agpredict.py 文件源码

def qualityCheck(self):
        d = self.fullPath
        dataset = self.dataset

        outfile = d + '/qualityCheck' + dataset + '.txt'
        sys.stdout = open(outfile, 'w')

        array = np.load(d + '.npy')
        t = d + '.txt'
        with open(t, 'r') as tfile:
            text = tfile.read().split('\n')
        text = text[0:-1]
        nv = array.max()

        #entire dataset
        print 'Data for entire array of %s data:' % (dataset)
        print '\t>>> included datasets: %s' % (str(text))
        print '\t>>> shape:', array.shape
        print '\t>>> max w nv:', array.max()
        print '\t>>> max wo nv:', array[array<nv].max()
        print '\t>>> min wo nv:', array[array<nv].min()
        print '\t>>> mean wo nv:', array[array<nv].mean()

        #each band
        for b in range(array.shape[1]):
            print 'Data for column %d, %s:'% (b, text[b])
            print '\t>>> max w nv:', array[:,b].max()
            print '\t>>> max wo nv:', array[:,b][array[:,b]<nv].max()
            print '\t>>> min wo nv:', array[:,b][array[:,b]<nv].min()
            print '\t>>> mean wo nv:', array[:,b][array[:,b]<nv].mean()

        sys.stdout = sys.__stdout__

        logger.log('SUCCESS', 'See file qualityCheck%s.txt for detailed information about the final matrix.' % (self.dataset))