Table of Contents

    • 0.1  Imports

    • 0.2  Load test data

    • 0.3  Create noise object

    • 0.4  Calculate the PSD and corrCoeff

  • 1  Calculate unCorrelated noise

    • 1.1  Test saving

    • 1.2  Test plotting of PSD and corrCoeff

  • 2  Plot a few CSDs

    • 2.1  Try to plot a CSD for a non existant channel

    • 2.2  Try to save a figure with a bad path

  • 3  Plot Real vs Imaginary PSDs

  • 4  Plot unCorrelated part of the noise PSD

  • 5  Create noise simulation object

Noise Analysis Test

Imports

In [1]:

from qetpy import Noise
from qetpy.sim import TESnoise
from qetpy.plotting import compare_noise, plot_noise_sim
import numpy as np
import matplotlib.pyplot as plt

Load test data

In [2]:

pathToTraces = ''
traces_PT_on = np.load(pathToTraces+'traces.npy')

Create noise object

In [3]:

#savePath = 'example_Figs/' #used for test, user should define new path for test so they don't save over these figs
savePath = '' #user needs to define new path

sampleRate = 625e3 #define sample rate
channels = [ 'PCS1' , 'PES1' , 'PFS1' , 'PAS2' , 'PBS2' , 'PES2' , 'PDS2' ] #define the channel names
g124_noise = Noise(traces_PT_on, sampleRate, channels) #initialize a noise object
g124_noise.name = 'G124 SLAC Run 37 Pulse Tube On'

Calculate the PSD and corrCoeff

In [4]:

g124_noise.calculate_psd()
g124_noise.calculate_corrcoeff()
g124_noise.calculate_csd()

Calculate unCorrelated noise

In [5]:

g124_noise.calculate_uncorr_noise()

Test saving

Uncomment to save and re-load

In [6]:

#saveName = pathToTraces + g124_noise.name.replace(" ", "_") + '.pkl'
#g124_noise.save(pathToTraces)

In [7]:

#del g124_noise

In [8]:

# with open(pathToTraces,'rb') as savefile:
#     g124_noise = pickle.load(savefile)

Test plotting of PSD and corrCoeff

In [9]:

g124_noise.plot_psd(lgcoverlay=True)
../../_images/demos_noise_noise_example_17_0.png 
In [10]:


g124_noise.plot_psd(lgcoverlay=False)
../../_images/demos_noise_noise_example_18_0.png 
In [11]:

g124_noise.plot_corrcoeff(lgcsave=False, lgcsmooth=True, nwindow=13 )
../../_images/demos_noise_noise_example_19_0.png

Plot a few CSDs

In [12]:

g124_noise.plot_csd(whichcsd=['66','26'])
../../_images/demos_noise_noise_example_21_0.png
../../_images/demos_noise_noise_example_21_1.png

Try to plot a CSD for a non existant channel

In [13]:

g124_noise.plot_csd(whichcsd=['68'])

index out of range

Try to save a figure with a bad path

In [14]:

g124_noise.plot_csd(whichcsd=['11'], lgcsave=True, savepath = 'yay/python/is/great')

Invalid save path. Figure not saved
../../_images/demos_noise_noise_example_25_1.png

Plot Real vs Imaginary PSDs

In [15]:

g124_noise.plot_reim_psd()
../../_images/demos_noise_noise_example_27_0.png

Plot unCorrelated part of the noise PSD

In [16]:

g124_noise.calculate_uncorr_noise()

In [17]:


g124_noise.plot_decorrelatednoise(lgccorrelated=True,lgcsum = True, lgcsave=False)
../../_images/demos_noise_noise_example_30_0.png 
In [18]:

g124_noise.plot_decorrelatednoise(lgcoverlay = True)
../../_images/demos_noise_noise_example_31_0.png

Create noise simulation object

In [19]:


noise_sim = TESnoise(freqs = g124_noise.freqs[1:])

Note, these default noise parameters are completely made up, just for demostration

In [20]:

plot_noise_sim(g124_noise.freqs, g124_noise.psd[0,:], noise_sim, istype='power')

Out[20]:

(<Figure size 864x576 with 1 Axes>,
 <matplotlib.axes._subplots.AxesSubplot at 0x7f8e4b5a4908>)
../../_images/demos_noise_noise_example_35_1.png 
In [ ]: