#!/usr/bin/env python
# Copyright 2004 Robert Bussell, Jr.  All rights reserved.
#
# This code is part of the Biopython distribution and governed by its
# license.  Please see the LICENSE file that should have been included
# as part of this package.

"""Generate NOE crosspeak peaklists from diagonal peaklist.

** What is this code? **

This is an example script for using new biopython modules for
generating NOE crosspeak peaklists from diagonal peaklist within
the framework of nmrview.
nmrview is not required to run this script, only an installed
version of python.


** What's important? **

The xpktools.py and NOEtools.py modules are what I'm trying to
demonstrate.  They provide methods and a data class for performing
some general analysis on NMR data taken directly from peaklist.
The code in this script will demonstrate how they are used.


** Who wrote this code? **

Robert Bussell, Jr.
rgb2003@med.cornell.edu


** Running this script **

To run this script on a UNIX/Linux system, make it executable and
modify the first line of this script to point to python if necessary.
First try running the code with the peaklist that I provide to get
the feel of how things work, then you can use your own peaklist if you
modify the variables under the "INITS" code block to make it work
with your data.  The modules xpktools and NOEtools can be called from
your own scripts when you have them in place on your computer.
NOTE: It is very important to have an intact peaklist.  If you copy and
paste mine into a file be prepared to remove inappropriate line breaks.


** Output of this script **

This script generates a human readable standard output version of the
NOE coordinates as well as an nmrview peaklist out_example.xpk.
"""

from __future__ import print_function

# -- don't need to modify sys.path with the *tools in Biopython
# -- just need Biopython installed somewhere in the PYTHONPATH
# sys.path=[sys.path,"./"]
# sys.path=[sys.path,"/usr/people/robert/development/xpktools"]
from Bio.NMR import xpktools  # Contains data classes and functions for .xpk files
from Bio.NMR import NOEtools  # A module specific for generate NOE predictions

# * * * * * * * * * * MAIN * * * * * * * * * *

# ***** INITS *****

inc = 1                      # The NOE increment (n where i->i+n and i->i-n are noes)
infn = "./noed.xpk"          # Input peaklist
outfn = "./out_example.xpk"  # Output peaklist
detectatom = "H1"           # Directly detected atom
relayatom = "N15"           # J-coupling from here to detected atom
fromatom = "15N2"           # The other labelled nucleus

#  First the peaklist is read into a data class from xpktools
#  that contains methods for easily extracting information from
#  the peaklist file

peaklist = xpktools.Peaklist(infn)  # infn is the name of the xpk file

# The class attribute residue_dict allows the data lines
# to be separated from the header and returned here to
# the dictionary <dict> as a list indexed by the assignment
# of any of the nuclei in the file -- here, the detected atom
# is used

dict = peaklist.residue_dict(detectatom)

# As well as the data, the dictionary contains two other entries,
# corresponding to the maximum and minimum residues indexed

MAXRES = dict["maxres"]
MINRES = dict["minres"]

# ****** CALCULATE AND WRITE CROSSPEAK PEAKLIST *****

# The peaklist class has a method for writing out the header
# information in a format recognizable by nmrview

peaklist.write_header(outfn)  # Write the header to the output file

# Predict the i->i+inc and i->i-inc noe positions if possible
# Write each one to the output file as they are calculated

count = 0     # A counter that number the output data lines in order
res = MINRES  # minimum residue number in the set
outlist = []  # Holds the output data

while (res <= MAXRES):
    # Predicting the NOE positions based on peak assignment data
    # is done by supplying the peaklist to and specifying the label
    # of the origin and detected atom in the NOE transfer as well as
    # the residues between which the NOE transfer takes places.

    noe1 = NOEtools.predictNOE(peaklist, "15N2", "H1", res, res + inc)
    noe2 = NOEtools.predictNOE(peaklist, "15N2", "H1", res, res - inc)

    # The output of predictNOE is in the form of an xpk entry line
    # suitable for printing to an output file
    # Additionally, it is possible to extract information easily from
    # these output lines by using the xpktools.XpkEntry class

    entry1 = xpktools.XpkEntry(noe1, peaklist.datalabels)

    if noe1 != "":

        # Here I'm using the XpkEntry class to gain access to
        # specific fields in the file that make the information
        # more readable and suitable for creating data tables
        # This output will be printed to the screen.
        # The data table contains the assignment, coordinates and
        # intensity of the resonance.

        print(entry1.fields["15N2.L"].split(".")[0], "-->",
              entry1.fields["N15.L"].split(".")[0], "\t",
              entry1.fields["H1.P"], entry1.fields["N15.P"],
              entry1.fields["15N2.P"], entry1.fields["int"])

        noe1 = noe1 + "\012"
        noe1 = xpktools.replace_entry(noe1, 1, count)
        outlist.append(noe1)
        count += 1

        if noe2 != "":
            noe2 = noe2 + "\012"
            noe2 = xpktools.replace_entry(noe2, 1, count)
            outlist.append(noe2)
            count += 1
    res += 1

# Open the output file and write the data
with open(outfn, "a") as outfile:
    outfile.writelines(outlist)  # Write the output lines to the file
