home.md

@@ -81,8 +81,8 @@ $ sudo apt-get install python3 pandas
 $ sudo apt-get install python3-matplotlib
 $ sudo apt-get install python-pip
 
-pip install nbconvert
-pip install jupyter_client
+$ pip install nbconvert
+$ pip install jupyter_client
 ```
 ### Producing a notebook with plots
 
@@ -125,11 +125,21 @@ def load_datafile(basename):
         times[:] = [x - tmpVal for x in times]
     return pd.DataFrame({"Time": times, "Latency": values, "Frequency1": frequency1, "Frequency2": frequency2, "Frequency3": frequency3, "Frequency4": frequency4})
 ```
+Then add some global variables in order to scale the axes into seconds (from us in the data):
+
+```python
+scale = 1e6
+ticks = ticker.FuncFormatter(lambda x, pos: '{0:g}'.format(x/scale))
+```
 
 Then to plot, simply use the code:
 
 ```python
 load_datafile(<filename>).plot(title=<title>, x="Time", y="Latency", linewidth=0.5)
+ax = plt.gca()
+ax.xaxis.set_major_formatter(ticks)
+plt.xlabel("Time (s)")
+plt.ylabel("Latency (us)")
 ```
 
 To add multiple files as subplots, define an array of axes for the plots to use (each subplot is one array element), then in `plot()` add an argument `ax=axes[n]` defining which subplot to use. Note that 2D arrays can be used to plot subplots in grids (i.e. 4 plots in a 2x2 grid).