Updated documentation

Update README with usage of function j_oldpars. Add version history.
Add Julia version ("0.7-") to Project.toml.
Remove script MCMparameters.jl from src folder.
Updated docstrings.

Project.toml

@@ -2,6 +2,7 @@ name = "MCMphotolysis"
 uuid = "37f95c2c-7f9b-11e8-13ad-816be0d1e117"
 authors = ["Peter Bräuer <pb866@york.ac.uk>"]
 version = "0.1.0"
+julia = "0.7-"
 
 [deps]
 DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"

README.md

@@ -13,18 +13,49 @@ Install the Package by adding it to your environment using `Pkg`
 ```julia
 using Pkg
 Pkg.add("https://github.com/pb866/MCMphotolysis.git")
+Pkg.instantiate()
 Pkg.precomile()
 ```
 
 or go to the package manager typing `]` in the julia prompt and in the 
 package manager the following commands:
 
-```julia
+```
 add https://github.com/pb866/MCMphotolysis.git
+instantiate
 precompile
 ```
 
-### Trouble shooting of common errors
+
+Usage
+-----
+
+After installation run the following lines in the REPL or write a julia
+script with the following lines and call it from the terminal.
+
+```julia
+using MCMphotolysis
+jvals = j_oldpars("<scenario name>")
+```
+
+If you haven't installed the package directly to your Julia default environment,
+you need to activate the environment first.
+
+Call function `j_oldpars` handing over the scenario name, i.e. the name of
+the TUV input file without the `.txt` file ending. If you only want the data
+returned in the REPL without file output, set the optional keyword argument
+`output = false`.  
+Function `j_oldpars` returns a dictionary with entries for a DataFrame with
+the _j_ values (`:jvals`), where the `:order` of magnitude is stored in a
+different array, arrays with the solor zenith angles (`:deg`/`:rad`),
+an array with LsqFit output, statistical data (`:σ`, `:RMSE`, and `:R2`).
+Moreover, a folder `params_<scenario name>` is created, where parameters are
+printed to `parameters.dat` and parameterisations are visualised in 
+`<scenario name>.pdf`.
+
+
+Trouble shooting of common errors
+---------------------------------
 
 If you get an error message, follow the the instructions of the error message, e.g.
 
@@ -43,3 +74,14 @@ Pkg.build("PyPlot")
 
 You can get the system python version by typing `which python` in the terminal
 and copying the output.
+
+
+Version history
+===============
+
+Version 0.1.0
+-------------
+
+- Function `j_oldpars` to write the legacy MCM parameterisations and statistical
+  data to a text file and plot the parameterisations in a pdf compiled in the
+  folder `params_<scenario name>`

src/MCMphotolysis.jl

@@ -34,14 +34,22 @@ function __init__()
 end
 
 """
-    j_oldpars(scen)
+    j_oldpars(scen::String; output::Bool=true)
 
 Read reactions from a TUV output file named `scen`.txt, derive MCM l,m,n-parameterisations
-for photolysis, plot the _j_ values from TUV and the parameterisation for all reactions
-to a pdf and print the j values and errors/statistical data to a text file in a folder
-`params_<scen>`.
-Return solar zenith angle as tuple of arrays with deg/rad, the TUV _j_ value data,
-and the fit data (as array with entries for each reaction).
+for photolysis and return a dictionary with the following entries:
+
+- `:jvals`: DataFrame with j values (devided by maximum order of magnitude, i.e. without the `e-...`)
+- `:order`: Vector with order of magnitudes
+- `:deg`/`:rad`: Vector with solar zenith angles in deg/rad
+- `:fit`: Vector with LsqFit data
+- `:σ`: Vector of Vectors with σ-values for the 95% confidence interval for the `l`, `m`, and `n` parameters
+- `:RMSE`: Vector of root mean square errors
+- `:R2`: Vector of correlation cofficients R²
+
+If output is set to `true` (_default_), _j_ values from TUV and the parameterisations
+for all reactions are plotted to a pdf and _j_ values and errors/statistical data
+are printed to a text file in a folder named `params_<scen>`.
 """
 function j_oldpars(scen::String; output::Bool=true)
   # Initialise system time and output path/file name

src/fitTUV.jl

@@ -3,10 +3,12 @@
 #########################################
 
 """
-    fit_j(jvals)
+    fit_j(jvals, sza)
 
-Derive MCM parameterisations for dataframe jvals with χ-dependent _j_ values.
-    j / s^-1 = l·cos^m(χ)·exp(-n·sec(χ))
+Derive MCM parameterisations for DataFrame `jvals` with `sza`-dependent _j_ values.
+    j / s^-1 = l·cos^m(sza)·exp(-n·sec(sza))]
+
+The Vector of solar zenith angles `sza` must be in rad.
 """
 function fit_jold(jvals,sza)
 

src/output.jl

@@ -1,8 +1,9 @@
 """
-    plot_j(jvals, iofolder, fit, systime)
+    plot_j(jvals::Dict{Symbol,Any},systime::DateTime,iofolder::String,ifile::String)
 
-Plot j values saved in dataframe jvals and parameterisations derived from parameters
-in fit to file parameters.dat in the iofolder together with the time of creation (time).
+Plot j values saved in `jvals[:jvals]` and parameterisations derived from parameters
+in `jvals[:fit]` to file `ifile.pdf` in the `iofolder` together with the
+`systime` of creation.
 """
 function plot_jold(jvals::Dict{Symbol,Any},systime::DateTime,iofolder::String,ifile::String)
 
@@ -49,13 +50,11 @@ end #function plot_j
 
 
 """
-    wrt_params(rxn, fit, sigma, rmse, R2, iofolder, time)
+    wrt_params(jvals, iofolder, systime)
 
-For each reaction (rxn), from param in fit and sigma, print parameters
-and 95% confidence together with RMSE and R^2 to file 'parameters.dat'
-in the designated output folder (iofolder).
-
-Print the time of creation (time) to the output file.
+Write the parameters, statistical data, and reaction labels stored in the
+dictionary `jvals` to the file `parameters.dat` in the `iofolder` and state
+the `systime` of creation.
 """
 function wrt_params(jvals, iofolder, systime)
 

src/rdfiles.jl

@@ -1,8 +1,11 @@
 """
-    get_fnames(scen)
+    get_fnames(scen, output)
 
-From the scenario name (scen) used in TUV derive names for the TUV output file
+From the scenario name (scen) used in TUV, derive names for the TUV output file
 and the output folder.
+
+If `output` is `true`, create a output folder `./params_<scen>`. Ask to overwrite,
+if folder already exists.
 """
 function setup_files(scen, output)
   # Test script argument and ask for input file, if missing