145 lines
4.9 KiB
Python
145 lines
4.9 KiB
Python
import sys
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sys.path.insert(0,"../../../")
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import collections
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import os
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import numpy as np
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import matplotlib.pyplot as plt
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from matplotlib import gridspec
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import dispersiveXanes_utils as utils
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import xppl37_spectra
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import xanes_analyzeRun
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import mcutils as mc
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import trx
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import datastorage as ds
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nice_colors = ["#1b9e77", "#d95f02", "#7570b3"]
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nice_colors = "#1f78b4 #a6cee3 #b2df8a #33a02c".split()
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gradual_colors = ['#014636', '#016c59', '#02818a', '#3690c0', '#67a9cf', '#a6bddb', '#d0d1e6']#, '#ece2f0']
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def get_data(run=82,calib=1,threshold=0.02,force=False):
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fname = "../data/fig_fe_xas_run%04d.h5" % run
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if not os.path.isfile(fname) or force:
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E,p1,p2,Abs=xppl37_spectra.calcAbsForRun(run,merge_calibs=True,threshold=threshold)
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temp = ds.DataStorage( E=E,p1=p1,p2=p2,Abs=Abs)
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temp.info="Abs calculated with threshold = %.3f" % threshold
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temp.save(fname)
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data = ds.read(fname)
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# nan is saved as -1 for masked arrays
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for k in data.keys():
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try:
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data[k][data[k]==-1] =np.nan
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except TypeError:
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pass
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return data
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def get_ref():
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E,data=np.loadtxt("../data/Fe_ref.txt",unpack=True)
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return ds.DataStorage(E=E*1e3,data=data/2.05+0.07)
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def get_1b():
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E,data=np.loadtxt("../data/Fe_1bunch.txt",unpack=True)
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return ds.DataStorage(E=E*1e3,data=data/2.05+0.07)
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def fig_fe_xas(run=82,shots = slice(100,105),showAv=True,force=False,threshold=0.02,smoothWidth=0.3):
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ref = get_ref()
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color_ss = '#08519c'
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color_av = '#238b45'
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color_av_all = '#d95f0e'
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shifty = 1
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data = get_data(run,force=force)
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E = data.E;p1=data.p1;p2=data.p2;Abs=data.Abs
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p1_sum = p1.sum(-1)
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p1_av = np.nanmean(p1,axis=0)
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p2_av = np.nanmean(p2,axis=0)
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# somehow nanmedian screws up when array is too big ... so using nanmean
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abs_av = np.nanmean(Abs,axis=0)
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n = 2**np.arange(4)
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av = np.nanmedian(Abs[:],0)
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av = xppl37_spectra.smoothSpectra(E,av,res=smoothWidth)
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for ni in n:
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aa = np.nanmedian(Abs[:ni],0)
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aa = xppl37_spectra.smoothSpectra(E,aa,res=smoothWidth)
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print(ni,np.nanstd(aa-av))
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p1 = p1[shots]; p2=p2[shots]; Abs = Abs[shots]
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if smoothWidth > 0:
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Abs = xppl37_spectra.smoothSpectra(E,Abs,res=smoothWidth)
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idx = E< 7080
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Abs[:,idx]=np.nan
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#fig,ax = plt.subplots(1,3,sharex=True,sharey=False,squeeze=False,figsize=[6,4])
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figure = plt.figure(figsize = [7,5])
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gs = gridspec.GridSpec(1, 3, width_ratios=[1, 1, 1.5],)
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ax = []
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ax.append( plt.subplot(gs[0]) )
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ax.append( plt.subplot(gs[1],sharex=ax[0],sharey=ax[0]) )
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ax.append( plt.subplot(gs[2],sharex=ax[0]) )
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#ax = ax[0]
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normalization = np.nanmax( p1 )
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to_save = []
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for ishot,(s1,s2,a) in enumerate(zip(p1,p2,Abs)):
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s1_norm = s1/normalization
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s2_norm = s2/normalization
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ax[0].axhline(ishot*shifty,ls='--',color="0.9")
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ax[1].axhline(ishot*shifty,ls='--',color=color_ss)
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if showAv:
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ax[1].plot(E,np.nanmedian(Abs,0)+ishot*shifty,color=color_av_all,lw=1,zorder=10,alpha=0.8)
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ax[0].plot(E,s1_norm+ishot*shifty,ls = '-' ,color='0.8',lw=2)
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ax[0].plot(E,s2_norm+ishot*shifty,ls = '-' ,color='0.3',lw=2)
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ax[1].plot(E,a+ishot*shifty,color=color_ss,lw=2)
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#ax[1].plot(ref.E,ref.data+ishot*shifty,color=color_av_all,lw=2,zorder=100)
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to_save.append(s1_norm)
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to_save.append(s2_norm)
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to_save.append(a)
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ax[0].set_title("Run %s"%str(run))
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ax[1].set_ylabel("Sample Absorption")
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ax[0].set_ylabel("Normalized Spectra")
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ax[2].plot(E,xppl37_spectra.smoothSpectra(E,Abs[-1],res=smoothWidth)[0],color=color_ss,label="1 shot LCLS")
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ax[2].plot(E,xppl37_spectra.smoothSpectra(E,np.nanmedian(Abs,axis=0),res=smoothWidth)[0],color=color_av_all,label="5 shots LCLS")
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ref = get_1b()
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ax[2].plot(ref.E,ref.data-0.05,color=nice_colors[-2],label="1 shot ESRF")
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ref = get_ref()
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ax[2].plot(ref.E,ref.data-0.05,color=nice_colors[-1],label="ref ESRF")
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ax[2].legend()
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ref = get_1b()
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rr = mc.interpolate(ref.E,ref.data,E)
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to_save.insert(0,rr)
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ref = get_ref()
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rr = mc.interpolate(ref.E,ref.data,E)
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to_save.insert(1,rr)
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to_save.insert(2,xppl37_spectra.smoothSpectra(E,np.nanmedian(Abs,axis=0),res=smoothWidth)[0])
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to_save = np.vstack(to_save)
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info = "# threshold=%.2f; smoothWidth=%.2f eV" %(threshold,smoothWidth)
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info += "\n#E esrf_1b esrf_ref abs_average_over_shots nshots x (spectro1 spectro2 abs)"
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trx.utils.saveTxt("../data/fig_fe_xas_spectra_run%04d.txt"%run,E,to_save,info=info)
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ax[0].set_xlabel("Energy (keV)")
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ax[1].set_xlabel("Energy (keV)")
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ax[2].set_xlabel("Energy (keV)")
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ax[0].grid(axis='x',color="0.7",lw=0.5)
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ax[1].grid(axis='x',color="0.7",lw=0.5)
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ax[0].set_xlim(7070,7180)
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ax[1].set_xlim(7070,7180)
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ax[2].set_xlim(7090,7180)
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ax[0].set_yticks( () )
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ax[1].set_yticks( () )
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ax[2].set_yticks( () )
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ax[0].set_ylim(-0.1,len(Abs)+0.2)
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ax[1].set_ylim(-0.1,len(Abs)+0.2)
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ax[2].set_ylim(0,0.7)
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ax[2].grid(color="0.7",lw=0.5)
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plt.tight_layout()
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plt.savefig("fig_fe_xas.png",transparent=True,dpi=300)
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plt.savefig("fig_fe_xas.pdf",transparent=True)
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#if __name__ == "__main__": fig_fe_xas()
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