#import astropy
#import h5py
#import math
#import numpy as np
#from scipy.constants import c 
#from astropy.io import fits
#import subprocess
#import statistics as stat
#from operator import mul
#from operator import truediv
#import itertools as it

# plotting variables
from setup_matplotlib import *
from matplotlib.ticker import MaxNLocator
width = 8.8
# Create the plot
#fig = plt.figure(figsize=(1.25*cm2inch(width), 6./8.*cm2inch(width)))
fig = plt.figure(figsize=(1.25*cm2inch(width), 1.25*cm2inch(width)))
#ax = fig.add_subplot(111)
ax = fig.add_subplot(111,aspect='equal')
#ax.set_aspect('equal')
#end plotting variables


betafilnavn33="/mn/stornext/d5/unnif/sindex_bp/coswmap23_coswmap33ab/combab_011-195/ut_sample_betas_invvar.txt"
b33=[]
u33=[]
with open(betafilnavn33) as f_p33:
    for line in f_p33:
        data = line.split()
        b33.append(float(data[1]))
        u33.append(float(data[2]))
f_p33.close()

betafilnavn30="/mn/stornext/d5/unnif/sindex_bp/coswmap23_cos30ab/combab_011-195/ut_sample_betas_invvar.txt"
b30=[]
u30=[]
with open(betafilnavn30) as f_p30:
    for line in f_p30:
        data = line.split()
        #rx.append(float(data[0]))  #plot the point next to the first two                                                                        
        b30.append(float(data[1]))
        u30.append(float(data[2]))
f_p30.close()

# a plot with numbers
n = np.arange(1, 25)
colors=['#1f77b4', '#ff7f0e', '#2ca02c', '#d62728', '#9467bd', '#8c564b', '#e377c2', '#7f7f7f', '#bcbd22', '#17becf','#1f77b4', '#ff7f0e', '#2ca02c', '#d62728', '#9467bd', '#8c564b', '#e377c2', '#7f7f7f', '#bcbd22', '#17becf','#1f77b4', '#ff7f0e', '#2ca02c', '#d62728', '#9467bd', '#8c564b', '#e377c2', '#7f7f7f', '#bcbd22', '#17becf']
for xi, yi, ux, uy, txt, col in zip(b33, b30, u33, u30, n, colors):
    #ax.scatter(xi, yi, marker=f'${txt}$')
    #markers, caps, bars = plt.errorbar(xi,yi, xerr=ux, yerr=uy, marker=f'${txt}$', capsize=2) #, alpha=0.5) #, linewidth=0.5, color='black',markersize=3,capsize=2,ls='none')
    markers, caps, bars = plt.errorbar(xi,yi, xerr=ux, yerr=uy, marker='.', capsize=2, color=col) #, alpha=0.5) #, linewidth=0.5, color='black',markersize=3,capsize=2,ls='none')
    [bar.set_alpha(0.35) for bar in bars]
    [cap.set_alpha(0.35) for cap in caps]
    
    #sette paa text
    xt=xi
    yt=yi
    #oppe til hoyre
    if txt==6 or txt==7 or txt==8 or txt==9 or txt==12 or txt==18 or txt==21 or txt==22 or txt==23: 
        xt=xi+0.018; yt=yt+0.003
        ha='left' ; va='bottom'
        if txt==9: xt=xi+0.025
    #oppe til venstre
    elif txt==3 or txt==4 or txt==5 or txt==11 or txt==15 or txt==17 or txt==19 or txt==20: 
        xt=xi-0.01; yt=yt+0.003
        ha='right' ; va='bottom'
        if txt==15 or txt==5: xt=xi #-0.001
        if txt==3 or txt==5: yt=yi
    #nede til venstre
    elif txt==1 or txt==2 or txt==10 or txt==13 or txt==14: 
        xt=xi-0.005; yt=yt-0.015
        ha='right' ; va='top'
    #nede til hoyre
    elif txt==16 or txt==24: 
        xt=xi+0.005; yt=yt-0.015
        ha='left' ; va='top'
    ax.annotate(txt, (xi, yi), xytext=(xt, yt), color=col, fontsize=9, horizontalalignment=ha, verticalalignment=va)

#['#1f77b4', '#ff7f0e', '#2ca02c', '#d62728', '#9467bd', '#8c564b', '#e377c2', '#7f7f7f', '#bcbd22', '#17becf']

#for i, txt in enumerate(n):
#    ax.annotate(txt, (z[i], y[i]))

# a x plot 
#plt.plot(b33, b30, marker='x', color='black', markersize=3, ls='none')

print("b33 "+str(min(b33))+" "+str(max(b33)))
print("b30 "+str(min(b30))+" "+str(max(b30)))

# straight line
xlin = np.linspace(-6,-1,100)
plt.plot(xlin,xlin, color='gray',linestyle='--', linewidth=0.5, alpha=0.9)

# general plot parameters
plt.xlim(-4.8,-2.2)
plt.ylim(-4.8,-2.2)
# plt.xlim(0.2,24.8)
# plt.xticks([1,5, 10, 15, 20, 24])
#ax.set_xticks([2,3,4], minor=True)
ax.minorticks_on()
plt.xlabel(r"Spectral index, $\beta_\mathrm{s}$ 23/33 GHz", fontsize=10)
plt.ylabel(r"Spectral index, $\beta_\mathrm{s}$ 23/30 GHz", fontsize=10) #;plt.xlabel(r"Region number", fontsize=10);
#leg = plt.legend(frameon=True, loc='lower right', prop={'size':7})
leg = plt.legend(frameon=True, loc='upper left', prop={'size':7})
# remove box around legend
leg.get_frame().set_edgecolor("white")
leg.get_frame().set_alpha(.0)
plt.show()
plt.savefig("xy_regions.png", bbox_inches='tight', bbox_extra_artists=[],pad_inches=0.03)


#ut_sample_scatter_alpha_spectral_index.txt