def loaddata(self):
'''
Loads the data defined in self.filein1 .. 5
'''
(self.I1I1, d3,
self.d2, self.d1, self.dz) = loadmtx(self.fifolder + self.filein1)
self.Q1Q1, d3, d2, d1, dz = loadmtx(self.fifolder + self.filein2)
self.I2I2, d3, d2, d1, dz = loadmtx(self.fifolder + self.filein3)
self.Q2Q2, d3, d2, d1, dz = loadmtx(self.fifolder + self.filein4)
self.Vm, self.d3, dv2, dv1, dvz = loadmtx(self.fifolder + self.filein5)
def loaddata(self):
'''
Loads the data defined in self.filein1 ..
This loads the shotnoise relevant data files
'''
self.I1I1, d3, d2, d1, dz = loadmtx(self.fifolder + self.filein1, True)
self.Q1Q1, d3, d2, d1, dz = loadmtx(self.fifolder + self.filein2, True)
self.I2I2, d3, d2, d1, dz = loadmtx(self.fifolder + self.filein3, True)
self.Q2Q2, self.d3I, self.d2, self.d1, self.dz = loadmtx(self.fifolder + self.filein4, True)
self.Vm, self.d3, dv2, dv1, dvz = loadmtx(self.fifolder + self.filein5, True)
self.lags0 = find_nearest(self.d1.lin, 0.0) # lags position
self.Ib0 = find_nearest(self.d3.lin, 0.0) # Zero current position
def loadCcor(self):
'''
want to simply load the amplitude at max correlation position
i.e. at lags = 0
'''
self.I1I2, d3, d2, d1, dz = loadmtx(self.fifolder + self.filein6, True)
self.I1Q2, d3, d2, d1, dz = loadmtx(self.fifolder + self.filein7, True)
self.Q1I2, d3, d2, d1, dz = loadmtx(self.fifolder + self.filein8, True)
self.Q1Q2, d3, d2, d1, dz = loadmtx(self.fifolder + self.filein9, True)
self.I1Q1, d3, d2, d1, dz = loadmtx(self.fifolder + self.filein10, True)
self.I2Q2, d3, d2, d1, dz = loadmtx(self.fifolder + self.filein11, True)
# fix single pixel shifts in the data.
self.I1I2 = self.f1pN(self.I1I2)
self.I1Q2 = self.f1pN(self.I1Q2)
self.Q1I2 = self.f1pN(self.Q1I2)
self.Q1Q2 = self.f1pN(self.Q1Q2)
# self.PD1 = (self.I1I1[self.lags0] + self.Q1Q1[self.lags0])
# self.PD2 = (self.I2I2[self.lags0] + self.Q2Q2[self.lags0])
# self.cPD1 = ( np.abs((self.I1I1[self.lags0]) + np.abs(self.Q1Q1[self.lags0])) +
# (np.abs(self.I2I2[self.lags0]) + np.abs(self.Q2Q2[self.lags0])) )
# self.psi( ((self.I1I2[self.lags0]) - (self.Q1Q2[self.lags0])) +
# 1j * ((self.Q1I2[self.lags0]) + (self.I1Q2[self.lags0])))
# self.phase0 = np.angle(self.psy)
# self.mag0 =
self.cPD1 = (self.I1I1[self.lags0] + self.Q1Q1[self.lags0])
self.cPD2 = (self.I2I2[self.lags0] + self.Q2Q2[self.lags0])
self.cPD3 = ((abs(self.I1I1[self.lags0]) + abs(self.Q1Q1[self.lags0])) +
(abs(self.I2I2[self.lags0]) + abs(self.Q2Q2[self.lags0])))
self.cPD4 = ((abs(self.I1I2[self.lags0]) + abs(self.Q1Q2[self.lags0])) +
(abs(self.Q1I2[self.lags0]) + abs(self.I1Q2[self.lags0])))
def loadCcor(self):
'''
want to simply load the amplitude at max correlation position
i.e. at lags = 0
'''
self.I1I2, d3, d2, d1, dz = loadmtx(self.fifolder + self.filein6)
self.I1Q2, d3, d2, d1, dz = loadmtx(self.fifolder + self.filein7)
self.Q1I2, d3, d2, d1, dz = loadmtx(self.fifolder + self.filein8)
self.Q1Q2, d3, d2, d1, dz = loadmtx(self.fifolder + self.filein9)
self.I1Q1, d3, d2, d1, dz = loadmtx(self.fifolder + self.filein10)
self.I2Q2, d3, d2, d1, dz = loadmtx(self.fifolder + self.filein11)
self.cPD1 = (self.I1I1[self.lags0] + self.Q1Q1[self.lags0])
self.cPD2 = (self.I2I2[self.lags0] + self.Q2Q2[self.lags0])
def loadCcor(self):
'''
want to simply load the amplitude at max correlation position
i.e. at lags = 0
'''
self.I1I2, d3, d2, d1, dz = loadmtx(self.fifolder + self.filein6, True)
self.I1Q2, d3, d2, d1, dz = loadmtx(self.fifolder + self.filein7, True)
self.Q1I2, d3, d2, d1, dz = loadmtx(self.fifolder + self.filein8, True)
self.Q1Q2, d3, d2, d1, dz = loadmtx(self.fifolder + self.filein9, True)
self.I1Q1, d3, d2, d1, dz = loadmtx(self.fifolder + self.filein10, True)
self.I2Q2, d3, d2, d1, dz = loadmtx(self.fifolder + self.filein11, True)
self.I1I2 = self.f1pN(self.I1I2) # fix 1 pixel shift noises
self.I1Q2 = self.f1pN(self.I1Q2)
self.Q1I2 = self.f1pN(self.Q1I2)
self.Q1Q2 = self.f1pN(self.Q1Q2)
self.cPD1 = (self.I1I1[self.lags0] + self.Q1Q1[self.lags0])
self.cPD2 = (self.I2I2[self.lags0] + self.Q2Q2[self.lags0])
def loadCcor(self):
'''
want to simply load the amplitude at max correlation position
i.e. at lags = 0
'''
I1I2, d3, d2, d1, dz = loadmtx(self.fifolder + self.filein6)
I1Q2, d3, d2, d1, dz = loadmtx(self.fifolder + self.filein7)
Q1I2, d3, d2, d1, dz = loadmtx(self.fifolder + self.filein8)
Q1Q2, d3, d2, d1, dz = loadmtx(self.fifolder + self.filein9)
I1Q1, d3, d2, d1, dz = loadmtx(self.fifolder + self.filein7)
I2Q2, d3, d2, d1, dz = loadmtx(self.fifolder + self.filein7)
lags0 = find_nearest(d1.lin, 0.0) # lags position
self.cI1I2 = I1I2[lags0]
self.cI1Q2 = I1Q2[lags0]
self.cQ1I2 = Q1I2[lags0]
self.cQ1Q2 = Q1Q2[lags0]
self.cI1Q1 = I1Q1[lags0]
self.cI2Q2 = I2Q2[lags0]
self.cPD1 = (self.I1I1[lags0]+self.Q1Q1[lags0])
self.cPD2 = (self.I2I2[lags0]+self.Q2Q2[lags0])
# import matplotlib
# matplotlib.use('macosx') # macosx
# import matplotlib.pyplot as plt
import bottleneck as bn
import numpy as np
import Gnuplot as gp
from parsers import loadmtx, read_header_old
# , make_header, dim, savemtx, savedat
from scipy.constants import h, e, pi
# mtx file to be loaded
# filename1 = "data/S1_164_voltage_adj.mtx"
# filename1 = "data/S1_160_voltage_adj2.mtx"
# filename1 = "data/S1_420_voltage_adj.mtx"
filename1 = "data/S1_905_SI.mtx"
data, head = loadmtx(filename1)
d1, d2, d3, dz = read_header_old(head, Data=data)
flux0 = h/(2.0*e)
# manual found flux offset
# d2.scale = 0.5/0.237
# d2.update_lin()
# d2.off = 0.177*d2.scale
# d2.lin = d2.lin+d2.off
# d2.scale = 1.0/0.85
# d2.update_lin()
# d2.lin = d2.lin-0.207
def xderiv(d2MAT, d1):
def crop_at_target(data1d, pos, fit_left, fit_right):
p0 = pos - fit_left
p1 = pos + fit_right
if p0 < 0:
print 'p0 is less than 0, decrease left range'
data1d2 = data1d[p0:p1]
return data1d2
#all manual changes are done in parameters.py
execfile('parameters.py') #this file contain all the parameters above
#----- Load files (given by parameters.py)----
meas_raw = parser.loaddat(filename_2)
sim_raw, sim_raw_head = parser.loadmtx(filename_1)
#to be adjusted to ensure the pre alignment works well
fit_adj = 0.5 #
fit_adjf = 0.1 #0.0
pre_range = 120 #points
fit_left = 70#20#38 #points
fit_right = 600#300 #points
Qr_0 = eval(sim_raw_head[9])
Qr_1 = eval(sim_raw_head[10])
Qr_p = sim_raw.shape[0]
Qr_array = np.linspace(Qr_0, Qr_1, Qr_p)
