Update README.md

Author: hpparvi

README.md

@@ -4,7 +4,7 @@ PyTransit
 Fast and easy-to-use tools for exoplanet transit light curve modelling using Python or Fortran.
 
 
-    from pytransit.gimenez import Gimenez
+    from pytransit import Gimenez
     m = Gimenez()
     f = m.evaluate(t, *pv)
 
@@ -13,8 +13,13 @@ Fast and easy-to-use tools for exoplanet transit light curve modelling using Pyt
 Modules
 -------
 Transit models
-  - Optimized and parallelized Fortran implementation of the transit model by A. Gimenez (A&A 450, 1231--1237, 2006).
+  - Series-expansion based transit model by A. Gimenez (A&A 450, 1231--1237, 2006).
+  - Quadratic limb-darkening transit model by Mandel & Agol (ApJ 580, L171–L175, 2002).
+ 
+  - Common features
+    - Optimized and parallelized Fortran implementatios. 
     - Can calculate the transit model simultaneously for several limb darkening coefficient sets.
+    - Built-in model interpolation for the modelling of large datasets.
     - Built-in supersampling.
 
 Utilities
@@ -41,19 +46,26 @@ Examples
 ### Basics
 Basic usage is simple:
 
-    from pytransit.gimenez import Gimenez
+    from pytransit import Gimenez
 
     m = Gimenez()
     f = m.evaluate(t, *pv)
 
+or
+
+    from pytransit import MandelAgol
+    
+    m = MandelAgol()
+    f = m.evaluate(t, *pv)
+
 Here we first initialize the model accepting the defaults (quadratic limb darkening law, no supersampling, 
 and the use of all available cores), and then calculate the model for times in the time array `t`, `pv` being 
 a list containing the system parameters.
 
 For a slightly more useful example, we can do:
 
     import numpy as np
-    from pytransit.gimenez import Gimenez
+    from pytransit import Gimenez
 
     t = np.linspace(0.8,1.2,500)
     k, t0, p, a, i, e, w = 0.1, 1.01, 4, 8, 0.48*np.pi, 0.2, 0.5*np.pi