# code2.1b.py
# import plotsvg   <-- not accessible
import matplotlib
import matplotlib.pyplot as plt
import scipy.stats as sp
import numpy as np
import hwbfiles as hf 
import hwblines as hl
import statpos as sp

#varaxis = True
varaxis = False
nline = 6           
lines = np.arange(nline,dtype='f')
posx  = np.arange(nline,dtype='f')
posy  = np.arange(nline,dtype='f')

#--- Main program starts here. ---              
print('--- Read a file and make a cumulative plot ---')
print("MatPlotLib Version." + str(matplotlib.__version__))
print("NumPy Version." + str(np.__version__))
tocheck = False

f = hf.fileRead('tab2.1x.csv', False)
ndata = f.ndata
x = f.xa
y = f.ya
z = f.za

print(ndata, ' points in ' + f.fname)

med = np.median(x)
aver = np.average(x)
sigma = np.std(x)

if varaxis:
    f2 = hl.binwidths.varbins(x, y, ndata, aver, sigma, 0.3, True)
    zz = f2.za
#dz = f3.dz
    f3 = hl.accumlines.prepareLine(x, zz, ndata, 0.0, False)
  
else:    
    f3 = hl.accumlines.prepareLine(x, y, ndata, 0.0, False)

u = f3.ua
v = f3.va
plt.plot(u, v)

if varaxis:
    fp = sp.positions.posn(lines,nline,x,zz,ndata,aver,sigma,med)
else:
    fp = sp.positions.posn(lines,nline,x,y,ndata,aver,sigma,med)   
posx = fp.posx
posy = fp.posy

for i in range(nline):
    print(i,'-th point =',f'{posx[i]:,.2f}, {posy[i]:,.2f}')
    xs = np.array([posx[i]-1, posx[i]+1])
    ys = np.array([posy[i], posy[i]])
    plt.plot(xs, ys)

font1 = {'family':'serif','color':'blue','size':11}
font2 = {'family':'serif','color':'darkred','size':12}
plt.title("Figs. P1 or 2.2  Cumulative distribution", fontdict = font1)
plt.xlabel("Observed values", fontdict = font2)
plt.ylabel("Cumulative distribution", fontdict = font2)
#  plt.ylabel("Cumulative percent", fontdict = font2)
if not varaxis:
    plt.grid()
       
plt.show()