plot_pdf

sherpa.ui.plot_pdf(points, name='x', xlabel='x', bins=12, normed=True, replot=False, overplot=False, clearwindow=True)

Plot the probability density function of an array of values.

Create and plot the probability density function (PDF) of the input array.

Parameters:
  • points (array) – The values used to create the probability density function.
  • name (str, optional) – The label to use as part of the plot title.
  • xlabel (str, optional) – The label for the X axis
  • bins (int, optional) – The number of bins to use to create the PDF.
  • normed (bool, optional) – Should the PDF be normalized (the default is True).
  • replot (bool, optional) – Set to True to use the values calculated by the last call to plot_pdf. The default is False.
  • overplot (bool, optional) – If True then add the data to an exsiting plot, otherwise create a new plot. The default is False.
  • clearwindow (bool, optional) – When using ChIPS for plotting, should the existing frame be cleared before creating the plot?

See also

get_draws()
Run the pyBLoCXS MCMC algorithm.
get_pdf_plot()
Return the data used to plot the last PDF.
plot_cdf()
Plot the cumulative density function of an array.
plot_scatter()
Create a scatter plot.

Examples

>>> mu, sigma, n = 100, 15, 500
>>> x = np.random.normal(loc=mu, scale=sigma, size=n)
>>> plot_pdf(x, bins=25)

>>> plot_pdf(x, normed=False, xlabel="mu", name="Simulations")