diff --git a/scripts/psdlag_5bin.py b/scripts/psdlag_5bin.py
new file mode 100644
index 0000000..45cde88
--- /dev/null
+++ b/scripts/psdlag_5bin.py
@@ -0,0 +1,112 @@
+#!/usr/bin/env python
+import numpy as np
+from scipy.stats import norm
+from scipy.stats import lognorm
+import sys
+import getopt
+sys.path.insert(1,"/usr/local/science/clag-agn/data/")
+import clag
+import matplotlib
+# %pylab inline
+
+
+#ref_file="data/lc/1367A.lc"
+#echo_file="data/lc/2246A.lc"
+
+ref_file  = str(sys.argv[1])
+echo_file = str(sys.argv[2])
+
+
+dt = 0.01
+t1, l1, l1e = np.loadtxt(ref_file).T
+# errorbar(t1, l1, yerr=l1e, fmt='o')
+
+#A
+fqL = np.logspace(np.log10(0.0049999999),np.log10(0.340002000),6)
+
+# not done for this bin number
+#B
+#fqL = np.array([0.0049999999, 0.018619375, 0.044733049,
+#                0.069336227, 0.10747115, 0.16658029,
+#                0.25819945, 0.40020915])
+
+
+#C
+#fqL = np.array([0.0049999999, 0.018619375, 0.044733049,
+#                0.069336227, 0.10747115, 0.16658029,
+#                0.25819945, 0.40020915])
+
+nfq = len(fqL) - 1
+fqd = 10**(np.log10( (fqL[:-1]*fqL[1:]) )/2.)
+
+
+
+
+
+P1 = clag.clag('psd10r', [t1], [l1], [l1e], dt, fqL)
+p1 = np.ones(nfq)
+p1, p1e = clag.optimize(P1, p1)
+
+p1, p1e = clag.errors(P1, p1, p1e)
+
+# xscale('log'); ylim(-4,2)
+# errorbar(fqd, p1, yerr=p1e, fmt='o', ms=10, color="black")
+
+ref_psd = p1
+ref_psd_err = p1e
+
+
+
+t2, l2, l2e = np.loadtxt(echo_file).T
+# errorbar(t1, l1, yerr=l1e, fmt='o', color="green")
+# errorbar(t2, l2, yerr=l2e, fmt='o', color="black")
+
+
+P2 = clag.clag('psd10r', [t2], [l2], [l2e], dt, fqL)
+p2 = np.ones(nfq)
+p2, p2e = clag.optimize(P2, p2)
+
+p2, p2e = clag.errors(P2, p2, p2e)
+
+# xscale('log'); ylim(-6,2)
+# errorbar(fqd, p1, yerr=p1e, fmt='o', ms=10, color="green")
+# errorbar(fqd, p2, yerr=p2e, fmt='o', ms=10, color="black")
+echo_psd = p2
+echo_psd_err = p2e
+
+
+
+
+Cx = clag.clag('cxd10r', [[t1,t2]], [[l1,l2]], [[l1e,l2e]], dt, fqL, p1, p2)
+p  = np.concatenate( ((p1+p2)*0.5-0.3,p1*0+0.1) ) # a  good starting point generally
+p, pe = clag.optimize(Cx, p)
+
+phi, phie = p[nfq:], pe[nfq:]
+lag, lage = phi/(2*np.pi*fqd), phie/(2*np.pi*fqd)    
+cx, cxe   = p[:nfq], pe[:nfq]
+
+cross_spectrm = cx
+cross_spectrm_err = cxe
+
+# xscale('log'); ylim(-2,1)
+# errorbar(fqd, lag, yerr=lage, fmt='o', ms=10,color="black")
+
+
+
+
+s, loc, scale = lognorm.fit(lag,loc=.01)
+# xscale('log'); ylim(-4,1.5)
+# errorbar(fqd, lag, yerr=lage, fmt='o', ms=10,color="black")
+##plot(fqd,norm.pdf(fqd,mu,sigma))
+#plot(fqd,lognorm.pdf(fqd,s,loc,scale))
+# mu,sigma
+
+
+
+#plot(ifft(lag))
+
+np.savetxt("freq.out",fqL.reshape((-1,len(fqL))))
+np.savetxt("ref_psd.out",[ref_psd,ref_psd_err])
+np.savetxt("echo_psd.out",[echo_psd,echo_psd_err])
+np.savetxt("crsspctrm.out",[cross_spectrm,cross_spectrm_err])
+np.savetxt("lag.out",[lag,lage])
diff --git a/scripts/psdlag_6bin.py b/scripts/psdlag_6bin.py
new file mode 100644
index 0000000..364eb00
--- /dev/null
+++ b/scripts/psdlag_6bin.py
@@ -0,0 +1,112 @@
+#!/usr/bin/env python
+import numpy as np
+from scipy.stats import norm
+from scipy.stats import lognorm
+import sys
+import getopt
+sys.path.insert(1,"/usr/local/science/clag-agn/data/")
+import clag
+import matplotlib
+# %pylab inline
+
+
+#ref_file="data/lc/1367A.lc"
+#echo_file="data/lc/2246A.lc"
+
+ref_file  = str(sys.argv[1])
+echo_file = str(sys.argv[2])
+
+
+dt = 0.01
+t1, l1, l1e = np.loadtxt(ref_file).T
+# errorbar(t1, l1, yerr=l1e, fmt='o')
+
+#A
+fqL = np.logspace(np.log10(0.0049999999),np.log10(0.340002000),7)
+
+# not done for this bin number
+#B
+#fqL = np.array([0.0049999999, 0.018619375, 0.044733049,
+#                0.069336227, 0.10747115, 0.16658029,
+#                0.25819945, 0.40020915])
+
+
+#C
+#fqL = np.array([0.0049999999, 0.018619375, 0.044733049,
+#                0.069336227, 0.10747115, 0.16658029,
+#                0.25819945, 0.40020915])
+
+nfq = len(fqL) - 1
+fqd = 10**(np.log10( (fqL[:-1]*fqL[1:]) )/2.)
+
+
+
+
+
+P1 = clag.clag('psd10r', [t1], [l1], [l1e], dt, fqL)
+p1 = np.ones(nfq)
+p1, p1e = clag.optimize(P1, p1)
+
+p1, p1e = clag.errors(P1, p1, p1e)
+
+# xscale('log'); ylim(-4,2)
+# errorbar(fqd, p1, yerr=p1e, fmt='o', ms=10, color="black")
+
+ref_psd = p1
+ref_psd_err = p1e
+
+
+
+t2, l2, l2e = np.loadtxt(echo_file).T
+# errorbar(t1, l1, yerr=l1e, fmt='o', color="green")
+# errorbar(t2, l2, yerr=l2e, fmt='o', color="black")
+
+
+P2 = clag.clag('psd10r', [t2], [l2], [l2e], dt, fqL)
+p2 = np.ones(nfq)
+p2, p2e = clag.optimize(P2, p2)
+
+p2, p2e = clag.errors(P2, p2, p2e)
+
+# xscale('log'); ylim(-6,2)
+# errorbar(fqd, p1, yerr=p1e, fmt='o', ms=10, color="green")
+# errorbar(fqd, p2, yerr=p2e, fmt='o', ms=10, color="black")
+echo_psd = p2
+echo_psd_err = p2e
+
+
+
+
+Cx = clag.clag('cxd10r', [[t1,t2]], [[l1,l2]], [[l1e,l2e]], dt, fqL, p1, p2)
+p  = np.concatenate( ((p1+p2)*0.5-0.3,p1*0+0.1) ) # a  good starting point generally
+p, pe = clag.optimize(Cx, p)
+
+phi, phie = p[nfq:], pe[nfq:]
+lag, lage = phi/(2*np.pi*fqd), phie/(2*np.pi*fqd)    
+cx, cxe   = p[:nfq], pe[:nfq]
+
+cross_spectrm = cx
+cross_spectrm_err = cxe
+
+# xscale('log'); ylim(-2,1)
+# errorbar(fqd, lag, yerr=lage, fmt='o', ms=10,color="black")
+
+
+
+
+s, loc, scale = lognorm.fit(lag,loc=.01)
+# xscale('log'); ylim(-4,1.5)
+# errorbar(fqd, lag, yerr=lage, fmt='o', ms=10,color="black")
+##plot(fqd,norm.pdf(fqd,mu,sigma))
+#plot(fqd,lognorm.pdf(fqd,s,loc,scale))
+# mu,sigma
+
+
+
+#plot(ifft(lag))
+
+np.savetxt("freq.out",fqL.reshape((-1,len(fqL))))
+np.savetxt("ref_psd.out",[ref_psd,ref_psd_err])
+np.savetxt("echo_psd.out",[echo_psd,echo_psd_err])
+np.savetxt("crsspctrm.out",[cross_spectrm,cross_spectrm_err])
+np.savetxt("lag.out",[lag,lage])