getting started in Readme.md

README.md

@@ -1,3 +1,90 @@
 # Galaxy Ninja
 
-A useful binning and computation tool for numerical simulations
+A efficient binning and computation tool for numerical simulations
+
+Galaxy ninja uses `numba` for fast processing of huge simulation dataset.
+
+## Download
+
+The easiest way to get Galaxy Ninja is to clone this repository
+
+```
+git clone https://git.brucy.fr/noe/galaxy_ninja.git
+```
+
+
+## Install 
+
+Assuming `pip` is available on your system, just run 
+
+``` pip install . ```
+
+in the downloaded folder.
+
+## Getting started
+
+### Load data
+
+The first step is to write a loader for your simulation dataset. 
+A loader is a python function that for a given simulation snapshot returns a dictionnary with the following structure:    
+
+```python
+        gas:
+            position (Ngas, 3) [kpc], centered
+            volume   (Ngas)    [pc^3]
+            velocity (Ngas, 3) [km/s]
+            mass     (Ngas)    [Msun]
+        stars:
+            position (Nstar, 3) [kpc], centered
+            velocity (Nstar, 3) [km/s]
+            mass     (Nstar)    [Msun]
+            birth_time      (Nstar)    [Myr]
+        dm:
+            position (Ngas, 3) [kpc], centered
+            velocity (Ngas, 3) [km/s]
+            mass     (Ngas)    [Msun]
+        maps:
+            extent      (xmin, xmax, ymin, ymax) Coordinates of the edges of the map, centered
+            gas_coldens (Nx, Ny) [Msun/pc^2], map of column densityructure:
+```
+
+Example loaders for Ramses and Arepo are provided.
+
+### Compute binned quantities
+
+1. Instanciate a galsec object
+
+```python
+from galaxy_ninja import Galsec
+
+data = your_loader(path)
+galsec = Galsec(data, copy=False)
+```
+
+2. Choose your binning method.
+Pre-set binning methods includes radial rings, sectors and cartesian binning.
+
+```python
+rings = galex.rings_analysis(
+    delta_r=0.1 * u.kpc,
+    rmax=30 * u.kpc,
+    zmin=-4 * u.kpc,
+    zmax=4 * u.kpc,
+)
+```
+
+### Access averaged binned quantities
+
+Example for a velocity curve:
+```python 
+import matplotlib.pyplot as plt
+plt.plot(rings["gas"]["r"], sectors["gas"]["velphi"])
+```
+
+
+
+
+
+
+
+