Update description

ASvyatkovskiy · web-flow · commit 1e2556ce38d2 · 2016-12-12T23:35:53.000-05:00
diff --git a/docs/Primitives.md b/docs/Primitives.md
@@ -2,11 +2,13 @@
 
 Each shot is a measurement of plasma current as a function of time. The Shot objects contains following attributes:
 
- 1. number - unique identifier of a shot (integer)
- 1. t_dsirupt - disruption time in milliseconds
- 1. ttd - ...
- 1. valid - whether plasma current reaches a certain value during the shot
+ 1. number - integer, unique identifier of a shot
+ 1. t_disrupt - double, disruption time in milliseconds (second column in the shotlist input file)
+ 1. ttd - array of doubles, time profile of the shot converted to time-to-disruption values
+ 1. valid - boolean, whether plasma current reaches a certain value during the shot
+ 1. is_disruptive - boolean, 
 
+        
 For 0D data, each shot is modeled as 2D array - time vs plasma current.
 
 ## ShotList
@@ -27,6 +29,24 @@ Since shot lengthes are not multiples of the min shot length in general, some no
 
 ## Chunk
 
+A subset of `patch` defined as:
+```
+num_chunks = Length of the patch/ num_timesteps
+```        
+where `num_timesteps` is the sequence length fed to the RNN model.
 
 ## Batch
 
+Mini-batch gradient descent is used to train neural network model.
+`num_batches` represents the number of *patches* per mini-batch.
+
+### Batch input shape
+
+The data in batches fed to the Keras model should have shape:
+
+```
+batch_input_shape = (num_chunks*batch_size,num_timesteps,num_dimensions_of_data)
+```
+
+where `num_dimensions_of_data` is the signal dimensionality. For 0D dataset we only have a time profile of plasma current,
+so `num_dimensions_of_data = 1`
