#!/usr/bin/env python
# coding: utf-8

# # QCoDeS Example with HP8753D

# This is the example notebook illustrating how to use the QCoDeS driver for the HP 8753D Network Analyzer.
# 
# Throughout the notebook, we assume that a Mini-Circuits SLP-450+ Low Pass filter is connected as the DUT. The test setup is as the following picture:

# ![title](../files/HP8753D.png)

# ### Required imports

# In[1]:


from qcodes.instrument_drivers.HP.HP8753D import HP8753D
from qcodes.utils.dataset import doNd
import time


# ### Connecting to the instrument and running the test

# In[2]:


vna = HP8753D('vna', 'GPIB0::15::INSTR')


# For the sake of this tutorial, we reset the instrument

# In[3]:


vna.reset()


# Let's look at the current snapshot of the instrument:

# In[4]:


vna.print_readable_snapshot(update=True)


# We setup the test such as the low-pass filter is connecting Port 1 to Port2. Let's setup the trace of S21 with 10 averages with a frequency range from 100 kHz to 1 GHz on a linear scale. Then, the instrument settings are as below:

# In[5]:


vna.display_format('Lin mag')
vna.s_parameter('S21')
vna.start_freq(100e3)
vna.stop_freq(1e9)

# and let's adjust the y-scale to fit
vna.display_scale(0.12)
vna.display_reference(-0.1)

# and finally enable averaging
vna.averaging('ON')
vna.number_of_averages(10)


# ### Single trace measurement

# Now we aquire a single trace. Before each aqcuisition, we must run prepare_trace for the instrument trace:

# In[6]:


vna.trace.prepare_trace()
doNd.do0d(vna.trace)


# ### Acquiring traces while sweeping

# Now we will vary the output power and acquire a trace for each power to examine how applying more power reduces the measurement noise.
# We have to ensure that the vna finishes averaging before moving to the next power step. Therefore, we setup a function to do this average and pass it to our measurement setup (note that this function can be implemented in several different ways)

# In[7]:


n_avgs = 10
vna.number_of_averages(n_avgs)
def run_sweeper():
    vna.run_N_times(n_avgs)


# We prepare our trace and run the sweep and time it:

# In[8]:


vna.trace.prepare_trace()
t1 = time.time()
doNd.do1d(vna.output_power, -84, -40, 20, 0.1, run_sweeper,vna.trace)
t2 = time.time()
t2-t1


# n_avgs can be changed between 1 and 999 (the higher average, more detailed result and longer time to finish)

# In[9]:


vna.close()