Update ReadMe

docs/source/ReadInData.rst

@@ -54,7 +54,7 @@ Since we are only interested in the forces generated by the cells, we use a mask
 	
 Next, we can use matplotlib to plot and examine the timelines. We look at the contractility, which gives us a measure of all the force vectors pointing to the epicenter of the force field. 
 We also look at the strain energy, which gives us the amount of energy stored in the matrix, taking into account the displacements and the nonlinear material model (the strain energy does not depend on the 
-epicenter of the force field).
+epicenter of the force field; while in this case the contractility shows more variation).
 
 .. code-block:: python
    
@@ -73,7 +73,7 @@ epicenter of the force field).
 	plt.tight_layout()
 	plt.savefig(r"Fig1.png",dpi=300)
 
-ADD IMAGE HERE
+.. figure:: images/ReadInA.png   
 
 
 We can also access the x, y, and z components of the force and deformation vectors individually. 
@@ -106,7 +106,7 @@ We also plot the maximum matrix deformations at each time step.
 	plt.savefig(r"Fig2.png",dpi=300)
 
 
-ADD IMAGE HERE
+.. figure:: images/ReadInB.png   
 
 Finally, we want to investigate how the matrix deformations propagate with the distance to the organoid. Nonlinear materials such as collagen are known to propagate matrix cues over long distances.
 For this, we transform our coordinates with respect to the organoid center (actually we use the epicenter of the deformation field). Then, we apply a running window analysis, where we average the matrix deformations within