def get_processed_data(self, do_coarsen=True, do_trim=True):
<EOL>xdatas, ydatas, eydatas = self.get_data()<EOL>xmins   = self['<STR_LIT>']<EOL>xmaxs   = self['<STR_LIT>']<EOL>ymins   = self['<STR_LIT>']<EOL>ymaxs   = self['<STR_LIT>']<EOL>coarsen = self['<STR_LIT>'] <EOL>if type(xmins)   is not list: xmins   = [xmins]  *len(xdatas)<EOL>if type(xmaxs)   is not list: xmaxs   = [xmaxs]  *len(xdatas)<EOL>if type(ymins)   is not list: ymins   = [ymins]  *len(xdatas)<EOL>if type(ymaxs)   is not list: ymaxs   = [ymaxs]  *len(xdatas)<EOL>if type(coarsen) is not list: coarsen = [coarsen]*len(xdatas)<EOL>xdata_massaged  = []<EOL>ydata_massaged  = []<EOL>eydata_massaged = []<EOL>for n in range(len(xdatas)):<EOL><INDENT>x  = xdatas[n]<EOL>y  = ydatas[n]<EOL>ey = eydatas[n]<EOL>if do_coarsen:<EOL><INDENT>x  =         _s.fun.coarsen_array(x,     self['<STR_LIT>'][n], '<STR_LIT>')<EOL>y  =         _s.fun.coarsen_array(y,     self['<STR_LIT>'][n], '<STR_LIT>')<EOL>ey = _n.sqrt(_s.fun.coarsen_array(ey**<NUM_LIT:2>, self['<STR_LIT>'][n], '<STR_LIT>')/self['<STR_LIT>'][n])<EOL><INDENT>if not ex == None:<EOL><INDENT>ex = _n.sqrt(_s.fun.coarsen_array(ex**<NUM_LIT:2>, self['<STR_LIT>'][n], '<STR_LIT>')/self['<STR_LIT>'][n])<EOL><DEDENT><DEDENT><DEDENT>if do_trim:<EOL><INDENT>xmin = xmins[n]<EOL>ymin = ymins[n]<EOL>xmax = xmaxs[n]<EOL>ymax = ymaxs[n]<EOL>if xmin is None: xmin = min(x)<EOL>if xmax is None: xmax = max(x)<EOL>if ymin is None: ymin = min(y)<EOL>if ymax is None: ymax = max(y)<EOL>[xt, yt, eyt] = _s.fun.trim_data_uber([x, y, ey],<EOL>[x>=xmin, x<=xmax,<EOL>y>=ymin, y<=ymax])<EOL>if(len(xt)==<NUM_LIT:0>): <EOL><INDENT>self._error("<STR_LIT>"+str(n)+"<STR_LIT>")<EOL><DEDENT>else:<EOL><INDENT>x = xt<EOL>y = yt<EOL>ey = eyt<EOL><DEDENT><DEDENT>xdata_massaged.append(x)<EOL>ydata_massaged.append(y)<EOL>eydata_massaged.append(ey)<EOL><DEDENT>return xdata_massaged, ydata_massaged, eydata_massaged<EOL>
This will coarsen and then trim the data sets according to settings.

Returns processed xdata, ydata, eydata.

Parameters
----------
do_coarsen=True
    Whether we should coarsen the data
do_trim=True
    Whether we should trim the data

Settings
--------
xmin, xmax, ymin, ymax
    Limits on x and y data points for trimming.    
coarsen
    Break the data set(s) into this many groups of points, and average
    each group into one point, propagating errors.