probem with FaceColor of bar

R=[0.779810425627480	0.000659297275251825	0.688360393160301	0.184532497610895	0.0905962113611394	0.0626722269195076	0.115760244765211	9.82482188727207e-06]
R2=[0.780896183843548	0.783089437325240	0.824384828931732	0.783480655246833	0.782324163937975	0.843400789787716	0.780259820660027	0.692761472581375	0.186630591612089	0.112331622540645	0.0684118151132265	0.124754260377728	0.000750940658416743	0.786209417062528	0.696211586340910	0.704468853008563	0.793533655775326	0.689231222654964	0.247394539787509	0.259526400351099	0.187357565089202	0.306685869655797	0.221985207424738	0.213936150337528	0.0911810803863357	0.226392210021089	0.0628097955366125	0.177330398333869]
R3=[0.783714743066040	0.826211863604426	0.783570491492865	0.784235776628874	0.846564931503649	0.781795435841793	0.824795480225099	0.793293977502063	0.807394055917125	0.843543223850931	0.784225204506264	0.828604905652616	0.830131797565598	0.845605618105580	0.866367812401167	0.784125887674771	0.844962871032082	0.783775317173255	0.857006696649914	0.782646132825257	0.886525345744327	0.792443729599900	0.707602204791307	0.706291944439437	0.795689075333992	0.692960273475268	0.269367754096017	0.269897642276868	0.187804460375981	0.338233654026156	0.308011853235251	0.214628124374582	0.117141128901629	0.229057283333948	0.0684491039966618	0.183900696434232	0.789982210441524	0.793671406033401	0.807345796487103	0.835447142202684	0.705376496011716	0.804011717368906	0.696706432568307	0.795703083661133	0.705025556256066	0.832447316043765	0.383708291936295	0.256938376298548	0.368132130189507	0.275653288847231	0.375594581589765	0.328508421589727	0.426445219789627	0.222082122851731	0.295080637436694	0.303500075279901]
R4=[0.826996774935897	0.794557334602349	0.809619574536623	0.846642577477218	0.785322675618129	0.828939025798648	0.833675796861419	0.847202474959195	0.881468153988862	0.784703824104669	0.851106275596922	0.784004921796498	0.858781120350036	0.785070083916637	0.888559577339896	0.828833804725073	0.834955475482176	0.846195401779085	0.867140402842741	0.813983848871127	0.845075441261779	0.794705445368061	0.872508246817512	0.810962400206204	0.886525524768893	0.831303117637229	0.847642143194423	0.868934285031242	0.858409734520770	0.872566944267203	0.906757870765131	0.857428757371442	0.784387451549559	0.886620441089954	0.905697241656523	0.801922541124688	0.797636506176264	0.807358981738157	0.862781849694327	0.710334094086818	0.804080272956492	0.707686352900283	0.798434388040983	0.706487674364295	0.833750942309195	0.471755923663536	0.270095621013156	0.456472753439997	0.277630257351045	0.430498750484947	0.343336309036551	0.454955851249911	0.317945379843094	0.298347039374467	0.304574520635417	0.794166474258310	0.814390776564570	0.840239456373557	0.810347726332535	0.841150193698107	0.877516625338572	0.804070982436114	0.705841896439888	0.849259411824625	0.832907343342206	0.437358816488236	0.495244980869643	0.405878538783720	0.424820970524598	0.547495448988831]
R5=[0.828991929369686	0.838411193709899	0.847498079098537	0.884286848091013	0.813984689455561	0.852689268734507	0.795461615160834	0.873675836205425	0.815033194461026	0.888567443766334	0.833676221089556	0.851532466108260	0.881503316538568	0.859249568891160	0.893364109834186	0.907586430555856	0.858785564028645	0.785320228500511	0.889516792068951	0.906442600699576	0.838035644265987	0.847642955904863	0.868937970747267	0.873278896824283	0.876253552968026	0.908008036718245	0.872689586925684	0.817720580546422	0.886663386046064	0.937203366812540	0.858609315682532	0.872839144872220	0.907099734481859	0.924204051669980	0.910846971035114	0.802163827732857	0.815595411648910	0.884996077524746	0.810350740286317	0.864252213958193	0.883287964927457	0.804103360669447	0.710335861966019	0.849504374181575	0.834436602026480	0.484612221304780	0.704965265425382	0.460974241930084	0.447415007134505	0.598056626502316	0.814518098488400	0.842523239334591	0.888286770499680	0.878177732084617	0.852719060026541	0.604403396129531]
R6=[0.839071360465035	0.852704784532168	0.887822544505265	0.876021378692969	0.896575199509569	0.909363801082844	0.875080432727216	0.818093523631484	0.890239643298577	0.937369178243077	0.859250167086107	0.903297054324622	0.907629634392680	0.926273966668406	0.911091067394923	0.873423351158586	0.877473297910146	0.908008113026594	0.941060841208969	0.938200096744872	0.927636099224910	0.815597023464531	0.891134879647912	0.903795572804284	0.883537686178393	0.854841118650416	0.733815636601844	0.889727749438983]
R7=[0.878642031246962	0.903669866631326	0.910417834781449	0.941547570214469	0.938233123072641	0.937500290384948	0.942085824188201	0.914574284340743]
R8=[0.945329036585856]
R_all = [R R2 R3 R4 R5 R6 R7 R8];
label_all = [label,label2,label3,label4,label5,label6,label7,label8];


[R_all_sort,ind_sort] = sort(R_all,'descend');
label_all_sort = label_all(ind_sort);

threshold = 0.95;
logical_index = R_all_sort>=threshold;
N_true = length(find(logical_index));

figure
hall=bar(R_all_sort(logical_index));
hold on
grid on
xlabel('metriche lavatrice');
ylabel('R^2 lavatrice ');
ax=gca;
ax.XTick = 1:N_true; 
ax.XTickLabels = label_all_sort(logical_index);
ax.XTickLabelRotation = 90;
legend({'soggettività:lavatrice' });
ylim([threshold 1]);

hi i have a problem, i need to have differet color when i plot the figure bar (Facecolor) like this:

R = red

R2= green

R3= white

R4 =cyan

R5=blue

R6=yellow

R7=black

R8= magenta

[dpb]

threshold = 0.95;
logical_index = R_all_sort>=threshold;
...

>> sum(logical_index)
ans =
     0
>> max(R_all)
ans =
    0.9453
>> 

There are no elements above the threshold so nothing will show up on the plot.

Also, you've mixed all elements up in combining into one long vector and then sorted that vector so there's no identification from which element any particular value came.

Would need to define corollary array of group number to carry along.

Answer 1

[darova]

One way:

R=[0.779810425627480	0.000659297275251825	0.688360393160301	0.184532497610895	0.0905962113611394	0.0626722269195076	0.115760244765211	9.82482188727207e-06];
R2=[0.780896183843548	0.783089437325240	0.824384828931732	0.783480655246833	0.782324163937975	0.843400789787716	0.780259820660027	0.692761472581375	0.186630591612089	0.112331622540645	0.0684118151132265	0.124754260377728	0.000750940658416743	0.786209417062528	0.696211586340910	0.704468853008563	0.793533655775326	0.689231222654964	0.247394539787509	0.259526400351099	0.187357565089202	0.306685869655797	0.221985207424738	0.213936150337528	0.0911810803863357	0.226392210021089	0.0628097955366125	0.177330398333869];
R3=[0.783714743066040	0.826211863604426	0.783570491492865	0.784235776628874	0.846564931503649	0.781795435841793	0.824795480225099	0.793293977502063	0.807394055917125	0.843543223850931	0.784225204506264	0.828604905652616	0.830131797565598	0.845605618105580	0.866367812401167	0.784125887674771	0.844962871032082	0.783775317173255	0.857006696649914	0.782646132825257	0.886525345744327	0.792443729599900	0.707602204791307	0.706291944439437	0.795689075333992	0.692960273475268	0.269367754096017	0.269897642276868	0.187804460375981	0.338233654026156	0.308011853235251	0.214628124374582	0.117141128901629	0.229057283333948	0.0684491039966618	0.183900696434232	0.789982210441524	0.793671406033401	0.807345796487103	0.835447142202684	0.705376496011716	0.804011717368906	0.696706432568307	0.795703083661133	0.705025556256066	0.832447316043765	0.383708291936295	0.256938376298548	0.368132130189507	0.275653288847231	0.375594581589765	0.328508421589727	0.426445219789627	0.222082122851731	0.295080637436694	0.303500075279901];
R4=[0.826996774935897	0.794557334602349	0.809619574536623	0.846642577477218	0.785322675618129	0.828939025798648	0.833675796861419	0.847202474959195	0.881468153988862	0.784703824104669	0.851106275596922	0.784004921796498	0.858781120350036	0.785070083916637	0.888559577339896	0.828833804725073	0.834955475482176	0.846195401779085	0.867140402842741	0.813983848871127	0.845075441261779	0.794705445368061	0.872508246817512	0.810962400206204	0.886525524768893	0.831303117637229	0.847642143194423	0.868934285031242	0.858409734520770	0.872566944267203	0.906757870765131	0.857428757371442	0.784387451549559	0.886620441089954	0.905697241656523	0.801922541124688	0.797636506176264	0.807358981738157	0.862781849694327	0.710334094086818	0.804080272956492	0.707686352900283	0.798434388040983	0.706487674364295	0.833750942309195	0.471755923663536	0.270095621013156	0.456472753439997	0.277630257351045	0.430498750484947	0.343336309036551	0.454955851249911	0.317945379843094	0.298347039374467	0.304574520635417	0.794166474258310	0.814390776564570	0.840239456373557	0.810347726332535	0.841150193698107	0.877516625338572	0.804070982436114	0.705841896439888	0.849259411824625	0.832907343342206	0.437358816488236	0.495244980869643	0.405878538783720	0.424820970524598	0.547495448988831];
R5=[0.828991929369686	0.838411193709899	0.847498079098537	0.884286848091013	0.813984689455561	0.852689268734507	0.795461615160834	0.873675836205425	0.815033194461026	0.888567443766334	0.833676221089556	0.851532466108260	0.881503316538568	0.859249568891160	0.893364109834186	0.907586430555856	0.858785564028645	0.785320228500511	0.889516792068951	0.906442600699576	0.838035644265987	0.847642955904863	0.868937970747267	0.873278896824283	0.876253552968026	0.908008036718245	0.872689586925684	0.817720580546422	0.886663386046064	0.937203366812540	0.858609315682532	0.872839144872220	0.907099734481859	0.924204051669980	0.910846971035114	0.802163827732857	0.815595411648910	0.884996077524746	0.810350740286317	0.864252213958193	0.883287964927457	0.804103360669447	0.710335861966019	0.849504374181575	0.834436602026480	0.484612221304780	0.704965265425382	0.460974241930084	0.447415007134505	0.598056626502316	0.814518098488400	0.842523239334591	0.888286770499680	0.878177732084617	0.852719060026541	0.604403396129531];
R6=[0.839071360465035	0.852704784532168	0.887822544505265	0.876021378692969	0.896575199509569	0.909363801082844	0.875080432727216	0.818093523631484	0.890239643298577	0.937369178243077	0.859250167086107	0.903297054324622	0.907629634392680	0.926273966668406	0.911091067394923	0.873423351158586	0.877473297910146	0.908008113026594	0.941060841208969	0.938200096744872	0.927636099224910	0.815597023464531	0.891134879647912	0.903795572804284	0.883537686178393	0.854841118650416	0.733815636601844	0.889727749438983];
R7=[0.878642031246962	0.903669866631326	0.910417834781449	0.941547570214469	0.938233123072641	0.937500290384948	0.942085824188201	0.914574284340743];
R8=[0.945329036585856];
R_all = [R R2 R3 R4 R5 R6 R7 R8];
color_ind = [R*0+1 R2*0+2 R3*0+3 R4*0+4 R5*0+5 R6*0+6 R7*0+7 R8*0+8];
cm = 'rgwcbykm';        % reg green white ...
[R_all_sort,ind_sort] = sort(R_all,'descend');
color_sort = color_ind(ind_sort);
threshold = 0.95;
ind1 = find( R_all_sort<=threshold );
cla
hold on
for i = ind1
    h = bar(ind1(i),R_all_sort(i));
    set(h,'EdgeColor','none','FaceColor',cm(color_sort(i)))
end
hold off

But works slow. Any idea of how speed it up?

[dpb]

Use the array form for the bar plot so only have one handle then set the 'CData' property for the face color. There's an example in the doc for it.

BUT yet again example of the difficult and "user-belligerent" interface to the bar() function. That one can't just set 'FaceColor' by bar is incomprehensible TMW would have designed it this way--couldn't be made more unintuitive if had tried on purpose.

[darova]

That part with bar i replaced with:

h = bar(ind1,R_all_sort);
h1 = get(h,'children');
mcolor(ind1,:) = cm(color_sort(ind1),:);    
set(h1,'faceVertexCData',mcolor)
set(h1,'EdgeColor','none')

ANd it works fast now

[dpb]

Curiousity only--why choose to go "handle diving" instead of using the CData property of the bar object directly as below Answer?

[darova]

I have older version (v2013)

And this doesn't work

hBar.FaceColor='flat';
hBar.CData=clrs(isort(G),:);

[dpb]

Ah so!

[darova]

Yes, Sir!

Answer 2

[dpb]

Carrying on from the above after defining data...

clrs=[[1 0 0];[0 1 0];[1 1 1];[0 1 1];[0 0 1];[1 1 0];[0 0 0];[1 0 1]]; % rgb for named colors
R1=R;      % just for symmetry in naming
G=[1+R1*0 2+R2*0 3+R3*0 4+R4*0 5+R5*0 6+R6*0 7+R7*0 8+R8*0];
threshold=0.925;      % 0.95 > max() --> no elements selected
ix=(R_all>=threshold);
R=R_all(ix); 
[~,isort]=sort(R,'descend');
hBar=bar(R(isort));
hBar.FaceColor='flat';
hBar.CData=clrs(isort(G),:);

returns

[darova]

Works olrait thenks!