#!/usr/bin/env python

# --------------------------------------------------------- #
#  Simple python script for reading ASCII data file
# --------------------------------------------------------- #

from ROOT import *
import math 


# Next, we inform ROOT what plotting style it should use for statistics and fitting box:
gStyle.SetOptStat("emr")  # Options for statistics box: "e" = entries, "m" = mean, "r" = RMS
gStyle.SetOptFit(1111)    # Options for fitting box.


# Open file
f = open('datafile.txt', 'r')
Nread = 0

verbose = True

# Read and ignore the header line
header = f.readline()

V_low = -0.56
V_high = 3.62
isLow = True


Hist_V = TH1F("Hist_V", "Hist_V", 160, -0.6, -0.5)
Hist_Vt = TH1F("Hist_Vt", "Hist_Vt", 80000, 0.0, 2.0)

# Loop over lines and extract variables of interest
for line in f :
    line = line.strip()          # Strip the line read for space characters
    columns = line.split()       # Split the line read into numbers (thus "columns" is a list)

    t = 0.0
    V = 0.0
    if (len(columns) == 2) :
        t = float(columns[0])       # Make "n1" the float (i.e. decimal number) value of the first string in "columns"
        V = float(columns[1])       # Voltage...
        Hist_V.Fill(V)
        Hist_Vt.SetBinContent(Nread+1, V)
        Hist_Vt.SetBinError(Nread+1, 0.0015)
        # Consider graph!!!

    if (isLow and V > V_low + 0.5*(V_high-V_low)) :
        isLow = False
        print t
    if (not isLow and V < V_low + 0.5*(V_high-V_low)) :
        isLow = True
        print t


    Nread += 1 
    if (t < -1.0) :
        print "Somthing wrong!"
    if (V < -10.0) :
        print "Somthing also wrong!"

    if (verbose and Nread < 10) :
        print "  %2d:  t = %8.6f    V = %9.6f "%(Nread, t, V)


f.close()

print "  Total number of lines: ", Nread




# Plot result:
# ------------
canvas = TCanvas( "canvas", "canvas", 50, 50, 1100, 500 )

Hist_Vt.SetTitle("Distribution of V vs. t")
Hist_Vt.GetXaxis().SetRangeUser(0.8, 1.2)
# Hist_Vt.GetXaxis().SetRangeUser(0.859, 0.863)
Hist_Vt.GetXaxis().SetTitle("t")
Hist_Vt.GetYaxis().SetTitle("V")
Hist_Vt.SetLineColor(kBlue)
Hist_Vt.SetLineWidth(2)
Hist_Vt.Draw("")

# Fitting histogram (with predefined function):
fit_Vt = TF1("fit_Vt", "[0] + [1]*(x-0.86) + [2]*(x-0.86)*(x-0.86) + [3]*(x-0.86)*(x-0.86)*(x-0.86)", 0.8603, 0.8613)
fit_Vt.SetLineColor(kRed)
fit_Vt.SetLineWidth(3)
Hist_Vt.Fit("fit_Vt", "R")

canvas.Update()







# Tell python to wait here until you do something...
raw_input( ' ... Press enter to exit ... ' )