《 Dive Into Python 》 is a free Python book for experienced programmers.
It was originally hosted at DiveIntoPython.org, but the author has pulled down all copies. It is being mirrored here. You can read the book online, or download it in a variety of formats. It is also available in multiple languages.
我們讀書越多，就越發現我們是無知的。── 雪萊
《 Dive Into Python 3 》 covers Python 3 and its differences from Python 2. Compared to Dive Into Python, it’s about 20% revised and 80% new material. The book is now complete, but feedback is always welcome.
腹有詩書氣自華，讀書萬卷始通神。── 蘇軾
既是活在資訊爆炸的時代，怎麼可能缺乏知識的呢？這事頂不好說，借人家的話來講︰
蒲松齡‧《阿寶》
異史氏曰︰『性癡則其志凝，故書癡者文必工，藝癡者技必良。世之落拓而無成者，皆自謂不癡者也。且如粉花蕩產，盧雉頃家，顧癡人事哉！以是知慧黠而過，乃是真癡，彼孫子何癡乎！』
密尔顿‧《论出版自由》
因 为书籍并不是绝对死的东西。它包藏着一种生命的潜力，和作者一样活跃。不仅如此，它还象一个宝瓶，把创作者活生生的智慧中最纯净的菁华保存起来。我知道它 们是非常活跃的，而且繁殖力也是极强的，就象神话中的龙齿①一样。当它们被撒在各处以后，就可能长出武士来。但是，从另一方面来说，如果不特别小心的话， 误杀好人和误禁好书就会同样容易。杀人只是杀死了一个理性的动物，破坏了一个上帝的象；而禁止好书则是扼杀了理性本身，破坏了瞳仁中的上帝圣象②。
也許『郭沫若』說的好︰
『人』是『活』的，書是『死』的。『活』『人』讀『死』『書』，可以把『書』讀『活』。『死』『書』讀『活』『人』，可以把『人』讀『死』。
─── 《W!o 的派生‧十日談之《七》》
如果沒有一個理論說明連續時變訊號 
可以用離散取樣數據 
無誤復現，想來 Miller Puckette 的 Pure Data 箱子世界亦難存在了。因此在進入
In performance, musicians convert sheet music representations into sound which is transmitted through the air as air pressure oscillations. In essence, sound is simply air vibrating (Wikipedia). Sound vibrates through the air as longitudinal waves, i.e. the oscillations are parallel to the direction of propagation.
Audio refers to the production, transmission, or reception of sounds that are audible by humans. An audio signal is a representation of sound that represents the fluctuation in air pressure caused by the vibration as a function of time. Unlike sheet music or symbolic representations, audio representations encode everything that is necessary to reproduce an acoustic realization of a piece of music. However, note parameters such as onsets, durations, and pitches are not encoded explicitly. This makes converting from an audio representation to a symbolic representation a difficult and ill-defined task.
MIR 筆記前，藉著引用
先生著作之機會︰
Sampling Theory
In this appendix, sampling theory is derived as an application of the DTFT and the Fourier theorems developed in Appendix C. First, we must derive a formula for aliasing due to uniformly sampling a continuous-time signal. Next, the sampling theorem is proved. The sampling theorem provides that a properly bandlimited continuous-time signal can be sampled and reconstructed from its samples without error, in principle.
An early derivation of the sampling theorem is often cited as a 1928 paper by Harold Nyquist, and Claude Shannon is credited with reviving interest in the sampling theorem after World War II when computers became public.D.1As a result, the sampling theorem is often called “Nyquist’s sampling theorem,” “Shannon’s sampling theorem,” or the like. Also, the sampling rate has been called the Nyquist rate in honor of Nyquist’s contributions [50]. In the author’s experience, however, modern usage of the term “Nyquist rate” refers instead to half the sampling rate. To resolve this clash between historical and current usage, the term Nyquist limit will always mean half the sampling rate in this book series, and the term “Nyquist rate” will not be used at all.
再次推薦這本好書呦！堅實的理論基礎畢竟無往而不利乎？