# cython: c_string_type=str, c_string_encoding=ascii
##############################################################################
# MDTraj: A Python Library for Loading, Saving, and Manipulating
#         Molecular Dynamics Trajectories.
# Copyright 2012-2013 Stanford University and the Authors
#
# Authors: Robert McGibbon
# Contributors:
#
# MDTraj is free software: you can redistribute it and/or modify
# it under the terms of the GNU Lesser General Public License as
# published by the Free Software Foundation, either version 2.1
# of the License, or (at your option) any later version.
#
# This library is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# GNU Lesser General Public License for more details.
#
# You should have received a copy of the GNU Lesser General Public
# License along with MDTraj. If not, see <http://www.gnu.org/licenses/>.
##############################################################################


###############################################################################
# Imports
###############################################################################

import os
import warnings
import cython
cimport cython
import numpy as np
cimport numpy as np
np.import_array()
from mdtraj.utils import ensure_type, cast_indices, in_units_of
from mdtraj.utils.six import string_types
from mdtraj.formats.registry import _FormatRegistry
cimport trrlib

__all__ = ['load_trr', 'TRRTrajectoryFile']


###############################################################################
# globals
###############################################################################

cdef int _EXDROK = 0             # OK
cdef int _EXDRENDOFFILE = 11     # End of file
_EXDR_ERROR_MESSAGES = {
    1: "Header",
    2: "String",
    3: "Double",
    4: "Integer",
    5: "Float",
    6: "Unsigned integer",
    7: "Compressed 3d coordinate",
    8: "Closing file",
    9: " Magic number",
    10: 'Not enough memory',
    12: "File not found"
}

# numpy variable types include the specific numpy of bytes of each, but the c
# variables in our interface file don't. this could get bad if we're on a wierd
# machine, so lets make sure first
if sizeof(int) != sizeof(np.int32_t):
    raise RuntimeError('Integers on your compiler are not 32 bits. This is not good.')
if sizeof(float) != sizeof(np.float32_t):
    raise RuntimeError('Floats on your compiler are not 32 bits. This is not good')

###############################################################################
# Code
###############################################################################

@_FormatRegistry.register_loader('.trr')
def load_trr(filename, top=None, stride=None, atom_indices=None, frame=None):
    """load_trr(filename, top=None, stride=None, atom_indices=None, frame=None)
    
    Load a Gromacs TRR file from disk.

    The .trr format is a cross-platform compressed binary trajectory format
    produced by the gromacs software that stores atomic coordinates, box
    vectors, and time information.

    Parameters
    ----------
    filename : str
        Filename of TRR trajectory file.
    top : {str, Trajectory, Topology}
        The TRR format does not contain topology information. Pass in either the
        path to a pdb file, a trajectory, or a topology to supply this information.
    stride : int, default=None
        Only read every stride-th frame
    atom_indices : array_like, optional
        If not none, then read only a subset of the atoms coordinates from the
        file. This may be slightly slower than the standard read because it
        requires an extra copy, but will save memory.
    frame : int, optional
        Use this option to load only a single frame from a trajectory on disk.
        If frame is None, the default, the entire trajectory will be loaded.
        If supplied, ``stride`` will be ignored.

    Examples
    --------
    >>> import mdtraj as md                                        # doctest: +SKIP
    >>> traj = md.load_trr('output.trr', top='topology.pdb')       # doctest: +SKIP
    >>> print traj                                                 # doctest: +SKIP
    <mdtraj.Trajectory with 500 frames, 423 atoms at 0x110740a90>  # doctest: +SKIP

    Returns
    -------
    trajectory : md.Trajectory
        The resulting trajectory, as an md.Trajectory object.

    See Also
    --------
    mdtraj.TRRTrajectoryFile :  Low level interface to TRR files
    """
    # we make it not required in the signature, but required here. although this
    # is a little wierd, its good because this function is usually called by a
    # dispatch from load(), where top comes from **kwargs. So if its not supplied
    # we want to give the user an informative error message
    from mdtraj.core.trajectory import _parse_topology, Trajectory
    if top is None:
        raise ValueError('"top" argument is required for load_trr')

    if not isinstance(filename, string_types):
        raise TypeError('filename must be of type string for load_trr. '
            'you supplied %s' % type(filename))

    topology = _parse_topology(top)
    atom_indices = cast_indices(atom_indices)
    if atom_indices is not None:
        topology = topology.subset(atom_indices)

    with TRRTrajectoryFile(filename) as f:
        if frame is not None:
            f.seek(frame)
            xyz, time, step, box, lambd = f.read(n_frames=1, atom_indices=atom_indices)
        else:
            xyz, time, step, box, lambd = f.read(stride=stride, atom_indices=atom_indices)

        in_units_of(xyz, f.distance_unit, Trajectory._distance_unit, inplace=True)
        in_units_of(box, f.distance_unit, Trajectory._distance_unit, inplace=True)

    trajectory = Trajectory(xyz=xyz, topology=topology, time=time)
    trajectory.unitcell_vectors = box
    return trajectory


cdef class TRRTrajectoryFile:
    """TRRTrajectoryFile(filename, mode='r', force_overwrite=True, **kwargs)

    Interface for reading and writing to a GROMACS TRR file.
    This is a file-like objec that supports both reading and writing.
    It also supports the context manager protocol, so you can use it
    with the python 'with' statement.

    The conventional units in the TRR file are nanometers and picoseconds.
    The format only supports saving coordinates, the time, the md step,
    and the unit cell parametrs (box vectors)

    Parameters
    ----------
    filename : str
        The filename to open. A path to a file on disk.
    mode : {'r', 'w'}
        The mode in which to open the file, either 'r' for read or 'w' for write.
    force_overwrite : bool
        If opened in write mode, and a file by the name of `filename` already
        exists on disk, should we overwrite it?

    Other Parameters
    ----------------
    min_chunk_size : int, default=100
        In read mode, we need to allocate a buffer in which to store the data
        without knowing how many frames are in the file. This parameter is the
        minimum size of the buffer to allocate.
    chunk_size_multiplier, int, default=1.5
        In read mode, we need to allocate a buffer in which to store the data
        without knowing how many frames are in the file. We can *guess* this
        information based on the size of the file on disk, but it's not perfect.
        This parameter inflates the guess by a multiplicative factor.

    Examples
    --------
    >>> # load up the data from a trr
    >>> with XTCTrajectoryFile('traj.trr') as f:
    >>>    xyz, time, step, box, lambdas = f.read()

    See Also
    --------
    mdtraj.load_trr : High-level wrapper that returns a ``md.Trajectory``
    """
    cdef trrlib.XDRFILE* fh
    cdef str filename
    cdef int n_atoms          # number of atoms in the file
    cdef unsigned long n_frames  # numnber of frames in the file, cached
    cdef int frame_counter    # current position in the file, in read mode
    cdef int is_open          # is the file handle currently open?
    cdef int approx_n_frames  # appriximate number of frames in the file, as guessed based on its size
    cdef char* mode           # mode in which the file is open, either 'r' or 'w'
    cdef int min_chunk_size
    cdef float chunk_size_multiplier
    cdef int with_unitcell    # used in mode='w' to know if we're writing unitcells or nor
    cdef readonly char* distance_unit


    def __cinit__(self, char* filename, char* mode='r', force_overwrite=True, **kwargs):
        """Open a GROMACS TRR file for reading/writing.
        """
        self.distance_unit = 'nanometers'
        self.is_open = False
        self.frame_counter = 0
        self.n_frames = -1
        self.filename = filename

        if str(mode) == 'r':
            self.n_atoms = 0
            if not os.path.exists(filename):
                raise IOError("The file '%s' doesn't exist" % filename)
            trrlib.read_trr_natoms(filename, &self.n_atoms)
            if self.n_atoms <= 0:
                raise IOError('Malformed TRR file. Number of atoms <= 0. '
                              'Are you sure this is a valid GROMACS TRR file?')

            self.fh = trrlib.xdrfile_open(filename, b'r')
            if self.fh is NULL:
                raise IOError('File not found: "%s"' % filename)
            self.approx_n_frames = self._estimate_n_frames_from_filesize(os.stat(filename).st_size)

            self.min_chunk_size = max(kwargs.pop('min_chunk_size', 100), 1)
            self.chunk_size_multiplier = max(kwargs.pop('chunk_size_multiplier', 1.5), 0.01)


        elif str(mode) == 'w':
            if force_overwrite and os.path.exists(filename):
                os.unlink(filename)

            self.fh = trrlib.xdrfile_open(filename, 'w')
            if self.fh is NULL:
                raise IOError('Unable to open file "%s"' % filename)
        else:
            raise ValueError('mode must be one of "r" or "w". '
                             'you supplied %s' % mode)

        for key in kwargs.keys():
            warnings.warn('kwarg "%s" was not recognized or processed' % key)

        self.is_open = True
        self.mode = mode

    def _estimate_n_frames_from_filesize(self, filesize):
        # this approximation is pretty bad. on 5000/500 frames, 50/100 atoms,
        # it seems to be about 30%
        approx_n_frames = filesize / ((self.n_atoms * 2 * + 16) / 2)
        return approx_n_frames

    def __dealloc__(self):
        self.close()

    def close(self):
        """Close the TRR file"""
        if self.is_open:
            trrlib.xdrfile_close(self.fh)
            self.is_open = False

    def read(self, n_frames=None, stride=None, atom_indices=None):
        """read(n_frames=None, stride=None, atom_indices=None)

        Read data from a TRR file

        Parameters
        ----------
        n_frames : int, None
            The number of frames you would like to read from the file.
            If None, all of the remaining frames will be loaded.
        stride : int, optional
            Read only every stride-th frame.
        atom_indices : array_like, optional
            If not none, then read only a subset of the atoms coordinates from the
            file. This may be slightly slower than the standard read because it required
            an extra copy, but will save memory.

        Returns
        -------
        xyz : np.ndarray, shape=(n_frames, n_atoms, 3), dtype=np.float32
            The cartesian coordinates, in nanometers
        time : np.ndarray, shape=(n_frames), dtype=np.float32
            The simulation time, in picoseconds, corresponding to each frame
        step : np.ndarray, shape=(n_frames), dtype=np.int32
            The step in the simulation corresponding to each frame
        box : np.ndarray, shape=(n_frames, 3, 3), dtype=np.float32
            The box vectors in each frame.
        lambd : np.ndarray, shape=(n_frames), dtype=np.float32
            The alchemical lambda value of each frame.

        Notes
        -----
        The TRR format DOES support saving velocities and forces, but those
        fields are not read (or written) by the current implementation of this
        wrapper.
        """
        if not str(self.mode) == 'r':
            raise ValueError('read() is only available when file is opened in mode="r"')
        if not self.is_open:
            raise IOError('file must be open to read from it.')

        if n_frames is not None:
            # if they supply the number of frames they want, that's easy
            if not int(n_frames) == n_frames:
                raise ValueError('n_frames must be an int, you supplied "%s"' % n_frames)
            xyz, time, step, box, lambd = self._read(int(n_frames), atom_indices)
            xyz, time, step, box, lambd = xyz[::stride], time[::stride], step[::stride], box[::stride], lambd[::stride]
            if np.all(np.logical_and(box < 1e-10, box > -1e-10)):
                box = None
            return xyz, time, step, box, lambd

        # if they want ALL of the remaining frames, we need to guess at the chunk
        # size, and then check the exit status to make sure we're really at the EOF
        all_xyz, all_time, all_step, all_box, all_lambd = [], [], [], [], []

        while True:
            # guess the size of the chunk to read, based on how many frames we
            # think are in the file and how many we've currently read
            chunk = max(abs(int((self.approx_n_frames - self.frame_counter) * self.chunk_size_multiplier)),
                        self.min_chunk_size)
            xyz, time, step, box, lambd = self._read(chunk, atom_indices)
            if len(xyz) <= 0:
                break

            all_xyz.append(xyz)
            all_time.append(time)
            all_step.append(step)
            all_box.append(box)
            all_lambd.append(lambd)

        all_xyz = np.concatenate(all_xyz)[::stride]
        all_time = np.concatenate(all_time)[::stride]
        all_step = np.concatenate(all_step)[::stride]
        all_box =  np.concatenate(all_box)[::stride]
        all_lambd = np.concatenate(all_lambd)[::stride]
        if np.all(np.logical_and(all_box < 1e-10, all_box > -1e-10)):
            all_box = None
        return all_xyz, all_time, all_step, all_box, all_lambd

    def _read(self, int n_frames, atom_indices):
        """Read a specified number of TRR frames from the buffer"""

        cdef int i = 0
        cdef int status = _EXDROK
        cdef int n_atoms_to_read

        if atom_indices is None:
            n_atoms_to_read = self.n_atoms
        elif isinstance(atom_indices, slice):
            n_atoms_to_read = len(np.arange(self.n_atoms)[atom_indices])
        else:
            atom_indices = np.asarray(atom_indices)
            if min(atom_indices) < 0:
                raise ValueError('atom_indices should be zero indexed. you gave an index less than zero')
            if max(atom_indices) >= self.n_atoms:
                raise ValueError('atom indices should be zero indexed. you gave an index bigger than the number of atoms')
            n_atoms_to_read = len(atom_indices)

        cdef np.ndarray[ndim=3, dtype=np.float32_t, mode='c'] xyz = \
            np.empty((n_frames, n_atoms_to_read, 3), dtype=np.float32)
        cdef np.ndarray[ndim=1, dtype=np.float32_t, mode='c'] time = \
            np.empty((n_frames), dtype=np.float32)
        cdef np.ndarray[ndim=1, dtype=np.int32_t, mode='c'] step = \
            np.empty((n_frames), dtype=np.int32)
        cdef np.ndarray[ndim=1, dtype=np.float32_t, mode='c'] lambd = \
            np.empty((n_frames), dtype=np.float32)
        cdef np.ndarray[ndim=3, dtype=np.float32_t, mode='c'] box = \
            np.empty((n_frames, 3, 3), dtype=np.float32)

        # only used if atom_indices is given
        cdef np.ndarray[dtype=np.float32_t, ndim=2] framebuffer = np.zeros((self.n_atoms, 3), dtype=np.float32)



        while (i < n_frames) and (status != _EXDRENDOFFILE):
            if atom_indices is None:
                status = trrlib.read_trr(self.fh, self.n_atoms, <int*> &step[i], &time[i], &lambd[i],
                                         <trrlib.matrix>&box[i,0,0], <trrlib.rvec*>&xyz[i,0,0], NULL, NULL)
            else:
                status = trrlib.read_trr(self.fh, self.n_atoms, <int*> &step[i], &time[i], &lambd[i],
                                         <trrlib.matrix> &box[i,0,0], <trrlib.rvec*>&framebuffer[0,0], NULL, NULL)
                xyz[i, :, :] = framebuffer[atom_indices, :]

            if status != _EXDRENDOFFILE and status != _EXDROK:
                raise RuntimeError('TRR read error: %s' % _EXDR_ERROR_MESSAGES.get(status, 'unknown'))
            i += 1

        if status == _EXDRENDOFFILE:
            xyz = xyz[:i-1]
            box = box[:i-1]
            time = time[:i-1]
            step = step[:i-1]
            lambd = lambd[:i-1]

        self.frame_counter += i

        return xyz, time, step, box, lambd

    def write(self, xyz, time=None, step=None, box=None, lambd=None):
        """write(xyz, time=None, step=None, box=None, lambd=None)

        Write data to a TRR file

        Parameters
        ----------
        xyz : np.ndarray, dtype=np.float32, shape=(n_frames, n_atoms, 3)
            The cartesian coordinates of the atoms, in nanometers
        time : np.ndarray, dtype=float32, shape=(n_frames), optional
            The simulation time corresponding to each frame, in picoseconds.
            If not supplied, the numbers 0..n_frames will be written.
        step :  np.ndarray, dtype=int32, shape=(n_frames), optional
            The simulation timestep corresponding to each frame, in steps.
            If not supplied, the numbers 0..n_frames will be written
        box : np.ndarray, dtype=float32, shape=(n_frames, 3, 3), optional
            The periodic box vectors of the simulation in each frame, in nanometers.
            If not supplied, the vectors (1,0,0), (0,1,0) and (0,0,1) will
            be written for each frame.
        lambd : np.ndarray, dtype=np.float32, shape=(n_frames), optional
            The alchemical lambda value at each frame. If not supplied, all
            zeros will be written.
        """
        if str(self.mode) != 'w':
            raise ValueError('write() is only available when the file is opened in mode="w"')

        # do typechecking, and then dispatch to the c level function
        xyz = ensure_type(xyz, dtype=np.float32, ndim=3, name='xyz', can_be_none=False,
                          add_newaxis_on_deficient_ndim=True, warn_on_cast=False)
        n_frames = len(xyz)
        time = ensure_type(time, dtype=np.float32, ndim=1, name='time', can_be_none=True,
                           shape=(n_frames,), add_newaxis_on_deficient_ndim=True,
                           warn_on_cast=False)
        step = ensure_type(step, dtype=np.int32, ndim=1, name='step', can_be_none=True,
                           shape=(n_frames,), add_newaxis_on_deficient_ndim=True,
                           warn_on_cast=False)
        box = ensure_type(box, dtype=np.float32, ndim=3, name='box', can_be_none=True,
                          shape=(n_frames, 3, 3), add_newaxis_on_deficient_ndim=True,
                          warn_on_cast=False)
        lambd = ensure_type(lambd, dtype=np.float32, ndim=1, name='lambd', can_be_none=True,
                            shape=(n_frames,), add_newaxis_on_deficient_ndim=True,
                            warn_on_cast=False)

        if self.frame_counter == 0:
            self.n_atoms = xyz.shape[1]
            self.with_unitcell = (box is not None)
        else:
            if not self.n_atoms == xyz.shape[1]:
                raise ValueError("This file has %d atoms, but you're now trying to write %d atoms" % (self.n_atoms, xyz.shape[1]))
            if self.with_unitcell and (box is None):
                raise ValueError("The file that you're saving to expects each frame "
                    "to contain unitcell information, but you did not supply it.")
            if (not self.with_unitcell) and (box is not None):
                raise ValueError("The file that you're saving to was created without "
                    "unitcell information.")

        if time is None:
            time = np.arange(0, n_frames, dtype=np.float32)
        if step is None:
            step = np.arange(0, n_frames, dtype=np.int32)
        if box is None:
            # make each box[i] be the all zeros, which indicates the lack of
            # a unitcell
            box = np.zeros((n_frames, 3, 3), dtype=np.float32)
        if lambd is None:
            lambd = np.zeros(n_frames, dtype=np.float32)

        self._write(xyz, time, step, box, lambd)

    def _write(self, np.ndarray[ndim=3, dtype=np.float32_t, mode='c'] xyz not None,
               np.ndarray[ndim=1, dtype=np.float32_t, mode='c'] time not None,
               np.ndarray[ndim=1, dtype=np.int32_t, mode='c'] step not None,
               np.ndarray[ndim=3, dtype=np.float32_t, mode='c'] box not None,
               np.ndarray[ndim=1, dtype=np.float32_t, mode='c'] lambd not None):

        cdef int n_frames = len(xyz)
        cdef int n_atoms = xyz.shape[1]
        cdef int status, i

        # all same length
        assert n_frames == len(box) == len(step) == len(time) == len(lambd)

        for i in range(n_frames):
            status = trrlib.write_trr(self.fh, n_atoms, step[i], time[i], lambd[i],
                <trrlib.matrix>&box[i, 0, 0], <trrlib.rvec*>&xyz[i, 0, 0], NULL, NULL)
            if status != _EXDROK:
                raise RuntimeError('TRR write error: %s' % status)

        self.frame_counter += n_frames
        return status

    def seek(self, int offset, int whence=0):
        """seek(offset, whence=0)

        Move to a new file position

        Parameters
        ----------
        offset : int
            A number of frames.
        whence : {0, 1, 2}
            0: offset from start of file, offset should be >=0.
            1: move relative to the current position, positive or negative
            2: move relative to the end of file, offset should be <= 0.
            Seeking beyond the end of a file is not supported
        """
        cdef int i, status, step
        cdef float time, prec, lambd
        cdef np.ndarray[dtype=np.float_t] box = np.empty(9, dtype=np.float)
        cdef np.ndarray[dtype=np.float_t] xyz = np.empty(self.n_atoms * 3, dtype=np.float)

        if str(self.mode) != 'r':
            raise NotImplementedError('seek() only available in mode="r" currently')
        if whence == 0 and offset >= 0:
            absolute = offset
        elif whence == 1:
            absolute = offset + self.frame_counter
        elif whence == 2 and offset <= 0:
            raise NotImplementedError('offsets from the end are not supported yet')
        else:
            raise IOError('Invalid argument')

        trrlib.xdrfile_close(self.fh)
        self.fh = trrlib.xdrfile_open(self.filename, self.mode)

        for i in range(absolute):
            status = trrlib.read_trr(self.fh, self.n_atoms, &step, &time,
                &lambd, <trrlib.matrix>&box[0], <trrlib.rvec*>&xyz[0], NULL, NULL)
            if status != _EXDROK:
                raise RuntimeError('TRR seek error: %s' % status)

        self.frame_counter = absolute

    def tell(self):
        """Current file position

        Returns
        -------
        offset : int
            The current frame in the file.
        """
        if str(self.mode) != 'r':
            raise NotImplementedError('tell() only available in mode="r" currently')
        return int(self.frame_counter)

    def __enter__(self):
        "Support the context manager protocol"
        return self

    def __exit__(self, *exc_info):
        "Support the context manager protocol"
        self.close()

    def __len__(self):
        "Number of frames in the file"
        if str(self.mode) != 'r':
            raise NotImplementedError('len() only available in mode="r" currently')
        if not self.is_open:
            raise ValueError('I/O operation on closed file')
        if self.n_frames == -1:
            trrlib.read_trr_nframes(self.filename, &self.n_frames)
        return int(self.n_frames)
_FormatRegistry.register_fileobject('.trr')(TRRTrajectoryFile)
