import contextlib
import logging
import os
from pathlib import Path
from typing import Any, List, Mapping, Optional, Union

import numpy as np

from bed_reader import get_num_threads, open_bed

from .bed_reader import (  # type: ignore
    encode1_f32,
    encode1_f64,
    encode1_i8,
    write_f32,
    write_f64,
    write_i8,
)


class create_bed:
    """Open a file to write values into PLINK .bed format.

    Values may be given in a SNP-by-SNP (or individual-by-individual) manner.
    For large datasets, `create_bed` requires less memory than :func:`to_bed`.

    Parameters
    ----------
    location: pathlib.Path or str, optional
        local .bed file to create.
    iid_count: int:
        The number of individuals (samples).
    sid_count: int:
        The number of SNPs (variants).
    properties: dict, optional
        A dictionary of property names and values to write to the .fam and .bim files.
        Any properties not mentioned will be filled in with default values.

        The possible property names are:

             "fid" (family id), "iid" (individual or sample id), "father" (father id),
             "mother" (mother id), "sex", "pheno" (phenotype), "chromosome", "sid"
             (SNP or variant id), "cm_position" (centimorgan position), "bp_position"
             (base-pair position), "allele_1", "allele_2".

         The values are lists or arrays. See example, below.
    count_A1: bool, optional
        True (default) to count the number of A1 alleles (the PLINK standard).
        False to count the number of A2 alleles.
    fam_location: pathlib.Path or str, optional
        Path to the file containing information about each individual (sample).
        Defaults to replacing the .bed file’s suffix with .fam.
    bim_location: pathlib.Path or str, optional
        Path to the file containing information about each SNP (variant).
        Defaults to replacing the .bed file’s suffix with .bim.
    major: str, optional
        Use "SNP" (default) to write the file is usual SNP-major mode. This makes reading
        the data SNP-by-SNP faster. Use "individual" to write the file in the uncommon
        individual-major mode.
    force_python_only
        If False (default), uses the faster Rust helper functions; otherwise it uses the slower
        pure Python code.
    num_threads: None or int, optional
        Not currently used.


    create_bed Errors
    -----------------

    Raises an error if you write the wrong number of vectors or if any vector has the wrong length.

    Also, all vector values must be 0, 1, 2, or missing. If floats, missing is ``np.nan``.
    If integers, missing is -127.

    Behind the scenes, `create_bed` first creates a temporary bed file. At the end,
    if there are no errors,
    it renames the temporary file to the final file name. This helps prevent creation
    of corrupted files.


    Examples
    --------
    In this example, all properties are given and we write
    the data out SNP-by-SNP. The data is floats.

    .. doctest::

        >>> import numpy as np
        >>> from bed_reader import create_bed, tmp_path
        >>>
        >>> output_file = tmp_path() / "small.bed"
        >>> properties = {
        ...    "fid": ["fid1", "fid1", "fid2"],
        ...    "iid": ["iid1", "iid2", "iid3"],
        ...    "father": ["iid23", "iid23", "iid22"],
        ...    "mother": ["iid34", "iid34", "iid33"],
        ...    "sex": [1, 2, 0],
        ...    "pheno": ["red", "red", "blue"],
        ...    "chromosome": ["1", "1", "5", "Y"],
        ...    "sid": ["sid1", "sid2", "sid3", "sid4"],
        ...    "cm_position": [100.4, 2000.5, 4000.7, 7000.9],
        ...    "bp_position": [1, 100, 1000, 1004],
        ...    "allele_1": ["A", "T", "A", "T"],
        ...    "allele_2": ["A", "C", "C", "G"],
        ... }
        >>> with create_bed(output_file, iid_count=3, sid_count=4, properties=properties) as bed_writer:
        ...     bed_writer.write([1.0, 2.0, 0.0])
        ...     bed_writer.write([0.0, 0.0, 1.0])
        ...     bed_writer.write([np.nan, np.nan, 2.0])
        ...     bed_writer.write([0.0, 2.0, 0.0])


    In this next example, no properties are given, so default values are assigned.
    Also, we write out ints. Finally, we write the same data out as above,
    but individual-by-individual.
    If we then read the new file and list the chromosome property,
    it is an array of '0's, the default chromosome value.

    .. doctest::

        >>> output_file2 = tmp_path() / "small2.bed"
        >>> with create_bed(output_file2, iid_count=3, sid_count=4, major="individual") as bed_writer: # noqa: E501
        ...     bed_writer.write([1, 0, -127, 0])
        ...     bed_writer.write([2, 0, -127, 2])
        ...     bed_writer.write([0, 1, 2, 0])
        >>>
        >>> from bed_reader import open_bed
        >>> with open_bed(output_file2) as bed2:
        ...     print(bed2.chromosome)
        ['0' '0' '0' '0']

    """

    def __init__(
        self,
        location: Union[str, Path],
        iid_count: int,
        sid_count: int,
        properties: Mapping[str, List[Any]] = {},
        count_A1: bool = True,
        fam_location: Optional[Union[str, Path]] = None,
        bim_location: Optional[Union[str, Path]] = None,
        major: str = "SNP",
        force_python_only: bool = False,
        num_threads=None,
    ) -> None:
        self.location = Path(location)
        self.iid_count = iid_count
        self.sid_count = sid_count
        self.count_A1 = count_A1
        self.force_python_only = force_python_only
        self.num_threads = num_threads or os.cpu_count()

        if major == "SNP":
            self.major_count = sid_count
            self.minor_count = iid_count
        elif major == "individual":
            self.major_count = iid_count
            self.minor_count = sid_count
        else:
            msg = f"major must be 'SNP' or 'individual', not '{major}'"
            raise ValueError(msg)
        self.major = major
        self.minor_count_div4 = (self.minor_count - 1) // 4 + 1
        self.buffer = np.zeros(self.minor_count_div4, dtype=np.uint8)

        if not count_A1:
            self.zero_code = 0b00
            self.two_code = 0b11
        else:
            self.zero_code = 0b11
            self.two_code = 0b00

        fam_location = (
            Path(fam_location)
            if fam_location is not None
            else self._replace_extension(self.location, "fam")
        )
        bim_location = (
            Path(bim_location)
            if bim_location is not None
            else self._replace_extension(self.location, "bim")
        )

        properties, _ = open_bed._fix_up_properties(
            properties,
            iid_count,
            sid_count,
            use_fill_sequence=True,
        )

        open_bed._write_fam_or_bim(self.location, properties, "fam", fam_location)
        open_bed._write_fam_or_bim(self.location, properties, "bim", bim_location)

        self.temp_filepath = self.location.with_suffix(".bed_temp")
        self.file_pointer = open(self.temp_filepath, "wb")
        # see http://zzz.bwh.harvard.edu/plink/binary.shtml
        self.file_pointer.write(bytes(bytearray([0b01101100])))  # magic numbers
        self.file_pointer.write(bytes(bytearray([0b00011011])))  # magic numbers
        if self.major == "SNP":
            self.file_pointer.write(bytes(bytearray([0b00000001])))  # snp major
        else:
            assert self.major == "individual"  # real assert
            self.file_pointer.write(bytes(bytearray([0b00000000])))
        self.write_count = 0

        if os.path.exists(self.location):
            os.unlink(self.location)

    def __enter__(self):
        return self

    def __exit__(self, exc_type, exc_value, traceback):
        self.close()

    def close(self) -> None:
        """Close the bed_writer, writing the file to disk. If you use
        :class:`create_bed` with the `with` statement,
        you don't need to use this.

        See :class:`create_bed` for more information.
        """
        if self.file_pointer is not None:
            try:
                self.file_pointer.close()
                self.file_pointer = None
                if self.write_count != self.major_count:
                    msg = (
                        f"Attempt to write fewer vectors ({self.write_count}) "
                        f"than expected ({self.major_count})"
                    )
                    raise ValueError(
                        msg,
                    )
                os.rename(self.temp_filepath, self.location)
            except Exception:
                self._clean_up_error()
                raise
        else:
            self._clean_up_error()

    def _clean_up_error(self) -> None:
        with contextlib.suppress(Exception):
            os.unlink(self.temp_filepath)

    @staticmethod
    def _replace_extension(location, extension):
        if open_bed._is_url(location):
            return location.parent / (location.stem + "." + extension)
        return None

    def write(self, vector) -> None:
        """Write a vector of values to the bed_writer.

        See :class:`create_bed` for more information.
        """
        if self.file_pointer is None:
            msg = "Attempt to write after file was closed for writing."
            raise RuntimeError(msg)

        try:
            self.write_count += 1
            if self.write_count > self.major_count:
                msg = (
                    f"Attempt to write more vectors ({self.write_count}) "
                    f"than expected ({self.major_count})"
                )
                raise ValueError(
                    msg,
                )

            vector = _fix_up_vector(vector)
            if len(vector) != self.minor_count:
                msg = f"Expected vector to {self.minor_count} values, got {len(vector)} instead"
                raise ValueError(
                    msg,
                )

            self._internal_write(vector)

        except Exception:
            self.file_pointer.close()
            self.file_pointer = None  # Prevent further writes
            raise  # Re-raise the exception to handle it externally

    def _internal_write(self, vector) -> None:
        if not self.force_python_only:
            if vector.dtype == np.int8:
                encode1_i8(self.count_A1, vector, self.buffer, self.num_threads)
            elif vector.dtype == np.float32:
                encode1_f32(self.count_A1, vector, self.buffer, self.num_threads)
            elif vector.dtype == np.float64:
                encode1_f64(self.count_A1, vector, self.buffer, self.num_threads)
            else:
                msg = (
                    f"dtype '{vector.dtype}' not known, only 'int8', 'float32', "
                    f"and 'float64' are allowed."
                )
                raise ValueError(
                    msg,
                )
            self.file_pointer.write(self.buffer)
        else:
            for minor_by_four in range(0, self.minor_count, 4):
                vals_for_this_byte = vector[minor_by_four : minor_by_four + 4]
                byte = 0b00000000
                for val_index in range(len(vals_for_this_byte)):
                    val_for_byte = vals_for_this_byte[val_index]
                    if val_for_byte == 0:
                        code = self.zero_code
                    elif val_for_byte == 1:
                        code = 0b10  # backwards on purpose
                    elif val_for_byte == 2:
                        code = self.two_code
                    elif (vector.dtype == np.int8 and val_for_byte == -127) or np.isnan(
                        val_for_byte,
                    ):
                        code = 0b01  # backwards on purpose
                    else:
                        raise ValueError(
                            "Attempt to write illegal value to .bed file. "
                            + "Only 0,1,2,missing allowed.",
                        )
                    byte |= code << (val_index * 2)
                # This is writing one byte at a time
                self.file_pointer.write(bytes(bytearray([byte])))


def _fix_up_vector(input):
    if not isinstance(input, np.ndarray):
        return _fix_up_vector(np.array(input))

    if np.issubdtype(input.dtype, np.integer) and input.dtype != np.int8:
        return _fix_up_vector(np.array(input, dtype=np.int8))
    if np.issubdtype(input.dtype, np.floating) and input.dtype not in (
        np.float32,
        np.float64,
    ):
        return _fix_up_vector(np.array(input, dtype=np.float32))

    if len(input.shape) != 1:
        msg = "vector should be one dimensional"
        raise ValueError(msg)

    return input


def to_bed(
    filepath: Union[str, Path],
    val: np.ndarray,
    properties: Mapping[str, List[Any]] = {},
    count_A1: bool = True,
    fam_filepath: Optional[Union[str, Path]] = None,
    bim_filepath: Optional[Union[str, Path]] = None,
    major: str = "SNP",
    force_python_only: bool = False,
    num_threads=None,
) -> None:
    """Write values to a file in PLINK .bed format.

    If your data is too large to fit in memory, use :class:`create_bed` instead.

    Parameters
    ----------
    filepath:
        .bed file to write to.
    val: array-like:
        A two-dimension array (or array-like object) of values. The values should
        be (or be convertible to) all floats or all integers.
        The values should be 0, 1, 2, or missing.
        If floats, missing is ``np.nan``. If integers, missing is -127.
    properties: dict, optional
        A dictionary of property names and values to write to the .fam and .bim files.
        Any properties not mentioned will be filled in with default values.

        The possible property names are:

             "fid" (family id), "iid" (individual or sample id), "father" (father id),
             "mother" (mother id), "sex", "pheno" (phenotype), "chromosome", "sid"
             (SNP or variant id), "cm_position" (centimorgan position), "bp_position"
             (base-pair position), "allele_1", "allele_2".

         The values are lists or arrays. See example, below.
    count_A1: bool, optional
        True (default) to count the number of A1 alleles (the PLINK standard).
        False to count the number of A2 alleles.
    fam_filepath: pathlib.Path or str, optional
        Path to the file containing information about each individual (sample).
        Defaults to replacing the .bed file’s suffix with .fam.
    bim_filepath: pathlib.Path or str, optional
        Path to the file containing information about each SNP (variant).
        Defaults to replacing the .bed file’s suffix with .bim.
    major: str, optional
        Use "SNP" (default) to write the file is usual SNP-major mode. This makes reading
        the data SNP-by-SNP faster. Use "individual" to write the file in the uncommon
        individual-major mode.
    force_python_only
        If False (default), uses the faster Rust helper functions; otherwise it uses the slower
        pure Python code.
    num_threads: None or int, optional
        The number of threads with which to write data.
        Defaults to all available processors.
        Can also be set with these environment variables (listed in priority order):
        'PST_NUM_THREADS', 'NUM_THREADS', 'MKL_NUM_THREADS'.


    Examples
    --------
    In this example, all properties are given.

    .. doctest::

        >>> import numpy as np
        >>> from bed_reader import to_bed, tmp_path
        >>>
        >>> output_file = tmp_path() / "small.bed"
        >>> val = [[1.0, 0.0, np.nan, 0.0],
        ...        [2.0, 0.0, np.nan, 2.0],
        ...        [0.0, 1.0, 2.0, 0.0]]
        >>> properties = {
        ...    "fid": ["fid1", "fid1", "fid2"],
        ...    "iid": ["iid1", "iid2", "iid3"],
        ...    "father": ["iid23", "iid23", "iid22"],
        ...    "mother": ["iid34", "iid34", "iid33"],
        ...    "sex": [1, 2, 0],
        ...    "pheno": ["red", "red", "blue"],
        ...    "chromosome": ["1", "1", "5", "Y"],
        ...    "sid": ["sid1", "sid2", "sid3", "sid4"],
        ...    "cm_position": [100.4, 2000.5, 4000.7, 7000.9],
        ...    "bp_position": [1, 100, 1000, 1004],
        ...    "allele_1": ["A", "T", "A", "T"],
        ...    "allele_2": ["A", "C", "C", "G"],
        ... }
        >>> to_bed(output_file, val, properties=properties)

    Here, no properties are given, so default values are assigned.
    If we then read the new file and list the chromosome property,
    it is an array of '0's, the default chromosome value.

    .. doctest::

        >>> output_file2 = tmp_path() / "small2.bed"
        >>> val = [[1, 0, -127, 0], [2, 0, -127, 2], [0, 1, 2, 0]]
        >>> to_bed(output_file2, val)
        >>>
        >>> from bed_reader import open_bed
        >>> with open_bed(output_file2) as bed2:
        ...     print(bed2.chromosome)
        ['0' '0' '0' '0']

    """
    filepath = Path(filepath)

    val = _fix_up_val(val)
    iid_count = val.shape[0]
    sid_count = val.shape[1]

    if major == "SNP":
        major_count = sid_count
        minor_count = iid_count
    elif major == "individual":
        major_count = iid_count
        minor_count = sid_count
    else:
        msg = f"major must be 'SNP' or 'individual', not '{major}'"
        raise ValueError(msg)

    properties, _ = open_bed._fix_up_properties(
        properties, iid_count=iid_count, sid_count=sid_count, use_fill_sequence=True,
    )

    open_bed._write_fam_or_bim(filepath, properties, "fam", fam_filepath)
    open_bed._write_fam_or_bim(filepath, properties, "bim", bim_filepath)

    if not force_python_only:
        if not val.flags["C_CONTIGUOUS"] and not val.flags["F_CONTIGUOUS"]:
            msg = "val must be contiguous."
            raise ValueError(msg)

        num_threads = get_num_threads(num_threads)

        if major == "individual":
            val = val.T

        try:
            if val.dtype == np.float64:
                write_f64(
                    str(filepath),
                    is_a1_counted=count_A1,
                    val=val,
                    num_threads=num_threads,
                )
            elif val.dtype == np.float32:
                write_f32(
                    str(filepath),
                    is_a1_counted=count_A1,
                    val=val,
                    num_threads=num_threads,
                )
            elif val.dtype == np.int8:
                write_i8(
                    str(filepath),
                    is_a1_counted=count_A1,
                    val=val,
                    num_threads=num_threads,
                )
            else:
                raise ValueError(
                    f"dtype '{val.dtype}' not known, only "
                    + "'int8', 'float32', and 'float64' are allowed.",
                )

            if major == "individual":
                # change the 3rd byte in the file to 0b00000000
                with open(filepath, "r+b") as bed_filepointer:
                    bed_filepointer.seek(2)
                    bed_filepointer.write(bytes(bytearray([0b00000000])))

        except SystemError as system_error:
            with contextlib.suppress(Exception):
                os.unlink(filepath)
            raise system_error.__cause__
    else:
        if not count_A1:
            zero_code = 0b00
            two_code = 0b11
        else:
            zero_code = 0b11
            two_code = 0b00

        with open(filepath, "wb") as bed_filepointer:
            # see http://zzz.bwh.harvard.edu/plink/binary.shtml
            bed_filepointer.write(bytes(bytearray([0b01101100])))  # magic numbers
            bed_filepointer.write(bytes(bytearray([0b00011011])))  # magic numbers

            if major == "SNP":
                bed_filepointer.write(bytes(bytearray([0b00000001])))  # snp major
            else:
                assert major == "individual"
                bed_filepointer.write(
                    bytes(bytearray([0b00000000])),
                )  # individual major

            for major_index in range(major_count):
                if major_index % 1 == 0:
                    logging.info(
                        f"Writing {major} # {major_index} to file '{filepath}'",
                    )

                if major == "SNP":
                    vector = val[:, major_index]
                else:
                    assert major == "individual"
                    vector = val[major_index, :]

                for minor_by_four in range(0, minor_count, 4):
                    vals_for_this_byte = vector[minor_by_four : minor_by_four + 4]
                    byte = 0b00000000
                    for val_index in range(len(vals_for_this_byte)):
                        val_for_byte = vals_for_this_byte[val_index]
                        if val_for_byte == 0:
                            code = zero_code
                        elif val_for_byte == 1:
                            code = 0b10  # backwards on purpose
                        elif val_for_byte == 2:
                            code = two_code
                        elif (
                            val.dtype == np.int8 and val_for_byte == -127
                        ) or np.isnan(val_for_byte):
                            code = 0b01  # backwards on purpose
                        else:
                            raise ValueError(
                                "Attempt to write illegal value to .bed file. "
                                + "Only 0,1,2,missing allowed.",
                            )
                        byte |= code << (val_index * 2)
                    bed_filepointer.write(bytes(bytearray([byte])))
    logging.info(f"Done writing {filepath}")


def _fix_up_val(input):
    if not isinstance(input, np.ndarray):
        return _fix_up_val(np.array(input))

    if np.issubdtype(input.dtype, np.integer) and input.dtype != np.int8:
        return _fix_up_val(np.array(input, dtype=np.int8))
    if np.issubdtype(input.dtype, np.floating) and input.dtype not in (
        np.float32,
        np.float64,
    ):
        return _fix_up_val(np.array(input, dtype=np.float32))

    if len(input.shape) != 2:
        msg = "val should be two dimensional"
        raise ValueError(msg)

    return input


# if __name__ == "__main__":
#    logging.basicConfig(level=logging.INFO)

#    import pytest

#    pytest.main(["--doctest-modules", __file__])