Python KDE.grid_evaluate Examples

Example #1

File: bmodes_ia.py Project: ssamuroff/y3cosmicshear

 def smooth_likelihood(obj,x, y):
     n = obj.options.get("n_kde", 100)
     factor = obj.options.get("factor_kde", 2.0)
     kde = KDE([x,y], factor=factor)
     x_range = (x.min(), x.max())
     y_range = (y.min(), y.max())
     (x_axis, y_axis), like = kde.grid_evaluate(n, [x_range, y_range])
     return n, x_axis, y_axis, like

Example #2

File: mkplt.py Project: ssamuroff/cosmology_code

 def smooth_likelihood(self, x, y):
     n = self.options.get("n_kde", 100)
     factor = self.options.get("factor_kde", 2.0)
     kde = KDE([x,y], factor=factor)
     x_range = (x.min(), x.max())
     y_range = (y.min(), y.max())
     (x_axis, y_axis), like = kde.grid_evaluate(n, [x_range, y_range])
     return n, x_axis, y_axis, like

Example #3

File: bmodes_ia.py Project: ssamuroff/y3cosmicshear

 def smooth_likelihood(obj,x, y):
     n = 100
     factor =  2.0
     kde = KDE([x,y], factor=factor)
     x_range = (x.min(), x.max())
     y_range = (y.min(), y.max())
     (x_axis, y_axis), like = kde.grid_evaluate(n, [x_range, y_range])
     return n, x_axis, y_axis, like