def gray_plot(data, min=0, max=1, name=""):
reshape = importr('reshape')
gg = ggplot2.ggplot(reshape.melt(data,id_var=['x','y']))
pg = gg + ggplot2.aes_string(x='L1',y='L2')+ \
ggplot2.geom_tile(ggplot2.aes_string(fill='value'))+ \
ggplot2.scale_fill_gradient(low="black", high="white",limits=FloatVector((min,max)))+ \
ggplot2.coord_equal() + ggplot2.scale_x_continuous(name)
return pg
def gray_plot(data, min=0, max=1, name=""):
reshape = importr('reshape')
gg = ggplot2.ggplot(reshape.melt(data, id_var=['x', 'y']))
pg = gg + ggplot2.aes_string(x='L1',y='L2')+ \
ggplot2.geom_tile(ggplot2.aes_string(fill='value'))+ \
ggplot2.scale_fill_gradient(low="black", high="white",limits=FloatVector((min,max)))+ \
ggplot2.coord_equal() + ggplot2.scale_x_continuous(name)
return pg
## (see http://permalink.gmane.org/gmane.comp.python.rpy/2349)
## note that we use dictionary to set the opts to be able to set options as keywords, for example legend.key.size
p_map = ggplot2.ggplot(IL_final) + \
ggplot2.geom_polygon(ggplot2.aes(x = 'long', y = 'lat', group = 'group', color = 'ObamaShare', fill = 'ObamaShare')) + \
ggplot2.scale_fill_gradient(high = 'blue', low = 'red') + \
ggplot2.scale_fill_continuous(name = "Obama Vote Share") + \
ggplot2.scale_colour_continuous(name = "Obama Vote Share") + \
ggplot2.opts(**{'legend.position': 'left', 'legend.key.size': robjects.r.unit(2, 'lines'), 'legend.title' : ggplot2.theme_text(size = 14, hjust=0), \
'legend.text': ggplot2.theme_text(size = 12), 'title' : "Obama Vote Share and Distance to Railroads in IL", \
'plot.title': ggplot2.theme_text(size = 24), 'plot.margin': robjects.r.unit(robjects.r.rep(0,4),'lines'), \
'panel.background': ggplot2.theme_blank(), 'panel.grid.minor': ggplot2.theme_blank(), 'panel.grid.major': ggplot2.theme_blank(), \
'axis.ticks': ggplot2.theme_blank(), 'axis.title.x': ggplot2.theme_blank(), 'axis.title.y': ggplot2.theme_blank(), \
'axis.title.x': ggplot2.theme_blank(), 'axis.title.x': ggplot2.theme_blank(), 'axis.text.x': ggplot2.theme_blank(), \
'axis.text.y': ggplot2.theme_blank()} ) + \
ggplot2.geom_line(ggplot2.aes(x='long', y='lat', group='group'), data=IL_railroads, color='grey', size=0.2) + \
ggplot2.coord_equal()
p_map.plot()
## add the scatterplot
## define layout of subplot with viewports
vp_sub = grid.viewport(x = 0.19, y = 0.2, width = 0.32, height = 0.4)
p_sub = ggplot2.ggplot(RR_distance) + \
ggplot2.aes_string(x = 'OBAMA_SHAR', y= 'NEAR_DIST') + \
ggplot2.geom_point(ggplot2.aes(color='OBAMA_SHAR')) + \
ggplot2.stat_smooth(color="black") + \
ggplot2.opts(**{'legend.position': 'none'}) + \
ggplot2.scale_x_continuous("Obama Vote Share") + \
ggplot2.scale_y_continuous("Distance to nearest Railroad")
## (see http://permalink.gmane.org/gmane.comp.python.rpy/2349)
## note that we use dictionary to set the opts to be able to set options as keywords, for example legend.key.size
p_map = ggplot2.ggplot(IL_final) + \
ggplot2.geom_polygon(ggplot2.aes(x = 'long', y = 'lat', group = 'group', color = 'ObamaShare', fill = 'ObamaShare')) + \
ggplot2.scale_fill_gradient(high = 'blue', low = 'red') + \
ggplot2.scale_fill_continuous(name = "Obama Vote Share") + \
ggplot2.scale_colour_continuous(name = "Obama Vote Share") + \
ggplot2.opts(**{'legend.position': 'left', 'legend.key.size': robjects.r.unit(2, 'lines'), 'legend.title' : ggplot2.theme_text(size = 14, hjust=0), \
'legend.text': ggplot2.theme_text(size = 12), 'title' : "Obama Vote Share and Distance to Railroads in IL", \
'plot.title': ggplot2.theme_text(size = 24), 'plot.margin': robjects.r.unit(robjects.r.rep(0,4),'lines'), \
'panel.background': ggplot2.theme_blank(), 'panel.grid.minor': ggplot2.theme_blank(), 'panel.grid.major': ggplot2.theme_blank(), \
'axis.ticks': ggplot2.theme_blank(), 'axis.title.x': ggplot2.theme_blank(), 'axis.title.y': ggplot2.theme_blank(), \
'axis.title.x': ggplot2.theme_blank(), 'axis.title.x': ggplot2.theme_blank(), 'axis.text.x': ggplot2.theme_blank(), \
'axis.text.y': ggplot2.theme_blank()} ) + \
ggplot2.geom_line(ggplot2.aes(x='long', y='lat', group='group'), data=IL_railroads, color='grey', size=0.2) + \
ggplot2.coord_equal()
p_map.plot()
## add the scatterplot
## define layout of subplot with viewports
vp_sub = grid.viewport(x=0.19, y=0.2, width=0.32, height=0.4)
p_sub = ggplot2.ggplot(RR_distance) + \
ggplot2.aes_string(x = 'OBAMA_SHAR', y= 'NEAR_DIST') + \
ggplot2.geom_point(ggplot2.aes(color='OBAMA_SHAR')) + \
ggplot2.stat_smooth(color="black") + \
ggplot2.opts(**{'legend.position': 'none'}) + \
ggplot2.scale_x_continuous("Obama Vote Share") + \
ggplot2.scale_y_continuous("Distance to nearest Railroad")