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)