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.ipynb_checkpoints/Untitled-checkpoint.ipynb

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+{
+ "cells": [],
+ "metadata": {},
+ "nbformat": 4,
+ "nbformat_minor": 4
+}

.ipynb_checkpoints/try2-checkpoint.py

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+import numpy as np
+import matplotlib.pyplot as plt
+import os
+
+#定义迭代函数
+iter_func = lambda z,c:(z**2 + c)
+def calc_steps(c,max_iter_num = 128):
+    z = complex(0,0)
+    num = 0
+    while abs(z)<2 and num <max_iter_num:
+        z = iter_func(z , c)
+        num = num+1
+    if num == max_iter_num:
+        return z.real
+    else:
+        return num
+def display_mandelbrot(xArea=[-2,2],yArea=[-2,2],num = 1000):
+    X,Y = np.meshgrid(np.linspace(xArea[0],xArea[1],num+1),np.linspace(yArea[1],yArea[0],num+1))
+    C = X + Y*1j
+    result  = np.zeros((num+1,num+1))
+    plt.ion()
+    plt.hot()
+    #计算出结果
+    for i in range(num+1):
+        for j in range(num+1):
+            result[i,j] = calc_steps(C[i,j])
+        if i*100%num == 0 :
+            # print( i / num * 100 ) 
+            plt.imshow(result,vmax=abs(result).max(),vmin=abs(result).min(),extent = xArea + yArea)
+    plt.show(block=False)
+    plt.pause(0.1)
+        # threading._start_new_thread(plt.pause,(0.5,))
+        # plt.pause(0.5)
+    # plt.savefig("fig1.png")
+
+
+
+if __name__ =="__main__":
+    # display_mandelbrot([-0.5226,-0.5225],[0.6243,0.6244])
+    # display_mandelbrot([0.2537269133080432,0.2537269133080432+0.0000000000000009],[0.000365995381749671,0.000365995381749671+0.0000000000000009],100)
+    # display_mandelbrot(num = 200)
+    display_mandelbrot([-0.56,-0.53],[-0.55,-0.52],4096)
+    input()

.vscode/launch.json

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+{
+    // 使用 IntelliSense 了解相关属性。 
+    // 悬停以查看现有属性的描述。
+    // 欲了解更多信息，请访问: https://go.microsoft.com/fwlink/?linkid=830387
+    "version": "0.2.0",
+    "configurations": [
+        {
+            "name": "Python: 当前文件",
+            "type": "python",
+            "request": "launch",
+            "program": "${file}",
+            "console": "integratedTerminal"
+        }
+    ]
+}

.vscode/settings.json

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+{
+    "python.pythonPath": "C:\\ProgramData\\Anaconda3\\python.exe"
+}

readme.md

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+# 生成曼德勃罗集图像
+
+**GPU版本暂时无法使用！！！**
+**GPU版本暂时无法使用！！！**
+**GPU版本暂时无法使用！！！**
+
+随便写的，玩玩而已，功能还不完善。
+借鉴了其他大佬的思路。
+
+## 依赖库
+
+- numpy
+- matplotlab
+- numba (cuda GPU support)(但是GPU版目前用不了)
+
+```shell
+pip install numpy,matplotlib,numba
+```
+
+## 实例
+
+```python
+from try2 import mandelbrot
+import matplotlab as mp
+mp.hot()
+mandelbrot([-0.56,-0.53],[-0.55,-0.52],100)
+#前两个参数为需要生成的图形的区域（建议传入方形区域，不然可能会变形。），最后一个参数是方阵的阶数。
+mp.show()
+```
+
+目前还有很多要改的地方。本来还想加入捕获matplotlab的鼠标事件的交互功能，但是实在没精力了。
+随缘更新吧。
+
+<!-- 现实太残酷了。 -->

try2.py

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+import numpy as np
+import matplotlib.pyplot as plt
+import os
+
+#定义迭代函数
+iterFunction = lambda z,c:(z**2 + c)
+def calcPoints(c,maxIterNum = 128):
+    z = complex(0,0)
+    num = 0
+    while abs(z)<2 and num <maxIterNum:
+        z = iterFunction(z , c)
+        num = num+1
+    if num == maxIterNum:
+        return z.real
+    else:
+        return num
+
+def mandelbrot(xArea=[-2,2],yArea=[-2,2],num = 1000):
+    X,Y = np.meshgrid(np.linspace(xArea[0],xArea[1],num+1),np.linspace(yArea[1],yArea[0],num+1))
+    C = X + Y*1j
+    result  = np.zeros((num+1,num+1))
+    for i in range(num+1):
+        for j in range(num+1):
+            result[i,j] = calcPoints(C[i,j])
+        ##打印百分比
+        if i*10%num == 0 :
+            print( i / num * 100 ) 
+    plt.imshow(result,vmax=abs(result).max(),vmin=abs(result).min(),extent = xArea + yArea)
+    return result
+
+
+
+if __name__ =="__main__":
+    # display_mandelbrot([-0.5226,-0.5225],[0.6243,0.6244])
+    # display_mandelbrot(num = 200)
+    plt.hot()
+    mandelbrot([-0.56,-0.53],[-0.55,-0.52],100)
+    # plt.imshow()
+    plt.show()

try2_gpu.py

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+import numpy as np
+import matplotlib.pyplot as plt
+import os
+import math
+from numba import cuda
+
+#定义迭代函数
+iterFunc = lambda z,c:(z**2 + c)
+maxIterNum = 128
+class index2D:
+    def __init__(self,x,y):
+        self.x = x
+        self.y = y
+
+@cuda.jit
+def calcMandelbrot(img,C,accuracy):
+    idx = index2D(cuda.blockIdx.x * cuda.blockDim.x + cuda.threadIdx.x , cuda.blockIdx.y * cuda.blockDim.y + cuda.threadIdx.y)
+    z = complex(0,0)
+    num = 0
+    if idx.x<accuracy and idx.y<accuracy:
+        while abs(z)<2 and num <maxIterNum:
+            z = iterFunc(z , C[idx.x,idx.y])
+            num = num+1
+        if num == maxIterNum:
+            img[idx.x,idx.y] = z.real
+        else:
+            img[idx.x,idx.y] = num 
+
+
+
+def mandelbrot(xArea = [-2,2],yArea = [-2,2],accuracy = 1000):
+    X,Y = np.meshgrid(np.linspace(xArea[0],xArea[1],accuracy+1),np.linspace(yArea[1],yArea[0],accuracy+1))
+    C = X + Y*1j
+    img = np.zeros((accuracy+1,accuracy+1))
+    # resurt = np.zeros((accuracy+1,accuracy+1))
+
+    #GPU计算
+    threadsPerBlock = 1024
+    blocksPerGrid = math.ceil(accuracy / threadsPerBlock)
+    calcMandelbrot[blocksPerGrid,threadsPerBlock](img,C,accuracy)
+    cuda.synchronize()
+    return img
+
+
+
+if __name__ =="__main__":
+    # display_mandelbrot(x_num=200,y_num=200)
+    # display_mandelbrot([-1,0],[0,1],x_num=200,y_num=200)
+    # display_mandelbrot([-0.5226,-0.5225],[0.6243,0.6244])
+    img = mandelbrot()
+    # os.system('pause')
+    # display_mandelbrot()
+    # input()