Plot columns of data in discrete datapoints?

Hello,

I am looking to create a plot that creates vertically-connected lines of data over discrete datapoints. So, for example, if I have a matrix such as

Z = [1 2 1; 
     2 2 1; 
     1 1 3]

then I would like to make a plot that looks something like this:

where the numbers at each vertex represent that "x" value for that discrete datapoint.

I have tried using "contour(Z)" however this does not produce the results I am looking for.

Any help is greatly appreciated.

Answer 1

[Star Strider]

Try this —

Z = [1 2 1; 
    2 2 1; 
    1 1 3];

Y = size(Z,2):-1:1;

figure
hold on
for k = 1:numel(Y)
    X = Z(k,:)+2*(k-1);
    plot(X, Y, 'LineWidth',2)
    text(X(end), Y(end), compose('  %.0f',Z(k,end)), 'Horiz','left', 'Vert','bottom')
    text(X(1:end-1), Y(1:end-1), compose('  %.0f',Z(k,1:end-1)), 'Horiz','left', 'Vert','middle')
end
hold off
grid
xlim([-1 1]+xlim)

Experiment with other ‘Z’ matrices. The ‘Y’ vector should adapt to all of them if they are similar in structure to the one provided.

.

[David Gordon]

Wow this is very close to what I need, thank you very much! The only problem now is that my actual data is much more complex than the example I gave, and the lines are not quite behaving how I would expect.

For instance, the lower ends of each line are sloping off to the right, although the bottom column is not any bigger than the rest on average. Do you have any idea why this might be occuring? Here is the plot that I got with my data:

I've changed the 2* in the "for" loop to 20* so that the lines do not overlap, could this be causing the issue?

I've pasted my actual Z matrix below for reference. Once again any help is much appreciated!!

6.89802950000001	28.9361840000000	43.6304410000000	43.8531870000000	44.0390865000000	44.1954830000000	44.3385180000000	44.5337445000000	45.3732045000000	45.6237585000000	45.7038675000000	45.8610375000000	46.7153150000000	48.8962465000000	50.8511520000000	72.6838415000000
6.69302949999999	26.0815615000000	39.9511045000000	41.5139480000000	41.9944020000000	42.4394105000000	42.6730865000000	42.9532755000000	43.7100375000000	43.8761795000000	44.0134950000000	44.1593785000000	44.3030425000000	44.5025020000000	47.8452200000000	78.7887060000000
13.3380295000000	25.9993330000000	40.1603615000000	43.4413890000000	43.8530155000000	44.2218685000000	44.4520075000000	44.6838675000000	44.9680945000000	45.1764650000000	45.4546395000000	47.1048850000000	50.1790095000000	51.5719655000000	55.3720860000000	85.5064055000000
0.423921500000006	26.0737770000000	44.8096360000000	45.1080585000000	45.4921360000000	45.6683455000000	45.7844745000000	45.9245355000000	46.6472775000000	47.3289625000000	49.8861470000000	50.1371645000000	50.2870925000000	50.6038675000000	56.8766320000000	82.8717060000000
0	45.8109945000000	45.7428270000000	46.2208365000000	46.0566360000000	52.2291795000000	25.9593360000000	52.0406880000000	54.2925860000000	29.1180340000000	54.2943935000000	50.0449285000000	50.2411145000000	54.2495200000000	55.4246235000000	87.9383485000000
13.3610295000000	29.8860340000000	44.2388675000000	45.7055020000000	45.8657115000000	45.9151360000000	46.0402290000000	46.2501160000000	50.1017060000000	50.4220095000000	50.5893935000000	51.0051145000000	51.9436880000000	52.3129190000000	54.8636235000000	85.2997060000000
6.73502950000000	26.0761995000000	45.4503400000000	45.7652970000000	45.8496185000000	45.9142465000000	45.9892435000000	46.0471135000000	46.1339375000000	46.3167035000000	47.5945355000000	48.0745200000000	51.1480095000000	51.9409075000000	53.6576235000000	82.5318415000000
6.78402950000000	30.1551490000000	43.3768160000000	43.5401260000000	43.6071795000000	43.6804410000000	43.7337775000000	43.7976880000000	43.9057360000000	43.9769075000000	44.1627445000000	44.3444830000000	49.6495810000000	50.0704770000000	52.0529480000000	85.3387060000000
0.450921499999993	28.2946300000000	46.3818675000000	47.6524135000000	48.2848585000000	49.1199355000000	50.2550585000000	51.9273950000000	52.0262465000000	52.1092290000000	52.2141145000000	52.2942755000000	52.4315115000000	53.2938885000000	59.4984345000000	84.6607060000000
6.75992150000002	25.8729545000000	47.1207850000000	50.1513890000000	50.8393065000000	51.7940390000000	51.9363790000000	52.0784320000000	52.1702465000000	52.3188580000000	52.5160550000000	53.7917025000000	55.6950275000000	55.9688850000000	61.7377060000000	89.8827060000000
6.62002949999999	26.0271785000000	41.2913615000000	43.5608205000000	43.6786100000000	43.7722080000000	43.8103865000000	43.8854180000000	43.9496630000000	44.0600530000000	44.3379075000000	46.7531470000000	50.0065855000000	51.2508885000000	58.3680310000000	90.9347060000000
6.50502950000001	25.9091915000000	43.2387850000000	43.6036415000000	43.9661740000000	45.8286360000000	46.0692045000000	46.3352775000000	46.4713215000000	46.6159810000000	46.7600155000000	47.0298070000000	50.0361520000000	50.5105200000000	52.7421750000000	88.2633485000000
6.16407849999999	30.0050340000000	43.6514440000000	44.0151135000000	44.1037850000000	44.2153005000000	44.3032080000000	44.4465860000000	44.6302700000000	44.7453800000000	44.9564180000000	46.0801195000000	47.6639865000000	48.0279500000000	49.1156585000000	87.8467060000000
6.82602950000000	26.2551995000000	43.6138205000000	43.8570130000000	43.9678580000000	44.1253005000000	44.2520075000000	44.4699075000000	46.1990530000000	48.3000310000000	50.1409865000000	51.2848675000000	51.5292565000000	51.7471255000000	53.7812680000000	69.7527060000000
12.4669705000000	25.8391785000000	43.6289985000000	43.7495860000000	43.8192775000000	43.9273790000000	43.9911135000000	44.0459350000000	44.1342130000000	44.3426190000000	45.2698270000000	48.1712465000000	48.5640860000000	50.2355810000000	50.6806415000000	90.7257060000000
0.302921499999997	30.3441490000000	43.6727975000000	43.7870130000000	43.8730190000000	43.9167780000000	43.9608585000000	43.9998580000000	44.0590530000000	44.0884745000000	44.2328685000000	45.8243615000000	48.4002040000000	48.6644820000000	52.5781255000000	87.0477060000000
0.286921500000005	28.4366300000000	43.6681045000000	43.7574575000000	43.8138850000000	43.9009355000000	43.9743880000000	44.0138365000000	44.0743935000000	44.1754105000000	44.2926415000000	46.5787765000000	50.3582040000000	50.7298800000000	56.8046235000000	89.3317060000000
6.62402950000001	28.4511490000000	45.5114745000000	45.6670275000000	45.7511260000000	45.9385980000000	50.2952710000000	50.8637775000000	51.8370945000000	52.0716485000000	52.3349480000000	53.2237765000000	54.1958110000000	59.7508885000000	65.8241750000000	92.6047060000000
0.316921500000007	30.4031555000000	45.7129075000000	45.8487975000000	46.0590275000000	47.0816360000000	47.2272290000000	47.6106630000000	50.1872700000000	50.3531870000000	50.4410390000000	50.5894020000000	51.0924050000000	54.4152270000000	58.7797060000000	86.8947060000000
6.76302949999999	29.5281315000000	44.5431045000000	45.2171360000000	45.7313455000000	46.5159415000000	46.7651260000000	52.1048675000000	52.2097035000000	52.3133935000000	52.3986415000000	52.4973835000000	53.0732775000000	58.5386320000000	59.2410860000000	86.2513895000000
6.80302949999998	26.2631785000000	45.4156415000000	45.6322290000000	45.8319745000000	46.6802080000000	46.9213325000000	47.4068275000000	49.9080425000000	51.5807080000000	52.5006415000000	52.8969305000000	53.3220095000000	56.8446320000000	58.9505115000000	84.5507060000000
12.9259215000000	26.0361785000000	43.2347975000000	43.3693455000000	43.5644180000000	43.6710585000000	43.8503005000000	45.5878675000000	48.0918675000000	49.8932565000000	50.1730945000000	50.4894820000000	52.0802270000000	53.9436320000000	56.1043150000000	87.4934055000000
0.741029499999996	32.6043045000000	43.5229075000000	43.7979415000000	44.0208160000000	45.6583790000000	45.9200130000000	46.2884030000000	47.9218070000000	50.1323225000000	50.3971255000000	51.9259285000000	53.0777765000000	53.5002040000000	58.0618210000000	78.7958415000000
0.378921500000018	26.0231785000000	43.3048270000000	44.0567955000000	45.8057025000000	45.9910375000000	46.2079985000000	46.5089075000000	48.0358675000000	51.7270945000000	52.0004830000000	53.2525180000000	58.0160925000000	58.2769480000000	61.8468210000000	84.5223485000000
12.1241555000000	30.3400340000000	45.4226415000000	45.8909745000000	46.2618365000000	47.7343785000000	49.9934050000000	51.6310130000000	52.1032435000000	52.3577080000000	53.1764480000000	53.7676360000000	54.1727025000000	56.6001520000000	60.0549865000000	80.0737060000000

[Star Strider]

With respect to what’s causing the lines, the data are the data, and the code simply must adapt to them. For that reason, I created the ‘SepVal’ scalar to replace the current separation value (apparently 20 in your code, 2 in my original code) to be the maximum value in the ‘Z’ matrix. I later multiplied it by 2 so that the numbers are easier to read (otherwise they collide with the line to the right), since the numbers were part of the original request. (The numbers are rounded to the nearest integer.)

(I also created the ‘DG_Z.txt’ to avoid having to copy the ‘Z’ matrix in its entirety here. I also attached it.)

Z = readmatrix('DG_Z.txt')

Z = 25×16

6.8980 28.9362 43.6304 43.8532 44.0391 44.1955 44.3385 44.5337 45.3732 45.6238 45.7039 45.8610 46.7153 48.8962 50.8512 72.6838 6.6930 26.0816 39.9511 41.5139 41.9944 42.4394 42.6731 42.9533 43.7100 43.8762 44.0135 44.1594 44.3030 44.5025 47.8452 78.7887 13.3380 25.9993 40.1604 43.4414 43.8530 44.2219 44.4520 44.6839 44.9681 45.1765 45.4546 47.1049 50.1790 51.5720 55.3721 85.5064 0.4239 26.0738 44.8096 45.1081 45.4921 45.6683 45.7845 45.9245 46.6473 47.3290 49.8861 50.1372 50.2871 50.6039 56.8766 82.8717 0 45.8110 45.7428 46.2208 46.0566 52.2292 25.9593 52.0407 54.2926 29.1180 54.2944 50.0449 50.2411 54.2495 55.4246 87.9383 13.3610 29.8860 44.2389 45.7055 45.8657 45.9151 46.0402 46.2501 50.1017 50.4220 50.5894 51.0051 51.9437 52.3129 54.8636 85.2997 6.7350 26.0762 45.4503 45.7653 45.8496 45.9142 45.9892 46.0471 46.1339 46.3167 47.5945 48.0745 51.1480 51.9409 53.6576 82.5318 6.7840 30.1551 43.3768 43.5401 43.6072 43.6804 43.7338 43.7977 43.9057 43.9769 44.1627 44.3445 49.6496 50.0705 52.0529 85.3387 0.4509 28.2946 46.3819 47.6524 48.2849 49.1199 50.2551 51.9274 52.0262 52.1092 52.2141 52.2943 52.4315 53.2939 59.4984 84.6607 6.7599 25.8730 47.1208 50.1514 50.8393 51.7940 51.9364 52.0784 52.1702 52.3189 52.5161 53.7917 55.6950 55.9689 61.7377 89.8827

SepVal = 2*ceil(max(Z(:)))

SepVal = 186

Y = size(Z,2):-1:1;

figure
hold on
for k = 1:numel(Y)
    X = Z(k,:)+SepVal*(k-1);
    plot(X, Y, 'LineWidth',2)
    text(X(end), Y(end), compose('  %.0f',Z(k,end)), 'Horiz','left', 'Vert','bottom', 'FontSize',8)
    text(X(1:end-1), Y(1:end-1), compose('  %.0f',Z(k,1:end-1)), 'Horiz','left', 'Vert','middle', 'FontSize',8)
end
hold off
grid
xlim([-1 1]*20+xlim)

Experiment with various plot (actually axes)properties to get different results.

.