#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Sep 5 21:07:23 2019
@author: ext-poulter_b
"""
import numpy as np
from matplotlib import pyplot as plt
from TimeCorrection import TimeCorrection
import ProcessedDataClass as PDC
XASProData = PDC.XASProData()
numstds = 4
minIzero = 0.015
lin_filter = 0.03
minTime = -5
maxTime = 30
def FilterData(xasrawdata, PlotOn, time_zero_mm):
# numstds is the number of standard deviations to take from the median
# minIzero sets the minimum permissable Izero
# lin_filter sets upper and lower bounds for the filter
# if time_zero_mm > 0:
FilterParameters = [
'numstds:' + str(numstds) + ' minIzero:' + str(minIzero) +
' lin_filter:' + str(lin_filter), 'minTime: ' + str(minTime),
'maxTime: ' + str(maxTime)
]
FileNums = [106]
xesRawData = loadData(FileNums, "XES", 1)
if ReLoadData:
with open(folder + "xesRawData.pkl", "rb") as f:
xesRawData = pickle.load(f)
confolder = "D://LCLS_Data/LCLS_python_data/XES_conversion_info/"
exists = os.path.isfile(confolder + "t0.pkl")
if exists:
with open(confolder + "t0.pkl", "rb") as f:
t0 = pickle.load(f)
xesProData = PDC.XESProcessedData(TTDelay=1000 * xesRawData.TimeTool -
1500 - t0)
print('read in t0')
else:
xesProData = PDC.XESProcessedData(TTDelay=1000 * xesRawData.TimeTool)
#xesProData = PDC.XESProcessedData(TTDelay = 1000*xesRawData.TimeTool)
xesProData.changeValue(UniAngle=np.unique(xesRawData.Angle))
#xesProData.changeValue(RowWOffset = xesRawData.RowlandY - xesRawData.Offset)
xesProData.changeValue(RowWOffset=xesRawData.RowlandY)
xesProData.makeLaserXES(xesRawData, MaxTime, MinTime, FPlots)
#xesProData.energyConversion(True)
UA = 75.445
import numpy as np
import json
import os
from matplotlib import pyplot as plt
from scipy.optimize import curve_fit
from alvra_tools.load_data import *
from alvra_tools.channels import *
from alvra_tools.utils import errfunc_sigma, errfunc_fwhm
from LoadData import LoadData
from Filter import FilterData
import pickle
from make_bar_stamp import make_bar_stamp
from GetXES import get_xes_pumped
import ProcessedDataClass as PDC
rixsprodata = PDC.RIXSProData()
scannum = [7]
name = "2900eV_Rubpy3_pink_Cl3"
loadDir = "/das/work/p17/p17983/SwissFEL19DA/PostExperiment/Ben/Processed/RuBpy3/XES/Calibration/" + name + "/"
saveDir = "/das/work/p17/p17983/SwissFEL19DA/PostExperiment/Ben/Processed/RuBpy3/XES/Calibration/" + name + "/roi2/"
if not os.path.isdir(saveDir):
os.mkdir(saveDir)
#
#with open(loadDir + "xasrawdata.pkl", "rb") as f:
# xasrawdata = pickle.load(f)
filename_base = name + '%02d' % scannum[0] + "_step00"
scan_name = name + '%02d' % scannum[0]
DIR = '/das/work/p17/p17983/cropped_data/' + name + '/'
DIRBS = "/sf/alvra/data/p17983/raw/"
#numsteps = len(xasrawdata.Energy)
plt.fill_between(Energy, stdev_high, stdev_low, alpha=0.3, color='blue')
plt.xlabel('energy (eV)')
plt.ylabel('Delta T / T')
plt.title('XAS')
plt.figure()
plt.plot(Energy, TFY_Difference)
plt.xlabel('energy (eV)')
plt.ylabel('absorption')
Dir = 'C:/Users/poult/Documents/Research/Beamtimes/SwissFEL_July_2019/Transfered_Data/Processed/RuDimerACN/TFY' \
'/600fs/'
save = True
XASAveraged = PDC.XASAveraged()
XASAveraged.changeValue(Averaged_Spectrum_unpumped=TFYunpump,
Scans_in_average=scans,
Shots_Per_Point_unpumped=TotalShotsUnpumped,
Energy=Energy)
if save:
with open(Dir + "Pumped_Averaged_600fs.pkl", "wb") as f:
pickle.dump(XASAveraged, f)
sp.savemat(
'C:/Users/poult/Documents/Research/Beamtimes/SwissFEL_July_2019/Transfered_Data/Jan-16-2020/DimerACN/DifferenceSpectra_time_filter.mat',
mdict={
'pumped': TFYpump,
'Difference_time_filter': TFY_Difference,
'TotalShots_time_filter': TotalShotsPumped,
'TotalShots_time_filter': TotalShotsUnpumped,
'Energy': Energy,
#FileNums = [408, 409, 410, 413, 417, 418] #[398, 401, 402, 403, 404, 405, 407]
#FileNumsC = list(range(348, 366+1))
#FileNumsC = list(range(348, 359+1))
FileNumsC = list(range(350, 359 + 1))
FileNumsW = list(range(342, 347 + 1))
peaksRawDataA = loadData(FileNumsA, "Peaks", 1)
peaksRawDataC = loadData(FileNumsC, "Peaks", 1)
peaksRawDataW = loadData(FileNumsW, "Peaks", 1)
if ReLoadData:
with open(folder + "xasPeaksData.pkl", "rb") as f:
peaksRawData = pickle.load(f)
xasPeaksDataC = PDC.PeaksProcessedData(
TTSteps=np.linspace(750, 1500, NumTTStepsC + 1),
Delay=1000 * peaksRawDataC.TimeTool + peaksRawDataC.StageDelay * 1e15)
xasPeaksDataC.makeProPeaks(peaksRawDataC, DorH, FPlots)
XASDiffPlotC = xasPeaksDataC.XASOn_Norm - xasPeaksDataC.XASOff_Norm
t0 = find_t0_XAS(xasPeaksDataC.TTSteps, XASDiffPlotC, False, True)
xasPeaksDataW = PDC.PeaksProcessedData(
TTSteps=np.linspace(mintime, maxtime, NumTTStepsW + 1),
Delay=1000 * peaksRawDataW.TimeTool + peaksRawDataW.StageDelay * 1e15 - t0)
xasPeaksDataW.makeProPeaks(peaksRawDataW, DorH, FPlots)
XASDiffPlotW = xasPeaksDataW.XASOn_Norm - xasPeaksDataW.XASOff_Norm
XASDiffErrorW = np.sqrt(
(np.square(xasPeaksDataW.Error_On) + np.square(xasPeaksDataW.Error_Off)) /
np.square(xasPeaksDataW.XASOff_Norm) + np.square(xasPeaksDataW.Error_Off) *
np.square(XASDiffPlotW) / np.square(np.square(xasPeaksDataW.XASOff_Norm)))
if ReEnterData:
FileNumsP = list(range(123, 130 + 1))
#FileNumsP = list(range(131, 140+1))
peaksRawDataP = loadData(FileNumsP, "Peaks", 1)
if ReLoadData:
with open(folder + "peaksRawDataP.pkl", "rb") as f:
peaksRawDataP = pickle.load(f)
with open(folder + "FileNumsP.pkl", "rb") as f:
FileNumsP = pickle.load(f)
peaksProDataP = PDC.PeaksProcessedData(
Delay=1000 * peaksRawDataP.TimeTool + peaksRawDataP.StageDelay * 1e15,
RowWOffset=peaksRawDataP.RowlandY - peaksRawDataP.Offset)
peaksProDataP.makeProPeaks(peaksRawDataP, NumTTSteps, MinTime, MaxTime, FPlots)
#plus2 data
if ReEnterData:
FileNumsP2 = list(range(155, 164 + 1))
#FileNumsP2 = list(range(143, 154+1))
peaksRawDataP2 = loadData(FileNumsP2, "Peaks", 1)
if ReLoadData:
with open(folder + "peaksRawDataP2.pkl", "rb") as f:
peaksRawDataP2 = pickle.load(f)
FileNums = list(range(190, 190 + 1))
xesRawData = loadData(FileNums, "XES", 2)
if ReLoadData:
with open(folder + "xesRawData.pkl", "rb") as f:
xesRawData = pickle.load(f)
confolder = "D://LCLS_Data/LCLS_python_data/XES_conversion_info/"
exists = os.path.isfile(confolder + "t0.pkl")
if exists:
with open(confolder + "t0.pkl", "rb") as f:
t0 = pickle.load(f)
xesProData = PDC.XESProcessedData(TTDelay=1000 * xesRawData.TimeTool -
1400 - t0)
print('read in t0')
else:
xesProData = PDC.XESProcessedData(TTDelay=1000 * xesRawData.TimeTool)
xesProData.changeValue(UniAngle=np.unique(xesRawData.Angle))
xesProData.changeValue(RowWOffset=xesRawData.RowlandY - xesRawData.Offset)
xesProData.makeProXES(xesRawData, MaxTime, MinTime, FPlots)
xesProData.energyConversion(True)
numboot = 1000
startT = time.time()
for ii in range(numboot):
#FileNums = list(range(384, 395+1))
FileNums = list(range(372, 395+1))
#FileNums = list(range(371,373+1))+list(range(375,377+1))+list(range(379,382+1))+list(range(384,391+1))+list(range(393,394+1))
#FileNums = list(range(372, 372+1))
xasRawData = loadData(FileNums, "XAS", 1)
if ReLoadData:
with open(folder + "xasRawData.pkl", "rb") as f:
xasRawData = pickle.load(f)
if Redot0:
xasProData = PDC.XASProcessedData(TTSteps = np.linspace(-200,100,NumTTSteps+1), TTDelay = 1000*xasRawData.TimeTool, \
XEnergy = np.round(xasRawData.XEnergyRaw*1000,1)*1)
uniXEnergy = np.unique(xasProData.XEnergy)
xasProData.changeValue(UniXEnergy = uniXEnergy[np.logical_and(uniXEnergy >= 7100, uniXEnergy <= 7130)])
xasProData.makeProXAS(xasRawData, True, FPlots)
XASDiff = np.empty((NumTTSteps, len(xasProData.UniXEnergy)))
Peak = np.empty(NumTTSteps)
for ii in range(NumTTSteps):
xasdiff = xasProData.XASOn_Norm[ii] - xasProData.XASOff_Norm