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Session 9 Nerdy Vandheka 21181213
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{
"cells": [
{
"cell_type": "markdown",
"id": "485bb878",
"metadata": {},
"source": [
"# RESUME SESSION 9 NERDY VANDHEKA 21181213"
]
},
{
"cell_type": "markdown",
"id": "e93db7b6",
"metadata": {},
"source": [
"## Bilangan acak dan metode Monte Carlo : Pengenalan dan pemanfaatan sederhananya dalam fisika"
]
},
{
"cell_type": "markdown",
"id": "0cf5774e",
"metadata": {},
"source": [
"### A. BILANGAN ACAK"
]
},
{
"cell_type": "markdown",
"id": "f7eb7fb8",
"metadata": {},
"source": [
"Bilangan acak adalah sebuah bilangan yang dipilih seakan-akan secara kebetulan dari suatu distribusi tertentu sehingga seleksi suatu himpunan besar bilangan-bilangan ini menghasilkan distribusi yang mendasarinya. Bilangan-bilangan tersebut juga perlu saling bebas, sehingga tidak terdapat korelasi di antara bilangan-bilangan berurutan."
]
},
{
"cell_type": "markdown",
"id": "d65f0af5",
"metadata": {},
"source": [
"### B. BILANGAN PSEUDO-ACAK (PSEUDO RANDOM)"
]
},
{
"cell_type": "markdown",
"id": "d78a636a",
"metadata": {},
"source": [
" Merupakan himpunan nilai atau elemen yang acak secara statistik, akan tetapi diturunkan dari sebuah titik awal yang diketahui dan umumnya diulang-ulang lagi dan lagi. Bilangan ini menyediakan nilai-nilai yang diperlukan bagi proses-proses yang membutuhkan keacakan, seperti menghasilkan sinyal uji. Disebut ‘pseudo’ acak karena algoritmanya dapat mengulangi pembangkitan kembali urutan bilangan-bilangan acak, dan sebenarnya tidaklah sepenuhnya acak."
]
},
{
"cell_type": "markdown",
"id": "8bcbf666",
"metadata": {},
"source": [
"### C. BILANGAN ACAK SEBENARNYA"
]
},
{
"cell_type": "markdown",
"id": "abfd79a5",
"metadata": {},
"source": [
" Untuk kualitas tinggi bilangan acak sebenarnya (true random numbers) dapat dibangkitkan menggunakan efek-efek fisika seperti derau termal dalam sebuah dioda atau dari suatu sumber cahaya."
]
},
{
"cell_type": "markdown",
"id": "d76f0a00",
"metadata": {},
"source": [
"### D. ALGORITMA "
]
},
{
"cell_type": "markdown",
"id": "d7f96196",
"metadata": {},
"source": [
"Algoritme khusus tersedia untuk membangkitan bilangan pseudo-acak, yang memiliki sifat statistik terbandingkan, tetapi nilainya tidak dapat diprediksi karena bergantung pada sejumlah nilai-nilai awal (seed)."
]
},
{
"cell_type": "markdown",
"id": "c8bdafdf",
"metadata": {},
"source": [
"### E. LINEAR CONGRUENCE GENERATOR "
]
},
{
"cell_type": "markdown",
"id": "ebd9dab5",
"metadata": {},
"source": [
"Untuk membangkitkan bilangan bulat dalam rentang 0 sampai m–1 dapat digunakan generator linier kongruen. Kelemahannya adalah bila digunakan untuk sistem keamanan dan penyusup mengetahui nilai a, c, m, X0, nilai Xn tertebak.\n",
" Permasalahan fisis seringkali melibatkan integral berdimensi tinggi, seperti misalnya pada integral lintasan (path integrals) dan rata-rata termodinamika (thermodynamics averages)."
]
},
{
"cell_type": "markdown",
"id": "f68e4076",
"metadata": {},
"source": [
"Tugas mandiri\n",
"1. Carilah sumber pustaka daring yang diberikan pada slide-side.\n",
"2. Baca secara ringkas pustaka-pustaka tersebut.\n",
"3. Temukan bagian yang memanfaatkan bilangan acak.\n",
"4. Usulkan aplikasi pengembangan dari sistem-sistem tersebut."
]
},
{
"cell_type": "markdown",
"id": "d936abc6",
"metadata": {},
"source": [
"Sumber Pustaka :\n",
"1. Eric W. Weisstein, \"Random Number“, from MathWorld--A Wolfram Web Resource, url https://mathworld.wolfram.com/RandomNumber.html\n",
"2. pseudo-random numbers“, PCMag Encyclopedia, Ziff Davis, 2022, url https://www.pcmag.com/encyclopedia/term/pseudo-random-numbers\n",
"3. Radosław Cybulski, “Pseudo-random number generator based on linear congruence and delayed Fibonacci method”, Technical Sciences [TechSci], vol 24, no 1, p 331-349, Dec 2021, url https://doi.org/10.31648/ts.7238."
]
},
{
"cell_type": "markdown",
"id": "3af3c9b9",
"metadata": {},
"source": [
" Bilangan acak adalah bilangan yang dipilih seolah-olah secara kebetulan dari suatu distribusi tertentu sehingga pemilihan sejumlah besar bilangan tersebut mereproduksi distribusi yang mendasarinya. Hampir selalu, bilangan-bilangan tersebut juga harus independen, sehingga tidak ada korelasi antar bilangan yang berurutan. Bilangan acak yang dihasilkan komputer terkadang disebut bilangan pseudorandom , sedangkan istilah \"acak\" digunakan untuk keluaran proses fisik yang tidak dapat diprediksi. \n",
" Tidak mungkin menghasilkan rangkaian angka acak yang panjangnya sewenang-wenang dan membuktikan bahwa itu acak. Anehnya, manusia juga sangat sulit menghasilkan serangkaian angka acak, dan program komputer dapat ditulis yang rata-rata memprediksi beberapa angka yang akan ditulis manusia berdasarkan angka sebelumnya. Ada sejumlah metode umum yang digunakan untuk menghasilkan bilangan pseudorandom."
]
},
{
"cell_type": "markdown",
"id": "bf5a56d9",
"metadata": {},
"source": [
" Bilangan pseudo acak merupakan sekumpulan nilai atau elemen yang acak secara statistik, namun berasal dari titik awal yang diketahui dan biasanya diulang terus menerus. Bilangan acak semu memberikan nilai yang diperlukan untuk proses yang memerlukan keacakan, seperti membuat sinyal uji atau untuk menyinkronkan perangkat pengirim dan penerima dalam transmisi spektrum tersebar. Ini disebut acak \"semu\", karena algoritme dapat mengulangi urutannya, dan angka-angkanya tidak sepenuhnya acak."
]
},
{
"cell_type": "markdown",
"id": "47453170",
"metadata": {},
"source": [
"Aplikasi yang mungkin bisa dikembangkan dari sistem sistem tersebut salah satu nya pengaplikasian pada keamanan siber, dimana dapat digunakan untuk menghasilkan kunci kriptografi yang aman dan acak untuk melindungi data sensitif."
]
},
{
"cell_type": "markdown",
"id": "3987700c",
"metadata": {},
"source": [
"## MONTE CARLO INTEGRATION"
]
},
{
"cell_type": "markdown",
"id": "a54cc5c9",
"metadata": {},
"source": [
"Metode Monte Carlo adalah pendekatan statistik yang digunakan untuk memahami sistem fisik atau matematika yang kompleks dengan menggunakan angka-angka yang dihasilkan secara acak sebagai masukan untuk menghasilkan serangkaian solusi. Dengan menjalankan banyak uji coba, kemungkinan solusi tertentu dapat ditentukan dengan membagi berapa kali solusi tersebut dihasilkan dengan jumlah total uji coba. Metode ini banyak diterapkan di berbagai bidang seperti matematika, fisika, biologi, teknik, dan keuangan, terutama dalam situasi di mana pencarian solusi analitik akan memakan waktu terlalu lama."
]
},
{
"cell_type": "markdown",
"id": "f5c9f55c",
"metadata": {},
"source": [
"Average rectangular area adalah metode yang digunakan untuk memperkirakan hasil integral dengan menjumlahkan luas persegi panjang dan kemudian meratakannya. Semakin banyak jumlah panjang yang ditambahkan, rata-ratanya semakin mendekati hasil integral sebenarnya. Teknik ini umumnya digunakan dalam integrasi numerik, khususnya dalam menggambarkan luas area di bawah kurva ketika solusi analitis tidak memungkinkan."
]
},
{
"cell_type": "markdown",
"id": "e0cdf7d3",
"metadata": {},
"source": [
"Basic Monte Carlo estimator melibatkan penggunaan rumus dengan N sebagai jumlah sampel yang digunakan dan <F_N> sebagai perkiraan F menggunakan N sampel. Ini menggunakan angka acak dalam interval dan melibatkan penghitungan perkiraan fungsi atau nilai berdasarkan sampel acak ini. Metode ini merupakan teknik dasar dalam simulasi Monte Carlo untuk mengambil nilai atau menyelesaikan masalah melalui pengambilan sampel statistik."
]
},
{
"cell_type": "markdown",
"id": "72da34dc",
"metadata": {},
"source": [
"Keuntungan:\n",
"1. Kesederhanaan: Metode Monte Carlo beradaptasi dengan baik pada integral multidimensi.\n",
"2. Tidak memihak dan Konsisten: Memberikan hasil yang tidak memihak dan konsisten.\n",
"3. Sifat Paralel: Setiap prosesor dapat bekerja menyelesaikan integrasi secara paralel dengan menangani uji coba acak."
]
},
{
"cell_type": "markdown",
"id": "c3b57efc",
"metadata": {},
"source": [
"Kekurangan:\n",
"1. Tingkat Konvergensi yang Lambat: Metode Monte Carlo memiliki tingkat konvergensi yang lambat.\n",
"2. Evaluasi Varians: Sulit untuk memancarkan varians suatu fungsi dan menentukan kesalahan pendekatan secara akurat."
]
},
{
"cell_type": "markdown",
"id": "7cb9a1ec",
"metadata": {},
"source": [
"Berikut adalah penjelasan singkat tentang fungsi-fungsi yang umum digunakan dalam simulasi Monte Carlo:\n",
"1. Bilangan Acak (Random Numbers):\n",
" Bilangan acak merupakan elemen penting dalam simulasi Monte Carlo. Bilangan ini digunakan untuk mensimulasikan skenario acak dalam model, memungkinkan untuk memperhitungkan berbagai kemungkinan dan menghasilkan perkiraan yang lebih akurat.\n",
"2. Fungsi Linier (Linear Function):\n",
" Fungsi linier memiliki bentuk y = mx + b, di mana m dan b adalah konstanta. Fungsi ini sering digunakan dalam simulasi Monte Carlo untuk memodelkan hubungan proporsional antara dua variabel.\n",
"3. Fungsi Kuadrat (Quadratic Function):\n",
" Fungsi kuadrat memiliki bentuk y = ax^2 + bx + c, di mana a, b, dan c adalah konstanta. Fungsi ini sering digunakan dalam simulasi Monte Carlo untuk memodelkan hubungan non-linier antara dua variabel.\n",
"4. Fungsi Kubik (Cubic Function):\n",
" Fungsi kubik memiliki bentuk y = ax^3 + bx^2 + cx + d, di mana a, b, c, dan d adalah konstanta. Fungsi ini digunakan dalam simulasi Monte Carlo untuk memodelkan hubungan non-linier yang lebih kompleks antara dua variabel.\n",
"5. Fungsi Sinus Kuadrat (Sine Squared Function):\n",
" Fungsi sinus kuadrat memiliki bentuk y = sin^2(x). Fungsi ini sering digunakan dalam simulasi Monte Carlo untuk memodelkan fenomena yang memiliki pola periodik, seperti gelombang atau getaran.\n",
"6. Seperempat Lingkaran (Quarter Circle):\n",
" Seperempat lingkaran adalah area yang dibatasi oleh jari-jari lingkaran dan seperempat keliling lingkaran. Area ini sering digunakan dalam simulasi Monte Carlo sebagai metode integrasi numerik. Dengan mensimulasikan titik-titik acak di dalam seperempat lingkaran, dimungkinkan untuk memperkirakan luas area yang kompleks."
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "e8e278de",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"4 7 2 6 6 8 5 3 5 7 5 7 6 5 7 6 4 6 5 7 3 8 2 3 3 7 6 5 7 4 4 2 7 5 4 7 4 8 5 7 6 5 4 2 7 4 7 6 4 7 7 6 2 4 6 6 2 3 5 8 5 7 4 7 2 4 7 8 8 4 3 5 3 3 8 6 2 4 5 2 6 4 2 7 3 7 6 5 4 2 5 2 4 2 5 6 4 3 2 5 \n",
"\n",
"\n",
"100\n"
]
}
],
"source": [
"#Libraries and packages, random numbers\n",
"import random as rnd\n",
"import matplotlib.pyplot as plt\n",
"\n",
"N = 100\n",
"a = 2\n",
"b = 8\n",
"x = []\n",
"for i in range(N):\n",
" j = rnd.randint(a, b)\n",
" x.append(j)\n",
" print(j, end=' ')\n",
"print('\\n\\n')\n",
"\n",
"print(len(x))"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "c293d29a",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 400x300 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"#Histogram of the random number\n",
"bins = (b - a) + 1\n",
"\n",
"plt.figure(figsize=(4, 3))\n",
"plt.hist(x, range=[a, b + 1], bins=bins)\n",
"plt.xlabel('x')\n",
"plt.ylabel('N')\n",
"plt.xticks(range(a, b + 2))\n",
"plt.yticks(range(0, 26, 2))\n",
"plt.grid()\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"id": "10c1d5a6",
"metadata": {},
"source": [
"LINEAR FUNCTION"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "555e680e",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 400x300 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"#f(x)=3(x-2)+4\n",
"def f(x):\n",
" y = 3*(x - 2) + 4\n",
" return y\n",
"\n",
"y = [f(i) for i in x]\n",
"\n",
"plt.figure(figsize=(4, 3))\n",
"plt.plot(x,y)\n",
"plt.xticks(range(a, b + 2))\n",
"plt.yticks(range(0, 26, 4))\n",
"plt.xlabel('x')\n",
"plt.ylabel('y')\n",
"plt.grid()\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "e3fdcbf4",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 400x300 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"#A rectangular area\n",
"rx = rnd.randint(a, b)\n",
"ry = f(rx)\n",
"xr = [a, b]\n",
"yr = [ry, ry]\n",
"c = '#cfc'\n",
"\n",
"plt.figure(figsize=(4, 3))\n",
"plt.plot(x,y)\n",
"plt.plot(rx, ry, 'o')\n",
"plt.plot(xr, yr, '-')\n",
"plt.fill_between(xr, yr, y2=0, color=c)\n",
"plt.xticks(range(a, b + 2))\n",
"plt.yticks(range(0, 26, 4))\n",
"plt.xlabel('x')\n",
"plt.ylabel('y')\n",
"plt.grid()\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "bc5acf3d",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 500x500 with 6 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"#Some rectangular areas\n",
"c = '#cfc'\n",
"\n",
"plt.figure(figsize=(5, 5))\n",
"for i in range(6):\n",
" rx = rnd.randint(a, b)\n",
" ry = f(rx)\n",
" xr = [a, b]\n",
" yr = [ry, ry]\n",
" \n",
" plt.subplot(2, 3, i+1)\n",
" plt.plot(x,y)\n",
" plt.plot(rx, ry, 'o')\n",
" plt.plot(xr, yr, '-')\n",
" plt.fill_between(xr, yr, y2=0, color=c)\n",
" plt.xticks(range(a, b + 2))\n",
" plt.yticks(range(0, 26, 4))\n",
" plt.xlabel('x')\n",
" plt.ylabel('y')\n",
" plt.grid()\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "7c473f0f",
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"#Numerical (with Monte Carlo) solution\n",
"N2 = 1000\n",
"n = []\n",
"A = []\n",
"AA = 0\n",
"for i in range(1, N2 + 1):\n",
" xi = rnd.randint(a, b)\n",
" fi = f(xi)\n",
" Ai = (b - a) * fi\n",
" \n",
" n.append(i)\n",
" if i == 1:\n",
" AA = Ai\n",
" else:\n",
" AA = (A[i-2] * (i-1) + Ai) / i\n",
" A.append(AA)\n",
"plt.plot([0, N2], [78, 78], 'r-')\n",
"plt.plot(n, A, '-')\n",
"plt.xlabel('n')\n",
"plt.ylabel('A')\n",
"plt.grid()\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"id": "b80eba1f",
"metadata": {},
"source": [
"QUADRATIC FUNCTION"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "32b1f5f3",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 400x300 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"#f(x)=3x^2+2x+1\n",
"def f(x):\n",
" y = 3*x**2 + 2*x + 1\n",
" return y\n",
"\n",
"xx = [*range(a, b + 1)]\n",
"y = [f(i) for i in xx]\n",
"\n",
"plt.figure(figsize=(4, 3))\n",
"plt.plot(xx, y, 'o-')\n",
"plt.xticks(range(a, b + 2))\n",
"plt.xlabel('x')\n",
"plt.ylabel('y')\n",
"plt.grid()\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "8c2c12a9",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 400x300 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"#A rectangular area\n",
"rx = rnd.randint(a, b)\n",
"ry = f(rx)\n",
"xr = [a, b]\n",
"yr = [ry, ry]\n",
"c = '#cfc'\n",
"\n",
"plt.figure(figsize=(4, 3))\n",
"plt.plot(xx,y)\n",
"plt.plot(rx, ry, 'o')\n",
"plt.plot(xr, yr, '-')\n",
"plt.fill_between(xr, yr, y2=0, color=c)\n",
"plt.xticks(range(a, b + 2))\n",
"plt.xlabel('x')\n",
"plt.ylabel('y')\n",
"plt.grid()\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "107e0b08",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 500x500 with 6 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"#Some rectangular areas\n",
"c = '#cfc'\n",
"\n",
"plt.figure(figsize=(5, 5))\n",
"for i in range(6):\n",
" rx = rnd.randint(a, b)\n",
" ry = f(rx)\n",
" xr = [a, b]\n",
" yr = [ry, ry]\n",
" \n",
" plt.subplot(2, 3, i+1)\n",
" plt.plot(xx,y)\n",
" plt.plot(rx, ry, 'o')\n",
" plt.plot(xr, yr, '-')\n",
" plt.fill_between(xr, yr, y2=0, color=c)\n",
" plt.xticks(range(a, b + 2))\n",
" plt.xlabel('x')\n",
" plt.ylabel('y')\n",
" plt.grid()\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"id": "2296b1d4",
"metadata": {},
"source": [
"CUBIC FUNCTION"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "219b2e0f",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 400x300 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"#f(x)=(x-3)(x-5)(x-7)\n",
"def f(x):\n",
" y = (x - 3)*(x - 5)*(x - 7)\n",
" return y\n",
"\n",
"xx = [*range(a, b + 1)]\n",
"y = [f(i) for i in xx]\n",
"\n",
"plt.figure(figsize=(4, 3))\n",
"plt.plot(xx, y, 'o-')\n",
"plt.xticks(range(a, b + 2))\n",
"plt.xlabel('x')\n",
"plt.ylabel('y')\n",
"plt.grid()\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "bb9b9296",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 400x300 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"#A rectangular area\n",
"rx = rnd.randint(a, b)\n",
"ry = f(rx)\n",
"xr = [a, b]\n",
"yr = [ry, ry]\n",
"c = '#cfc'\n",
"y2 = [0, 0]\n",
"\n",
"plt.figure(figsize=(4, 3))\n",
"plt.plot(xx,y)\n",
"plt.plot(rx, ry, 'o')\n",
"plt.plot(xr, yr, '-')\n",
"if yr[0] > 0:\n",
" plt.fill_between(xr, yr, y2, color=c)\n",
"else:\n",
" plt.fill_between(xr, y2, yr, color=c)\n",
"plt.xticks(range(a, b + 2))\n",
"plt.xlabel('x')\n",
"plt.ylabel('y')\n",
"plt.grid()\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "51d36cf5",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 500x500 with 6 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"#Some rectangular areas\n",
"c = '#cfc'\n",
"\n",
"plt.figure(figsize=(5, 5))\n",
"for i in range(6):\n",
" rx = rnd.randint(a, b)\n",
" ry = f(rx)\n",
" xr = [a, b]\n",
" yr = [ry, ry]\n",
" y2 = [0, 0]\n",
" \n",
" plt.subplot(2, 3, i+1)\n",
" plt.plot(xx,y)\n",
" plt.plot(rx, ry, 'o')\n",
" plt.plot(xr, yr, '-')\n",
" \n",
" if yr[0] > 0:\n",
" plt.fill_between(xr, yr, y2, color=c)\n",
" else:\n",
" plt.fill_between(xr, y2, yr, color=c)\n",
" \n",
" plt.xticks(range(a, b + 2))\n",
" plt.xlabel('x')\n",
" plt.ylabel('y')\n",
" plt.grid()\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "12e7da50",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.5"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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