def range_timeplot(ranged_ts, **pltkwds):
''' Makes plots based on ranged time intervals from spec_utilities.wavelength_slices().
Uses a special function, _uvvis_colorss() to map the visible spectrum. Changes default legend
behavior to true.'''
pltkwds['color']=pltkwds.pop('color', _uvvis_colors(ts))
pltkwds['legend']=pltkwds.pop('legend', True)
pltkwds['linewidth']=pltkwds.pop('linewidth', 3.0 )
pltkwds['legend']=pltkwds.pop('legend', True) #Turn legend on
xlabel=pltkwds.pop('xlabel', ranged_ts.full_timeunit)
ylabel=pltkwds.pop('ylabel', ranged_ts.full_iunit)
title=pltkwds.pop('title', 'Ranged Time Plot: '+str(ranged_ts.name) )
return _genplot(ranged_ts.transpose(), xlabel, ylabel, title,**pltkwds) #ts TRANSPOSE
def range_timeplot(df, **pltkwds):
''' Makes plots based on ranged time intervals from spec_utilities.wavelength_slices().
Uses a special function, _uvvis_colorss() to map the visible spectrum. Changes default legend
behavior to true.'''
pltkwds['color']=pltkwds.pop('color', _uvvis_colors(df))
pltkwds['legend']=pltkwds.pop('legend', True)
pltkwds['linewidth']=pltkwds.pop('linewidth', 3.0 )
pltkwds['legend']=pltkwds.pop('legend', True) #Turn legend on
pltkwds['ylabel_def']='Intensity'
pltkwds['xlabel_def']='Time'
pltkwds['title_def']='Ranged Time Plot'
return _genplot(df.transpose(), **pltkwds) #DF TRANSPOSE
