Decrased the number of fragments made in the example movie script to …

…make it run faster, and rearranged script to make the variable that controls fragment number more obvious.

examples/Fragmentation/Fragmentation_Movie.py

@@ -14,22 +14,24 @@
 Generates and runs a set of Swiftest input files from initial conditions with the SyMBA integrator. All simulation 
 outputs are stored in the subdirectory named after their collisional regime. 
 
+**NOTE: You must have ffmpeg installed on your system before running this script. For instance, on MacOS:
+
+```brew install ffmpeg```
+
+on Ubuntu:
+
+```sudo apt-get install ffmpeg```
+
+
 Inputs
 _______
-None.
+User selects which collisional movie to generate
 
 Output
 ------
-collisions.log   : An ASCII file containing the information of any collisional events that occured.
-collisions.nc    : A NetCDF file containing the collision output.
-data.nc          : A NetCDF file containing the simulation output.
-encounters.nc    : A NetCDF file containing the encounter output.
-init_cond.nc     : A NetCDF file containing the initial conditions for the simulation.
-param.00...0.in  : A series of parameter input files containing the parameters for the simulation at every output stage.
-param.in         : An ASCII file containing the inital parameters for the simulation.
-param.restart.in : An ASCII file containing the parameters for the simulation at the last output. 
-swiftest.log     : An ASCII file containing the information on the status of the simulation as it runs.
-collision.mp4    : A movie file named after the collisional regime depicting the collision.
+
+Files are stored in directories for each collision type name requested
+[COLLISION_TYPE].mp4    : A movie file named after the collisional regime depicting the collision.
 
 """
 
@@ -48,6 +50,22 @@
 movie_titles = dict(zip(available_movie_styles, movie_title_list))
 num_movie_frames = 1000
 
+
+# ----------------------------------------------------------------------------------------------------------------------
+# To increase the number of bodies generated in each collision type, decrease the value of the corresponding nfrag_reduction number 
+# ----------------------------------------------------------------------------------------------------------------------
+nfrag_reduction = {"disruption_headon" : 10.0,
+         "disruption_off_axis"         : 10.0,
+         "supercatastrophic_headon"    : 10.0,
+         "supercatastrophic_off_axis"  : 10.0,
+         "hitandrun_disrupt"           : 10.0,
+         "hitandrun_pure"              : 1.0,
+         "merge"                       : 1.0,
+         "merge_spinner"               : 1.0,
+         }
+
+
+
 # These initial conditions were generated by trial and error
 names = ["Target","Projectile"]
 pos_vectors = {"disruption_headon"         : [np.array([1.0, -5.0e-05, 0.0]),
@@ -124,16 +142,6 @@
          "merge_spinner"             : 5.0e-3,
          }
 
-nfrag_reduction = {"disruption_headon" : 1.0,
-         "disruption_off_axis"         : 1.0,
-         "supercatastrophic_headon"    : 1.0,
-         "supercatastrophic_off_axis"  : 10.0,
-         "hitandrun_disrupt"           : 1.0,
-         "hitandrun_pure"              : 1.0,
-         "merge"                       : 1.0,
-         "merge_spinner"               : 1.0,
-         }
-
 density = 3000 * swiftest.AU2M**3 / swiftest.MSun
 GU = swiftest.GMSun * swiftest.YR2S**2 / swiftest.AU2M**3
 body_radius = body_Gmass.copy()