Simple tool for reading .lvm files or other tabular data with columns that are stacked. In traditional text files, a single column represents a distinct set of data of a single unit (intensity, wavelength, etc.). For example, the first column is x and the second column is y — the x and y columns are represented by only one unit and the header (if there is one) appears at the top of the column. For some reason, I have a program that spits out data where there are columns a, b, c, d at the top, but then below these data are additional data e and f, with different units and with their own headers. The number of columns in each stack is also different, throwing up errors when trying to read these files. These .lvm files cannot simply be read by a program like CSV.jl and must be pre-processed.
This program takes these text files and returns a Julia dictionary with each real column of data as a separate key-value pair. This dictionary can easily be read by into a DataFrame using DataFrames.jl or similar package.
Example of the offending text file type:
A B C
0.1 0.1 0.1
0.2 0.2 0.2
0.3 0.3 0.3
0.2 0.2 0.2
0.1 0.2 0.1
D E
1 1
2 2
3 3
4 4
5 5
This becomes
Dict(:A => [0.1, 0.2, 0.3, 0.2, 0.1], :B => [...], :C => [...], :D => [...], :E => [...])
If anyone besides me is using this, then they should pass getall=true in the arguments.
Otherwise, it will look for keywords in the headers specific to my experiment and change the
corresponding dictionary keys to be more readable.
julia> LVM.read(filename, getall=true)
Dict{Any, Any}:
"CH0" => [...]
"CH1" => [...]
...