    "### Анализ детерминированного случая"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f1cfbac2",
   "metadata": {
    "id": "f1cfbac2"
   },
   "source": [
    "Как и было обговорено ранее, мы считаем детерминированный случай просто вырожденным случаем для стохастического, где $\\sigma = 0$."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "34f97028",
   "metadata": {
    "id": "34f97028"
   },
   "source": [
    "#### Эргодическое среднее"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dd13e8aa",
   "metadata": {
    "id": "dd13e8aa"
   },
   "source": [
    "**Теорема о глобальной сходимости (для эргодического среднего):** пусть вариационная задача удовлетворяет условиям:\n",
    "1. $\\cX^* \\neq \\emptyset$ - множество решений вариационного неравенства непусто\n",
    "2. $V$ является $\\beta$-липшицевым оператором\n",
    "3. $V$ является монотонным оператором\n",
    "\n",
    "Если рассмотреть 1-EG метод с постоянным шагом $\\gamma < 1 / (c\\beta)$ (где $c = 1 + \\sqrt{2}$ для RG и $c = 2$ для PEG, OG). Тогда имеет место неравенство:\n",
    "\n",
    "$$\n",
    "    \\forall R > 0\\ \\ \\Err_R\\big(\\ole{X}_t\\big) \\le \\frac{1}{t} \\cdot \\frac{R^2 + \\|X_1 - X_{1 / 2}\\|^2}{2\\gamma}\n",
    "$$\n",
    "\n",
    "где в определении $\\Err_R$ берётся $\\cX_R = \\cX \\cap \\ole{B}_R(X_1)$, а также $\\ole{X}_t = \\frac{1}{t}\\sum_{s = 1}^t X_{s + 1 / 2}$ - эргодическое среднее по ведущим точкам"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "de01d9f0",
   "metadata": {
    "id": "de01d9f0"
   },
   "source": [
    "**Лемма:** если $V$ является монотонным оператором и удовлетворяет следующему неравенству:\n",
    "$$\n",
    "    \\exists \\mu_s, \\lambda_s \\ge 0 \\such \\forall p \\in \\cX_R, s \\in \\range{1}{t}\\; \\|X_{s + 1} - p\\|^2 \\le \\|X_s - p\\|^2 - 2\\lambda_s\\tbr{V(X_{s + 1 / 2}), X_{s + 1 / 2} - p} + \\mu_s - \\mu_{s + 1}\n",
    "$$\n",
    "где $\\cX_R = \\cX \\cap \\ole{B}_R(X_1)$. Тогда имеет место следующее неравенство для ошибки:\n",
    "$$\n",
    "    \\Err_R \\ps{\\ole{X}} \\le \\frac{R^2 + \\mu_1}{2\\sum_{s = 1}^t \\lambda_s}\n",
    "$$\n",
    "где $\\ole{X} = \\frac{\\sum_{s = 1}^t \\lambda_sX_{s + 1 / 2}}{\\sum_{s = 1}^t \\lambda_s}$ - средневзвешенное ведущих точек $X_{s + 1 / 2}$ по весам $\\lambda_s$"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d3a7a298",
   "metadata": {
    "id": "d3a7a298"
   },
   "source": [
    "**Доказательство леммы:** как и во многих других случаях с эргодическим средним, мы будем делать телескопическую сумму, в чём нам особенно хорошо помогает тот объект, который дан в условии. Перенесём скалярное произведение в левую сторону и просуммируем:\n",
    "\n",
    "$$\n",
    "    \\sum_{s = 1}^t 2\\lambda_s\\tbr{V(X_{s + 1 / 2}), X_{s + 1 / 2} - p} \\le \\|X_1 - p\\|^2 - \\|X_{t + 1} - p\\|^2 + \\mu_1 - \\mu_{t + 1} \\le \\|X_1 - p\\|^2 + \\mu_1\n",
    "$$\n",
    "\n",
    "Согласно условию, $p \\in \\cX_R = \\cX \\cap \\ole{B}_R(X_1)$, а значит автоматически $\\|X_1 - p\\|^2 \\le R^2$. Более того, по монотонности $V$ мы можем преобразовать сумму слева:\n",
    "\n",
    "$$\n",
    "    \\tbr{V(X_{s + 1 / 2}) - V(p), X_{s + 1 / 2} - p} \\ge 0 \\Lora \\tbr{V(p), X_{s + 1 / 2} - p} \\le \\tbr{V(X_{s + 1 / 2}), X_{s + 1 / 2} - p}\n",
    "$$\n",
    "\n",
    "Теперь соберём всё вместе:\n",
    "\n",
    "$$\n",
    "    \\sum_{s = 1}^t 2\\lambda_s\\tbr{V(p), X_{s + 1 / 2} - p} \\le R^2 + \\mu_1\n",
    "$$\n",
    "\n",
    "Поделим обе стороны на 2, занесём сумму под скалярное произведение, а также поделим на $\\sum_{s = 1}^t \\lambda_s$:\n",
    "\n",
    "$$\n",
    "    \\tbr{V(p), \\frac{\\sum_{s = 1}^t \\lambda_sX_{s + 1 / 2}}{\\sum_{s = 1}^t \\lambda_s} - p} \\le \\frac{R^2 + \\mu_1}{2\\sum_{s = 1}^t \\lambda_s}\n",
    "$$\n",
    "\n",
    "Максимизация по $p$ приводит значение левой части к значению $\\Err_R$ с соответствующим аргументом."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "61e7d0c4",
   "metadata": {
    "id": "61e7d0c4"
   },
   "source": [
    "**Доказательство теоремы:** вся идея состоит в том, чтобы свести по отдельности PEG, OG и RG к доказанной лемме. Нужно отметить, что мы будем требовать для PEG и OG инициализацию с любым $X_{1 / 2}$ и $X_1 \\in \\cX$, в то время как для RG всё начиинается точек $X_0$ и $X_{1 / 2}$. К сожалению, каждый метод нужно сводить отдельно:\n",
    "\n",
    "- **PEG.**\n",
    "  1. (Подстановка параметров во 2е неравенство Техлеммы 2, использование липшцевости $V$) При $t \\ge 1$ мы можем воспользоваться неравенствами Техлеммы 2 с подстановкой $(x, y_1, y_2, x_1^+, x_2^+, \\cC_1, \\cC_2) \\la (X_t, \\gamma V(X_{t - 1 / 2}), \\gamma V(X_{t + 1 / 2}), X_{t + 1 / 2}, X_{t + 1}, \\cX, \\cX)$:\n",
    "  \n",
    "  $$\n",
    "      \\|X_{t + 1} - p\\|^2 \\le \\|X_t - p\\|^2 - 2\\gamma\\tbr{V(X_{t + 1 / 2}), X_{t + 1 / 2} - p} + \\gamma^2\\|V(X_{t + 1 / 2}) - V(X_{t - 1 / 2})\\|^2 - \\|X_{t + 1 / 2} - X_t\\|^2\n",
    "  $$\n",
    "  \n",
    "  Можем перейти от нормы разности с $V$ к норме разности аргументов в силу $\\beta$-липшицевости:\n",
    "  $$\n",
    "      \\|X_{t + 1} - p\\|^2 \\le \\|X_t - p\\|^2 - 2\\gamma\\tbr{V(X_{t + 1 / 2}), X_{t + 1 / 2} - p} + \\gamma^2\\beta^2\\|X_{t + 1 / 2} - X_{t - 1 / 2}\\|^2 - \\|X_{t + 1 / 2} - X_t\\|^2\n",
    "  $$\n",
    "  \n",
    "  2. (За счёт неравенства Юнга и свойства нерасширяемости проекции получить неравенство на норму одного слагаемого из первого пункта) Сведём последние 2 слагаемых так, чтобы получить $\\mu_s - \\mu_{s + 1}$ согласно лемме. Идея в том, что предпоследнее слагаемое можно оценить так, что при заданной оценке $\\gamma < 1/(2\\beta)$ оно уберёт последнее, останется только нужная разность каких-то величин. Итак, по следствию неравенства Юнга:\n",
    "  \n",
    "  $$\n",
    "      \\|X_{t + 1 / 2} - X_{t - 1 / 2}\\|^2 \\le 2\\|X_{t + 1 / 2} - X_t\\|^2 + 2\\|X_t - X_{t - 1 / 2}\\|^2\n",
    "  $$\n",
    "  \n",
    "  Через свойство нерасширяемости проекции оцениваем первую норму (это работает только при $t \\ge 2$! Случай $t = 1$ разберём отдельно):\n",
    "  \n",
    "  $$\n",
    "      \\begin{aligned}\n",
    "          \\|X_t - X_{t - 1 / 2}\\|^2 &\\le \\Big\\|\\big(X_{t - 1} - \\gamma V(X_{t - 1 / 2})\\big) - \\big(X_{t - 1} - \\gamma V(X_{t - 3 / 2})\\big)\\Big\\|^2 = \\gamma^2\\|V(X_{t - 3 / 2}) - V(X_{t - 1 / 2})\\|^2\n",
    "          \\\\\n",
    "          &\\le [\\text{Lipschitz}] \\le \\gamma^2\\beta^2\\|X_{t - 1 / 2} - X_{t - 3 / 2}\\|^2\n",
    "      \\end{aligned}\n",
    "  $$\n",
    "  \n",
    "  Теперь соберём всё вместе *и учтём, что по условию $\\gamma\\beta < 1 / 2$*. Маленькое наравенство:\n",
    "  \n",
    "  $$\n",
    "      \\|X_{t + 1 / 2} - X_{t - 1 / 2}\\|^2 \\le 2\\|X_{t + 1 / 2} - X_t\\|^2 + \\frac{1}{2}\\|X_{t - 1 / 2} - X_{t - 3 / 2}\\|^2\n",
    "  $$\n",
    "  \n",
    "  Если мы подставим это выражение в таком виде в основное неравенство, то заветного сокращения не будет. Схитрим, ведь $a = 2a - a$:\n",
    "  \n",
    "  $$\n",
    "      \\|X_{t + 1 / 2} - X_{t - 1 / 2}\\|^2 \\le 4\\|X_{t + 1 / 2} - X_t\\|^2 + \\|X_{t - 1 / 2} - X_{t - 3 / 2}\\|^2 - \\|X_{t + 1 / 2} - X_{t - 1 / 2}\\|^2\n",
    "  $$\n",
    "  \n",
    "  Ну и теперь подстановка в главное неравенство ($4\\gamma^2\\beta^2 < 4 \\cdot (1 / 4) = 1$):\n",
    "  \n",
    "  $$\n",
    "      \\begin{aligned}\n",
    "          \\|X_{t + 1} - p\\|^2 &\\le \\|X_t - p\\|^2 - 2\\gamma\\tbr{V(X_{t + 1 / 2}), X_{t + 1 / 2} - p}\n",
    "          \\\\\n",
    "          &+ \\gamma^2\\beta^2\\Big(4\\|X_{t + 1 / 2} - X_t\\|^2 + \\|X_{t - 1 / 2} - X_{t - 3 / 2}\\|^2 - \\|X_{t + 1 / 2} - X_{t - 1 / 2}\\|^2\\Big) - \\|X_{t + 1 / 2} - X_t\\|^2\n",
    "          \\\\\n",
    "          &\\le \\|X_t - p\\|^2 - 2\\gamma\\tbr{V(X_{t + 1 / 2}), X_{t + 1 / 2} - p} + \\underbrace{\\gamma^2\\beta^2\\|X_{t - 1 / 2} - X_{t - 3 / 2}\\|^2}_{\\mu_t} - \\underbrace{\\gamma^2\\beta^2\\|X_{t + 1 / 2} - X_{t - 1 / 2}\\|^2}_{\\mu_{t + 1}}\n",
    "      \\end{aligned}\n",
    "  $$\n",
    "  \n",
    "  При указанных $\\mu_t$ и $\\lambda_t = \\gamma$, получаем выполнение условий леммы при $t \\ge 2$. Случай $t = 1$ нужно разобрать, ибо там участвует уже определённое $\\mu_2$, а значит надо корректно определить $\\mu_1$. Берём эти последние 2 слагаемых и действуем уже имеющимися неравенствами:\n",
    "  \n",
    "  $$\n",
    "      \\begin{aligned}\n",
    "          \\gamma^2\\beta^2\\|X_{3 / 2} - X_{1 / 2}\\|^2 - \\|X_{3 / 2} - X_1\\|^2 &\\le [\\text{Young and trick}]\n",
    "          \\\\\n",
    "          &\\le \\gamma^2\\beta^2\\Big(2\\big(2\\|X_{3 / 2} - X_1\\|^2 + 2\\|X_1 - X_{1 / 2}\\|^2\\big) - \\|X_{3 / 2} - X_{1 / 2}\\|^2\\Big) - \\|X_{3 / 2} - X_1\\|^2\n",
    "          \\\\\n",
    "          &\\le \\underbrace{4\\gamma^2\\beta^2\\|X_1 - X_{1 / 2}\\|^2}_{\\mu_1} - \\underbrace{\\gamma^2\\beta^2\\|X_{3 / 2} - X_{1 / 2}\\|^2}_{\\mu_2}\n",
    "      \\end{aligned}\n",
    "  $$\n",
    "  \n",
    "  Отсюда $\\mu_1 = 4\\gamma^2\\beta^2\\|X_1 - X_{1 / 2}\\|^2 \\le \\|X_1 - X_{1 / 2}\\|^2$. Подстановка всех величин в лемму даёт искомый результат.\n",
    "\n",
    "- **OG.**\n",
    "  1. Подстановка параметров в 1е неравенство Техлеммы 2\n",
    "  2. Подставив неравенства из свойства разделения проекции, липшицевости $V$ и того же неравенства Юнга в первый пункт, получить искомое неравенство\n",
    "\n",
    "- **RG.**\n",
    "  1. Подстановка параметров в 2е неравенство Техлеммы 2\n",
    "  2. Увидеть 2 неравенства из свойства разделения проекции, просуммировать их.\n",
    "  3. Сделать оценку на единственное скалярное произведение из пункта 1, собрать это воедино\n",
    "  4. Дважды неравенство Юнга для произведения модулей из третьего пункта. Собрать воедино"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2545b646",
   "metadata": {
    "id": "2545b646"
   },
   "source": [
    "**Улучшение леммы в задачах минизации и min-max**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "61c09592",
   "metadata": {
    "id": "61c09592"
   },
   "source": [
    "Лемма 2 может быть улучшена для конкретных задач: получаются другие функции ошибок, которые могут лучше отражать специфику задачи."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9f7d1553",
   "metadata": {
    "id": "9f7d1553"
   },
   "source": [
    "**Задача минимизации:** $V = \\nabla f$. В силу монотонности $V$ по условию, сама $f$ является выпуклой. Отсюда для любой точки $p \\in \\cX$ по неравенству Йенсена получаем:\n",
    "\n",
    "$$\n",
    "    \\tbr{V(X_{s + 1 / 2}), X_{s + 1 / 2} - p} = \\tbr{\\nabla f(X_{s + 1 / 2}), X_{s + 1 / 2} - p} \\ge f(X_{s + 1 / 2}) - f(p)\n",
    "$$\n",
    "\n",
    "Объединив это с рассматриваемым средневзвешенным в лемме, получим следующее:\n",
    "\n",
    "$$\n",
    "    \\frac{1}{\\sum_{s = 1}^t \\lambda_s} \\sum_{s = 1}^t \\lambda_s \\tbr{V(X_{s + 1 / 2}), X_{s + 1 / 2} - p} \\ge \\frac{1}{\\sum_{s = 1}^t \\lambda_s} \\sum_{s = 1}^t \\lambda_s f(X_{s + 1 / 2}) - f(p) \\ge f(\\ole{X}) - f(p)\n",
    "$$\n",
    "\n",
    "Применим это неравенство к $p \\in \\cX^*$. Тогда, используя первое неравенство из доказательства леммы с $R = \\rho(X_1, \\cX^*)$, мы получаем следующий результат:\n",
    "\n",
    "$$\n",
    "    f(\\ole{X}) - f^* \\le \\frac{R^2 + \\mu_1}{2\\sum_{s = 1}^t \\lambda_s}\n",
    "$$"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "29a13411",
   "metadata": {
    "id": "29a13411"
   },
   "source": [
    "**Задача min-max:** $V = (\\nabla_\\theta \\cL, -\\nabla_\\phi \\cL)$. Монотонность такой $V$ эквивалентна тому, что $\\cL$ является выпуклой по $\\theta$ и вогнутой по $\\phi$. Обозначим $X_{s + 1 / 2} = (\\theta_{s + 1 / 2}, \\phi_{s + 1 / 2})$ и $p = (\\theta, \\phi)$. За счёт уже упомянутой выпуклости-вогнутости $\\cL$, мы получаем следующее неравенство:\n",
    "\n",
    "$$\n",
    "    \\begin{aligned}\n",
    "        \\tbr{V(X_{s + 1 / 2}), X_{s + 1 / 2} - p} &= \\tbr{\\nabla_\\theta \\cL(\\theta_{s + 1 / 2}, \\phi_{s + 1 / 2}), \\theta_{s + 1 / 2} - \\theta} - \\tbr{\\nabla_\\phi \\cL(\\theta_{s + 1 / 2}, \\phi_{s + 1 / 2}), \\phi_{s + 1 / 2} - \\phi}\n",
    "        \\\\\n",
    "        &\\ge \\cL(\\theta_{s + 1 / 2}, \\phi_{s + 1 / 2}) - \\cL(\\theta, \\phi_{s + 1 / 2}) + \\cL(\\theta_{s + 1 / 2}, \\phi) - \\cL(\\theta_{s + 1 / 2}, \\phi_{s + 1 / 2})\n",
    "        \\\\\n",
    "        &= \\cL(\\theta_{s + 1 / 2}, \\phi) - \\cL(\\theta, \\phi_{s + 1 / 2})\n",
    "    \\end{aligned}\n",
    "$$\n",
    "\n",
    "Как и ранее, теперь мы объединяем это со средневзвешенным (тут $\\ole{X} = (\\ole{\\theta}, \\ole{\\phi})$):\n",
    "\n",
    "$$\n",
    "    \\frac{1}{\\sum_{s = 1}^t \\lambda_s} \\sum_{s = 1}^t \\lambda_s \\tbr{V(X_{s + 1 / 2}), X_{s + 1 / 2} - p} \\ge \\cL(\\ole{\\theta}, \\phi) - \\cL(\\theta, \\ole{\\phi})\n",
    "$$\n",
    "\n",
    "Снова подставляем полученный результат в первое неравенство леммы. Максимизация по $p = (\\theta, \\phi) \\in \\cX \\cap \\ole{B}_R(X_1)$ даёт следующую оценку:\n",
    "\n",
    "$$\n",
    "    NI_R(\\ole{X}) \\le \\frac{R^2 + \\mu_1}{2\\sum_{s = 1}^t \\lambda_s}\n",
    "$$"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5eaed74f",
   "metadata": {
    "id": "5eaed74f"
   },
   "source": [
    "#### Последняя итерация"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a141b7ef",
   "metadata": {
    "id": "a141b7ef"
   },
   "source": [
    "\n",
    "**Теорема о глобальной сходимости (для последней итерации в монотонном случае):** пусть вариационная задача удовлетворяет условиям:\n",
    "1. $\\cX^* \\neq \\emptyset$ - множество решений вариационного неравенства непусто\n",
    "2. $V$ является $\\beta$-липшицевым оператором\n",
    "3. $V$ является $\\alpha$-строго монотонным оператором\n",
    "\n",
    "Пусть также $x^*$ - единственное решение вариационного неравенства. Тогда, если 1-EG метод запущен с постоянным достаточно малым шагом $\\gamma$, то полученная последовательность точек $X_t$ сходится к $x^*$ со следущей асимптотикой:\n",
    "$$\n",
    "    \\exists \\rho > 0 \\such \\|X_t - x^*\\| = O\\big(\\exp(-\\rho t)\\big)\n",
    "$$"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "23fa4657",
   "metadata": {
    "id": "23fa4657"
   },
   "source": [
    "**Теорема о локальной сходимости (для последней итерации в немонотонном случае):** пусть $x^*$ - регулярное решение вариационного неравенства. Тогда, если рассмотреть 1-EG метод, который инициализирован достаточно близко к $x^*$ и имеет достаточно малый шаг $\\gamma$, то полученная последовательность точек $X_t$ сходится к $x^*$ со следующей асимптотикой:\n",
    "$$\n",
    "    \\exists \\rho > 0 \\such \\|X_t - x^*\\| = O\\big(\\exp(-\\rho t)\\big)\n",
    "$$"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9cbb42ea",
   "metadata": {
    "id": "9cbb42ea"
   },
   "source": [
    "**Доказательство немонотонного случая для PEG и OG:** согласно Техлемме 4, существуют такие константы $r, \\alpha, \\beta > 0$, что выполнены условия:\n",
    "- $V$ является $\\beta$-липшицевым на $K = \\ole{B}_r(x^*)$\n",
    "- $\\forall x \\in U := \\cX \\cap K\\ \\ \\tbr{V(x), x - x^*} \\ge \\alpha\\|x - x^*\\|^2$\n",
    "\n",
    "Из второго факта на самом деле следует, что если мы покажем принадлежность $X_t \\in K$ при всех $t \\in \\N / 2$, то всё будет доказано (случай просто сведётся к монотонному, где ключевым фактом служит как раз аналогичное неравенство $\\tbr{V(X_{t + 1 / 2}), X_{t + 1 / 2} - x^*} \\ge \\alpha\\|X_{t + 1 / 2} - x^*\\|^2$). Итак, чтобы показать требуемое, мы найдём такие начальные условия, что все точки попадут под результат Техлеммы 4:\n",
    "1. $\\forall t \\in \\N\\ \\ \\|X_t - x^*\\| \\le \\frac{r^2}{4}$\n",
    "2. $\\forall t \\in \\N\\ \\ X_{t + 1 / 2} \\in K$\n",
    "\n",
    "Мы найдём такие начальные значения, что факты выше будут выполнены индуктивно.\n",
    "1. Покажем как делать индукционный переход для $t > 1$ в предположении, что при всех $s \\in \\N \\wedge s \\le t$ у нас есть  принадлежность $X_s \\in K$. Тогда в случаях PEG и OG $X_{s + 1 / 2} \\in \\cX \\cap K = U$ и у нас выполнено неравенство $\\tbr{V(X_{s + 1 / 2}), X_{s + 1 / 2} - x^*} \\ge 0$. За счёт этой оценки, мы напрямую из неравенства леммы можем получить такую связь:\n",
    "\n",
    "   $$\n",
    "       \\|X_t - x^*\\|^2 + \\mu_t \\le \\|X_{t - 1} - x^*\\|^2 + \\mu_{t - 1} \\le \\ldots \\le \\|X_1 - x^*\\|^2 + \\mu_1\n",
    "   $$\n",
    "\n",
    "   В силу того, как мы выбираем начальные условия в PEG и OG, мы можем потребовать $X_{1 / 2} = X_1$ и тогда $\\mu_1 = 0$, а подобрать $X_1$ так, чтобы выполнить неравенство $\\|X_1 - x^*\\|^2 \\le \\frac{r^2}{4}$ мы уже как-нибудь сможем.\n",
    "   \n",
    "2. Теперь покажем, что мы сможем подобрать достаточно малый шаг $\\gamma$ такой, что $\\|X_t - x^*\\|^2 \\le \\frac{r^2}{4}$ и $X_{t - 1 / 2} \\in K$, то и $X_{t + 1 / 2} \\in K$. В силу нерасширяемости проекции, мы имеем право записать следующее:\n",
    "\n",
    "   $$\n",
    "       \\|X_{t + 1 / 2} - X_t\\|^2 \\le \\|X_t - \\gamma V(X_{t - 1 / 2}) - X_t\\|^2 = \\gamma^2\\|V(X_{t - 1 / 2})\\|^2\n",
    "   $$\n",
    "\n",
    "   В силу непрерывности $V$ на компактности $K$, оператор ограничен. Обозначим за $M$ соответствующую константу. Тогда мы можем потребовать $\\gamma < r / (2M)$, откуда получим\n",
    "\n",
    "   $$\n",
    "       X_{t - 1 / 2} \\in K \\Ra \\gamma^2\\|V(X_{t - 1 / 2})\\|^2 \\le \\frac{r^2}{4M^2} \\cdot M^2 = \\frac{r^2}{4}\n",
    "   $$\n",
    "   \n",
    "   Остаётся воспользоваться неравенством Юнга и получить требуемое:\n",
    "   \n",
    "   $$\n",
    "       \\|X_{t + 1 / 2} - x^*\\|^2 \\le 2\\|X_{t + 1 / 2} - X_t\\|^2 + 2\\|X_t - x^*\\|^2 \\le r^2 \\Ra X_{t + 1 / 2} \\in K\n",
    "   $$"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0767a969",
   "metadata": {
    "id": "0767a969"
   },
   "source": [
    "### Обзор стохастического случая"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cb331032",
   "metadata": {
    "id": "cb331032"
   },
   "source": [
    "**Теорема о глобальной сходимости:** пусть вариационная задача удовлетворяет условиям:\n",
    "1. $\\cX^* \\neq \\emptyset$ - множество решений вариационного неравенства непусто\n",
    "2. $V$ является $\\beta$-липшицевым оператором\n",
    "3. $V$ является $\\alpha$-строго монотонным оператором\n",
    "\n",
    "Если рассмотреть PEG-алгоритм со стохастическим оракулом, чьи ответы удовлетворяют модели, а также шаг имеет вид $\\gamma_t = \\gamma / (t + b)$ для некоторых $\\gamma > 1 / \\alpha$ и $b \\ge 4\\beta\\gamma$, то имеет место неравенство:\n",
    "$$\n",
    "    \\E\\big(\\|X_t - x^*\\|^2\\big) \\le \\frac{6\\gamma^2\\sigma^2}{\\alpha\\gamma - 1} \\cdot \\frac{1}{t} + o\\ps{\\frac{1}{t}}\n",
    "$$\n",
    "При этом, для эргодического среднего $\\ole{X}_t = \\frac{1}{t}\\sum_{s = 1}^t X_s$ тоже верно похожее неравенство:\n",
    "$$\n",
    "    \\E\\big(\\|\\ole{X}_t - x^*\\|^2\\big) \\le \\frac{6\\gamma^2\\sigma^2}{\\alpha\\gamma - 1} \\cdot \\frac{\\log t}{t} + o\\ps{\\frac{\\log t}{t}}\n",
    "$$"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3dd3b441",
   "metadata": {
    "id": "3dd3b441"
   },
   "source": [
    "**Теорема о локальной сходимости:** пусть $x^*$ - регулярное решение вариационного неравенства, $\\delta > 0$ - *уровень терпимости*. Если рассмотреть PEG-алгоритм со стохастическим оракулом, чьи ответы удовлетворяют описанной модели, а также шаг имеет вид $\\gamma_t = \\gamma / (t + b)$ для некоторых $\\gamma > 1 / \\alpha$ и достаточно большого $b$, то имеют место утверждения:\n",
    "1. Существуют окрестности $U, U_1 \\subseteq \\cX$ около точки $x^*$ такие, что если $X_{1 / 2} \\in U$ и $X_1 \\in U_1$, то событие $E_\\infty = \\{\\forall t \\in \\N\\ \\ X_{t + 1 / 2} \\in U\\}$  (все ведущие точки лежат в окрестности $U$) происходит с вероятностью не менее $1 - \\delta$.\n",
    "\n",
    "2. В предположении первого пункта, имеет место неравенство:\n",
    "$$\n",
    "    \\E\\big(\\|X_t - x^*\\|^2 | E_\\infty\\big) \\le \\frac{4\\gamma^2(M^2 + \\sigma^2)}{(\\alpha\\gamma - 1)(1 - \\delta)} \\cdot \\frac{1}{t} + o\\ps{\\frac{1}{t}}\n",
    "$$\n",
    "где $M = \\sup_{x \\in U} \\|V(x)\\| < \\infty$ и $\\alpha = \\inf_{x \\in U} \\frac{\\tbr{V(x), x - x^*}}{\\|x - x^*\\|^2} > 0$"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5a4725a3",
   "metadata": {
    "id": "5a4725a3"
   },
   "source": [
    "**Замечание к теореме:** конечность $M$ и положительность $\\alpha$ являются следствием регулярности $x^*$, а их значения зависят только на величине окрестности $U$. Так, с ростом окрестности $U$, которая отвечает за область почти достоверной сходимости, мы получаем более плохую сходимость, ибо $M$ неубывает с этим ростом, а $\\alpha$ может только уменьшится (это плохо, ибо оно в знаменателе). Схожим образом $U_1$ зависит только от $U$, причём имеет смысл рассматривать такие $U_1$, что они составляют четверть от $U$ (в смысле меры)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4117e50b",
   "metadata": {
    "id": "4117e50b"
   },
   "source": [
    "## Практическая часть"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5450ecc6",
   "metadata": {
    "id": "5450ecc6"
   },
   "source": [
    "### Цели"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d249c066",
   "metadata": {
    "id": "d249c066"
   },
   "source": [
    "1. Показать работу экстра-градиентных методов для решения задачи вариационного неравенства\n",
    "2. Показать, что рассмотренные 1-EG методы показывают себя качественно и количественно лучше чем стандартный экстраградиентный метод\n",
    "3. Попробовать выбрать лучший из предложенных методов\n",
    "4. Подтвердить результаты статьи"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "163f7f18",
   "metadata": {
    "id": "163f7f18"
   },
   "source": [
    "### Постановка конкретной задачи, исследование констант оператора $V$\n",
    "\n",
    "Рассмотрим min-max задачу без ограничений для функции $\\cL(\\theta, \\phi)$ следующего вида:\n",
    "\n",
    "$$\n",
    "    \\cL(\\theta, \\phi) = 2\\eps_1(\\theta^TA_1\\theta) + \\eps_2(\\theta^TA_2\\theta)^2 - 2\\eps_1(\\phi^TB_1\\phi) - \\eps_2(\\phi^TB_2\\phi)^2 + 4(\\theta^TC\\phi)\n",
    "$$\n",
    "\n",
    "Пусть $\\cX = \\R^d = \\R^{d_1} \\times \\R^{d_2}$ для $d_1 = d_2 = 1000$, а также $A_i, B_i \\succ 0$.\n",
    "\n",
    "Мы рассмотрим 3 конкретных случая, для простоты $C = E_d$:\n",
    "\n",
    "1. $\\eps_1 = 1$, $\\eps_2 = 0$. В этом случае $\\cL(\\theta, \\phi) = 2\\theta^TA_1\\theta - 2\\phi^TB_1\\phi + 4\\theta^T\\phi$. Оператор $V$ имеет следующий вид:\n",
    "\n",
    "$$\n",
    "    V(\\theta, \\phi) = (\\nabla_\\theta \\cL, -\\nabla_\\phi \\cL) = 4(A_1\\theta + С\\phi, B_1\\phi - С\\theta)\n",
    "$$\n",
    "\n",
    "**Исследование:** покажем, что он является строго монотонным. Воспользуемся определением:\n",
    "\n",
    "$$\n",
    "    \\tbr{V(x') - V(x), x' - x} \\ge \\alpha\\|x' - x\\|^2 = \\alpha\\tbr{x' - x, x' - x}\n",
    "$$\n",
    "\n",
    "Перенесём всё в левую часть и подставим $V$:\n",
    "\n",
    "$$\n",
    "    \\tbr{\\big((4A_1 - \\alpha E_d)(\\theta' - \\theta) + 4С(\\phi' - \\phi), (4B_1 - \\alpha E_d)(\\phi' - \\phi) - 4С(\\theta' - \\theta)\\big), x' - x} \\ge 0\n",
    "$$\n",
    "\n",
    "Скалярное произведение можно разбить на четыре в силу определения:\n",
    "\n",
    "$$\n",
    "    \\tbr{(4A_1 - \\alpha E_d)(\\theta' - \\theta), \\theta' - \\theta} + 4\\tbr{С(\\phi' - \\phi), \\theta' - \\theta} + \\tbr{(4B_1 - \\alpha E_d)(\\phi' - \\phi), \\phi' - \\phi} - 4\\tbr{С(\\theta' - \\theta), \\phi' - \\phi} \\ge 0\n",
    "$$\n",
    "\n",
    "По итогу остаётся 2 скалярных произведения (в силу $C = C^T$ можно перенести матрицу в скалярном произведении и сократить), которые не зависят друг от друга. Несложно увидеть, что если хоть одно из них меньше нуля, то можно устремить всё в $-\\infty$. Стало быть, мы хотим, чтобы и то, и другое было неотрицательно. Это выполняется тогда и только тогда, когда соответствующие матрицы неотрицательно определены:\n",
    "\n",
    "$$\n",
    "    \\alpha \\colon \\System{\n",
    "        &{4A_1 - \\alpha E_d \\succeq 0 \\Lra \\alpha \\le 4\\lambda_\\min(A_1)}\n",
    "        \\\\\n",
    "        &{4B_1 - \\alpha E_d \\succeq 0 \\Lra \\alpha \\le 4\\lambda_\\min(B_1)}\n",
    "    }\n",
    "$$\n",
    "\n",
    "Отсюда $\\alpha \\le 4\\min\\{\\lambda_\\min(A_1), \\lambda_\\min(B_1)\\}$.\n",
    "\n",
    "Также нам надо получить оценку на $\\beta$-липшицевость. Распишем квадрат нормы $\\|V(x') - V(x)\\|^2$, это просто сделать в силу $\\|x\\|^2 = \\|\\theta\\|^2 + \\|\\phi\\|^2$:\n",
    "\n",
    "$$\n",
    "    \\begin{aligned}\n",
    "        \\|V(x') - V(x)\\|^2 &= \\|(A_1(\\theta' - \\theta) + 4C(\\phi' - \\phi), B_1(\\phi' - \\phi) - 4C(\\theta' - \\theta))\\|^2\n",
    "        \\\\\n",
    "        &= \\|A_1(\\theta' - \\theta) + 4C(\\phi' - \\phi)\\|^2 + \\|B_1(\\phi' - \\phi) - 4C(\\theta' - \\theta)\\|^2\n",
    "        \\\\\n",
    "        &= \\|A_1(\\theta' - \\theta)\\|^2 + \\|4C(\\phi' - \\phi)\\|^2 + \\|B_1(\\phi' - \\phi)\\|^2 + \\|4C(\\theta' - \\theta)\\|^2\n",
    "        \\\\\n",
    "        &+ 2\\tbr{A_1(\\theta' - \\theta), 4C(\\phi' - \\phi)} - 2\\tbr{B_1(\\phi' - \\phi), 4C(\\theta' - \\theta)}\n",
    "        \\\\\n",
    "        &= \\tbr{(A_1^2 + 16C^2)(\\theta' - \\theta), \\theta' - \\theta} + \\tbr{(B_1^2 + 16C^2)(\\phi' - \\phi), \\phi' - \\phi} + 2\\tbr{(4A_1C - 4B_1C)(\\theta' - \\theta), \\phi' - \\phi}\n",
    "        \\\\\n",
    "        &\\le \\|A_1^2 + 16C^2\\| \\cdot \\|\\theta' - \\theta\\|^2 + \\|B_1^2 + 16C^2\\| \\cdot \\|\\phi' - \\phi\\|^2 + \\|8(A_1 - B_1)C\\| \\cdot \\|\\theta' - \\theta\\| \\cdot \\|\\phi' - \\phi\\|\n",
    "        \\\\\n",
    "        &\\le \\|A_1^2 + 16C^2\\| \\cdot \\|\\theta' - \\theta\\|^2 + \\|B_1^2 + 16C^2\\| \\cdot \\|\\phi' - \\phi\\|^2 + \\|4(A_1 - B_1)C\\| \\cdot (\\|\\theta' - \\theta\\|^2 + \\|\\phi' - \\phi\\|^2)\n",
    "    \\end{aligned}\n",
    "$$\n",
    "\n",
    "Таким образом, уже можем дать оценку на $\\beta$-липшицевость $V$ через неравенство $0 < \\beta \\le \\sqrt{\\max\\{\\|A_1^2 + 16C^2\\|, \\|B_1^2 + 16C^2\\|\\} - \\|4(A_1 - B_1)C\\|}$. Интересный факт о матрицах: $\\|A\\| = \\max |\\lambda(A)| = |\\lambda|_\\max(A)$. Сделаем такую грубую оценку на $\\beta$:\n",
    "\n",
    "$$\n",
    "    \\begin{aligned}\n",
    "        \\beta &\\le \\sqrt{\\max\\{\\|A_1^2 + 16C^2\\|, \\|B_1^2 + 16C^2\\|\\} - \\|4(A_1 - B_1)C\\|}\n",
    "        \\\\\n",
    "        &\\le \\sqrt{\\max\\{\\|A_1^2 + 16C^2\\|, \\|B_1^2 + 16C^2\\|\\}}\n",
    "        \\\\\n",
    "        &\\le \\sqrt{\\max\\{\\lambda_\\max^2(A_1), \\lambda_\\max^2(B_1)\\} + 16\\lambda_\\max^2(C)}\n",
    "    \\end{aligned}\n",
    "$$\n",
    "\n",
    "2. $\\eps_1 = 0$, $\\eps_2 = 1$. В такой ситуации $\\cL(\\theta, \\phi) = (\\theta^TA_2\\theta)^2 - (\\phi^TB_2\\phi)^2 + 4(\\theta^TC\\phi)$. Оператор $V$ принимает вид:\n",
    "\n",
    "$$\n",
    "    V(\\theta, \\phi) = 4\\big(2(\\theta^TA_2\\theta)A_2\\theta + C\\phi, 2(\\phi^TB_2\\phi)B_2\\phi - C\\theta\\big) = 4(2A_2\\theta\\theta^TA_2\\theta + C\\phi, 2B_2\\phi\\phi^TB_2\\phi - C\\theta)\n",
    "$$\n",
    "\n",
    "**Исследование:** покажем, что $V$ монотонна. Это можно сделать [по теореме Качуровского](https://en.wikipedia.org/wiki/Kachurovskii%27s_theorem), либо доказать явным образом, что мы и проделаем:\n",
    "\n",
    "$$\n",
    "    V(x') - V(x) = 4\\big(2A_2(\\theta'\\theta'^TA_2\\theta' - \\theta\\theta^TA_2\\theta) + C(\\phi' - \\phi), 2B_2(\\phi'\\phi'^TB_2\\phi' - \\phi\\phi^TB_2\\phi) - C(\\theta' - \\theta)\\big)\n",
    "$$\n",
    "\n",
    "Как и ранее, требование $\\tbr{V(x') - V(x), x' - x} \\ge 0$ можно переписать в эквивалентном виде:\n",
    "\n",
    "$$\n",
    "    \\begin{aligned}\n",
    "        \\tbr{V(x') - V(x), x' - x} &= \\tbr{V_\\theta(x') - V_\\theta(x), \\theta' - \\theta} + \\tbr{V_\\phi(x') - V_\\phi(x), \\phi' - \\phi}\n",
    "        \\\\\n",
    "        &= 4\\tbr{2A_2(\\theta'\\theta'^TA_2\\theta' - \\theta\\theta^TA_2\\theta) + C(\\phi' - \\phi), \\theta' - \\theta}\n",
    "        \\\\\n",
    "        &+ 4\\tbr{2B_2(\\phi'\\phi'^TB_2\\phi' - \\phi\\phi^TB_2\\phi) - C(\\theta' - \\theta), \\phi' - \\phi}\n",
    "        \\\\\n",
    "        &= 4\\tbr{2A_2(\\theta'\\theta'^TA_2\\theta' - \\theta\\theta^TA_2\\theta), \\theta' - \\theta} + 4\\tbr{2B_2(\\phi'\\phi'^TB_2\\phi' - \\phi\\phi^TB_2\\phi), \\phi' - \\phi}\n",
    "        \\\\\n",
    "        &+ 4\\tbr{C(\\phi' - \\phi), \\theta' - \\theta} - 4\\tbr{C(\\theta' - \\theta), \\phi' - \\phi}\n",
    "        \\\\\n",
    "        &= 8\\tbr{A_2(\\theta'\\theta'^TA_2\\theta' - \\theta\\theta^TA_2\\theta), \\theta' - \\theta} + 8\\tbr{B_2(\\phi'\\phi'^TB_2\\phi' - \\phi\\phi^TB_2\\phi), \\phi' - \\phi}\n",
    "    \\end{aligned}\n",
    "$$\n",
    "\n",
    "В силу аналогичности, разберём только случай с $\\theta$:\n",
    "\n",
    "$$\n",
    "    \\begin{aligned}\n",
    "        \\tbr{V_\\theta(x') - V_\\theta(x), \\theta' - \\theta} &= 8\\tbr{A_2\\theta'\\theta'^TA_2\\theta' - A_2\\theta\\theta^TA_2\\theta, \\theta' - \\theta}\n",
    "        \\\\\n",
    "        &= 8\\tbr{A_2\\theta'\\theta'^TA_2\\theta', \\theta'} - 8\\tbr{A_2\\theta\\theta^TA_2\\theta, \\theta'} - 8\\tbr{A_2\\theta'\\theta'^TA_2\\theta', \\theta} + 8\\tbr{A_2\\theta\\theta^TA_2\\theta, \\theta}\n",
    "    \\end{aligned}\n",
    "$$\n",
    "\n",
    "Так как $\\theta^TA_2\\theta = \\tbr{\\theta, A_2\\theta} = \\tbr{\\theta, \\theta}_{A_2} = \\|\\theta\\|_{A_2}^2$ - число, то его можно вынести из скалярного произведения:\n",
    "\n",
    "$$\n",
    "    \\begin{aligned}\n",
    "        \\tbr{V_\\theta(x') - V_\\theta(x), \\theta' - \\theta} &= 8\\|\\theta'\\|_{A_2}^2 \\tbr{\\theta', \\theta'}_{A_2} - 8\\|\\theta\\|_{A_2}^2 \\tbr{\\theta, \\theta'}_{A_2} - 8\\|\\theta'\\|_{A_2}^2 \\tbr{\\theta', \\theta}_{A_2} + 8\\|\\theta\\|_{A_2}^2 \\tbr{\\theta, \\theta}_{A_2}\n",
    "        \\\\\n",
    "        &= 8\\|\\theta'\\|_{A_2}^4 - 8\\tbr{\\theta, \\theta'}_{A_2}(\\|\\theta\\|_{A_2}^2 + \\|\\theta'\\|_{A_2}^2) + 8\\|\\theta\\|_{A_2}^4\n",
    "    \\end{aligned}\n",
    "$$\n",
    "\n",
    "Как известно, есть неравенство КБШ $|\\tbr{\\theta, \\theta'}_{A_2}| \\le \\|\\theta\\|_{A_2} \\cdot \\|\\theta'\\|_{A_2}$, причём оно достигается при линейной зависимости векторов. Обозначим $a = \\|\\theta\\|_{A_2}$, $b = \\|\\theta'\\|_{A_2}$. Тогда всё доказательство сводится к тому, чтобы доказать неравенство в худшем случае (то есть при достижении КБШ):\n",
    "\n",
    "$$\n",
    "    \\forall a, b \\ge 0 \\quad 8(a^4 - ab(a^2 + b^2) + b^4) \\ge 0 \\Lra a^3(a - b) - b^3(a - b) \\ge 0 \\Lra (a - b)^2(a^2 + ab + b^2) \\ge 0\n",
    "$$\n",
    "\n",
    "Последнее неравенство выполнено всегда тривиальным образом, поэтому монотонность установлена.\n",
    "\n",
    "Теперь $\\beta$-липшицевость. Как и в первом случае, мы просто происследуем часть $V_\\theta(\\theta)$, а затем возьмём среднее геометрическое от оценок. Сразу стоит отметить, что **тут не может получиться глобальной константы Липшица**, просто в силу квадратичной зависимости. Итак, рассмотрим $\\|\\theta\\|_2 \\le R$ (ноль - это седловая точка). Тогда:\n",
    "\n",
    "$$\n",
    "    \\begin{aligned}\n",
    "        \\|V_\\theta(x') - V_\\theta(x)\\|_2 &= \\|A_2\\theta'\\theta'^TA_2\\theta' - A_2\\theta\\theta^TA_2\\theta + C(\\phi' - \\phi)\\|_2\n",
    "        \\\\\n",
    "        &\\le \\|A_2\\| \\cdot \\nm{\\|\\theta'\\|_{A_2}^2\\theta' - \\|\\theta\\|_{A_2}^2\\theta} \\cdot \\|C\\| \\cdot \\|\\phi' - \\phi\\|_2\n",
    "    \\end{aligned}\n",
    "$$\n",
    "\n",
    "Таким образом, задача свелась к исследованию оператора $f(v) = \\|v\\|_{A_2}^2v$ при $\\|v\\|_2 \\le R$. Его производная, она же якобиан, считается покоординатно (используется тензорная нотация, $\\delta_{ij} = \\chi\\{i = j\\}$ - символ Кронекера):\n",
    "\n",
    "$$\n",
    "    \\begin{aligned}\n",
    "        \\pd{f_l}{v_t} = \\pd{}{v_t}(\\|v\\|_{A_2}^2v_l) = \\pd{}{v_t}(v_iA_{ij}v_jv_l) &= \\delta_{lt} v_iA_{ij}v_j + \\delta_{jt} v_iA_{ij}v_l + \\delta_{it} A_{ij}v_jv_l\n",
    "        \\\\\n",
    "        &= \\delta_{lt} v_iA_{ij}v_j + v_iA_{it}v_l + A_{tj}v_jv_l\n",
    "        \\\\\n",
    "        &= \\delta_{lt} v_iA_{ij}v_j + v_l(A_{it}v_i + A_{jt}v_j) = \\delta_{lt}(v_iA_{ij}v_j) + 2v_lA_{it}v_i\n",
    "    \\end{aligned}\n",
    "$$\n",
    "\n",
    "Итак, распишем приращение $\\nabla f(v)(y - z)$ в координатном виде, а потом посмотрим на его норму:\n",
    "\n",
    "$$\n",
    "    (\\nabla f(v)(y - z))_l = [\\delta_{lt}(v_iA_{ij}v_j) + 2v_lA_{it}v_i](y_t - z_t) = (v^TA_2v)(y - z)_l + 2v_lv_iA_{it}(y - z)_t = (v^TA_2v)(y - z)_l + 2v_l\\big(v^TA_2(y - z)\\big)\n",
    "$$\n",
    "\n",
    "Таким образом, $\\nabla f(v)(y - z) = (v^TA_2v)(y - z) + \\big(2v_l(v^TA_2(y - z))\\big)$, норму оценим через неравенство треугольника.\n",
    "\n",
    "1. $\\|(v^TA_2v)(y - z)\\|_2 = |\\tbr{v, A_2v}|\\|y - z\\|_2 \\le \\|A_2\\| \\cdot \\|v\\|_2^2 \\cdot \\|y - z\\|_2$\n",
    "2. $\\nm{\\big(2v_l(v^TA_2(y - z))\\big)}_2 = 2|v^TA_2(y - z)| \\cdot \\|v\\|_2 \\le 2\\|A_2\\| \\cdot \\|v\\|_2^2 \\cdot \\|y - z\\|_2$\n",
    "\n",
    "Всё это вместе даёт оценку $\\|\\nabla f(v)(y - z)\\|_2 \\le 3\\|A_2\\| \\cdot \\|v\\|_2^2 \\cdot \\|y - z\\|_2$, а стало быть можно подставить это в исходное выражение и получить оценку на константу Липшица для части с $\\theta$:\n",
    "\n",
    "$$\n",
    "    \\|V_\\theta(x') - V_\\theta(x)\\|_2 \\le 3\\|A_2\\|^2 \\|C\\| \\cdot (\\max_{\\|v\\|_2 \\le R} \\|v\\|_2^2) \\cdot \\|\\theta' - \\theta\\|_2 \\cdot \\|\\phi' - \\phi\\|_2\n",
    "$$\n",
    "\n",
    "С такой оценкой мы можем сделать общую:\n",
    "\n",
    "$$\n",
    "    \\begin{aligned}\n",
    "        \\|V(x') - V(x)\\|_2^2 &= \\|V_\\theta(x') - V_\\theta(x)\\|_2^2 + \\|V_\\phi(x') - V_\\phi(x)\\|_2^2 \\le (3\\|C\\|R^2)^2 (\\|A_2\\|^4 + \\|B_2\\|^4) \\|\\theta' - \\theta\\|_2^2 \\cdot \\|\\phi' - \\phi\\|_2^2\n",
    "        \\\\\n",
    "        &\\le (3\\|C\\|R^2)^2 (\\|A_2\\|^4 + \\|B_2\\|^4) \\ps{\\frac{\\|\\theta' - \\theta\\|_2^2 + \\|\\phi' - \\phi\\|_2^2}{2}}^2 = (1.5\\|C\\|R^2)^2 (\\|A_2\\|^4 + \\|B_2\\|^4) \\|x' - x\\|_2^2\n",
    "    \\end{aligned}\n",
    "$$\n",
    "\n",
    "Последний переход сделан по неравенству Коши между средним геометрическим и квадратичным. Из этого выражения получаем общую оценку на константу Липшица $\\beta \\le 1.5\\|C\\|R^2\\sqrt{\\|A_2\\|^4 + \\|B_2\\|^4}$. Ещё её можно переписать как $\\beta \\le 1.5 \\lambda_\\max(C)R^2\\sqrt{\\lambda_\\max^4(A_2) + \\lambda_\\max^4(B_2)}$\n",
    "\n",
    "3. $\\eps_1 = 1 = -\\eps_2$, случайный оракул с ошибкой $Z \\sim N(0, 10^{-2})$"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "984a8b14",
   "metadata": {
    "id": "984a8b14"
   },
   "source": [
    "### Изучение требований для сходимости\n",
    "\n",
    "1. Мы рассмотрим $\\gamma \\le 1.2$. Чтобы была сходимость детерминированного PEG-алгоритма, нам нужно потребовать $\\gamma = 1.2 \\le \\frac{1}{2\\beta}$, то есть $\\beta \\le \\frac{1}{2\\gamma} = \\frac{5}{12}$, а это чуть больше чем $\\beta_0 = 0.416$\n",
    "\n",
    "2. В случае $\\eps_1 = 1$, $\\eps_2 = 0$ потребуем $\\max\\{\\lambda_\\max^2(A_1), \\lambda_\\max^2(B_1)\\} + 16\\lambda_\\max^2(C) \\le \\beta_0^2$. Достаточным условием станет $\\max\\{\\lambda_\\max^2(A_1), \\lambda_\\max^2(B_1)\\} \\le \\frac{\\beta_0^2}{2}$ ($\\lambda_\\max \\le \\frac{\\beta_0}{\\sqrt{2}} \\approx 0.1223$) и $16\\lambda_\\max^2(C) \\le \\frac{\\beta_0^2}{2}$ ($\\lambda_\\max(C) \\le \\frac{\\beta_0^2}{4\\sqrt{2}} \\approx 0.0305$)\n",
    "\n",
    "3. Допустим, мы хотим в случае $\\eps_1 = 0$, $\\eps_2 = 1$ сходимость для стартовой точки $x_{0, i} = 17$. Тогда (не учитывая того, что точки могут вылететь за пределы радиуса и сходимости не будет) $\\|x_0\\| = \\sqrt{1000 \\cdot 17^2} = 170\\sqrt{10} \\approx R$. Тогда $1.5\\lambda_\\max(C)R^2 \\cdot \\lambda_\\max^2\\sqrt{2} \\le \\frac{5}{12}$, а значит $\\lambda_\\max \\le \\frac{1}{R}\\sqrt{\\frac{5}{\\lambda_\\max(C) \\cdot 18\\sqrt{2}}} \\approx 0.00472$"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dc502643",
   "metadata": {
    "id": "dc502643"
   },
   "source": [
    "### Код"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "e74f8dc6",
   "metadata": {
    "id": "e74f8dc6"
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from functools import partial\n",
    "import jax.numpy as jnp\n",
    "from jax import grad, hessian, jit, vmap\n",
    "#from jax import random"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "a297373b",
   "metadata": {
    "id": "a297373b"
   },
   "outputs": [],
   "source": [
    "from jax import config\n",
    "config.update(\"jax_enable_x64\", True) # for float64"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5d12e21f",
   "metadata": {
    "id": "5d12e21f"
   },
   "source": [
    "#### Постановка задачи в коде:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "c2c58fd9",
   "metadata": {
    "id": "c2c58fd9"
   },
   "outputs": [],
   "source": [
    "def generate_possymm_matrix(d, m, L):\n",
    "    B = jnp.diag(np.random.rand(d) * (L - m) + m)\n",
    "    Q, _ = jnp.linalg.qr(np.random.rand(d, d))\n",
    "    return Q.T @ B @ Q"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "19e7c0d2",
   "metadata": {
    "id": "19e7c0d2"
   },
   "outputs": [],
   "source": [
    "np.random.seed(1580)\n",
    "d = 1000\n",
    "sigma = 0.1\n",
    "coefs_arr = [(1, 0), (0, 1)] #, (1, -1)]\n",
    "coefs_labels = ['Строго монотонный случай', 'Монотонный случай'] #, '']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "f2ff25fc",
   "metadata": {
    "id": "f2ff25fc"
   },
   "outputs": [],
   "source": [
    "ms = jnp.array([0.1200, 0.004, 0.1200, 0.004, 0.0250])\n",
    "Ls = jnp.array([0.1223, 0.00472, 0.1223, 0.00472, 0.0305])\n",
    "\n",
    "Mtxs = np.zeros(shape=(len(ms), d // 2, d // 2))\n",
    "\n",
    "for i, (m, L) in enumerate(zip(ms, Ls)):\n",
    "    Mtxs[i] = generate_possymm_matrix(d // 2, m, L)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "d268c484",
   "metadata": {
    "id": "d268c484"
   },
   "outputs": [],
   "source": [
    "def general_L_func(theta, phi, e1, e2, A1, A2, B1, B2, C):\n",
    "    s1 = 2 * e1 * (theta.T @ A1 @ theta)\n",
    "    s2 = e2 * (theta.T @ A2 @ theta) ** 2\n",
    "    s3 = 2 * e1 * (phi.T @ B1 @ phi)\n",
    "    s4 = e2 * (phi.T @ B2 @ phi) ** 2\n",
    "    s5 = 4 * (theta.T @ C @ phi)\n",
    "    return s1 + s2 - s3 - s4 + s5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "4e2db7f8",
   "metadata": {
    "id": "4e2db7f8"
   },
   "outputs": [],
   "source": [
    "L_funcs = np.array([\n",
    "    jit(lambda theta, phi, coefs=coefs, Mtxs=Mtxs: general_L_func(theta,\n",
    "                                                                  phi,\n",
    "                                                                  *coefs,\n",
    "                                                                  *Mtxs)) for coefs in coefs_arr\n",
    "], dtype='O')\n",
    "\n",
    "oracle_funcs = np.array([\n",
    "    jit(lambda x, L_func=L_func: jnp.hstack((\n",
    "                                             grad(L_func, 0)(x[:d // 2], x[d // 2:]),\n",
    "                                             -grad(L_func, 1)(x[:d // 2], x[d // 2:]))\n",
    "    )) for L_func in L_funcs\n",
    "], dtype='O')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fb4d3c98",
   "metadata": {
    "id": "fb4d3c98"
   },
   "source": [
    "#### Реализация функций ошибок:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "a31d34d5",
   "metadata": {
    "id": "a31d34d5"
   },
   "outputs": [],
   "source": [
    "def total_arg_sqdist_error_func(xs, x_sol):\n",
    "    vs = xs - x_sol\n",
    "    return np.sum(vs * vs, axis=1)\n",
    "\n",
    "def total_arg_dist_error_func(xs, x_sol):\n",
    "    return np.linalg.norm(xs - x_sol, axis=1)\n",
    "\n",
    "def total_func_dist_error_func(L_func, xs, x_sol):\n",
    "    v_L_func = vmap(L_func)\n",
    "    return v_L_func(xs) - L_func(x_sol)\n",
    "\n",
    "def neigh_arg_dist_error_func(xs):\n",
    "    return np.linalg.norm(np.append([xs[0]], xs[1:] - xs[:-1]), axis=1)\n",
    "\n",
    "def neigh_func_dist_error_func(L_func, xs, x_sol):\n",
    "    v_L_func = vmap(L_func)\n",
    "    L_vals = v_L_func(xs)\n",
    "    return np.append([L_vals[0]], L_vals[1:] - L_vals[:-1])\n",
    "\n",
    "# def merge_coords(x_coords, y_coords):\n",
    "#     return jnp.concatenate((jnp.expand_dims(x_coords, axis=1), jnp.expand_dims(y_coords, axis=1)), axis=1)\n",
    "\n",
    "# def get_grid_points(R, eps):\n",
    "#     xspace = yspace = jnp.arange(-R, R, eps)\n",
    "#     ps_xs, ps_ys = jnp.meshgrid(xspace, yspace)\n",
    "#     ps_xs = ps_xs.flatten()\n",
    "#     ps_ys = ps_ys.flatten()\n",
    "#     return merge_coords(ps_xs, ps_ys)\n",
    "\n",
    "# def vi_error_func(V_func, xs, R, eps):\n",
    "#     ps = get_grid_points(R, eps)\n",
    "#     v_V_func = vmap(V_func)\n",
    "#     V_vals = v_V_func(ps)\n",
    "\n",
    "#     vi_value_func = vmap(lambda x: jnp.sum(V_vals * (x - ps)))\n",
    "#     return np.max(vi_value_func(xs)[np.norm(ps) <= R])\n",
    "\n",
    "# def ni_error_func(L_func, xs, R, eps):\n",
    "#     ps = get_grid_points(R, eps)\n",
    "#     v_L_func = vmap(L_func)\n",
    "\n",
    "#     xs1 = xs[:, 0]\n",
    "#     xs2 = xs[:, 1]\n",
    "#     ps1 = ps[:, 0]\n",
    "#     ps2 = ps[:, 1]\n",
    "\n",
    "#     ni_value_func = vmap(lambda x: )\n",
    "    # max L(theta_k, psi) - min L(theta, psi_k)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "54af3b62",
   "metadata": {
    "id": "54af3b62"
   },
   "source": [
    "**Реализация методов:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "5d69ddd6",
   "metadata": {
    "id": "5d69ddd6"
   },
   "outputs": [],
   "source": [
    "def extra_gradient_descent(oracle_func, gamma_func, x_0, K=10**3):\n",
    "    '''\n",
    "        oracle_func - функция оракула\n",
    "        gamma_func - функция шага\n",
    "        x_0 - стартовая точка\n",
    "        K - количество итераций (по умолчанию 1е3)\n",
    "\n",
    "       Функция возвращает вектор всех полученных точек.\n",
    "    '''\n",
    "    xs = np.zeros(shape=(2 * K + 1, d))\n",
    "    xs[0] = x_0\n",
    "\n",
    "    for t in jnp.arange(0, K):\n",
    "        gamma = gamma_func(t + 1)\n",
    "        x = xs[2 * t]\n",
    "        xs[2 * t + 1] = leading_x = x - gamma * oracle_func(x)\n",
    "        xs[2 * t + 2] = x - gamma * oracle_func(leading_x)\n",
    "\n",
    "    return xs\n",
    "\n",
    "def past_extra_gradient_descent(oracle_func, gamma_func, x_0, K=10**3):\n",
    "    '''\n",
    "        oracle_func - функция оракула\n",
    "        gamma_func - функция шага\n",
    "        x_0 - стартовая точка\n",
    "        K - количество итераций (по умолчанию 1е3)\n",
    "\n",
    "       Функция возвращает вектор всех полученных точек.\n",
    "    '''\n",
    "    xs = np.zeros(shape=(2 * K + 1, d))\n",
    "    xs[0] = x_0\n",
    "    prev_oracle_value = 0\n",
    "\n",
    "    for t in jnp.arange(0, K):\n",
    "        gamma = gamma_func(t + 1)\n",
    "        x = xs[2 * t]\n",
    "        xs[2 * t + 1] = leading_x = x - gamma * prev_oracle_value\n",
    "        oracle_value = oracle_func(leading_x)\n",
    "        xs[2 * t + 2] = x - gamma * oracle_func(leading_x)\n",
    "        prev_oracle_value = oracle_value\n",
    "\n",
    "    return xs"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "126ea57f",
   "metadata": {
    "id": "126ea57f"
   },
   "source": [
    "#### Повторение экспериментов:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "187d9330",
   "metadata": {
    "id": "187d9330"
   },
   "outputs": [],
   "source": [
    "gamma_steps_cnt = 6\n",
    "gamma_steps = np.linspace(0.1, 0.6, gamma_steps_cnt)\n",
    "gamma_funcs = [\n",
    "    (lambda t, step=step: step) for step in gamma_steps\n",
    "]\n",
    "\n",
    "fixed_gamma_func_ind = 0\n",
    "fixed_gamma_step = gamma_steps[fixed_gamma_func_ind]\n",
    "fixed_gamma_func = gamma_funcs[fixed_gamma_func_ind]\n",
    "\n",
    "x_0_cnt = 10\n",
    "x_0_coords = np.exp(np.linspace(np.log(0.01), np.log(20), x_0_cnt))\n",
    "x_0s = np.zeros(shape=(x_0_cnt, d))\n",
    "\n",
    "for i, x_0_coord in enumerate(x_0_coords):\n",
    "    x_0s[i] = np.full_like(x_0s[i], x_0_coord)\n",
    "\n",
    "fixed_x_0_coord = 1.25\n",
    "fixed_x_0 = np.full(shape=d, fill_value=fixed_x_0_coord)\n",
    "\n",
    "K = 1000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "94e10bc7",
   "metadata": {
    "id": "94e10bc7"
   },
   "outputs": [],
   "source": [
    "eg_one_start_results = np.zeros(shape=(len(coefs_arr), gamma_steps_cnt, 2 * K + 1, d))\n",
    "peg_one_start_results = np.zeros(shape=(len(coefs_arr), gamma_steps_cnt, 2 * K + 1, d))\n",
    "\n",
    "for i, oracle_func in enumerate(oracle_funcs):\n",
    "    for j, gamma_func in enumerate(gamma_funcs):\n",
    "        eg_one_start_results[i, j] = extra_gradient_descent(oracle_func, gamma_func, fixed_x_0, K)\n",
    "        peg_one_start_results[i, j] = past_extra_gradient_descent(oracle_func, gamma_func, fixed_x_0, K)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "5b528f3d",
   "metadata": {
    "id": "5b528f3d"
   },
   "outputs": [],
   "source": [
    "eg_one_step_results = np.zeros(shape=(len(coefs_arr), x_0_cnt, 2 * K + 1, d))\n",
    "peg_one_step_results = np.zeros(shape=(len(coefs_arr), x_0_cnt, 2 * K + 1, d))\n",
    "\n",
    "for i, oracle_func in enumerate(oracle_funcs):\n",
    "    for j, x_0 in enumerate(x_0s):\n",
    "        eg_one_step_results[i, j] = extra_gradient_descent(oracle_func, fixed_gamma_func, x_0, K)\n",
    "        peg_one_step_results[i, j] = past_extra_gradient_descent(oracle_func, fixed_gamma_func, x_0, K)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ebe9e624",
   "metadata": {
    "id": "ebe9e624"
   },
   "source": [
    "#### Построение массивов ошибок:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "c5cc30d7",
   "metadata": {
    "id": "c5cc30d7"
   },
   "outputs": [],
   "source": [
    "def get_cummean(xs):\n",
    "    return np.cumsum(xs, axis=0) / np.expand_dims(np.arange(1, len(xs) + 1), axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "a8fbb748",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "a8fbb748",
    "outputId": "31f42ad8-04a6-4196-87e9-c434a36b48a1"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.10/dist-packages/numpy/linalg/linalg.py:2556: RuntimeWarning: overflow encountered in multiply\n",
      "  s = (x.conj() * x).real\n"
     ]
    }
   ],
   "source": [
    "x_sol = np.zeros_like(fixed_x_0)\n",
    "\n",
    "eg_one_start_errors = np.zeros(shape=(len(coefs_arr), gamma_steps_cnt, 2 * K + 1))\n",
    "peg_one_start_errors = np.zeros(shape=(len(coefs_arr), gamma_steps_cnt, 2 * K + 1))\n",
    "\n",
    "for i, oracle_func in enumerate(oracle_funcs):\n",
    "    for j, gamma_func in enumerate(gamma_funcs):\n",
    "        eg_results = eg_one_start_results[i, j]\n",
    "        peg_results = peg_one_start_results[i, j]\n",
    "\n",
    "        if i == 1:\n",
    "            eg_results = get_cummean(eg_results)\n",
    "            peg_results = get_cummean(peg_results)\n",
    "\n",
    "        eg_one_start_errors[i, j] = total_arg_dist_error_func(eg_results, x_sol)\n",
    "        peg_one_start_errors[i, j] = total_arg_dist_error_func(peg_results, x_sol)\n",
    "\n",
    "eg_one_step_errors = np.zeros(shape=(len(coefs_arr), x_0_cnt, 2 * K + 1))\n",
    "peg_one_step_errors = np.zeros(shape=(len(coefs_arr), x_0_cnt, 2 * K + 1))\n",
    "\n",
    "for i, oracle_func in enumerate(oracle_funcs):\n",
    "    for j, x_0 in enumerate(x_0s):\n",
    "        eg_results = eg_one_step_results[i, j]\n",
    "        peg_results = peg_one_step_results[i, j]\n",
    "\n",
    "        if i == 1:\n",
    "            eg_results = get_cummean(eg_results)\n",
    "            peg_results = get_cummean(peg_results)\n",
    "\n",
    "        eg_one_step_errors[i, j] = total_arg_dist_error_func(eg_results, x_sol)\n",
    "        peg_one_step_errors[i, j] = total_arg_dist_error_func(peg_results, x_sol)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9b98f403",
   "metadata": {
    "id": "9b98f403"
   },
   "source": [
    "**Построение графиков:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "396c086d",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "id": "396c086d",
    "outputId": "198852a8-041a-4ac2-c3f5-acb735344ddb",
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x1200 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "with sns.axes_style('darkgrid'), sns.color_palette('Paired', n_colors=2 * gamma_steps_cnt) as pal:\n",
    "    plt.figure(figsize=(10, 12))\n",
    "    plt.suptitle('Ошибка от номера итерации, фикс. $x_0$ со всеми координатами $x_' + r'{i, 0}' + ' = {:.2f}$'.format(fixed_x_0_coord))\n",
    "\n",
    "    legend_lines = [\n",
    "        plt.Line2D([0], [0], color='k', lw=4),\n",
    "        plt.Line2D([0], [0], color='k', lw=4, dashes=(2, 2))\n",
    "    ]\n",
    "    legend_labels = [\n",
    "        'EG',\n",
    "        'PEG'\n",
    "    ]\n",
    "\n",
    "    ns = np.arange(K + 1)\n",
    "\n",
    "    for i, gamma in enumerate(gamma_steps):\n",
    "        legend_lines.append(plt.Line2D([0], [0], color=pal[2 * i + 1], lw=4))\n",
    "        legend_labels.append('$\\\\gamma = {:.2f}$'.format(gamma))\n",
    "\n",
    "    for i, lbl in enumerate(coefs_labels):\n",
    "        plt.subplot(2, 1, i + 1)\n",
    "        plt.title(lbl)\n",
    "\n",
    "        for j in range(0, gamma_steps_cnt):\n",
    "            sns.lineplot(x=ns, y=eg_one_start_errors[i, j, ::2], color=pal[2 * j + 1])\n",
    "            sns.lineplot(x=ns, y=peg_one_start_errors[i, j, ::2], color=pal[2 * j], dashes=(2, 2), lw=3)\n",
    "\n",
    "        plt.yscale('log')\n",
    "\n",
    "        plt.xlabel('Номер итерации k')\n",
    "\n",
    "        if i == 1:\n",
    "            plt.ylabel('Логарифм ' + r'$\\|\\overline{X} - x^*\\|$')\n",
    "        else:\n",
    "            plt.ylabel('Логарифм ' + r'$\\|X_k - x^*\\|$')\n",
    "\n",
    "        plt.legend(legend_lines, legend_labels, handlelength=3)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "7a00f133",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "id": "7a00f133",
    "outputId": "40382464-af2d-4cc5-f70e-0ad548ac5b5c"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x1200 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "with sns.axes_style('darkgrid'), sns.color_palette('viridis', n_colors=2 * x_0_cnt) as pal:\n",
    "    plt.figure(figsize=(12, 12))\n",
    "    plt.suptitle('Ошибка от номера итерации, фикс. $\\\\gamma = {}$'.format(fixed_gamma_step))\n",
    "\n",
    "    legend_lines = [\n",
    "        plt.Line2D([0], [0], color='k', lw=4),\n",
    "        plt.Line2D([0], [0], color='k', lw=4, dashes=(2, 2))\n",
    "    ]\n",
    "    legend_labels = [\n",
    "        'EG',\n",
    "        'PEG'\n",
    "    ]\n",
    "\n",
    "    ns = np.arange(K + 1)\n",
    "\n",
    "    for i, x_0_coord in enumerate(x_0_coords):\n",
    "        legend_lines.append(plt.Line2D([0], [0], color=pal[2 * i + 1], lw=4))\n",
    "        legend_labels.append(r'$x_{i, 0} = ' + '{:.2f}$'.format(x_0_coord))\n",
    "\n",
    "    ylims = [(None, None), (10 ** -2, 10 ** 3)]\n",
    "\n",
    "    for i, (lbl, ylim) in enumerate(zip(coefs_labels, ylims)):\n",
    "        plt.subplot(2, 1, i + 1)\n",
    "        plt.title(lbl)\n",
    "\n",
    "        for j in range(0, x_0_cnt):\n",
    "            sns.lineplot(x=ns, y=eg_one_step_errors[i, j, ::2], color=pal[2 * j + 1])\n",
    "            sns.lineplot(x=ns, y=peg_one_step_errors[i, j, ::2], color=pal[2 * j], dashes=(2, 2), lw=3)\n",
    "\n",
    "        plt.yscale('log')\n",
    "        plt.ylim(ylim)\n",
    "\n",
    "        plt.xlabel('Номер итерации k')\n",
    "\n",
    "        if i == 1:\n",
    "            plt.ylabel('Логарифм ' + r'$\\|\\overline{X} - x^*\\|$')\n",
    "        else:\n",
    "            plt.ylabel('Логарифм ' + r'$\\|X_k - x^*\\|$')\n",
    "\n",
    "        plt.legend(legend_lines, legend_labels, handlelength=3)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ca6254c4",
   "metadata": {
    "id": "ca6254c4"
   },
   "source": [
    "**Дополнительные выводы:**\n",
    "1. Сходимость в строго монотонном случае не зависит от расстояния до ответа\n",
    "2. PEG не особо лучше EG с точки зрения сходимости. В нестрого монотонном случае разница вообще не наблюдается, а в строго монотонном она незначительна для разумной точности (около $10^{-18}$) и также требует большой шаг\n",
    "3. В нестрого монотонном случае сходимость может быть значительно медленнее (разница в 10-20 порядков точности эргодической точки к последней итерации)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "383e175b",
   "metadata": {
    "id": "383e175b"
   },
   "source": [
    "## Затронутая при анализе литература\n",
    "\n",
    "1. https://arxiv.org/abs/1908.08465\n",
    "2. https://arxiv.org/abs/2006.08141"
   ]
  }
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