How to scale colors in a surface plot?

I am trying to generate a surface plot of Z values which are spaced very closely. I want to increase the contrast between neighboring cells on the surface plot for better visualization. What caxis/cdata properties should I use to get the best results?

Data examples:

I used a trial surface plot as follows:

x = [1 2]
y = [1 10]
z = [1,2;3 4]
surf(x,y,z)
view([0 90])
colorbar

Ideally, I would expect to see 4 blocks of different colors, but that is not the case. The entire surface shows up in one color. I am also unable to see the edges between the blocks. Changing the colormap by using

colormap(parula(4))

also does not make any difference.

My actual data is a 10x10 matrix with values between 0.0088 and 0.0127. The values in adjacent cells differ by really small amounts (0.00884 vs 0.00888). The data matrix is as follows:

0.00876220534845146  0.00877104243587021  0.00876090584272109  0.00876567260262740  0.00877338265553330  0.00880918902217270  0.00895731874309425  0.00951657095953469  0.0109001629521629  0.0126821110606861
0.00876247970885279  0.00876690070321591  0.00876721289176976  0.00877044328278834  0.00877564055025469  0.00881049364717492  0.00896310746064269  0.00951343028626726  0.0108689023842528  0.0126510510201670
0.00876481343830752  0.00876054127638956  0.00876546930498490  0.00876490398040193  0.00877568263726239  0.00881585329363156  0.00896272910588365  0.00952730819295550  0.0109010913028391  0.0126706393115163
0.00876600015772925  0.00876949737661547  0.00876931859294129  0.00876402911687813  0.00876557010714387  0.00881606549775236  0.00896451857976756  0.00952714448559324  0.0108471119108242  0.0125212904479189
0.00876760428031093  0.00875823445220582  0.00876319476549683  0.00876488785196009  0.00877212913497060  0.00880570616657179  0.00896058270945542  0.00948143683254961  0.0107756633536715  0.0122492486134851
0.00876724755370901  0.00875868602315279  0.00876292742174361  0.00876389151819509  0.00877614757341313  0.00880405920256963  0.00895849194783554  0.00945441140843719  0.0106578297353646  0.0117705806178655
0.00875709751801196  0.00876230443405094  0.00875877221862310  0.00875675590916622  0.00877170577177424  0.00879671567609802  0.00893077626458064  0.00937227941125520  0.0102882513321246  0.0110844990048619
0.00875236460269681  0.00875436716031473  0.00875502024420794  0.00874780733728857  0.00875710181594459  0.00877867781225910  0.00886642910075277  0.00920957851223199  0.00977919981733224  0.0102216960444418
0.00873770435277100  0.00874090882972177  0.00872472010882448  0.00873518319625914  0.00873764376473520  0.00874310305392874  0.00876976131446554  0.00885262900954216  0.00911920911788668  0.00934021837836617
0.00869739094626631  0.00869465228868750  0.00869366725125587  0.00870410776620277  0.00867693016050622  0.00864493598374698  0.00853265992213025  0.00841254480825253  0.00835353175045488  0.00832560991088847

Any ideas on how to visualize this using surf would be appreciated.

Answer 1

[Chad Greene]

Ah, that's because surf and pcolor delete a row and column of data. I know, it's nonsensical. Try this instead:

 imagesc(x,y,z)
 axis xy

[Chad Greene]

And if you want to change the color scale values more you can do so like

 caxis([0.009 0.011])

[smog]

I did try caxis, but it didn't work on the test data due to surf deleting a row and column.

I used padarray to pad the data with 0's and used the new array to generate the surface plot. Ended up working for me.