message: Code review : Add a bw_method parameter to plot_persistence_density for the standard deviation of the Gaussian
diff: @@ -223,7 +223,8 @@ try:
  import math
  def plot_persistence_density(persistence=[], persistence_file='',
  - nbins=300, max_plots=1000, dimension=None,
  + nbins=300, bw_method=None,
  + max_plots=1000, dimension=None,
  cmap=plt.cm.hot_r, legend=False):
  """This function plots the persistence density from persistence
  values list or from a :doc:`persistence file <fileformats>`. Be
  @@ -238,6 +239,14 @@ try:
  :param nbins: Evaluate a gaussian kde on a regular grid of nbins x
  nbins over data extents (default is 300)
  :type nbins: int.
  + :param bw_method: The method used to calculate the estimator
  + bandwidth. This can be 'scott', 'silverman', a scalar constant
  + or a callable. If a scalar, this will be used directly as
  + kde.factor. If a callable, it should take a gaussian_kde
  + instance as only parameter and return a scalar. If None
  + (default), 'scott' is used. See scipy.stats.gaussian_kde
  + documentation for more details.
  + :type bw_method: str, scalar or callable, optional.
  :param max_plots: maximal number of points to display. Selected points
  are those with the longest life time. Set it to 0 to see all,
  default value is 1000.
  @@ -286,7 +295,7 @@ try:
  plt.plot(x, x, color='k', linewidth=1.0)
  # Evaluate a gaussian kde on a regular grid of nbins x nbins over data extents
  - k = kde.gaussian_kde([birth,death])
  + k = kde.gaussian_kde([birth,death], bw_method=bw_method)
  xi, yi = np.mgrid[birth.min():birth.max():nbins*1j, death.min():death.max():nbins*1j]
  zi = k(np.vstack([xi.flatten(), yi.flatten()]))
  