tfinterp.py 文件源码

def interp1d_(xin_,xp,yp_):
    """
    Interpolate a uniformly sampled piecewise linear function. Mapping elements
    from xin_ to the result.  Input values will be clipped to range of xp.
        xin_ :  input tensor (real)
        xp : x grid (constant -- must be a 1d numpy array, uniformly spaced)
        yp_ : tensor of the result values at the gridpoints xp
    """
    import tensorflow as tf
    x_ = tf.clip_by_value(xin_,xp.min(),xp.max())
    dx = xp[1]-xp[0]
    assert len(xp.shape)==1,'only 1d interpolation'
    assert xp.shape[0]==int(yp_.get_shape()[0])
    assert abs(np.diff(xp)/dx - 1.0).max() < 1e-6,'must be uniformly sampled'

    newshape = [  ]
    x1_ = tf.expand_dims(x_,-1)
    dt = yp_.dtype
    wt_ = tf.maximum(tf.constant(0.,dtype=dt), 1-abs(x1_ - tf.constant(xp,dtype=dt))/dx  )
    y_ = tf.reduce_sum(wt_ * yp_,axis=-1)
    return y_