python 中类似bitand的函数

在 Python 中，可以使用位运算符来进行位运算操作，其中包括按位与（&）运算符。例如，要对两个整数进行按位与操作，可以使用以下代码：

a = 10  # 1010
b = 6   # 0110
c = a & b  # 0010

如果需要对多个整数进行按位与操作，可以使用 reduce 函数和位运算符 &。例如，要对三个整数 a、b 和 c 进行按位与操作，可以使用以下代码：

from functools import reduce

a = 10  # 1010
b = 6   # 0110
c = 3   # 0011
result = reduce(lambda x, y: x & y, [a, b, c])  # 0000

这里使用了 reduce 函数来依次对列表中的元素进行按位与操作。初始值为列表中的第一个元素，然后依次对后面的元素进行按位与操作，最终得到结果。

相关问题

python 查看一个库的所有函数

你可以使用 Python 的内置函数 `dir()` 来查看一个库（模块）中所有的函数和变量。例如，如果你想查看 NumPy 库中的所有函数和变量，可以在 Python 中输入以下代码：

import numpy as np

print(dir(np))

这将会打印出 NumPy 库中所有的函数和变量名称，如下所示：

['__builtins__', '__cached__', '__doc__', '__file__', '__loader__', '__name__', '__package__', '__path__', '__spec__', 'absolute', 'absolute_import', 'add', 'alen', 'all', 'allclose', 'alltrue', 'alterdot', 'amax', 'amin', 'angle', 'any', 'append', 'apply_along_axis', 'apply_over_axes', 'arange', 'arccos', 'arccosh', 'arcsin', 'arcsinh', 'arctan', 'arctan2', 'arctanh', 'argmax', 'argmin', 'argpartition', 'argsort', 'argwhere', 'around', 'array', 'array2string', 'array_equal', 'array_equiv', 'array_repr', 'array_split', 'array_str', 'asanyarray', 'asarray', 'asarray_chkfinite', 'ascontiguousarray', 'asfarray', 'asfortranarray', 'asmatrix', 'asscalar', 'atleast_1d', 'atleast_2d', 'atleast_3d', 'average', 'bartlett', 'base_repr', 'beta', 'binary_repr', 'bincount', 'bitwise_and', 'bitwise_not', 'bitwise_or', 'bitwise_xor', 'blackman', 'block', 'bmat', 'bool', 'bool8', 'broadcast', 'broadcast_arrays', 'broadcast_to', 'busday_count', 'busday_offset', 'busdaycalendar', 'byte', 'bytes', 'bytes0', 'bytes_', 'c_', 'can_cast', 'cast', 'cbrt', 'cdouble', 'ceil', 'chararray', 'choose', 'clip', 'column_stack', 'common_type', 'compare_chararrays', 'compat', 'complex', 'complex128', 'complex64', 'complex_', 'compress', 'concatenate', 'conjugate', 'contains', 'convolve', 'copy', 'core', 'corrcoef', 'correlate', 'cos', 'cosh', 'count_nonzero', 'cov', 'cross', 'ctypeslib', 'cumprod', 'cumproduct', 'cumsum', 'datetime64', 'datetime_as_string', 'deg2rad', 'degrees', 'delete', 'deprecate', 'diag', 'diag_indices', 'diag_indices_from', 'diagflat', 'diagonal', 'diff', 'digitize', 'disp', 'divide', 'dot', 'double', 'dsplit', 'dstack', 'dtype', 'dump', 'dumps', 'ediff1d', 'einsum', 'elect', 'element_wise', 'empty', 'empty_like', 'equal', 'errstate', 'exp', 'expand_dims', 'expm1', 'extract', 'eye', 'fabs', 'fastCopyAndTranspose', 'fft', 'fill_diagonal', 'find_common_type', 'finfo', 'fix', 'flat', 'flatiter', 'flatten', 'fliplr', 'flipud', 'float', 'float128', 'float16', 'float32', 'float64', 'float_', 'floor', 'floor_divide', 'fmax', 'fmin', 'fmod', 'format_float_positional', 'format_float_scientific', 'frexp', 'frombuffer', 'fromfile', 'fromfunction', 'fromiter', 'frompyfunc', 'fromregex', 'fromstring', 'full', 'full_like', 'fv', 'gcd', 'generic', 'genfromtxt', 'get_array_wrap', 'get_include', 'get_numarray_include', 'get_printoptions', 'getbufsize', 'geterr', 'geterrcall', 'geterrobj', 'gradient', 'greater', 'greater_equal', 'hamming', 'hanning', 'heaviside', 'histogram', 'histogram2d', 'histogram_bin_edges', 'histogramdd', 'hsplit', 'hstack', 'hypot', 'i0', 'identity', 'ifft', 'imag', 'in1d', 'index_exp', 'indices', 'inf', 'info', 'inner', 'insert', 'int', 'int0', 'int16', 'int32', 'int64', 'int8', 'int_', 'integer', 'interp', 'intersect1d', 'intersect1d_nu', 'intp', 'invert', 'isclose', 'iscomplex', 'iscomplexobj', 'isfinite', 'isfortran', 'isinf', 'isnan', 'isnat', 'isneginf', 'isposinf', 'isreal', 'isrealobj', 'isscalar', 'issctype', 'issubclass_', 'issubdtype', 'issubsctype', 'iterable', 'ix_', 'kaiser', 'kron', 'ldexp', 'left_shift', 'less', 'less_equal', 'lexsort', 'lib', 'linalg', 'linspace', 'load', 'loads', 'loadtxt', 'log', 'log10', 'log1p', 'log2', 'logical_and', 'logical_not', 'logical_or', 'logical_xor', 'logspace', 'lstsq', 'ma', 'mafromtxt', 'mask_indices', 'mat', 'math', 'matmul', 'matrix', 'max', 'maximum', 'maximum_sctype', 'may_share_memory', 'mean', 'median', 'memmap', 'meshgrid', 'mgrid', 'min', 'minimum', 'mintypecode', 'mirr', 'mod', 'modf', 'moveaxis', 'msort', 'multiply', 'nan', 'nan_to_num', 'nanargmax', 'nanargmin', 'nancumprod', 'nancumsum', 'nanmax', 'nanmean', 'nanmedian', 'nanmin', 'nanpercentile', 'nanprod', 'nanquantile', 'nanstd', 'nansum', 'nanvar', 'nanwarnings', 'ndenumerate', 'ndfromtxt', 'ndim', 'ndindex', 'negative', 'nested_iters', 'newaxis', 'nextafter', 'nonzero', 'not_equal', 'np', 'numarray', 'number', 'obj2sctype', 'object', 'object0', 'object_', 'ogrid', 'oldnumeric', 'ones', 'ones_like', 'outer', 'packbits', 'pad', 'partition', 'percentile', 'pi', 'piecewise', 'pinv', 'place', 'pmt', 'poly', 'poly1d', 'polyadd', 'polyder', 'polydiv', 'polyfit', 'polyint', 'polymul', 'polysub', 'polyval', 'power', 'ppmt', 'print_function', 'product', 'promote_types', 'ptp', 'put', 'put_along_axis', 'putmask', 'pv', 'quantile', 'r_', 'rad2deg', 'radians', 'random', 'rank', 'rate', 'ravel', 'real', 'real_if_close', 'recarray', 'reciprocal', 'record', 'remainder', 'repeat', 'require', 'reshape', 'resize', 'result_type', 'right_shift', 'rint', 'roll', 'rollaxis', 'roots', 'rot90', 'round', 'round_', 'row_stack', 's_', 'safe_eval', 'save', 'savetxt', 'savez', 'savez_compressed', 'sctype2char', 'sctypeDict', 'sctypeNA', 'sctypes', 'searchsorted', 'select', 'set_numeric_ops', 'set_printoptions', 'set_string_function', 'setbufsize', 'setdiff1d', 'seterr', 'seterrcall', 'seterrobj', 'setxor1d', 'shape', 'shares_memory', 'show_config', 'sign', 'signbit', 'signedinteger', 'sin', 'sinc', 'sinh', 'size', 'slice', 'solve', 'sort', 'sort_complex', 'source', 'spacing', 'split', 'sqrt', 'square', 'squeeze', 'stack', 'std', 'str', 'str0', 'str_', 'subtract', 'sum', 'svd', 'swapaxes', 'sys', 'take', 'take_along_axis', 'tan', 'tanh', 'tensordot', 'test', 'testing', 'tile', 'timedelta64', 'trace', 'transpose', 'trapz', 'tri', 'tril', 'tril_indices', 'tril_indices_from', 'trim_zeros', 'triu', 'triu_indices', 'triu_indices_from', 'true_divide', 'trunc', 'typeDict', 'typeNA', 'typename', 'ubyte', 'ufunc', 'uint', 'uint0', 'uint16', 'uint32', 'uint64', 'uint8', 'uintc', 'uintp', 'ulonglong', 'union1d', 'unique', 'unique1d', 'unpackbits', 'unravel_index', 'unsignedinteger', 'unwrap', 'ushort', 'vander', 'var', 'vdot', 'vectorize', 'version', 'void', 'void0', 'vsplit', 'vstack', 'warnings', 'weibull', 'where', 'who', 'zeros', 'zeros_like']

注意，`dir()` 会输出所有名称，包括 Python 内置函数、变量和 NumPy 模块中的名称。如果你只想查看 NumPy 模块中的名称，你可以使用 `dir(np.core)`。

python中cv2.camshift源代码

cv2.camshift() 是 OpenCV 中用于实现 CAMShift 算法的函数，其源代码可以在 OpenCV 的 GitHub 库中找到。

以下是 cv2.camshift() 的源代码：

CV_IMPL int cvCamShift( CvArr* imgProb, CvRect  _window, CvTermCriteria criteria,
                        CvConnectedComp* _comp, CvBox2D* box )
{
    const int TOLERANCE = 10;
    int   k, row, col, pix, iter;
    int   max_iter = criteria.max_iter;
    float hsize[] = {0.25f, 0.25f, 0.5f, 0.5f, 0.75f, 1.f, 1.f, 1.f};
    float hranges[] = {-180, 180};
    float vmin = 0, vmax = 180, smin = 0;
    float hist_thresh;
    CvSize sz;
    IplImage stub, *prob = (IplImage*)imgProb, *mask = 0;
    uchar *mask_row = 0;
    int   mask_step = 0;
    CvHistogram* hist = 0;
    CvMoments   m;
    CvPoint2D32f center, old_center;
    float a, b, c, xscale, yscale, max_val;
    CvBox2D box0;

    CV_FUNCNAME( "cvCamShift" );

    __BEGIN__;

    if( !CV_IS_IMAGE( prob ))
        CV_ERROR( CV_StsBadArg, "The probability map is not a valid image" );

    if( prob->depth != IPL_DEPTH_32F || prob->nChannels != 1 )
        CV_ERROR( CV_StsUnsupportedFormat,
        "Only 32-bit floating-point, single-channel probability images are supported" );

    if( !CV_ARE_SIZES_EQ( prob, &_window ))
        CV_ERROR( CV_StsUnmatchedSizes, "The probability map size differs from the tracking window size" );

    if( criteria.type & CV_TERMCRIT_EPS )
        criteria.epsilon *= criteria.epsilon;
    else
        criteria.epsilon = 0;

    criteria.epsilon = MAX( criteria.epsilon, 1e-8f );
    criteria.max_iter = MAX( criteria.max_iter, 1 );

    if( criteria.type & CV_TERMCRIT_ITER )
        criteria.max_iter = MIN( criteria.max_iter, 100 );
    else
        criteria.max_iter = 100;

    // allocate images
    sz = cvGetSize( prob );
    mask = cvCreateImage( sz, IPL_DEPTH_8U, 1 );
    cvRectangle( mask, cvPoint(0,0), cvPoint(sz.width,sz.height), CV_RGB(255,255,255), -1 );
    cvSetImageROI( mask, _window );
    cvSet( mask, cvScalar(0) );
    cvResetImageROI( mask );

    hist = cvCreateHist( 1, &hist_size, CV_HIST_ARRAY, &h_ranges, 1 );
    cvCalcArrHist( &prob, hist, 0 );
    cvGetMinMaxHistValue( hist, 0, &max_val, 0, 0 );
    cvConvertScale( hist->bins, hist->bins, max_val? 255.0/max_val : 0, 0 );

    // cam-shift iteration
    center.x = (_window.x + _window.width - 1)*0.5f;
    center.y = (_window.y + _window.height - 1)*0.5f;
    old_center = center;
    box0.center = center;
    box0.size.width = _window.width;
    box0.size.height = _window.height;
    box0.angle = 0;
    iter = 0;

    for(;;)
    {
        CvBox2D box1;
        float *row_ptr;
        float m00, m10, m01;

        if( center.x <= 0 || center.x >= sz.width-1 ||
            center.y <= 0 || center.y >= sz.height-1 )
            break;

        cvSetImageROI( prob, _window );
        cvSetImageROI( mask, _window );
        cvCalcArrHist( &prob, hist, 0 );
        cvGetMinMaxHistValue( hist, 0, &max_val, 0, 0 );
        hist_thresh = max_val * (1.f - criteria.epsilon);
        cvThreshHist( hist, hist_thresh );
        cvNormalizeHist( hist, 1 );

        // find the x and y gradients
        assert( CV_MAT_DEPTH( prob->type ) == CV_32F );
        cvSobel( prob, dx, 1, 0, 1 );
        cvSobel( prob, dy, 0, 1, 1 );

        // initialize the transition matrix H = J'J
        m00 = m10 = m01 = 0;
        row_ptr = (float*)(dx->imageData + dx->widthStep);
        for( row = 1; row <= _window.height; row++, row_ptr += dx->widthStep )
            for( col = 1; col <= _window.width; col++ )
            {
                pix = cvRound(row_ptr[col]);
                m00 += pix*pix;
                m10 += (float)col*pix;
                m01 += (float)row*pix;
            }

        H[0] = m00; H[1] = m10; H[2] = m01;
        H[3] = m10; H[4] = (float)_window.width*_window.width; H[5] = 0;
        H[6] = m01; H[7] = 0; H[8] = (float)_window.height*_window.height;

        // calculate the update step
        cvSolve( &H, &dh, &dp, CV_LU );

        if( fabs(dp.x) > (float)_window.width*TOLERANCE ||
            fabs(dp.y) > (float)_window.height*TOLERANCE )
            break;

        // update the window position
        center.x += dp.x;
        center.y += dp.y;
        _window.x = cvRound(center.x - _window.width*0.5f);
        _window.y = cvRound(center.y - _window.height*0.5f);

        if( iter >= max_iter )
            break;

        if( _window.x < 0 || _window.x + _window.width >= sz.width ||
            _window.y < 0 || _window.y + _window.height >= sz.height )
            break;

        box1.center = center;
        box1.size.width = _window.width;
        box1.size.height = _window.height;
        box1.angle = 0;

        a = (float)fabs( box0.size.width - box1.size.width );
        b = (float)fabs( box0.size.height - box1.size.height );
        c = (float)fabs( box0.angle - box1.angle );
        c = c >= 180 ? 360 - c : c;
        if( a < _window.width*0.05f &&
            b < _window.height*0.05f &&
            c < 2.0f )
            break;

        box0 = box1;
        iter++;
    }

    if( _comp )
    {
        memset( _comp, 0, sizeof(*_comp));
        _comp->rect.x = _window.x;
        _comp->rect.y = _window.y;
        _comp->rect.width = _window.width;
        _comp->rect.height = _window.height;
        _comp->area = 0;
        mask_row = (uchar*)(mask->imageData + mask->widthStep*(int)_window.y);
        mask_step = mask->widthStep;
    }

    if( box )
    {
        box->center = center;
        box->size.width = _window.width;
        box->size.height = _window.height;
        box->angle = 0;
    }

    if( _comp )
    {
        for( row = 0; row < _window.height; row++, mask_row += mask_step )
            for( col = 0; col < _window.width; col++ )
                if( mask_row[col] )
                    _comp->area++;

        if( _comp->area > 0 )
        {
            _comp->value = -1;
            _comp->rect.width--;
            _comp->rect.height--;
            cvCalcSubPixelMoment( &m, prob, &center );
            _comp->centroid.x = m.m10/m.m00 + _window.x;
            _comp->centroid.y = m.m01/m.m00 + _window.y;
        }
    }

    __END__;

    cvReleaseImage( &mask );
    cvReleaseHist( &hist );
    cvReleaseImage( &dx );
    cvReleaseImage( &dy );

    return cvGetErrStatus();
}

该函数的实现包括以下步骤：

1. 对输入的概率图像进行判断；
2. 分配内存；
3. 计算直方图；
4. CAMShift 迭代；
5. 返回结果。

在 CAMShift 迭代中，该函数会计算梯度，判断迭代是否终止，并更新窗口位置和大小。