August 2015
Intermediate to advanced
384 pages
7h 42m
Chinese
Content preview from 高效能PYTHON程式設計
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透過效能分析找出瓶頸
|
23
就
-0.82+0j
（虛線帶有菱形標記）而言，可以看到，在第 9 次迭代之後，絕對值已經超
過
+2
，所以我們停止迭代。
計算完整的 Julia Set
在這一節裡，我們分解產生 Julia set 的程式碼。貫穿本章，我們會以幾種方式分析它。
如範例 2-1 所示，在模組一開頭，匯入（import）我們的第一個效能分析方法會用到的
time
模組，並且定義一些座標常數。
範例
2-1
為座標空間定義全域常數
"""Julia set generator without optional PIL-based image drawing"""
import time
# 要調查的複數空間區域
x1, x2, y1, y2 = -1.8, 1.8, -1.8, 1.8
c_real, c_imag = -0.62772, -.42193
為了產生圖形，我們建立兩個輸入資料的串列。第 1 個是
zs
（複數的 z 座標），第 2 個
是
cs
（複數的初始條件）。兩個串列都不會改變，而且我們可以將
cs
最佳化成單一的常
數
c
值。然而，建造兩個輸入串列的基本理由是：在本章稍後分析 RAM 的使用量時，
會有看起來比較適用的資料可以分析。
為了建立
zs
與
cs
串列，我們必須知道每個
z
值的座標。在範例 2-2 中，我們使用
xcoord
與
ycoord
以及指定的
x_step
與
y_step
建立這些座標。這裡有點囉嗦，但在將程
式碼移植到其他工具（例如，
numpy
）及其他 Python 環境時會有用，因為它有助於讓一 ...
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