Calibration curve fitting and interpolating magnetization values

Int2Field.py

import numpy as np
import matplotlib.pyplot as plt
from scipy import interpolate
import sys
sys.path.append("./modules/")
####################################################################################################################################
filename = '08.0K_20x_01_d1_intensity_v_01'
#08.0K_20x_01_d1_intensity_h_02
#08.0K_20x_01_d1_intensity_v_01
#08.0K_20x_01_d1_intensity_v_02
filenameOut = '08.0K_20x_01_d1_gauss_v_01'
dataIn = np.loadtxt(filename+".dat")
####################################################################################################################################
writeIt = open(filenameOut+".dat", "w")	

relPath = "./"
filename = 'd01_Hyst_08.0K_20x_01_IvsH_bkgId_2_01'
#filename = 'd01_Hyst_08.0K_20x_01_IvsH_bkgId_2_02'
calCurve = np.loadtxt(relPath+filename+".dat")




Int = np.array([calCurve[i,0] for i in range(len(calCurve[:,0]))])
Ha = np.array([calCurve[i,1] for i in range(len(calCurve[:,0]))])
correction = min(Int)-34520.0
Int=Int-correction
#34520.0
tck = interpolate.splrep(Int, Ha, s=0)
yPy = interpolate.splev(Int, tck, der=0)



lenRow = dataIn.shape[0]
lenCol = dataIn.shape[1]

minVals = []
spline3MinVals = []

maxVals = []
spline3MaxVals = []

print Int[1]-Int[0]
for j in range(lenCol):
	writeIt.write("%.2f\t" % (dataIn[0,j])) #800
writeIt.write("\n")
for i in range(1,lenRow):
	writeIt.write("%.2f\t" % (dataIn[i,0])) #800
	for j in range(1,lenCol):
		if(dataIn[i,j]<min(Int)):
			minVals.append(dataIn[i,j])
			spline3MinVals.append(interpolate.splev(dataIn[i,j], tck, der=0))
		 	print "MIN %d %d (%.2f G) - value %d- min %d - dif %d"%(i,j,dataIn[0,j],dataIn[i,j],min(Int),dataIn[i,j]-min(Int))
		if(dataIn[i,j]>max(Int)):
			maxVals.append(dataIn[i,j])
			spline3MaxVals.append(interpolate.splev(dataIn[i,j], tck, der=0))
			print "MAX %d %d (%.2f G) - value %d- max %d - dif %d"%(i,j,dataIn[0,j],dataIn[i,j],max(Int),dataIn[i,j]-max(Int))
		writeIt.write("%.4f\t" % (interpolate.splev(dataIn[i,j], tck, der=0))) #800
		#writeIt.write("%.4f\t" % (interpolate.splev(dataIn[i,j], tck, der=0))) #800
	writeIt.write("\n")
writeIt.close()
if(len(minVals)!=0): print min(minVals)

plt.plot(Int, Ha, 'o',Int, yPy , 'b',minVals,spline3MinVals ,'ko' ,maxVals,spline3MaxVals ,'go')
plt.legend(['data', 'cubic spline python'], loc='best')


plt.show()