python/mxnet/ndarray/numpy/random.py
def lognormal(mean=0.0, sigma=1.0, size=None, dtype=None, ctx=None, out=None):
    r"""Draw samples from a log-normal distribution.
    Draw samples from a log-normal distribution with specified mean,
    standard deviation, and array shape.  Note that the mean and standard
    deviation are not the values for the distribution itself, but of the
    underlying normal distribution it is derived from.
    Parameters
    ----------
    mean : float or array_like of floats, optional
        Mean value of the underlying normal distribution. Default is 0.
    sigma : float or array_like of floats, optional
        Standard deviation of the underlying normal distribution. Must be
        non-negative. Default is 1.
    size : int or tuple of ints, optional
        Output shape.  If the given shape is, e.g., ``(m, n, k)``, then
        ``m * n * k`` samples are drawn.  If size is ``None`` (default),
        a single value is returned if ``mean`` and ``sigma`` are both scalars.
        Otherwise, ``np.broadcast(mean, sigma).size`` samples are drawn.
    dtype : {'float16', 'float32', 'float64'}, optional
        Data type of output samples. Default is 'float32'
    ctx : Context, optional
        Device context of output. Default is current context.
    out : ``ndarray``, optional
        Store output to an existing ``ndarray``.
    Returns
    -------
    out : ndarray or scalar
        Drawn samples from the parameterized log-normal distribution.
    """
    from . import _op as _mx_np_op
    return _mx_np_op.exp(normal(loc=mean, scale=sigma, size=size, dtype=dtype, ctx=ctx, out=out))
r"""Draw samples from a log-normal distribution.
    Draw samples from a log-normal distribution with specified mean,
    standard deviation, and array shape.  Note that the mean and standard
    deviation are not the values for the distribution itself, but of the
    underlying normal distribution it is derived from.
    Parameters
    ----------
    mean : float or array_like of floats, optional
        Mean value of the underlying normal distribution. Default is 0.
    sigma : float or array_like of floats, optional
        Standard deviation of the underlying normal distribution. Must be
        non-negative. Default is 1.
    size : int or tuple of ints, optional
        Output shape.  If the given shape is, e.g., ``(m, n, k)``, then
        ``m * n * k`` samples are drawn.  If size is ``None`` (default),
        a single value is returned if ``mean`` and ``sigma`` are both scalars.
        Otherwise, ``np.broadcast(mean, sigma).size`` samples are drawn.
    dtype : {'float16', 'float32', 'float64'}, optional
        Data type of output samples. Default is 'float32'
    ctx : Context, optional
        Device context of output. Default is current context.
    out : ``ndarray``, optional
        Store output to an existing ``ndarray``.
    Returns
    -------
    out : ndarray or scalar
        Drawn samples from the parameterized log-normal distribution.
    
r"""Draw samples from a log-normal distribution.
Draw samples from a log-normal distribution with specified mean,
standard deviation, and array shape.  Note that the mean and standard
deviation are not the values for the distribution itself, but of the
underlying normal distribution it is derived from.
Parameters

mean : float or array_like of floats, optional
Mean value of the underlying normal distribution. Default is 0.
sigma : float or array_like of floats, optional
Standard deviation of the underlying normal distribution. Must be
non-negative. Default is 1.
size : int or tuple of ints, optional
Output shape.

out : ndarray or scalar
Drawn samples from the parameterized log-normal distribution.
r " " " Draw samples from a log - normal distribution . Draw samples from a log - normal distribution with specified mean standard deviation and array shape . Note that the mean and standard deviation are not the values for the distribution itself but of the underlying normal distribution it is derived from . Parameters mean : float or array_like of floats optional Mean value of the underlying normal distribution . Default is 0 . sigma : float or array_like of floats optional Standard deviation of the underlying normal distribution . Must be non - negative . Default is 1 . size : int or tuple of ints optional Output shape . out : ndarray or scalar Drawn samples from the parameterized log - normal distribution .
def lognormal(mean=0.0, sigma=1.0, size=None, dtype=None, ctx=None, out=None):
    from . import _op as _mx_np_op
    return _mx_np_op.exp(normal(loc=mean, scale=sigma, size=size, dtype=dtype, ctx=ctx, out=out))
def lognormal ( mean = 0.0 , sigma = 1.0 , size = None , dtype = None , ctx = None , out = None ) : from . import _op as _mx_np_op return _mx_np_op . exp ( normal ( loc = mean , scale = sigma , size = size , dtype = dtype , ctx = ctx , out = out ) )
r"""Draw samples from a log-normal distribution.
r " " " Draw samples from a log - normal distribution .
r"""Draw samples from a log-normal distribution.
    Draw samples from a log-normal distribution with specified mean,
    standard deviation, and array shape.  Note that the mean and standard
    deviation are not the values for the distribution itself, but of the
    underlying normal distribution it is derived from.
    Parameters
    ----------
    mean : float or array_like of floats, optional
        Mean value of the underlying normal distribution. Default is 0.
    sigma : float or array_like of floats, optional
        Standard deviation of the underlying normal distribution. Must be
        non-negative. Default is 1.
    size : int or tuple of ints, optional
        Output shape.  If the given shape is, e.g., ``(m, n, k)``, then
        ``m * n * k`` samples are drawn.  If size is ``None`` (default),
        a single value is returned if ``mean`` and ``sigma`` are both scalars.
        Otherwise, ``np.broadcast(mean, sigma).size`` samples are drawn.
    dtype : {'float16', 'float32', 'float64'}, optional
        Data type of output samples. Default is 'float32'
    ctx : Context, optional
        Device context of output. Default is current context.
    out : ``ndarray``, optional
        Store output to an existing ``ndarray``.
    Returns
    -------
    out : ndarray or scalar
        Drawn samples from the parameterized log-normal distribution.
    """
mean
sigma
size
dtype
ctx
out