12345678910111213141516171819202122232425262728293031323334353637383940414243444546 |
- """
- evaluation of the standard deviation for different numbers of point
- if the noise is such that we have sigma as a standard deviations
- then averaging N points should give a std of sigma/N**0.5
- """
- from struct import*
- import ctypes
- import array
- import numpy as np
- import matplotlib.pyplot as plt
- import time
- from ADUCv2p0 import*
- chip1 = ADUCv2p0(0x50,True)
- chip1.set_channel(3) #ADC
- chip1.set_remote_trigg(1)
- chip1.set_pga_state(0x18)
- chip1.set_Vout(0,800)
- Nwf = 100
- dat1 = np.zeros(Nwf)
- dat10 = np.zeros(Nwf)
- dat100 = np.zeros(Nwf)
- for k in range(0,Nwf):
- data = chip1.read_data()
- dat1[k] = data[50]
- dat10[k] = np.mean(data[50:60])
- dat100[k] = np.mean(data[50:150])
- print(k)
-
- print(np.std(dat1))
- print(np.std(dat10))
- print(np.std(dat100))
|