#Plotting
import matplotlib.pyplot as plt
import matplotlib.mlab as ml
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from matplotlib import cm
from matplotlib.ticker import LinearLocator, FormatStrFormatter
filename='2d_T_profile_2.dat'
data=np.genfromtxt(filename)
print(np.shape(data))
xscan=data[:,0]*500
yscan=data[:,1]*500


T=data[:,2]


xi = np.linspace(min(xscan), max(xscan),500)
yi = np.linspace(min(yscan), max(yscan),500)


#zi = ml.griddata(xscan, yscan, z, xi, yi, interp='nn')
#zi1 = ml.griddata(xscan, yscan, z1, xi, yi, interp='linear')
#zi2 = ml.griddata(xscan, yscan, z2, xi, yi, interp='linear')
maxpo=np.zeros((9,3))
sx=np.size(xi)
sy=np.size(yi)
fig = plt.figure(figsize=(20,20))
plt.subplots_adjust(hspace=1)
xpp=[]
ypp=[]
maxT=[]

z1=T

zi1 = ml.griddata(xscan, yscan, z1, xi, yi, interp='linear')
mp=np.argmax(zi1)
xp=int(mp/sx)
yp=(mp%sx)
#print(sx)
#print(xp,yp)
print(xi[xp],yi[yp],np.max(zi1))
#plotting
xpp.append(xp)
ypp.append(yp)
maxT.append(np.max(zi1))

ax1=plt.subplot(1,1,1)
zi1 = ml.griddata(xscan, yscan, z1, xi, yi, interp='linear')
plt.contour(xi, yi, zi1, linewidths = 0.5,colors='b')
plt.pcolormesh(xi, yi, zi1, cmap = plt.get_cmap('rainbow'))
plt.colorbar()
#plt.scatter(xscan, yscan, marker = '.-', c = 'b', s = 10, zorder = 10)
#plt.plot(xscan,yscan,'.-')
plt.xlim(min(xscan), max(xscan))
plt.ylim(min(yscan), max(yscan))

	#plt.savefig('foo'+'_'+str(i)+'.pdf')
plt.tight_layout()
plt.savefig(filename+'.pdf')
plt.show()
print('zi1 shape',np.shape(zi1))
print('size of xscan and yscan',np.size(xscan),np.size(yscan))
print('size of xi,yi ',np.size(xi),np.size(yi))
'''
surf = ax.plot_surface(xi, yi, zi1, rstride=1, cstride=1, cmap=cm.coolwarm,
                       linewidth=0, antialiased=False)
surf = ax.plot_surface(xi, yi, zi2+1000, rstride=1, cstride=1, cmap=cm.coolwarm,
                       linewidth=0, antialiased=False)
ax.zaxis.set_major_locator(LinearLocator(10))
ax.zaxis.set_major_formatter(FormatStrFormatter('%.02f'))
'''
plt.show()