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How can I make a custom divergent colormap in Sage? What I want is the same than the reverse seismic divergend colormap (Divergend Colormaps) but the blue value schould be less intensiv (e. g. conflower blue [Hex color code: #6495ED]).

In the sage source code I found the following link Divergend Colormaps, which explains the divergent colormaps and has a python class in the attachments. But still I have no clue to make such a divergent colormap.

I have also tryed to make it with a LinearSegementedColormap:
from pylab import *
startcolor = '#FF0000'
midcolor = '#FFFFFF'
endcolor = '#0030CC'
own_cmap1 = matplotlib.colors.LinearSegmentedColormap.from_list( 'own2', [startcolor, midcolor, endcolor] )
matrix_plot( matrix( [ [1,3,5,1], [2,4,5,6], [1,-3,5,7] ] ), cmap = own_cmap1, colorbar = True )


but the result is absolutely not what I want, because it goes to fast from red into pink.

How can I make a custom divergent diverging colormap in Sage? What I want is the same than the reverse seismic divergend diverging colormap (Divergend Diverging Colormaps) but the blue value schould should be less intensiv intense (e. g. conflower blue [Hex color code: #6495ED]).

In the sage source code I found the following link Divergend Diverging Colormaps, which explains the divergent colormaps and has a python class in the attachments. But still I have no clue to make such a divergent diverging colormap.

I have also tryed tried to make it with a LinearSegementedColormap:
LinearSegementedColormap:

 from pylab import * 
 *
startcolor = '#FF0000' 
 '#FF0000'
midcolor = '#FFFFFF' 
 '#FFFFFF'
endcolor = '#0030CC' 
 '#0030CC'
own_cmap1 = matplotlib.colors.LinearSegmentedColormap.from_list( 'own2', [startcolor, midcolor, endcolor] ) 
 )
matrix_plot( matrix( [ [1,3,5,1], [2,4,5,6], [1,-3,5,7] ] ), cmap = own_cmap1, colorbar = True ) 
 )

but the result is absolutely not what I want, because it goes to too fast from red into pink.