#NEWLINE# def get_min_size( self , width , height , strength = medium , weight = 0.1 ) : #NEWLINE# #INDENT# ' Run an iteration of the solver with the suggested size of the\n        component set to (0, 0). This will cause the solver to effectively\n        compute the minimum size that the window can be to solve the\n        system.\n\n        Parameters\n        ----------\n        width : Constraint Variable\n            The constraint variable representing the width of the\n            main layout container.\n\n        height : Constraint Variable\n            The constraint variable representing the height of the\n            main layout container.\n\n        strength : casuarius strength, optional\n            The strength with which to perform the layout using the\n            current size of the container. i.e. the strength of the\n            resize. The default is casuarius.medium.\n\n        weight : float, optional\n            The weight to apply to the strength. The default is 0.1\n            so that constraints of medium strength but default weight\n            have a higher precedence than the minimum size.\n\n        Returns\n        -------\n        result : (float, float)\n            The floating point (min_width, min_height) size of the\n            container which would best satisfy the set of constraints.\n\n        ' #NEWLINE# if ( not self . _initialized ) : #NEWLINE# #INDENT# raise RuntimeError ( 'Get min size on uninitialized solver' ) #NEWLINE# #UNINDENT# values = [ ( width , 0.0 ) , ( height , 0.0 ) ] #NEWLINE# with self . _solver . suggest_values ( values , strength , strength ) : #NEWLINE# #INDENT# min_width = width . value #NEWLINE# min_height = height . value #NEWLINE# #UNINDENT# return ( min_width , min_height )