Getting-started.md

@@ -10,7 +10,8 @@ If you downloaded the archive in the [_dist_](https://gitlab.obspm.fr/dblain/exo
 5. Verify if all the condensates and gases thermochemical tables are in the _data/thermochemical_tables_ directory. If you want to add more species to the chemical model, respect the same format and use "speciesName.tct.dat" as file name (e.g. "H2O.tct.dat").
 6. Put a temperature profile as a priori inside the _inputs/atmospheres/temperature_profiles_ directory. The *Exo-REM* data format must be respected. You should have received an example of such a file with your *Exo-REM* distribution.
 
-# Setup
+# First run
+## Setup
 In this example, we will simulate the atmosphere of CoRoT-4 b, a well studied planet. A good source of planetary information can be found [here](https://exoplanetarchive.ipac.caltech.edu/). We will use the parameters from Moutou et al. 2008.
 
 Copy and edit the file _inputs/example.nml_, rename it _corot-4b.nml_. An extended description of the input parameters is available [here]().
@@ -70,7 +71,7 @@ Copy and edit the file _inputs/example.nml_, rename it _corot-4b.nml_. An extend
     ```
 9. Now we should be ready to go !
 
-# Running
+## Running
 1. Open a terminal.
 2. `cd` yourself into the Exo-REM _bin_ directory.
 3. Launch the calculations by executing:
@@ -82,7 +83,9 @@ During the run, keep a look in the terminal at how much the temperature vary (`d
 
 By default, at the end of the calculations, the results are stored in the _outputs/exorem_ directory.
 
-# Plotting
+## Plotting
+**Before starting:** The *Exo-REM* plot functions require Python3. Sometimes to force the use of the Python3 interpreter over the Python2 interpreter, you need to use the command `python3` instead of `python`.
+
 Let's take a look at our results. Go back to the _exorem_ directory and execute:
 ```bash
 python exorem_plot.py corot-4b
@@ -185,3 +188,21 @@ The temperature profile figure (temperature_profile_corot-4b) should look like t
 And the transmission spectrum should look like this:
 
 ![transmission_spectrum_corot-4b_R500](uploads/51da1babc3b2219569a0d861ae645c73/transmission_spectrum_corot-4b_R500.png)
+
+## Better figures
+Not happy with the figures you get ? What if for example you wanted to see the contributions of everything but clouds between 0.5 and 1.5 µm ? To do that, open inside the *Exo-REM* main directory a python console:
+```bash
+python
+```
+
+Then, simply do:
+```python
+from src.python.plot_figures import *  # import everything from plot_figures
+plot_contribution_transmission_spectra(
+    './outputs/exorem/spectra_corot-4b_R500.dat', 
+    wvn2wvl=True, 
+    xmin=0.5e-6, 
+    xmax=1.5e-6, 
+    exclude=['clouds']
+)
+```
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