Updated docs for jupyterlab/bqplot instructions

doc/readme.md

@@ -34,19 +34,31 @@ QGL relies on the concept of a "channel" to represent a qubit. The channel embod
 
 While QGL is *not* dependent on [Auspex](https://github.com/BBN-Q/auspex), Auspex is an experiment control framework which greatly facilitates executing QGL programs on laboratory hardware. Auspex provides constructs for abstracting (defining) instruments, connectivity, and post processing to enable "hands off" experimental control of sophiscated experiments on a variety of laboratory equipment including AWGs, digitizers, current sources, etc.    
 
+For plotting pulse waveforms within jupyter notebooks, QGL uses the bqplot library (which should be installed automatically when using the methods detailed below) and should not require any additional infrastructure. **For Jupyter Lab compatibility** additional steps are required:
 
+```
+conda install nodejs
+jupyter labextension install @jupyter-widgets/jupyterlab-manager
+jupyter labextension install bqplot
+```
 
 ## Installation <a name="Installation"></a>
 
-QGL can be downloaded from GitHub:
+There are a number of ways to obtain QGL:
 
-```https://github.com/BBN-Q/QGL/archive/master.zip```   
+Directly from the pypi, which will get the most recent master release, e.g. 2019.2:
+
+```pip install qgl```
 
-Or QGL can be cloned from GitHub to participate in QGL development:
+QGL can be cloned from GitHub to participate in QGL development:
 
 ```git clone https://github.com/BBN-Q/qgl.git```   
 
-And subsequently installed using pip:
+Or the source tree can be downloaded from GitHub. For the master branch:
+
+```https://github.com/BBN-Q/QGL/archive/master.zip```   
+
+For downloaded or cloned repositories, one most subsequently install the package using pip:
 
 ```
 cd QGL