Commit JT 042418

- adding the README
- some corrects pair_spin*.cpp/h

examples/SPIN/cobalt_fcc/exchange_fit_fcc_co/exchange_fcc_cobalt.dat

@@ -0,0 +1,5 @@
+2.503 0.01476
+3.54  0.001497
+4.33  0.001578
+5.01  -0.001224
+5.597 0.000354

examples/SPIN/cobalt_fcc/exchange_fit_fcc_co/exchange_fit.py

@@ -0,0 +1,32 @@
+#Program fitting the exchange interaction
+#Model curve: Bethe-Slater function
+import numpy as np, pylab, tkinter
+import matplotlib.pyplot as plt
+from scipy.optimize import curve_fit
+from decimal import *
+
+print("Loop begin")
+
+#Definition of the Bethe-Slater function
+def func(x,a,b,c):
+    return 4*a*((x/c)**2)*(1-b*(x/c)**2)*np.exp(-(x/c)**2)
+
+#Exchange coeff table (data to fit)
+rdata, Jdata = np.loadtxt('exchange_fcc_cobalt.dat', usecols=(0,1), unpack=True)
+plt.plot(rdata, Jdata, 'b-', label='data')
+
+#Perform the fit
+popt, pcov = curve_fit(func, rdata, Jdata, bounds=(0, [500.,5.,5.]))
+plt.plot(rdata, func(rdata, *popt), 'r--', label='fit')
+
+#Print the fitted params
+print("Parameters: a={:.10} (in meV), b={:.10} (adim), c={:.10} (in Ang)".format(*popt))
+
+#Ploting the result
+plt.xlabel('r_ij')
+pylab.xlim([0,6.5])
+plt.ylabel('J_ij')
+plt.legend()
+plt.show()
+
+print("Loop end")

examples/SPIN/iron/exchange_fit_bcc_iron/exchange_bcc_iron.dat

@@ -1,3 +1,5 @@
 2.4824 0.01948336
 2.8665 0.01109
 4.0538 -0.0002176
+4.753 -0.001714
+4.965 -0.001986

examples/SPIN/nickel/exchange_fit_fcc_ni/exchange_fcc_ni.dat

@@ -1,5 +1,5 @@
-2.495 8.3
-3.524 -3.99
-4.31 0.998
-4.99 -0.955
-5.56 0.213
+2.492 0.0028027
+3.524 0.0000816
+4.316 0.0003537
+4.984 0.0001632
+5.572 0.0000408

examples/SPIN/nickel/exchange_fit_fcc_ni/exchange_fcc_ni2.dat

@@ -0,0 +1,5 @@
+2.495 8.3
+3.524 -3.99
+4.31 0.998
+4.99 -0.955
+5.56 0.213

examples/SPIN/nickel/exchange_fit_fcc_ni/exchange_fit.py

@@ -16,7 +16,7 @@ rdata, Jdata = np.loadtxt('exchange_fcc_ni.dat', usecols=(0,1), unpack=True)
 plt.plot(rdata, Jdata, 'b-', label='data')
 
 # perform the fit
-popt, pcov = curve_fit(func, rdata, Jdata, bounds=(0, [500.,5.,5.]))
+popt, pcov = curve_fit(func, rdata, Jdata, bounds=([0.0,-1.0,0.0], [100.,5.,5.]))
 plt.plot(rdata, func(rdata, *popt), 'r--', label='fit')
 
 # print the fitted parameters
@@ -24,7 +24,8 @@ print("Parameters: a={:.10} (in meV), b={:.10} (adim), c={:.10} (in Ang)".format
 
 # ploting the result
 plt.xlabel('r_ij')
-pylab.xlim([0,6.5])
+pylab.xlim([0.0,6.5])
+#pylab.ylim([-2.0,10.0])
 plt.ylabel('J_ij')
 plt.legend()
 plt.show()