#  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: modelFit.py,
# Fit a linear combination of oscillators to data from a data file


import numpy             as np
import matplotlib.pyplot as plt
import array                       # to read and write binary files
import sys                         # to read command line arguments
import importlib                   # for importing of the info file

runName = sys.argv[1]              # this is the argument given on the command line
infoImportFile = "info_"+runName   # name to be used for importing

#   Import the info file for the run with this name
#   This has the effect of: import infoImportFile as info, except that
#   you don't know the name of the file to import in advance.

info = importlib.import_module(infoImportFile)
n    = info.n

#   Get the data for this example

DataFileName = "data_"+runName   # binary data filename
with open(DataFileName, 'rb') as DF:    # 'rb' is for "read binary"

   cpD = array.array('d')         # for "core python Data"
   cpD.fromstring(DF.read())      # Fix this to run on your system
   times = cpD[0:n]               # The first numbers are the times
   xvals = cpD[n:(2*n)]

fig,ax = plt.subplots()

ax.plot(times, xvals, "o")

ax.grid()
titleString = "raw data from " + runName
ax.set_title(titleString)
ax.set_ylabel("x")
ax.set_xlabel("t")
plotFileName = runName + "RawData.pdf"
plt.savefig(plotFileName)