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nextbigthing id:nextbigthing

numpyã«é–¢ã™ã‚‹nextbigthingã®ãƒ–ãƒƒã‚¯ãƒžãƒ¼ã‚¯ (7)

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æ•°å¼ã‚’numpyã«è½ã¨ã—ã“ã‚€ã‚³ãƒ„
Tokyo.SciPy #2 ã«ã¦ç™ºè¡¨ã—ãŸã€æ•°å¼(ã‚ã‚‹ã„ã¯æ•°å¼å…¥ã‚Šã®ã‚¢ãƒ«ã‚´ãƒªã‚ºãƒ )ã‹ã‚‰å®Ÿè£…ã«è½ã¨ã™å ´åˆã€ä½•ã«æ°—ã‚’ã¤ã‘ã‚‹ã®ã‹ã€ã©ã†è€ƒãˆã‚Œã°ã„ã„ã®ã‹ã€ã¨ã„ã†ãŠè©±ã€‚ å¯¾è±¡ã¯ã€ã©ã†ã‚„ã£ã¦æ•°å¼ã‚’ãƒ—ãƒã‚°ãƒ©ãƒ ã™ã‚Œã°ã„ã„ã‹ã‚ˆãã‚ã‹ã‚‰ãªã„äººã€ã¡ã‚‡ã£ã¨ã‚„ã‚„ã“ã—ã„æ•°å¼ã«ãªã‚‹ã¨å››è‹¦å…«è‹¦ã—ã¦ã—ã¾ã„ã€ã‚³ãƒ¼ãƒ‰ã«è½ã¨ã™ã®ã«ã™ã”ãæ™‚é–“ãŒã‹ã‹ã£ã¦ã—ã¾ã†äººã€ãªã©ã€‚ ã“ã“ã§ã¯å®Ÿè¡Œé€Ÿåº¦ã«ã¤ã„ã¦ã¯ã²ã¨ã¾ãšãŠã„ã¨ã„ã¦ã€ç°¡æ½”ã§é–“é•ã„ã«ãã„ã€ã¡ã‚ƒã‚“ã¨å‹•ãã‚³ãƒ¼ãƒ‰ã‚’æ›¸ãã“ã¨ã‚’ç›®æ¨™ã«ã—ã¦ã„ã¾ã™ã€‚ Read less
nextbigthing 2013/03/21
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numpy

python
ãƒªãƒ³ã‚¯
é«˜é€Ÿæ•°å€¤è¨ˆç®—ãƒ©ã‚¤ãƒ–ãƒ©ãƒªã€ŒNumpyã€è¦šæ›¸ã - Pashangoâ€™s Blog
Pythonã§ä¸€ç•ªæœ‰åã§æ™®åŠã—ã¦ã„ã‚‹ãƒ©ã‚¤ãƒ–ãƒ©ãƒªã¨è¨€ã£ã¦ã‚‚éŽè¨€ã§ã¯ãªã„ã€ŒNumpyã€ã®è¦šæ›¸ãã§ã™ã€‚ã‹ãªã‚Šå¤šæ©Ÿèƒ½ãªæ•°å€¤è¨ˆç®—ãƒ©ã‚¤ãƒ–ãƒ©ãƒªã§ã€å†…éƒ¨ã¯Cè¨€èªžã§è¨˜è¿°ã•ã‚Œã¦ã„ã‚‹ãŸã‚è¶…é«˜é€Ÿã«å‹•ä½œã—ã¾ã™ã€‚ ãƒ™ã‚¯ãƒˆãƒ« ãƒ™ã‚¯ãƒˆãƒ«ã®é•·ã•ï¼†æ£è¦åŒ– import numpy a = numpy.array([[2,2]]) #ãƒ™ã‚¯ãƒˆãƒ«ã®é•·ã• length = numpy.linalg.norm(a) #length=>2.8284271247461903 #ãƒ™ã‚¯ãƒˆãƒ«ã®æ£è¦åŒ– a / numpy.linalg.norm(a) #=>array([[ 0.70710678, 0.70710678]]) å†…ç©ï¼†å¤–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
nextbigthing 2013/03/17
Python

numpy
ãƒªãƒ³ã‚¯
ç§è¨³ã€Œæš«å®šçš„ NumPy ãƒãƒ¥ãƒ¼ãƒˆãƒªã‚¢ãƒ«ã€ - naoya_t@hatenablog
# åŽŸæ–‡ï¼šhttp://www.scipy.org/Tentative_NumPy_Tutorial ã“ã®ãƒãƒ¥ãƒ¼ãƒˆãƒªã‚¢ãƒ«ã‚’èªã‚€å‰ã«ã€Pythonã«ã¤ã„ã¦ã¡ã‚‡ã£ã¨ã¯çŸ¥ã£ã¦ã„ã‚‹ã¹ãã ã€‚è¨˜æ†¶ã‚’ãƒªãƒ•ãƒ¬ãƒƒã‚·ãƒ¥ã—ãŸã„ã¨æ€ã†ãªã‚‰ã€Pythonãƒãƒ¥ãƒ¼ãƒˆãƒªã‚¢ãƒ«ã‚’è¦‹ã¦ãã‚‹ãŒã„ã„ã€‚ ã“ã®ãƒãƒ¥ãƒ¼ãƒˆãƒªã‚¢ãƒ«ã«å‡ºã¦ãã‚‹ä¾‹ã‚’è©¦ã—ãŸã„ãªã‚‰ã€ã‚ãªãŸã®PCã«å°‘ãªãã¨ã‚‚ Python NumPy ã¯ã‚¤ãƒ³ã‚¹ãƒˆãƒ¼ãƒ«ã•ã‚Œã¦ã„ã‚‹ã¹ãã§ã€ä»–ã«å…¥ã£ã¦ã‚‹ã¨ä¾¿åˆ©ãªã®ã¯ï¼š ipython ã¯æ‹¡å¼µã•ã‚ŒãŸã‚¤ãƒ³ã‚¿ãƒ©ã‚¯ãƒ†ã‚£ãƒ–ãªPythonã‚·ã‚§ãƒ«ã§ã€NumPyã®æ©Ÿèƒ½ã‚’æŽ¢æ¤œã™ã‚‹ã®ã«ã¨ã¦ã‚‚ä¾¿åˆ© matplotlib ãŒã‚ã‚‹ã¨å›³è¡¨ã®æç”»ãŒå¯èƒ½ã«ãªã‚‹ SciPy ã¯NumPyã®ä¸Šã§å‹•ãç§‘å¦è¨ˆç®—ãƒ«ãƒ¼ãƒãƒ³ã‚’æ²¢å±±ç”¨æ„ã—ã¦ãã‚Œã‚‹ åŸºç¤Ž NumPy ã®ä¸»è¦ãªã‚ªãƒ–ã‚¸ã‚§ã‚¯ãƒˆã¯ã€åŒã˜åž‹ï¼ˆæ™®é€šã¯æ•°ï¼‰ã®è¦ç´ ã®ã¿ã‹ã‚‰æˆã‚Šã€æ£ã®æ•´æ•°ã®ã‚¿ãƒ—ãƒ«ã§æ·»å—ä»˜ã‘ã•ã‚ŒãŸã€å‡è³ªãªãƒ†ãƒ¼ãƒ–ãƒ«ï¼ˆã¨ã„ã†ã‹å¤šæ¬¡å…ƒ
nextbigthing 2013/02/03
numpy
ãƒªãƒ³ã‚¯
Pythonã®listã¨numpy.arrayã¨ã‹ã®é€Ÿåº¦æ¯”è¼ƒ - å”¯ç‰©æ˜¯çœŸ @Scaled_Wurm
å°Žå…¥ Pythonã®æ•°å€¤è¨ˆç®—ãƒ©ã‚¤ãƒ–ãƒ©ãƒªNumPyã®arrayã‚’ä½¿ã£ã¦ã€æ¨™æº–ã®listã‚’å˜ç´”ã«ç½®ãæ›ãˆã¦ã¿ã‚‹ã¨é…ããªã‚‹ã“ã¨ãŒå¤šã„ã§ã™ã€‚ å®Ÿéš›ã©ã‚Œãã‚‰ã„é€Ÿåº¦ã«å·®ãŒã‚ã‚‹ã®ã‹list, array, numpy.arrayã§æ¯”è¼ƒã—ã¦ã¿ã¾ã—ãŸã€‚ å‡¦ç†æ™‚é–“ã®è¨ˆæ¸¬ Pythonã«å«ã¾ã‚Œã‚‹ãƒ©ã‚¤ãƒ–ãƒ©ãƒªã®timeitã‚’ä½¿ã„ã¾ã™ã€‚ 100000å€‹ã®è¦ç´ (ã™ã¹ã¦ãŒ1)ã‚’æŒã¤é…åˆ—ã®å„è¦ç´ ã®ç·å’Œã‚’1000å›žè¨ˆç®—ã—ãŸæ™‚ã®å‡¦ç†æ™‚é–“ã‚’æ±‚ã‚ã¾ã™ã€‚ forãƒ«ãƒ¼ãƒ—ã®å ´åˆ(ã‚¤ãƒ†ãƒ¬ãƒ¼ã‚¿ã§ã‚¢ã‚¯ã‚»ã‚¹ã—ãŸå ´åˆ)ã¨sumé–¢æ•°ã€numpy.sumé–¢æ•°ã‚’ä½¿ã£ãŸå ´åˆã«ã¤ã„ã¦èª¿ã¹ã¦ã„ã¾ã™ã€‚ ã‚½ãƒ¼ã‚¹ã‚³ãƒ¼ãƒ‰ã¯ä¸€ç•ªä¸‹ã«ã‚ã‚Šã¾ã™ã€‚ ä½¿ã£ãŸãƒãƒ¼ã‚¸ãƒ§ãƒ³ã¯Python 2.7.2, NumPy 1.6.2ã€‚ çµæžœã¯ä»¥ä¸‹ã®ã¨ãŠã‚Š(å˜ä½ã¯ç§’)ã€‚ for sum numpy.sum list 3.17386984825 0.524603128433 9.5617320
nextbigthing 2012/12/25
numpy
ãƒªãƒ³ã‚¯
Scipy Lecture Notes â€” Scipy lecture notes
One document to learn numerics, science, and data with PythonÂ¶ Tutorials on the scientific Python ecosystem: a quick introduction to central tools and techniques. The different chapters each correspond to a 1 to 2 hours course with increasing level of expertise, from beginner to expert.
nextbigthing 2012/12/05
python

scipy

numpy
ãƒªãƒ³ã‚¯
çµ±è¨ˆè§£æž - memoring
nextbigthing 2012/11/12
numpy
ãƒªãƒ³ã‚¯
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