# Copyright (C) 2002, Thomas Hamelryck (thamelry@binf.ku.dk)
#
# This file is part of the Biopython distribution and governed by your
# choice of the "Biopython License Agreement" or the "BSD 3-Clause License".
# Please see the LICENSE file that should have been included as part of this
# package.

"""Half-sphere exposure and coordination number calculation."""

import warnings
from math import pi

from Bio.PDB.AbstractPropertyMap import AbstractPropertyMap
from Bio.PDB.Polypeptide import CaPPBuilder
from Bio.PDB.Polypeptide import is_aa
from Bio.PDB.vectors import rotaxis


class _AbstractHSExposure(AbstractPropertyMap):
    """Abstract class to calculate Half-Sphere Exposure (HSE).

    The HSE can be calculated based on the CA-CB vector, or the pseudo CB-CA
    vector based on three consecutive CA atoms. This is done by two separate
    subclasses.
    """

    def __init__(self, model, radius, offset, hse_up_key, hse_down_key, angle_key=None):
        """Initialize class.

        :param model: model
        :type model: L{Model}

        :param radius: HSE radius
        :type radius: float

        :param offset: number of flanking residues that are ignored in the
                       calculation of the number of neighbors
        :type offset: int

        :param hse_up_key: key used to store HSEup in the entity.xtra attribute
        :type hse_up_key: string

        :param hse_down_key: key used to store HSEdown in the entity.xtra attribute
        :type hse_down_key: string

        :param angle_key: key used to store the angle between CA-CB and CA-pCB in
                          the entity.xtra attribute
        :type angle_key: string
        """
        assert offset >= 0
        # For PyMOL visualization
        self.ca_cb_list = []
        ppb = CaPPBuilder()
        ppl = ppb.build_peptides(model)
        hse_map = {}
        hse_list = []
        hse_keys = []
        for pp1 in ppl:
            for i in range(len(pp1)):
                if i == 0:
                    r1 = None
                else:
                    r1 = pp1[i - 1]
                r2 = pp1[i]
                if i == len(pp1) - 1:
                    r3 = None
                else:
                    r3 = pp1[i + 1]
                # This method is provided by the subclasses to calculate HSE
                result = self._get_cb(r1, r2, r3)
                if result is None:
                    # Missing atoms, or i==0, or i==len(pp1)-1
                    continue
                pcb, angle = result
                hse_u = 0
                hse_d = 0
                ca2 = r2["CA"].get_vector()
                for pp2 in ppl:
                    for j in range(len(pp2)):
                        if pp1 is pp2 and abs(i - j) <= offset:
                            # neighboring residues in the chain are ignored
                            continue
                        ro = pp2[j]
                        if not is_aa(ro) or not ro.has_id("CA"):
                            continue
                        cao = ro["CA"].get_vector()
                        d = cao - ca2
                        if d.norm() < radius:
                            if d.angle(pcb) < (pi / 2):
                                hse_u += 1
                            else:
                                hse_d += 1
                res_id = r2.get_id()
                chain_id = r2.get_parent().get_id()
                # Fill the 3 data structures
                hse_map[(chain_id, res_id)] = (hse_u, hse_d, angle)
                hse_list.append((r2, (hse_u, hse_d, angle)))
                hse_keys.append((chain_id, res_id))
                # Add to xtra
                r2.xtra[hse_up_key] = hse_u
                r2.xtra[hse_down_key] = hse_d
                if angle_key:
                    r2.xtra[angle_key] = angle
        AbstractPropertyMap.__init__(self, hse_map, hse_keys, hse_list)

    def _get_cb(self, r1, r2, r3):
        return NotImplemented

    def _get_gly_cb_vector(self, residue):
        """Return a pseudo CB vector for a Gly residue (PRIVATE).

        The pseudoCB vector is centered at the origin.

        CB coord=N coord rotated over -120 degrees
        along the CA-C axis.
        """
        try:
            n_v = residue["N"].get_vector()
            c_v = residue["C"].get_vector()
            ca_v = residue["CA"].get_vector()
        except Exception:
            return None
        # center at origin
        n_v = n_v - ca_v
        c_v = c_v - ca_v
        # rotation around c-ca over -120 deg
        rot = rotaxis(-pi * 120.0 / 180.0, c_v)
        cb_at_origin_v = n_v.left_multiply(rot)
        # move back to ca position
        cb_v = cb_at_origin_v + ca_v
        # This is for PyMol visualization
        self.ca_cb_list.append((ca_v, cb_v))
        return cb_at_origin_v


class HSExposureCA(_AbstractHSExposure):
    """Class to calculate HSE based on the approximate CA-CB vectors.

    Uses three consecutive CA positions.
    """

    def __init__(self, model, radius=12, offset=0):
        """Initialize class.

        :param model: the model that contains the residues
        :type model: L{Model}

        :param radius: radius of the sphere (centred at the CA atom)
        :type radius: float

        :param offset: number of flanking residues that are ignored
                       in the calculation of the number of neighbors
        :type offset: int
        """
        _AbstractHSExposure.__init__(
            self,
            model,
            radius,
            offset,
            "EXP_HSE_A_U",
            "EXP_HSE_A_D",
            "EXP_CB_PCB_ANGLE",
        )

    def _get_cb(self, r1, r2, r3):
        """Calculate approx CA-CB direction (PRIVATE).

        Calculate the approximate CA-CB direction for a central
        CA atom based on the two flanking CA positions, and the angle
        with the real CA-CB vector.

        The CA-CB vector is centered at the origin.

        :param r1, r2, r3: three consecutive residues
        :type r1, r2, r3: L{Residue}
        """
        if r1 is None or r3 is None:
            return None
        try:
            ca1 = r1["CA"].get_vector()
            ca2 = r2["CA"].get_vector()
            ca3 = r3["CA"].get_vector()
        except Exception:
            return None
        # center
        d1 = ca2 - ca1
        d3 = ca2 - ca3
        d1.normalize()
        d3.normalize()
        # bisection
        b = d1 + d3
        b.normalize()
        # Add to ca_cb_list for drawing
        self.ca_cb_list.append((ca2, b + ca2))
        if r2.has_id("CB"):
            cb = r2["CB"].get_vector()
            cb_ca = cb - ca2
            cb_ca.normalize()
            angle = cb_ca.angle(b)
        elif r2.get_resname() == "GLY":
            cb_ca = self._get_gly_cb_vector(r2)
            if cb_ca is None:
                angle = None
            else:
                angle = cb_ca.angle(b)
        else:
            angle = None
        # vector b is centered at the origin!
        return b, angle

    def pcb_vectors_pymol(self, filename="hs_exp.py"):
        """Write PyMol script for visualization.

        Write a PyMol script that visualizes the pseudo CB-CA directions
        at the CA coordinates.

        :param filename: the name of the pymol script file
        :type filename: string
        """
        if not self.ca_cb_list:
            warnings.warn("Nothing to draw.", RuntimeWarning)
            return
        with open(filename, "w") as fp:
            fp.write("from pymol.cgo import *\n")
            fp.write("from pymol import cmd\n")
            fp.write("obj=[\n")
            fp.write("BEGIN, LINES,\n")
            fp.write(f"COLOR, {1.0:.2f}, {1.0:.2f}, {1.0:.2f},\n")
            for ca, cb in self.ca_cb_list:
                x, y, z = ca.get_array()
                fp.write(f"VERTEX, {x:.2f}, {y:.2f}, {z:.2f},\n")
                x, y, z = cb.get_array()
                fp.write(f"VERTEX, {x:.2f}, {y:.2f}, {z:.2f},\n")
            fp.write("END]\n")
            fp.write("cmd.load_cgo(obj, 'HS')\n")


class HSExposureCB(_AbstractHSExposure):
    """Class to calculate HSE based on the real CA-CB vectors."""

    def __init__(self, model, radius=12, offset=0):
        """Initialize class.

        :param model: the model that contains the residues
        :type model: L{Model}

        :param radius: radius of the sphere (centred at the CA atom)
        :type radius: float

        :param offset: number of flanking residues that are ignored
                       in the calculation of the number of neighbors
        :type offset: int
        """
        _AbstractHSExposure.__init__(
            self, model, radius, offset, "EXP_HSE_B_U", "EXP_HSE_B_D"
        )

    def _get_cb(self, r1, r2, r3):
        """Calculate CB-CA vector (PRIVATE).

        :param r1, r2, r3: three consecutive residues (only r2 is used)
        :type r1, r2, r3: L{Residue}
        """
        if r2.get_resname() == "GLY":
            return self._get_gly_cb_vector(r2), 0.0
        else:
            if r2.has_id("CB") and r2.has_id("CA"):
                vcb = r2["CB"].get_vector()
                vca = r2["CA"].get_vector()
                return (vcb - vca), 0.0
        return None


class ExposureCN(AbstractPropertyMap):
    """Residue exposure as number of CA atoms around its CA atom."""

    def __init__(self, model, radius=12.0, offset=0):
        """Initialize class.

        A residue's exposure is defined as the number of CA atoms around
        that residue's CA atom. A dictionary is returned that uses a L{Residue}
        object as key, and the residue exposure as corresponding value.

        :param model: the model that contains the residues
        :type model: L{Model}

        :param radius: radius of the sphere (centred at the CA atom)
        :type radius: float

        :param offset: number of flanking residues that are ignored in
                       the calculation of the number of neighbors
        :type offset: int

        """
        assert offset >= 0
        ppb = CaPPBuilder()
        ppl = ppb.build_peptides(model)
        fs_map = {}
        fs_list = []
        fs_keys = []
        for pp1 in ppl:
            for i in range(len(pp1)):
                fs = 0
                r1 = pp1[i]
                if not is_aa(r1) or not r1.has_id("CA"):
                    continue
                ca1 = r1["CA"]
                for pp2 in ppl:
                    for j in range(len(pp2)):
                        if pp1 is pp2 and abs(i - j) <= offset:
                            continue
                        r2 = pp2[j]
                        if not is_aa(r2) or not r2.has_id("CA"):
                            continue
                        ca2 = r2["CA"]
                        d = ca2 - ca1
                        if d < radius:
                            fs += 1
                res_id = r1.get_id()
                chain_id = r1.get_parent().get_id()
                # Fill the 3 data structures
                fs_map[(chain_id, res_id)] = fs
                fs_list.append((r1, fs))
                fs_keys.append((chain_id, res_id))
                # Add to xtra
                r1.xtra["EXP_CN"] = fs
        AbstractPropertyMap.__init__(self, fs_map, fs_keys, fs_list)
