Pythonã«ãããã¼ã¿åæå ¥éââNumPyãpandasã使ã£ããã¼ã¿å¦ç ãèªãã§ãã¦ãããããããªãã£ãç®æããã£ãã®ã§ã¡ã¢ã numpyã®argsort()ã®åãã«ã¤ãã¦ã§ãã http://docs.scipy.org/doc/numpy/reference/generated/numpy.argsort.html >>> x = np.array([3, 1, 2]) >>> np.argsort(x) array([1, 2, 0]) ããã¥ã¡ã³ãã«ããã°ãargsort()ã¯ãã½ã¼ãçµæã®é åã®ã¤ã³ããã¯ã¹ãè¿ãã¨ã®ãã¨ã®ããã§ããã ããã®æå³ãå½åããããããªãã£ãã®ã§å®éã«åããã¦ç¢ºèªãã¦ã¿ã¾ããã ãã¨ã®é åã¯ã[3, 1, 2]ã¨ãªã£ã¦ãããããããã®ã¤ã³ããã¯ã¹ã¯ã å·¦ãã0(対å¿ããå¤ã¯3), 1(対å¿ããå¤ã¯1), 2(対å¿ããå¤ã¯2)ã¨ãªãã¾ãã 対å¿ã
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æ¦è¦ loadtxtã¨genfromtxtã§ãã¡ã¤ã«ãããã¼ã¿ãèªã¿è¾¼ãã å人çã«ä»ã®è¨èªã§åºåãä»ãã¡ã¤ã«ã¨é£æºãã¦ä½¿ããã¨ãå¤ãã®ã§ããã®ãããã®å¦çã¯ãã使ãã csv/tsvã®èªã¿è¾¼ã¿ csvèªã¿è¾¼ã¿ã import numpy as np data = np.loadtxt("foo.csv",delimiter=",") ãããè¡ãé£ã°ããskiprowsãæå®ã data = np.loadtxt("foo.csv",delimiter=",", skiprows=1) tsvã®èªã¿è¾¼ã¿ã data = np.loadtxt("foo.tsv",delimiter="\t") åãæå®ãã¦èªã¿è¾¼ã¿ãusecolsæå®ãä¸è¨ã¯1,2,4åç®ãèªãã data = np.loadtxt("bar.csv",delimiter="\t", usecols=(0,1,3)) loa
Pythonã§ä¸çªæåã§æ®åãã¦ããã©ã¤ãã©ãªã¨è¨ã£ã¦ãéè¨ã§ã¯ãªããNumpyãã®è¦æ¸ãã§ããããªãå¤æ©è½ãªæ°å¤è¨ç®ã©ã¤ãã©ãªã§ãå é¨ã¯Cè¨èªã§è¨è¿°ããã¦ããããè¶ é«éã«åä½ãã¾ãã ãã¯ãã« ãã¯ãã«ã®é·ãï¼æ£è¦å import numpy a = numpy.array([[2,2]]) #ãã¯ãã«ã®é·ã length = numpy.linalg.norm(a) #length=>2.8284271247461903 #ãã¯ãã«ã®æ£è¦å a / numpy.linalg.norm(a) #=>array([[ 0.70710678, 0.70710678]]) å ç©ï¼å¤ç© import numpy v1 = numpy.array((1,0,0)) v2 = numpy.array((0,1,0)) #å ç© numpy.dot(v1,v2) #=> 0 #å¤ç© numpy.cros
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