获取数组交集

#方法一:
a=[2,3,4,5]
b=[2,5,8]
tmp = [val for val in a if val in b]
print tmp
#[2, 5]

#方法二
print list(set(a).intersection(set(b)))

获取数组并集 (合并去重)

print list(set(a).union(set(b)))

获取数组差集

print list(set(b).difference(set(a))) # b中有而a中没有的

利用PIL比较两个图片的相似度

需要安装PIL图像模块，代码虽短但效果不错，还是非常靠谱的，前提是图片要大一些，太小的图片不好比较, 代码如下：

#!/usr/bin/python
# -*- coding: utf-8 -*-

import Image, sys, os

reload(sys)
sys.setdefaultencoding('utf-8')

def make_regalur_image(img, size = (256, 256)):
    return img.resize(size).convert('RGB')

def split_image(img, part_size = (64, 64)):
    w, h = img.size
    pw, ph = part_size

    assert w % pw == h % ph == 0

    return [img.crop((i, j, i+pw, j+ph)).copy() \
                for i in xrange(0, w, pw) \
                for j in xrange(0, h, ph)]

def hist_similar(lh, rh):
    assert len(lh) == len(rh)
    return sum(1 - (0 if l == r else float(abs(l - r))/max(l, r)) for l, r in zip(lh, rh))/len(lh)

def calc_similar(li, ri):
#   return hist_similar(li.histogram(), ri.histogram())
    return sum(hist_similar(l.histogram(), r.histogram()) for l, r in zip(split_image(li), split_image(ri))) / 16.0

def calc_similar_by_path(lf, rf):
    li, ri = make_regalur_image(Image.open(lf)), make_regalur_image(Image.open(rf))
    return calc_similar(li, ri)

def make_doc_data(lf, rf):
    li, ri = make_regalur_image(Image.open(lf)), make_regalur_image(Image.open(rf))
    li.save(lf + '_regalur.png')
    ri.save(rf + '_regalur.png')
    fd = open('stat.csv', 'w')
    fd.write('\n'.join(l + ',' + r for l, r in zip(map(str, li.histogram()), map(str, ri.histogram()))))
#   print >>fd, '\n'
#   fd.write(','.join(map(str, ri.histogram())))
    fd.close()
    import ImageDraw
    li = li.convert('RGB')
    draw = ImageDraw.Draw(li)
    for i in xrange(0, 256, 64):
        draw.line((0, i, 256, i), fill = '#ff0000')
        draw.line((i, 0, i, 256), fill = '#ff0000')
    li.save(lf + '_lines.png')

if __name__ == '__main__':
    path = u'E:\\data\\tmp' 
    toPath = u'E:\\data\\tmp'

    path = path.replace('\\', '/')
    toPath = toPath.replace('\\', '/')

    print 'start compare similar....'
    for x in os.listdir(path):
        for y in os.listdir(toPath):
            if x == y:
                continue

            degree = calc_similar_by_path(os.path.join(path,x), os.path.join(toPath,y))
            if degree > 0.6:
                print 'similar so much in test_case (%s <-> %s): %.3f%%'%(x, y, degree * 100)
                # make_doc_data(x, y)

    print 'end compare similar....'