#  Python 3
#  Author: Jonathan Goodman, goodman@cims.nyu.edu
#  Fall 2024
#  for the class Scientific Computing
#  https://math.nyu.edu/~goodman/teaching/ScientificComputing2024/ScientificComputing.html

#  Illustrate writing and reading numerical data to and from files

# This file: DataAnalysis.py,
# Reads time series data described in DataInfo.py
# The datafile and model parameter file names are in DataInfo.py

import numpy as np
import array
import DataInfo as df         # Information about the data file

m = df.m                         # time series length
n = df.n                         # number of time series

DataFileName  = df.DataFileName    # binary data file names
ModelFileName = df.ModelFileName

with open(DataFileName, 'rb') as DF:    # 'rb' is for "read binary"

   allData = array.array('d')           # the whole file
   allData.fromstring(DF.read())        # read the whole file
   T_vals = np.array( allData[0: m ] )  # values 0, 1 ,...,m-1
   f_vals = np.array( allData[m:(2*m)]) # values m,m+1,...,2m

for j in range(m):
   line = "j is {j:4d}, t_j is {t_j:10.5f}, f(t_j) is {f:10.5f}"
   line = line.format(j=j, t_j = T_vals[j], f = f_vals[j])
   print(line)
   
with open(ModelFileName, 'rb') as MF:    # 'rb' is for "read binary"

   allData = array.array('d')           # the whole file
   allData.fromstring(MF.read())        # read the whole file
   lam = np.array( allData[0: n ] )  # values 0, 1 ,...,m-1
   a = np.array( allData[n:(2*n)]) # values m,m+1,...,2m

for k in range(n):
   line = "k is {k:4d}, lambda is {lam:10.5f}, a is {a:10.5f}"
   line = line.format(k=k, lam = lam[k], a = a[k])
   print(line)