Python numpy 模块，dsplit() 实例源码

def dsplit(ary, indices_or_sections):
    """Splits an array into multiple sub arrays along the third axis.

    This is equivalent to ``split`` with ``axis=2``.

    .. seealso:: :func:`cupy.split` for more detail, :func:`numpy.dsplit`

    """
    if ary.ndim <= 2:
        raise ValueError('Cannot dsplit an array with less than 3 dimensions')
    return split(ary, indices_or_sections, 2)

def vsplit(ary, indices_or_sections):
    """Splits an array into multiple sub arrays along the first axis.

    This is equivalent to ``split`` with ``axis=0``.

    .. seealso:: :func:`cupy.split` for more detail, :func:`numpy.dsplit`

    """
    if ary.ndim <= 1:
        raise ValueError('Cannot vsplit an array with less than 2 dimensions')
    return split(ary, indices_or_sections, 0)

def char2wordBB(self, charBB, text):
        """
        Converts character bounding-boxes to word-level
        bounding-boxes.

        charBB : 2x4xn matrix of BB coordinates
        text   : the text string

        output : 2x4xm matrix of BB coordinates,
                 where, m == number of words.
        """
        wrds = text.split()
        bb_idx = np.r_[0, np.cumsum([len(w) for w in wrds])]
        wordBB = np.zeros((2,4,len(wrds)), 'float32')

        for i in xrange(len(wrds)):
            cc = charBB[:,:,bb_idx[i]:bb_idx[i+1]]

            # fit a rotated-rectangle:
            # change shape from 2x4xn_i -> (4*n_i)x2
            cc = np.squeeze(np.concatenate(np.dsplit(cc,cc.shape[-1]),axis=1)).T.astype('float32')
            rect = cv2.minAreaRect(cc.copy())
            box = np.array(cv2.cv.BoxPoints(rect))

            # find the permutation of box-coordinates which
            # are "aligned" appropriately with the character-bb.
            # (exhaustive search over all possible assignments):
            cc_tblr = np.c_[cc[0,:],
                            cc[-3,:],
                            cc[-2,:],
                            cc[3,:]].T
            perm4 = np.array(list(itertools.permutations(np.arange(4))))
            dists = []
            for pidx in xrange(perm4.shape[0]):
                d = np.sum(np.linalg.norm(box[perm4[pidx],:]-cc_tblr,axis=1))
                dists.append(d)
            wordBB[:,:,i] = box[perm4[np.argmin(dists)],:].T

        return wordBB

def dsplit(ary, indices_or_sections):
    """Splits an array into multiple sub arrays along the third axis.

    This is equivalent to ``split`` with ``axis=2``.

    .. seealso:: :func:`cupy.split` for more detail, :func:`numpy.dsplit`

    """
    if ary.ndim <= 2:
        raise ValueError('Cannot dsplit an array with less than 3 dimensions')
    return split(ary, indices_or_sections, 2)

def vsplit(ary, indices_or_sections):
    """Splits an array into multiple sub arrays along the first axis.

    This is equivalent to ``split`` with ``axis=0``.

    .. seealso:: :func:`cupy.split` for more detail, :func:`numpy.dsplit`

    """
    if ary.ndim <= 1:
        raise ValueError('Cannot vsplit an array with less than 2 dimensions')
    return split(ary, indices_or_sections, 0)

def _ros_read_images(self, stream_buffer, number, staleness_limit = 10.):
        """ Reads images from a stream buffer

        Parameters
        ----------
        stream_buffer : string
            absolute path to the image buffer service
        number : int
            The number of frames to get. Must be less than the image buffer service's
            current buffer size
        staleness_limit : float, optional
            Max value of how many seconds old the oldest image is. If the oldest image
            grabbed is older than this value, a RuntimeError is thrown.

            If None, staleness is ignored.
        Returns
        -------
        List of nump.ndarray objects, each one an image
        Images are in reverse chronological order (newest first)
        """

        rospy.wait_for_service(stream_buffer, timeout = self.timeout)
        ros_image_buffer = rospy.ServiceProxy(stream_buffer, ImageBuffer)
        ret = ros_image_buffer(number, 1)
        if not staleness_limit == None:
            if ret.timestamps[-1] > staleness_limit:
                raise RuntimeError("Got data {0} seconds old, more than allowed {1} seconds"
                                   .format(ret.timestamps[-1], staleness_limit))

        data = ret.data.reshape(ret.data_dim1, ret.data_dim2, ret.data_dim3).astype(ret.dtype)

        # Special handling for 1 element, since dstack's behavior is different
        if number == 1:
            return [data]
        return np.dsplit(data, number)

def _rpc(self, x):
        L, P, H = np.dsplit(x, 3)
        return np.dstack([np.ones((x.shape[0], x.shape[1]), dtype=np.float32), L, P, H, L*P, L*H, P*H, L**2, P**2, H**2,
                           L*P*H, L**3, L*(P**2), L*(H**2), (L**2)*P, P**3, P*(H**2),
                           (L**2)*H, (P**2)*H, H**3])