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6_Function.ipynb 21 kB

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  1. {
  2. "cells": [
  3. {
  4. "cell_type": "markdown",
  5. "metadata": {},
  6. "source": [
  7. "# 函数"
  8. ]
  9. },
  10. {
  11. "cell_type": "markdown",
  12. "metadata": {},
  13. "source": [
  14. "在大部分时候,在一个算法中,语句是不断重复的,一次又一次地执行相同的语句是一项乏味的工作,而且会消耗大量的内存,效率不高。这个时候我们就需要函数。"
  15. ]
  16. },
  17. {
  18. "cell_type": "markdown",
  19. "metadata": {},
  20. "source": [
  21. "这是一个函数的基本语法"
  22. ]
  23. },
  24. {
  25. "cell_type": "markdown",
  26. "metadata": {},
  27. "source": [
  28. "```\n",
  29. "def funcname(arg1, arg2,... argN):\n",
  30. " \n",
  31. " ''' Document String'''\n",
  32. "\n",
  33. " statements\n",
  34. "\n",
  35. "\n",
  36. " return <value>\n",
  37. "```"
  38. ]
  39. },
  40. {
  41. "cell_type": "markdown",
  42. "metadata": {},
  43. "source": [
  44. "将上面的语法理解为,定义了一个名为“funcname”的函数,它接受“arg1,arg2,…argN”的论点。函数被记录为“文档字符串”。函数在执行语句后返回一个“值”。"
  45. ]
  46. },
  47. {
  48. "cell_type": "code",
  49. "execution_count": 1,
  50. "metadata": {},
  51. "outputs": [
  52. {
  53. "name": "stdout",
  54. "output_type": "stream",
  55. "text": [
  56. "Hey Rajath!\n",
  57. "Rajath, How do you do?\n"
  58. ]
  59. }
  60. ],
  61. "source": [
  62. "print(\"Hey Rajath!\")\n",
  63. "print(\"Rajath, How do you do?\")"
  64. ]
  65. },
  66. {
  67. "cell_type": "markdown",
  68. "metadata": {},
  69. "source": [
  70. "不需要每次都写上面的两个语句,可以通过定义一个函数来替换它,这个函数只需一行就能完成任务。\n",
  71. "\n",
  72. "定义一个函数 firstfunc()."
  73. ]
  74. },
  75. {
  76. "cell_type": "code",
  77. "execution_count": 2,
  78. "metadata": {},
  79. "outputs": [],
  80. "source": [
  81. "def firstfunc():\n",
  82. " print(\"Hey Rajath!\")\n",
  83. " print(\"Rajath, How do you do?\")"
  84. ]
  85. },
  86. {
  87. "cell_type": "code",
  88. "execution_count": 7,
  89. "metadata": {},
  90. "outputs": [
  91. {
  92. "name": "stdout",
  93. "output_type": "stream",
  94. "text": [
  95. "Hey Rajath!\n",
  96. "Rajath, How do you do?\n",
  97. "Hey Rajath!\n",
  98. "Rajath, How do you do?\n"
  99. ]
  100. }
  101. ],
  102. "source": [
  103. "firstfunc()\n",
  104. "funca=firstfunc\n",
  105. "funca()"
  106. ]
  107. },
  108. {
  109. "cell_type": "markdown",
  110. "metadata": {},
  111. "source": [
  112. "**firstfunc()** 每一次只打印一个人的消息。我们可以让我们的函数 **firstfunc()** 接受参数,该参数将存储名称然后打印相应地接受名词。为了这样做我们需要像所示的那样在函数内添加一个参数。"
  113. ]
  114. },
  115. {
  116. "cell_type": "code",
  117. "execution_count": 8,
  118. "metadata": {},
  119. "outputs": [],
  120. "source": [
  121. "def firstfunc(username):\n",
  122. " print(\"Hey\", username + '!')\n",
  123. " print(username + ',' ,\"How do you do?\")"
  124. ]
  125. },
  126. {
  127. "cell_type": "code",
  128. "execution_count": 9,
  129. "metadata": {},
  130. "outputs": [
  131. {
  132. "name": "stdout",
  133. "output_type": "stream",
  134. "text": [
  135. "Please enter your name : Willam\n"
  136. ]
  137. }
  138. ],
  139. "source": [
  140. "name1 = input('Please enter your name : ')"
  141. ]
  142. },
  143. {
  144. "cell_type": "markdown",
  145. "metadata": {},
  146. "source": [
  147. "名称“Willam”实际上存储在name1中。我们将这个变量传递给函数**firstfunc()** 作为变量username,因为它是为这个函数定义的变量。即name1作为用户名传递。"
  148. ]
  149. },
  150. {
  151. "cell_type": "code",
  152. "execution_count": 10,
  153. "metadata": {},
  154. "outputs": [
  155. {
  156. "name": "stdout",
  157. "output_type": "stream",
  158. "text": [
  159. "Hey Willam!\n",
  160. "Willam, How do you do?\n"
  161. ]
  162. }
  163. ],
  164. "source": [
  165. "firstfunc(name1)"
  166. ]
  167. },
  168. {
  169. "cell_type": "markdown",
  170. "metadata": {},
  171. "source": [
  172. "让我们通过定义另一个函数**secondfunc()** 来进一步简化它,该函数接受名称并将其存储在一个变量中,然后从函数本身内部调用**firstfunc()**。"
  173. ]
  174. },
  175. {
  176. "cell_type": "code",
  177. "execution_count": 1,
  178. "metadata": {},
  179. "outputs": [],
  180. "source": [
  181. "def firstfunc(username):\n",
  182. " print(\"Hey\", username + '!')\n",
  183. " print(username + ',' ,\"How do you do?\")\n",
  184. "def secondfunc():\n",
  185. " name = input(\"Please enter your name : \")\n",
  186. " firstfunc(name)"
  187. ]
  188. },
  189. {
  190. "cell_type": "code",
  191. "execution_count": 2,
  192. "metadata": {},
  193. "outputs": [
  194. {
  195. "name": "stdout",
  196. "output_type": "stream",
  197. "text": [
  198. "Please enter your name : Tom\n",
  199. "Hey Tom!\n",
  200. "Tom, How do you do?\n"
  201. ]
  202. }
  203. ],
  204. "source": [
  205. "secondfunc()"
  206. ]
  207. },
  208. {
  209. "cell_type": "markdown",
  210. "metadata": {},
  211. "source": [
  212. "## 1. 返回语句"
  213. ]
  214. },
  215. {
  216. "cell_type": "markdown",
  217. "metadata": {},
  218. "source": [
  219. "当函数产生某个值,并且该值必须存储在一个变量中,或者需要返回或返回给主算法进行进一步操作时,使用return语句。"
  220. ]
  221. },
  222. {
  223. "cell_type": "code",
  224. "execution_count": 11,
  225. "metadata": {},
  226. "outputs": [],
  227. "source": [
  228. "def times(x,y):\n",
  229. " z = x*y\n",
  230. " return z"
  231. ]
  232. },
  233. {
  234. "cell_type": "markdown",
  235. "metadata": {},
  236. "source": [
  237. "上面定义的**times()** 函数接受两个参数并返回变量z,该变量包含两个参数的乘积结果。"
  238. ]
  239. },
  240. {
  241. "cell_type": "code",
  242. "execution_count": 12,
  243. "metadata": {},
  244. "outputs": [
  245. {
  246. "name": "stdout",
  247. "output_type": "stream",
  248. "text": [
  249. "20\n"
  250. ]
  251. }
  252. ],
  253. "source": [
  254. "c = times(4,5)\n",
  255. "print(c)"
  256. ]
  257. },
  258. {
  259. "cell_type": "markdown",
  260. "metadata": {},
  261. "source": [
  262. "z值存储在变量c中,可以用于进一步的操作。"
  263. ]
  264. },
  265. {
  266. "cell_type": "markdown",
  267. "metadata": {},
  268. "source": [
  269. "可以在return语句中使用整个语句本身,而不是声明另一个变量,如下所示。"
  270. ]
  271. },
  272. {
  273. "cell_type": "code",
  274. "execution_count": 13,
  275. "metadata": {},
  276. "outputs": [],
  277. "source": [
  278. "def times(x,y):\n",
  279. " '''This multiplies the two input arguments'''\n",
  280. " return x*y"
  281. ]
  282. },
  283. {
  284. "cell_type": "code",
  285. "execution_count": 14,
  286. "metadata": {},
  287. "outputs": [
  288. {
  289. "name": "stdout",
  290. "output_type": "stream",
  291. "text": [
  292. "20\n"
  293. ]
  294. }
  295. ],
  296. "source": [
  297. "c = times(4,5)\n",
  298. "print(c)"
  299. ]
  300. },
  301. {
  302. "cell_type": "markdown",
  303. "metadata": {},
  304. "source": [
  305. "由于现在定义了**times()**,我们可以如上所示记录它。在**help()** 函数下调用**times()** 函数时返回该文档。"
  306. ]
  307. },
  308. {
  309. "cell_type": "code",
  310. "execution_count": 15,
  311. "metadata": {},
  312. "outputs": [
  313. {
  314. "name": "stdout",
  315. "output_type": "stream",
  316. "text": [
  317. "Help on function times in module __main__:\n",
  318. "\n",
  319. "times(x, y)\n",
  320. " This multiplies the two input arguments\n",
  321. "\n"
  322. ]
  323. }
  324. ],
  325. "source": [
  326. "help(times)"
  327. ]
  328. },
  329. {
  330. "cell_type": "code",
  331. "execution_count": 16,
  332. "metadata": {},
  333. "outputs": [],
  334. "source": [
  335. "times?"
  336. ]
  337. },
  338. {
  339. "cell_type": "markdown",
  340. "metadata": {},
  341. "source": [
  342. "也可以返回多个变量,但请记住顺序。"
  343. ]
  344. },
  345. {
  346. "cell_type": "code",
  347. "execution_count": 17,
  348. "metadata": {},
  349. "outputs": [],
  350. "source": [
  351. "eglist = [10,50,30,12,6,8,100]"
  352. ]
  353. },
  354. {
  355. "cell_type": "code",
  356. "execution_count": 19,
  357. "metadata": {},
  358. "outputs": [],
  359. "source": [
  360. "def egfunc(eglist):\n",
  361. " highest = max(eglist)\n",
  362. " lowest = min(eglist)\n",
  363. " first = eglist[0]\n",
  364. " last = eglist[-1]\n",
  365. " return highest,lowest,first,last"
  366. ]
  367. },
  368. {
  369. "cell_type": "markdown",
  370. "metadata": {},
  371. "source": [
  372. "如果调用函数时没有为其分配任何变量,则结果将在一个元组中返回。但是如果变量被提到了,那么结果会以特定的顺序分配给变量,这个顺序在return语句中声明。"
  373. ]
  374. },
  375. {
  376. "cell_type": "code",
  377. "execution_count": 20,
  378. "metadata": {},
  379. "outputs": [
  380. {
  381. "name": "stdout",
  382. "output_type": "stream",
  383. "text": [
  384. "(100, 6, 10, 100)\n"
  385. ]
  386. }
  387. ],
  388. "source": [
  389. "a = egfunc(eglist)\n",
  390. "print(a)"
  391. ]
  392. },
  393. {
  394. "cell_type": "code",
  395. "execution_count": 21,
  396. "metadata": {},
  397. "outputs": [
  398. {
  399. "name": "stdout",
  400. "output_type": "stream",
  401. "text": [
  402. " a = 100 \n",
  403. " b = 6 \n",
  404. " c = 10 \n",
  405. " d = 100\n"
  406. ]
  407. }
  408. ],
  409. "source": [
  410. "a,b,c,d = egfunc(eglist)\n",
  411. "print(' a =',a,'\\n b =',b,'\\n c =',c,'\\n d =',d)"
  412. ]
  413. },
  414. {
  415. "cell_type": "markdown",
  416. "metadata": {},
  417. "source": [
  418. "## 2. 隐式参数"
  419. ]
  420. },
  421. {
  422. "cell_type": "markdown",
  423. "metadata": {},
  424. "source": [
  425. "当一个函数的参数在大多数情况下是常见的或者它是“隐式的”时,使用这个概念。"
  426. ]
  427. },
  428. {
  429. "cell_type": "code",
  430. "execution_count": 25,
  431. "metadata": {},
  432. "outputs": [],
  433. "source": [
  434. "def implicitadd(x,y=3):\n",
  435. " return x+y"
  436. ]
  437. },
  438. {
  439. "cell_type": "markdown",
  440. "metadata": {},
  441. "source": [
  442. "**implicitadd( )** 是一个函数接受两个参数,但大多数时候第一个参数只需要加3。因此,第二个参数被赋值为3。这里第二个参数是隐式的。"
  443. ]
  444. },
  445. {
  446. "cell_type": "markdown",
  447. "metadata": {},
  448. "source": [
  449. "现在,如果在调用**implicitadd()** 函数时没有定义第二个参数,则将其视为3。"
  450. ]
  451. },
  452. {
  453. "cell_type": "code",
  454. "execution_count": 23,
  455. "metadata": {},
  456. "outputs": [
  457. {
  458. "data": {
  459. "text/plain": [
  460. "7"
  461. ]
  462. },
  463. "execution_count": 23,
  464. "metadata": {},
  465. "output_type": "execute_result"
  466. }
  467. ],
  468. "source": [
  469. "implicitadd(4)"
  470. ]
  471. },
  472. {
  473. "cell_type": "markdown",
  474. "metadata": {},
  475. "source": [
  476. "但如果指定了第二个参数,则此值将覆盖分配给该参数的隐式值"
  477. ]
  478. },
  479. {
  480. "cell_type": "code",
  481. "execution_count": 24,
  482. "metadata": {},
  483. "outputs": [
  484. {
  485. "data": {
  486. "text/plain": [
  487. "8"
  488. ]
  489. },
  490. "execution_count": 24,
  491. "metadata": {},
  492. "output_type": "execute_result"
  493. }
  494. ],
  495. "source": [
  496. "implicitadd(4,4)"
  497. ]
  498. },
  499. {
  500. "cell_type": "code",
  501. "execution_count": 20,
  502. "metadata": {},
  503. "outputs": [
  504. {
  505. "data": {
  506. "text/plain": [
  507. "11"
  508. ]
  509. },
  510. "execution_count": 20,
  511. "metadata": {},
  512. "output_type": "execute_result"
  513. }
  514. ],
  515. "source": [
  516. "implicitadd(5, y=6)"
  517. ]
  518. },
  519. {
  520. "cell_type": "markdown",
  521. "metadata": {},
  522. "source": [
  523. "## 3. 任意数量的参数"
  524. ]
  525. },
  526. {
  527. "cell_type": "markdown",
  528. "metadata": {},
  529. "source": [
  530. "如果函数要接受的参数数量未知,则在参数前使用星号。"
  531. ]
  532. },
  533. {
  534. "cell_type": "code",
  535. "execution_count": 29,
  536. "metadata": {},
  537. "outputs": [],
  538. "source": [
  539. "def add_n(*args):\n",
  540. " res = 0\n",
  541. " reslist = []\n",
  542. " for i in args:\n",
  543. " reslist.append(i)\n",
  544. " print(reslist)\n",
  545. " return sum(reslist)"
  546. ]
  547. },
  548. {
  549. "cell_type": "markdown",
  550. "metadata": {},
  551. "source": [
  552. "上面的函数接受任意数量的参数,定义一个列表,并将所有参数附加到该列表中,并返回所有参数的总和。"
  553. ]
  554. },
  555. {
  556. "cell_type": "code",
  557. "execution_count": 30,
  558. "metadata": {},
  559. "outputs": [
  560. {
  561. "name": "stdout",
  562. "output_type": "stream",
  563. "text": [
  564. "[1, 2, 3, 4, 5]\n"
  565. ]
  566. },
  567. {
  568. "data": {
  569. "text/plain": [
  570. "15"
  571. ]
  572. },
  573. "execution_count": 30,
  574. "metadata": {},
  575. "output_type": "execute_result"
  576. }
  577. ],
  578. "source": [
  579. "add_n(1,2,3,4,5)"
  580. ]
  581. },
  582. {
  583. "cell_type": "code",
  584. "execution_count": 26,
  585. "metadata": {},
  586. "outputs": [
  587. {
  588. "name": "stdout",
  589. "output_type": "stream",
  590. "text": [
  591. "[1, 2, 3]\n"
  592. ]
  593. },
  594. {
  595. "data": {
  596. "text/plain": [
  597. "6"
  598. ]
  599. },
  600. "execution_count": 26,
  601. "metadata": {},
  602. "output_type": "execute_result"
  603. }
  604. ],
  605. "source": [
  606. "add_n(1,2,3)"
  607. ]
  608. },
  609. {
  610. "cell_type": "code",
  611. "execution_count": 31,
  612. "metadata": {},
  613. "outputs": [
  614. {
  615. "name": "stdout",
  616. "output_type": "stream",
  617. "text": [
  618. "[30, 10, 20]\n"
  619. ]
  620. },
  621. {
  622. "data": {
  623. "text/plain": [
  624. "60"
  625. ]
  626. },
  627. "execution_count": 31,
  628. "metadata": {},
  629. "output_type": "execute_result"
  630. }
  631. ],
  632. "source": [
  633. "def add_nd(**kwargs):\n",
  634. " res = 0\n",
  635. " reslist = []\n",
  636. " for (k,v) in kwargs.items():\n",
  637. " reslist.append(v)\n",
  638. " print(reslist)\n",
  639. " return sum(reslist)\n",
  640. "\n",
  641. "add_nd(x=10, y=20, c=30)"
  642. ]
  643. },
  644. {
  645. "cell_type": "markdown",
  646. "metadata": {},
  647. "source": [
  648. "## 4. 全局和局部变量"
  649. ]
  650. },
  651. {
  652. "cell_type": "markdown",
  653. "metadata": {},
  654. "source": [
  655. "在函数内部声明的变量是局部变量,在函数外部声明的是全局变量。"
  656. ]
  657. },
  658. {
  659. "cell_type": "code",
  660. "execution_count": 10,
  661. "metadata": {},
  662. "outputs": [],
  663. "source": [
  664. "eg1 = [1,2,3,4,5]"
  665. ]
  666. },
  667. {
  668. "cell_type": "markdown",
  669. "metadata": {},
  670. "source": [
  671. "在下面的函数中,我们将在函数内部声明的列表中追加一个元素。函数内部声明的eg2变量是一个局部变量。"
  672. ]
  673. },
  674. {
  675. "cell_type": "code",
  676. "execution_count": 11,
  677. "metadata": {},
  678. "outputs": [],
  679. "source": [
  680. "def egfunc1():\n",
  681. " eg1 = [1, 2, 3, 4, 5, 7]\n",
  682. " print(\"egfunc1>> eg1: \", eg1)\n",
  683. "\n",
  684. "def egfunc2():\n",
  685. " eg1.append(8)\n",
  686. " print(\"egfunc2>> eg1: \", eg1)\n",
  687. "\n",
  688. "def egfunc3():\n",
  689. " global eg1\n",
  690. " eg1 = [5, 4, 3, 2, 1]\n",
  691. " print(\"egfunc3>> eg1: \", eg1)"
  692. ]
  693. },
  694. {
  695. "cell_type": "code",
  696. "execution_count": 12,
  697. "metadata": {},
  698. "outputs": [
  699. {
  700. "name": "stdout",
  701. "output_type": "stream",
  702. "text": [
  703. "egfunc1>> eg1: [1, 2, 3, 4, 5, 7]\n",
  704. "eg1: [1, 2, 3, 4, 5] \n",
  705. "\n",
  706. "egfunc2>> eg1: [1, 2, 3, 4, 5, 8]\n",
  707. "eg1: [1, 2, 3, 4, 5, 8] \n",
  708. "\n",
  709. "egfunc3>> eg1: [5, 4, 3, 2, 1]\n",
  710. "eg1: [5, 4, 3, 2, 1] \n",
  711. "\n"
  712. ]
  713. }
  714. ],
  715. "source": [
  716. "egfunc1()\n",
  717. "print(\"eg1: \", eg1, \"\\n\")\n",
  718. "\n",
  719. "egfunc2()\n",
  720. "print(\"eg1: \", eg1, \"\\n\")\n",
  721. "\n",
  722. "egfunc3()\n",
  723. "print(\"eg1: \", eg1, \"\\n\")\n"
  724. ]
  725. },
  726. {
  727. "cell_type": "markdown",
  728. "metadata": {},
  729. "source": [
  730. "## 5. Lambda 函数"
  731. ]
  732. },
  733. {
  734. "cell_type": "markdown",
  735. "metadata": {},
  736. "source": [
  737. "这些小函数没有使用任何名称定义,只携带一个表达式,返回其结果。Lambda函数在操作列表时非常方便。这些函数由关键字**lambda**定义,后面跟着变量、冒号和相应的表达式。"
  738. ]
  739. },
  740. {
  741. "cell_type": "code",
  742. "execution_count": 48,
  743. "metadata": {},
  744. "outputs": [],
  745. "source": [
  746. "z = lambda x: x * x"
  747. ]
  748. },
  749. {
  750. "cell_type": "code",
  751. "execution_count": 49,
  752. "metadata": {},
  753. "outputs": [
  754. {
  755. "data": {
  756. "text/plain": [
  757. "64"
  758. ]
  759. },
  760. "execution_count": 49,
  761. "metadata": {},
  762. "output_type": "execute_result"
  763. }
  764. ],
  765. "source": [
  766. "z(8)"
  767. ]
  768. },
  769. {
  770. "cell_type": "code",
  771. "execution_count": 50,
  772. "metadata": {},
  773. "outputs": [
  774. {
  775. "data": {
  776. "text/plain": [
  777. "(6, 8)"
  778. ]
  779. },
  780. "execution_count": 50,
  781. "metadata": {},
  782. "output_type": "execute_result"
  783. }
  784. ],
  785. "source": [
  786. "zz = lambda x, y: (x*y, x**y)\n",
  787. "zz(2, 3)"
  788. ]
  789. },
  790. {
  791. "cell_type": "code",
  792. "execution_count": 51,
  793. "metadata": {},
  794. "outputs": [
  795. {
  796. "data": {
  797. "text/plain": [
  798. "function"
  799. ]
  800. },
  801. "execution_count": 51,
  802. "metadata": {},
  803. "output_type": "execute_result"
  804. }
  805. ],
  806. "source": [
  807. "type(z)"
  808. ]
  809. },
  810. {
  811. "cell_type": "code",
  812. "execution_count": 52,
  813. "metadata": {},
  814. "outputs": [
  815. {
  816. "data": {
  817. "text/plain": [
  818. "function"
  819. ]
  820. },
  821. "execution_count": 52,
  822. "metadata": {},
  823. "output_type": "execute_result"
  824. }
  825. ],
  826. "source": [
  827. "def sqr(x):\n",
  828. " return x*x\n",
  829. "\n",
  830. "type(sqr)"
  831. ]
  832. },
  833. {
  834. "cell_type": "markdown",
  835. "metadata": {},
  836. "source": [
  837. "### 5.1 map"
  838. ]
  839. },
  840. {
  841. "cell_type": "markdown",
  842. "metadata": {},
  843. "source": [
  844. "**map( )** 函数主要执行分别为列表的每个元素定义的函数。"
  845. ]
  846. },
  847. {
  848. "cell_type": "code",
  849. "execution_count": 53,
  850. "metadata": {},
  851. "outputs": [],
  852. "source": [
  853. "list1 = [1,2,3,4,5,6,7,8,9]"
  854. ]
  855. },
  856. {
  857. "cell_type": "code",
  858. "execution_count": 54,
  859. "metadata": {},
  860. "outputs": [
  861. {
  862. "name": "stdout",
  863. "output_type": "stream",
  864. "text": [
  865. "[3, 4, 5, 6, 7, 8, 9, 10, 11]\n"
  866. ]
  867. }
  868. ],
  869. "source": [
  870. "eg = map(lambda x:x+2, list1)\n",
  871. "print(list(eg))"
  872. ]
  873. },
  874. {
  875. "cell_type": "code",
  876. "execution_count": 55,
  877. "metadata": {},
  878. "outputs": [
  879. {
  880. "name": "stdout",
  881. "output_type": "stream",
  882. "text": [
  883. "[1, 4, 9, 16, 25, 36, 49, 64, 81]\n"
  884. ]
  885. }
  886. ],
  887. "source": [
  888. "eg = map(sqr, list1)\n",
  889. "print(list(eg))"
  890. ]
  891. },
  892. {
  893. "cell_type": "markdown",
  894. "metadata": {},
  895. "source": [
  896. "你也可以添加两个列表。"
  897. ]
  898. },
  899. {
  900. "cell_type": "code",
  901. "execution_count": 34,
  902. "metadata": {},
  903. "outputs": [],
  904. "source": [
  905. "list2 = [9,8,7,6,5,4,3,2,1]"
  906. ]
  907. },
  908. {
  909. "cell_type": "code",
  910. "execution_count": 35,
  911. "metadata": {},
  912. "outputs": [
  913. {
  914. "name": "stdout",
  915. "output_type": "stream",
  916. "text": [
  917. "[10, 10, 10, 10, 10, 10, 10, 10, 10]\n"
  918. ]
  919. }
  920. ],
  921. "source": [
  922. "eg2 = map(lambda x,y:x+y, list1,list2)\n",
  923. "print(eg2)"
  924. ]
  925. },
  926. {
  927. "cell_type": "markdown",
  928. "metadata": {},
  929. "source": [
  930. "不仅可以使用lambda函数,还可以使用其他内建函数。"
  931. ]
  932. },
  933. {
  934. "cell_type": "code",
  935. "execution_count": 36,
  936. "metadata": {},
  937. "outputs": [
  938. {
  939. "name": "stdout",
  940. "output_type": "stream",
  941. "text": [
  942. "['10', '10', '10', '10', '10', '10', '10', '10', '10']\n"
  943. ]
  944. }
  945. ],
  946. "source": [
  947. "eg3 = map(str,eg2)\n",
  948. "print(eg3)"
  949. ]
  950. },
  951. {
  952. "cell_type": "markdown",
  953. "metadata": {},
  954. "source": [
  955. "### 5.2 filter"
  956. ]
  957. },
  958. {
  959. "cell_type": "markdown",
  960. "metadata": {},
  961. "source": [
  962. "**filter( )** 函数用于过滤列表中的值。 注意 **filter()** 函数返回一个新列表中的结果。"
  963. ]
  964. },
  965. {
  966. "cell_type": "code",
  967. "execution_count": 56,
  968. "metadata": {},
  969. "outputs": [],
  970. "source": [
  971. "list1 = [1,2,3,4,5,6,7,8,9]"
  972. ]
  973. },
  974. {
  975. "cell_type": "markdown",
  976. "metadata": {},
  977. "source": [
  978. "为了得到小于5的元素。"
  979. ]
  980. },
  981. {
  982. "cell_type": "code",
  983. "execution_count": 57,
  984. "metadata": {},
  985. "outputs": [
  986. {
  987. "name": "stdout",
  988. "output_type": "stream",
  989. "text": [
  990. "[1, 2, 3, 4]\n"
  991. ]
  992. }
  993. ],
  994. "source": [
  995. "res = filter(lambda x:x<5,list1)\n",
  996. "print(list(res))"
  997. ]
  998. },
  999. {
  1000. "cell_type": "markdown",
  1001. "metadata": {},
  1002. "source": [
  1003. "注意当使用**map()** 时会发生什么"
  1004. ]
  1005. },
  1006. {
  1007. "cell_type": "code",
  1008. "execution_count": 58,
  1009. "metadata": {},
  1010. "outputs": [
  1011. {
  1012. "data": {
  1013. "text/plain": [
  1014. "<map at 0x7f72a418c780>"
  1015. ]
  1016. },
  1017. "execution_count": 58,
  1018. "metadata": {},
  1019. "output_type": "execute_result"
  1020. }
  1021. ],
  1022. "source": [
  1023. "map(lambda x:x<5, list1)"
  1024. ]
  1025. },
  1026. {
  1027. "cell_type": "markdown",
  1028. "metadata": {},
  1029. "source": [
  1030. "我们可以得出这样的结论,在**map()** 函数中返回的值为真,在使用**filter()** 函数时将返回特定的元素。"
  1031. ]
  1032. },
  1033. {
  1034. "cell_type": "code",
  1035. "execution_count": 59,
  1036. "metadata": {},
  1037. "outputs": [
  1038. {
  1039. "data": {
  1040. "text/plain": [
  1041. "<filter at 0x7f72a4195240>"
  1042. ]
  1043. },
  1044. "execution_count": 59,
  1045. "metadata": {},
  1046. "output_type": "execute_result"
  1047. }
  1048. ],
  1049. "source": [
  1050. "filter(lambda x:x%4==0,list1)"
  1051. ]
  1052. }
  1053. ],
  1054. "metadata": {
  1055. "kernelspec": {
  1056. "display_name": "Python 3",
  1057. "language": "python",
  1058. "name": "python3"
  1059. },
  1060. "language_info": {
  1061. "codemirror_mode": {
  1062. "name": "ipython",
  1063. "version": 3
  1064. },
  1065. "file_extension": ".py",
  1066. "mimetype": "text/x-python",
  1067. "name": "python",
  1068. "nbconvert_exporter": "python",
  1069. "pygments_lexer": "ipython3",
  1070. "version": "3.6.8"
  1071. }
  1072. },
  1073. "nbformat": 4,
  1074. "nbformat_minor": 1
  1075. }

机器学习越来越多应用到飞行器、机器人等领域,其目的是利用计算机实现类似人类的智能,从而实现装备的智能化与无人化。本课程旨在引导学生掌握机器学习的基本知识、典型方法与技术,通过具体的应用案例激发学生对该学科的兴趣,鼓励学生能够从人工智能的角度来分析、解决飞行器、机器人所面临的问题和挑战。本课程主要内容包括Python编程基础,机器学习模型,无监督学习、监督学习、深度学习基础知识与实现,并学习如何利用机器学习解决实际问题,从而全面提升自我的《综合能力》。