Band Width: 50%
Outlier threshold: 1.5
Constant: 1e-10
Constant: 1e-10

Choose file to visualize functional boxplots.

Select a comma separated value (csv) file to view functional boxplots. The first row of the file should include header names for the columns. One of these headers must be labeled 't' to indicate which column contains the x-values for all funcitons. The other headers can be named anything as long as they are unique.

For example, let's say you wanted to visualize the following five functions between zero and one.

  • F1(t) = 0.75t2
  • F2(t) = t2
  • F3(t) = 1.25t2
  • F4(t) = t5
  • F5(t) = 2t1.5

To create a table in the format needed you would sample each function uniformly between zero and one. In this example they are sampled at intervals of 0.1. You can see that the first column is labeled 't' and contains values between 0 and 1 with an interval of 0.1. Your file must include a column with a header labeled 't'. All other coluumn headers can have any name as long as they are unique.

raw .csv format data

t,F1,F2,F3,F4,F5
0,0,0,0,0,0
0.1,0.0075,0.01,0.0125,0.00001,0.0632455532
0.2,0.03,0.04,0.05,0.00032,0.1788854382
0.3,0.0675,0.09,0.1125,0.00243,0.3286335345
0.4,0.12,0.16,0.2,0.01024,0.5059644256
0.5,0.1875,0.25,0.3125,0.03125,0.7071067812
0.6,0.27,0.36,0.45,0.07776,0.9295160031
0.7,0.3675,0.49,0.6125,0.16807,1.171324037
0.8,0.48,0.64,0.8,0.32768,1.431083506
0.9,0.6075,0.81,1.0125,0.59049,1.707629936
1,0.75,1,1.25,1,2

formatted data

t F1 F2 F3 F4 F5
0 0 0 0 0 0
0.1 0.0075 0.01 0.0125 0.00001 0.0632455532
0.2 0.03 0.04 0.05 0.00032 0.1788854382
0.3 0.0675 0.09 0.1125 0.00243 0.3286335345
0.4 0.12 0.16 0.2 0.01024 0.5059644256
0.5 0.1875 0.25 0.3125 0.03125 0.7071067812
0.6 0.27 0.36 0.45 0.07776 0.9295160031
0.7 0.3675 0.49 0.6125 0.16807 1.171324037
0.8 0.48 0.64 0.8 0.32768 1.431083506
0.9 0.6075 0.81 1.0125 0.59049 1.707629936
1 0.75 1 1.25 1 2

You can optionally include depth calculations in your file to greatly increase processing time of the file. The depth can be included on the second row of the file. The column labeled 't' must include the keyword "depth". Every other column must include the depth calculation.

If we continue our example with depth calculations the file would look like the following.

raw .csv format data

t,F1,F2,F3,F4,F5
depth,0.7,0.8272, 0.7272, 0.5, 0.4545
0,0,0,0,0,0
0.1,0.0075,0.01,0.0125,0.00001,0.0632455532
0.2,0.03,0.04,0.05,0.00032,0.1788854382
0.3,0.0675,0.09,0.1125,0.00243,0.3286335345
0.4,0.12,0.16,0.2,0.01024,0.5059644256
0.5,0.1875,0.25,0.3125,0.03125,0.7071067812
0.6,0.27,0.36,0.45,0.07776,0.9295160031
0.7,0.3675,0.49,0.6125,0.16807,1.171324037
0.8,0.48,0.64,0.8,0.32768,1.431083506
0.9,0.6075,0.81,1.0125,0.59049,1.707629936
1,0.75,1,1.25,1,2

formatted data

t F1 F2 F3 F4 F5
depth 0.7 0.8727 0.7272 0.5 0.4545
0 0 0 0 0 0
0.1 0.0075 0.01 0.0125 0.00001 0.0632455532
0.2 0.03 0.04 0.05 0.00032 0.1788854382
0.3 0.0675 0.09 0.1125 0.00243 0.3286335345
0.4 0.12 0.16 0.2 0.01024 0.5059644256
0.5 0.1875 0.25 0.3125 0.03125 0.7071067812
0.6 0.27 0.36 0.45 0.07776 0.9295160031
0.7 0.3675 0.49 0.6125 0.16807 1.171324037
0.8 0.48 0.64 0.8 0.32768 1.431083506
0.9 0.6075 0.81 1.0125 0.59049 1.707629936
1 0.75 1 1.25 1 2