Formatowanie notesów do lab. 1 i 2

This commit is contained in:
Paweł Skórzewski 2022-10-14 11:38:56 +02:00
parent 8f1331c439
commit e5c9192df3
2 changed files with 250 additions and 262 deletions

View File

@ -47,13 +47,13 @@
}
],
"source": [
"zdanie = 'tracz tarł tarcicę tak takt w takt jak takt w takt tarcicę tartak tarł'\n",
"zdanie = \"tracz tarł tarcicę tak takt w takt jak takt w takt tarcicę tartak tarł\"\n",
"wyrazy = zdanie.split()\n",
"dlugosci_wyrazow = []\n",
"for wyraz in wyrazy:\n",
" dlugosci_wyrazow.append(len(wyraz))\n",
"\n",
"print(dlugosci_wyrazow)"
"print(dlugosci_wyrazow)\n"
]
},
{
@ -77,11 +77,11 @@
}
],
"source": [
"zdanie = 'tracz tarł tarcicę tak takt w takt jak takt w takt tarcicę tartak tarł'\n",
"zdanie = \"tracz tarł tarcicę tak takt w takt jak takt w takt tarcicę tartak tarł\"\n",
"wyrazy = zdanie.split()\n",
"dlugosci_wyrazow = [len(wyraz) for wyraz in wyrazy]\n",
"\n",
"print(dlugosci_wyrazow)"
"print(dlugosci_wyrazow)\n"
]
},
{
@ -105,19 +105,19 @@
}
],
"source": [
"zdanie = 'tracz tarł tarcicę tak takt w takt jak takt w takt tarcicę tartak tarł'\n",
"zdanie = \"tracz tarł tarcicę tak takt w takt jak takt w takt tarcicę tartak tarł\"\n",
"wyrazy = zdanie.split()\n",
"\n",
"# Ta konstrukcja:\n",
"dlugosci_wyrazow = []\n",
"for wyraz in wyrazy:\n",
" if wyraz != 'takt':\n",
" if wyraz != \"takt\":\n",
" dlugosci_wyrazow.append(wyraz)\n",
"\n",
"# ...jest równoważna tej jednolinijkowej:\n",
"dlugosci_wyrazow = [len(wyraz) for wyraz in wyrazy if wyraz != 'takt']\n",
"dlugosci_wyrazow = [len(wyraz) for wyraz in wyrazy if wyraz != \"takt\"]\n",
"\n",
"print(dlugosci_wyrazow)"
"print(dlugosci_wyrazow)\n"
]
},
{
@ -149,9 +149,9 @@
}
],
"source": [
"napis = 'abcde'\n",
"napis = \"abcde\"\n",
"print(napis[0]) # 'a'\n",
"print(napis[4]) # 'e'"
"print(napis[4]) # 'e'\n"
]
},
{
@ -177,10 +177,10 @@
}
],
"source": [
"napis = 'abcde'\n",
"napis = \"abcde\"\n",
"print(napis[-1]) # 'e' („ostatni”)\n",
"print(napis[-2]) # 'd' („drugi od końca”)\n",
"print(napis[-5]) # 'a' („piąty od końca”)"
"print(napis[-5]) # 'a' („piąty od końca”)\n"
]
},
{
@ -210,14 +210,18 @@
}
],
"source": [
"napis = 'abcde'\n",
"napis = \"abcde\"\n",
"print(napis[1:4]) # 'bcd' („znaki od 1. włącznie do 4. wyłącznie”)\n",
"print(napis[1:2]) # 'b' (to samo co `napis[1]`)\n",
"print(napis[-3:-1]) # 'cd' (kroić można też stosując indeksowanie od końca)\n",
"print(napis[1:-1]) # 'bcd' (możemy nawet mieszać te dwa sposoby indeksowania)\n",
"print(napis[3:]) # 'de' (jeżeli koniec przedziału nie jest podany, to kroimy do samego końca łańcucha)\n",
"print(napis[:3]) # 'abc' (jeżeli początek przedziału nie jest podany, to kroimy od początku łańcucha)\n",
"print(napis[:]) # 'abcde' (kopia całego napisu)"
"print(\n",
" napis[3:]\n",
") # 'de' (jeżeli koniec przedziału nie jest podany, to kroimy do samego końca łańcucha)\n",
"print(\n",
" napis[:3]\n",
") # 'abc' (jeżeli początek przedziału nie jest podany, to kroimy od początku łańcucha)\n",
"print(napis[:]) # 'abcde' (kopia całego napisu)\n"
]
},
{
@ -268,7 +272,7 @@
"import numpy as np\n",
"\n",
"x = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])\n",
"print(x)"
"print(x)\n"
]
},
{
@ -295,7 +299,7 @@
}
],
"source": [
"x.shape"
"x.shape\n"
]
},
{
@ -315,7 +319,7 @@
}
],
"source": [
"x.sum(axis=0)"
"x.sum(axis=0)\n"
]
},
{
@ -335,7 +339,7 @@
}
],
"source": [
"x.mean(axis=1)"
"x.mean(axis=1)\n"
]
},
{
@ -362,7 +366,7 @@
}
],
"source": [
"np.arange(10)"
"np.arange(10)\n"
]
},
{
@ -382,7 +386,7 @@
}
],
"source": [
"np.arange(5, 10)"
"np.arange(5, 10)\n"
]
},
{
@ -402,7 +406,7 @@
}
],
"source": [
"np.arange(5, 10, 0.5)"
"np.arange(5, 10, 0.5)\n"
]
},
{
@ -434,7 +438,7 @@
"x = np.arange(1, 13)\n",
"print(x)\n",
"y = x.reshape(3, 4)\n",
"print(y)"
"print(y)\n"
]
},
{
@ -459,7 +463,7 @@
],
"source": [
"x = np.linspace(0, 5, 5)\n",
"print(x)"
"print(x)\n"
]
},
{
@ -520,7 +524,7 @@
}
],
"source": [
"help(np.shape)"
"help(np.shape)\n"
]
},
{
@ -552,8 +556,8 @@
"x = np.array([0.1, 0.2, 0.3])\n",
"print(x, \"- typ: \", x.dtype)\n",
"\n",
"x = np.array([1, 2, 3], dtype='float64')\n",
"print(x, \"- typ: \", x.dtype)"
"x = np.array([1, 2, 3], dtype=\"float64\")\n",
"print(x, \"- typ: \", x.dtype)\n"
]
},
{
@ -580,7 +584,7 @@
],
"source": [
"x = np.zeros([3, 4])\n",
"print(x)"
"print(x)\n"
]
},
{
@ -600,7 +604,7 @@
],
"source": [
"x = np.ones([3, 4])\n",
"print(x)"
"print(x)\n"
]
},
{
@ -635,7 +639,7 @@
"\n",
"a = np.array([3, 4, 5])\n",
"b = np.ones(3)\n",
"print(a - b)"
"print(a - b)\n"
]
},
{
@ -661,7 +665,7 @@
],
"source": [
"a = np.array([[1, 2], [3, 4]])\n",
"print(a)"
"print(a)\n"
]
},
{
@ -680,7 +684,7 @@
],
"source": [
"b = np.array([[1, 2], [3, 4]])\n",
"print(b)"
"print(b)\n"
]
},
{
@ -701,7 +705,7 @@
}
],
"source": [
"a * b # mnożenie element po elemencie"
"a * b # mnożenie element po elemencie\n"
]
},
{
@ -722,7 +726,7 @@
}
],
"source": [
"np.dot(a,b) # mnożenie macierzowe"
"np.dot(a, b) # mnożenie macierzowe\n"
]
},
{
@ -743,7 +747,7 @@
}
],
"source": [
"np.matmul(a,b) # mnożenie macierzowe"
"np.matmul(a, b) # mnożenie macierzowe\n"
]
},
{
@ -771,9 +775,9 @@
}
],
"source": [
"a = np.zeros((2, 2), dtype='float')\n",
"a = np.zeros((2, 2), dtype=\"float\")\n",
"a += 5\n",
"a"
"a\n"
]
},
{
@ -795,7 +799,7 @@
],
"source": [
"a *= 5\n",
"a"
"a\n"
]
},
{
@ -816,7 +820,7 @@
}
],
"source": [
"a + a"
"a + a\n"
]
},
{
@ -846,7 +850,7 @@
"a = np.array([1, 2, 3])\n",
"b = np.array([4, 5, 6])\n",
"c = np.array([7, 8, 9])\n",
"np.hstack([a, b, c])"
"np.hstack([a, b, c])\n"
]
},
{
@ -870,7 +874,7 @@
}
],
"source": [
"np.vstack([a, b, c])"
"np.vstack([a, b, c])\n"
]
},
{
@ -898,7 +902,7 @@
],
"source": [
"x = np.arange(1, 5)\n",
"np.sqrt(x) * np.pi"
"np.sqrt(x) * np.pi\n"
]
},
{
@ -918,7 +922,7 @@
}
],
"source": [
"2**4"
"2**4\n"
]
},
{
@ -938,7 +942,7 @@
}
],
"source": [
"np.power(2, 4)"
"np.power(2, 4)\n"
]
},
{
@ -958,7 +962,7 @@
}
],
"source": [
"np.log(np.e)"
"np.log(np.e)\n"
]
},
{
@ -979,7 +983,7 @@
],
"source": [
"x = np.arange(5)\n",
"x.max() - x.min()"
"x.max() - x.min()\n"
]
},
{
@ -1014,7 +1018,7 @@
],
"source": [
"a = np.arange(10)\n",
"a[2:4]"
"a[2:4]\n"
]
},
{
@ -1034,7 +1038,7 @@
}
],
"source": [
"a[:10:2]"
"a[:10:2]\n"
]
},
{
@ -1054,7 +1058,7 @@
}
],
"source": [
"a[::-1]"
"a[::-1]\n"
]
},
{
@ -1084,7 +1088,7 @@
],
"source": [
"x = np.arange(12).reshape(3, 4)\n",
"x"
"x\n"
]
},
{
@ -1104,7 +1108,7 @@
}
],
"source": [
"x[2, 3]"
"x[2, 3]\n"
]
},
{
@ -1124,7 +1128,7 @@
}
],
"source": [
"x[:, 1]"
"x[:, 1]\n"
]
},
{
@ -1144,7 +1148,7 @@
}
],
"source": [
"x[1, :]"
"x[1, :]\n"
]
},
{
@ -1165,7 +1169,7 @@
}
],
"source": [
"x[1:3, :]"
"x[1:3, :]\n"
]
},
{
@ -1200,7 +1204,7 @@
],
"source": [
"a = np.array([1, 1, 1, 2, 2, 2, 3, 3, 3])\n",
"a[a > 1]"
"a[a > 1]\n"
]
},
{
@ -1220,7 +1224,7 @@
}
],
"source": [
"a[a == 3]"
"a[a == 3]\n"
]
},
{
@ -1240,7 +1244,7 @@
}
],
"source": [
"np.where(a < 3)"
"np.where(a < 3)\n"
]
},
{
@ -1260,7 +1264,7 @@
}
],
"source": [
"np.where(a < 3)[0]"
"np.where(a < 3)[0]\n"
]
},
{
@ -1280,7 +1284,7 @@
}
],
"source": [
"np.where(a > 9)"
"np.where(a > 9)\n"
]
},
{
@ -1307,7 +1311,7 @@
],
"source": [
"for row in x:\n",
" print(row)"
" print(row)\n"
]
},
{
@ -1336,7 +1340,7 @@
],
"source": [
"for element in x.flat:\n",
" print(element) "
" print(element)\n"
]
},
{
@ -1363,7 +1367,7 @@
}
],
"source": [
"np.random.randint(0, 10, 5)"
"np.random.randint(0, 10, 5)\n"
]
},
{
@ -1383,7 +1387,7 @@
}
],
"source": [
"np.random.normal(0, 1, 5) "
"np.random.normal(0, 1, 5)\n"
]
},
{
@ -1403,7 +1407,7 @@
}
],
"source": [
"np.random.uniform(0, 2, 5)"
"np.random.uniform(0, 2, 5)\n"
]
},
{
@ -1453,7 +1457,7 @@
"import numpy as np\n",
"\n",
"x = np.array([[1, 2, 3]]).T\n",
"x.shape"
"x.shape\n"
]
},
{
@ -1474,7 +1478,7 @@
],
"source": [
"xt = x.T\n",
"xt.shape"
"xt.shape\n"
]
},
{
@ -1512,7 +1516,7 @@
],
"source": [
"x = np.array([[3, 4, 5, 6]]).T\n",
"x"
"x\n"
]
},
{
@ -1544,7 +1548,7 @@
],
"source": [
"x = np.array([[3, 4, 5, 6]])\n",
"x"
"x\n"
]
},
{
@ -1571,7 +1575,7 @@
],
"source": [
"x = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9]).reshape(3, 3)\n",
"print(x)"
"print(x)\n"
]
},
{
@ -1591,7 +1595,7 @@
],
"source": [
"y = np.array([4, 6, 3, 8, 7, 1, 3, 0, 3]).reshape(3, 3)\n",
"print(y)"
"print(y)\n"
]
},
{
@ -1601,7 +1605,7 @@
"outputs": [],
"source": [
"X = np.matrix(x)\n",
"Y = np.matrix(y)"
"Y = np.matrix(y)\n"
]
},
{
@ -1620,7 +1624,7 @@
}
],
"source": [
"print(x * y) # Tablice np.array mnożone są element po elemencie"
"print(x * y) # Tablice np.array mnożone są element po elemencie\n"
]
},
{
@ -1641,7 +1645,7 @@
}
],
"source": [
"print(X * Y) # Macierze np.matrix mnożone są macierzowo"
"print(X * Y) # Macierze np.matrix mnożone są macierzowo\n"
]
},
{
@ -1660,7 +1664,7 @@
}
],
"source": [
"print(np.matmul(x, y))"
"print(np.matmul(x, y))\n"
]
},
{
@ -1688,7 +1692,7 @@
],
"source": [
"a = np.array([[3, -9], [2, 5]])\n",
"np.linalg.det(a)"
"np.linalg.det(a)\n"
]
},
{
@ -1717,7 +1721,7 @@
],
"source": [
"A = np.array([[-4, -2], [5, 5]])\n",
"A"
"A\n"
]
},
{
@ -1739,7 +1743,7 @@
],
"source": [
"invA = np.linalg.inv(A)\n",
"invA"
"invA\n"
]
},
{
@ -1760,7 +1764,7 @@
}
],
"source": [
"np.round(np.dot(A, invA))"
"np.round(np.dot(A, invA))\n"
]
},
{
@ -1797,7 +1801,7 @@
],
"source": [
"a = np.diag((1, 2, 3))\n",
"a"
"a\n"
]
},
{
@ -1819,7 +1823,7 @@
"source": [
"w, v = np.linalg.eig(a)\n",
"print(w) # wartości własne\n",
"print(v) # wektory własne"
"print(v) # wektory własne\n"
]
},
{
@ -1884,7 +1888,7 @@
"import torch\n",
"\n",
"x = torch.tensor([[1, 2, 3], [4, 5, 6], [7, 8, 9]])\n",
"print(x)"
"print(x)\n"
]
},
{
@ -1919,7 +1923,7 @@
"# Wymiary (rozmiar) tensora\n",
"\n",
"print(x.shape)\n",
"print(x.size()) # Można użyć `size()` zamiast `shape`"
"print(x.size()) # Można użyć `size()` zamiast `shape`\n"
]
},
{
@ -1967,7 +1971,7 @@
],
"source": [
"x = torch.zeros([3, 4])\n",
"print(x)"
"print(x)\n"
]
},
{
@ -1987,7 +1991,7 @@
],
"source": [
"x = torch.ones([3, 4])\n",
"print(x)"
"print(x)\n"
]
},
{
@ -2007,7 +2011,7 @@
],
"source": [
"x = torch.rand([3, 4])\n",
"print(x)"
"print(x)\n"
]
},
{
@ -2046,7 +2050,9 @@
"for i, row in enumerate(x):\n",
" print(f\"\\nWiersz {i}:\")\n",
" for element in row:\n",
" print(element.item()) # `item()` zamienia jednoelementowy (bezwymiarowy) tensor na liczbę"
" print(\n",
" element.item()\n",
" ) # `item()` zamienia jednoelementowy (bezwymiarowy) tensor na liczbę\n"
]
},
{
@ -2081,7 +2087,7 @@
"print(B)\n",
"\n",
"C = torch.rand([4, 2])\n",
"print(C)"
"print(C)\n"
]
},
{
@ -2114,7 +2120,7 @@
"print(A + B)\n",
"print(A - B)\n",
"print(A * B)\n",
"print(A / B)"
"print(A / B)\n"
]
},
{
@ -2135,7 +2141,7 @@
"source": [
"# Mnożenie macierzowe\n",
"\n",
"print(torch.matmul(A, C))"
"print(torch.matmul(A, C))\n"
]
},
{
@ -2169,7 +2175,7 @@
"print(A)\n",
"\n",
"A_numpy = A.numpy()\n",
"print(A_numpy)"
"print(A_numpy)\n"
]
},
{
@ -2197,7 +2203,7 @@
"print(X)\n",
"\n",
"X_pytorch = torch.from_numpy(X)\n",
"print(X_pytorch)"
"print(X_pytorch)\n"
]
},
{

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