Python scipy.signal.html() Examples

The following are 9 code examples of scipy.signal.html(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module scipy.signal , or try the search function .
Example #1
Source File: tensor_utils.py    From garage with MIT License 6 votes vote down vote up 
def discount_cumsum(x, discount):
    """Discounted cumulative sum.

    See https://docs.scipy.org/doc/scipy/reference/tutorial/signal.html#difference-equation-filtering  # noqa: E501
    Here, we have y[t] - discount*y[t+1] = x[t]
    or rev(y)[t] - discount*rev(y)[t-1] = rev(x)[t]

    Args:
        x (np.ndarrary): Input.
        discount (float): Discount factor.

    Returns:
        np.ndarrary: Discounted cumulative sum.

    """
    return scipy.signal.lfilter([1], [1, float(-discount)], x[::-1],
                                axis=0)[::-1]
Example #2
Source File: np_util.py    From leap with MIT License 6 votes vote down vote up 
def batch_discounted_cumsum(values, discount):
    """
    Return a matrix of discounted returns.

    output[i, j] = discounted sum of returns of rewards[i, j:]

    So

    output[i, j] = rewards[i, j] + rewards[i, j+1] * discount
                    + rewards[i, j+2] * discount**2 + ...

    Based on rllab.misc.special.discounted_cumsum
    :param rewards: FloatTensor, size [batch_size, sequence_length, 1]
    :param discount: float, discount factor
    :return FloatTensor, size [batch_size, sequence_length, 1]
    """
    # See https://docs.scipy.org/doc/scipy/reference/tutorial/signal.html#difference-equation-filtering
    # Here, we have y[t] - discount*y[t+1] = x[t]
    # or reverse(y)[t] - discount*reverse(y)[t-1] = reverse(x)[t]
    return scipy.signal.lfilter(
        [1], [1, float(-discount)], values.T[::-1], axis=0,
    )[::-1].T
Example #3
Source File: utils.py    From dynamic-training-with-apache-mxnet-on-aws with Apache License 2.0 5 votes vote down vote up 
def discount_cumsum(x, discount):
    # See https://docs.scipy.org/doc/scipy/reference/tutorial/signal.html#difference-equation-filtering
    # Here, we have y[t] - discount*y[t+1] = x[t]
    # or rev(y)[t] - discount*rev(y)[t-1] = rev(x)[t]
    return scipy.signal.lfilter([1], [1, -discount], x[::-1], axis=0)[::-1]
Example #4
Source File: utils.py    From training_results_v0.6 with Apache License 2.0 5 votes vote down vote up 
def discount_cumsum(x, discount):
    # See https://docs.scipy.org/doc/scipy/reference/tutorial/signal.html#difference-equation-filtering
    # Here, we have y[t] - discount*y[t+1] = x[t]
    # or rev(y)[t] - discount*rev(y)[t-1] = rev(x)[t]
    return scipy.signal.lfilter([1], [1, -discount], x[::-1], axis=0)[::-1]
Example #5
Source File: special.py    From gym-sawyer with MIT License 5 votes vote down vote up 
def discount_cumsum(x, discount):
    # See https://docs.scipy.org/doc/scipy/reference/tutorial/signal.html#difference-equation-filtering  # noqa: E501
    # Here, we have y[t] - discount*y[t+1] = x[t]
    # or rev(y)[t] - discount*rev(y)[t-1] = rev(x)[t]
    return scipy.signal.lfilter(
        [1], [1, float(-discount)], x[::-1], axis=0)[::-1]
Example #6
Source File: math.py    From Jacinle with MIT License 5 votes vote down vote up 
def discount_cumsum(x, gamma):
    """Compute the discounted cumulative summation of an 1-d array.
    From https://github.com/rll/rllab/blob/master/rllab/misc/special.py"""
    # See https://docs.scipy.org/doc/scipy/reference/tutorial/signal.html#difference-equation-filtering
    # Here, we have y[t] - discount*y[t+1] = x[t]
    # or rev(y)[t] - discount*rev(y)[t-1] = rev(x)[t]
    return scipy.signal.lfilter([1], [1, float(-gamma)], x[::-1], axis=0)[::-1]
Example #7
Source File: utils.py    From ProMP with MIT License 5 votes vote down vote up 
def discount_cumsum(x, discount):
    """
    See https://docs.scipy.org/doc/scipy/reference/tutorial/signal.html#difference-equation-filtering

    Returns:
        (float) : y[t] - discount*y[t+1] = x[t] or rev(y)[t] - discount*rev(y)[t-1] = rev(x)[t]
    """
    return scipy.signal.lfilter([1], [1, float(-discount)], x[::-1], axis=0)[::-1]
Example #8
Source File: utils.py    From Python-Reinforcement-Learning-Projects with MIT License 5 votes vote down vote up 
def discount_cumsum(x, discount):
    # See https://docs.scipy.org/doc/scipy/reference/tutorial/signal.html#difference-equation-filtering
    # Here, we have y[t] - discount*y[t+1] = x[t]
    # or rev(y)[t] - discount*rev(y)[t-1] = rev(x)[t]
    return scipy.signal.lfilter([1], [1, float(-discount)], x[::-1], axis=0)[::-1]
Example #9
Source File: utils.py    From SNIPER-mxnet with Apache License 2.0 5 votes vote down vote up 
def discount_cumsum(x, discount):
    # See https://docs.scipy.org/doc/scipy/reference/tutorial/signal.html#difference-equation-filtering
    # Here, we have y[t] - discount*y[t+1] = x[t]
    # or rev(y)[t] - discount*rev(y)[t-1] = rev(x)[t]
    return scipy.signal.lfilter([1], [1, -discount], x[::-1], axis=0)[::-1]