# code2.1c.py
# import plotsvg   <-- not accessible
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
import numpy.random as rnd
import hwblines as hl
import statpos as sp

sigmafit = 0.3
#varaxis = True
nline = 6          
lines = np.arange(nline,dtype='f')
# posx  = np.arange(nline,dtype='f')
# posy  = np.arange(nline,dtype='f')
ndata = 200

#--- 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__))

# The following line in code2.1a.py is replaced
# f = hf.fileRead('tab2.1x.csv', False); x = f.xa; etc.

sig = 0.3     # fitting parameter

x = rnd.normal(8.5, 1.5, ndata)  
x.sort()
y = np.arange(ndata, dtype="f")
for i in range(ndata):
    y[i] = i + 1

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

for loop in range(2):
    varaxis = (loop==1)
    if varaxis:
        f2 = hl.binwidths.varbins(x, y, ndata, aver, sigma, sig, True)
        zz = f2.za
        dz = f2.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()