

def imshow_gray(self):
    '\n        .. todo::\n\n            WRITEME\n        '
    filters = self._filters.get_value()
    (modR, modC, colors, rows, cols, grps, fs_per_grp) = filters.shape
    logger.info(filters.shape)
    rval = np.zeros((((modR * (rows + 1)) - 1), ((modC * (cols + 1)) - 1)))
    for (rr, modr) in enumerate(xrange(0, rval.shape[0], (rows + 1))):
        for (cc, modc) in enumerate(xrange(0, rval.shape[1], (cols + 1))):
            rval[modr:(modr + rows), modc:(modc + cols)] = filters[rr, cc, 0, :, :, 0, 0]
    plt.imshow(rval, cmap='gray')
    return rval

dataset/ETHPy150Open lisa-lab/pylearn2/pylearn2/packaged_dependencies/theano_linear/unshared_conv/localdot.py LocalDot.imshow_gray/original